diff --git a/.github/workflows/_test_release.yml b/.github/workflows/_test_release.yml index ea0c352aa..2a2324c6f 100644 --- a/.github/workflows/_test_release.yml +++ b/.github/workflows/_test_release.yml @@ -11,6 +11,9 @@ on: env: PYTHON_VERSION: "3.10" +permissions: + contents: read + jobs: build: if: github.ref == 'refs/heads/main' diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 9ee07bc32..050daa704 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -24,7 +24,6 @@ jobs: runs-on: ubuntu-latest outputs: python: ${{ steps.filter.outputs.python }} - sdk-js: ${{ steps.filter.outputs.sdk-js }} deps: ${{ steps.filter.outputs.deps }} steps: - uses: actions/checkout@v4 @@ -40,8 +39,6 @@ jobs: - 'libs/checkpoint-sqlite/**' - 'libs/checkpoint-postgres/**' - 'libs/prebuilt/**' - sdk-js: - - 'libs/sdk-js/**' deps: - '**/pyproject.toml' - '**/uv.lock' @@ -152,68 +149,16 @@ jobs: uses: ./.github/workflows/_integration_test.yml secrets: inherit - lint-js: - needs: changes - if: needs.changes.outputs.sdk-js == 'true' - runs-on: ubuntu-latest - strategy: - matrix: - working-directory: - - "libs/sdk-js" - defaults: - run: - working-directory: ${{ matrix.working-directory }} - steps: - - uses: actions/checkout@v4 - - name: Setup Node.js (LTS) - uses: actions/setup-node@v4 - with: - node-version: "20" - cache: "yarn" - cache-dependency-path: ${{ matrix.working-directory }}/yarn.lock - - name: Install dependencies - run: yarn install - - name: Run lint - run: yarn lint - - name: Build - run: yarn build - - test-js: - needs: changes - if: needs.changes.outputs.sdk-js == 'true' - runs-on: ubuntu-latest - strategy: - matrix: - working-directory: - - "libs/sdk-js" - defaults: - run: - working-directory: ${{ matrix.working-directory }} - steps: - - uses: actions/checkout@v4 - - name: Setup Node.js (LTS) - uses: actions/setup-node@v4 - with: - node-version: "20" - cache: "yarn" - cache-dependency-path: ${{ matrix.working-directory }}/yarn.lock - - name: Install dependencies - run: yarn install - - name: Run tests - run: yarn test - ci_success: name: "CI Success" needs: [ lint, - lint-js, test, test-langgraph, check-sdk-methods, check-schema, integration-test, - test-js, ] if: | always() diff --git a/.github/workflows/release_js.yml b/.github/workflows/release_js.yml deleted file mode 100644 index bce535330..000000000 --- a/.github/workflows/release_js.yml +++ /dev/null @@ -1,41 +0,0 @@ -name: JS Release - -on: - workflow_dispatch: - -permissions: - contents: read - -jobs: - publish: - # Disallow publishing from branches that aren't `main`. - if: github.ref == 'refs/heads/main' - runs-on: ubuntu-latest - - strategy: - matrix: - working-directory: - - "libs/sdk-js" - - defaults: - run: - working-directory: ${{ matrix.working-directory }} - - steps: - - uses: actions/checkout@v4 - # JS Build - - name: Use Node.js - uses: actions/setup-node@v4 - with: - node-version: "20" - cache: "yarn" - cache-dependency-path: ${{ matrix.working-directory }}/yarn.lock - - - name: Install dependencies - run: yarn install - - name: Build - run: yarn build - - name: Publish package to NPM - run: | - echo "//registry.npmjs.org/:_authToken=${{ secrets.NPM_TOKEN }}" > .npmrc - npm publish \ No newline at end of file diff --git a/docs/.gitignore b/docs/.gitignore index f4d716881..540583df2 100644 --- a/docs/.gitignore +++ b/docs/.gitignore @@ -1,4 +1,3 @@ site/ -docs/cloud/reference/sdk/js_ts_sdk_ref.md .vercel diff --git a/docs/Makefile b/docs/Makefile index 5696fbc6f..95d256241 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -1,10 +1,4 @@ -.PHONY: lint-docs format-docs build-docs serve-docs serve-clean-docs clean-docs codespell build-typedoc llms-text build-prebuilt tests - -build-typedoc: - cd ../libs/sdk-js && yarn install --include-dev && yarn typedoc - cd ../libs/sdk-js && yarn --silent concat-md --decrease-title-levels --ignore=js_ts_sdk_ref.md --start-title-level-at 2 docs > ../../docs/docs/cloud/reference/sdk/js_ts_sdk_ref.md 2>/dev/null - # Add links to the monorepo - sed -e '1,10s|@langchain/langgraph-sdk|[@langchain/langgraph-sdk](https://github.com/langchain-ai/langgraph/tree/main/libs/sdk-js)|g' docs/cloud/reference/sdk/js_ts_sdk_ref.md > temp_file && mv temp_file docs/cloud/reference/sdk/js_ts_sdk_ref.md +.PHONY: lint-docs format-docs build-docs serve-docs serve-clean-docs clean-docs codespell llms-text build-prebuilt tests build-prebuilt: # Use to create an update to date prebuilt page. @@ -21,7 +15,7 @@ build-prebuilt: fi uv run python -m _scripts.third_party_page.create_third_party_page stats.yml docs/agents/prebuilt.md --language python -build-docs: build-typedoc build-prebuilt +build-docs: build-prebuilt uv run python -m mkdocs build --clean -f mkdocs.yml --strict llms-text: @@ -45,7 +39,7 @@ vercel-build-docs: install-vercel-deps serve-clean-docs: clean-docs uv run python -m mkdocs serve -c -f mkdocs.yml --strict -w ../libs/langgraph -serve-docs: build-typedoc +serve-docs: uv run python -m mkdocs serve -f mkdocs.yml -w ../libs/langgraph -w ../libs/checkpoint -w ../libs/sdk-py --dirty clean-docs: diff --git a/docs/_scripts/notebook_hooks.py b/docs/_scripts/notebook_hooks.py index 34dceb064..7b7f049eb 100644 --- a/docs/_scripts/notebook_hooks.py +++ b/docs/_scripts/notebook_hooks.py @@ -34,20 +34,20 @@ REDIRECT_MAP = { "how-tos/streaming-from-final-node.ipynb": "how-tos/streaming-specific-nodes.ipynb", "how-tos/streaming-events-from-within-tools-without-langchain.ipynb": "how-tos/streaming-events-from-within-tools.ipynb#example-without-langchain", # graph-api - "how-tos/state-reducers.ipynb": "how-tos/graph-api#define-and-update-state", - "how-tos/sequence.ipynb": "how-tos/graph-api#create-a-sequence-of-steps", - "how-tos/branching.ipynb": "how-tos/graph-api#create-branches", - "how-tos/recursion-limit.ipynb": "how-tos/graph-api#create-and-control-loops", - "how-tos/visualization.ipynb": "how-tos/graph-api#visualize-your-graph", - "how-tos/input_output_schema.ipynb": "how-tos/graph-api#define-input-and-output-schemas", - "how-tos/pass_private_state.ipynb": "how-tos/graph-api#pass-private-state-between-nodes", - "how-tos/state-model.ipynb": "how-tos/graph-api#use-pydantic-models-for-graph-state", - "how-tos/map-reduce.ipynb": "how-tos/graph-api/#map-reduce-and-the-send-api", - "how-tos/command.ipynb": "how-tos/graph-api/#combine-control-flow-and-state-updates-with-command", - "how-tos/configuration.ipynb": "how-tos/graph-api/#add-runtime-configuration", - "how-tos/node-retries.ipynb": "how-tos/graph-api/#add-retry-policies", - "how-tos/return-when-recursion-limit-hits.ipynb": "how-tos/graph-api/#impose-a-recursion-limit", - "how-tos/async.ipynb": "how-tos/graph-api/#async", + "how-tos/state-reducers.ipynb": "how-tos/graph-api.md#define-and-update-state", + "how-tos/sequence.ipynb": "how-tos/graph-api.md#create-a-sequence-of-steps", + "how-tos/branching.ipynb": "how-tos/graph-api.md#create-branches", + "how-tos/recursion-limit.ipynb": "how-tos/graph-api.md#create-and-control-loops", + "how-tos/visualization.ipynb": "how-tos/graph-api.md#visualize-your-graph", + "how-tos/input_output_schema.ipynb": "how-tos/graph-api.md#define-input-and-output-schemas", + "how-tos/pass_private_state.ipynb": "how-tos/graph-api.md#pass-private-state-between-nodes", + "how-tos/state-model.ipynb": "how-tos/graph-api.md#use-pydantic-models-for-graph-state", + "how-tos/map-reduce.ipynb": "how-tos/graph-api.md#map-reduce-and-the-send-api", + "how-tos/command.ipynb": "how-tos/graph-api.md#combine-control-flow-and-state-updates-with-command", + "how-tos/configuration.ipynb": "how-tos/graph-api.md#add-runtime-configuration", + "how-tos/node-retries.ipynb": "how-tos/graph-api.md#add-retry-policies", + "how-tos/return-when-recursion-limit-hits.ipynb": "how-tos/graph-api.md#impose-a-recursion-limit", + "how-tos/async.ipynb": "how-tos/graph-api.md#async", # memory how-tos "how-tos/memory/manage-conversation-history.ipynb": "how-tos/memory/add-memory.md", "how-tos/memory/delete-messages.ipynb": "how-tos/memory/add-memory.md#delete-messages", @@ -55,8 +55,8 @@ REDIRECT_MAP = { "how-tos/memory.ipynb": "how-tos/memory/add-memory.md", "agents/memory.ipynb": "how-tos/memory/add-memory.md", # subgraph how-tos - "how-tos/subgraph-transform-state.ipynb": "how-tos/subgraph.ipynb#different-state-schemas", - "how-tos/subgraphs-manage-state.ipynb": "how-tos/subgraph.ipynb#add-persistence", + "how-tos/subgraph-transform-state.ipynb": "how-tos/subgraph.md#different-state-schemas", + "how-tos/subgraphs-manage-state.ipynb": "how-tos/subgraph.md#add-persistence", # persistence how-tos "how-tos/persistence_postgres.ipynb": "how-tos/memory/add-memory.md#use-in-production", "how-tos/persistence_mongodb.ipynb": "how-tos/memory/add-memory.md#use-in-production", @@ -73,9 +73,9 @@ REDIRECT_MAP = { "how-tos/pass-run-time-values-to-tools.ipynb": "how-tos/tool-calling.ipynb#read-state", "how-tos/update-state-from-tools.ipynb": "how-tos/tool-calling.ipynb#update-state", # multi-agent how-tos - "how-tos/agent-handoffs.ipynb": "how-tos/multi_agent.ipynb#handoffs", - "how-tos/multi-agent-network.ipynb": "how-tos/multi_agent.ipynb#use-in-a-multi-agent-system", - "how-tos/multi-agent-multi-turn-convo.ipynb": "how-tos/multi_agent.ipynb#multi-turn-conversation", + "how-tos/agent-handoffs.ipynb": "how-tos/multi_agent.md#handoffs", + "how-tos/multi-agent-network.ipynb": "how-tos/multi_agent.md#use-in-a-multi-agent-system", + "how-tos/multi-agent-multi-turn-convo.ipynb": "how-tos/multi_agent.md#multi-turn-conversation", # cloud redirects "cloud/index.md": "index.md", "cloud/how-tos/index.md": "concepts/langgraph_platform", diff --git a/docs/docs/agents/mcp.md b/docs/docs/agents/mcp.md index 9b654ffa5..f4bb1276d 100644 --- a/docs/docs/agents/mcp.md +++ b/docs/docs/agents/mcp.md @@ -9,21 +9,12 @@ hide: # Use MCP -[Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) is an open protocol that standardizes how applications provide tools and context to language models. LangGraph agents can use tools defined on MCP servers through the `langchain-mcp-adapters` library. - -![MCP](./assets/mcp.png) - -Install the `langchain-mcp-adapters` library to use MCP tools in LangGraph: - -```bash -pip install langchain-mcp-adapters -``` +The Model Context Protocol (MCP) is an open protocol that standardizes how applications provide tools and context to language models. LangGraph agents can use tools defined on MCP servers through the `langchain-mcp-adapters` library. ## Use MCP tools The `langchain-mcp-adapters` package enables agents to use tools defined across one or more MCP servers. - === "In an agent" ```python title="Agent using tools defined on MCP servers" diff --git a/docs/docs/agents/overview.md b/docs/docs/agents/overview.md index 35426cc1d..d61b9d6ed 100644 --- a/docs/docs/agents/overview.md +++ b/docs/docs/agents/overview.md @@ -30,7 +30,7 @@ LangGraph includes several capabilities essential for building robust, productio - [**Memory integration**](../how-tos/memory/add-memory.md): Native support for *short-term* (session-based) and *long-term* (persistent across sessions) memory, enabling stateful behaviors in chatbots and assistants. - [**Human-in-the-loop control**](../concepts/human_in_the_loop.md): Execution can pause *indefinitely* to await human feedback—unlike websocket-based solutions limited to real-time interaction. This enables asynchronous approval, correction, or intervention at any point in the workflow. - [**Streaming support**](../how-tos/streaming.md): Real-time streaming of agent state, model tokens, tool outputs, or combined streams. -- [**Deployment tooling**](./deployment.md): Includes infrastructure-free deployment tools. [**LangGraph Platform**](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) supports testing, debugging, and deployment. +- [**Deployment tooling**](../tutorials/langgraph-platform/local-server.md): Includes infrastructure-free deployment tools. [**LangGraph Platform**](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) supports testing, debugging, and deployment. - **[Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/)**: A visual IDE for inspecting and debugging workflows. - Supports multiple [**deployment options**](https://langchain-ai.github.io/langgraph/concepts/deployment_options.md) for production. diff --git a/docs/docs/agents/ui.md b/docs/docs/agents/ui.md index 64b321f60..41735d652 100644 --- a/docs/docs/agents/ui.md +++ b/docs/docs/agents/ui.md @@ -13,7 +13,7 @@ You can use a prebuilt chat UI for interacting with any LangGraph agent through ## Run agent in UI -First, set up LangGraph API server [locally](./deployment.md#launch-langgraph-server-locally) or deploy your agent on [LangGraph Platform](https://langchain-ai.github.io/langgraph/cloud/quick_start/). +First, set up LangGraph API server [locally](../tutorials/langgraph-platform/local-server.md) or deploy your agent on [LangGraph Platform](https://langchain-ai.github.io/langgraph/cloud/quick_start/). Then, navigate to [Agent Chat UI](https://agentchat.vercel.app), or clone the repository and [run the dev server locally](https://github.com/langchain-ai/agent-chat-ui?tab=readme-ov-file#setup): @@ -25,7 +25,7 @@ Then, navigate to [Agent Chat UI](https://agentchat.vercel.app), or clone the re ## Add human-in-the-loop -Agent Chat UI has full support for [human-in-the-loop](../concepts/human_in_the_loop.md) workflows. To try it out, replace the agent code in `src/agent/graph.py` (from the [deployment](./deployment.md) guide) with this [agent implementation](../how-tos/human_in_the_loop/add-human-in-the-loop.md#add-interrupts-to-any-tool): +Agent Chat UI has full support for [human-in-the-loop](../concepts/human_in_the_loop.md) workflows. To try it out, replace the agent code in `src/agent/graph.py` (from the [deployment](../tutorials/langgraph-platform/local-server.md) guide) with this [agent implementation](../how-tos/human_in_the_loop/add-human-in-the-loop.md#add-interrupts-to-any-tool): diff --git a/docs/docs/cloud/reference/api/api_ref.md b/docs/docs/cloud/reference/api/api_ref.md index 13b30acf2..c2d6a10a7 100644 --- a/docs/docs/cloud/reference/api/api_ref.md +++ b/docs/docs/cloud/reference/api/api_ref.md @@ -1,12 +1,12 @@ -# API Reference +# LangGraph Server API Reference -The LangGraph Platform API reference is available with each deployment at the `/docs` URL path (e.g. `http://localhost:8124/docs`). +The LangGraph Server API reference is available within each deployment at the `/docs` endpoint (e.g. `http://localhost:8124/docs`). Click here to view the API reference. ## Authentication -For deployments to LangGraph Platform, authentication is required. Pass the `X-Api-Key` header with each request to the LangGraph Platform API. The value of the header should be set to a valid LangSmith API key for the organization where the API is deployed. +For deployments to LangGraph Platform, authentication is required. Pass the `X-Api-Key` header with each request to the LangGraph Server. The value of the header should be set to a valid LangSmith API key for the organization where the LangGraph Server is deployed. Example `curl` command: ```shell @@ -18,5 +18,5 @@ curl --request POST \ "metadata": {}, "limit": 10, "offset": 0 -}' +}' ``` diff --git a/docs/docs/cloud/reference/api/api_ref_control_plane.md b/docs/docs/cloud/reference/api/api_ref_control_plane.md new file mode 100644 index 000000000..b6f3827ae --- /dev/null +++ b/docs/docs/cloud/reference/api/api_ref_control_plane.md @@ -0,0 +1,247 @@ +# LangGraph Control Plane API Reference + +The LangGraph Control Plane API is used to programmatically create and manage LangGraph Server deployments. For example, the APIs can be orchestrated to create custom CI/CD workflows. + +Click here to view the API reference. + +## Host + +LangGraph Control Plane hosts for Cloud SaaS data regions: + +| US | EU | +|----|----| +| `https://api.host.langchain.com` | `https://eu.api.host.langchain.com` | + +**Note**: Self-hosted deployments of LangGraph Platform will have a custom host for the LangGraph Control Plane. + +## Authentication + +To authenticate with the LangGraph Control Plane API, set the `X-Api-Key` header to a valid LangSmith API key. + +Example `curl` command: +```shell +curl --request GET \ + --url http://localhost:8124/v2/deployments \ + --header 'X-Api-Key: LANGSMITH_API_KEY' +``` + +## Versioning + +Each endpoint path is prefixed with a version (e.g. `v1`, `v2`). + +## Quick Start + +1. Call `POST /v2/deployments` to create a new Deployment. The response body contains the Deployment ID (`id`) and the ID of the latest (and first) revision (`latest_revision_id`). +1. Call `GET /v2/deployments/{deployment_id}` to retrieve the Deployment. Set `deployment_id` in the URL to the value of Deployment ID (`id`). +1. Poll for revision `status` until `status` is `DEPLOYED` by calling `GET /v2/deployments/{deployment_id}/revisions/{latest_revision_id}`. +1. Call `PATCH /v2/deployments/{deployment_id}` to update the deployment. + +## Example Code +Below is example Python code that demonstrates how to orchestrate the LangGraph Control Plane APIs to create a deployment, update the deployment, and delete the deployment. +```python +import os +import time + +import requests +from dotenv import load_dotenv + + +load_dotenv() + +# required environment variables +CONTROL_PLANE_HOST = os.getenv("CONTROL_PLANE_HOST") +LANGSMITH_API_KEY = os.getenv("LANGSMITH_API_KEY") +INTEGRATION_ID = os.getenv("INTEGRATION_ID") +MAX_WAIT_TIME = 1800 # 30 mins + + +def get_headers() -> dict: + """Return common headers for requests to LangGraph Control Plane API.""" + return { + "X-Api-Key": LANGSMITH_API_KEY, + } + + +def create_deployment() -> str: + """Create deployment. Return deployment ID.""" + headers = get_headers() + headers["Content-Type"] = "application/json" + + deployment_name = "my_deployment" + + request_body = { + "name": deployment_name, + "source": "github", + "source_config": { + "integration_id": INTEGRATION_ID, + "repo_url": "https://github.com/langchain-ai/langgraph-example", + "deployment_type": "dev", + "build_on_push": False, + "custom_url": None, + "resource_spec": None, + }, + "source_revision_config": { + "repo_ref": "main", + "langgraph_config_path": "langgraph.json", + "image_uri": None, + }, + "secrets": [ + { + "name": "OPENAI_API_KEY", + "value": "test_openai_api_key", + }, + { + "name": "ANTHROPIC_API_KEY", + "value": "test_anthropic_api_key", + }, + { + "name": "TAVILY_API_KEY", + "value": "test_tavily_api_key", + }, + ], + } + + response = requests.post( + url=f"{CONTROL_PLANE_HOST}/v2/deployments", + headers=headers, + json=request_body, + ) + + if response.status_code != 201: + raise Exception(f"Failed to create deployment: {response.text}") + + deployment_id = response.json()["id"] + print(f"Created deployment {deployment_name} ({deployment_id})") + return deployment_id + + +def get_deployment(deployment_id: str) -> dict: + """Get deployment.""" + response = requests.get( + url=f"{CONTROL_PLANE_HOST}/v2/deployments/{deployment_id}", + headers=get_headers(), + ) + + if response.status_code != 200: + raise Exception(f"Failed to get deployment ID {deployment_id}: {response.text}") + + return response.json() + + +def list_revisions(deployment_id: str) -> list[dict]: + """List revisions. + + Return list is sorted by created_at in descending order (latest first). + """ + response = requests.get( + url=f"{CONTROL_PLANE_HOST}/v2/deployments/{deployment_id}/revisions", + headers=get_headers(), + ) + + if response.status_code != 200: + raise Exception( + f"Failed to list revisions for deployment ID {deployment_id}: {response.text}" + ) + + return response.json() + + +def get_revision( + deployment_id: str, + revision_id: str, +) -> dict: + """Get revision.""" + response = requests.get( + url=f"{CONTROL_PLANE_HOST}/v2/deployments/{deployment_id}/revisions/{revision_id}", + headers=get_headers(), + ) + + if response.status_code != 200: + raise Exception(f"Failed to get revision ID {revision_id}: {response.text}") + + return response.json() + + +def patch_deployment(deployment_id: str) -> None: + """Patch deployment.""" + headers = get_headers() + headers["Content-Type"] = "application/json" + + response = requests.patch( + url=f"{CONTROL_PLANE_HOST}/v2/deployments/{deployment_id}", + headers=headers, + json={ + "source_config": { + "build_on_push": True, + }, + "source_revision_config": { + "repo_ref": "main", + "langgraph_config_path": "langgraph.json", + }, + }, + ) + + if response.status_code != 200: + raise Exception(f"Failed to patch deployment: {response.text}") + + print(f"Patched deployment ID {deployment_id}") + + +def wait_for_deployment(deployment_id: str, revision_id: str) -> None: + """Wait for revision status to be DEPLOYED.""" + start_time = time.time() + revision, status = None, None + while time.time() - start_time < MAX_WAIT_TIME: + revision = get_revision(deployment_id, revision_id) + status = revision["status"] + if status == "DEPLOYED": + break + elif "FAILED" in status: + raise Exception(f"Revision ID {revision_id} failed: {revision}") + + print(f"Waiting for revision ID {revision_id} to be DEPLOYED...") + time.sleep(60) + + if status != "DEPLOYED": + raise Exception( + f"Timeout waiting for revision ID {revision_id} to be DEPLOYED: {revision}" + ) + + +def delete_deployment(deployment_id: str) -> None: + """Delete deployment.""" + response = requests.delete( + url=f"{CONTROL_PLANE_HOST}/v2/deployments/{deployment_id}", + headers=get_headers(), + ) + + if response.status_code != 204: + raise Exception( + f"Failed to delete deployment ID {deployment_id}: {response.text}" + ) + + print(f"Deployment ID {deployment_id} deleted") + + +if __name__ == "__main__": + # create deployment and get the latest revision + deployment_id = create_deployment() + revisions = list_revisions(deployment_id) + latest_revision = revisions["resources"][0] + latest_revision_id = latest_revision["id"] + + # wait for latest revision to be DEPLOYED + wait_for_deployment(deployment_id, latest_revision_id) + + # patch the deployment and get the latest revision + patch_deployment(deployment_id) + revisions = list_revisions(deployment_id) + latest_revision = revisions["resources"][0] + latest_revision_id = latest_revision["id"] + + # wait for latest revision to be DEPLOYED + wait_for_deployment(deployment_id, latest_revision_id) + + # delete the deployment + delete_deployment(deployment_id) +``` \ No newline at end of file diff --git a/docs/docs/cloud/reference/cli.md b/docs/docs/cloud/reference/cli.md index 84e5f3f66..b43be5485 100644 --- a/docs/docs/cloud/reference/cli.md +++ b/docs/docs/cloud/reference/cli.md @@ -53,7 +53,7 @@ The LangGraph CLI requires a JSON configuration file that follows this [schema]( | `pip_installer` | _(Added in v0.3)_ Optional. Python package installer selector. It can be set to `"auto"`, `"pip"`, or `"uv"`. From version 0.3 onward the default strategy is to run `uv pip`, which typically delivers faster builds while remaining a drop-in replacement. In the uncommon situation where `uv` cannot handle your dependency graph or the structure of your `pyproject.toml`, specify `"pip"` here to revert to the earlier behaviour. | | `dockerfile_lines` | Array of additional lines to add to Dockerfile following the import from parent image. | | `checkpointer` | Configuration for the checkpointer. Contains a `ttl` field which is an object with the following keys: | - | `http` | HTTP server configuration with the following fields: | + | `http` | HTTP server configuration with the following fields: | === "JS" diff --git a/docs/docs/cloud/reference/sdk/js_ts_sdk_ref.md b/docs/docs/cloud/reference/sdk/js_ts_sdk_ref.md new file mode 100644 index 000000000..e90a54cad --- /dev/null +++ b/docs/docs/cloud/reference/sdk/js_ts_sdk_ref.md @@ -0,0 +1,3403 @@ + + + +**[@langchain/langgraph-sdk](https://github.com/langchain-ai/langgraph/tree/main/libs/sdk-js)** + +*** + +## [@langchain/langgraph-sdk](https://github.com/langchain-ai/langgraph/tree/main/libs/sdk-js) + +### Classes + +- [AssistantsClient](#classesassistantsclientmd) +- [Client](#classesclientmd) +- [CronsClient](#classescronsclientmd) +- [RunsClient](#classesrunsclientmd) +- [StoreClient](#classesstoreclientmd) +- [ThreadsClient](#classesthreadsclientmd) + +### Interfaces + +- [ClientConfig](#interfacesclientconfigmd) + +### Functions + +- [getApiKey](#functionsgetapikeymd) + + + + +**@langchain/langgraph-sdk** + +*** + +## @langchain/langgraph-sdk/auth + +### Classes + +- [Auth](#authclassesauthmd) +- [HTTPException](#authclasseshttpexceptionmd) + +### Interfaces + +- [AuthEventValueMap](#authinterfacesautheventvaluemapmd) + +### Type Aliases + +- [AuthFilters](#authtype-aliasesauthfiltersmd) + + + + +[**@langchain/langgraph-sdk**](#authreadmemd) + +*** + +[@langchain/langgraph-sdk](#authreadmemd) / Auth + +## Class: Auth\ + +Defined in: [src/auth/index.ts:11](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/index.ts#L11) + +### Type Parameters + +• **TExtra** = \{\} + +• **TAuthReturn** *extends* `BaseAuthReturn` = `BaseAuthReturn` + +• **TUser** *extends* `BaseUser` = `ToUserLike`\<`TAuthReturn`\> + +### Constructors + +#### new Auth() + +> **new Auth**\<`TExtra`, `TAuthReturn`, `TUser`\>(): [`Auth`](#authclassesauthmd)\<`TExtra`, `TAuthReturn`, `TUser`\> + +##### Returns + +[`Auth`](#authclassesauthmd)\<`TExtra`, `TAuthReturn`, `TUser`\> + +### Methods + +#### authenticate() + +> **authenticate**\<`T`\>(`cb`): [`Auth`](#authclassesauthmd)\<`TExtra`, `T`\> + +Defined in: [src/auth/index.ts:25](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/index.ts#L25) + +##### Type Parameters + +• **T** *extends* `BaseAuthReturn` + +##### Parameters + +###### cb + +`AuthenticateCallback`\<`T`\> + +##### Returns + +[`Auth`](#authclassesauthmd)\<`TExtra`, `T`\> + +*** + +#### on() + +> **on**\<`T`\>(`event`, `callback`): `this` + +Defined in: [src/auth/index.ts:32](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/index.ts#L32) + +##### Type Parameters + +• **T** *extends* `CallbackEvent` + +##### Parameters + +###### event + +`T` + +###### callback + +`OnCallback`\<`T`, `TUser`\> + +##### Returns + +`this` + + + + +[**@langchain/langgraph-sdk**](#authreadmemd) + +*** + +[@langchain/langgraph-sdk](#authreadmemd) / HTTPException + +## Class: HTTPException + +Defined in: [src/auth/error.ts:66](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/error.ts#L66) + +### Extends + +- `Error` + +### Constructors + +#### new HTTPException() + +> **new HTTPException**(`status`, `options`?): [`HTTPException`](#authclasseshttpexceptionmd) + +Defined in: [src/auth/error.ts:70](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/error.ts#L70) + +##### Parameters + +###### status + +`number` + +###### options? + +####### cause? + +`unknown` + +####### headers? + +`HeadersInit` + +####### message? + +`string` + +##### Returns + +[`HTTPException`](#authclasseshttpexceptionmd) + +##### Overrides + +`Error.constructor` + +### Properties + +#### cause? + +> `optional` **cause**: `unknown` + +Defined in: node\_modules/typescript/lib/lib.es2022.error.d.ts:24 + +##### Inherited from + +`Error.cause` + +*** + +#### headers + +> **headers**: `HeadersInit` + +Defined in: [src/auth/error.ts:68](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/error.ts#L68) + +*** + +#### message + +> **message**: `string` + +Defined in: node\_modules/typescript/lib/lib.es5.d.ts:1077 + +##### Inherited from + +`Error.message` + +*** + +#### name + +> **name**: `string` + +Defined in: node\_modules/typescript/lib/lib.es5.d.ts:1076 + +##### Inherited from + +`Error.name` + +*** + +#### stack? + +> `optional` **stack**: `string` + +Defined in: node\_modules/typescript/lib/lib.es5.d.ts:1078 + +##### Inherited from + +`Error.stack` + +*** + +#### status + +> **status**: `number` + +Defined in: [src/auth/error.ts:67](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/error.ts#L67) + +*** + +#### prepareStackTrace()? + +> `static` `optional` **prepareStackTrace**: (`err`, `stackTraces`) => `any` + +Defined in: node\_modules/@types/node/globals.d.ts:28 + +Optional override for formatting stack traces + +##### Parameters + +###### err + +`Error` + +###### stackTraces + +`CallSite`[] + +##### Returns + +`any` + +##### See + +https://v8.dev/docs/stack-trace-api#customizing-stack-traces + +##### Inherited from + +`Error.prepareStackTrace` + +*** + +#### stackTraceLimit + +> `static` **stackTraceLimit**: `number` + +Defined in: node\_modules/@types/node/globals.d.ts:30 + +##### Inherited from + +`Error.stackTraceLimit` + +### Methods + +#### captureStackTrace() + +> `static` **captureStackTrace**(`targetObject`, `constructorOpt`?): `void` + +Defined in: node\_modules/@types/node/globals.d.ts:21 + +Create .stack property on a target object + +##### Parameters + +###### targetObject + +`object` + +###### constructorOpt? + +`Function` + +##### Returns + +`void` + +##### Inherited from + +`Error.captureStackTrace` + + + + +[**@langchain/langgraph-sdk**](#authreadmemd) + +*** + +[@langchain/langgraph-sdk](#authreadmemd) / AuthEventValueMap + +## Interface: AuthEventValueMap + +Defined in: [src/auth/types.ts:218](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L218) + +### Properties + +#### assistants:create + +> **assistants:create**: `object` + +Defined in: [src/auth/types.ts:226](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L226) + +##### assistant\_id? + +> `optional` **assistant\_id**: `Maybe`\<`string`\> + +##### config? + +> `optional` **config**: `Maybe`\<`AssistantConfig`\> + +##### graph\_id + +> **graph\_id**: `string` + +##### if\_exists? + +> `optional` **if\_exists**: `Maybe`\<`"raise"` \| `"do_nothing"`\> + +##### metadata? + +> `optional` **metadata**: `Maybe`\<`Record`\<`string`, `unknown`\>\> + +##### name? + +> `optional` **name**: `Maybe`\<`string`\> + +*** + +#### assistants:delete + +> **assistants:delete**: `object` + +Defined in: [src/auth/types.ts:229](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L229) + +##### assistant\_id + +> **assistant\_id**: `string` + +*** + +#### assistants:read + +> **assistants:read**: `object` + +Defined in: [src/auth/types.ts:227](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L227) + +##### assistant\_id + +> **assistant\_id**: `string` + +##### metadata? + +> `optional` **metadata**: `Maybe`\<`Record`\<`string`, `unknown`\>\> + +*** + +#### assistants:search + +> **assistants:search**: `object` + +Defined in: [src/auth/types.ts:230](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L230) + +##### graph\_id? + +> `optional` **graph\_id**: `Maybe`\<`string`\> + +##### limit? + +> `optional` **limit**: `Maybe`\<`number`\> + +##### metadata? + +> `optional` **metadata**: `Maybe`\<`Record`\<`string`, `unknown`\>\> + +##### offset? + +> `optional` **offset**: `Maybe`\<`number`\> + +*** + +#### assistants:update + +> **assistants:update**: `object` + +Defined in: [src/auth/types.ts:228](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L228) + +##### assistant\_id + +> **assistant\_id**: `string` + +##### config? + +> `optional` **config**: `Maybe`\<`AssistantConfig`\> + +##### graph\_id? + +> `optional` **graph\_id**: `Maybe`\<`string`\> + +##### metadata? + +> `optional` **metadata**: `Maybe`\<`Record`\<`string`, `unknown`\>\> + +##### name? + +> `optional` **name**: `Maybe`\<`string`\> + +##### version? + +> `optional` **version**: `Maybe`\<`number`\> + +*** + +#### crons:create + +> **crons:create**: `object` + +Defined in: [src/auth/types.ts:232](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L232) + +##### cron\_id? + +> `optional` **cron\_id**: `Maybe`\<`string`\> + +##### end\_time? + +> `optional` **end\_time**: `Maybe`\<`string`\> + +##### payload? + +> `optional` **payload**: `Maybe`\<`Record`\<`string`, `unknown`\>\> + +##### schedule + +> **schedule**: `string` + +##### thread\_id? + +> `optional` **thread\_id**: `Maybe`\<`string`\> + +##### user\_id? + +> `optional` **user\_id**: `Maybe`\<`string`\> + +*** + +#### crons:delete + +> **crons:delete**: `object` + +Defined in: [src/auth/types.ts:235](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L235) + +##### cron\_id + +> **cron\_id**: `string` + +*** + +#### crons:read + +> **crons:read**: `object` + +Defined in: [src/auth/types.ts:233](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L233) + +##### cron\_id + +> **cron\_id**: `string` + +*** + +#### crons:search + +> **crons:search**: `object` + +Defined in: [src/auth/types.ts:236](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L236) + +##### assistant\_id? + +> `optional` **assistant\_id**: `Maybe`\<`string`\> + +##### limit? + +> `optional` **limit**: `Maybe`\<`number`\> + +##### offset? + +> `optional` **offset**: `Maybe`\<`number`\> + +##### thread\_id? + +> `optional` **thread\_id**: `Maybe`\<`string`\> + +*** + +#### crons:update + +> **crons:update**: `object` + +Defined in: [src/auth/types.ts:234](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L234) + +##### cron\_id + +> **cron\_id**: `string` + +##### payload? + +> `optional` **payload**: `Maybe`\<`Record`\<`string`, `unknown`\>\> + +##### schedule? + +> `optional` **schedule**: `Maybe`\<`string`\> + +*** + +#### store:delete + +> **store:delete**: `object` + +Defined in: [src/auth/types.ts:242](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L242) + +##### key + +> **key**: `string` + +##### namespace? + +> `optional` **namespace**: `Maybe`\<`string`[]\> + +*** + +#### store:get + +> **store:get**: `object` + +Defined in: [src/auth/types.ts:239](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L239) + +##### key + +> **key**: `string` + +##### namespace + +> **namespace**: `Maybe`\<`string`[]\> + +*** + +#### store:list\_namespaces + +> **store:list\_namespaces**: `object` + +Defined in: [src/auth/types.ts:241](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L241) + +##### limit? + +> `optional` **limit**: `Maybe`\<`number`\> + +##### max\_depth? + +> `optional` **max\_depth**: `Maybe`\<`number`\> + +##### namespace? + +> `optional` **namespace**: `Maybe`\<`string`[]\> + +##### offset? + +> `optional` **offset**: `Maybe`\<`number`\> + +##### suffix? + +> `optional` **suffix**: `Maybe`\<`string`[]\> + +*** + +#### store:put + +> **store:put**: `object` + +Defined in: [src/auth/types.ts:238](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L238) + +##### key + +> **key**: `string` + +##### namespace + +> **namespace**: `string`[] + +##### value + +> **value**: `Record`\<`string`, `unknown`\> + +*** + +#### store:search + +> **store:search**: `object` + +Defined in: [src/auth/types.ts:240](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L240) + +##### filter? + +> `optional` **filter**: `Maybe`\<`Record`\<`string`, `unknown`\>\> + +##### limit? + +> `optional` **limit**: `Maybe`\<`number`\> + +##### namespace? + +> `optional` **namespace**: `Maybe`\<`string`[]\> + +##### offset? + +> `optional` **offset**: `Maybe`\<`number`\> + +##### query? + +> `optional` **query**: `Maybe`\<`string`\> + +*** + +#### threads:create + +> **threads:create**: `object` + +Defined in: [src/auth/types.ts:219](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L219) + +##### if\_exists? + +> `optional` **if\_exists**: `Maybe`\<`"raise"` \| `"do_nothing"`\> + +##### metadata? + +> `optional` **metadata**: `Maybe`\<`Record`\<`string`, `unknown`\>\> + +##### thread\_id? + +> `optional` **thread\_id**: `Maybe`\<`string`\> + +*** + +#### threads:create\_run + +> **threads:create\_run**: `object` + +Defined in: [src/auth/types.ts:224](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L224) + +##### after\_seconds? + +> `optional` **after\_seconds**: `Maybe`\<`number`\> + +##### assistant\_id + +> **assistant\_id**: `string` + +##### if\_not\_exists? + +> `optional` **if\_not\_exists**: `Maybe`\<`"reject"` \| `"create"`\> + +##### kwargs + +> **kwargs**: `Record`\<`string`, `unknown`\> + +##### metadata? + +> `optional` **metadata**: `Maybe`\<`Record`\<`string`, `unknown`\>\> + +##### multitask\_strategy? + +> `optional` **multitask\_strategy**: `Maybe`\<`"reject"` \| `"interrupt"` \| `"rollback"` \| `"enqueue"`\> + +##### prevent\_insert\_if\_inflight? + +> `optional` **prevent\_insert\_if\_inflight**: `Maybe`\<`boolean`\> + +##### run\_id + +> **run\_id**: `string` + +##### status + +> **status**: `Maybe`\<`"pending"` \| `"running"` \| `"error"` \| `"success"` \| `"timeout"` \| `"interrupted"`\> + +##### thread\_id? + +> `optional` **thread\_id**: `Maybe`\<`string`\> + +*** + +#### threads:delete + +> **threads:delete**: `object` + +Defined in: [src/auth/types.ts:222](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L222) + +##### run\_id? + +> `optional` **run\_id**: `Maybe`\<`string`\> + +##### thread\_id? + +> `optional` **thread\_id**: `Maybe`\<`string`\> + +*** + +#### threads:read + +> **threads:read**: `object` + +Defined in: [src/auth/types.ts:220](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L220) + +##### thread\_id? + +> `optional` **thread\_id**: `Maybe`\<`string`\> + +*** + +#### threads:search + +> **threads:search**: `object` + +Defined in: [src/auth/types.ts:223](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L223) + +##### limit? + +> `optional` **limit**: `Maybe`\<`number`\> + +##### metadata? + +> `optional` **metadata**: `Maybe`\<`Record`\<`string`, `unknown`\>\> + +##### offset? + +> `optional` **offset**: `Maybe`\<`number`\> + +##### status? + +> `optional` **status**: `Maybe`\<`"error"` \| `"interrupted"` \| `"idle"` \| `"busy"` \| `string` & `object`\> + +##### thread\_id? + +> `optional` **thread\_id**: `Maybe`\<`string`\> + +##### values? + +> `optional` **values**: `Maybe`\<`Record`\<`string`, `unknown`\>\> + +*** + +#### threads:update + +> **threads:update**: `object` + +Defined in: [src/auth/types.ts:221](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L221) + +##### action? + +> `optional` **action**: `Maybe`\<`"interrupt"` \| `"rollback"`\> + +##### metadata? + +> `optional` **metadata**: `Maybe`\<`Record`\<`string`, `unknown`\>\> + +##### thread\_id? + +> `optional` **thread\_id**: `Maybe`\<`string`\> + + + + +[**@langchain/langgraph-sdk**](#authreadmemd) + +*** + +[@langchain/langgraph-sdk](#authreadmemd) / AuthFilters + +## Type Alias: AuthFilters\ + +> **AuthFilters**\<`TKey`\>: \{ \[key in TKey\]: string \| \{ \[op in "$contains" \| "$eq"\]?: string \} \} + +Defined in: [src/auth/types.ts:367](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/auth/types.ts#L367) + +### Type Parameters + +• **TKey** *extends* `string` \| `number` \| `symbol` + + + + +[**@langchain/langgraph-sdk**](#readmemd) + +*** + +[@langchain/langgraph-sdk](#readmemd) / AssistantsClient + +## Class: AssistantsClient + +Defined in: [client.ts:294](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L294) + +### Extends + +- `BaseClient` + +### Constructors + +#### new AssistantsClient() + +> **new AssistantsClient**(`config`?): [`AssistantsClient`](#classesassistantsclientmd) + +Defined in: [client.ts:88](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L88) + +##### Parameters + +###### config? + +[`ClientConfig`](#interfacesclientconfigmd) + +##### Returns + +[`AssistantsClient`](#classesassistantsclientmd) + +##### Inherited from + +`BaseClient.constructor` + +### Methods + +#### create() + +> **create**(`payload`): `Promise`\<`Assistant`\> + +Defined in: [client.ts:359](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L359) + +Create a new assistant. + +##### Parameters + +###### payload + +Payload for creating an assistant. + +####### assistantId? + +`string` + +####### config? + +`Config` + +####### description? + +`string` + +####### graphId + +`string` + +####### ifExists? + +`OnConflictBehavior` + +####### metadata? + +`Metadata` + +####### name? + +`string` + +##### Returns + +`Promise`\<`Assistant`\> + +The created assistant. + +*** + +#### delete() + +> **delete**(`assistantId`): `Promise`\<`void`\> + +Defined in: [client.ts:415](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L415) + +Delete an assistant. + +##### Parameters + +###### assistantId + +`string` + +ID of the assistant. + +##### Returns + +`Promise`\<`void`\> + +*** + +#### get() + +> **get**(`assistantId`): `Promise`\<`Assistant`\> + +Defined in: [client.ts:301](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L301) + +Get an assistant by ID. + +##### Parameters + +###### assistantId + +`string` + +The ID of the assistant. + +##### Returns + +`Promise`\<`Assistant`\> + +Assistant + +*** + +#### getGraph() + +> **getGraph**(`assistantId`, `options`?): `Promise`\<`AssistantGraph`\> + +Defined in: [client.ts:311](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L311) + +Get the JSON representation of the graph assigned to a runnable + +##### Parameters + +###### assistantId + +`string` + +The ID of the assistant. + +###### options? + +####### xray? + +`number` \| `boolean` + +Whether to include subgraphs in the serialized graph representation. If an integer value is provided, only subgraphs with a depth less than or equal to the value will be included. + +##### Returns + +`Promise`\<`AssistantGraph`\> + +Serialized graph + +*** + +#### getSchemas() + +> **getSchemas**(`assistantId`): `Promise`\<`GraphSchema`\> + +Defined in: [client.ts:325](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L325) + +Get the state and config schema of the graph assigned to a runnable + +##### Parameters + +###### assistantId + +`string` + +The ID of the assistant. + +##### Returns + +`Promise`\<`GraphSchema`\> + +Graph schema + +*** + +#### getSubgraphs() + +> **getSubgraphs**(`assistantId`, `options`?): `Promise`\<`Subgraphs`\> + +Defined in: [client.ts:336](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L336) + +Get the schemas of an assistant by ID. + +##### Parameters + +###### assistantId + +`string` + +The ID of the assistant to get the schema of. + +###### options? + +Additional options for getting subgraphs, such as namespace or recursion extraction. + +####### namespace? + +`string` + +####### recurse? + +`boolean` + +##### Returns + +`Promise`\<`Subgraphs`\> + +The subgraphs of the assistant. + +*** + +#### getVersions() + +> **getVersions**(`assistantId`, `payload`?): `Promise`\<`AssistantVersion`[]\> + +Defined in: [client.ts:453](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L453) + +List all versions of an assistant. + +##### Parameters + +###### assistantId + +`string` + +ID of the assistant. + +###### payload? + +####### limit? + +`number` + +####### metadata? + +`Metadata` + +####### offset? + +`number` + +##### Returns + +`Promise`\<`AssistantVersion`[]\> + +List of assistant versions. + +*** + +#### search() + +> **search**(`query`?): `Promise`\<`Assistant`[]\> + +Defined in: [client.ts:426](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L426) + +List assistants. + +##### Parameters + +###### query? + +Query options. + +####### graphId? + +`string` + +####### limit? + +`number` + +####### metadata? + +`Metadata` + +####### offset? + +`number` + +####### sortBy? + +`AssistantSortBy` + +####### sortOrder? + +`SortOrder` + +##### Returns + +`Promise`\<`Assistant`[]\> + +List of assistants. + +*** + +#### setLatest() + +> **setLatest**(`assistantId`, `version`): `Promise`\<`Assistant`\> + +Defined in: [client.ts:481](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L481) + +Change the version of an assistant. + +##### Parameters + +###### assistantId + +`string` + +ID of the assistant. + +###### version + +`number` + +The version to change to. + +##### Returns + +`Promise`\<`Assistant`\> + +The updated assistant. + +*** + +#### update() + +> **update**(`assistantId`, `payload`): `Promise`\<`Assistant`\> + +Defined in: [client.ts:388](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L388) + +Update an assistant. + +##### Parameters + +###### assistantId + +`string` + +ID of the assistant. + +###### payload + +Payload for updating the assistant. + +####### config? + +`Config` + +####### description? + +`string` + +####### graphId? + +`string` + +####### metadata? + +`Metadata` + +####### name? + +`string` + +##### Returns + +`Promise`\<`Assistant`\> + +The updated assistant. + + + + +[**@langchain/langgraph-sdk**](#readmemd) + +*** + +[@langchain/langgraph-sdk](#readmemd) / Client + +## Class: Client\ + +Defined in: [client.ts:1448](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1448) + +### Type Parameters + +• **TStateType** = `DefaultValues` + +• **TUpdateType** = `TStateType` + +• **TCustomEventType** = `unknown` + +### Constructors + +#### new Client() + +> **new Client**\<`TStateType`, `TUpdateType`, `TCustomEventType`\>(`config`?): [`Client`](#classesclientmd)\<`TStateType`, `TUpdateType`, `TCustomEventType`\> + +Defined in: [client.ts:1484](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1484) + +##### Parameters + +###### config? + +[`ClientConfig`](#interfacesclientconfigmd) + +##### Returns + +[`Client`](#classesclientmd)\<`TStateType`, `TUpdateType`, `TCustomEventType`\> + +### Properties + +#### ~ui + +> **~ui**: `UiClient` + +Defined in: [client.ts:1482](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1482) + +**`Internal`** + +The client for interacting with the UI. + Used by LoadExternalComponent and the API might change in the future. + +*** + +#### assistants + +> **assistants**: [`AssistantsClient`](#classesassistantsclientmd) + +Defined in: [client.ts:1456](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1456) + +The client for interacting with assistants. + +*** + +#### crons + +> **crons**: [`CronsClient`](#classescronsclientmd) + +Defined in: [client.ts:1471](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1471) + +The client for interacting with cron runs. + +*** + +#### runs + +> **runs**: [`RunsClient`](#classesrunsclientmd)\<`TStateType`, `TUpdateType`, `TCustomEventType`\> + +Defined in: [client.ts:1466](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1466) + +The client for interacting with runs. + +*** + +#### store + +> **store**: [`StoreClient`](#classesstoreclientmd) + +Defined in: [client.ts:1476](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1476) + +The client for interacting with the KV store. + +*** + +#### threads + +> **threads**: [`ThreadsClient`](#classesthreadsclientmd)\<`TStateType`, `TUpdateType`\> + +Defined in: [client.ts:1461](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1461) + +The client for interacting with threads. + + + + +[**@langchain/langgraph-sdk**](#readmemd) + +*** + +[@langchain/langgraph-sdk](#readmemd) / CronsClient + +## Class: CronsClient + +Defined in: [client.ts:197](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L197) + +### Extends + +- `BaseClient` + +### Constructors + +#### new CronsClient() + +> **new CronsClient**(`config`?): [`CronsClient`](#classescronsclientmd) + +Defined in: [client.ts:88](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L88) + +##### Parameters + +###### config? + +[`ClientConfig`](#interfacesclientconfigmd) + +##### Returns + +[`CronsClient`](#classescronsclientmd) + +##### Inherited from + +`BaseClient.constructor` + +### Methods + +#### create() + +> **create**(`assistantId`, `payload`?): `Promise`\<`CronCreateResponse`\> + +Defined in: [client.ts:238](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L238) + +##### Parameters + +###### assistantId + +`string` + +Assistant ID to use for this cron job. + +###### payload? + +`CronsCreatePayload` + +Payload for creating a cron job. + +##### Returns + +`Promise`\<`CronCreateResponse`\> + +*** + +#### createForThread() + +> **createForThread**(`threadId`, `assistantId`, `payload`?): `Promise`\<`CronCreateForThreadResponse`\> + +Defined in: [client.ts:205](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L205) + +##### Parameters + +###### threadId + +`string` + +The ID of the thread. + +###### assistantId + +`string` + +Assistant ID to use for this cron job. + +###### payload? + +`CronsCreatePayload` + +Payload for creating a cron job. + +##### Returns + +`Promise`\<`CronCreateForThreadResponse`\> + +The created background run. + +*** + +#### delete() + +> **delete**(`cronId`): `Promise`\<`void`\> + +Defined in: [client.ts:265](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L265) + +##### Parameters + +###### cronId + +`string` + +Cron ID of Cron job to delete. + +##### Returns + +`Promise`\<`void`\> + +*** + +#### search() + +> **search**(`query`?): `Promise`\<`Cron`[]\> + +Defined in: [client.ts:276](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L276) + +##### Parameters + +###### query? + +Query options. + +####### assistantId? + +`string` + +####### limit? + +`number` + +####### offset? + +`number` + +####### threadId? + +`string` + +##### Returns + +`Promise`\<`Cron`[]\> + +List of crons. + + + + +[**@langchain/langgraph-sdk**](#readmemd) + +*** + +[@langchain/langgraph-sdk](#readmemd) / RunsClient + +## Class: RunsClient\ + +Defined in: [client.ts:776](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L776) + +### Extends + +- `BaseClient` + +### Type Parameters + +• **TStateType** = `DefaultValues` + +• **TUpdateType** = `TStateType` + +• **TCustomEventType** = `unknown` + +### Constructors + +#### new RunsClient() + +> **new RunsClient**\<`TStateType`, `TUpdateType`, `TCustomEventType`\>(`config`?): [`RunsClient`](#classesrunsclientmd)\<`TStateType`, `TUpdateType`, `TCustomEventType`\> + +Defined in: [client.ts:88](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L88) + +##### Parameters + +###### config? + +[`ClientConfig`](#interfacesclientconfigmd) + +##### Returns + +[`RunsClient`](#classesrunsclientmd)\<`TStateType`, `TUpdateType`, `TCustomEventType`\> + +##### Inherited from + +`BaseClient.constructor` + +### Methods + +#### cancel() + +> **cancel**(`threadId`, `runId`, `wait`, `action`): `Promise`\<`void`\> + +Defined in: [client.ts:1063](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1063) + +Cancel a run. + +##### Parameters + +###### threadId + +`string` + +The ID of the thread. + +###### runId + +`string` + +The ID of the run. + +###### wait + +`boolean` = `false` + +Whether to block when canceling + +###### action + +`CancelAction` = `"interrupt"` + +Action to take when cancelling the run. Possible values are `interrupt` or `rollback`. Default is `interrupt`. + +##### Returns + +`Promise`\<`void`\> + +*** + +#### create() + +> **create**(`threadId`, `assistantId`, `payload`?): `Promise`\<`Run`\> + +Defined in: [client.ts:885](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L885) + +Create a run. + +##### Parameters + +###### threadId + +`string` + +The ID of the thread. + +###### assistantId + +`string` + +Assistant ID to use for this run. + +###### payload? + +`RunsCreatePayload` + +Payload for creating a run. + +##### Returns + +`Promise`\<`Run`\> + +The created run. + +*** + +#### createBatch() + +> **createBatch**(`payloads`): `Promise`\<`Run`[]\> + +Defined in: [client.ts:921](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L921) + +Create a batch of stateless background runs. + +##### Parameters + +###### payloads + +`RunsCreatePayload` & `object`[] + +An array of payloads for creating runs. + +##### Returns + +`Promise`\<`Run`[]\> + +An array of created runs. + +*** + +#### delete() + +> **delete**(`threadId`, `runId`): `Promise`\<`void`\> + +Defined in: [client.ts:1157](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1157) + +Delete a run. + +##### Parameters + +###### threadId + +`string` + +The ID of the thread. + +###### runId + +`string` + +The ID of the run. + +##### Returns + +`Promise`\<`void`\> + +*** + +#### get() + +> **get**(`threadId`, `runId`): `Promise`\<`Run`\> + +Defined in: [client.ts:1050](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1050) + +Get a run by ID. + +##### Parameters + +###### threadId + +`string` + +The ID of the thread. + +###### runId + +`string` + +The ID of the run. + +##### Returns + +`Promise`\<`Run`\> + +The run. + +*** + +#### join() + +> **join**(`threadId`, `runId`, `options`?): `Promise`\<`void`\> + +Defined in: [client.ts:1085](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1085) + +Block until a run is done. + +##### Parameters + +###### threadId + +`string` + +The ID of the thread. + +###### runId + +`string` + +The ID of the run. + +###### options? + +####### signal? + +`AbortSignal` + +##### Returns + +`Promise`\<`void`\> + +*** + +#### joinStream() + +> **joinStream**(`threadId`, `runId`, `options`?): `AsyncGenerator`\<\{ `data`: `any`; `event`: `StreamEvent`; \}\> + +Defined in: [client.ts:1111](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1111) + +Stream output from a run in real-time, until the run is done. +Output is not buffered, so any output produced before this call will +not be received here. + +##### Parameters + +###### threadId + +`string` + +The ID of the thread. + +###### runId + +`string` + +The ID of the run. + +###### options? + +Additional options for controlling the stream behavior: + - signal: An AbortSignal that can be used to cancel the stream request + - cancelOnDisconnect: When true, automatically cancels the run if the client disconnects from the stream + - streamMode: Controls what types of events to receive from the stream (can be a single mode or array of modes) + Must be a subset of the stream modes passed when creating the run. Background runs default to having the union of all + stream modes enabled. + +`AbortSignal` | \{ `cancelOnDisconnect`: `boolean`; `signal`: `AbortSignal`; `streamMode`: `StreamMode` \| `StreamMode`[]; \} + +##### Returns + +`AsyncGenerator`\<\{ `data`: `any`; `event`: `StreamEvent`; \}\> + +An async generator yielding stream parts. + +*** + +#### list() + +> **list**(`threadId`, `options`?): `Promise`\<`Run`[]\> + +Defined in: [client.ts:1013](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1013) + +List all runs for a thread. + +##### Parameters + +###### threadId + +`string` + +The ID of the thread. + +###### options? + +Filtering and pagination options. + +####### limit? + +`number` + +Maximum number of runs to return. +Defaults to 10 + +####### offset? + +`number` + +Offset to start from. +Defaults to 0. + +####### status? + +`RunStatus` + +Status of the run to filter by. + +##### Returns + +`Promise`\<`Run`[]\> + +List of runs. + +*** + +#### stream() + +Create a run and stream the results. + +##### Param + +The ID of the thread. + +##### Param + +Assistant ID to use for this run. + +##### Param + +Payload for creating a run. + +##### Call Signature + +> **stream**\<`TStreamMode`, `TSubgraphs`\>(`threadId`, `assistantId`, `payload`?): `TypedAsyncGenerator`\<`TStreamMode`, `TSubgraphs`, `TStateType`, `TUpdateType`, `TCustomEventType`\> + +Defined in: [client.ts:781](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L781) + +###### Type Parameters + +• **TStreamMode** *extends* `StreamMode` \| `StreamMode`[] = `StreamMode` + +• **TSubgraphs** *extends* `boolean` = `false` + +###### Parameters + +####### threadId + +`null` + +####### assistantId + +`string` + +####### payload? + +`Omit`\<`RunsStreamPayload`\<`TStreamMode`, `TSubgraphs`\>, `"multitaskStrategy"` \| `"onCompletion"`\> + +###### Returns + +`TypedAsyncGenerator`\<`TStreamMode`, `TSubgraphs`, `TStateType`, `TUpdateType`, `TCustomEventType`\> + +##### Call Signature + +> **stream**\<`TStreamMode`, `TSubgraphs`\>(`threadId`, `assistantId`, `payload`?): `TypedAsyncGenerator`\<`TStreamMode`, `TSubgraphs`, `TStateType`, `TUpdateType`, `TCustomEventType`\> + +Defined in: [client.ts:799](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L799) + +###### Type Parameters + +• **TStreamMode** *extends* `StreamMode` \| `StreamMode`[] = `StreamMode` + +• **TSubgraphs** *extends* `boolean` = `false` + +###### Parameters + +####### threadId + +`string` + +####### assistantId + +`string` + +####### payload? + +`RunsStreamPayload`\<`TStreamMode`, `TSubgraphs`\> + +###### Returns + +`TypedAsyncGenerator`\<`TStreamMode`, `TSubgraphs`, `TStateType`, `TUpdateType`, `TCustomEventType`\> + +*** + +#### wait() + +Create a run and wait for it to complete. + +##### Param + +The ID of the thread. + +##### Param + +Assistant ID to use for this run. + +##### Param + +Payload for creating a run. + +##### Call Signature + +> **wait**(`threadId`, `assistantId`, `payload`?): `Promise`\<`DefaultValues`\> + +Defined in: [client.ts:938](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L938) + +###### Parameters + +####### threadId + +`null` + +####### assistantId + +`string` + +####### payload? + +`Omit`\<`RunsWaitPayload`, `"multitaskStrategy"` \| `"onCompletion"`\> + +###### Returns + +`Promise`\<`DefaultValues`\> + +##### Call Signature + +> **wait**(`threadId`, `assistantId`, `payload`?): `Promise`\<`DefaultValues`\> + +Defined in: [client.ts:944](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L944) + +###### Parameters + +####### threadId + +`string` + +####### assistantId + +`string` + +####### payload? + +`RunsWaitPayload` + +###### Returns + +`Promise`\<`DefaultValues`\> + + + + +[**@langchain/langgraph-sdk**](#readmemd) + +*** + +[@langchain/langgraph-sdk](#readmemd) / StoreClient + +## Class: StoreClient + +Defined in: [client.ts:1175](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1175) + +### Extends + +- `BaseClient` + +### Constructors + +#### new StoreClient() + +> **new StoreClient**(`config`?): [`StoreClient`](#classesstoreclientmd) + +Defined in: [client.ts:88](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L88) + +##### Parameters + +###### config? + +[`ClientConfig`](#interfacesclientconfigmd) + +##### Returns + +[`StoreClient`](#classesstoreclientmd) + +##### Inherited from + +`BaseClient.constructor` + +### Methods + +#### deleteItem() + +> **deleteItem**(`namespace`, `key`): `Promise`\<`void`\> + +Defined in: [client.ts:1296](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1296) + +Delete an item. + +##### Parameters + +###### namespace + +`string`[] + +A list of strings representing the namespace path. + +###### key + +`string` + +The unique identifier for the item. + +##### Returns + +`Promise`\<`void`\> + +Promise + +*** + +#### getItem() + +> **getItem**(`namespace`, `key`, `options`?): `Promise`\<`null` \| `Item`\> + +Defined in: [client.ts:1252](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1252) + +Retrieve a single item. + +##### Parameters + +###### namespace + +`string`[] + +A list of strings representing the namespace path. + +###### key + +`string` + +The unique identifier for the item. + +###### options? + +####### refreshTtl? + +`null` \| `boolean` + +Whether to refresh the TTL on this read operation. If null, uses the store's default behavior. + +##### Returns + +`Promise`\<`null` \| `Item`\> + +Promise + +##### Example + +```typescript +const item = await client.store.getItem( + ["documents", "user123"], + "item456", + { refreshTtl: true } +); +console.log(item); +// { +// namespace: ["documents", "user123"], +// key: "item456", +// value: { title: "My Document", content: "Hello World" }, +// createdAt: "2024-07-30T12:00:00Z", +// updatedAt: "2024-07-30T12:00:00Z" +// } +``` + +*** + +#### listNamespaces() + +> **listNamespaces**(`options`?): `Promise`\<`ListNamespaceResponse`\> + +Defined in: [client.ts:1392](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1392) + +List namespaces with optional match conditions. + +##### Parameters + +###### options? + +####### limit? + +`number` + +Maximum number of namespaces to return (default is 100). + +####### maxDepth? + +`number` + +Optional integer specifying the maximum depth of namespaces to return. + +####### offset? + +`number` + +Number of namespaces to skip before returning results (default is 0). + +####### prefix? + +`string`[] + +Optional list of strings representing the prefix to filter namespaces. + +####### suffix? + +`string`[] + +Optional list of strings representing the suffix to filter namespaces. + +##### Returns + +`Promise`\<`ListNamespaceResponse`\> + +Promise + +*** + +#### putItem() + +> **putItem**(`namespace`, `key`, `value`, `options`?): `Promise`\<`void`\> + +Defined in: [client.ts:1196](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1196) + +Store or update an item. + +##### Parameters + +###### namespace + +`string`[] + +A list of strings representing the namespace path. + +###### key + +`string` + +The unique identifier for the item within the namespace. + +###### value + +`Record`\<`string`, `any`\> + +A dictionary containing the item's data. + +###### options? + +####### index? + +`null` \| `false` \| `string`[] + +Controls search indexing - null (use defaults), false (disable), or list of field paths to index. + +####### ttl? + +`null` \| `number` + +Optional time-to-live in minutes for the item, or null for no expiration. + +##### Returns + +`Promise`\<`void`\> + +Promise + +##### Example + +```typescript +await client.store.putItem( + ["documents", "user123"], + "item456", + { title: "My Document", content: "Hello World" }, + { ttl: 60 } // expires in 60 minutes +); +``` + +*** + +#### searchItems() + +> **searchItems**(`namespacePrefix`, `options`?): `Promise`\<`SearchItemsResponse`\> + +Defined in: [client.ts:1347](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L1347) + +Search for items within a namespace prefix. + +##### Parameters + +###### namespacePrefix + +`string`[] + +List of strings representing the namespace prefix. + +###### options? + +####### filter? + +`Record`\<`string`, `any`\> + +Optional dictionary of key-value pairs to filter results. + +####### limit? + +`number` + +Maximum number of items to return (default is 10). + +####### offset? + +`number` + +Number of items to skip before returning results (default is 0). + +####### query? + +`string` + +Optional search query. + +####### refreshTtl? + +`null` \| `boolean` + +Whether to refresh the TTL on items returned by this search. If null, uses the store's default behavior. + +##### Returns + +`Promise`\<`SearchItemsResponse`\> + +Promise + +##### Example + +```typescript +const results = await client.store.searchItems( + ["documents"], + { + filter: { author: "John Doe" }, + limit: 5, + refreshTtl: true + } +); +console.log(results); +// { +// items: [ +// { +// namespace: ["documents", "user123"], +// key: "item789", +// value: { title: "Another Document", author: "John Doe" }, +// createdAt: "2024-07-30T12:00:00Z", +// updatedAt: "2024-07-30T12:00:00Z" +// }, +// // ... additional items ... +// ] +// } +``` + + + + +[**@langchain/langgraph-sdk**](#readmemd) + +*** + +[@langchain/langgraph-sdk](#readmemd) / ThreadsClient + +## Class: ThreadsClient\ + +Defined in: [client.ts:489](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L489) + +### Extends + +- `BaseClient` + +### Type Parameters + +• **TStateType** = `DefaultValues` + +• **TUpdateType** = `TStateType` + +### Constructors + +#### new ThreadsClient() + +> **new ThreadsClient**\<`TStateType`, `TUpdateType`\>(`config`?): [`ThreadsClient`](#classesthreadsclientmd)\<`TStateType`, `TUpdateType`\> + +Defined in: [client.ts:88](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L88) + +##### Parameters + +###### config? + +[`ClientConfig`](#interfacesclientconfigmd) + +##### Returns + +[`ThreadsClient`](#classesthreadsclientmd)\<`TStateType`, `TUpdateType`\> + +##### Inherited from + +`BaseClient.constructor` + +### Methods + +#### copy() + +> **copy**(`threadId`): `Promise`\<`Thread`\<`TStateType`\>\> + +Defined in: [client.ts:566](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L566) + +Copy an existing thread + +##### Parameters + +###### threadId + +`string` + +ID of the thread to be copied + +##### Returns + +`Promise`\<`Thread`\<`TStateType`\>\> + +Newly copied thread + +*** + +#### create() + +> **create**(`payload`?): `Promise`\<`Thread`\<`TStateType`\>\> + +Defined in: [client.ts:511](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L511) + +Create a new thread. + +##### Parameters + +###### payload? + +Payload for creating a thread. + +####### graphId? + +`string` + +Graph ID to associate with the thread. + +####### ifExists? + +`OnConflictBehavior` + +How to handle duplicate creation. + +**Default** + +```ts +"raise" +``` + +####### metadata? + +`Metadata` + +Metadata for the thread. + +####### supersteps? + +`object`[] + +Apply a list of supersteps when creating a thread, each containing a sequence of updates. + +Used for copying a thread between deployments. + +####### threadId? + +`string` + +ID of the thread to create. + +If not provided, a random UUID will be generated. + +##### Returns + +`Promise`\<`Thread`\<`TStateType`\>\> + +The created thread. + +*** + +#### delete() + +> **delete**(`threadId`): `Promise`\<`void`\> + +Defined in: [client.ts:599](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L599) + +Delete a thread. + +##### Parameters + +###### threadId + +`string` + +ID of the thread. + +##### Returns + +`Promise`\<`void`\> + +*** + +#### get() + +> **get**\<`ValuesType`\>(`threadId`): `Promise`\<`Thread`\<`ValuesType`\>\> + +Defined in: [client.ts:499](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L499) + +Get a thread by ID. + +##### Type Parameters + +• **ValuesType** = `TStateType` + +##### Parameters + +###### threadId + +`string` + +ID of the thread. + +##### Returns + +`Promise`\<`Thread`\<`ValuesType`\>\> + +The thread. + +*** + +#### getHistory() + +> **getHistory**\<`ValuesType`\>(`threadId`, `options`?): `Promise`\<`ThreadState`\<`ValuesType`\>[]\> + +Defined in: [client.ts:752](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L752) + +Get all past states for a thread. + +##### Type Parameters + +• **ValuesType** = `TStateType` + +##### Parameters + +###### threadId + +`string` + +ID of the thread. + +###### options? + +Additional options. + +####### before? + +`Config` + +####### checkpoint? + +`Partial`\<`Omit`\<`Checkpoint`, `"thread_id"`\>\> + +####### limit? + +`number` + +####### metadata? + +`Metadata` + +##### Returns + +`Promise`\<`ThreadState`\<`ValuesType`\>[]\> + +List of thread states. + +*** + +#### getState() + +> **getState**\<`ValuesType`\>(`threadId`, `checkpoint`?, `options`?): `Promise`\<`ThreadState`\<`ValuesType`\>\> + +Defined in: [client.ts:659](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L659) + +Get state for a thread. + +##### Type Parameters + +• **ValuesType** = `TStateType` + +##### Parameters + +###### threadId + +`string` + +ID of the thread. + +###### checkpoint? + +`string` | `Checkpoint` + +###### options? + +####### subgraphs? + +`boolean` + +##### Returns + +`Promise`\<`ThreadState`\<`ValuesType`\>\> + +Thread state. + +*** + +#### patchState() + +> **patchState**(`threadIdOrConfig`, `metadata`): `Promise`\<`void`\> + +Defined in: [client.ts:722](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L722) + +Patch the metadata of a thread. + +##### Parameters + +###### threadIdOrConfig + +Thread ID or config to patch the state of. + +`string` | `Config` + +###### metadata + +`Metadata` + +Metadata to patch the state with. + +##### Returns + +`Promise`\<`void`\> + +*** + +#### search() + +> **search**\<`ValuesType`\>(`query`?): `Promise`\<`Thread`\<`ValuesType`\>[]\> + +Defined in: [client.ts:611](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L611) + +List threads + +##### Type Parameters + +• **ValuesType** = `TStateType` + +##### Parameters + +###### query? + +Query options + +####### limit? + +`number` + +Maximum number of threads to return. +Defaults to 10 + +####### metadata? + +`Metadata` + +Metadata to filter threads by. + +####### offset? + +`number` + +Offset to start from. + +####### sortBy? + +`ThreadSortBy` + +Sort by. + +####### sortOrder? + +`SortOrder` + +Sort order. +Must be one of 'asc' or 'desc'. + +####### status? + +`ThreadStatus` + +Thread status to filter on. +Must be one of 'idle', 'busy', 'interrupted' or 'error'. + +##### Returns + +`Promise`\<`Thread`\<`ValuesType`\>[]\> + +List of threads + +*** + +#### update() + +> **update**(`threadId`, `payload`?): `Promise`\<`Thread`\<`DefaultValues`\>\> + +Defined in: [client.ts:579](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L579) + +Update a thread. + +##### Parameters + +###### threadId + +`string` + +ID of the thread. + +###### payload? + +Payload for updating the thread. + +####### metadata? + +`Metadata` + +Metadata for the thread. + +##### Returns + +`Promise`\<`Thread`\<`DefaultValues`\>\> + +The updated thread. + +*** + +#### updateState() + +> **updateState**\<`ValuesType`\>(`threadId`, `options`): `Promise`\<`Pick`\<`Config`, `"configurable"`\>\> + +Defined in: [client.ts:693](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L693) + +Add state to a thread. + +##### Type Parameters + +• **ValuesType** = `TUpdateType` + +##### Parameters + +###### threadId + +`string` + +The ID of the thread. + +###### options + +####### asNode? + +`string` + +####### checkpoint? + +`Checkpoint` + +####### checkpointId? + +`string` + +####### values + +`ValuesType` + +##### Returns + +`Promise`\<`Pick`\<`Config`, `"configurable"`\>\> + + + + +[**@langchain/langgraph-sdk**](#readmemd) + +*** + +[@langchain/langgraph-sdk](#readmemd) / getApiKey + +## Function: getApiKey() + +> **getApiKey**(`apiKey`?): `undefined` \| `string` + +Defined in: [client.ts:53](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L53) + +Get the API key from the environment. +Precedence: + 1. explicit argument + 2. LANGGRAPH_API_KEY + 3. LANGSMITH_API_KEY + 4. LANGCHAIN_API_KEY + +### Parameters + +#### apiKey? + +`string` + +Optional API key provided as an argument + +### Returns + +`undefined` \| `string` + +The API key if found, otherwise undefined + + + + +[**@langchain/langgraph-sdk**](#readmemd) + +*** + +[@langchain/langgraph-sdk](#readmemd) / ClientConfig + +## Interface: ClientConfig + +Defined in: [client.ts:71](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L71) + +### Properties + +#### apiKey? + +> `optional` **apiKey**: `string` + +Defined in: [client.ts:73](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L73) + +*** + +#### apiUrl? + +> `optional` **apiUrl**: `string` + +Defined in: [client.ts:72](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L72) + +*** + +#### callerOptions? + +> `optional` **callerOptions**: `AsyncCallerParams` + +Defined in: [client.ts:74](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L74) + +*** + +#### defaultHeaders? + +> `optional` **defaultHeaders**: `Record`\<`string`, `undefined` \| `null` \| `string`\> + +Defined in: [client.ts:76](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L76) + +*** + +#### timeoutMs? + +> `optional` **timeoutMs**: `number` + +Defined in: [client.ts:75](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/client.ts#L75) + + + + +**@langchain/langgraph-sdk** + +*** + +## @langchain/langgraph-sdk/react + +### Interfaces + +- [UseStream](#reactinterfacesusestreammd) +- [UseStreamOptions](#reactinterfacesusestreamoptionsmd) + +### Type Aliases + +- [MessageMetadata](#reacttype-aliasesmessagemetadatamd) + +### Functions + +- [useStream](#reactfunctionsusestreammd) + + + + +[**@langchain/langgraph-sdk**](#reactreadmemd) + +*** + +[@langchain/langgraph-sdk](#reactreadmemd) / useStream + +## Function: useStream() + +> **useStream**\<`StateType`, `Bag`\>(`options`): [`UseStream`](#reactinterfacesusestreammd)\<`StateType`, `Bag`\> + +Defined in: [react/stream.tsx:618](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L618) + +### Type Parameters + +• **StateType** *extends* `Record`\<`string`, `unknown`\> = `Record`\<`string`, `unknown`\> + +• **Bag** *extends* `object` = `BagTemplate` + +### Parameters + +#### options + +[`UseStreamOptions`](#reactinterfacesusestreamoptionsmd)\<`StateType`, `Bag`\> + +### Returns + +[`UseStream`](#reactinterfacesusestreammd)\<`StateType`, `Bag`\> + + + + +[**@langchain/langgraph-sdk**](#reactreadmemd) + +*** + +[@langchain/langgraph-sdk](#reactreadmemd) / UseStream + +## Interface: UseStream\ + +Defined in: [react/stream.tsx:507](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L507) + +### Type Parameters + +• **StateType** *extends* `Record`\<`string`, `unknown`\> = `Record`\<`string`, `unknown`\> + +• **Bag** *extends* `BagTemplate` = `BagTemplate` + +### Properties + +#### assistantId + +> **assistantId**: `string` + +Defined in: [react/stream.tsx:592](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L592) + +The ID of the assistant to use. + +*** + +#### branch + +> **branch**: `string` + +Defined in: [react/stream.tsx:542](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L542) + +The current branch of the thread. + +*** + +#### client + +> **client**: `Client` + +Defined in: [react/stream.tsx:587](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L587) + +LangGraph SDK client used to send request and receive responses. + +*** + +#### error + +> **error**: `unknown` + +Defined in: [react/stream.tsx:519](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L519) + +Last seen error from the thread or during streaming. + +*** + +#### experimental\_branchTree + +> **experimental\_branchTree**: `Sequence`\<`StateType`\> + +Defined in: [react/stream.tsx:558](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L558) + +**`Experimental`** + +Tree of all branches for the thread. + +*** + +#### getMessagesMetadata() + +> **getMessagesMetadata**: (`message`, `index`?) => `undefined` \| [`MessageMetadata`](#reacttype-aliasesmessagemetadatamd)\<`StateType`\> + +Defined in: [react/stream.tsx:579](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L579) + +Get the metadata for a message, such as first thread state the message +was seen in and branch information. + +##### Parameters + +###### message + +`Message` + +The message to get the metadata for. + +###### index? + +`number` + +The index of the message in the thread. + +##### Returns + +`undefined` \| [`MessageMetadata`](#reacttype-aliasesmessagemetadatamd)\<`StateType`\> + +The metadata for the message. + +*** + +#### history + +> **history**: `ThreadState`\<`StateType`\>[] + +Defined in: [react/stream.tsx:552](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L552) + +Flattened history of thread states of a thread. + +*** + +#### interrupt + +> **interrupt**: `undefined` \| `Interrupt`\<`GetInterruptType`\<`Bag`\>\> + +Defined in: [react/stream.tsx:563](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L563) + +Get the interrupt value for the stream if interrupted. + +*** + +#### isLoading + +> **isLoading**: `boolean` + +Defined in: [react/stream.tsx:524](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L524) + +Whether the stream is currently running. + +*** + +#### messages + +> **messages**: `Message`[] + +Defined in: [react/stream.tsx:569](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L569) + +Messages inferred from the thread. +Will automatically update with incoming message chunks. + +*** + +#### setBranch() + +> **setBranch**: (`branch`) => `void` + +Defined in: [react/stream.tsx:547](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L547) + +Set the branch of the thread. + +##### Parameters + +###### branch + +`string` + +##### Returns + +`void` + +*** + +#### stop() + +> **stop**: () => `void` + +Defined in: [react/stream.tsx:529](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L529) + +Stops the stream. + +##### Returns + +`void` + +*** + +#### submit() + +> **submit**: (`values`, `options`?) => `void` + +Defined in: [react/stream.tsx:534](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L534) + +Create and stream a run to the thread. + +##### Parameters + +###### values + +`undefined` | `null` | `GetUpdateType`\<`Bag`, `StateType`\> + +###### options? + +`SubmitOptions`\<`StateType`, `GetConfigurableType`\<`Bag`\>\> + +##### Returns + +`void` + +*** + +#### values + +> **values**: `StateType` + +Defined in: [react/stream.tsx:514](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L514) + +The current values of the thread. + + + + +[**@langchain/langgraph-sdk**](#reactreadmemd) + +*** + +[@langchain/langgraph-sdk](#reactreadmemd) / UseStreamOptions + +## Interface: UseStreamOptions\ + +Defined in: [react/stream.tsx:408](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L408) + +### Type Parameters + +• **StateType** *extends* `Record`\<`string`, `unknown`\> = `Record`\<`string`, `unknown`\> + +• **Bag** *extends* `BagTemplate` = `BagTemplate` + +### Properties + +#### apiKey? + +> `optional` **apiKey**: `string` + +Defined in: [react/stream.tsx:430](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L430) + +The API key to use. + +*** + +#### apiUrl? + +> `optional` **apiUrl**: `string` + +Defined in: [react/stream.tsx:425](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L425) + +The URL of the API to use. + +*** + +#### assistantId + +> **assistantId**: `string` + +Defined in: [react/stream.tsx:415](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L415) + +The ID of the assistant to use. + +*** + +#### callerOptions? + +> `optional` **callerOptions**: `AsyncCallerParams` + +Defined in: [react/stream.tsx:435](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L435) + +Custom call options, such as custom fetch implementation. + +*** + +#### client? + +> `optional` **client**: `Client`\<`DefaultValues`, `DefaultValues`, `unknown`\> + +Defined in: [react/stream.tsx:420](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L420) + +Client used to send requests. + +*** + +#### defaultHeaders? + +> `optional` **defaultHeaders**: `Record`\<`string`, `undefined` \| `null` \| `string`\> + +Defined in: [react/stream.tsx:440](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L440) + +Default headers to send with requests. + +*** + +#### messagesKey? + +> `optional` **messagesKey**: `string` + +Defined in: [react/stream.tsx:448](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L448) + +Specify the key within the state that contains messages. +Defaults to "messages". + +##### Default + +```ts +"messages" +``` + +*** + +#### onCustomEvent()? + +> `optional` **onCustomEvent**: (`data`, `options`) => `void` + +Defined in: [react/stream.tsx:470](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L470) + +Callback that is called when a custom event is received. + +##### Parameters + +###### data + +`GetCustomEventType`\<`Bag`\> + +###### options + +####### mutate + +(`update`) => `void` + +##### Returns + +`void` + +*** + +#### onDebugEvent()? + +> `optional` **onDebugEvent**: (`data`) => `void` + +Defined in: [react/stream.tsx:494](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L494) + +**`Internal`** + +Callback that is called when a debug event is received. + This API is experimental and subject to change. + +##### Parameters + +###### data + +`unknown` + +##### Returns + +`void` + +*** + +#### onError()? + +> `optional` **onError**: (`error`) => `void` + +Defined in: [react/stream.tsx:453](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L453) + +Callback that is called when an error occurs. + +##### Parameters + +###### error + +`unknown` + +##### Returns + +`void` + +*** + +#### onFinish()? + +> `optional` **onFinish**: (`state`) => `void` + +Defined in: [react/stream.tsx:458](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L458) + +Callback that is called when the stream is finished. + +##### Parameters + +###### state + +`ThreadState`\<`StateType`\> + +##### Returns + +`void` + +*** + +#### onLangChainEvent()? + +> `optional` **onLangChainEvent**: (`data`) => `void` + +Defined in: [react/stream.tsx:488](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L488) + +Callback that is called when a LangChain event is received. + +##### Parameters + +###### data + +####### data + +`unknown` + +####### event + +`string` & `object` \| `"on_tool_start"` \| `"on_tool_stream"` \| `"on_tool_end"` \| `"on_chat_model_start"` \| `"on_chat_model_stream"` \| `"on_chat_model_end"` \| `"on_llm_start"` \| `"on_llm_stream"` \| `"on_llm_end"` \| `"on_chain_start"` \| `"on_chain_stream"` \| `"on_chain_end"` \| `"on_retriever_start"` \| `"on_retriever_stream"` \| `"on_retriever_end"` \| `"on_prompt_start"` \| `"on_prompt_stream"` \| `"on_prompt_end"` + +####### metadata + +`Record`\<`string`, `unknown`\> + +####### name + +`string` + +####### parent_ids + +`string`[] + +####### run_id + +`string` + +####### tags + +`string`[] + +##### Returns + +`void` + +##### See + +https://langchain-ai.github.io/langgraph/cloud/how-tos/stream_events/#stream-graph-in-events-mode for more details. + +*** + +#### onMetadataEvent()? + +> `optional` **onMetadataEvent**: (`data`) => `void` + +Defined in: [react/stream.tsx:482](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L482) + +Callback that is called when a metadata event is received. + +##### Parameters + +###### data + +####### run_id + +`string` + +####### thread_id + +`string` + +##### Returns + +`void` + +*** + +#### onThreadId()? + +> `optional` **onThreadId**: (`threadId`) => `void` + +Defined in: [react/stream.tsx:504](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L504) + +Callback that is called when the thread ID is updated (ie when a new thread is created). + +##### Parameters + +###### threadId + +`string` + +##### Returns + +`void` + +*** + +#### onUpdateEvent()? + +> `optional` **onUpdateEvent**: (`data`) => `void` + +Defined in: [react/stream.tsx:463](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L463) + +Callback that is called when an update event is received. + +##### Parameters + +###### data + +##### Returns + +`void` + +*** + +#### threadId? + +> `optional` **threadId**: `null` \| `string` + +Defined in: [react/stream.tsx:499](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L499) + +The ID of the thread to fetch history and current values from. + + + + +[**@langchain/langgraph-sdk**](#reactreadmemd) + +*** + +[@langchain/langgraph-sdk](#reactreadmemd) / MessageMetadata + +## Type Alias: MessageMetadata\ + +> **MessageMetadata**\<`StateType`\>: `object` + +Defined in: [react/stream.tsx:169](https://github.com/langchain-ai/langgraph/blob/d4f644877db6264bd46d0b00fc4c37f174e502d5/libs/sdk-js/src/react/stream.tsx#L169) + +### Type Parameters + +• **StateType** *extends* `Record`\<`string`, `unknown`\> + +### Type declaration + +#### branch + +> **branch**: `string` \| `undefined` + +The branch of the message. + +#### branchOptions + +> **branchOptions**: `string`[] \| `undefined` + +The list of branches this message is part of. +This is useful for displaying branching controls. + +#### firstSeenState + +> **firstSeenState**: `ThreadState`\<`StateType`\> \| `undefined` + +The first thread state the message was seen in. + +#### messageId + +> **messageId**: `string` + +The ID of the message used. diff --git a/docs/docs/concepts/agentic_concepts.md b/docs/docs/concepts/agentic_concepts.md index 5c18fce31..0dce56cd9 100644 --- a/docs/docs/concepts/agentic_concepts.md +++ b/docs/docs/concepts/agentic_concepts.md @@ -97,7 +97,7 @@ Parallel processing is vital for efficient multi-agent systems and complex tasks - Implementation of map-reduce-like operations - Efficient handling of independent subtasks -For practical implementation, see our [map-reduce tutorial](../how-tos/graph-api.ipynb#map-reduce-and-the-send-api) +For practical implementation, see our [map-reduce tutorial](../how-tos/graph-api.md#map-reduce-and-the-send-api) ### Subgraphs @@ -107,7 +107,7 @@ For practical implementation, see our [map-reduce tutorial](../how-tos/graph-api - Hierarchical organization of agent teams - Controlled communication between agents and the main system -Subgraphs communicate with the parent graph through overlapping keys in the state schema. This enables flexible, modular agent design. For implementation details, refer to our [subgraph how-to guide](../how-tos/subgraph.ipynb). +Subgraphs communicate with the parent graph through overlapping keys in the state schema. This enables flexible, modular agent design. For implementation details, refer to our [subgraph how-to guide](../how-tos/subgraph.md). ### Reflection diff --git a/docs/docs/concepts/auth.md b/docs/docs/concepts/auth.md index 7788ce37f..204764ed3 100644 --- a/docs/docs/concepts/auth.md +++ b/docs/docs/concepts/auth.md @@ -143,6 +143,54 @@ The returned user information is available: In many of our tutorials, we will just show the "authorization" parameter to be concise, but you can opt to accept more information as needed to implement your custom authentication scheme. +### Agent authentication + +Custom authentication permits delegated access. The values you return in `@auth.authenticate` are added to the run context, giving agents user-scoped credentials lets them access resources on the user’s behalf. + +```mermaid +sequenceDiagram + %% Actors + participant ClientApp as Client + participant AuthProv as Auth Provider + participant LangGraph as LangGraph Backend + participant SecretStore as Secret Store + participant ExternalService as External Service + + %% Platform login / AuthN + ClientApp ->> AuthProv: 1. Login (username / password) + AuthProv -->> ClientApp: 2. Return token + ClientApp ->> LangGraph: 3. Request with token + + Note over LangGraph: 4. Validate token (@auth.authenticate) + LangGraph -->> AuthProv: 5. Fetch user info + AuthProv -->> LangGraph: 6. Confirm validity + + %% Fetch user tokens from secret store + LangGraph ->> SecretStore: 6a. Fetch user tokens + SecretStore -->> LangGraph: 6b. Return tokens + + Note over LangGraph: 7. Apply access control (@auth.on.*) + + %% External Service round-trip + LangGraph ->> ExternalService: 8. Call external service (with header) + Note over ExternalService: 9. External service validates header and executes action + ExternalService -->> LangGraph: 10. Service response + + %% Return to caller + LangGraph -->> ClientApp: 11. Return resources +``` + +After authentication, the platform creates a special configuration object that is passed to your graph and all nodes via the configurable context. +This object contains information about the current user, including any custom fields you return from your [`@auth.authenticate`](../cloud/reference/sdk/python_sdk_ref.md#langgraph_sdk.auth.Auth.authenticate) handler. + +To enable an agent to act on behalf of the user, use [custom authentication middleware](../how-tos/auth/custom_auth.md). This will allow the agent to interact with external systems like MCP servers, external databases, and even other agents on behalf of the user. + +For more information, see the [Use custom auth](../how-tos/auth/custom_auth.md#enable-agent-authentication) guide. + +### Agent authentication with MCP + +For information on how to authenticate an agent to an MCP server, see the [MCP conceptual guide](../concepts/mcp.md). + ## Authorization After authentication, LangGraph calls your [`@auth.on`](../cloud/reference/sdk/python_sdk_ref.md#langgraph_sdk.auth.Auth.on) handlers to control access to specific resources (e.g., threads, assistants, crons). These handlers can: diff --git a/docs/docs/concepts/langgraph_control_plane.md b/docs/docs/concepts/langgraph_control_plane.md index 2e3ecc84d..ebc880ce5 100644 --- a/docs/docs/concepts/langgraph_control_plane.md +++ b/docs/docs/concepts/langgraph_control_plane.md @@ -26,7 +26,7 @@ The Control Plane UI is embedded in [LangSmith](https://docs.smith.langchain.com ## Control Plane API -This section describes data model of the control plane API. The API is used to create, update, and delete deployments. However, they are not publicly accessible. +This section describes the data model of the control plane API. The API is used to create, update, and delete deployments. See the [control plane API reference](../cloud/reference/api/api_ref_control_plane.md) for more details. ### Deployment @@ -34,11 +34,7 @@ A deployment is an instance of a LangGraph Server. A single deployment can have ### Revision -A revision is an iteration of a deployment. When a new deployment is created, an initial revision is automatically created. To deploy code changes or update environment variables for a deployment, a new revision must be created. - -### Environment Variable - -Environment variables are set for a deployment. All environment variables are stored as secrets (i.e. saved in a secrets store). +A revision is an iteration of a deployment. When a new deployment is created, an initial revision is automatically created. To deploy code changes or update secrets for a deployment, a new revision must be created. ## Control Plane Features @@ -50,21 +46,40 @@ For simplicity, the control plane offers two deployment types with different res | **Deployment Type** | **CPU/Memory** | **Scaling** | **Database** | |---------------------|-----------------|---------------------|----------------------------------------------------------------------------------| -| Development | 1 CPU, 1 GB RAM | Up to 1 container | 10 GB disk, no backups | -| Production | 2 CPU, 2 GB RAM | Up to 10 containers | Autoscaling disk, automatic backups, highly available (multi-zone configuration) | +| Development | 1 CPU, 1 GB RAM | Up to 1 replica | 10 GB disk, no backups | +| Production | 2 CPU, 2 GB RAM | Up to 10 replicas | Autoscaling disk, automatic backups, highly available (multi-zone configuration) | -CPU and memory resources are per container. +CPU and memory resources are per replica. !!! warning "Immutable Deployment Type" Once a deployment is created, the deployment type cannot be changed. -!!! info "Resource Customization" - For `Production` type deployments, resources can be manually increased on a case-by-case basis depending on use case and capacity constraints. Contact support@langchain.dev to request an increase in resources. +!!! info "Self-Hosted Deployment" + Resources for [Self-Hosted Data Plane](../concepts/langgraph_self_hosted_data_plane.md) and [Self-Hosted Control Plane](../concepts/langgraph_self_hosted_control_plane.md) deployments can be fully customized. Deployment types are only applicable for [Cloud SaaS](../concepts/langgraph_cloud.md) deployments. - For `Development` types deployments, database disk size can be manually increased on a case-by-case basis depending on use case and capacity constraints. For most use cases, [TTLs](../how-tos/ttl/configure_ttl.md) should be configured to manage disk usage. Contact support@langchain.dev to request an increase in resources. +#### Production - Resources for [Self-Hosted Data Plane](../concepts/langgraph_self_hosted_data_plane.md) and [Self-Hosted Control Plane](../concepts/langgraph_self_hosted_control_plane.md) deployments can be fully customized. +`Production` type deployments are suitable for "production" workloads. For example, select `Production` for customer-facing applications in the critical path. + +Resources for `Production` type deployments can be manually increased on a case-by-case basis depending on use case and capacity constraints. Contact support@langchain.dev to request an increase in resources. + +#### Development + +`Development` type deployments are suitable development and testing. For example, select `Development` for internal testing environments. `Development` type deployments are not suitable for "production" workloads. + +!!! danger "Preemptible Compute Infrastructure" + `Development` type deployments (API server, queue server, and database) are provisioned on preemptible compute infrastructure. This means the compute infrastructure **may be terminated at any time without notice**. This may result in intermittent... + + - Redis connection timeouts/errors + - Postgres connection timeouts/errors + - Failed or retrying background runs + + This behavior is expected. Preemptible compute infrastructure **significantly reduces the cost to provision a `Development` type deployment**. By design, LangGraph Server is fault-tolerant. The implementation will automatically attempt to recover from Redis/Postgres connection errors and retry failed background runs. + + `Production` type deployments are provisioned on durable compute infrastructure, not preemptible compute infrastructure. + +Database disk size for `Development` type deployments can be manually increased on a case-by-case basis depending on use case and capacity constraints. For most use cases, [TTLs](../how-tos/ttl/configure_ttl.md) should be configured to manage disk usage. Contact support@langchain.dev to request an increase in resources. ### Database Provisioning diff --git a/docs/docs/concepts/low_level.md b/docs/docs/concepts/low_level.md index f277b742e..13c0fa0f7 100644 --- a/docs/docs/concepts/low_level.md +++ b/docs/docs/concepts/low_level.md @@ -45,9 +45,9 @@ The first thing you do when you define a graph is define the `State` of the grap ### Schema -The main documented way to specify the schema of a graph is by using `TypedDict`. However, we also support [using a Pydantic BaseModel](../how-tos/graph-api.ipynb#use-pydantic-models-for-graph-state) as your graph state to add **default values** and additional data validation. +The main documented way to specify the schema of a graph is by using `TypedDict`. However, we also support [using a Pydantic BaseModel](../how-tos/graph-api.md#use-pydantic-models-for-graph-state) as your graph state to add **default values** and additional data validation. -By default, the graph will have the same input and output schemas. If you want to change this, you can also specify explicit input and output schemas directly. This is useful when you have a lot of keys, and some are explicitly for input and others for output. See the [guide here](../how-tos/graph-api.ipynb#define-input-and-output-schemas) for how to use. +By default, the graph will have the same input and output schemas. If you want to change this, you can also specify explicit input and output schemas directly. This is useful when you have a lot of keys, and some are explicitly for input and others for output. See the [guide here](../how-tos/graph-api.md#define-input-and-output-schemas) for how to use. #### Multiple schemas @@ -56,9 +56,9 @@ Typically, all graph nodes communicate with a single schema. This means that the - Internal nodes can pass information that is not required in the graph's input / output. - We may also want to use different input / output schemas for the graph. The output might, for example, only contain a single relevant output key. -It is possible to have nodes write to private state channels inside the graph for internal node communication. We can simply define a private schema, `PrivateState`. See [this guide](../how-tos/graph-api.ipynb#pass-private-state-between-nodes) for more detail. +It is possible to have nodes write to private state channels inside the graph for internal node communication. We can simply define a private schema, `PrivateState`. See [this guide](../how-tos/graph-api.md#pass-private-state-between-nodes) for more detail. -It is also possible to define explicit input and output schemas for a graph. In these cases, we define an "internal" schema that contains _all_ keys relevant to graph operations. But, we also define `input` and `output` schemas that are sub-sets of the "internal" schema to constrain the input and output of the graph. See [this guide](../how-tos/graph-api.ipynb#define-input-and-output-schemas) for more detail. +It is also possible to define explicit input and output schemas for a graph. In these cases, we define an "internal" schema that contains _all_ keys relevant to graph operations. But, we also define `input` and `output` schemas that are sub-sets of the "internal" schema to constrain the input and output of the graph. See [this guide](../how-tos/graph-api.md#define-input-and-output-schemas) for more detail. Let's look at an example: @@ -406,7 +406,7 @@ def my_node(state: State) -> Command[Literal["my_other_node"]]: When returning `Command` in your node functions, you must add return type annotations with the list of node names the node is routing to, e.g. `Command[Literal["my_other_node"]]`. This is necessary for the graph rendering and tells LangGraph that `my_node` can navigate to `my_other_node`. -Check out this [how-to guide](../how-tos/graph-api.ipynb#combine-control-flow-and-state-updates-with-command) for an end-to-end example of how to use `Command`. +Check out this [how-to guide](../how-tos/graph-api.md#combine-control-flow-and-state-updates-with-command) for an end-to-end example of how to use `Command`. ### When should I use Command instead of conditional edges? @@ -433,17 +433,17 @@ def my_node(state: State) -> Command[Literal["other_subgraph"]]: !!! important "State updates with `Command.PARENT`" - When you send updates from a subgraph node to a parent graph node for a key that's shared by both parent and subgraph [state schemas](#schema), you **must** define a [reducer](#reducers) for the key you're updating in the parent graph state. See this [example](../how-tos/graph-api.ipynb#navigate-to-a-node-in-a-parent-graph). + When you send updates from a subgraph node to a parent graph node for a key that's shared by both parent and subgraph [state schemas](#schema), you **must** define a [reducer](#reducers) for the key you're updating in the parent graph state. See this [example](../how-tos/graph-api.md#navigate-to-a-node-in-a-parent-graph). This is particularly useful when implementing [multi-agent handoffs](./multi_agent.md#handoffs). -Check out [this guide](../how-tos/graph-api.ipynb#navigate-to-a-node-in-a-parent-graph) for detail. +Check out [this guide](../how-tos/graph-api.md#navigate-to-a-node-in-a-parent-graph) for detail. ### Using inside tools A common use case is updating graph state from inside a tool. For example, in a customer support application you might want to look up customer information based on their account number or ID in the beginning of the conversation. -Refer to [this guide](../how-tos/graph-api.ipynb#use-inside-tools) for detail. +Refer to [this guide](../how-tos/graph-api.md#use-inside-tools) for detail. ### Human-in-the-loop @@ -489,7 +489,7 @@ def node_a(state, config): ... ``` -See [this guide](../how-tos/graph-api.ipynb#add-runtime-configuration) for a full breakdown on configuration. +See [this guide](../how-tos/graph-api.md#add-runtime-configuration) for a full breakdown on configuration. ### Recursion Limit @@ -503,4 +503,4 @@ Read [this how-to](https://langchain-ai.github.io/langgraph/how-tos/recursion-li ## Visualization -It's often nice to be able to visualize graphs, especially as they get more complex. LangGraph comes with several built-in ways to visualize graphs. See [this how-to guide](../how-tos/graph-api.ipynb#visualize-your-graph) for more info. +It's often nice to be able to visualize graphs, especially as they get more complex. LangGraph comes with several built-in ways to visualize graphs. See [this how-to guide](../how-tos/graph-api.md#visualize-your-graph) for more info. diff --git a/docs/docs/concepts/mcp.md b/docs/docs/concepts/mcp.md new file mode 100644 index 000000000..4b05d008e --- /dev/null +++ b/docs/docs/concepts/mcp.md @@ -0,0 +1,57 @@ +# MCP + +[Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) is an open protocol that standardizes how applications provide tools and context to language models. LangGraph agents can use tools defined on MCP servers through the `langchain-mcp-adapters` library. + +![MCP](../agents/assets/mcp.png) + +Install the `langchain-mcp-adapters` library to use MCP tools in LangGraph: + +```bash +pip install langchain-mcp-adapters +``` + +## Authenticate to an MCP server + +You can set up [custom authentication middleware](../how-tos/auth/custom_auth.md) to authenticate a user with an MCP server to get access to user-scoped tools within your LangGraph Platform deployment. + +!!! note + Custom authentication is a LangGraph Platform feature. + +An example architecture for this flow: + +```mermaid +sequenceDiagram + %% Actors + participant ClientApp as Client + participant AuthProv as Auth Provider + participant LangGraph as LangGraph Backend + participant SecretStore as Secret Store + participant MCPServer as MCP Server + + %% Platform login / AuthN + ClientApp ->> AuthProv: 1. Login (username / password) + AuthProv -->> ClientApp: 2. Return token + ClientApp ->> LangGraph: 3. Request with token + + Note over LangGraph: 4. Validate token (@auth.authenticate) + LangGraph -->> AuthProv: 5. Fetch user info + AuthProv -->> LangGraph: 6. Confirm validity + + %% Fetch user tokens from secret store + LangGraph ->> SecretStore: 6a. Fetch user tokens + SecretStore -->> LangGraph: 6b. Return tokens + + Note over LangGraph: 7. Apply access control (@auth.on.*) + + %% MCP round-trip + Note over LangGraph: 8. Build MCP client with user token + LangGraph ->> MCPServer: 9. Call MCP tool (with header) + Note over MCPServer: 10. MCP validates header and runs tool + MCPServer -->> LangGraph: 11. Tool response + + %% Return to caller + LangGraph -->> ClientApp: 12. Return resources / tool output +``` + +For more information, see [MCP endpoint in LangGraph Server](../concepts/server-mcp.md#use-user-scoped-mcp-tools-in-your-deployment). + diff --git a/docs/docs/concepts/multi_agent.md b/docs/docs/concepts/multi_agent.md index 0cd4e7f61..81967f610 100644 --- a/docs/docs/concepts/multi_agent.md +++ b/docs/docs/concepts/multi_agent.md @@ -166,7 +166,7 @@ network = builder.compile() ### Supervisor -In this architecture, we define agents as nodes and add a supervisor node (LLM) that decides which agent nodes should be called next. We use [`Command`](./low_level.md#command) to route execution to the appropriate agent node based on supervisor's decision. This architecture also lends itself well to running multiple agents in parallel or using [map-reduce](../how-tos/graph-api.ipynb#map-reduce-and-the-send-api) pattern. +In this architecture, we define agents as nodes and add a supervisor node (LLM) that decides which agent nodes should be called next. We use [`Command`](./low_level.md#command) to route execution to the appropriate agent node based on supervisor's decision. This architecture also lends itself well to running multiple agents in parallel or using [map-reduce](../how-tos/graph-api.md#map-reduce-and-the-send-api) pattern. ```python from typing import Literal @@ -414,5 +414,5 @@ There are two high-level approaches to achieve that: An agent might need to have a different state schema from the rest of the agents. For example, a search agent might only need to keep track of queries and retrieved documents. There are two ways to achieve this in LangGraph: -- Define [subgraph](./subgraphs.md) agents with a separate state schema. If there are no shared state keys (channels) between the subgraph and the parent graph, it’s important to [add input / output transformations](../how-tos/subgraph.ipynb#different-state-schemas) so that the parent graph knows how to communicate with the subgraphs. -- Define agent node functions with a [private input state schema](../how-tos/graph-api.ipynb/#pass-private-state-between-nodes) that is distinct from the overall graph state schema. This allows passing information that is only needed for executing that particular agent. +- Define [subgraph](./subgraphs.md) agents with a separate state schema. If there are no shared state keys (channels) between the subgraph and the parent graph, it’s important to [add input / output transformations](../how-tos/subgraph.md#different-state-schemas) so that the parent graph knows how to communicate with the subgraphs. +- Define agent node functions with a [private input state schema](../how-tos/graph-api.md/#pass-private-state-between-nodes) that is distinct from the overall graph state schema. This allows passing information that is only needed for executing that particular agent. diff --git a/docs/docs/concepts/server-mcp.md b/docs/docs/concepts/server-mcp.md index 7f144e87f..0d40bfb2e 100644 --- a/docs/docs/concepts/server-mcp.md +++ b/docs/docs/concepts/server-mcp.md @@ -8,8 +8,7 @@ hide: # MCP endpoint in LangGraph Server -The **Model Context Protocol (MCP)** is an open protocol for describing tools and data sources in a model-agnostic format, enabling LLMs to discover -and use them via a structured API. +The [Model Context Protocol (MCP)](./mcp.md) is an open protocol for describing tools and data sources in a model-agnostic format, enabling LLMs to discover and use them via a structured API. [LangGraph Server](./langgraph_server.md) implements MCP using the [Streamable HTTP transport](https://spec.modelcontextprotocol.io/specification/2025-03-26/basic/transports/#streamable-http). This allows LangGraph **agents** to be exposed as **MCP tools**, making them usable with any MCP-compliant client supporting Streamable HTTP. @@ -28,79 +27,6 @@ Install them with: pip install "langgraph-api>=0.2.3" "langgraph-sdk>=0.1.61" ``` -## Exposing an agent as MCP tool - - -When deployed, your agent will appear as a tool in the MCP endpoint -with this configuration: - -- **Tool name**: The agent's name. -- **Tool description**: The agent's description. -- **Tool input schema**: The agent's input schema. - -### Setting name and description - -You can set the name and description of your agent in `langgraph.json`: - -```json -{ - "graphs": { - "my_agent": { - "path": "./my_agent/agent.py:graph", - "description": "A description of what the agent does" - } - }, - "env": ".env" -} -``` - -After deployment, you can update the name and description using the LangGraph SDK. - -### Schema - -Define clear, minimal input and output schemas to avoid exposing unnecessary internal complexity to the LLM. - -The default [MessagesState](./low_level.md#messagesstate) uses `AnyMessage`, which supports many message types but is too general for direct LLM exposure. - -Instead, define **custom agents or workflows** that use explicitly typed input and output structures. - -For example, a workflow answering documentation questions might look like this: - -```python -from langgraph.graph import StateGraph, START, END -from typing_extensions import TypedDict - -# Define input schema -class InputState(TypedDict): - question: str - -# Define output schema -class OutputState(TypedDict): - answer: str - -# Combine input and output -class OverallState(InputState, OutputState): - pass - -# Define the processing node -def answer_node(state: InputState): - # Replace with actual logic and do something useful - return {"answer": "bye", "question": state["question"]} - -# Build the graph with explicit schemas -builder = StateGraph(OverallState, input_schema=InputState, output_schema=OutputState) -builder.add_node(answer_node) -builder.add_edge(START, "answer_node") -builder.add_edge("answer_node", END) -graph = builder.compile() - -# Run the graph -print(graph.invoke({"question": "hi"})) -``` - -For more details, see the [low-level concepts guide](https://langchain-ai.github.io/langgraph/concepts/low_level/#state). - - ## Usage overview To enable MCP: @@ -201,6 +127,109 @@ Use an MCP-compliant client to connect to the LangGraph server. The following ex asyncio.run(main()) ``` +## Expose an agent as MCP tool + +When deployed, your agent will appear as a tool in the MCP endpoint +with this configuration: + +- **Tool name**: The agent's name. +- **Tool description**: The agent's description. +- **Tool input schema**: The agent's input schema. + +### Setting name and description + +You can set the name and description of your agent in `langgraph.json`: + +```json +{ + "graphs": { + "my_agent": { + "path": "./my_agent/agent.py:graph", + "description": "A description of what the agent does" + } + }, + "env": ".env" +} +``` + +After deployment, you can update the name and description using the LangGraph SDK. + +### Schema + +Define clear, minimal input and output schemas to avoid exposing unnecessary internal complexity to the LLM. + +The default [MessagesState](./low_level.md#messagesstate) uses `AnyMessage`, which supports many message types but is too general for direct LLM exposure. + +Instead, define **custom agents or workflows** that use explicitly typed input and output structures. + +For example, a workflow answering documentation questions might look like this: + +```python +from langgraph.graph import StateGraph, START, END +from typing_extensions import TypedDict + +# Define input schema +class InputState(TypedDict): + question: str + +# Define output schema +class OutputState(TypedDict): + answer: str + +# Combine input and output +class OverallState(InputState, OutputState): + pass + +# Define the processing node +def answer_node(state: InputState): + # Replace with actual logic and do something useful + return {"answer": "bye", "question": state["question"]} + +# Build the graph with explicit schemas +builder = StateGraph(OverallState, input_schema=InputState, output_schema=OutputState) +builder.add_node(answer_node) +builder.add_edge(START, "answer_node") +builder.add_edge("answer_node", END) +graph = builder.compile() + +# Run the graph +print(graph.invoke({"question": "hi"})) +``` + +For more details, see the [low-level concepts guide](https://langchain-ai.github.io/langgraph/concepts/low_level/#state). + +## Use user-scoped MCP tools in your deployment + +!!! tip "Prerequisites" + + You have added your own [custom auth middleware](https://langchain-ai.github.io/langgraph/how-tos/auth/custom_auth/) that populates the `langgraph_auth_user` object, making it accessible through configurable context for every node in your graph. + +To make user-scoped tools available to your LangGraph Platform deployment, start with implementing a snippet like the following: + +```python +from langchain_mcp_adapters.client import MultiServerMCPClient + +def get_mcp_tools_node(state, config): + user = config["configurable"].get("langgraph_auth_user") + # e.g., user["github_token"], user["email"], etc. + + client = MultiServerMCPClient({ + "github": { + "transport": "streamable_http", # (1) + "url": "https://my-github-mcp-server/mcp", # (2) + "headers": { + "Authorization": f"Bearer {user['github_token']}" + } + } + }) + tools = await client.get_tools() # (3) + return {"tools": tools} + +``` + +1. MCP only supports adding headers to requests made to `streamable_http` and `sse` `transport` servers. +2. Your MCP server URL. +3. Get available tools from your MCP server. ## Session behavior @@ -210,7 +239,7 @@ The current LangGraph MCP implementation does not support sessions. Each `/mcp` The `/mcp` endpoint uses the same authentication as the rest of the LangGraph API. Refer to the [authentication guide](./auth.md) for setup details. -## Disabling MCP +## Disable MCP To disable the MCP endpoint, set `disable_mcp` to `true` in your `langgraph.json` configuration file: @@ -222,4 +251,4 @@ To disable the MCP endpoint, set `disable_mcp` to `true` in your `langgraph.json } ``` -This will prevent the server from exposing the `/mcp` endpoint. \ No newline at end of file +This will prevent the server from exposing the `/mcp` endpoint. diff --git a/docs/docs/concepts/subgraphs.md b/docs/docs/concepts/subgraphs.md index 6a4aefb23..218bf8cac 100644 --- a/docs/docs/concepts/subgraphs.md +++ b/docs/docs/concepts/subgraphs.md @@ -12,7 +12,7 @@ Some reasons for using subgraphs are: The main question when adding subgraphs is how the parent graph and subgraph communicate, i.e. how they pass the [state](./low_level.md#state) between each other during the graph execution. There are two scenarios: -* parent and subgraph have **shared state keys** in their state [schemas](./low_level.md#state). In this case, you can [include the subgraph as a node in the parent graph](../how-tos/subgraph.ipynb#shared-state-schemas) +* parent and subgraph have **shared state keys** in their state [schemas](./low_level.md#state). In this case, you can [include the subgraph as a node in the parent graph](../how-tos/subgraph.md#shared-state-schemas) ```python from langgraph.graph import StateGraph, MessagesState, START @@ -40,7 +40,7 @@ The main question when adding subgraphs is how the parent graph and subgraph com graph.invoke({"messages": [{"role": "user", "content": "hi!"}]}) ``` -* parent graph and subgraph have **different schemas** (no shared state keys in their state [schemas](./low_level.md#state)). In this case, you have to [call the subgraph from inside a node in the parent graph](../how-tos/subgraph.ipynb#different-state-schemas): this is useful when the parent graph and the subgraph have different state schemas and you need to transform state before or after calling the subgraph +* parent graph and subgraph have **different schemas** (no shared state keys in their state [schemas](./low_level.md#state)). In this case, you have to [call the subgraph from inside a node in the parent graph](../how-tos/subgraph.md#different-state-schemas): this is useful when the parent graph and the subgraph have different state schemas and you need to transform state before or after calling the subgraph ```python from typing_extensions import TypedDict, Annotated diff --git a/docs/docs/how-tos/assets/graph_api_image_1.png b/docs/docs/how-tos/assets/graph_api_image_1.png new file mode 100644 index 000000000..c1ac60da9 Binary files /dev/null and b/docs/docs/how-tos/assets/graph_api_image_1.png differ diff --git a/docs/docs/how-tos/assets/graph_api_image_10.png b/docs/docs/how-tos/assets/graph_api_image_10.png new file mode 100644 index 000000000..18ea05fa8 Binary files /dev/null and b/docs/docs/how-tos/assets/graph_api_image_10.png differ diff --git a/docs/docs/how-tos/assets/graph_api_image_2.png b/docs/docs/how-tos/assets/graph_api_image_2.png new file mode 100644 index 000000000..4f890a3dd Binary files /dev/null and b/docs/docs/how-tos/assets/graph_api_image_2.png differ diff --git a/docs/docs/how-tos/assets/graph_api_image_3.png b/docs/docs/how-tos/assets/graph_api_image_3.png new file mode 100644 index 000000000..7cd869d09 Binary files /dev/null and b/docs/docs/how-tos/assets/graph_api_image_3.png differ diff --git a/docs/docs/how-tos/assets/graph_api_image_4.png b/docs/docs/how-tos/assets/graph_api_image_4.png new file mode 100644 index 000000000..09bb71be2 Binary files /dev/null and b/docs/docs/how-tos/assets/graph_api_image_4.png differ diff --git a/docs/docs/how-tos/assets/graph_api_image_5.png b/docs/docs/how-tos/assets/graph_api_image_5.png new file mode 100644 index 000000000..c1ebb138c Binary files /dev/null and b/docs/docs/how-tos/assets/graph_api_image_5.png differ diff --git a/docs/docs/how-tos/assets/graph_api_image_6.png b/docs/docs/how-tos/assets/graph_api_image_6.png new file mode 100644 index 000000000..3d60cbfb9 Binary files /dev/null and b/docs/docs/how-tos/assets/graph_api_image_6.png differ diff --git a/docs/docs/how-tos/assets/graph_api_image_7.png b/docs/docs/how-tos/assets/graph_api_image_7.png new file mode 100644 index 000000000..d607bdc4a Binary files /dev/null and b/docs/docs/how-tos/assets/graph_api_image_7.png differ diff --git a/docs/docs/how-tos/assets/graph_api_image_8.png b/docs/docs/how-tos/assets/graph_api_image_8.png new file mode 100644 index 000000000..67049fb59 Binary files /dev/null and b/docs/docs/how-tos/assets/graph_api_image_8.png differ diff --git a/docs/docs/how-tos/assets/graph_api_image_9.png b/docs/docs/how-tos/assets/graph_api_image_9.png new file mode 100644 index 000000000..2eb23cc16 Binary files /dev/null and b/docs/docs/how-tos/assets/graph_api_image_9.png differ diff --git a/docs/docs/how-tos/auth/custom_auth.md b/docs/docs/how-tos/auth/custom_auth.md index 64f95e1ef..03df45780 100644 --- a/docs/docs/how-tos/auth/custom_auth.md +++ b/docs/docs/how-tos/auth/custom_auth.md @@ -1,138 +1,147 @@ # Add custom authentication -!!! tip "Prerequisites" - - This guide assumes familiarity with the following concepts: - - * [**Authentication & Access Control**](../../concepts/auth.md) - * [**LangGraph Platform**](../../concepts/langgraph_platform.md) - - For a more guided walkthrough, see [**setting up custom authentication**](../../tutorials/auth/getting_started.md) tutorial. - -???+ note "Support by deployment type" - - Custom auth is supported for all deployments in the **managed LangGraph Platform**, as well as **Enterprise** self-hosted plans. It is not supported for **Lite** self-hosted plans. - This guide shows how to add custom authentication to your LangGraph Platform application. This guide applies to both LangGraph Platform and self-hosted deployments. It does not apply to isolated usage of the LangGraph open source library in your own custom server. -## 1. Implement authentication +!!! note + + Custom auth is supported for all **managed LangGraph Platform** deployments, as well as **Enterprise** self-hosted plans. It is not supported for **Lite** self-hosted plans. + +## Add custom authentication to your deployment + +To leverage custom authentication and access user-level metadata in your deployments, set up custom authentication to automatically populate the `config["configurable"]["langgraph_auth_user"]` object through a custom authentication handler. You can then access this object in your graph with the `langgraph_auth_user` key to [allow an agent to perform authenticated actions on behalf of the user](#enable-agent-authentication). + +1. Implement authentication: + + !!! note + + Without a custom `@auth.authenticate` handler, LangGraph sees only the API-key owner (usually the developer), so requests aren’t scoped to individual end-users. To propagate custom tokens, you must implement your own handler. + + ```python + from langgraph_sdk import Auth + import requests + + auth = Auth() + + def is_valid_key(api_key: str) -> bool: + is_valid = # your API key validation logic + return is_valid + + @auth.authenticate # (1)! + async def authenticate(headers: dict) -> Auth.types.MinimalUserDict: + api_key = headers.get("x-api-key") + if not api_key or not is_valid_key(api_key): + raise Auth.exceptions.HTTPException(status_code=401, detail="Invalid API key") + + # Fetch user-specific tokens from your secret store + user_tokens = await fetch_user_tokens(api_key) + + return { # (2)! + "identity": api_key, # fetch user ID from LangSmith + "github_token" : user_tokens.github_token + "jira_token" : user_tokens.jira_token + # ... custom fields/secrets here + } + ``` + + 1. This handler receives the request (headers, etc.), validates the user, and returns a dictionary with at least an identity field. + 2. You can add any custom fields you want (e.g., OAuth tokens, roles, org IDs, etc.). + +2. In your `langgraph.json`, add the path to your auth file: + + ```json hl_lines="7-9" + { + "dependencies": ["."], + "graphs": { + "agent": "./agent.py:graph" + }, + "env": ".env", + "auth": { + "path": "./auth.py:my_auth" + } + } + ``` + +3. Once you've set up authentication in your server, requests must include the required authorization information based on your chosen scheme. Assuming you are using JWT token authentication, you could access your deployments using any of the following methods: + + === "Python Client" + + ```python + from langgraph_sdk import get_client + + my_token = "your-token" # In practice, you would generate a signed token with your auth provider + client = get_client( + url="http://localhost:2024", + headers={"Authorization": f"Bearer {my_token}"} + ) + threads = await client.threads.search() + ``` + + === "Python RemoteGraph" + + ```python + from langgraph.pregel.remote import RemoteGraph + + my_token = "your-token" # In practice, you would generate a signed token with your auth provider + remote_graph = RemoteGraph( + "agent", + url="http://localhost:2024", + headers={"Authorization": f"Bearer {my_token}"} + ) + threads = await remote_graph.ainvoke(...) + ``` + + === "JavaScript Client" + + ```javascript + import { Client } from "@langchain/langgraph-sdk"; + + const my_token = "your-token"; // In practice, you would generate a signed token with your auth provider + const client = new Client({ + apiUrl: "http://localhost:2024", + defaultHeaders: { Authorization: `Bearer ${my_token}` }, + }); + const threads = await client.threads.search(); + ``` + + === "JavaScript RemoteGraph" + + ```javascript + import { RemoteGraph } from "@langchain/langgraph/remote"; + + const my_token = "your-token"; // In practice, you would generate a signed token with your auth provider + const remoteGraph = new RemoteGraph({ + graphId: "agent", + url: "http://localhost:2024", + headers: { Authorization: `Bearer ${my_token}` }, + }); + const threads = await remoteGraph.invoke(...); + ``` + + === "CURL" + + ```bash + curl -H "Authorization: Bearer ${your-token}" http://localhost:2024/threads + ``` + +## Enable agent authentication + +After [authentication](#add-custom-authentication-to-your-deployment), the platform creates a special configuration object (`config`) that is passed to LangGraph Platform deployment. This object contains information about the current user, including any custom fields you return from your `@auth.authenticate` handler. + +To allow an agent to perform authenticated actions on behalf of the user, access this object in your graph with the `langgraph_auth_user` key: ```python -from langgraph_sdk import Auth - -my_auth = Auth() - -@my_auth.authenticate -async def authenticate(authorization: str) -> str: - token = authorization.split(" ", 1)[-1] # "Bearer " - try: - # Verify token with your auth provider - user_id = await verify_token(token) - return user_id - except Exception: - raise Auth.exceptions.HTTPException( - status_code=401, - detail="Invalid token" - ) - -# Add authorization rules to actually control access to resources -@my_auth.on -async def add_owner( - ctx: Auth.types.AuthContext, - value: dict, -): - """Add owner to resource metadata and filter by owner.""" - filters = {"owner": ctx.user.identity} - metadata = value.setdefault("metadata", {}) - metadata.update(filters) - return filters - -# Assumes you organize information in store like (user_id, resource_type, resource_id) -@my_auth.on.store() -async def authorize_store(ctx: Auth.types.AuthContext, value: dict): - namespace: tuple = value["namespace"] - assert namespace[0] == ctx.user.identity, "Not authorized" - +def my_node(state, config): + user_config = config["configurable"].get("langgraph_auth_user") + # token was resolved during the @auth.authenticate function + token = user_config.get("github_token","") + ... ``` -## 2. Update configuration +!!! note + Fetch user credentials from a secure secret store. Storing secrets in graph state is not recommended. -In your `langgraph.json`, add the path to your auth file: +## Learn more -```json hl_lines="7-9" -{ - "dependencies": ["."], - "graphs": { - "agent": "./agent.py:graph" - }, - "env": ".env", - "auth": { - "path": "./auth.py:my_auth" - } -} -``` - -## 3. Connect from the client - -Once you've set up authentication in your server, requests must include the required authorization information based on your chosen scheme. -Assuming you are using JWT token authentication, you could access your deployments using any of the following methods: - -=== "Python Client" - - ```python - from langgraph_sdk import get_client - - my_token = "your-token" # In practice, you would generate a signed token with your auth provider - client = get_client( - url="http://localhost:2024", - headers={"Authorization": f"Bearer {my_token}"} - ) - threads = await client.threads.search() - ``` - -=== "Python RemoteGraph" - - ```python - from langgraph.pregel.remote import RemoteGraph - - my_token = "your-token" # In practice, you would generate a signed token with your auth provider - remote_graph = RemoteGraph( - "agent", - url="http://localhost:2024", - headers={"Authorization": f"Bearer {my_token}"} - ) - threads = await remote_graph.ainvoke(...) - ``` - -=== "JavaScript Client" - - ```javascript - import { Client } from "@langchain/langgraph-sdk"; - - const my_token = "your-token"; // In practice, you would generate a signed token with your auth provider - const client = new Client({ - apiUrl: "http://localhost:2024", - defaultHeaders: { Authorization: `Bearer ${my_token}` }, - }); - const threads = await client.threads.search(); - ``` - -=== "JavaScript RemoteGraph" - - ```javascript - import { RemoteGraph } from "@langchain/langgraph/remote"; - - const my_token = "your-token"; // In practice, you would generate a signed token with your auth provider - const remoteGraph = new RemoteGraph({ - graphId: "agent", - url: "http://localhost:2024", - headers: { Authorization: `Bearer ${my_token}` }, - }); - const threads = await remoteGraph.invoke(...); - ``` - -=== "CURL" - - ```bash - curl -H "Authorization: Bearer ${your-token}" http://localhost:2024/threads - ``` +* [Authentication & Access Control](../../concepts/auth.md) +* [LangGraph Platform](../../concepts/langgraph_platform.md) +* [Setting up custom authentication tutorial](../../tutorials/auth/getting_started.md) diff --git a/docs/docs/how-tos/graph-api.ipynb b/docs/docs/how-tos/graph-api.ipynb deleted file mode 100644 index 9d890beae..000000000 --- a/docs/docs/how-tos/graph-api.ipynb +++ /dev/null @@ -1,3438 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "9c19faa1-795c-451e-95e4-7aa40a19aa20", - "metadata": {}, - "source": [ - "# How to use the graph API\n", - "\n", - "This guide demonstrates the basics of LangGraph's Graph API. It walks through [state](#define-and-update-state), as well as composing common graph structures such as [sequences](#create-a-sequence-of-steps), [branches](#create-branches), and [loops](#create-and-control-loops). It also covers LangGraph's control features, including the [Send API](#map-reduce-and-the-send-api) for map-reduce workflows and the [Command API](#combine-control-flow-and-state-updates-with-command) for combining state updates with \"hops\" across nodes." - ] - }, - { - "cell_type": "markdown", - "id": "f6fcda61-9c21-43de-af0d-0d9efb063c40", - "metadata": {}, - "source": [ - "## Setup\n", - "\n", - "Install `langgraph`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f031bc56-26f5-4ece-b27e-3c87b3b34f0a", - "metadata": {}, - "outputs": [], - "source": [ - "%pip install -qU langgraph" - ] - }, - { - "cell_type": "markdown", - "id": "55c22136-74cc-495a-94ab-82ccac247cef", - "metadata": {}, - "source": [ - "
\n", - "

Set up LangSmith for better debugging

\n", - "

\n", - " Sign up for LangSmith to quickly spot issues and improve the performance of your LangGraph projects. LangSmith lets you use trace data to debug, test, and monitor your LLM aps built with LangGraph — read more about how to get started in the docs. \n", - "

\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "b462f26d-8795-4dc2-9420-722d3e21656c", - "metadata": {}, - "source": [ - "## Define and update state\n", - "\n", - "Here we show how to define and update [state](../../concepts/low_level/#state) in LangGraph. We will demonstrate:\n", - "\n", - "1. How to use state to define a graph's [schema](../../concepts/low_level/#schema)\n", - "2. How to use [reducers](../../concepts/low_level/#reducers) to control how state updates are processed." - ] - }, - { - "cell_type": "markdown", - "id": "ca7ac66a-a3ae-43c6-bb9d-7ee2bd0030f0", - "metadata": {}, - "source": [ - "### Define state\n", - "\n", - "[State](../../concepts/low_level/#state) in LangGraph can be a `TypedDict`, `Pydantic` model, or dataclass. Below we will use `TypedDict`. See [this section](#use-pydantic-models-for-graph-state) for detail on using Pydantic.\n", - "\n", - "By default, graphs will have the same input and output schema, and the state determines that schema. See [this section](#define-input-and-output-schemas) for how to define distinct input and output schemas.\n", - "\n", - "Let's consider a simple example using [messages](../../concepts/low_level/#messagesstate). This represents a versatile formulation of state for many LLM applications. See our [concepts page](../../concepts/low_level/#working-with-messages-in-graph-state) for more detail." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "e7c3b392-50fb-4af3-bf2d-7b769f47efc6", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_core.messages import AnyMessage\n", - "from typing_extensions import TypedDict\n", - "\n", - "\n", - "class State(TypedDict):\n", - " messages: list[AnyMessage]\n", - " extra_field: int" - ] - }, - { - "cell_type": "markdown", - "id": "c3555791-9dc9-4593-923e-9aa599d4c547", - "metadata": {}, - "source": [ - "This state tracks a list of [message](https://python.langchain.com/docs/concepts/messages/) objects, as well as an extra integer field.\n", - "\n", - "### Update state\n", - "\n", - "Let's build an example graph with a single node. Our [node](../../concepts/low_level/#nodes) is just a Python function that reads our graph's state and makes updates to it. The first argument to this function will always be the state:" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "f5db493b-c977-4f15-a06f-27b460cd7e4c", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_core.messages import AIMessage\n", - "\n", - "\n", - "def node(state: State):\n", - " messages = state[\"messages\"]\n", - " new_message = AIMessage(\"Hello!\")\n", - "\n", - " return {\"messages\": messages + [new_message], \"extra_field\": 10}" - ] - }, - { - "cell_type": "markdown", - "id": "9f6cef5d-2635-45bc-a415-b422bb571685", - "metadata": {}, - "source": [ - "This node simply appends a message to our message list, and populates an extra field.\n", - "\n", - "!!! important\n", - "\n", - " Nodes should return updates to the state directly, instead of mutating the state.\n", - "\n", - "Let's next define a simple graph containing this node. We use [StateGraph](../../concepts/low_level/#stategraph) to define a graph that operates on this state. We then use [add_node](../../concepts/low_level/#nodes) populate our graph." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "92402ca2-9e46-4ad9-8378-83f98f597c00", - "metadata": {}, - "outputs": [], - "source": [ - "from langgraph.graph import StateGraph\n", - "\n", - "builder = StateGraph(State)\n", - "builder.add_node(node)\n", - "builder.set_entry_point(\"node\")\n", - "graph = builder.compile()" - ] - }, - { - "cell_type": "markdown", - "id": "f765d37d-3793-4ac9-90e5-fe28c6142202", - "metadata": {}, - "source": [ - "LangGraph provides built-in utilities for visualizing your graph. Let's inspect our graph. See [this section](#visualize-your-graph) for detail on visualization." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "263470d0-a9fa-48bc-86b1-c5a28b242aec", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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rKVM2z9OOfOAYYblukaWwH3wyhi+Ixnz220AP2tFmSs4S8yWIQDpP38fCLC6Hxe60uCrqk/NKYjXnyMc8zcDs67R+24liVlKiEnL4HJgHc3gQzKXpKukFboIicZIkKMKOT0865CpuSYWkaBX9s2RmM6/vNGFWcvQyNjmG+z6OzOFCdjrmYIgVXLeLEklhqQJWZvFyi4V8ZP7uYEx8K2xhwdy5/AuFhMFoSRiMloTBaEkYjJaEwWj5G9cmpR4/Ig13AAAAAElFTkSuQmCC", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from IPython.display import Image, display\n", - "\n", - "display(Image(graph.get_graph().draw_mermaid_png()))" - ] - }, - { - "cell_type": "markdown", - "id": "ca3cd1a1-38b1-4cbb-9301-5aec62659e70", - "metadata": {}, - "source": [ - "In this case, our graph just executes a single node. Let's proceed with a simple invocation:" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "7d932703-932f-48cb-842c-c372f82510f9", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'messages': [HumanMessage(content='Hi', additional_kwargs={}, response_metadata={}),\n", - " AIMessage(content='Hello!', additional_kwargs={}, response_metadata={})],\n", - " 'extra_field': 10}" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from langchain_core.messages import HumanMessage\n", - "\n", - "result = graph.invoke({\"messages\": [HumanMessage(\"Hi\")]})\n", - "result" - ] - }, - { - "cell_type": "markdown", - "id": "e5918e84-49ac-4ab1-80bb-863a2e5461e2", - "metadata": {}, - "source": [ - "Note that:\n", - "\n", - "- We kicked off invocation by updating a single key of the state.\n", - "- We receive the entire state in the invocation result.\n", - "\n", - "For convenience, we frequently inspect the content of [message objects](https://python.langchain.com/docs/concepts/messages/) via pretty-print:" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "5009dbb2-77c3-47de-9d9d-3fc6e5b649b9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "Hi\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Hello!\n" - ] - } - ], - "source": [ - "for message in result[\"messages\"]:\n", - " message.pretty_print()" - ] - }, - { - "cell_type": "markdown", - "id": "4c4da6ff-a677-41bf-b51e-f2826fc51926", - "metadata": {}, - "source": [ - "### Process state updates with reducers\n", - "\n", - "Each key in the state can have its own independent [reducer](../../concepts/low_level/#reducers) function, which controls how updates from nodes are applied. If no reducer function is explicitly specified then it is assumed that all updates to the key should override it.\n", - "\n", - "For `TypedDict` state schemas, we can define reducers by annotating the corresponding field of the state with a reducer function.\n", - "\n", - "In the earlier example, our node updated the `\"messages\"` key in the state by appending a message to it. Below, we add a reducer to this key, such that updates are automatically appended:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "35db8bfc-8747-423f-858a-b4f069d6199f", - "metadata": {}, - "outputs": [], - "source": [ - "from typing_extensions import Annotated\n", - "\n", - "\n", - "def add(left, right):\n", - " \"\"\"Can also import `add` from the `operator` built-in.\"\"\"\n", - " return left + right\n", - "\n", - "\n", - "class State(TypedDict):\n", - " # highlight-next-line\n", - " messages: Annotated[list[AnyMessage], add]\n", - " extra_field: int" - ] - }, - { - "cell_type": "markdown", - "id": "4979a906-fff3-48de-9215-8a12b9bc4acf", - "metadata": {}, - "source": [ - "Now our node can be simplified:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "f24f8d3f-973f-468e-8895-8c4cf01951dd", - "metadata": {}, - "outputs": [], - "source": [ - "def node(state: State):\n", - " new_message = AIMessage(\"Hello!\")\n", - " # highlight-next-line\n", - " return {\"messages\": [new_message], \"extra_field\": 10}" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "6ef429ed-a0fa-4c00-a88c-bb61df59f578", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "Hi\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Hello!\n" - ] - } - ], - "source": [ - "from langgraph.graph import START\n", - "\n", - "\n", - "graph = StateGraph(State).add_node(node).add_edge(START, \"node\").compile()\n", - "\n", - "result = graph.invoke({\"messages\": [HumanMessage(\"Hi\")]})\n", - "\n", - "for message in result[\"messages\"]:\n", - " message.pretty_print()" - ] - }, - { - "cell_type": "markdown", - "id": "7827723b-64aa-4d8b-b17a-5a3bcd8206f7", - "metadata": {}, - "source": [ - "#### MessagesState\n", - "\n", - "In practice, there are additional considerations for updating lists of messages:\n", - "\n", - "- We may wish to update an existing message in the state.\n", - "- We may want to accept short-hands for [message formats](../../concepts/low_level/#using-messages-in-your-graph), such as [OpenAI format](https://python.langchain.com/docs/concepts/messages/#openai-format).\n", - "\n", - "LangGraph includes a built-in reducer `add_messages` that handles these considerations:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "89880b92-5d00-421f-83c3-46382c1d1c17", - "metadata": {}, - "outputs": [], - "source": [ - "from langgraph.graph.message import add_messages\n", - "\n", - "\n", - "class State(TypedDict):\n", - " # highlight-next-line\n", - " messages: Annotated[list[AnyMessage], add_messages]\n", - " extra_field: int\n", - "\n", - "\n", - "def node(state: State):\n", - " new_message = AIMessage(\"Hello!\")\n", - " return {\"messages\": [new_message], \"extra_field\": 10}\n", - "\n", - "\n", - "graph = StateGraph(State).add_node(node).set_entry_point(\"node\").compile()" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "51aeb731-e7f0-4d28-a096-436ef7fe004a", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "Hi\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Hello!\n" - ] - } - ], - "source": [ - "# highlight-next-line\n", - "input_message = {\"role\": \"user\", \"content\": \"Hi\"}\n", - "\n", - "result = graph.invoke({\"messages\": [input_message]})\n", - "\n", - "for message in result[\"messages\"]:\n", - " message.pretty_print()" - ] - }, - { - "cell_type": "markdown", - "id": "17583dde-2520-464c-a962-eae511d0928e", - "metadata": {}, - "source": [ - "This is a versatile representation of state for applications involving [chat models](https://python.langchain.com/docs/concepts/chat_models/). LangGraph includes a pre-built `MessagesState` for convenience, so that we can have:" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "05956122-5ba0-4b4c-8b66-6362982227f2", - "metadata": {}, - "outputs": [], - "source": [ - "from langgraph.graph import MessagesState\n", - "\n", - "\n", - "class State(MessagesState):\n", - " extra_field: int" - ] - }, - { - "cell_type": "markdown", - "id": "f262985e-e973-4a27-9c9e-dbb3a06a35b7", - "metadata": {}, - "source": [ - "### Define input and output schemas\n", - "\n", - "By default, `StateGraph` operates with a single schema, and all nodes are expected to communicate using that schema. However, it's also possible to define distinct input and output schemas for a graph.\n", - "\n", - "When distinct schemas are specified, an internal schema will still be used for communication between nodes. The input schema ensures that the provided input matches the expected structure, while the output schema filters the internal data to return only the relevant information according to the defined output schema.\n", - "\n", - "Below, we'll see how to define distinct input and output schema." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6ec0eb77-874e-443e-8c73-93125b515106", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'answer': 'bye'}\n" - ] - } - ], - "source": [ - "from langgraph.graph import StateGraph, START, END\n", - "from typing_extensions import TypedDict\n", - "\n", - "\n", - "# Define the schema for the input\n", - "class InputState(TypedDict):\n", - " question: str\n", - "\n", - "\n", - "# Define the schema for the output\n", - "class OutputState(TypedDict):\n", - " answer: str\n", - "\n", - "\n", - "# Define the overall schema, combining both input and output\n", - "class OverallState(InputState, OutputState):\n", - " pass\n", - "\n", - "\n", - "# Define the node that processes the input and generates an answer\n", - "def answer_node(state: InputState):\n", - " # Example answer and an extra key\n", - " return {\"answer\": \"bye\", \"question\": state[\"question\"]}\n", - "\n", - "\n", - "# Build the graph with input and output schemas specified\n", - "builder = StateGraph(OverallState, input_schema=InputState, output_schema=OutputState)\n", - "builder.add_node(answer_node) # Add the answer node\n", - "builder.add_edge(START, \"answer_node\") # Define the starting edge\n", - "builder.add_edge(\"answer_node\", END) # Define the ending edge\n", - "graph = builder.compile() # Compile the graph\n", - "\n", - "# Invoke the graph with an input and print the result\n", - "print(graph.invoke({\"question\": \"hi\"}))" - ] - }, - { - "cell_type": "markdown", - "id": "6a68836f-98e1-4684-a8a6-c1473c73460c", - "metadata": {}, - "source": [ - "Notice that the output of invoke only includes the output schema." - ] - }, - { - "cell_type": "markdown", - "id": "47ed5db3-bda5-49e1-bf75-23e08c9a3af0", - "metadata": {}, - "source": [ - "### Pass private state between nodes\n", - "\n", - "In some cases, you may want nodes to exchange information that is crucial for intermediate logic but doesn’t need to be part of the main schema of the graph. This private data is not relevant to the overall input/output of the graph and should only be shared between certain nodes.\n", - "\n", - "Below, we'll create an example sequential graph consisting of three nodes (node_1, node_2 and node_3), where private data is passed between the first two steps (node_1 and node_2), while the third step (node_3) only has access to the public overall state." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "ce5b944d-4597-4af9-a7b5-15a00325f3e0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Entered node `node_1`:\n", - "\tInput: {'a': 'set at start'}.\n", - "\tReturned: {'private_data': 'set by node_1'}\n", - "Entered node `node_2`:\n", - "\tInput: {'private_data': 'set by node_1'}.\n", - "\tReturned: {'a': 'set by node_2'}\n", - "Entered node `node_3`:\n", - "\tInput: {'a': 'set by node_2'}.\n", - "\tReturned: {'a': 'set by node_3'}\n", - "\n", - "Output of graph invocation: {'a': 'set by node_3'}\n" - ] - } - ], - "source": [ - "from langgraph.graph import StateGraph, START, END\n", - "from typing_extensions import TypedDict\n", - "\n", - "\n", - "# The overall state of the graph (this is the public state shared across nodes)\n", - "class OverallState(TypedDict):\n", - " a: str\n", - "\n", - "\n", - "# Output from node_1 contains private data that is not part of the overall state\n", - "class Node1Output(TypedDict):\n", - " private_data: str\n", - "\n", - "\n", - "# The private data is only shared between node_1 and node_2\n", - "def node_1(state: OverallState) -> Node1Output:\n", - " output = {\"private_data\": \"set by node_1\"}\n", - " print(f\"Entered node `node_1`:\\n\\tInput: {state}.\\n\\tReturned: {output}\")\n", - " return output\n", - "\n", - "\n", - "# Node 2 input only requests the private data available after node_1\n", - "class Node2Input(TypedDict):\n", - " private_data: str\n", - "\n", - "\n", - "def node_2(state: Node2Input) -> OverallState:\n", - " output = {\"a\": \"set by node_2\"}\n", - " print(f\"Entered node `node_2`:\\n\\tInput: {state}.\\n\\tReturned: {output}\")\n", - " return output\n", - "\n", - "\n", - "# Node 3 only has access to the overall state (no access to private data from node_1)\n", - "def node_3(state: OverallState) -> OverallState:\n", - " output = {\"a\": \"set by node_3\"}\n", - " print(f\"Entered node `node_3`:\\n\\tInput: {state}.\\n\\tReturned: {output}\")\n", - " return output\n", - "\n", - "\n", - "# Connect nodes in a sequence\n", - "# node_2 accepts private data from node_1, whereas\n", - "# node_3 does not see the private data.\n", - "builder = StateGraph(OverallState).add_sequence([node_1, node_2, node_3])\n", - "builder.add_edge(START, \"node_1\")\n", - "graph = builder.compile()\n", - "\n", - "# Invoke the graph with the initial state\n", - "response = graph.invoke(\n", - " {\n", - " \"a\": \"set at start\",\n", - " }\n", - ")\n", - "\n", - "print()\n", - "print(f\"Output of graph invocation: {response}\")" - ] - }, - { - "cell_type": "markdown", - "id": "51466c8d-8ce4-4b3d-be4e-18fdbeda5f53", - "metadata": {}, - "source": [ - "### Use Pydantic models for graph state\n", - "\n", - "A [StateGraph](https://langchain-ai.github.io/langgraph/reference/graphs/#langgraph.graph.StateGraph) accepts a `state_schema` argument on initialization that specifies the \"shape\" of the state that the nodes in the graph can access and update.\n", - "\n", - "In our examples, we typically use a python-native `TypedDict` for `state_schema`, but `state_schema` can be any [type](https://docs.python.org/3/library/stdtypes.html#type-objects).\n", - "\n", - "Here, we'll see how a [Pydantic BaseModel](https://docs.pydantic.dev/latest/api/base_model/). can be used for `state_schema` to add run time validation on **inputs**.\n", - "\n", - "\n", - "
\n", - "

Known Limitations

\n", - "

\n", - "

    \n", - "
  • \n", - " Currently, the output of the graph will NOT be an instance of a pydantic model.\n", - "
    • \n", - "
  • \n", - " Run-time validation only occurs on inputs into nodes, not on the outputs.\n", - "
    • \n", - "
  • \n", - " The validation error trace from pydantic does not show which node the error arises in.\n", - "
    • \n", - "
\n", - "

\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "efc46b36-425c-49c3-9f9e-d9785c70b034", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'a': 'goodbye'}" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from langgraph.graph import StateGraph, START, END\n", - "from typing_extensions import TypedDict\n", - "\n", - "from pydantic import BaseModel\n", - "\n", - "\n", - "# The overall state of the graph (this is the public state shared across nodes)\n", - "class OverallState(BaseModel):\n", - " a: str\n", - "\n", - "\n", - "def node(state: OverallState):\n", - " return {\"a\": \"goodbye\"}\n", - "\n", - "\n", - "# Build the state graph\n", - "builder = StateGraph(OverallState)\n", - "builder.add_node(node) # node_1 is the first node\n", - "builder.add_edge(START, \"node\") # Start the graph with node_1\n", - "builder.add_edge(\"node\", END) # End the graph after node_1\n", - "graph = builder.compile()\n", - "\n", - "# Test the graph with a valid input\n", - "graph.invoke({\"a\": \"hello\"})" - ] - }, - { - "cell_type": "markdown", - "id": "25b594c2-8198-4f76-9606-ea47151ff9d1", - "metadata": {}, - "source": [ - "Invoke the graph with an **invalid** input" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "05d7d43b-0b71-4e25-af6f-61d1560a46cb", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "An exception was raised because `a` is an integer rather than a string.\n", - "1 validation error for OverallState\n", - "a\n", - " Input should be a valid string [type=string_type, input_value=123, input_type=int]\n", - " For further information visit https://errors.pydantic.dev/2.9/v/string_type\n" - ] - } - ], - "source": [ - "try:\n", - " graph.invoke({\"a\": 123}) # Should be a string\n", - "except Exception as e:\n", - " print(\"An exception was raised because `a` is an integer rather than a string.\")\n", - " print(e)" - ] - }, - { - "cell_type": "markdown", - "id": "572ee9f1-45d2-428e-9b70-e7befaf2da80", - "metadata": {}, - "source": [ - "See below for additional features of Pydantic model state:\n", - "\n", - "
\n", - "Serialization Behavior\n", - "\n", - "When using Pydantic models as state schemas, it's important to understand how serialization works, especially when:\n", - "
    \n", - "
  • Passing Pydantic objects as inputs
    • \n", - "
  • Receiving outputs from the graph
    • \n", - "
  • Working with nested Pydantic models
    • \n", - "
\n", - "Let's see these behaviors in action.\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0e919cdc", - "metadata": {}, - "outputs": [], - "source": [ - "from langgraph.graph import StateGraph, START, END\n", - "from pydantic import BaseModel\n", - "\n", - "\n", - "class NestedModel(BaseModel):\n", - " value: str\n", - "\n", - "\n", - "class ComplexState(BaseModel):\n", - " text: str\n", - " count: int\n", - " nested: NestedModel\n", - "\n", - "\n", - "def process_node(state: ComplexState):\n", - " # Node receives a validated Pydantic object\n", - " print(f\"Input state type: {type(state)}\")\n", - " print(f\"Nested type: {type(state.nested)}\")\n", - "\n", - " # Return a dictionary update\n", - " return {\"text\": state.text + \" processed\", \"count\": state.count + 1}\n", - "\n", - "\n", - "# Build the graph\n", - "builder = StateGraph(ComplexState)\n", - "builder.add_node(\"process\", process_node)\n", - "builder.add_edge(START, \"process\")\n", - "builder.add_edge(\"process\", END)\n", - "graph = builder.compile()\n", - "\n", - "# Create a Pydantic instance for input\n", - "input_state = ComplexState(text=\"hello\", count=0, nested=NestedModel(value=\"test\"))\n", - "print(f\"Input object type: {type(input_state)}\")\n", - "\n", - "# Invoke graph with a Pydantic instance\n", - "result = graph.invoke(input_state)\n", - "print(f\"Output type: {type(result)}\")\n", - "print(f\"Output content: {result}\")\n", - "\n", - "# Convert back to Pydantic model if needed\n", - "output_model = ComplexState(**result)\n", - "print(f\"Converted back to Pydantic: {type(output_model)}\")" - ] - }, - { - "cell_type": "markdown", - "id": "f13f28ce", - "metadata": {}, - "source": [ - "
\n", - "\n", - "
Runtime Type Coercion\n", - "\n", - "Pydantic performs runtime type coercion for certain data types. This can be helpful but also lead to unexpected behavior if you're not aware of it.\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "faf59316", - "metadata": {}, - "outputs": [], - "source": [ - "from langgraph.graph import StateGraph, START, END\n", - "from pydantic import BaseModel\n", - "\n", - "\n", - "class CoercionExample(BaseModel):\n", - " # Pydantic will coerce string numbers to integers\n", - " number: int\n", - " # Pydantic will parse string booleans to bool\n", - " flag: bool\n", - "\n", - "\n", - "def inspect_node(state: CoercionExample):\n", - " print(f\"number: {state.number} (type: {type(state.number)})\")\n", - " print(f\"flag: {state.flag} (type: {type(state.flag)})\")\n", - " return {}\n", - "\n", - "\n", - "builder = StateGraph(CoercionExample)\n", - "builder.add_node(\"inspect\", inspect_node)\n", - "builder.add_edge(START, \"inspect\")\n", - "builder.add_edge(\"inspect\", END)\n", - "graph = builder.compile()\n", - "\n", - "# Demonstrate coercion with string inputs that will be converted\n", - "result = graph.invoke({\"number\": \"42\", \"flag\": \"true\"})\n", - "\n", - "# This would fail with a validation error\n", - "try:\n", - " graph.invoke({\"number\": \"not-a-number\", \"flag\": \"true\"})\n", - "except Exception as e:\n", - " print(f\"\\nExpected validation error: {e}\")" - ] - }, - { - "cell_type": "markdown", - "id": "2844475b", - "metadata": {}, - "source": [ - "
\n", - "\n", - "
Working with Message Models\n", - "\n", - "When working with LangChain message types in your state schema, there are important considerations for serialization. You should use AnyMessage (rather than BaseMessage) for proper serialization/deserialization when using message objects over the wire.\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bd0734b0", - "metadata": {}, - "outputs": [], - "source": [ - "from langgraph.graph import StateGraph, START, END\n", - "from pydantic import BaseModel\n", - "from langchain_core.messages import HumanMessage, AIMessage, AnyMessage\n", - "from typing import List\n", - "\n", - "\n", - "class ChatState(BaseModel):\n", - " messages: List[AnyMessage]\n", - " context: str\n", - "\n", - "\n", - "def add_message(state: ChatState):\n", - " return {\"messages\": state.messages + [AIMessage(content=\"Hello there!\")]}\n", - "\n", - "\n", - "builder = StateGraph(ChatState)\n", - "builder.add_node(\"add_message\", add_message)\n", - "builder.add_edge(START, \"add_message\")\n", - "builder.add_edge(\"add_message\", END)\n", - "graph = builder.compile()\n", - "\n", - "# Create input with a message\n", - "initial_state = ChatState(\n", - " messages=[HumanMessage(content=\"Hi\")], context=\"Customer support chat\"\n", - ")\n", - "\n", - "result = graph.invoke(initial_state)\n", - "print(f\"Output: {result}\")\n", - "\n", - "# Convert back to Pydantic model to see message types\n", - "output_model = ChatState(**result)\n", - "for i, msg in enumerate(output_model.messages):\n", - " print(f\"Message {i}: {type(msg).__name__} - {msg.content}\")" - ] - }, - { - "cell_type": "markdown", - "id": "c2e52e1f-c07a-4ebf-b28e-c370c8f50550", - "metadata": {}, - "source": [ - "
" - ] - }, - { - "cell_type": "markdown", - "id": "6e6a0a39-9a4c-47ae-a238-1a3a847eea5b", - "metadata": {}, - "source": [ - "## Add runtime configuration\n", - "\n", - "Sometimes you want to be able to configure your graph when calling it. For example, you might want to be able to specify what LLM or system prompt to use at runtime, *without polluting the graph state with these parameters*.\n", - "\n", - "To add runtime configuration:\n", - "\n", - "1. Specify a schema for your configuration\n", - "2. Add the configuration to the function signature for nodes or conditional edges\n", - "3. Pass the configuration into the graph.\n", - "\n", - "See below for a simple example:" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "97fc508b-1011-402e-8769-573ac3acb53a", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'my_state_value': 1}\n", - "{'my_state_value': 2}\n" - ] - } - ], - "source": [ - "from langchain_core.runnables import RunnableConfig\n", - "from langgraph.graph import END, StateGraph, START\n", - "from typing_extensions import TypedDict\n", - "\n", - "\n", - "# 1. Specify config schema\n", - "class ConfigSchema(TypedDict):\n", - " my_runtime_value: str\n", - "\n", - "\n", - "# 2. Define a graph that accesses the config in a node\n", - "class State(TypedDict):\n", - " my_state_value: str\n", - "\n", - "\n", - "# highlight-next-line\n", - "def node(state: State, config: RunnableConfig):\n", - " # highlight-next-line\n", - " if config[\"configurable\"][\"my_runtime_value\"] == \"a\":\n", - " return {\"my_state_value\": 1}\n", - " # highlight-next-line\n", - " elif config[\"configurable\"][\"my_runtime_value\"] == \"b\":\n", - " return {\"my_state_value\": 2}\n", - " else:\n", - " raise ValueError(\"Unknown values.\")\n", - "\n", - "\n", - "# highlight-next-line\n", - "builder = StateGraph(State, config_schema=ConfigSchema)\n", - "builder.add_node(node)\n", - "builder.add_edge(START, \"node\")\n", - "builder.add_edge(\"node\", END)\n", - "\n", - "graph = builder.compile()\n", - "\n", - "# 3. Pass in configuration at runtime:\n", - "# highlight-next-line\n", - "print(graph.invoke({}, {\"configurable\": {\"my_runtime_value\": \"a\"}}))\n", - "# highlight-next-line\n", - "print(graph.invoke({}, {\"configurable\": {\"my_runtime_value\": \"b\"}}))" - ] - }, - { - "cell_type": "markdown", - "id": "f080f50b-cec1-4dba-81e0-63cf40c990ee", - "metadata": {}, - "source": [ - "
Extended example: specifying LLM at runtime\n", - "\n", - "Below we demonstrate a practical example in which we configure what LLM to use at runtime. We will use both OpenAI and Anthropic models.\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ff4c1453-8cff-4679-9574-8602c530144e", - "metadata": {}, - "outputs": [], - "source": [ - "%%capture --no-stderr\n", - "%pip install -U langgraph \"langchain[anthropic,openai]\"" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "c031a059-7279-4e75-9164-58325d76242f", - "metadata": {}, - "outputs": [], - "source": [ - "import getpass\n", - "import os\n", - "\n", - "\n", - "def _set_env(var: str):\n", - " if not os.environ.get(var):\n", - " os.environ[var] = getpass.getpass(f\"{var}: \")\n", - "\n", - "\n", - "_set_env(\"ANTHROPIC_API_KEY\")\n", - "_set_env(\"OPENAI_API_KEY\")" - ] - }, - { - "cell_type": "markdown", - "id": "75ebea6f-e75f-42d4-9d32-68b37150bdde", - "metadata": {}, - "source": [ - "Build the graph:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "a6033c2a-3b56-46f5-9c3f-79310e31e545", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "claude-3-5-haiku-20241022\n", - "gpt-4.1-mini-2025-04-14\n" - ] - } - ], - "source": [ - "from langchain.chat_models import init_chat_model\n", - "from langchain_core.runnables import RunnableConfig\n", - "from langgraph.graph import MessagesState\n", - "from langgraph.graph import END, StateGraph, START\n", - "from typing_extensions import TypedDict\n", - "\n", - "\n", - "class ConfigSchema(TypedDict):\n", - " model: str\n", - "\n", - "\n", - "MODELS = {\n", - " \"anthropic\": init_chat_model(\"anthropic:claude-3-5-haiku-latest\"),\n", - " \"openai\": init_chat_model(\"openai:gpt-4.1-mini\"),\n", - "}\n", - "\n", - "\n", - "def call_model(state: MessagesState, config: RunnableConfig):\n", - " model = config[\"configurable\"].get(\"model\", \"anthropic\")\n", - " model = MODELS[model]\n", - " response = model.invoke(state[\"messages\"])\n", - " return {\"messages\": [response]}\n", - "\n", - "\n", - "builder = StateGraph(MessagesState, config_schema=ConfigSchema)\n", - "builder.add_node(\"model\", call_model)\n", - "builder.add_edge(START, \"model\")\n", - "builder.add_edge(\"model\", END)\n", - "\n", - "graph = builder.compile()\n", - "\n", - "# Usage\n", - "input_message = {\"role\": \"user\", \"content\": \"hi\"}\n", - "# With no configuration, uses default (Anthropic)\n", - "response_1 = graph.invoke({\"messages\": [input_message]})[\"messages\"][-1]\n", - "# Or, can set OpenAI\n", - "config = {\"configurable\": {\"model\": \"openai\"}}\n", - "response_2 = graph.invoke({\"messages\": [input_message]}, config=config)[\"messages\"][-1]\n", - "\n", - "print(response_1.response_metadata[\"model_name\"])\n", - "print(response_2.response_metadata[\"model_name\"])" - ] - }, - { - "cell_type": "markdown", - "id": "bd1ac2bc-9e3e-42c4-a68f-238c841e58d1", - "metadata": {}, - "source": [ - "
\n", - "\n", - "
Extended example: specifying model and system message at runtime\n", - "\n", - "Below we demonstrate a practical example in which we configure two parameters: the LLM and system message to use at runtime.\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "367bcedd-047c-4150-a059-0a7630ab2663", - "metadata": {}, - "outputs": [], - "source": [ - "%%capture --no-stderr\n", - "%pip install -U langgraph \"langchain[anthropic,openai]\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e5d0dd7d-9564-4a5f-aa2e-2f7be20e1647", - "metadata": {}, - "outputs": [], - "source": [ - "import getpass\n", - "import os\n", - "\n", - "\n", - "def _set_env(var: str):\n", - " if not os.environ.get(var):\n", - " os.environ[var] = getpass.getpass(f\"{var}: \")\n", - "\n", - "\n", - "_set_env(\"ANTHROPIC_API_KEY\")\n", - "_set_env(\"OPENAI_API_KEY\")" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "04924627-9326-438b-aa52-91cea76f4477", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "hi\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Ciao! Come posso aiutarti oggi?\n" - ] - } - ], - "source": [ - "from typing import Optional\n", - "\n", - "from langchain.chat_models import init_chat_model\n", - "from langchain_core.messages import SystemMessage\n", - "from langchain_core.runnables import RunnableConfig\n", - "from langgraph.graph import END, MessagesState, StateGraph, START\n", - "from typing_extensions import TypedDict\n", - "\n", - "\n", - "class ConfigSchema(TypedDict):\n", - " model: Optional[str]\n", - " system_message: Optional[str]\n", - "\n", - "\n", - "MODELS = {\n", - " \"anthropic\": init_chat_model(\"anthropic:claude-3-5-haiku-latest\"),\n", - " \"openai\": init_chat_model(\"openai:gpt-4.1-mini\"),\n", - "}\n", - "\n", - "\n", - "def call_model(state: MessagesState, config: RunnableConfig):\n", - " model = config[\"configurable\"].get(\"model\", \"anthropic\")\n", - " model = MODELS[model]\n", - " messages = state[\"messages\"]\n", - " if system_message := config[\"configurable\"].get(\"system_message\"):\n", - " messages = [SystemMessage(system_message)] + messages\n", - " response = model.invoke(messages)\n", - " return {\"messages\": [response]}\n", - "\n", - "\n", - "builder = StateGraph(MessagesState, config_schema=ConfigSchema)\n", - "builder.add_node(\"model\", call_model)\n", - "builder.add_edge(START, \"model\")\n", - "builder.add_edge(\"model\", END)\n", - "\n", - "graph = builder.compile()\n", - "\n", - "# Usage\n", - "input_message = {\"role\": \"user\", \"content\": \"hi\"}\n", - "config = {\"configurable\": {\"model\": \"openai\", \"system_message\": \"Respond in Italian.\"}}\n", - "response = graph.invoke({\"messages\": [input_message]}, config)\n", - "for message in response[\"messages\"]:\n", - " message.pretty_print()" - ] - }, - { - "cell_type": "markdown", - "id": "03eac38a-fca6-4baf-9ccf-94bf16321235", - "metadata": {}, - "source": [ - "
" - ] - }, - { - "cell_type": "markdown", - "id": "94715e3d-e98b-4be0-ae5f-1169cb795ce5", - "metadata": {}, - "source": [ - "## Add retry policies\n", - "\n", - "There are many use cases where you may wish for your node to have a custom retry policy, for example if you are calling an API, querying a database, or calling an LLM, etc. LangGraph lets you add retry policies to nodes.\n", - "\n", - "To configure a retry policy, pass the `retry_policy` parameter to the [add_node](https://langchain-ai.github.io/langgraph/reference/graphs/#langgraph.graph.state.StateGraph.add_node). The `retry_policy` parameter takes in a `RetryPolicy` named tuple object. Below we instantiate a `RetryPolicy` object with the default parameters and associate it with a node:\n", - "\n", - "```python\n", - "from langgraph.pregel import RetryPolicy\n", - "\n", - "builder.add_node(\n", - " \"node_name\",\n", - " node_function,\n", - " retry_policy=RetryPolicy(),\n", - ")\n", - "```" - ] - }, - { - "cell_type": "markdown", - "id": "af144b8f-761a-4456-a356-ce0812e92577", - "metadata": {}, - "source": [ - "By default, the `retry_on` parameter uses the `default_retry_on` function, which retries on any exception except for the following:\n", - "\n", - "* `ValueError`\n", - "* `TypeError`\n", - "* `ArithmeticError`\n", - "* `ImportError`\n", - "* `LookupError`\n", - "* `NameError`\n", - "* `SyntaxError`\n", - "* `RuntimeError`\n", - "* `ReferenceError`\n", - "* `StopIteration`\n", - "* `StopAsyncIteration`\n", - "* `OSError`\n", - "\n", - "In addition, for exceptions from popular http request libraries such as `requests` and `httpx` it only retries on 5xx status codes.\n", - "\n", - "
Extended example: customizing retry policies\n", - "\n", - "Consider an example in which we are reading from a SQL database. Below we pass two different retry policies to nodes:\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ad92598c-b688-42fa-aae0-9de36273d584", - "metadata": {}, - "outputs": [], - "source": [ - "import sqlite3\n", - "from typing_extensions import TypedDict\n", - "\n", - "from langchain.chat_models import init_chat_model\n", - "\n", - "from langgraph.graph import END, MessagesState, StateGraph, START\n", - "from langgraph.pregel import RetryPolicy\n", - "from langchain_community.utilities import SQLDatabase\n", - "from langchain_core.messages import AIMessage\n", - "\n", - "db = SQLDatabase.from_uri(\"sqlite:///:memory:\")\n", - "\n", - "model = init_chat_model(\"anthropic:claude-3-5-haiku-latest\")\n", - "\n", - "\n", - "def query_database(state: MessagesState):\n", - " query_result = db.run(\"SELECT * FROM Artist LIMIT 10;\")\n", - " return {\"messages\": [AIMessage(content=query_result)]}\n", - "\n", - "\n", - "def call_model(state: MessagesState):\n", - " response = model.invoke(state[\"messages\"])\n", - " return {\"messages\": [response]}\n", - "\n", - "\n", - "# Define a new graph\n", - "builder = StateGraph(MessagesState)\n", - "builder.add_node(\n", - " \"query_database\",\n", - " query_database,\n", - " retry_policy=RetryPolicy(retry_on=sqlite3.OperationalError),\n", - ")\n", - "builder.add_node(\"model\", call_model, retry_policy=RetryPolicy(max_attempts=5))\n", - "builder.add_edge(START, \"model\")\n", - "builder.add_edge(\"model\", \"query_database\")\n", - "builder.add_edge(\"query_database\", END)\n", - "\n", - "graph = builder.compile()" - ] - }, - { - "cell_type": "markdown", - "id": "068f806a", - "metadata": {}, - "source": [ - "
" - ] - }, - { - "cell_type": "markdown", - "id": "6d99d63c", - "metadata": {}, - "source": [ - "## Add node caching\n", - "\n", - "Node caching is useful in cases where you want to avoid repeating operations, like when doing something expensive (either in terms of time or cost). LangGraph lets you add individualized caching policies to nodes in a graph.\n", - "\n", - "To configure a cache policy, pass the `cache_policy` parameter to the [add_node](https://langchain-ai.github.io/langgraph/reference/graphs/#langgraph.graph.state.StateGraph.add_node) function. In the following example, a [`CachePolicy`](https://langchain-ai.github.io/langgraph/reference/types/?h=cachepolicy#langgraph.types.CachePolicy) object is instantiated with a time to live of 120 seconds and the default `key_func` generator. Then it is associated with a node:\n", - "\n", - "```python\n", - "from langgraph.types import CachePolicy\n", - "\n", - "builder.add_node(\n", - " \"node_name\",\n", - " node_function,\n", - " cache_policy=CachePolicy(ttl=120),\n", - ")\n", - "```\n", - "\n", - "Then, to enable node-level caching for a graph, set the `cache` argument when compiling the graph. The example below uses `InMemoryCache` to set up a graph with in-memory cache, but `SqliteCache` is also available.\n", - "\n", - "```python\n", - "from langgraph.cache.memory import InMemoryCache\n", - "\n", - "\n", - "graph = builder.compile(cache=InMemoryCache())\n", - "```" - ] - }, - { - "cell_type": "markdown", - "id": "e1a0213e-282f-4fad-b048-5f7465edfccb", - "metadata": {}, - "source": [ - "## Create a sequence of steps\n", - "\n", - "!!! info \"Prerequisites\"\n", - " This guide assumes familiarity with the above section on [state](#define-and-update-state).\n", - "\n", - "Here we demonstrate how to construct a simple sequence of steps. We will show:\n", - "\n", - "1. How to build a sequential graph\n", - "2. Built-in short-hand for constructing similar graphs.\n", - "\n", - "\n", - "To add a sequence of nodes, we use the `.add_node` and `.add_edge` methods of our [graph](../../concepts/low_level/#stategraph):\n", - "```python\n", - "from langgraph.graph import START, StateGraph\n", - "\n", - "builder = StateGraph(State)\n", - "\n", - "# Add nodes\n", - "builder.add_node(step_1)\n", - "builder.add_node(step_2)\n", - "builder.add_node(step_3)\n", - "\n", - "# Add edges\n", - "builder.add_edge(START, \"step_1\")\n", - "builder.add_edge(\"step_1\", \"step_2\")\n", - "builder.add_edge(\"step_2\", \"step_3\")\n", - "```\n", - "\n", - "We can also use the built-in shorthand `.add_sequence`:\n", - "```python\n", - "builder = StateGraph(State).add_sequence([step_1, step_2, step_3])\n", - "builder.add_edge(START, \"step_1\")\n", - "```\n", - "\n", - "\n", - "
\n", - "Why split application steps into a sequence with LangGraph?\n", - "\n", - "LangGraph makes it easy to add an underlying persistence layer to your application.\n", - "This allows state to be checkpointed in between the execution of nodes, so your LangGraph nodes govern:\n", - "\n", - "
    \n", - "
  • How state updates are [checkpointed](../../concepts/persistence/)
    • \n", - "
  • How interruptions are resumed in [human-in-the-loop](../../concepts/human_in_the_loop/) workflows
    • \n", - "
  • How we can \"rewind\" and branch-off executions using LangGraph's [time travel](../../concepts/time-travel/) features
    • \n", - "
\n", - "\n", - "They also determine how execution steps are [streamed](../../concepts/streaming/), and how your application is visualized\n", - "and debugged using [LangGraph Studio](../../concepts/langgraph_studio/).\n", - "\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "518cb5d1-c60f-44d7-b348-e03b6e487098", - "metadata": {}, - "source": [ - "Let's demonstrate an end-to-end example. We will create a sequence of three steps:\n", - "\n", - "1. Populate a value in a key of the state\n", - "2. Update the same value\n", - "3. Populate a different value\n", - "\n", - "Let's first define our [state](../../concepts/low_level/#state). This governs the [schema of the graph](../../concepts/low_level/#schema), and can also specify how to apply updates. See [this section](#process-state-updates-with-reducers) for more detail.\n", - "\n", - "In our case, we will just keep track of two values:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "aa1b04c6-2653-4ad4-a720-facc1f2906a7", - "metadata": {}, - "outputs": [], - "source": [ - "from typing_extensions import TypedDict\n", - "\n", - "\n", - "class State(TypedDict):\n", - " value_1: str\n", - " value_2: int" - ] - }, - { - "cell_type": "markdown", - "id": "6d4a8554-bc19-4bbe-a8c2-20adcfca8273", - "metadata": {}, - "source": [ - "Our [nodes](../../concepts/low_level/#nodes) are just Python functions that read our graph's state and make updates to it. The first argument to this function will always be the state:" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "c7db921a-dbfb-4039-a93b-8b2264143a3f", - "metadata": {}, - "outputs": [], - "source": [ - "def step_1(state: State):\n", - " return {\"value_1\": \"a\"}\n", - "\n", - "\n", - "def step_2(state: State):\n", - " current_value_1 = state[\"value_1\"]\n", - " return {\"value_1\": f\"{current_value_1} b\"}\n", - "\n", - "\n", - "def step_3(state: State):\n", - " return {\"value_2\": 10}" - ] - }, - { - "cell_type": "markdown", - "id": "2b454eb0-19c1-418e-a912-dc44c0c045e2", - "metadata": {}, - "source": [ - "!!! note\n", - "\n", - " Note that when issuing updates to the state, each node can just specify the value of the key it wishes to update.\n", - "\n", - "By default, this will **overwrite** the value of the corresponding key. You can also use [reducers](../../concepts/low_level/#reducers) to control how updates are processed— for example, you can append successive updates to a key instead. See [this section](#process-state-updates-with-reducers) for more detail.\n", - "\n", - "Finally, we define the graph. We use [StateGraph](../../concepts/low_level/#stategraph) to define a graph that operates on this state.\n", - "\n", - "We will then use [add_node](../../concepts/low_level/#messagesstate) and [add_edge](../../concepts/low_level/#edges) to populate our graph and define its control flow." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b02bdbcf-2bbb-4f08-b177-1a45b2a8bc6d", - "metadata": {}, - "outputs": [], - "source": [ - "from langgraph.graph import START, StateGraph\n", - "\n", - "builder = StateGraph(State)\n", - "\n", - "# Add nodes\n", - "builder.add_node(step_1)\n", - "builder.add_node(step_2)\n", - "builder.add_node(step_3)\n", - "\n", - "# Add edges\n", - "builder.add_edge(START, \"step_1\")\n", - "builder.add_edge(\"step_1\", \"step_2\")\n", - "builder.add_edge(\"step_2\", \"step_3\")" - ] - }, - { - "cell_type": "markdown", - "id": "79a696b2-ef9b-4f8d-ae83-ea674a16bab0", - "metadata": {}, - "source": [ - "!!! tip \"Specifying custom names\"\n", - "\n", - " You can specify custom names for nodes using `.add_node`:\n", - "\n", - " ```python\n", - " builder.add_node(\"my_node\", step_1)\n", - " ```" - ] - }, - { - "cell_type": "markdown", - "id": "7452c5ea-cf1b-47a5-8da0-32479c142dce", - "metadata": {}, - "source": [ - "Note that:\n", - "\n", - "- `.add_edge` takes the names of nodes, which for functions defaults to `node.__name__`.\n", - "- We must specify the entry point of the graph. For this we add an edge with the [START node](../../concepts/low_level/#start-node).\n", - "- The graph halts when there are no more nodes to execute.\n", - "\n", - "We next [compile](../../concepts/low_level/#compiling-your-graph) our graph. This provides a few basic checks on the structure of the graph (e.g., identifying orphaned nodes). If we were adding persistence to our application via a [checkpointer](../../concepts/persistence/), it would also be passed in here." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7aa2828c-0903-4775-b4ea-d62647f3bf0a", - "metadata": {}, - "outputs": [], - "source": [ - "graph = builder.compile()" - ] - }, - { - "cell_type": "markdown", - "id": "4c85772e-788c-49df-9327-11cb92f02c6a", - "metadata": {}, - "source": [ - "LangGraph provides built-in utilities for visualizing your graph. Let's inspect our sequence. See [this guide](../../how-tos/visualization) for detail on visualization." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "4162bc81-cbfd-49e3-b79f-8a97b9f417c2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from IPython.display import Image, display\n", - "\n", - "display(Image(graph.get_graph().draw_mermaid_png()))" - ] - }, - { - "cell_type": "markdown", - "id": "9406b427-c28c-4cd0-9f01-e5bc1f089f4c", - "metadata": {}, - "source": [ - "Let's proceed with a simple invocation:" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "3f7012ae-4f8f-4dd3-9f99-ebd179ff5fe9", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'value_1': 'a b', 'value_2': 10}" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "graph.invoke({\"value_1\": \"c\"})" - ] - }, - { - "cell_type": "markdown", - "id": "648421de-e43a-4242-8e62-afd84bc91b7e", - "metadata": {}, - "source": [ - "Note that:\n", - "\n", - "- We kicked off invocation by providing a value for a single state key. We must always provide a value for at least one key.\n", - "- The value we passed in was overwritten by the first node.\n", - "- The second node updated the value.\n", - "- The third node populated a different value." - ] - }, - { - "cell_type": "markdown", - "id": "1acdf7f1-d2f8-4863-a7f3-d5de4cc0ef28", - "metadata": {}, - "source": [ - "!!! tip \"Built-in shorthand\"\n", - "\n", - " `langgraph>=0.2.46` includes a built-in short-hand `add_sequence` for adding node sequences. You can compile the same graph as follows:\n", - "\n", - " ```python\n", - " # highlight-next-line\n", - " builder = StateGraph(State).add_sequence([step_1, step_2, step_3])\n", - " builder.add_edge(START, \"step_1\")\n", - " \n", - " graph = builder.compile()\n", - " \n", - " graph.invoke({\"value_1\": \"c\"}) \n", - " ```" - ] - }, - { - "attachments": { - "51f122de-b2ce-4c21-a5a7-c3be70c28a91.png": { - "image/png": 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" - } - }, - "cell_type": "markdown", - "id": "710dc4f0-1c88-4386-9e9d-fec3de6bb774", - "metadata": {}, - "source": [ - "## Create branches\n", - "\n", - "Parallel execution of nodes is essential to speed up overall graph operation. LangGraph offers native support for parallel execution of nodes, which can significantly enhance the performance of graph-based workflows. This parallelization is achieved through fan-out and fan-in mechanisms, utilizing both standard edges and [conditional_edges](https://langchain-ai.github.io/langgraph/reference/graphs/#langgraph.graph.MessageGraph.add_conditional_edges). Below are some examples showing how to add create branching dataflows that work for you. \n", - "\n", - "![Screenshot 2024-07-09 at 2.55.56 PM.png](attachment:51f122de-b2ce-4c21-a5a7-c3be70c28a91.png)" - ] - }, - { - "cell_type": "markdown", - "id": "d6c05fc4-ecd8-483f-a9fd-b1a055f922d9", - "metadata": {}, - "source": [ - "### Run graph nodes in parallel\n", - "\n", - "In this example, we fan out from `Node A` to `B and C` and then fan in to `D`. With our state, [we specify the reducer add operation](https://langchain-ai.github.io/langgraph/concepts/low_level/#reducers). This will combine or accumulate values for the specific key in the State, rather than simply overwriting the existing value. For lists, this means concatenating the new list with the existing list. See the above section on [state reducers](#process-state-updates-with-reducers) for more detail on updating state with reducers." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "09372b8b-edea-4b9d-9ec3-3d93ce1ba819", - "metadata": {}, - "outputs": [], - "source": [ - "import operator\n", - "from typing import Annotated, Any\n", - "\n", - "from typing_extensions import TypedDict\n", - "\n", - "from langgraph.graph import StateGraph, START, END\n", - "\n", - "\n", - "class State(TypedDict):\n", - " # The operator.add reducer fn makes this append-only\n", - " aggregate: Annotated[list, operator.add]\n", - "\n", - "\n", - "def a(state: State):\n", - " print(f'Adding \"A\" to {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"A\"]}\n", - "\n", - "\n", - "def b(state: State):\n", - " print(f'Adding \"B\" to {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"B\"]}\n", - "\n", - "\n", - "def c(state: State):\n", - " print(f'Adding \"C\" to {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"C\"]}\n", - "\n", - "\n", - "def d(state: State):\n", - " print(f'Adding \"D\" to {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"D\"]}\n", - "\n", - "\n", - "builder = StateGraph(State)\n", - "builder.add_node(a)\n", - "builder.add_node(b)\n", - "builder.add_node(c)\n", - "builder.add_node(d)\n", - "builder.add_edge(START, \"a\")\n", - "builder.add_edge(\"a\", \"b\")\n", - "builder.add_edge(\"a\", \"c\")\n", - "builder.add_edge(\"b\", \"d\")\n", - "builder.add_edge(\"c\", \"d\")\n", - "builder.add_edge(\"d\", END)\n", - "graph = builder.compile()" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "66f52a20", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from IPython.display import Image, display\n", - "\n", - "display(Image(graph.get_graph().draw_mermaid_png()))" - ] - }, - { - "cell_type": "markdown", - "id": "74dd577b-0474-44c4-b4bc-9113090e3121", - "metadata": {}, - "source": [ - "With the reducer, you can see that the values added in each node are accumulated." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "81646784-5e7d-4096-980d-9fdfafd6e7a3", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Adding \"A\" to []\n", - "Adding \"B\" to ['A']\n", - "Adding \"C\" to ['A']\n", - "Adding \"D\" to ['A', 'B', 'C']\n" - ] - }, - { - "data": { - "text/plain": [ - "{'aggregate': ['A', 'B', 'C', 'D']}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "graph.invoke({\"aggregate\": []}, {\"configurable\": {\"thread_id\": \"foo\"}})" - ] - }, - { - "cell_type": "markdown", - "id": "ea5495cf-9564-40c6-bc2d-0b2a8f72a5df", - "metadata": {}, - "source": [ - "!!! note\n", - "\n", - " In the above example, nodes `\"b\"` and `\"c\"` are executed concurrently in the same [superstep](../../concepts/low_level/#graphs). Because they are in the same step, node `\"d\"` executes after both `\"b\"` and `\"c\"` are finished.\n", - "\n", - " Importantly, updates from a parallel superstep may not be ordered consistently. If you need a consistent, predetermined ordering of updates from a parallel superstep, you should write the outputs to a separate field in the state together with a value with which to order them." - ] - }, - { - "cell_type": "markdown", - "id": "c392b3d2", - "metadata": {}, - "source": [ - "
Exception handling?\n", - "

LangGraph executes nodes within \"supersteps\", meaning that while parallel branches are executed in parallel, the entire superstep is transactional. If any of these branches raises an exception, none of the updates are applied to the state (the entire superstep errors).

\n", - "

Importantly, when using a checkpointer, results from successful nodes within a superstep are saved, and don't repeat when resumed.

\n", - " If you have error-prone (perhaps want to handle flakey API calls), LangGraph provides two ways to address this:
\n", - "
    \n", - "
  1. You can write regular python code within your node to catch and handle exceptions.
    2. \n", - "
  2. You can set a retry_policy to direct the graph to retry nodes that raise certain types of exceptions. Only failing branches are retried, so you needn't worry about performing redundant work.
    3. \n", - "

\n", - "Together, these let you perform parallel execution and fully control exception handling.\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "48731230", - "metadata": {}, - "source": [ - "### Defer node execution\n", - "\n", - "Deferring node execution is useful when you want to delay the execution of a node until all other pending tasks are completed. This is particularly relevant when branches have different lengths, which is common in workflows like map-reduce flows.\n", - "\n", - "The above example showed how to fan-out and fan-in when each path was only one step. But what if one branch had more than one step? Let's add a node `\"b_2\"` in the `\"b\"` branch:" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "3890af2f-fb14-4569-b48d-a91db2d3f026", - "metadata": {}, - "outputs": [], - "source": [ - "import operator\n", - "from typing import Annotated, Any\n", - "\n", - "from typing_extensions import TypedDict\n", - "\n", - "from langgraph.graph import StateGraph, START, END\n", - "\n", - "\n", - "class State(TypedDict):\n", - " # The operator.add reducer fn makes this append-only\n", - " aggregate: Annotated[list, operator.add]\n", - "\n", - "\n", - "def a(state: State):\n", - " print(f'Adding \"A\" to {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"A\"]}\n", - "\n", - "\n", - "def b(state: State):\n", - " print(f'Adding \"B\" to {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"B\"]}\n", - "\n", - "\n", - "def b_2(state: State):\n", - " print(f'Adding \"B_2\" to {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"B_2\"]}\n", - "\n", - "\n", - "def c(state: State):\n", - " print(f'Adding \"C\" to {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"C\"]}\n", - "\n", - "\n", - "def d(state: State):\n", - " print(f'Adding \"D\" to {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"D\"]}\n", - "\n", - "\n", - "builder = StateGraph(State)\n", - "builder.add_node(a)\n", - "builder.add_node(b)\n", - "builder.add_node(b_2)\n", - "builder.add_node(c)\n", - "# highlight-next-line\n", - "builder.add_node(d, defer=True)\n", - "builder.add_edge(START, \"a\")\n", - "builder.add_edge(\"a\", \"b\")\n", - "builder.add_edge(\"a\", \"c\")\n", - "builder.add_edge(\"b\", \"b_2\")\n", - "builder.add_edge(\"b_2\", \"d\")\n", - "builder.add_edge(\"c\", \"d\")\n", - "builder.add_edge(\"d\", END)\n", - "graph = builder.compile()" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "1a3508e6-bcaf-448e-bdc8-bf5701589d42", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from IPython.display import Image, display\n", - "\n", - "display(Image(graph.get_graph().draw_mermaid_png()))" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "b510379a-b82a-4658-973e-df56caf5cd01", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Adding \"A\" to []\n", - "Adding \"B\" to ['A']\n", - "Adding \"C\" to ['A']\n", - "Adding \"B_2\" to ['A', 'B', 'C']\n", - "Adding \"D\" to ['A', 'B', 'C', 'B_2']\n" - ] - }, - { - "data": { - "text/plain": [ - "{'aggregate': ['A', 'B', 'C', 'B_2', 'D']}" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "graph.invoke({\"aggregate\": []})" - ] - }, - { - "cell_type": "markdown", - "id": "70e67ced", - "metadata": {}, - "source": [ - "In the above example, nodes `\"b\"` and `\"c\"` are executed concurrently in the same superstep. We set `defer=True` on node `d` so it will not execute until all pending tasks are finished. In this case, this means that `\"d\"` waits to execute until the entire `\"b\"` branch is finished." - ] - }, - { - "cell_type": "markdown", - "id": "1a940eec-f36f-4236-9cc8-8d5dfd5cc860", - "metadata": {}, - "source": [ - "### Conditional branching\n", - "\n", - "If your fan-out should vary at runtime based on the state, you can use [add_conditional_edges](https://langchain-ai.github.io/langgraph/reference/graphs/#langgraph.graph.StateGraph.add_conditional_edges) to select one or more paths using the graph state. See example below, where node `a` generates a state update that determines the following node." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "8b270199-f07d-4831-9674-f18715fa26de", - "metadata": {}, - "outputs": [], - "source": [ - "import operator\n", - "from typing import Annotated, Literal, Sequence\n", - "\n", - "from typing_extensions import TypedDict\n", - "\n", - "from langgraph.graph import StateGraph, START, END\n", - "\n", - "\n", - "class State(TypedDict):\n", - " aggregate: Annotated[list, operator.add]\n", - " # Add a key to the state. We will set this key to determine\n", - " # how we branch.\n", - " which: str\n", - "\n", - "\n", - "def a(state: State):\n", - " print(f'Adding \"A\" to {state[\"aggregate\"]}')\n", - " # highlight-next-line\n", - " return {\"aggregate\": [\"A\"], \"which\": \"c\"}\n", - "\n", - "\n", - "def b(state: State):\n", - " print(f'Adding \"B\" to {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"B\"]}\n", - "\n", - "\n", - "def c(state: State):\n", - " print(f'Adding \"C\" to {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"C\"]}\n", - "\n", - "\n", - "builder = StateGraph(State)\n", - "builder.add_node(a)\n", - "builder.add_node(b)\n", - "builder.add_node(c)\n", - "builder.add_edge(START, \"a\")\n", - "builder.add_edge(\"b\", END)\n", - "builder.add_edge(\"c\", END)\n", - "\n", - "\n", - "def conditional_edge(state: State) -> Literal[\"b\", \"c\"]:\n", - " # Fill in arbitrary logic here that uses the state\n", - " # to determine the next node\n", - " return state[\"which\"]\n", - "\n", - "\n", - "# highlight-next-line\n", - "builder.add_conditional_edges(\"a\", conditional_edge)\n", - "\n", - "graph = builder.compile()" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "43999312-0198-49e4-86a9-4f71e343ed64", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from IPython.display import Image, display\n", - "\n", - "display(Image(graph.get_graph().draw_mermaid_png()))" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "c6e92bf6-5ee8-4a5a-8693-a0e028b73e3b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Adding \"A\" to []\n", - "Adding \"C\" to ['A']\n", - "{'aggregate': ['A', 'C'], 'which': 'c'}\n" - ] - } - ], - "source": [ - "result = graph.invoke({\"aggregate\": []})\n", - "print(result)" - ] - }, - { - "cell_type": "markdown", - "id": "b1c54e61-393d-4359-88e2-6117a6022ce3", - "metadata": {}, - "source": [ - "!!! tip\n", - "\n", - " Your conditional edges can route to multiple destination nodes. For example:\n", - "\n", - " ```python\n", - " def route_bc_or_cd(state: State) -> Sequence[str]:\n", - " if state[\"which\"] == \"cd\":\n", - " return [\"c\", \"d\"]\n", - " return [\"b\", \"c\"]\n", - " ```" - ] - }, - { - "attachments": { - "f0038a5c-08d9-4eff-a1cb-d1ee4dde4fe5.png": { - "image/png": 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" - } - }, - "cell_type": "markdown", - "id": "931a0f15-b8d2-4ff6-8772-fd99f708a099", - "metadata": {}, - "source": [ - "### Map-reduce and the `Send` API\n", - "\n", - "By default, `Nodes` and `Edges` are defined ahead of time and operate on the same shared state. However, there can be cases where the exact edges are not known ahead of time and/or you may want different versions of state to exist at the same time. A common example of this is with map-reduce design patterns. In this design pattern, a first node may generate a list of objects, and you may want to apply some other node to all those objects. The number of objects may be unknown ahead of time (meaning the number of edges may not be known) and the input state to the downstream `Node` should be different (one for each generated object).\n", - "\n", - "To support this design pattern, LangGraph supports returning [Send](/langgraph/reference/types/#langgraph.types.Send) objects from conditional edges. `Send` takes two arguments: first is the name of the node, and second is the state to pass to that node.\n", - "\n", - "```python\n", - "def continue_to_jokes(state: OverallState):\n", - " return [Send(\"generate_joke\", {\"subject\": s}) for s in state['subjects']]\n", - "\n", - "graph.add_conditional_edges(\"node_a\", continue_to_jokes)\n", - "```\n", - "\n", - "Below we implement a simple example, where we simulate using LLMs to (1) generate a list of subjects (the length of which is unknown ahead of time), (2) generate jokes in parallel, and (3) select a \"best\" joke. Importantly, the input state to the fan-out nodes is different than the graph's overall state.\n", - "\n", - "![Screenshot 2025-05-05 at 4.21.35 PM.png](attachment:f0038a5c-08d9-4eff-a1cb-d1ee4dde4fe5.png)" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "8b971a9c-337a-4899-bcf7-080193832935", - "metadata": {}, - "outputs": [], - "source": [ - "import operator\n", - "from typing import Annotated\n", - "from typing_extensions import TypedDict\n", - "\n", - "from langgraph.types import Send\n", - "from langgraph.graph import END, StateGraph, START\n", - "\n", - "\n", - "# This will be the overall state of the main graph.\n", - "# It will contain a topic (which we expect the user to provide)\n", - "# and then will generate a list of subjects, and then a joke for\n", - "# each subject\n", - "class OverallState(TypedDict):\n", - " topic: str\n", - " subjects: list\n", - " # Notice here we use the operator.add\n", - " # This is because we want combine all the jokes we generate\n", - " # from individual nodes back into one list - this is essentially\n", - " # the \"reduce\" part\n", - " jokes: Annotated[list, operator.add]\n", - " best_selected_joke: str\n", - "\n", - "\n", - "# This will be the state of the node that we will \"map\" all\n", - "# subjects to in order to generate a joke\n", - "class JokeState(TypedDict):\n", - " subject: str\n", - "\n", - "\n", - "# This is the function we will use to generate the subjects of the jokes.\n", - "# In general the length of the list generated by this node could vary each run.\n", - "def generate_topics(state: OverallState):\n", - " # Simulate a LLM.\n", - " return {\"subjects\": [\"lions\", \"elephants\", \"penguins\"]}\n", - "\n", - "\n", - "# Here we generate a joke, given a subject\n", - "def generate_joke(state: JokeState):\n", - " # Simulate a LLM.\n", - " joke_map = {\n", - " \"lions\": \"Why don't lions like fast food? Because they can't catch it!\",\n", - " \"elephants\": \"Why don't elephants use computers? They're afraid of the mouse!\",\n", - " \"penguins\": (\n", - " \"Why don’t penguins like talking to strangers at parties? \"\n", - " \"Because they find it hard to break the ice.\"\n", - " ),\n", - " }\n", - " return {\"jokes\": [joke_map[state[\"subject\"]]]}\n", - "\n", - "\n", - "# Here we define the logic to map out over the generated subjects\n", - "# We will use this as an edge in the graph\n", - "def continue_to_jokes(state: OverallState):\n", - " # We will return a list of `Send` objects\n", - " # Each `Send` object consists of the name of a node in the graph\n", - " # as well as the state to send to that node\n", - " return [Send(\"generate_joke\", {\"subject\": s}) for s in state[\"subjects\"]]\n", - "\n", - "\n", - "# Here we will judge the best joke\n", - "def best_joke(state: OverallState):\n", - " return {\"best_selected_joke\": \"penguins\"}\n", - "\n", - "\n", - "# Construct the graph: here we put everything together to construct our graph\n", - "builder = StateGraph(OverallState)\n", - "builder.add_node(\"generate_topics\", generate_topics)\n", - "builder.add_node(\"generate_joke\", generate_joke)\n", - "builder.add_node(\"best_joke\", best_joke)\n", - "builder.add_edge(START, \"generate_topics\")\n", - "builder.add_conditional_edges(\"generate_topics\", continue_to_jokes, [\"generate_joke\"])\n", - "builder.add_edge(\"generate_joke\", \"best_joke\")\n", - "builder.add_edge(\"best_joke\", END)\n", - "graph = builder.compile()" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "2760846f-a297-455c-a07c-155743f5e55f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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ixqnXBto6+OYvtx0Ao0ellJWWQCN4qRhcemh5QaMmvDP03drp5haNCCThqMDR1k6B1dqSV1RU8PkvJATh7e0c/t9vmVtAItRgTV3XUOPXwqAKQhB38NCez5cthACiSb4+0DQ+mDKJ8Qlx1KpEIrl79y9qGQJgsFcQ6EI9pf6gcYNLq//ovb3byeVyOGHNVlwuz9ra9tWSlfJKVMtgQFyWk5tdu2tALUPlAPsJ8a1mhw4OTuBfTU1M0b+h2ZtX67YJiU/BtFCr0EAhjPKuiaIpIOanFsABQZaLS4va+/Hw8AJ78+TJI2o1Le3Zh7OnpKamQB2Fw0bVkRqrQ4fOwdPmgEWEsAY1BU0ksKMzOKdjx76CA4UT27DpC4v/mVOIU6CnD7YR4ursnCwINCAQ/dehAwi4wEWt37DiwYO7INilmF9mfTgJgrVXS0JIBXUF4i/ogfx959aOneEQ6GU+T4cqxasBQvqk5AS4shPGvwchOsR3EAxDCuz84wXToS7WfyQmxibgb/b12gAAEABJREFU+6E8XHQI2isrZRC0wx7AbEBMDm0aYkaqJMgDoQA0QcjdvmMjpAwYMOSlkwIHvDliLRwnFIMYHmonePG/bt9YtmLR1T9isrKfww+dPh0NTd/Ozh41BU020AGdHDh08LXWVjaTJweD4YqPf9Gg587+BC7T/gM7QAPwo/49e08Pnlf/3uBibdq4E3q3K1eHQqfI3t5x6tQZ0MV6tSTYPejzREXtuvjbz61bt4G+U0Fh/tqwpYsWzz508NuJEz6IPvn1zZt/Hj3yY++3+n++dO2J6MOHDu8DYXx8/LZFRGpeyPI6Ro2asGHjF1AVoG/TrWvPzZt274/aOWPWRDhCX58OsAc4AE3hWTPm79y1+VlqMnSl1q7eAvW+9q7AMq8P275z9+ZVq0NZTBYEmxCHg+OYMjlYqVTs27e9sKiAOrCNG3a8asbfjCYb6IAoRqFUgJDU6qKQ2WA2qSiRDpz+4SR06GN+u430QT0DHU3WgiEugMA45JNlFhaWN2/9CaZ4w7rtiKBvmtJEwyDcipWLwUs5OjovCV31HweBdcbwkX1fl7UkdHVAQB/UnGkyE918gSDudVkW5pb1D1YbCLow0c2XVzvNOEEExhwiMOYQgTGHCIw5RGDMIQJjDhEYc4jAmEMExpy6BTYSsNQqNSI0E3jGLA6v7tuLdd/wN7Nm56RVIEIzITNebOXAqzOrboGdPQXyimb//mCaUF6isLDlmllz6sytW2AWm9F9iOXFb7IQweC5Ep391rvWr8ut73XCWSkVv36T26GPpbkdT2BCwjEDgsFAomKFqEh+81zBe8vdTK04ry1Z/wvBxaXKe5dLctNk0nIcLLZSoWAwmdSzT80avjGbw2U4tjLqHmhZ/+wtWnz5TEN4eLibm9v48eMRbaCX4R06dKixsTGiE/RqwTSEXq9wuHDhwu3b+pnZqi/oJfCjR49SU1MRnSA+GHOID8Yc4oMxh/hgzCE+GHOID8Yc4oMxh/hgzCE+GHOID8Yc4oMxh/hgzCE+GHOID8Yc4oMxh/hgzCE+GHOID8Yc4oMxh14mOjMzU/MyYJpAL4H9/f2JDyZgBfHBmEP6wZhD+sGYQ3ww5hAfjDnEB2MO8cGYQ3ww5hAfjDnEB2MO8cGYQ3ww5hAfjDnEB2MOLUz0hAkTmEwmnCnc7WfVUFVDdHQ0wh1aBFmgZWJi4kspHTp0QDSAFiZ67NixPN7/e52yQCCYNm0aogG0EHjMmDEuLi61U7y9vXv1ah4fR/2P0CXIAo25XC61bGJiEhwcjOgBjQSmGjF4X2i+PXv2RPSARt0k8MTQiE1NTadMmYJow5tH0aIiBYPJQM2Hgf1GfH/yvK2tbfu23ctLlKj5AD1ZU8s3VKrR/eCc1Ip7l0tT4ySO7nzQGBG0j6UDLytJ6uEn7D7UytSS06htGydw+lPpzZ+LAt61M7Pm1P8meULTolSoS/Pll0/mBM1zsrDlNnzDRggM6v71S1FgsAsi6I9TW1PHLHBueDtuRJB170rJgMk4f+6+WdBvvMOt88UNL99QgctLFKX5Ci6v2X+vpLljYcdLflDe8PINFbi0QOHsKUAEfcNiM1y9hKUF8gaWb2jwXaWu/oYSIhgAxXnyhke45HtmmEMExhwiMOYQgTGHCIw5RGDMIQJjDhEYc4jAmEMExhwiMObQ69GVJmHlqtCQxXPqL/PsWXK/AV0ePXqA9A3tWvAPP36bkPhkSegq9KYMGxakbD4vvKSdwImJT9F/o2uXHqj5oEWBlUrlnr1bL8X8olIpe781IMC/z4qVi09/d9HCwhKyjh47ePnKxby8HBsbu7FjJo8cMYbaatTogVMnT8/Lz7185deKCqmvb8fFi5ZbWVlTO6xzq9TUlOAZ49et3bo/aiffiL93zzcqleqbIwdiYn4pKMw3NTWDn/5w1gI+n79w0azY2Huwya+//rQ/8pinh1diUnxU1K6ExKdKpaJTx27z5obY2zvUf15gosXi8ogte2E5Pz9v775td+/+VSGrcHFxmzj+/YEDh766ydFjXx0/cWjb1v1erduUlpbs2bctNvZuWVmpu7vnzBkfdezQBWkNLfrg774/fu6n07Nmzt+7+xtra5t9+7+s/j1m9S/ui/zy5LdHJk+cdjDqJOi0a/eWn8//SG3FZrNPnPy6RQv3E8fOfRX1bVJS/JGjUVTW67bicKonKH39zf7x46Z+uvgL6qePnzgcHDz34IHo0E9XXr9xNeqr3ZAetmZra0/v/v0G/Xj6kntLj7y83EUhHzKYzG0RkRFb9onKy0I+nSOXN/ReukKh+PSzeZnP09euiTh08Nveb/Vfv/GL69evvlTs96uX4Ni+WLER1FWr1Z8tmR8X9/Cz0FWRe496e7VdsvRjcNhIa2ixBf968adeAX2HvTMKlqcHz33y5FFWViYsi8XiM2dPTZ40bfDgYbDq7OQCKoIe7wx9l9rQzbVl4JARsGBra9etq39CwpN/2arm7neHDl2orYC3BwR27dLT3d2juqSza7++g/66fR2WjY2NWWw2h8s1MzOH1bPnvoM758uXrTMxNoHVz5esnTh5+NU/Yga+HdiQE/zrr+sZGWmUJYDVD97/8O692z/8eDIgoI+mzNOnjzduWvnJwqU9ugfA6p27f4HN2Bqxj2q1H81bDCmnf4heHLIcaQdtteCqqqrnzzN82vlpUnr16kctpKQkgrHt0vkfT+bn1zk7+7lUKqVWwXBpskxMTEXlooZs1batryYL9ANF5370wbgJQ4PGDDr30/flNTt5Cbj63l7tKHUBOzt7Bwen5OQE1DCSkuN5PJ5Hq9aalNat2ySn/POcam5ezrIVi8aNnTI0cKTmF8HedPDrTK2CPWvv27Hhv/gGaKsFV1RUgB58wT/TuMAXUgtSqQT+/QRs4//mnVBTd4tLigQ15V961JPxb1tRq0LhP29X2blr82+Xzn+yYGk7Hz8el3ci+mvw6K8epEQiTkpOGDTkn+eUwOoWFReihiGWiI2M+LVnzwgFQuo4Kb7csRHqX1HRPzuEXPiJwYH+mhQIFywtrZDW0JbAlF+UyWSaFE0bopRY9nkYeMHam9ja2NWzw3q2yi/Iq50Cl+z8hTNTp8zQxDsg5Ov26evbIeSTZbUT+fyGzi00FhpDGAj1TKOxRCqpXc/AU3Tq1A2Csp493wJvRf0il8s9EHm89n6ouERLaFFg8KDxCXGalGvXrlALYIEht6Sk2LVPCyoFAku4RprHO+uk4VtBIAMaawyGRCK5cfOP2hdRM9e/TRsfCBQcHZ0hsqNSMjPTqYi9IXi1bgsRGfhUiJ6olCdxD72922kKDOg/BCrQkMHDt0SEtfH2gT1DLmwCh9eyZSuqTG5ujrm5BdIaWqw7fXq/ffXqJejVZGU/P/x1JPRYqHSIdGCsAFIgKzsn6/6DO4tD524MX1X/3hq+FdQDiHpAOfjdlJSkz5cv7N49AOwHBETgNcDjgs8Dywy9lOHDRkMT3BS+ClYhYvjmSNS06ePi4+NQw+jWzd/NrWVERNjT+Dj4rQNRu+ITnkB4/1IxiKQEfEH45tVQsTp36gbHtn7DigcP7ubkZkMfctaHkyB4RFpDi1H0tA9ml5QUbd6yhsczGjBgyJRJwdCLgBgWsubO/gQu9P4DO8A/gQfy79l7evC8f91hw7eCzhL8bvD0cfb2jsHT5kDriXscO2fee1EHokeNmrBh4xcfL5i+etXmbl17bo2I3L9/B6yyWKwWLVqFrd1aO1irH2j34Rt3QV8/9LN54IzAd6xdvaVTx64vFRMKhUuXrFnwyczTP5wcHTRh08adeyO3r1wdKpNVwOFNnTrj1TrRhDT02aSMeOndmNK3pzTi0RVoLjAgoLE/0D6gPwAdUNTMWfHFYtBmc/hupCd+2Jk+crajmXWDHk/Sook+dvzQpCkjoJsP5uva9d9B3cGDhqHmDATAYMzBwltZ26BmghZNNAxKyOWV+yK3FxcXQawLIxLvTZ2JmgNLly18/LiOG0EQHEH3z9HBKWjUBNRM0KKJbr6Aj5cr6h6wFAiEZv+Lz/VFo0w0ueFfBw3vKRk+RGDMIQJjDhEYc4jAmEMExhwiMOYQgTGHCIw5RGDMaajADCYysSS1wSCwtOch1ND3Ezb0bpKlHTfjqQQR9I1Crn6eKDGzbujrKhsqsNCMbe3MqxCTV2XpmeLcSs+OJg0v34j7wV0HWlw6mo0IeuXy8eyAEY2Yhdm41wnnZ8h++SY3YKSdqTXXSEDeW6k7JCJlWUHllejcqctchWaNeGV0o18IXpIvv/NbcdoTqakVp6ygmb0QXF2lro4Xm9ubrm2ceaX58pa+woDh1hxe4ybhvPmXz2QSNaO5PV385Zdfurq6jho1CjUrqtRVRsI3tJdv3vMxEjbDh8eZCgZLyePT6LF30rXFHCIw5hCBMYcIjDlEYMwhAmMOERhziMCYQwTGHCIw5hCBMYcIjDlEYMwhAmMOERhziMCYQwTGHCIw5hCBMYcIjDlEYMwhAmMOvQQ2Nzfn8/mITtDrw1ilpaUVFRWIThATjTlEYMwhAmMOERhziMCYQwTGHCIw5hCBMYcIjDlEYMwhAmMOERhziMCYQwTGHCIw5hCBMefN33TXjBg1alRGRgaDwVCr1UwmkzplLy+v48ePI9yhxYyOwYMHUx8Kp74DDkoLhcKpU6ciGkALgSdMmODi4lI7pWXLloGBgYgG0EJgc3PzIUOGsFgv3ucpEAjGjx+P6AFdJt0FBQW5urpSy9B8hw4diugBXQSmGjGbzaZV80W0mjY7evRoZ2dnNzc3+jRfpJtu0uPrZSkPJWp1VcHzSqRXlCoVhNAspp6rtYUdly9ktelh0srXGGkZrQv829E8njHb1sXIysGIyWpm79LXEgq5uihblhYndnQ36tjXHGkT7Qr888EcC3sj314WiFAXN8/lG5uz/Ic14isqjUWLxirhjsjYgkPUrYeew23LihQ5qVp8mkaLAqfHVzT8A120hW/MyUpungKrlFXgdxGhXiA6kYrVSGto8W5SSa6cBjcy/itqVZWkVIufnyK3CzGHCIw5RGDMIQJjDhEYc4jAmEMExhwiMOYQgTGHCIw5RGDMIQJjjgHNyXr2LLnfgC6PHj1AOqSBP7pyVWjI4jmoGYLzpLt3g97Oyc2uv4y1je3CBUscHZ0RpmBrovPycsvKSv+1mKmJ6cgRYxC+GJzAxSVFS5ctfPDgDpfLCxwyYtbM+dQDRYlJ8VFRuxISnyqVik4du82bG2Jv7wDpSqXyQNSu36/+VlJSbG5u0af327DJ47jYRSGzIXfS5BEBAX3C1kS87ufARE+fOWHH9ihf3w6wCrb6wMFdiYlPGQxGG2+fmTPnt/Fu99ImRUWF8+Z/4OvT4fOla6FYzOVfT506mp6RyucL+vcbPGP6PCMjA5rmYHAmOurg7q5den65PWrsmMknvz1y9tz3qKY5Lgr5kCNHCqUAAAyySURBVMFkbouIjNiyT1ReFvLpHLlcDlnHTxy++NvPi0NWHPrq1KKFn1/5/eLhryPh6n+xYgPkRu47uvSzNQ386czM9MWhc22sbXfvPLxrxyG+QLD40zn5+Xm1y8hksuVfhDg6OId+uhLUvXbt97B1yzp37n5g/wlI+ePPmIht65AhYXACB/j3CRo1vrWn95TJwW3b+l6KuQCJZ899B1dz+bJ17u4e3l5tP1+yNicn6+ofMZCVmprs3tKja5ceTo7OPXr02rpl35DBw2ueYBBCromJqVAobOBPnzn7HbTCpUvWtGrlCX/LloaBefj14k+aAlVVVRs2flFZKVuzeguHw4GU49GH/fw6zZzxkbOTS4/uATNnzL906cJLdUK/GJzA7X07apbbtW2fkZEGC0+fPvb2amdibEKl29nZOzg4JScnwLJ/z9737v+9Zu3S369eEpWLXF1buLi4oTciMekpVCyoHNSqQCCAXaWkJGoK7D+wE4z/xvU7jI2rJ6yr1Wow5l0699AU6ODXGVWb/SRkMBicDxYK/5nsz+fzZbLqGYcSiTgpOWHQkJ6aLIVCUVRcCAsDBw6Fxnrm7CloWyqVCgwARMUWFpao8UilEitL69opsGdIpJbjE+IexN7lcrnQgqkUMNfwi+ARvjlyoPZW1IEZCAYncIXsnzmkUqkUbCaqUR2CoJBPltUuSWUBEEbBX0VFxa2/ru3eE7E5Yu36sG2o8cCvQE2qnQKrGsk5HO7WiMht29avW798185D0NAhmIJ/g0ZNeGfou7W3Mn+j6qUlDM5EP378z5hDQuITN7eWsNCmjU9WVib0VsECU3/gkq2sqi89hDlUZxeae7++A+Fapz5L1uyhUc9teLVuC1E62AZqtVxcDg7C+39RdCt3T6/WbSByTkt/Bq0W1bwvwNPTOy8vR3NU4DhYbDZ0vZDBYHAC/3ntyuUrF3NzcyDkgU7L4EHDIHH4sNEVFdJN4avAUD9/nvHNkahp08fFx8dB1venT4ADjo29l52Tdf/BHfDEfh2qHSF1lW/dupaW9qyBPz1y5Fgwv+Fb1kA4Dd0nCI+hTVMHoAFUnDXz4xPRX1ODXxPGv/fHn5chkodN4NjWb1jx8YLpEokEGQwGZKKVKiX8Cx1c0Cx882ojI/7kSdOGBo6EROjygnncv38HXD4Wi9WiRauwtVshxoYs6A7t2bt15erQanNqZd2je68Z0z+C9Nat23Tr5r933zboMm2N2NeQA4A4fPOm3fujds6YNRF+BTaEXhn0rV8qNurdcbdu/QlaQteo91v9oU2fiD586PA+qA0+Pn6wScPjdh2gxYfPjm/M6BVkb2Fn0E+vJCcnzvxw0s4vD4I2SB+kPxFnxpcHTnNA2oHWd5NgTOrGzT9gwcraBmEK/gKDs/x8+cI6s6Cfw2SyRgwf7WDviDAFf4EhAj9+7Nzrco2FxhCQI3zBX2DoqmqGwGgImdGBOURgzCECYw4RGHOIwJhDBMYcIjDmEIExR4sCm1hwmEzy7sJ/gcVi8AQspDW0eD+YyUJlRXp++6jhU1IgNxJoUwWkNRzceZIyJSLUi7xCZePCQ1pDiwJ36m/5+HqJREQ0fi2Z8eKSvErPDlocKtfu22blMvXxTen+I+0cWgoQoRZw2VNiy1Mflr87z1GrkYrW3xetUlVdjs5PvFfu7mssEamQXqlSV78VkqHvF4KzOYznSVIff9O+Y2yRltHRh7FA5sLnlUqFnt9dGR0dbWdn169fP6RXuHymjZMW/W5tdNQPhs6AnZv+H8lScQs4pgInDz6iDWSgA3OIwJhDBMYcIjDmEIExhwiMOURgzCECYw4RGHOIwJhDBMYcIjDmEIExhwiMOURgzCECYw4RGHOIwJhDBMYcIjDmEIExhwiMOfQS2MTEhMs16FcrNjk4f1bnVcrLy6kvPdAHYqIxhwiMOURgzCECYw4RGHOIwJhDBMYcIjDmEIExhwiMOURgzCECYw4RGHOIwJhDBMYcIjDm6OhNd/olMDAwPz8f1bwhUvOdM0dHx3PnziHcocWMjr59+8K/IC2TyWTUwGKxxo0bh2gALQSeNGmSs7Nz7RQXFxciMD6AnAEBARpnBM135MiRPJ6OXgeqX+gy6W7ChAmaRuzk5DR27FhED+gisKura48ePVBN8w0KCuLz6fLCWRpNm504caJzDWPGjEG0wRC7SfJKddoTSVG2XFymkoiUanWVqonmMufm5nC4XCtLK9QU8E1YalWV0JRlbM62deG1bCdEhodhCRx3syzuVnlRdqWlszF0Zdg8FpsL/7GQQX5+CQ5KIVcp4a8S/hQlWRInT4GPv4lWP7LRWAxF4Kd/l18/U2juZGJkamRs2VwdpChfKhNVVJbLegdZu3kbxHdI9C+wWo3OROZKxVW2HpYcIxyGTitElQUpJdaO7MD37Rj6tj16Frg4t/JEeKZ7dye+KW7PhIkKJEWpJe8tc2Wx9SmyPgWWipXHNz5v1dOZgeknDisliqxHuVOXuXC4Wvw6Yf3oTeDyEkV0xHPPAFeENWqVOuFqxpzNrZCe0Fs/+PjGTPduTgh3mCymWyf7E5szkZ7QTwv+7XievEogtKTL9+7KckR2DuoegU3T/24UemjBWSkVuekK+qgLmDmYPvyjTFquh+906kHgP38otGphgWiGjYflnz8WIZ2ja4EzEyRVLLbAXP+fuasTiaR08YrusY9jUFNj4WhSlKuE0BLpFl0LnPxQyuXT4kbsqzA57LQ4CdItuhY49bHExIam3xIWWgmSYqVIt+h0aLA4T25qzeMKOEg7PM+OP//bHvhXpVR4tuo6IvATSwsHSL9x+/tfY/YHT4k4c35rfkGaQGA2oM+07p1HUFvdvH065o/DYkmJs4P3kIGzkdYwsRbk5pdBzxj6TkhX6LQFi0uVlVI10g4lpbn7vprLZDDnBO+ZHbxbKhVFHv5Ioay+0chismUy8aWrX703YcPaZTGdOww9fW5TaVn1PMtnafe/P7epfbsBi+YeHdB32rkLO5A2EZcodPyVbJ0KLBUpWVobtLv592nEYEweu9bBzsPFqe3EMauKS7IexV2mclVqZb+33jM3g9F/RrdOw1UqZXZuEqTffXDBxNjqnUEf2dq4tWnt36fXJKRN4G6KFGOBZRI1i6ctp5CR+djVqS2f/+JerIW5vaWFU1ZOoqaAo50ntSDgm1YfjKwc/s0rSHN28maxXlQ7V+d2SJtwhWwd94Z16oPh3plaoS0TXSGTZOcmfLaqlyZFpVKIygs1qxzO/4veqSG8ykqJqck/A0xcjnZvRSsr1Sy2ThuVTgUWmLJUCm0ZKCMjYUvXDmNGLqmdyOX+S8TO5fLBPWtWK2qatfZQVqrgIiAdotPaJDRjK+XaMlBuLj6FxZlWls62Ni2oPzAZpibW9W9lY+WanZesVr+wK0kpt5E2kVcohaY6bVQ6FdjClovU2jLRPbqMqqyURp9ek5WdUFCY8duVg1t2TczMiqt/q45+g8Xi4rMXtufkJT+Mu3Ln/nmkNcB6Cc04fGN8WzCcG5fPlJbKkBaALu/s4D3l4qLdUbO+3PdBQtKtaZO3uLn41r+Vl0f3EYELH8bFbN/7wdXrx8aOXIr+556bHFG+1NZF1xNXdH278M6l4uQnKntPS0Q/nj/K8w80dfc1RjpE10OVnh1MqhS6HnA3BKqfXEVqHauLdP8AuJk1x9KWVfxcZOlsWmeBMlHB5p0T6swy4hnLKsV1ZtnZtJw/Kwo1HcvXDXhdllqlZLLquG4uTm0+/GDX67bKSyr27qKHmfF6mNEhk6oOr0737utWZy6MMZWJ8uvMUigqX+rLamCxOGamNqjpKC7Jfl2WXFHJresw2Gzu64J26B09u501a31LpHP0M2XnbkxJRqrawskc0YPCZ0Ude/Fb+enhiQf9TLrrPMCCXSUX5en65qheKEorsXdh6UVdpMdZlcNnOpTnlZUX6vr+qI4pTCs14il7jdDDdDsKPT/Z8PXadHNnczN7XceWugHUNRaqhrxni/SH/p9N+ikqV67iWLpi5Y9VSnVRerG9E6v3KGukVwzi6cL7V0pv/FRo39rSytUMNX/yk4uLMkUDxtu27qz/50gN5fFRlbLq6unCvExFFWKZ2ApMrJvZvK0qdZWoQFpeIFUrFK07CnsEGspQnWE9AC4WKVMeSBLvi6Xl0B+uYnPZLC50cVmG+bY2Npslr5C/eABcobJz43t1ErbuaMziGNCLMQz0TXcKubqsUCEVqSRlSoW8Sq02SIE5DDaXAbf/4M/CjsPQ+7PAdUGLVxnSGfIyUswhAmMOERhziMCYQwTGHCIw5vwfAAAA//+6DtzUAAAABklEQVQDAFiqIpwyPw3aAAAAAElFTkSuQmCC", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from IPython.display import Image, display\n", - "\n", - "display(Image(graph.get_graph().draw_mermaid_png()))" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "cd91131a-b640-4604-9b48-b6cb5207be31", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'generate_topics': {'subjects': ['lions', 'elephants', 'penguins']}}\n", - "{'generate_joke': {'jokes': [\"Why don't lions like fast food? Because they can't catch it!\"]}}\n", - "{'generate_joke': {'jokes': [\"Why don't elephants use computers? They're afraid of the mouse!\"]}}\n", - "{'generate_joke': {'jokes': ['Why don’t penguins like talking to strangers at parties? Because they find it hard to break the ice.']}}\n", - "{'best_joke': {'best_selected_joke': 'penguins'}}\n" - ] - } - ], - "source": [ - "# Call the graph: here we call it to generate a list of jokes\n", - "for step in graph.stream({\"topic\": \"animals\"}):\n", - " print(step)" - ] - }, - { - "cell_type": "markdown", - "id": "4c505843-5449-4e9b-8ad4-27b88a987cc4", - "metadata": {}, - "source": [ - "## Create and control loops\n", - "\n", - "When creating a graph with a loop, we require a mechanism for terminating execution. This is most commonly done by adding a [conditional edge](../../concepts/low_level/#conditional-edges) that routes to the [END](../../concepts/low_level/#end-node) node once we reach some termination condition.\n", - "\n", - "You can also set the graph recursion limit when invoking or streaming the graph. The recursion limit sets the number of [supersteps](../../concepts/low_level/#graphs) that the graph is allowed to execute before it raises an error. Read more about the concept of recursion limits [here](../../concepts/low_level/#recursion-limit). \n", - "\n", - "Let's consider a simple graph with a loop to better understand how these mechanisms work.\n", - "\n", - "!!! tip\n", - "\n", - " To return the last value of your state instead of receiving a recursion limit error, see the [next section](#impose-a-recursion-limit).\n", - "\n", - "When creating a loop, you can include a conditional edge that specifies a termination condition:\n", - "```python\n", - "builder = StateGraph(State)\n", - "builder.add_node(a)\n", - "builder.add_node(b)\n", - "\n", - "def route(state: State) -> Literal[\"b\", END]:\n", - " if termination_condition(state):\n", - " return END\n", - " else:\n", - " return \"b\"\n", - "\n", - "builder.add_edge(START, \"a\")\n", - "builder.add_conditional_edges(\"a\", route)\n", - "builder.add_edge(\"b\", \"a\")\n", - "graph = builder.compile()\n", - "```\n", - "\n", - "To control the recursion limit, specify `\"recursion_limit\"` in the config. This will raise a `GraphRecursionError`, which you can catch and handle:\n", - "```python\n", - "from langgraph.errors import GraphRecursionError\n", - "\n", - "try:\n", - " graph.invoke(inputs, {\"recursion_limit\": 3})\n", - "except GraphRecursionError:\n", - " print(\"Recursion Error\")\n", - "```" - ] - }, - { - "cell_type": "markdown", - "id": "2de7cdff-3811-4d19-b93b-7b8dfbbdb4f1", - "metadata": {}, - "source": [ - "Let's define a graph with a simple loop. Note that we use a conditional edge to implement a termination condition." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "f087c028-b115-42a0-a85d-f53d96223720", - "metadata": {}, - "outputs": [], - "source": [ - "import operator\n", - "from typing import Annotated, Literal\n", - "\n", - "from typing_extensions import TypedDict\n", - "\n", - "from langgraph.graph import StateGraph, START, END\n", - "\n", - "\n", - "class State(TypedDict):\n", - " # The operator.add reducer fn makes this append-only\n", - " aggregate: Annotated[list, operator.add]\n", - "\n", - "\n", - "def a(state: State):\n", - " print(f'Node A sees {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"A\"]}\n", - "\n", - "\n", - "def b(state: State):\n", - " print(f'Node B sees {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"B\"]}\n", - "\n", - "\n", - "# Define nodes\n", - "builder = StateGraph(State)\n", - "builder.add_node(a)\n", - "builder.add_node(b)\n", - "\n", - "\n", - "# Define edges\n", - "def route(state: State) -> Literal[\"b\", END]:\n", - " if len(state[\"aggregate\"]) < 7:\n", - " return \"b\"\n", - " else:\n", - " return END\n", - "\n", - "\n", - "builder.add_edge(START, \"a\")\n", - "builder.add_conditional_edges(\"a\", route)\n", - "builder.add_edge(\"b\", \"a\")\n", - "graph = builder.compile()" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "c468e5b2-a1dd-4fac-84a9-9eb212a09752", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from IPython.display import Image, display\n", - "\n", - "display(Image(graph.get_graph().draw_mermaid_png()))" - ] - }, - { - "cell_type": "markdown", - "id": "255d288a-6e17-4f34-babe-0c6cf1e09a6f", - "metadata": {}, - "source": [ - "This architecture is similar to a [ReAct agent](../../agents/overview) in which node `\"a\"` is a tool-calling model, and node `\"b\"` represents the tools.\n", - "\n", - "In our `route` conditional edge, we specify that we should end after the `\"aggregate\"` list in the state passes a threshold length.\n", - "\n", - "Invoking the graph, we see that we alternate between nodes `\"a\"` and `\"b\"` before terminating once we reach the termination condition." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "83c759be-9bb7-4f96-8b79-028fe1ebb45f", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Node A sees []\n", - "Node B sees ['A']\n", - "Node A sees ['A', 'B']\n", - "Node B sees ['A', 'B', 'A']\n", - "Node A sees ['A', 'B', 'A', 'B']\n", - "Node B sees ['A', 'B', 'A', 'B', 'A']\n", - "Node A sees ['A', 'B', 'A', 'B', 'A', 'B']\n" - ] - }, - { - "data": { - "text/plain": [ - "{'aggregate': ['A', 'B', 'A', 'B', 'A', 'B', 'A']}" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "graph.invoke({\"aggregate\": []})" - ] - }, - { - "cell_type": "markdown", - "id": "8c596264-9a36-4c52-ba7d-9fa5dcb3467d", - "metadata": {}, - "source": [ - "### Impose a recursion limit\n", - "\n", - "In some applications, we may not have a guarantee that we will reach a given termination condition. In these cases, we can set the graph's [recursion limit](../../concepts/low_level/#recursion-limit). This will raise a `GraphRecursionError` after a given number of [supersteps](../../concepts/low_level/#graphs). We can then catch and handle this exception:" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "f7526e3c-357c-4eba-b101-751418523672", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Node A sees []\n", - "Node B sees ['A']\n", - "Node A sees ['A', 'B']\n", - "Node B sees ['A', 'B', 'A']\n", - "Recursion Error\n" - ] - } - ], - "source": [ - "from langgraph.errors import GraphRecursionError\n", - "\n", - "try:\n", - " graph.invoke({\"aggregate\": []}, {\"recursion_limit\": 4})\n", - "except GraphRecursionError:\n", - " print(\"Recursion Error\")" - ] - }, - { - "cell_type": "markdown", - "id": "0793b71a-fd92-4284-8d58-cc10f49872f6", - "metadata": {}, - "source": [ - "Note that this time we terminate after the fourth step. The default recursion limit is 25.\n", - "\n", - "
Extended example: return state on hitting recursion limit\n", - "\n", - "Instead of raising GraphRecursionError, we can introduce a new key to the state that keeps track of the number of steps remaining until reaching the recursion limit. We can then use this key to determine if we should end the run.\n", - "\n", - "LangGraph implements a special RemainingSteps annotation. Under the hood, it creates a ManagedValue channel -- a state channel that will exist for the duration of our graph run and no longer.\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "7fe57f1a-ab55-45ed-b229-8f29fc3da05b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Node A sees []\n", - "Node B sees ['A']\n", - "Node A sees ['A', 'B']\n", - "{'aggregate': ['A', 'B', 'A']}\n" - ] - } - ], - "source": [ - "import operator\n", - "from typing import Annotated, Literal\n", - "\n", - "from typing_extensions import TypedDict\n", - "\n", - "from langgraph.graph import StateGraph, START, END\n", - "\n", - "# highlight-next-line\n", - "from langgraph.managed.is_last_step import RemainingSteps\n", - "\n", - "\n", - "class State(TypedDict):\n", - " # The operator.add reducer fn makes this append-only\n", - " aggregate: Annotated[list, operator.add]\n", - " # highlight-next-line\n", - " remaining_steps: RemainingSteps\n", - "\n", - "\n", - "def a(state: State):\n", - " print(f'Node A sees {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"A\"]}\n", - "\n", - "\n", - "def b(state: State):\n", - " print(f'Node B sees {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"B\"]}\n", - "\n", - "\n", - "# Define nodes\n", - "builder = StateGraph(State)\n", - "builder.add_node(a)\n", - "builder.add_node(b)\n", - "\n", - "\n", - "# Define edges\n", - "def route(state: State) -> Literal[\"b\", END]:\n", - " # highlight-next-line\n", - " if state[\"remaining_steps\"] <= 2:\n", - " return END\n", - " else:\n", - " return \"b\"\n", - "\n", - "\n", - "builder.add_edge(START, \"a\")\n", - "builder.add_conditional_edges(\"a\", route)\n", - "builder.add_edge(\"b\", \"a\")\n", - "graph = builder.compile()\n", - "\n", - "# Test it out\n", - "result = graph.invoke({\"aggregate\": []}, {\"recursion_limit\": 4})\n", - "print(result)" - ] - }, - { - "cell_type": "markdown", - "id": "6c9e1818-079a-41bb-aed0-2bf993ca943f", - "metadata": {}, - "source": [ - "
" - ] - }, - { - "cell_type": "markdown", - "id": "308d93f4-6e78-411d-82de-78eac230e44d", - "metadata": {}, - "source": [ - "
Extended example: loops with branches\n", - "\n", - "To better understand how the recursion limit works, let's consider a more complex example. Below we implement a loop, but one step fans out into two nodes:\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "258d8613-8572-407a-941a-2ac50b8f1c3e", - "metadata": {}, - "outputs": [], - "source": [ - "import operator\n", - "from typing import Annotated, Literal\n", - "\n", - "from typing_extensions import TypedDict\n", - "\n", - "from langgraph.graph import StateGraph, START, END\n", - "\n", - "\n", - "class State(TypedDict):\n", - " aggregate: Annotated[list, operator.add]\n", - "\n", - "\n", - "def a(state: State):\n", - " print(f'Node A sees {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"A\"]}\n", - "\n", - "\n", - "def b(state: State):\n", - " print(f'Node B sees {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"B\"]}\n", - "\n", - "\n", - "def c(state: State):\n", - " print(f'Node C sees {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"C\"]}\n", - "\n", - "\n", - "def d(state: State):\n", - " print(f'Node D sees {state[\"aggregate\"]}')\n", - " return {\"aggregate\": [\"D\"]}\n", - "\n", - "\n", - "# Define nodes\n", - "builder = StateGraph(State)\n", - "builder.add_node(a)\n", - "builder.add_node(b)\n", - "builder.add_node(c)\n", - "builder.add_node(d)\n", - "\n", - "\n", - "# Define edges\n", - "def route(state: State) -> Literal[\"b\", END]:\n", - " if len(state[\"aggregate\"]) < 7:\n", - " return \"b\"\n", - " else:\n", - " return END\n", - "\n", - "\n", - "builder.add_edge(START, \"a\")\n", - "builder.add_conditional_edges(\"a\", route)\n", - "builder.add_edge(\"b\", \"c\")\n", - "builder.add_edge(\"b\", \"d\")\n", - "builder.add_edge([\"c\", \"d\"], \"a\")\n", - "graph = builder.compile()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "bdb2a545-3f1f-408b-8aa3-3702d37eedf8", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from IPython.display import Image, display\n", - "\n", - "display(Image(graph.get_graph().draw_mermaid_png()))" - ] - }, - { - "cell_type": "markdown", - "id": "a1d4cc42-590c-4de9-9e51-0bb8a79db86f", - "metadata": {}, - "source": [ - "This graph looks complex, but can be conceptualized as loop of [supersteps](../../concepts/low_level/#graphs):\n", - "\n", - "1. Node A\n", - "2. Node B\n", - "3. Nodes C and D\n", - "4. Node A\n", - "5. ...\n", - "\n", - "We have a loop of four supersteps, where nodes C and D are executed concurrently.\n", - "\n", - "Invoking the graph as before, we see that we complete two full \"laps\" before hitting the termination condition:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "d5c692d0-9a69-4743-bd47-e462adab8700", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Node A sees []\n", - "Node B sees ['A']\n", - "Node D sees ['A', 'B']\n", - "Node C sees ['A', 'B']\n", - "Node A sees ['A', 'B', 'C', 'D']\n", - "Node B sees ['A', 'B', 'C', 'D', 'A']\n", - "Node D sees ['A', 'B', 'C', 'D', 'A', 'B']\n", - "Node C sees ['A', 'B', 'C', 'D', 'A', 'B']\n", - "Node A sees ['A', 'B', 'C', 'D', 'A', 'B', 'C', 'D']\n" - ] - } - ], - "source": [ - "result = graph.invoke({\"aggregate\": []})" - ] - }, - { - "cell_type": "markdown", - "id": "42cb9253-93a9-4a33-b4fb-a235aa41d655", - "metadata": {}, - "source": [ - "However, if we set the recursion limit to four, we only complete one lap because each lap is four supersteps:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "d0ff64b3-eb78-48a4-aab5-bb78499f92df", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Node A sees []\n", - "Node B sees ['A']\n", - "Node C sees ['A', 'B']\n", - "Node D sees ['A', 'B']\n", - "Node A sees ['A', 'B', 'C', 'D']\n", - "Recursion Error\n" - ] - } - ], - "source": [ - "from langgraph.errors import GraphRecursionError\n", - "\n", - "try:\n", - " result = graph.invoke({\"aggregate\": []}, {\"recursion_limit\": 4})\n", - "except GraphRecursionError:\n", - " print(\"Recursion Error\")" - ] - }, - { - "cell_type": "markdown", - "id": "13579366-69fb-4aa4-9d95-a9865c1d5799", - "metadata": {}, - "source": [ - "
" - ] - }, - { - "cell_type": "markdown", - "id": "5a2d23ae-ea3f-478b-8db6-791cd29cfb6c", - "metadata": {}, - "source": [ - "## Async\n", - "\n", - "Using the [async](https://docs.python.org/3/library/asyncio.html) programming paradigm can produce significant performance improvements when running [IO-bound](https://en.wikipedia.org/wiki/I/O_bound) code concurrently (e.g., making concurrent API requests to a chat model provider).\n", - "\n", - "To convert a `sync` implementation of the graph to an `async` implementation, you will need to:\n", - "\n", - "1. Update `nodes` use `async def` instead of `def`.\n", - "2. Update the code inside to use `await` appropriately.\n", - "3. Invoke the graph with `.ainvoke` or `.astream` as desired.\n", - "\n", - "Because many LangChain objects implement the [Runnable Protocol](https://python.langchain.com/docs/expression_language/interface/) which has `async` variants of all the `sync` methods it's typically fairly quick to upgrade a `sync` graph to an `async` graph.\n", - "\n", - "See example below. To demonstrate async invocations of underlying LLMs, we will include a chat model:\n", - "\n", - "{!snippets/chat_model_tabs.md!}\n", - "\n", - "```python\n", - "from langchain.chat_models import init_chat_model\n", - "from langgraph.graph import MessagesState, StateGraph\n", - "\n", - "\n", - "# highlight-next-line\n", - "async def node(state: MessagesState): # (1)!\n", - " # highlight-next-line\n", - " new_message = await llm.ainvoke(state[\"messages\"]) # (2)!\n", - " return {\"messages\": [new_message]}\n", - "\n", - "\n", - "builder = StateGraph(MessagesState).add_node(node).set_entry_point(\"node\")\n", - "graph = builder.compile()\n", - "\n", - "input_message = {\"role\": \"user\", \"content\": \"Hello\"}\n", - "# highlight-next-line\n", - "result = await graph.ainvoke({\"messages\": [input_message]}) # (3)!\n", - "```\n", - "\n", - "1. Declare nodes to be async functions.\n", - "2. Use async invocations when available within the node.\n", - "3. Use async invocations on the graph object itself.\n", - "\n", - "!!! tip \"Async streaming\"\n", - " See the [streaming guide](../../how-tos/streaming) for examples of streaming with async." - ] - }, - { - "cell_type": "markdown", - "id": "d33ecddc-6818-41a3-9d0d-b1b1cbcd286d", - "metadata": {}, - "source": [ - "## Combine control flow and state updates with `Command`" - ] - }, - { - "cell_type": "markdown", - "id": "7c0a8d03-80b4-47fd-9b17-e26aa9b081f3", - "metadata": {}, - "source": [ - "It can be useful to combine control flow (edges) and state updates (nodes). For example, you might want to BOTH perform state updates AND decide which node to go to next in the SAME node. LangGraph provides a way to do so by returning a [Command](/langgraph/reference/types/#langgraph.types.Command) object from node functions:\n", - "\n", - "```python\n", - "def my_node(state: State) -> Command[Literal[\"my_other_node\"]]:\n", - " return Command(\n", - " # state update\n", - " update={\"foo\": \"bar\"},\n", - " # control flow\n", - " goto=\"my_other_node\"\n", - " )\n", - "```\n", - "\n", - "We show an end-to-end example below. Let's create a simple graph with 3 nodes: A, B and C. We will first execute node A, and then decide whether to go to Node B or Node C next based on the output of node A." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "4539b81b-09e9-4660-ac55-1b1775e13892", - "metadata": {}, - "outputs": [], - "source": [ - "import random\n", - "from typing_extensions import TypedDict, Literal\n", - "\n", - "from langgraph.graph import StateGraph, START\n", - "from langgraph.types import Command\n", - "\n", - "\n", - "# Define graph state\n", - "class State(TypedDict):\n", - " foo: str\n", - "\n", - "\n", - "# Define the nodes\n", - "\n", - "\n", - "def node_a(state: State) -> Command[Literal[\"node_b\", \"node_c\"]]:\n", - " print(\"Called A\")\n", - " value = random.choice([\"a\", \"b\"])\n", - " # this is a replacement for a conditional edge function\n", - " if value == \"a\":\n", - " goto = \"node_b\"\n", - " else:\n", - " goto = \"node_c\"\n", - "\n", - " # note how Command allows you to BOTH update the graph state AND route to the next node\n", - " return Command(\n", - " # this is the state update\n", - " update={\"foo\": value},\n", - " # this is a replacement for an edge\n", - " goto=goto,\n", - " )\n", - "\n", - "\n", - "def node_b(state: State):\n", - " print(\"Called B\")\n", - " return {\"foo\": state[\"foo\"] + \"b\"}\n", - "\n", - "\n", - "def node_c(state: State):\n", - " print(\"Called C\")\n", - " return {\"foo\": state[\"foo\"] + \"c\"}" - ] - }, - { - "cell_type": "markdown", - "id": "badc25eb-4876-482e-bb10-d763023cdaad", - "metadata": {}, - "source": [ - "We can now create the `StateGraph` with the above nodes. Notice that the graph doesn't have [conditional edges](../../concepts/low_level#conditional-edges) for routing! This is because control flow is defined with `Command` inside `node_a`." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "d6711650-4380-4551-a007-2805f49ab2d8", - "metadata": {}, - "outputs": [], - "source": [ - "builder = StateGraph(State)\n", - "builder.add_edge(START, \"node_a\")\n", - "builder.add_node(node_a)\n", - "builder.add_node(node_b)\n", - "builder.add_node(node_c)\n", - "# NOTE: there are no edges between nodes A, B and C!\n", - "\n", - "graph = builder.compile()" - ] - }, - { - "cell_type": "markdown", - "id": "0ab344c5-d634-4d7d-b3b4-edf4fa875311", - "metadata": {}, - "source": [ - "!!! important\n", - "\n", - " You might have noticed that we used `Command` as a return type annotation, e.g. `Command[Literal[\"node_b\", \"node_c\"]]`. This is necessary for the graph rendering and tells LangGraph that `node_a` can navigate to `node_b` and `node_c`." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "eeb810e5-8822-4c09-8d53-c55cd0f5d42e", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from IPython.display import display, Image\n", - "\n", - "display(Image(graph.get_graph().draw_mermaid_png()))" - ] - }, - { - "cell_type": "markdown", - "id": "58fb6c32-e6fb-4c94-8182-e351ed52a45d", - "metadata": {}, - "source": [ - "If we run the graph multiple times, we'd see it take different paths (A -> B or A -> C) based on the random choice in node A." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "d88a5d9b-ee08-4ed4-9c65-6e868210bfac", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Called A\n", - "Called C\n" - ] - }, - { - "data": { - "text/plain": [ - "{'foo': 'bc'}" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "graph.invoke({\"foo\": \"\"})" - ] - }, - { - "cell_type": "markdown", - "id": "68986cc4-97ec-43a1-b95d-5273d7ffc25a", - "metadata": {}, - "source": [ - "### Navigate to a node in a parent graph\n", - "\n", - "If you are using [subgraphs](../../concepts/subgraphs), you might want to navigate from a node within a subgraph to a different subgraph (i.e. a different node in the parent graph). To do so, you can specify `graph=Command.PARENT` in `Command`:\n", - "\n", - "```python\n", - "def my_node(state: State) -> Command[Literal[\"my_other_node\"]]:\n", - " return Command(\n", - " update={\"foo\": \"bar\"},\n", - " goto=\"other_subgraph\", # where `other_subgraph` is a node in the parent graph\n", - " graph=Command.PARENT\n", - " )\n", - "```" - ] - }, - { - "cell_type": "markdown", - "id": "02ccddf2-978c-41bf-b2eb-2d0c4b3f5d81", - "metadata": {}, - "source": [ - "Let's demonstrate this using the above example. We'll do so by changing `node_a` in the above example into a single-node graph that we'll add as a subgraph to our parent graph.\n", - "\n", - "!!! important \"State updates with `Command.PARENT`\"\n", - "\n", - " When you send updates from a subgraph node to a parent graph node for a key that's shared by both parent and subgraph [state schemas](../../concepts/low_level#schema), you **must** define a [reducer](../../concepts/low_level#reducers) for the key you're updating in the parent graph state. See the example below." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "91351541-67af-4c73-9437-426599dcf81e", - "metadata": {}, - "outputs": [], - "source": [ - "import operator\n", - "from typing_extensions import Annotated\n", - "\n", - "\n", - "class State(TypedDict):\n", - " # NOTE: we define a reducer here\n", - " # highlight-next-line\n", - " foo: Annotated[str, operator.add]\n", - "\n", - "\n", - "def node_a(state: State):\n", - " print(\"Called A\")\n", - " value = random.choice([\"a\", \"b\"])\n", - " # this is a replacement for a conditional edge function\n", - " if value == \"a\":\n", - " goto = \"node_b\"\n", - " else:\n", - " goto = \"node_c\"\n", - "\n", - " # note how Command allows you to BOTH update the graph state AND route to the next node\n", - " return Command(\n", - " update={\"foo\": value},\n", - " goto=goto,\n", - " # this tells LangGraph to navigate to node_b or node_c in the parent graph\n", - " # NOTE: this will navigate to the closest parent graph relative to the subgraph\n", - " # highlight-next-line\n", - " graph=Command.PARENT,\n", - " )\n", - "\n", - "\n", - "subgraph = StateGraph(State).add_node(node_a).add_edge(START, \"node_a\").compile()\n", - "\n", - "\n", - "def node_b(state: State):\n", - " print(\"Called B\")\n", - " # NOTE: since we've defined a reducer, we don't need to manually append\n", - " # new characters to existing 'foo' value. instead, reducer will append these\n", - " # automatically (via operator.add)\n", - " # highlight-next-line\n", - " return {\"foo\": \"b\"}\n", - "\n", - "\n", - "def node_c(state: State):\n", - " print(\"Called C\")\n", - " # highlight-next-line\n", - " return {\"foo\": \"c\"}" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "beb61d02-c868-4c2b-b83f-1dfd280f1c8e", - "metadata": {}, - "outputs": [], - "source": [ - "builder = StateGraph(State)\n", - "builder.add_edge(START, \"subgraph\")\n", - "builder.add_node(\"subgraph\", subgraph)\n", - "builder.add_node(node_b)\n", - "builder.add_node(node_c)\n", - "\n", - "graph = builder.compile()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "3f07b704-1fe2-48a3-ad40-c9bc7698cb1c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Called A\n", - "Called C\n" - ] - }, - { - "data": { - "text/plain": [ - "{'foo': 'bc'}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "graph.invoke({\"foo\": \"\"})" - ] - }, - { - "cell_type": "markdown", - "id": "bcd31ceb-f96f-4325-878d-ae1dea8cde8a", - "metadata": {}, - "source": [ - "### Use inside tools\n", - "\n", - "A common use case is updating graph state from inside a tool. For example, in a customer support application you might want to look up customer information based on their account number or ID in the beginning of the conversation. To update the graph state from the tool, you can return `Command(update={\"my_custom_key\": \"foo\", \"messages\": [...]})` from the tool:\n", - "\n", - "```python\n", - "@tool\n", - "def lookup_user_info(tool_call_id: Annotated[str, InjectedToolCallId], config: RunnableConfig):\n", - " \"\"\"Use this to look up user information to better assist them with their questions.\"\"\"\n", - " user_info = get_user_info(config.get(\"configurable\", {}).get(\"user_id\"))\n", - " return Command(\n", - " update={\n", - " # update the state keys\n", - " \"user_info\": user_info,\n", - " # update the message history\n", - " \"messages\": [ToolMessage(\"Successfully looked up user information\", tool_call_id=tool_call_id)]\n", - " }\n", - " )\n", - "```\n", - "\n", - "!!! important\n", - " You MUST include `messages` (or any state key used for the message history) in `Command.update` when returning `Command` from a tool and the list of messages in `messages` MUST contain a `ToolMessage`. This is necessary for the resulting message history to be valid (LLM providers require AI messages with tool calls to be followed by the tool result messages).\n", - "\n", - "If you are using tools that update state via `Command`, we recommend using prebuilt [`ToolNode`][langgraph.prebuilt.tool_node.ToolNode] which automatically handles tools returning `Command` objects and propagates them to the graph state. If you're writing a custom node that calls tools, you would need to manually propagate `Command` objects returned by the tools as the update from the node." - ] - }, - { - "cell_type": "markdown", - "id": "8bcd1a3d-7c50-4f58-be4e-1ed654aa33be", - "metadata": {}, - "source": [ - "## Visualize your graph\n", - "\n", - "Here we demonstrate how to visualize the graphs you create." - ] - }, - { - "cell_type": "markdown", - "id": "e130cf70-a30e-47d7-8fd5-464f1a92e374", - "metadata": {}, - "source": [ - "You can visualize any arbitrary [Graph](https://langchain-ai.github.io/langgraph/reference/graphs/), including [StateGraph](https://langchain-ai.github.io/langgraph/reference/graphs/#langgraph.graph.state.StateGraph). Let's have some fun by drawing fractals :)." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "6d604311", - "metadata": {}, - "outputs": [], - "source": [ - "import random\n", - "from typing import Annotated, Literal\n", - "\n", - "from typing_extensions import TypedDict\n", - "\n", - "from langgraph.graph import StateGraph, START, END\n", - "from langgraph.graph.message import add_messages\n", - "\n", - "\n", - "class State(TypedDict):\n", - " messages: Annotated[list, add_messages]\n", - "\n", - "\n", - "class MyNode:\n", - " def __init__(self, name: str):\n", - " self.name = name\n", - "\n", - " def __call__(self, state: State):\n", - " return {\"messages\": [(\"assistant\", f\"Called node {self.name}\")]}\n", - "\n", - "\n", - "def route(state) -> Literal[\"entry_node\", \"__end__\"]:\n", - " if len(state[\"messages\"]) > 10:\n", - " return \"__end__\"\n", - " return \"entry_node\"\n", - "\n", - "\n", - "def add_fractal_nodes(builder, current_node, level, max_level):\n", - " if level > max_level:\n", - " return\n", - "\n", - " # Number of nodes to create at this level\n", - " num_nodes = random.randint(1, 3) # Adjust randomness as needed\n", - " for i in range(num_nodes):\n", - " nm = [\"A\", \"B\", \"C\"][i]\n", - " node_name = f\"node_{current_node}_{nm}\"\n", - " builder.add_node(node_name, MyNode(node_name))\n", - " builder.add_edge(current_node, node_name)\n", - "\n", - " # Recursively add more nodes\n", - " r = random.random()\n", - " if r > 0.2 and level + 1 < max_level:\n", - " add_fractal_nodes(builder, node_name, level + 1, max_level)\n", - " elif r > 0.05:\n", - " builder.add_conditional_edges(node_name, route, node_name)\n", - " else:\n", - " # End\n", - " builder.add_edge(node_name, \"__end__\")\n", - "\n", - "\n", - "def build_fractal_graph(max_level: int):\n", - " builder = StateGraph(State)\n", - " entry_point = \"entry_node\"\n", - " builder.add_node(entry_point, MyNode(entry_point))\n", - " builder.add_edge(START, entry_point)\n", - "\n", - " add_fractal_nodes(builder, entry_point, 1, max_level)\n", - "\n", - " # Optional: set a finish point if required\n", - " builder.add_edge(entry_point, END) # or any specific node\n", - "\n", - " return builder.compile()\n", - "\n", - "\n", - "app = build_fractal_graph(3)" - ] - }, - { - "cell_type": "markdown", - "id": "edcd9ad2", - "metadata": { - "ExecuteTime": { - "end_time": "2024-04-18T12:18:30.629307Z", - "start_time": "2024-04-18T12:18:30.609323Z" - } - }, - "source": [ - "### Mermaid\n", - "\n", - "We can also convert a graph class into Mermaid syntax." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "66007b2d", - "metadata": { - "ExecuteTime": { - "end_time": "2024-04-19T11:25:38.733126Z", - "start_time": "2024-04-19T11:25:38.726838Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "%%{init: {'flowchart': {'curve': 'linear'}}}%%\n", - "graph TD;\n", - "\t__start__([

__start__

]):::first\n", - "\tentry_node(entry_node)\n", - "\tnode_entry_node_A(node_entry_node_A)\n", - "\tnode_entry_node_B(node_entry_node_B)\n", - "\tnode_node_entry_node_B_A(node_node_entry_node_B_A)\n", - "\tnode_node_entry_node_B_B(node_node_entry_node_B_B)\n", - "\tnode_node_entry_node_B_C(node_node_entry_node_B_C)\n", - "\t__end__([

__end__

]):::last\n", - "\t__start__ --> entry_node;\n", - "\tentry_node --> __end__;\n", - "\tentry_node --> node_entry_node_A;\n", - "\tentry_node --> node_entry_node_B;\n", - "\tnode_entry_node_B --> node_node_entry_node_B_A;\n", - "\tnode_entry_node_B --> node_node_entry_node_B_B;\n", - "\tnode_entry_node_B --> node_node_entry_node_B_C;\n", - "\tnode_entry_node_A -.-> entry_node;\n", - "\tnode_entry_node_A -.-> __end__;\n", - "\tnode_node_entry_node_B_A -.-> entry_node;\n", - "\tnode_node_entry_node_B_A -.-> __end__;\n", - "\tnode_node_entry_node_B_B -.-> entry_node;\n", - "\tnode_node_entry_node_B_B -.-> __end__;\n", - "\tnode_node_entry_node_B_C -.-> entry_node;\n", - "\tnode_node_entry_node_B_C -.-> __end__;\n", - "\tclassDef default fill:#f2f0ff,line-height:1.2\n", - "\tclassDef first fill-opacity:0\n", - "\tclassDef last fill:#bfb6fc\n", - "\n" - ] - } - ], - "source": [ - "print(app.get_graph().draw_mermaid())" - ] - }, - { - "cell_type": "markdown", - "id": "8f77ad75", - "metadata": {}, - "source": [ - "### PNG\n", - "\n", - "If preferred, we could render the Graph into a `.png`. Here we could use three options:\n", - "\n", - "- Using Mermaid.ink API (does not require additional packages)\n", - "- Using Mermaid + Pyppeteer (requires `pip install pyppeteer`)\n", - "- Using graphviz (which requires `pip install graphviz`)\n", - "\n", - "\n", - "**Using Mermaid.Ink**\n", - "\n", - "By default, `draw_mermaid_png()` uses Mermaid.Ink's API to generate the diagram." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "967f116d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/jpeg": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from IPython.display import Image, display\n", - "from langchain_core.runnables.graph import CurveStyle, MermaidDrawMethod, NodeStyles\n", - "\n", - "display(Image(app.get_graph().draw_mermaid_png()))" - ] - }, - { - "cell_type": "markdown", - "id": "b9e767fc", - "metadata": { - "ExecuteTime": { - "end_time": "2024-04-18T12:18:30.873950Z", - "start_time": "2024-04-18T12:18:30.871750Z" - } - }, - "source": [ - "**Using Mermaid + Pyppeteer**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d403e1e7", - "metadata": { - "ExecuteTime": { - "end_time": "2024-04-19T11:25:44.798703Z", - "start_time": "2024-04-19T11:25:44.793438Z" - } - }, - "outputs": [], - "source": [ - "%%capture --no-stderr\n", - "%pip install --quiet pyppeteer\n", - "%pip install --quiet nest_asyncio" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "058546ee", - "metadata": { - "ExecuteTime": { - "end_time": "2024-04-19T11:25:47.412695Z", - "start_time": "2024-04-19T11:25:45.405158Z" - } - }, - "outputs": [ - { - "data": { - "image/png": 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H9cQTva3jtWr5W+dXN2r06Inq1q2PdfvYsSPW95C9zqNudL4qXXnPzp37ts2Yh4enXnnl3TwFWNu2bdSMGZNtxpYunZfv3IR51BUrVy7WypWLr3pMvXoN9eKLb6paterFlAoASo/g4GDdddddql+/vukoAAAAQIHYTRUSK06VXh4ennrrrQXq3Lm7TTGSk5OTevXqp4CA1jbHHz0ak+cxPv54js22r28tvfXWApsTh5Lk6uqqYcPGqFevfjbjixa9J4vFYjO2fftGHT58wGbsuede0siR421yXnm+mnrnnUXX+EqlL75YqmPHjli3K1euqvfeW5rnZL905QOLt99elOfq4b9+sFHY9u2LynPF+X/+s1g9ejyc5/uzQoWKmjjxZXXt+pDN+KJF713zeZ56apyGDRtjcxJaklq0aKX+/R+3GTtw4Jfr+RJuWMeOD+rZZyfbFPn4+FRWjRq1rLeDgjrY3Gfr1vV/+3iRkT/YbN9xR3Ob4qXi0KFDV73yyrt5nrd6dV+NGDHOZiwjI11//JFkM3b06OE8LSDGjPl3nqIpSapdu57ef9/2av6TJxO0YcNqm7GEhON53sdduz6kN974MM/3rIeHh6ZMmaV69Rpe5auUzp8/p7femm4zFhIyViNHjrc52S9d+TnQv/8Tev75l23GN29eq/j4a7fQKCw7dnxr84HL3Xffb/1++Otqahs3hikzM7PYsgEA7IPFYlFISIhCQkK0Y8e1PxyHYymp86hly+blyfnee0vzXTGoTZt7NXnyjGt8pcyjchXGa14Unn12sk3RlHTldcj929Ye51E3O19dv/6/eVYemz37o3xXrWrf/h968cU3bMY2b16r336zff2YR12f3r3/KW/viqZjAIBD6tmzp4YPH6727dubjgIAAAAUiN0VTrHiVOnTvXuffE8e5vrHP4JtthMTT9psnzgRr2+/DbcZ69//8Twn+f7sryf8U1LOKipql3XbYrFo3rx3bI65775OV736t2rVW+Xh4fm3+y0Wi82VmZI0adJrKl/e+2/v4+bmpqefnmgzFhPzf+zdeVid9Z3//xdw2EmAhJAQ9n1fsplEq6bG2Fij1Wqt1lrHperYdrpo/fb7q9N2Wmem029rp5d2GuvSxWVqjTa2UaPGNDqxJlUTOOxLCAkQSCBsgUDCcn5/MNxycyBAWO7D4fm4Lq6c+z6fc/M+wCF87vO635/SMcdPh9/9bqtp+447vjJup5s77/yq6bm3tbWOurzhkOTkNH3mM58f8/6NGz9t2m5uPmF0pZtJd9zxlXHHjPx53LnzFeP310gjfy43bdpy/sWdp/vue0A+Pj6j3peZmeu07EpT03HT9iuvvGDaDgsLP+fzWLJkqa688lrTvldfNS8B+PTTj5m2Q0JCde+933LqdDXE19dXERHnfqPkL3950RRCWrVqndPrfKRPfvJTTksMHj1afc7HTKcdO14ybV922WbjdkpKhmkpjO7u005vIAEAgPnNFedRg6F7c2j+zju/qpSU9DGPGRUVO+Z9EvOo4ab6PZ8J8fFJE5rnzKV51HTMV5999gnT9qZNWxQXlzjmMdevv9RpbrZr16umbeZRk/Mf//E93XzzZr3//jtWlwIAAAC4pW984xtavXq1vvGNb1hdCgCMa86kkAhOzV8jrzoeaeTJw2PHak3bdXVHTNshIaG69NIrxj3m2rWfGHHcOuP2oUPlTiesb7vtH895zPGMrDsyMkaZmbnjPm7kmKNHD6u3t3dKtYzF4XA4vaFw+eVXjfu4BQsWKidnpWlfbW3NedcRFhbutK+treW8jzcRGzd+etTPO9LKlWtNgZaGhnoVFeU7jevq6nQ64T/yKuvZMN7ra+SV+CdPNpm2h1/ZL0k33fQPY56YHzIyOHX4cJUcDoekweUd9u7dbbr/rrv+SX5+fuc85niqqspN26N1NBjJw8NDF1xwkWlfTc2hKdUxUbW1NSoo+NC0b82aj2vx8vLShg2fMt3/5ps7ZqU2AAAwN7jiPGpk0DsiIlKbN5v/Npws5lEfm+r3fCZce+1NE+ocPtfmUecy3ny1q6vT6XzCZz/7hXMe08vLS1u23GDaN7yLE/Mosw0brtB//Md/6ZFHntRPf/prffe7/6577/2WPvnJzaZx3d2n9YMfPKAXX/z9GEcCAAAAAADzwbnf3XYhQ2+qD/0LDAkODjVtjzwB2dBQZ9pOTc0as8POcHFxidq/f++w49Qbt0e21M/JWWUs13a+jhwxX4FZX39UDz309fM6VmNjvaKj46ZUz2iam0+YrjaVpJ///OEJPfaDD8xvktTVHVF29orzriUsLFzNzSeM7VOnOpyWH5hOsbHx4w/S4PIEW7Zcr2effdLYt2vXq05veAz/2ZIGO5ad66p4q4SGLjZtnzrVbtx2OBxOy1WOd9W8NHrXgJaWk1q8OEzHjztf9T4yIHQ+Dh82L2Px/PNP6c03/zLu40a+wXX06PkH/iZjZG2bNm2Rv7+/ad+FF16q7dv/YGy///47amk5qUWLzN8zAACA0Vgxj6qtNYexNm3aYloG+3wwj5q48b7nM2GiX093m0eda746PEw4JD4+adxjjryoZXi4kXmUWVRUjPLy1ox632233atHH/2xPvro4yVsn3zyUa1bd8mMvP4BAAAAAIDrmzPBKWAs51oqQjJfhSlJS5dGTOi4I0M4w8NSI6/yHXkC83zU1h522jfyJPlEeXjMTGe20a5uPt8ap9o9LjR0kelE9ExbunT5hMdu3HiV6YT/G2/8Wffc803Tz+qePW+aHjN8GTZXcq43IVpaTjrtW7x4/K5co71mT5xo0OLFYU6dDSIiIqf8ZlpPT4/pDTtpsMvVyG5ZEzEbXQ/PnDmjv/xlm2nfpZduchqXmZknf/8A05twe/e+rWuuuXHGawQAzA1+fn768pe/LElKSUmxuBq4GivmUTU15r+/IiOndvGJxDxqMsb7ns+Eif7cSO41jzrXfHVkKDEyMmbcLk6DxzRfIFFff1R9fX2y2WzMoyYhIiJS/+f//Eh3332jKTz43HNP6Tvf+ZGFlQGA+/jpT3+qiooKrV27VnfeeafV5QAAAADjcp0zF8B5Gu8EY0dHm2l7ZNeWsSxcGGLabmw8ZtweeVXzyCUPzsfhw9PXun4iS8qdj6ksrzfSZE6gu4Lxlp8bbvnyKK1cuda07733/mrc7uho1/79/2Ns+/sHaNWq9VMvcgac6/U1vPvUkNDQRRM67sjXTFPTcUkzE0oc2SFuKqbjtT6e/fv/xxSG8vcP0IoVFziNs9lsTleRv/ban2a8PgDA3HLPPffonnvuUXJystWlwMXM9jyqv79flZVlpvuYR03eVOZREwnnTDdPz/GX6RviTvOoczl1qsO0PdFAW3BwiNO+9vbB4A/zqMkJDg7RDTd80bRv3753LaoGANxPeXm5Dhw4oMOHnQPuAID5IykpSStXruScFIA5gY5TcHteXrYR2xM7cXv6dKdpOyTk42UNOjtPme5zOAbOs7qPjQzmrFy5Vp/73K2TPo6Pj6/8/PymXM9oRn7t/P0D9L3v/WTSx/Hw8FBaWvZ0leWSPvWpa3TgwH5je+fOV3TFFVdLcj4hu2nTlgkte+JqRnstnTlzZkJvqo1cFiQoaIEk59fdwMDUX1ujXd38/e//P/n5TezNv+FiYxOnXM94Rnab2rRpi7y8vEZdqvbCCy/V669/HJY6fLhK1dWVSkhgIgIAAKZmuudRvb29TmPP52+9kV2hmEe5l/k4j5poN6bTp7uc9gUGMo86XzExCabt7u7TOnWqwyWXfgQAAADmoq9+9atWlwAAE0ZwCm5v+fIo03ZT08SWdxvZVn/58mjT7eLiAmO7sbFhChUOio01n7QLClrgdLWt1aKj45z2uVqNrmLduktMy6gVFxeotrZG0dFxTstLbNhwhRUlTll4uPPV7q2tJ+XvHzXK6I91d3ebOipJ0rJlkaZ/h4xccuJ8DH/tDv98rhguqq2tkd3+kWnfn//8R/35z3+c8DF2737dJZ8bAACYW6Z7HuXn56eQkFBTgP748Qalp08uCDTyohXmUe5lPsyjRnZfamysH2Ok2cmTTabtkJBQI+w33+dR52O0Tl/NzScITgHANLKi2yUAAABwPliqD25v5EnJEycaJ/S4ujpzW/rIyOHBKfObCMeO1Z5ndR8becL/0KGKKR9zukVFmU/4d3ef1smTzRZVc376+pyvdJ8Jfn5+uvLKa037du9+XS0tJ/XRR/uMfRERkcrIyJmVmqabr6+v03ImLS3j/zwcP37MaV94+DJJUkSE+bXV0FCvvr6+KVQ5WGdkZIxp33QuOzGd3nzzL1M+xo4dL035awYAADAT86iRXWcmGhg5F+ZRM6+39+ysfa75MI9aunS5abutrXVCf7+PfL0Mfz3N93nU+WhoqHPaN9FlEwEAE0NwCgAAAHMFwSm4vZFXXhYUfDjuSerW1ha9++4u077hJyJHXnl54MB+1dbWTKnOmJh403Z9/VEVFeVP6ZjTbfHiMPn7B5j2vfnmny2q5vyMXCJuJm3atMW0/dprf9J77+12GjOXTyKMfKPqvff+Ou5jdu161bQdERFpLLEy8g06afCNkqlKTk4zbb/22p9GXfrOSmfOnHFapu98dHefNi1vAgCY3+6++27dfffd2rdv3/iDgWFmYh41svPSzp2vjLqE32Qwj5p5DQ1TD7hNhrvPo0ZefCJJf//73nEf9/rr203bw19P83kedb5KS4tM2/7+AcYFPQCAqXniiSf04Ycf6oc//KHVpQAAAAATQnAKbi8+PtnpJPUbb7xyzse8/vqfnPYNX0JitNb0v//94+dZ4aDly6MVEhJq2vfIIz/S2bOzd3XvRKxZc6Fp+7e//ZXTVeWuZOHCENP2dCxZMFEJCcmmE81tba167LGfmMZs2PCpWatnJqxceYFp++WXn9fp011jju/q6tSLLz5j2rdq1Xrj9qJFYU6vg6eeelQ9PT1TqjM7e4Vp+8CB/dPyRsJ0ev/9d5yWMHz44V/oV796ftyPkW8YvvXWjtksHQDgorq7u3XgwAEdOHBAra2zFx6He5iJeVRSUqrpvoaGeu3cuX3kQyaFedT0CwgIdNrX1HR81j6/u8+jbDab08/D9u0vnPMxhYUHVVlZZtqXm7vKuD2f51Hno6DgI7366kumfTk5q8YYDQAAAOB87Ny5U48//rh27txpdSkAMC6CU3B7AQEBuuOOr5j2/fGPv1dBwYejjt+373/0u99tNe274YYvaunSCGM7JiZeGzd+2jTm3Xd36de//s8xT0xWVpY5hSKG8/b21je+8V3Tvvr6o/rZz/5F7e1tYz7u739/T9/61l1qbj4x5pjp9OUvf91p38MP/x/V1Bwa8zFHjx7WD37wgPbvH/8q2uk2MuT2l7+8qIGBgVn7/Js3f2bM+9LSskxLl8xFW7Z8zukE/S9+8W+jvg5Onz6tf//37zrt/8IX7jBue3p66vbbza/XtrZW/fCH3x5zeZiOjnZVVpaes87Nm691ulr60Uf/Q/v2/c+Yj+noaNevfvUzPfPMr8957Ony6qsvm7aTk9O0Zs2FSkhIHvfjsss2mx777ru71NHRPit1AwAA9zQT86jLLrvSqdvOY4/9RDt3vjJmF5vCwgPnrJN51PQLDV3kFJp77bWXxxg9M9x9HjVyzlNQ8KFefvn5UcfW1R3Vj3/8kGlfcnKaPvGJy4zt+TyPmoyenh69+urL+v73v+V034YNmyyoCAAAAHBfO3fu1BNPPEFwCsCcYLO6AGA2bN58rV544XfGSfHu7tN68MF/1O2336e8vDVavjxax47V6sMP33c6uefvH6DPf/4fnI5522336u23XzPte+ml5/S3v+3RtdfepOjoOIWHL9OxY3X6+9/f044d4y/BtX79pbrssitNV3Du2fOm9u/fqy9+8ctKSkrVkiXL1Np6UnV1R/S3v+0xTqI//fQv9eCD/zLpr81khYcv0ze+8V3953/+q7Hv8OEq3XPPTbrhhi8qO3ulIiOj1dPTo7q6Iyoqyjeee01NlfLy1sjX13fG6xySnJyuPXveNLaLiwv0ve99UzfeeJtCQkJ16FCFioryFRsbr2uuuXHaP/8ll2zSo4/+x6j3XXHFllH3zyV+fn66446v6pFHfmTs27PnTTU2HtPnP3+bEhJS5OnpqYqKEr3wwu9UUVFievytt96txYuXmPZdfvlVeuml53T06GFj30cf7dOtt16tW2+9WwkJyYqIiFJXV6fy8z/Qtm3PnjOUKA1e1X3//d/XvffebOzr7j6t73//W/rEJy7TxRdvVExMvLy8vHTsWK2qqyv14ovPGMe99NJNTl2dplNtbY3s9o9M+y677MoJP/7CCzfot7/9lWnf3r279elPXzct9QEA5qbhQZS5uqQVrDXd8yhfX1/dc8839a//+n9N+3/+84f1zjtv6ZJLLldUVKyCg0NUWVmqd97Zpf37xw5oDGEeNf1yclaaAlvPP/+0zp49q0sv3SQPD09VVBSrsDBfn/70dcrJWTntn9/d51GJiSnauPHTpnMKjz/+c1VXV2rjxisVG5uoU6faVVJi1+OP/9xpvvPlL39dnp7mayHn4zxqLPv371VfX58WLFio/v5+tbSc1IkTjTp48O+jPuerrrp+UvMvAAAAAADgXghOYV7w8fHR17/+/+mf//kbpv2/+c1/jfvY++57QAsXBjvtX7o0Qrfffp/TMRoa6vWrX/3svGu9995v6cCBfWpr+3g5le7u03riiV+c83Fvv/2arr3280pJyTjvzz1Rmzd/Ru+//47Tlc/btj2rbdueHfNxDQ312rFjm66//paZLtFw1VXX609/+m/TleQffPA3ffDB30zjVq1aNyPBqYULg3XJJZfr3Xd3Od33iU9snPbPZ4XBE/6vm7oPlJUV6V/+5dvnfFxMTLw++1nnnwWbzaavfvVBPfjgPzrdN5WrluPjk3TXXV/Tk08+atq/d+9u7d27+5yPffLJR/XDHz5y3p97PG+88WenfcOvIB9PbGyCIiNjVF//8XIvr7++neAUAMxzY3XwASZqJuZRF1+8UatWrdNHH+0z7T9wYL8OHNh/3rUyj5pet932jxOqMyEhaUaCU/NhHnXbbffqo4/eN/3MvvXWjnGX3f7Up65Rbu5qp/3zcR41lsrKMqelDceSmZmre+917kAFAAAAAADmD5bqw7xxwQUXaevW/1ZkZMyExoeEhOpnP3tCV1xx9Zhjbrrpdn3nOw9PV4mSpODgED3xxIvatGlyV9FmZeU5de6ZKR4eHvre9/6f7rzzq5N6XFhYuFJTM2eoqtH5+/vrW9/653HHHTpUPmM15OU5n9S+8MINCg4OmbHPOZtsNpv+7d8e1Re/eNeEH7Nlyw169NHfKyAgYNT7c3NX67HHnlFEROR0lSlJ+tznvqR/+ZefOS0vOJ716y+Z1jqGO3PmjHbseMm0LydnlcLDl03qOCOX66uoKFFra8uU6wMAzF2BgYHaunWrtm7dqgsuuMDqcjBH4T/BkAAAIABJREFUTfc8ysPDQz/84c91441fms4ymUdNs8TEFH3pS/eMO66mpnrGanD3edTSpRF64okXtX79pRN+zD/903f0zW8+NOb982keNVVhYeG6//7v6Sc/2SofHx+rywEAt3L77bdr9erV+sEPfmB1KQAAAMCE0HEKLsdm8zZte3t7jzFykKenl2n7XMsXxMcn6Ze/fFbPPPO4Pvjgb6YW9kMiIiK1cuU6/cM//OOoV0iP9MlPfkpJSal66qnHlJ//waht3y+8cIPuueeb+vrX/8F0NenI2ocsXBisBx74vi6+eKOef/4plZUVjTouJSVDCQnJ2rjx0zNyle+52Gw23XjjbVq//tJzPveYmHglJCTrggsu0qWXXiGbzfnXzsjvuZfX+L+afHzM3+eRxxhu1ap1evzxP+jHP35Ihw9XjTrG3z9APT098vPzG/V45zr+eGJjE532bdxozTIAvr6+pu/TyOUdRhr5+hvr62Cz2XTrrfcoJ2eV/vCH36q0tHDUn4esrDx99rNf0EUXfXLcWpOT0/TLXz6rp5/+pT766H01NNSPOubee+/Xzp2vmK7MPteJ73XrLtGTT27T73//uP72tz2mbmRDwsLClZiYqszMHF1xxTUKDV00br3nq7TU7vS1GhmCmogLL9zgdCV5ff3RGa0dAOD6Vq92Dh7APc2leZTNZtOdd35NWVkr9Mc//k5FRfmjjrvxxi/p4osv19e+9nHIyt8/cMzjzvd51HR+zyXpllvuUnx8kn7yk++PuaRbf3/fOWvy8hp9zjsRrjKPmsn56sKFwfr+9/+fduzYpl27Xhv1ZzYkJFTp6Tm67bZ7FR+fNO7nni/zqOEmMl+PiIhUVFSsoqJiFR+fpA0bPjWry18CwHwy1Pl2vPOOAAD3tnnzZqWnpys2NtbqUgBgXB6OObJ+w/r169Xb26v7779fN998s9XlzHlbv1eu7q5+5VwcpryLZ+fqWlfU09Oj2toaNTTUacmSpYqNTVBAwNgn4ifixIlG1dQcks1mU0RElJYsWTrqSe7J6OvrU2PjMdXWHpaPj6+iomK1ZMlSl5t8Njef0JEj1Tp79owiI2MUERE17sn72dbcfELV1ZXq7+/T4sXhWrx4iUJDF83o17K9vU033rjJ2Pb3D9Af/vCGEdJyV01Nx3X06GH19vYqJiZey5Ytn9LX+dSpDlVXV6qnp1vLli3X0qXLp+VreOpUh44cqVZr60ktXbpcUVExU/49AGdv/7FW9VWdiksL1HVfZqIEAJib/vPbJXIMSBdcsVRpq+dvOHm651F9fX1qaKhTXd0RLVgQrIiIKC1atFgeHh5TqpN51PTo7+/XsWO1Onp08OsYFhausLBwLViwcEY/73ycRw29Fmpra+TvH6DY2EQtWrR4SsdkHjV3/XVbrWorOhWbGqjP3s0cCsDcceutt6q0tFTXXnutHnpo7E6JAAAAgKug4xTmNT8/PyUnpyk5OW3ajhkevmzSS2yNx2azKSoqRlFRE1seQ5La2lo1nblIPz9/+fv7n3PM0Al0V2ZFjSdONJq2L7vsynOeqO7sPKXe3t5p+/w2m23G39QYzZIlS7VkydJpO96CBQuVm7tq2o43/LhZWXkTHt/T0zPmFffni65QAABgLpnueZTNZlN0dJyio+Om5XjDj8s8auq8vLxm5Psznvk4j5qJ14KrzKPc4fsDAJgYOk4BAABgriE4Bbihkyeb9IUvfHpaj/nJT27Wd77zo2k95nxw+nSXtm79mWnfeMuw/dM//YPq649OWw3+/gHavv2daTvefPfUU4/qz3/+47Qe88knX5z1N6IAAABgxjzKdTCPcj98fwBg/khLS1NAQIDi4+OtLgUAAACYEIJTgBuaiRU4HY6BaT+mO+vt7dXevbv1/PNP6ejRw8b+iIhIZWTknPOxAwP9M10epmBgYPpfCzNxTAAA2tradPnll0uSfvKTn+iyyy6zuCLAtTGPsh7zKPfF9wcA5g+W5wMAAMBcQ3AKcEO+vn5auXKt+vun78RkQkLytB3LnX3wwd/0q1/9bMwrab/ylQfHbVOdm7ta4eER01ZTcHDItB0LUmxsvHJzV0/rMYOCFkzr8QAAkMzBXJbJAMbHPMo6zKPcH98fAAAAYH557LHHZLfblZeXp/vuu8/qcgDgnAhOAW5owYKF+vd/f8zqMualjo62MU/233ffA1qz5sJxj/HNb3JVliu75pobdc01N1pdBgAA4yI4BUwO8yjrMI9yf3x/AAAAgPmloqJCBw4c0IIFXDgOwPURnAKAGZaSkqF77/2WMjNzrS4FAADMIwSnAMxlzKMAAAAAAAAwGwhOAcA0Cg1drOTkNC1dulzLl0fpkks2KTk5zeqyAADAPGSz2bRy5UpJUkgISxoBcF3MowAAcB/PP/+8Tp06pZUrV2rNmjVWlwMAsIjD4ZAkeXh4WFwJAIyP4BQATKOVK9dq5cq1VpcBAACgRYsW6de//rXVZQDAuJhHAQDgPp555hk1NTXprrvuIjgFAPPYUHAKAOYCglMAAAAAAAAAAACYst7eXkmSt7e3xZUAAKz02GOPWV0CAEyYp9UFAAAAAAAAAAAAYO7r6+uTRHAKAAAAcwfBKQAAAAAAAAAAAEwZHacAAAAw17BUHwAAAAC4oZMnT2rbtm2SpOuuu07h4eEWVwQAAADA3T366KMaGBhQbGys1aUAAAAAE0JwCgAAAADc0IkTJ/TEE09Iki655BKCUwAAAABm3MqVK60uAQDgAiorK9Xe3q7Q0FAlJiZaXQ4AnBNL9QEAAACAG+rr6zNu22xcMwMAAAAAAIDZ8Ytf/EL33nuvtm7danUpADAuglMAAAAA4IYITgEAAAAAAMAKDodDkuTh4WFxJQAwPoJTAAAAAOCGCE4BAAAAAADACgSnAMwlnD0HAAAAADeUmppqtEMPDw+3uBoAAAAA7u7o0aP67Gc/K0naunWrVq9ebXFFAACrEJwCMJcQnAIAAAAAN7Rw4ULeqAAAAAAwa06fPm3c9vf3t7ASAIDVrrrqKuXl5SkxMdHqUgBgXASnAAAAAAAAAAAAMCXd3d3G7YCAAAsrAQBYbcuWLVaXAAAT5ml1AQAAAAAAAAAAAJjb6DgFAACAuYjgFAAAAAAAAAAAAKbEz89PcXFxCggIIDgFAACAOYOl+gAAAADADe3Zs0fPP/+8bDab/uu//svqcgAAAAC4uVWrVmnbtm1WlwEAAABMCsEpAAAAAHBDtbW1OnDggAIDA60uBQAAAAAAAPPIX/7yFx07dkzJycm67LLLrC4HAM6JpfoAAAAAwA319PRIGlwuAwAAAAAAAJgtr7zyip544gnt3r3b6lIAYFwEpwAAAADADRGcml5FRUVyOBxWlwEAAAAAAODyhs6heHoSRwDg+liqDwAAAADcEMGp89PT06Py8nKVlZWprKxMpaWlOnz4sPr7+3XTxU/Ly5NpNAAAADCavXv3qrm5WUlJScrKyrK6HACAhQYGBiQRnAIwN3DGFwAAAADc0Le//W19+9vftroMl9bV1aXS0lIjJFVeXq7Dhw+POd7Dw2MWqwMAAADmlu3bt2vPnj1au3atfvnLX1pdDgDAQnTtBjCXEJwCAAAAALi99vZ2U0iqrKxMdXV1Y44PCQlRWlqa0tPTlZaWprS0NL34n+1yDMxi0QAAAMAc0t7eLkkKDg62uBIAgNW+853vqLOzU2FhYVaXAgDjIjgFAAAAAHArLS0tKikpMYWkGhsbxxy/ZMkSIxw19LF06dJRRrbPXNEAAADAHDcUnAoJCbG4EgCA1dLS0qwuAQAmjOAUAAAAAGDOamxsNAWkysrK1NzcPOb4iIgIIxyVnp6u9PR0hYaGzmLFAAAAgHvq6OiQRMcpAAAAzC0EpwAAAADADVVVVSkoKEjLli2zupRpU1dXZ4SjSktLVV5erra2tjHHx8TEOHWSWrhw4SxWDADA1DQ3N6upKUBLliyxuhQAGNeNN96o3t5eXXjhhVaXAgAAAEwYwSkAAAAAcEMPPvigjh49qptvvln333+/1eVMysDAgI4cOWLqIlVeXq7Ozs5Rx3t6eiouLs4pJBUQEDDLlQMAML0qKip05ZX3aOnSpcrJyVFubq6ys7OVmpoqm41TuwBcyx133GF1CQAAAMCkMbsGAAAAADc0FDIKCgqyuJJz6+/vV3V1tVNIqqenZ9TxNptNiYmJpoBUcnKy/Pz8ZrlyAABmz/Hjx/XWW2/prbfekiT5+voqIyNDubm5ysnJUU5OjkJCQiyuEgAAABj08MMP6+jRo7r00kt1yy23WF0OAJwTwSkAAAAAcEOuGJzq7e1VZWWlKSRVVVWls2fPjjrex8dHycnJppBUUlKSvL29Z7lyAACskZGRoZQL75bdbldRUZHx//uZM2d08OBBHTx40BgbHR1tClIlJibKw8PDqtIBAAAwjxUVFamqqkoJCQlWlwIA4yI4BQAAAABuZmBgwAgjLViwwJIaenp6VFFRYQpJVVdXq6+vb9Tx/v7+SklJUXp6uhGSio+Pl5eX1yxXDgCA6wgJCdFn775bkuRwOFRTUyO73a7CwkIVFhaqurpaDodDklRbW6va2lrt2LFD0mB4OisrywhSZWdnKzAw0LLnAgAAgPlj6G9UT09PiysBgPERnAIAAAAAN3P27FnddNNNampqUmRk5Ix/vq6uLpWXl6u0tNQISR05ckQDAwOjjg8KCjJ1kUpLS1NsbCxdMQAAOAcPDw/Fx8crPj5en/nMZyQNdpgsKioyglSFhYU6deqUcd++ffu0b98+4/GJiYmmrlTR0dGWPR8A7mXXrl16++23FR0drfvuu8/qcgAAFuvv75dEcArA3EBwCgAAAADcjJ+fnx544IEZOXZHR4cpIFVWVqba2toxx4eEhDiFpKKiomakNgAA5pugoCCtW7dO69atM/aN7Ep16NAhORwOORwOVVVVqaqqSi+99JIkKTQ01AhR5ebmKiMjQz4+PlY9HQBzWFFRkd566y0tX76c4BQAgI5TAOYUglMAAAAAgFG1tLQYIamhfxsbG8ccHxYW5hSSWrZs2SxWDAAA4uLiFBcXp2uuuUbSYGfIkV2pOjo6JEmtra1655139M4770iSbDabUlNTjSBVbm6ulixZYtlzATB3HD9+XJIUHh5ucSUAAFcwFNQHgLmA4NQ8ZYR7HZaWAQCYJxwDQ1eXsAQTALiqxsZGp+X2mpubxxy/bNkyU0AqIyNDixYtmsWKZ5+np4f6BxxiIgUAmGmO/13tdjou0A8MDNTatWu1du1aY19NTY2Kiopkt9tlt9uNrlR9fX0qLi5WcXGx/vu//1vS4P/5Q12pcnJylJqaKi8vr6kXBsCtDF1gwYUTAAAAmGsITs1T/oFe6jrVrzPdfVaXAgCYB86cHvz/JiCIPz0AwGoOh0N1dXUqKytTeXm5EZJqa2sb8zHR0dGmkFR6eroWLlw4i1W7Br8AT3V19Kvn9IDVpQAA3FzPDM+hhrpSbdmyRZJ0+vRpFRcXm5b4a29vlzQYhmhsbNSbb74paXBJ4IyMDNMSf8HBwTNSJ4C5o6GhQZK0fPlyiysBAAAAJod3L+cp/wU2qfGserr6rS4FADAPdP/v/zcBC7kqGQBmw65du/T2228rKipKmzdvNgWkKioq1NnZOerjPD09FRsb67TcXmBg4Cw/A9cUuMBbXR396u7stboUAICb6+763+DUwtk5fRsQEKA1a9ZozZo1xr6jR4+aglRVVVUaGBhQT0+PDhw4oAMHDhhjY2JijBBVTk6OEhIS5OFBx2FgPtm+fbsaGxsVEBBgdSkAAADApBCcmqfCI/1UW3lazQ3dVpcCAHBzPZ19On1q8KR/eKS/xdUAgPvq6+tTVVWVysrK9OKLL6q8vFyS9Jvf/GbU8TabTQkJCaaAVEpKivz8/Gaz7DllSaSfTtT36GRDj9WlAADc2JnufnW1D82hrPt/OSYmRjExMUZXqp6eHmN5v6Ew1VDHyqNHj+ro0aPasWOHJCkoKEhZWVlGkCo7O5swBeDm/Pz8FBcXZ3UZAAAXUVhYqDNnzmj58uV0IwTg8ghOzVMJGQv00Z4WdbX3qaWxW4uW8UY2AGBmHCnvMG7HpS6wsBIAcB89PT2qrKw0ukiVl5erqqpKfX2Db7I6HA55eHgY//r6+io5OVlpaWlKTU1VWlqakpKS5O3tbfEzmVviMxao+O9tajl+Rl3tvQoM5usHAJh+R8rajdvxaa6zNK6fn59Wr16t1atXG/tqa2tNQarKykoNDAyos7NT+/bt0759+yRJHh4eSkpKMi3vFxUVZdVTAQAAwAz79re/rebmZt1111269957rS4HAM6J4NQ8FRkfKJuPh/rOOpT/brMuuzHa6pIAAG5ooH9A9r3NkqTIhAB5+7JUAwBMVldXlxGOGgpK1dTUaGBgYNTxAQEBstls6ujoUHJysh5++GHFx8fLy4vlUqcqLjVIHh6SwyHl/88JXbQl0uqSAABuZqDfocL3TkqSlsf7u/wcKjo6WtHR0brqqqskfdyVaihIZbfb1dbWJofDocrKSlVWVuqll16SJIWEhCgvL0/Z2dnKzMxUWlqagoKCrHw6AAAAmCb9/f2SxPkoAHMCwal5ysNTWnHxIn3w9knVVXWqruqUopLoAgIAmF4H321Sd9fgBGnVJxdbXA0AuL7Ozk6VlJSotLTUCEnV1taOOT44ONjoIDXUTSomJka33nqrOjo6jM5SmB7ePh7KXhcq+/utOmTvUEpeqJZEsewQAGD6FOxtVlfHYAfJVRvCLK5m8kbrSlVXV2eEqIa6UvX396utrU179uzRnj17JA12pUpISFB2drZyc3OVnZ3Nsl/AHLF3717ZbDZlZ2crMDDQ6nIAAC5g6II/glMA5gKCU/PYusvDVfz3Np0+1a89L9XryltjtXg5S/YBAKbHocJWFb/fIkmKSwtUYgYBXQAYrr29XSUlJUZAqrS0VMeOHRtzfFhYmGmpvbS0NEVERIw69tlnn1Vtba08PT1nqvx56xNXLVVFQbt6Tg9o1wu1uvJLsQpZ4md1WQAAN3CosFWF7w127I1KDFBSlnvMoaKiohQVFaUrr7xS0mBXqpKSEtMSfy0tLXI4HDp06JAOHTqk7du3S5IWLlyo7OxsY4m/zMxMBQQQWgZczdNPPy273a4NGzbopz/9qdXlAABcwFDHKc5NAZgLCE7NYzYfD33mjhj98Zc16u9z6I3nj+iyz0VrWSxXhAAApqb8QIv27zwuSVq4yFtXfiHK4ooAwFotLS2mkFRZWZkaGxvHHL906VKlp6cbAamMjAwtWrRoUp8zOprluGeCr7/n4Dzqv2rUe2ZAbzx7RBs/H6MwLkIBAExBlb1Vf9sx+LdBULBNV93qvnMoPz8/rVy5UitXrjT2tbS0yG63Gx+lpaU6c+aMOjo69N577+m9996TNPjGW2JiotGRKjc3V1FR7vu1AuaKiooKSVJ8fLzFlQAAXMWPf/xj1dfXKzk52epSAGBcHg6Hw2F1EROxfv169fb26v7779fNN99sdTlu5XBpp7Y/edTYXrMpXMm5IbL50DoRADA5pzt6Zf9bsyoOtEmS/AO9dNM/xSskzMfiygBg9pw4ccK01F5paamam5vHHB8ZGWkEpIZCUsHBwbNYMc5HeUG7Xvt9vSTJ08tDF1wRrsTsEHnZuJISADBxpzt6Vfh+s8o/+ngO9fmvxSt0yfyeQ/X19am8vFyFhYUqKChQYWHhmKHzkJAQoyNVTk6OMjIy5OdHN0hgtjQ3N2vz5s2SpB/96EdGdzkAAABgriA4BUnSscOn9acnj+psz/+uN2vzUFzGQiXnBis8mg5UAIBzO1LWocqCNh071GXsWxTuo8/eHasFod4WVgYAM6uhocEUkCorK1NLS8uY42NiYpSWlmZ0k0pPT1dQUNAsVozpdLisU3/5ba36ewen1TYfDyVkBSspO1hhkSwjBAAY2+hzKG9d9+U4LVzEHGo0zc3NKigoMLpSlZWVqbe312mcl5eXkpOTTV2pxlreGMDU7d+/X1/5ylckSc8//7xSUlIsrggAAACYHIJTMLQ2ndVrz9TpRH2Pab+nzUOBC2zyD2JlRwDAxxwDDp0+1aeujj6n+1JXLNDlN0TKx4+uGwDcx7Fjx1RaWmrqJtXW1jbqWE9PT8XGxpqW20tLS1NAwMyHaVpbW9Xa2qrw8HBCWbOg6dgZvf5srU4eP2va7+XtoaCFNvkGMI8CAAxyOBw63cEcarr09vaqtLRUdrtdhYWFstvtampqGnVsWFiYEaLKyclRWlqafHzmd1cvYLo0NTXpzTffVHFxsf7t3/7N6nIAAACASSM4BSfl+e36+1tNam48O/5gAACGiU4K0Cc+Ha5lsXTZADC31dfXGwGpoX/b29tHHevl5aWEhARTQCo1NdWyJWK2bdumH//4x5Kkffv2yWYjuDMbSj5s0743m9R+0rnzBQAAY4lMCNDFV4UrIo451HRobGw0OlLZ7XZVVFSor885qGaz2ZSWlmYEqXJzcxUWFmZBxQAAAAAAq3EGHU5S84KVmhesU629qrR3qK35rDpP9aqna8Dq0gDLlZaWqru7W4sXL1ZsbKzV5QCW8vSU/AO9FLjQW4uX+So5J1h+AVwdDWDuqaurMwJSQyGpjo6OUcfabDYlJiaalttLTU2Vt7frLKlz7NgxSdKyZcsITc2ijNUhylgdopONZ1RT1qm25rPqOtWrntPMozC/tba26vDhw5KknJwcfi9hXvPwkAKCBudQi5b6KCUnWH6BXlaX5VaWLVumZcuW6YorrpAknT17ViUlJaYwVUtLi/r6+lRUVKSioiI999xzxmNzcnKMj5SUFH5nAQAAnKe7775bkvSlL31Jn/jEJyyuBgDOjZkfxrQg1FsrL11sdRmAS7nllu+qvLxc1113nW78yqVWlwMAACaprq7OCEgNhaROnTo16libzaakpCRTSColJcWlQlKjGQpORUREWFzJ/LR4ma8WL/O1ugzAZezaVaUntg8u2/N/H3lbwcHBFlcEYD7x8fFRXl6e8vLyjH11dXUqLCxUQUGB7Ha7qqqqNDAwoMbGRjU2NurNN9+UJPn6+iojI8MIUuXm5iokJMSqpwIAADBn9Pb26sCBA5Kkq6++2uJqAGB8BKcAAAAAuB2Hw6Ha2lqnTlKdnZ2jjh8KSaWnpxsfSUlJLh+SGk1DQ4MkKTIy0uJKAAAAXE9UVJSioqJ05ZVXSpJ6enpUVFRkBKkKCwvV0dGhM2fO6ODBgzp48KDpscOX90tISJCnJ52XAQAAhuvv7zdue3nRYRWA6yM4BQAAAGDOq62tdeokNVZIytvbe9SQlLssxbJhwwZFRUVp1apVVpcCAADg8vz8/LR69WqtXr3a2FdTU2Na3q+6ulrSYLequro6vfrqq5KkwMBAZWVlGUGqrKwsBQUFWfI8ACts27ZNL7zwgnJycvTP//zPVpcDAHARfX19xm2CUwDmAvd4ZwAAZslDDz2krq4uLVmyxOpSAACYt0Yut1daWjpmSMrHx0fJycmm5fbcKSQ1mttvv93qEgAAAOa0uLg4xcXF6ZprrpEkdXZ2Gsv7FRYWqqioSF1dXerq6tL+/fu1f/9+SZKHh4cSExOVnZ1tdKaKiYmx8qkAMyo/P1+HDx/mTXEAgAkdpwDMNe77bgEAzID09HSrSwAAYF6pr683OkiVlJSotLRUp06dGnWst7e3kpOTnTpJcYIGAAAAUxEUFKT169dr/fr1kqSBgQFVV1crPz/f6EpVV1cnh8OhqqoqVVVV6U9/+pMkKSQkRDk5OUZXqoyMDPn6+lr5dIBpU1BQIEnKycmxuBIAgCsJDg7W1q1bJUlJSUkWVwMA4yM4BQAAAMAlNDQ0GOGosrIylZaWqr29fdSxNpvNWG4vIyPD7ZbbAwAAgOvy9PRUUlKSkpKSdMMNN0iSWltbVVBQYASpSkpKdPbsWbW1tendd9/Vu+++K2nw79iUlBQjSJWXl0dnc8xJbW1tamhokCTl5uZaXA0AwNUMXwYZAFwd7yoAAAAAmHVNTU0qKSkxPkpLS9XW1jbqWJvNpsTERKOLVEZGhpKSkuTt7T3LVQMAAACjCw0N1YYNG7RhwwZJUl9fn8rKyowwVUFBgZqbm9XX12f8DfyHP/xBkhQeHm50pcrJyVFaWhoXBMDl1dbWKiAgQKdPn9bKlSutLgcAAAA4b8y+AAAAAMyotrY2FRcXm0JSzc3No4718vJSQkKC0UUqPT1dKSkphKQm6Le//a0OHTqkvLw8XX/99VaXAwAAMG/ZbDZlZWUpKytLt9xyi6TBDqvDu1JVVFRoYGBAJ06c0K5du7Rr1y5Jko+Pj9LT05WdnW2EqcLCwqx8OoCT7Oxsvfvuuzp06JAiIiKsLgcAAAA4bwSnAGASbrnlFpWXl+u6667Td7/7XavLAQDA5XR2dqq4uFilpaXGv42NjaOO9fLyUnx8vGm5vZSUFPn4+Mxy1e5jz549KioqkoeHB8EpAAAAFxMREaGIiAht3rxZktTT06PCwkIVFBQoPz9fhYWF6urq0tmzZ1VQUKCCggLTY3NycowwVUpKCl2p4BISExOtLgEAAACYEmZWAAAAAM5Ld3e30UFqKCRVV1c36lgPDw/FxsYqIyPD+EhNTZWvr+8sV+3eqqqqJEkJCQkWVwIAg7y8vIzbAwMDFlYCAK7Hz89Pa9as0Zo1ayQN/p6srq5Wfn6+8vPzVVBQoIaGBkmD3aoaGhr0xhtvSJJ8fX2VkZFhWuIvNDTUsucCAAAwpLKyUjfffLOkwe7oWVlZFlcEAOdGcAoAAADAuM6cOaOysjKVlpYaS+4dOXJEDodj1PFRUVFGJ6mhD39//1muen5pbGxUT0+PJK76BuA6hgen+vv7LawEAFyfp6enkpKatoSGAAAgAElEQVSSlJSUpBtuuEGS1NzcbHSfOnDggMrKyiQN/n1+8OBBHTx40Hj8okWLlJOTo9zcXOXm5iotLY1urgAAYNb19vYat+mQCWAu4DcVAAAAAJO+vj5VVVWpuLhYJSUlKi4uVnV19ZidQpYuXar09HRlZmYqPT1dWVlZCgoKmuWqcejQIeN2cnKyhZUAwMeGB6f6+vosrAQA5qawsDBt3LhRGzdulDS4vF9RUZERprLb7ers7JQktbS0aM+ePdqzZ48kydvbW+np6UaYKi8vj65UmBZPP/20QkJCtHHjRgUHB1tdDgDAxQwPTnl7e1tYCQBMDMEpAJiE9PR0BQYGKjY21upSAACYFg6HQ4cPHza6SJWUlKi8vNx0gmO4RYsWmbpIZWZm8uaLi7jooou0c+dONTU1admyZVaXAwCS6DgFANPNz89Pq1ev1urVq419lZWVys/P16FDh5Sfn28s39zb2yu73S673a5nn31WkrR8+XJlZ2drxYoVysnJUUpKiiXPA3NXf3+/nnrqKZ05c0bV1dV64IEHrC4JAOBi6DgFYK7hNxUATMJDDz1kdQkAAExJfX290UWqtLRUpaWlOn369Khjg4KCjE5SQ0EpAjmuLSwsTGFhYVaXAQCG4SfJCU4BwMxITk42dRzt6upSYWGhEZoqLCxUV1eXJOnYsWM6duyY3njjDUlSYGCgsrOzja5UWVlZCgwMtOR5YG748MMPdebMGUnSJZdcYnE1AABXFBAQoPj4eDU1NdFxCsCcQHAKAAAAcFOtra0qLCw0BaXa2tpGHevn56fU1FSji1R6ejodFgEAU+bp6WncJjgFALMjMDBQ69at07p16yRJAwMDqq6uNpb2KygoUF1dnaTBkNW+ffu0b98+SZKHh4eSkpKUm5ur3Nxc5eTkKDIy0rLnAtfz17/+VZK0YMECrVq1yuJqAACuKCMjQy+++KLVZQDAhBGcAgAAANxAd3e3iouLVVRUpOLiYpWUlOj48eOjjrXZbEpKSjItt5eQkGBaTgkAgOnAUn0AYD1PT08lJSUpKSlJ119/vaTBiywKCgqUn58vu92u0tJS9fb2yuFwqLKyUpWVldq2bZskafHixUaIKi8vT6mpqXSPmMfy8/MlSRs3bmQOCQAAALdAcAoAAACYY/r6+lRRUaHi4mLjo6amRg6Hw2msh4eH4uLiTCEp3uhwP21tbfLw8FBwcLDVpQCAia+vr3G7p6fHwkoAAMOFhoZqw4YN2rBhgyTp7NmzKi0tNXWlam1tlSSdPHlSu3fv1u7duyVJPj4+ysjIMLpS5ebm8nfoPPKHP/xBH330kUJCQqwuBQAAAJgWBKcAYBJeeuklNTc3KyMjQxdffLHV5QAA5gGHw6EjR44YXaSKi4tVXl6u3t7eUccvX77cCEgNhaX8/f1nuWrMttdee02PPPKIIiMj9corr1hdDgAYgoKCjNtdXV0WVgIAOBcfHx8jBDWktrZWBQUFxkd1dbWkwZBVfn6+0XlIkuLi4kxBKpb9dm8s0QcAAAB3QnAKACbh5ZdfVnl5ua677jqCUwCAGdHS0iK73W50kiopKVFnZ+eoY0NCQpSZmWl8ZGdna+HChbNcMVyB3W6XJC1YsMDiSgDAbHhwaqz/zwAArik6OlrR0dHasmWLpMHf40MhKrvdrqKiIqObYE1NjWpqaowQf0hIiLG8X25urjIyMuTj42PZcwEAALOntLRU7777riTpnnvusbgaABgfwSkAAADAIj09PSouLlZRUZHx74kTJ0Yd6+fnp7S0NFNQKjIycpYrhqs6ePCgJCkrK8viSgDAbHigl45TADC3BQUF6aKLLtJFF10kServ71d5ebmpK1VTU5OkwaWk33nnHb3zzjuSJG9vb6WnpxsdqfLy8ljqDQAAN2W32/XEE0/IZrMRnAIwJxCcAgAAAGbBwMCAqqurVVRUZHxUV1drYGDAaaynp6cSExOVmZmprKwsZWZmKjExUZ6enhZUDldXX1+vkydPSpJWrFhhcTUAYObp6SkfHx+dPXuW4BQAuBkvLy9jefCbb75ZktTQ0GAKUlVWVsrhcKi3t1d2u112u13PPPOMpMGOVkMhqtzcXMXHx1v5dDCOxx9/XEuWLNHll19Op2MAwDmdPXtWkug2CWDOIDgFAAAAzIDjx4+bOkmVlpaqu7t71LHLly83ukhlZWUpPT1dvr6+s1wx5qqgoCA98MADKioq0po1a6wuBwCcBAYGEpwCgHkiIiJCERER2rx5syTp9OnTKiwsNIJUhYWFOn36tCSptrZWtbW12rFjh6TBLoVDS/vl5uYqMzOTeZGLaGtr05NPPimHw6H29nbdfvvtVpcEAHBhBKcAzDUEpwBgEh566CF1dXVpyZIlVpcCAHAh3d3dRkBq6KO5uXnUsQsWLDACUllZWcrJyeFqXUxJcHCwbrrpJqvLAIAxBQYGqrW1VW1tbVaXAgCYZQEBAVq7dq3Wrl0rabATb1VVlRGkys/PV2NjoySpo6NDe/fu1d69eyVJNptNaWlpRpBqxYoVCg0Ntey5zGfbt2+Xw+GQh4eHrrvuOqvLAQC4OIJTAOYaglMAMAnp6elWlwAAsJjD4dChQ4dMIalDhw7J4XA4jbXZbEpOTjZCUpmZmYqLi7OgagAArBMSEqK6uroxQ8UAgPnD09NTKSkpSklJ0ec+9zlJUlNTkxGiKigoUEVFhfr7+9XX12fMuZ577jlJUlRUlLG039Dyfh4eHlY+pXlh27ZtkqQNGzYoJCTE4moAAK7u6quv1po1a+Tn52d1KQAwIQSnAAAAgHNob283lpQoKipSSUnJmEsNRUZGmrpJpaeny9vbe5YrBgDAtQx17G1pabG4EgCAK1qyZIkuv/xyXX755ZKknp4eFRUVKT8/X/n5+SosLDTmYHV1daqrqzOW91uwYIERosrNzVVWVhbdLaZZdXW10RVsKOwGAMC5REVFKSoqyuoyAGDCCE4BAAAA/6uvr09lZWUqKioyglL19fWjjh255F52draCg4NnuWIAAFxfWFiYJOnkyZMWVwIAmAv8/Py0evVqrV69WtLg8n6HDh0yulINX97v1KlToy7vl5eXpxUrVigvL4952hQlJCRoz549+utf/6oLLrjA6nIAAACAaUdwCgAAAPPWsWPHjIBUYWGhysvL1dvb6zTO09NTSUlJys7OVnZ2trKyslhyDy7hhz/8oaqqqnTllVfq5ptvtrocABjVUMcpglMAgPPh6emp5ORkJScn64YbbpA0uLzfUIhqaHm/gYEB0/J+zz77rCQpLi5OeXl5xgcdMCYvKChIV199tdVlAAAAADOC4BQATMLDDz+so0eP6pJLLtEXv/hFq8sBAEzCmTNnVFpaKrvdLrvdrsLCwjHfwF28eLERkMrOzlZmZqb8/PxmuWJgfO+8847a29uNq/EBwBUNdZzq7OxUb28vy9gCAKZsyZIl2rRpkzZt2iRpcHm/goICoytVYWGhuru7JUk1NTWqqanR9u3bJUmLFi0yBalSU1Pl5eVl2XMBAAAAYC2CUwAwCaWlpSovL1dsbKzVpQAAxtHQ0GAEpOx2uyoqKtTX1+c0ztvbW6mpqUY3qezsbEVERFhQMTA5RUVFam9vlyRdeOGFFlcDAGMb6jglDXYIWb58uYXVAADckZ+fn9auXau1a9dKkvr7+1VZWWl0pcrPz1dzc7MkqaWlRbt379bu3buNx2ZlZRlBqpycHAUEBFj2XAAAmOvuv/9+lZeX61Of+pS+9rWvWV0OAIyL4BQAAADmvLNnz6q0tNQISdntduOk+Ejh4eHKyclRdna2cnJylJaWRucLzEl79uyRJPn6+mrFihUWVwMAYxseSG5oaCA4BQCYcV5eXkpLS1NaWppuuukmSVJ9fb1peb/q6mpJg92qPvzwQ3344YeSPl4aMC8vT7m5uVq5cqXRPXE+eeSRR3Tq1Cndcccdio6OtrocAMAccurUKTU2NurYsWNWlwIAE0JwCgAAAHNOY2OjEZIqLCxUWVnZqN2kbDab0tLSjJBUTk6Oli5dakHFwPTz9/fXggULdMEFF7C0CACXNvzN1traWq1atcrCagAA81VkZKQiIyN11VVXSRpcQvbgwYNGmKqkpES9vb0aGBhQeXm5ysvL9cILL0gaDAEPX94vISFBHh4eVj6dGdXc3Kw//vGP6uvrk7+/vx588EGrSwIAzCE9PT2SBrs6AsBcQHAKAAAALq2/v18VFRUqKCgwPk6cODHq2LCwMCMglZ2drfT0dPn4+MxyxcDsuPPOO3XnnXeO2V0NAFyFl5eXli9frmPHjuno0aNWlwMAgCQpKChIF198sS6++GJJg52MS0pKTF2pTp06JWmwY2JDQ4Nef/11SdLChQuVk5NjBKkyMzPdqpPx1q1b1dfXJx8fH91xxx1WlwMAmGMITgGYawhOAcAkPPfcc1aXAABur7OzUwUFBbLb7SooKFBRUZEx2R7OZrMpJSXFCErl5ORo2bJlFlQMWGs+LhsCYO6JiYkhOAUAcGk+Pj5GEEqSHA6HqqurjSBVfn6+GhoaJEkdHR3au3ev9u7dK0ny9vZWZmamVqxYoRUrVig3N1eBgYGWPZepqK+v15///GdJ0k033cR8AwAwaTExMero6Jiz/xcCmH8ITgEAAMBSdXV1xtW8drtdhw4dGnVccHCwsrOzlZeXp5ycHGVlZdFNCgCAOSI6Olr79u0jOAUAmDM8PDyUmJioxMREXX/99ZIGl7A7cOCAEaSqrKyUw+FQb2+vse83v/mNPDw8lJycbASpVq5cqUWLFln8jCamu7tbF1xwgUpKSnTnnXdaXQ4AYA766U9/anUJADApBKcAAAAwa4aW3Rt+xe7JkydHHRsbG6vc3Fxj+YO4uLhZrhYAAEyXmJgYSdKRI0fU19cnm41TUgCAuScsLExXXHGFrrjiCklSV1eX7Ha7Mb8tLi5WT0+PHA6HKioqVFFRoRdeeEGSFBUVpby8PK1YsUJ5eXmKjY218qmMKSkpSY899phaW1vpFAIAAIB5gbNUAAAAmDFnzpwxnUS22+3q7u52Gufj46OMjAzl5uYaH8HBwRZUDLi+X//61yooKNDVV1+tzZs3W10OAExIUlKSpMEQdWVlpdLT0y2uCACAqQsMDNT69eu1fv16SVJfX5/Kysp08OBBHTx4UAUFBWpvb5c02G25rq5OO3bskCSFhoYaIaoVK1YoNTVVnp6elj2XkUJDQ60uAQAAAJgVBKcAYBJKS0vV1dWlJUuWuOxVYQBgpfb2duMEcX5+vsrLy9XX1+c0Ljg4WLm5ucrLy1NeXp4yMjLoPAFMgMPh0Msvv6zm5mYtWLCA4BSAOWN4UKq0tJTgFADALdlsNmVlZSkrK0u33nqrJKm6utqYIx88eFCNjY2SpNbWVu3evVu7d++WJAUEBBgdl1esWKHs7GyWpwcAAABmAe9OAcAkPPzwwyovL9d1112n7373u1aXAwCWa2pq0ocffvj/s3fnYVXW+f/HnwdBQBAQcfu6m6kgbiwKKi5JZoappRVao1M25XeysbTJvjmlaZs61a/JtKYyGyvHNNcUE02SFAUFzVxyQ8XcCAFZDuv5/cFwJkenRIEPy+txXXNdeJ8bep5rrktv7vO+Px/27NlDYmIiycnJ1zyvefPm9iGp7t2707Zt20ouFakZEhISSE1NBWDYsGGGa0RErp+7uzstW7bk9OnTHDx40HSOiIhIpWnXrh3t2rXj3nvvBUp+j969e7f9oaPjx48DkJOTQ1xcHHFxcUDJEJafnx89evSwr0zl7u5eIY3nz5/nyy+/ZOLEiRXy80VEpPbIyclh5cqVNG7cmODgYLy8vEwniYj8Jg1OiYiIiMh1S05OJikpyT4odfbs2avOcXBwoEOHDvYhqYCAALy9vQ3UitQ8q1evBqBhw4b27UBERKqLzp07a3BKRERqvUaNGjFkyBD76rGZmZlXrNx88OBBioqKKCwsZN++fezbt4/FixdjsVho3749PXr0ICAggMDAwHLbTu/ll19m+/btbNy4kVWrVpXLzxQRkdrp0qVLvPnmmwC88847hISEGC4SEfltGpwSERERkWuy2WwcOXLEPiSVmJhIWlraVec5OTnRuXNn+1OwAQEBuLi4GCgWqflsNht169Zl1KhRODg4mM4RESkTX19foqKiOHLkCIWFhdqmV0REBPDw8KB///70798fAKvVyvfff2//Pfz777/HarXaf0c/cuQIy5YtA6BFixYEBAQQEBBAjx49aN68eZn/+19//TXbt28HYOjQoeX3xkREpFbKycmxf12vXj2DJSIi1093qEREREQE+Peg1O7du+3b712+fPmq81xcXOjatSsBAQF0796drl27UrduXQPFIrXPyy+/TG5uLkVFRaZTRETKzM/PD4CioiL2799P9+7dDReJiIhUPS4uLgQHBxMcHAyU/Lt58OBBEhMT2bNnD0lJSfbf1VNSUkhJSWHNmjUANG7c+IqHmtq1a/er/62MjAxee+01ANq2bcvDDz9cge9MRERqg+zsbPvXbm5uBktERK6fBqdERMrgnnvuITU11X7DX0SkOrPZbBw7doyEhAQSEhJITEwkIyPjqvPc3d3tW+716NEDPz8/6tSpY6BYRABcXV1NJ4iI3JDOnTvj5OREQUEBcXFxGpwSERG5DnXq1MHf3x9/f38eeugh++/ye/bssQ9SpaamAnDhwgU2btzIxo0bAfDy8rIPUQUEBNChQwcsFov9Z1+8eBEPDw8yMzOZNWuWVoMUEZGb9ssVpzQ4JSLVhcVms9lMR1yP0NBQCgoKmDJlCpGRkaZzRERERKql48ePk5CQwO7du9m9ezfp6elXnePt7W1/QrVHjx5X3VgVERERuVGTJk1ix44d+Pv78/HHH5vOERERqRFOnz5tX5EqMTGRM2fOXPO80gejAgMDCQgIoFOnTtSpU4edO3fSq1evSq4WEZGaKDk52T7AO27cOFxcXAwXiYj8Nj0+ICIiIlKDnT9/nri4OOLj49m1axdpaWlXnePl5UVAQABBQUEEBQX95lL+IlL5fv75Zxo2bGg6Q0TkpvXu3ZsdO3awf/9+cnNztYqeiIhIOWjZsiUtW7bk7rvvBiAtLY2EhAT7ilRHjx4FICsri9jYWGJjY4GS1Wy7detGYGAgzs7O+Pv7a9UpERG5KW3atOGxxx4znSEiUia6AhYRERGpQTIyMuxDUrt27SIlJeWqc9zd3QkMDLQPSrVv314rSolUYUlJSUyYMIGIiAiefvppPDw8TCeJiNyw0NBQ+9c7duzgtttuM1gjIiJSM3l7ezN48GAGDx4MlAxMJSQkkJiYyO7du/nxxx8pLi4mNzeXuLg44uLiAHB2dqZr164EBQURGBioQSoRERERqRV0xSsiIiJSjVmtVvbs2cOuXbuIj4/n8OHDV53j7OxM9+7dCQ4OpmfPnnTq1AkHBwcDtSJyIxYvXgzA9u3bmTFjhuEaEZGb06ZNG5o0acL58+f55ptvNDglIiJSCdzd3RkwYAADBgxg+vTpPPDAA3h5eZGUlERCQgL79+8HIC8vj/j4eOLj44GS+wmlK1KVbvEnIiIiIlLTaHBKRKQMVqxYQWpqKn5+foSFhZnOEZFayGazcfjwYfsToUlJSRQWFl5xjoODA35+fvTs2ZOePXvStWtX6tata6hYRG7G3r172bZtGwBjxowxXCMiUj5uv/12lixZwubNm5k+fTrOzs6mk0RERGqFf/7zn0RFRREVFcXcuXN54okngJKHsr7//nuSkpJISkri+++/Jycnh7y8PPuK1gCOjo74+fnRo0cPunfvTo8ePXB3dzf5lkREREREbpoGp0REyuDLL7/k8OHDjBw5UoNTIlJp0tPT2b59Ozt27GDnzp2kpaVddU67du3sg1KBgYG4ubkZKBWR8rZgwQKg5Anx++67z3CNiEj5GDp0KEuWLCE/P5/o6Gjuuusu00kiIiI13sGDB5k7dy4AnTp1YuDAgfbXXFxcCA4OJjg4+Irz9+7dS1JSErt27SIzM5PCwkL27dvHvn377Cvjtm/fnuDgYPr27UuvXr0q902JiEiVM3v2bLZv307v3r2ZPn266RwRkeuiwSkRERGRKmj//v3ExsYSGxvLoUOHrnq9fv369OrViz59+tCnTx+8vb0NVIpIRRs/fjznz59n8ODB1KtXz3SOiEi56NChA23btuXEiROsX79eg1MiIiIVLC0tjSeffBIoeSijdIDq1/j6+uLr68sDDzyAzWbjxx9/JC4ujp07d5KUlER+fj4AR48e5ejRo3z++ee4urrSs2dPevfuTVhYGI0bN67Q9yUiIlXPpUuXuHDhAufOnTOdIiJy3TQ4JSIiIlIFWK1W4uLi+Pbbb4mNjb1qVSmLxULnzp0JCQmhd+/e+Pv74+DgYKhWRCpLSEgIK1euJDs723SKiEi5GjZsGG+//TY7d+7kzJkzNG/e3HSSiIhIjeXt7c348eN58803mTNnDs2aNSvT91ssFjp27EjHjh0ZN24ceXl5JCYmEhcXR3x8PIcPHwYgNzeXmJgYYmJiePXVV7nlllvsK1kFBgZqWz8RkVogMzMTAA8PD8MlIiLXT4NTIiIiIoZcuHCBLVu2EBsbS1xc3FWvu7u7M2DAAEJCQujTpw/169c3UCkiVYG23xSRmmbEiBG899575OXl8Y9//INp06aZThIREanRxo4dS0REBJ6enjf9s5ydnQkJCSEkJASAjIwM9uzZw+7du0lISODo0aMAHDt2jGPHjrF06VIsFgudOnUiODiYoKAgevTogaur6023iIhI1XL58mVAg1MiUr1ocEpEpAymT59OdnY2jRo1Mp0iItVUSkoKmzZtYvPmzdfcgq9t27aEhYXRr18/unbtqlWlREREpEby8PBg+PDhLFu2jFWrVvG///u/urEuIiJSwcpjaOq//dyBAwcycOBAANLT00lISGD37t3Ex8eTnJyMzWbj4MGDHDx4kE8++QSALl262AepunXrhrOzc4X0iYhI5SldcUoPAYtIdWKx2Ww20xHXIzQ0lIKCAqZMmUJkZKTpHBEREZHrdurUKTZu3MjmzZvtT12WcnR0JCAggLCwMAYMGFDm5fJFpOZZv349Xl5e9O7d23SKiEiFOnPmDCNGjMBms/HYY4/x6KOPmk4SERGpMebPn8+4ceOqxPZ4aWlp7Nq1i4SEBBISEkhJSbnqHCcnJ7p160bPnj3p2bMnvr6+1KlTx0CtiIjcDKvVyvnz53F2dqZp06amc0RErosGp0REREQqwJEjR9i8eTObN2/mxIkTV7xWOhDRr18/evfuTb169QxVikhVk5aWxvDhw8nNzWXChAk8/vjjppNERCrU9OnTiYqKol69eqxZswYvLy/TSSIiItXec889x6ZNm2jTpg2LFy+uclt/nz9/nvj4ePv/Lly4cNU57u7uBAYG2gep2rZta6BURERERGoDbdUnIiIiUk4OHTpEdHQ0W7Zs4dSpU1e85uXlxW233cbtt99OYGCgtuATkWt64403yM3NBaBfv36Ga0REKt4TTzzB5s2bycnJ4a233mLGjBmmk0RERKqtvLw8nn32WWJjY4GSB9Kr2tAUQJMmTYiIiCAiIgIoWal7165dxMfHk5CQQEZGBllZWcTExBATEwOAj4+PfYiqV69eNGrUyORbEBEREZEaRINTIiIiIjchLS2NNWvWsG7dOpKTk694zcvLi4EDBxIeHk5QUJCWmBeRX7Vz506ioqIAuPfee/Hz8zNcJCJS8Zo2bcq4ceP44IMPWLduHaNHj6Zz586ms0RERKqlv/71r/ahqTFjxvD0008bLro+rVq1olWrVowaNQqbzcbhw4eJj49n165dJCYmYrVaSU1NZf369axfvx6ANm3a0KtXL0JCQggKCsLV1dXwuxARERGR6kpb9YmIlMHYsWM5fPgwI0eO5PnnnzedIyKGFBYWEhMTw9q1a9m+fTvFxcX217y8vBgwYADh4eEEBwdrWEpErtumTZt4+eWXqVevHsuWLcPd3d10kohIpcjPz2fkyJGcP3+e9u3b8+mnn+oaSkRE5AZkZGQwfvx4+vbty5QpU0znlIvCwkK+//57+4pU+/fvp7Cw8IpzHB0d8ff3JyQkhJCQEHx9fXUtISJiQEZGBhcvXqRx48Z4eHiYzhERuW4anBIRKQMNTonUbsePH2flypVs2LCB9PR0+3FHR0f69etHREQEffr00c05EblhaWlpnDt3TqtNiUits3XrVqZOnQrAM888w/3332+4SEREpHrKzMys0R9W5+bmkpCQwM6dO4mLi7tq9W8Ad3d3goOD7StStWjRwkCpiEjts2nTJp577jkAoqOj8fLyMlwkInJ9tFWfiIiIyK8oLCxky5YtLF26lH379l3xWufOnYmIiODOO+/UyjAiUi68vb3x9vY2nSEiUukGDBhAcHAw8fHxvP322/Tu3ZuWLVuazhIREanSsrKyrrofUZOHpgBcXV0JCwsjLCwMgIsXL7Jjxw527tzJzp07SU9PJysri2+++YZvvvkGgObNmxMaGkpoaCg9e/bUtn4iIhUkLS3N/rWnp6fBEhGRstHglIiIiMg1ZGRksGLFCr744gsuXrxoP96oUSOGDh3KiBEj9GGeiIiISDmaOXMmkZGRZGRk8NRTT7FkyRJcXFxMZ4mIiFRJsbGx/N///R/z58+nS5cupnOMadSoEXfffTd33303NpuNH3/8kbi4OHbu3ElSUhL5+fmcOXOG5cuXs3z5chwdHenatat9kKpjx45YLBbTb0NEpEa4dOkSAD4+Pvq7VUSqFQ1OiYiUga+vL25ubrRu3dp0iohUkOPHj7NkyRKioqLIz8+3Hw8KCuKBBx6gX79+ODg4GCwUkZrkk08+ISwsjLZt21dsP9kAACAASURBVJpOERExrnHjxrz++us8/vjjJCcn88ILLzBnzhzTWSIiIlXOihUrePXVVwF46qmnWLdunYaNAYvFQseOHenYsSPjxo0jLy+P3bt3ExcXx44dOzhx4gSFhYXs2bOHPXv2MH/+fLy8vAgJCSE0NJTevXvToEED029DRKTaKl1xSqupi0h1Y7HZbDbTEdcjNDSUgoICpkyZQmRkpOkcERERqWGOHj3KO++8Q2xsrP2Yi4sLd911F5GRkbRp08ZgnYjURLGxsUyePBmAhQsXEhQUZLhIRKRqeO+99/j73/8OwNNPP82YMWMMF4mIiFQdn332GW+88QYAjo6OzJ49m/DwcMNV1UNqaiqxsbH2FakuX7581TmdOnWiT58+9OnTB39/fz08JyJSBlFRUcTFxeHj48MTTzxhOkdE5LppcEpERERqteTkZBYsWMDmzZvtxzw8PHjggQeIjIykfv36ButEpKY6d+4cY8eOJSMjg44dO/Lpp5+aThIRqTJsNhuPP/44u3fvpk6dOvz973+na9euprNERESqhPnz57No0SIaNmzIG2+8QefOnU0nVUvFxcX88MMP7Nixgx07dvDDDz9QXFx8xTmenp6EhobSp08fevfujaenp6FaEREREalIGpwSERGRWikrK4t3332X5cuX22+MNWzYkDFjxnDffffh6upquFBEaiqr1cr48eM5evQozs7OfPbZZ9oGWETkP6SnpxMZGcnFixfx9PTko48+0t+VIiIi/7Jw4UJGjx5Nw4YNTafUGFlZWezYsYPvvvuO7du327ebKmWxWOjcuTN9+vShb9++dOrUCYvFYqhWRERERMqTBqdERESk1lm7di1vv/02ly5dAqBp06Y89NBDjBw5krp16xquE5GarqCggFmzZrF+/XpmzJhBRESE6SQRkSrp2LFjPPLII2RlZeHj48MHH3xAixYtTGeJiIhIDWez2Th06BDfffcd33333TVXo/L29qZv376EhYUREhKiB/BEREREqjENTomIlMGKFStITU3Fz8+PsLAw0zkiUkZHjhzh1VdfZd++fQC4uLjwyCOP8NBDD+Ho6Gi4TkRqm/j4eIKDg01niIhUaT/88AN/+MMfyMvLo0mTJnz88cc0atTIdJaIiEiliI6OJioqijlz5uDg4GA6p9bKzMy8YjWq9PT0K153dHQkKCiIvn37MmDAAJo2bWqoVERERERuhAanRETKYOzYsRw+fJiRI0fy/PPPm84RkTL49NNPefvttykqKgIgPDycqVOn4uPjY7hMRERERH7N7t27+eMf/0hhYSGtWrXigw8+wNvb23SWiIhIhcnNzeVvf/sby5YtA+DRRx/lscceM1wlULIa1Q8//MC2bdvYtm0bP/7441Xn3HLLLfTv35/+/fvj5+enLf1EpFY4e/Ys8+bNo1GjRowfP15DpCJSrWhpBREREanRcnNzef755/n2228BaNmyJS+++CLdu3c3XCYitUlGRgaenp6mM0REqqXAwEDmzp3L008/zalTp/j973/PwoULadasmek0ERGRcnfo0CGmTp3KuXPnAAgKCuL+++83XCWlLBYL/v7++Pv7M3HiRFJTU9m6dSuxsbHEx8eTl5fHsWPHOHbsGB999BE+Pj6EhYXRv39/evXqhZOTk+m3ICJSIc6cOUNMTAwADzzwgOEaEZGy0dquIiIiUmOdOnWKMWPG2Iemhg4dyrJlyzQ0JSKV6vLlyzz88MM8++yz5OXlmc4REamWwsLCeOGFF4CSG/IPPfQQBw4cMFwlIiJS/ho1akRWVhYAEyZMYOHChXh5eRmukv/Gx8eHUaNG8dZbb7F582b++te/cvfdd9OgQQMAUlNTWblyJZMnT2bgwIFMnTqVdevWkZGRYbhcRKR8Xbhwwf61VpsSkepGK06JiIhIjXT27FnGjRvH5cuXqVOnDk8//bSe0BQRIyZPnszJkyc5efIkQ4cOpX///qaTRESqpWHDhmGxWJg5cybp6ek8+uijzJkzhz59+phOExERKTcNGzZk1qxZODo6EhoaajpHysDFxcW+RZ/NZuP7778nJiaGmJgYkpOTsVqtbN26la1bt2KxWOjevTsDBgxg4MCB/M///I/pfBGRm1I6OFWvXj1cXFwM14iIlI0Gp0REyuCee+4hNTUVPz8/0yki8isyMzOZOHEily9fxmKx8MorrzBo0CDTWSJSyxQVFTFlyhT27t0LwMSJEzU0JSJykyIiIvD09OTPf/4zeXl5TJ48menTpzN8+HDTaSIiIjfku+++u2oIOCwszFCNlBeLxULXrl3p2rUrkyZN4syZM3zzzTfExMSwd+9eiouLSUxMJDExkTfffJNbb72VgQMHMnDgQG699VbT+SIiZXbx4kUAGjdubLhERKTsLDabzWY64nqEhoZSUFDAlClTiIyMNJ0jIiIiVdjEiROJj48H4LnnnuPee+81XCQitdGZM2cYO3YsWVlZREREMGPGDNNJIiI1RlJSEpMnT7ZvZTR+/HieeOIJw1UiIiLX7+jRo8yYMYNDhw4xf/58evXqZTpJKklGRgYxMTFs2bKF2NjYq15v1qwZ4eHhDBo0CH9/fwOFIiI35uzZs+Tk5HDLLbeYThERKRMNTomIiEiNkpSUxIQJEwB49NFHeeyxxwwXiUhtduzYMd58803eeustHB214K+ISHk6evQoEydO5NKlSwCEhITw6quvUr9+fcNlIiIiv+6f//wnc+fOtf85PDyc1157zWCRmJKTk8N3333HN998Q2xsLDk5OVe8XjpENXjwYHx9fQ1VioiIiNRsGpwSERGRGmXKlCnExMTg4eHB119/rUEFERERkRrsp59+4n//939JSUkBSj5cnDdvHh07djRcJiIicm3JycmMGjUKAFdXV5588klGjx5tuEqqitjYWL755huio6PJzs6+4rUmTZowZMgQwsPDNUQlIiIiUo40OCUiIiI1St++fbFarYwdO5annnrKdI6I1DJZWVm4u7ubzhARqVWysrKYPn26fasbJycnZs6cyeDBgw2XiYiIXNubb77Jrl27mDt3Li1atDCdI1VQYWEhO3fuZNOmTWzdutW+PXGpli1bMmTIEIYOHUrLli0NVYqIiIjUDBqcEhEpg9mzZ3Pq1Cn69evHgw8+aDpHRP5DYWEhISEhAEybNs3+BKeISGXYunUrs2fPZuHChbRv3950johIrfPRRx+xYMECSm913X333fz5z3/GxcXFcJmIiNRmGRkZeHp6XnHMarXq3ye5boWFhezYsYOvv/6ab7/99qqVqPz8/Ljzzju544478Pb2NlQpIrVZTk4OKSkpNG7cGC8vL9M5IiJl5mA6QESkOjl48CB79uzh5MmTplNE5Bq0LZ+ImBIbG8vUqVNJT0/XanciIoY8/PDDvPvuu/aV/9asWcP999/PwYMHDZeJiEhtlJOTw5w5c7jrrrs4f/78Fa9paErKwtHRkbCwMGbNmkV0dDTz5s3jjjvuwNXVFYADBw7w17/+lSFDhvDHP/6RdevWkZOTY7haRGqTH374gTFjxhAeHk5ycrLpHBGRMtPglIiIiNQofn5+AMTHxxsuEZHaIj4+nqlTpwLg6urKnDlzDBeJiNRewcHBLF26lG7dugFw5swZfv/737N48WKqyaLrIiJSA0RFRTFixAiWLVuG1WplwYIFppOkhnBycmLAgAG8/PLLREdH88orr9C3b1/q1KlDcXExO3fuZMaMGYSHhzNt2jS2bt1KQUGB6WwRqeHOnDlj/7pp06YGS0REbowGp0RERKRG6dChA1CyZdbFixcN14hIbbBs2TIKCwtxcXHh3XffxdfX13SSiEit1rRpU/7+978zceJE6tSpQ2FhIX/729/4wx/+wNmzZ03niYhIDRcbG8v06dNJS0sDYNSoUfYHLUTKk7OzM4MHD+att97i66+/5tlnn6VLly4A5OfnEx0dzdSpU7njjjt4/fXXOXDggOFiEampfvrpJwAaNGigVRVFpFrS4JSIiIjUKPfccw8ARUVFLFq0yHCNiNQGs2bNonfv3rz77rv2m9QiImKWg4MDjzzyCB9//DHNmjUDIDExkfvvv59Vq1YZrhMRkZqsd+/etG/fniZNmrBo0SKmTZtm30ZWpKJ4enoyevRoFi1axOrVq3n88cdp1aoVAJmZmXzxxRf87ne/Y/To0XzyySf2wT4RkfJQOjhV+ruXiEh1Y7FVk3XKQ0NDKSgoYMqUKURGRprOERERkSrstddeY/ny5QC8/vrrDBo0yHCRiIiIiJiSk5PDG2+8ccXAVGhoKC+++CI+Pj4Gy0REpCZIT0/Hy8vrimOHDh2iRYsWGpgS4/bv38+6devYuHEjly9fth93cHAgJCSEiIgIBgwYQN26dQ1Wikh1t2zZMqKiomjZsiUzZ840nSMiUmYanBIREZEax2q18uCDD5KcnIyjoyMLFy6ke/fuprNEpIbYuXMnvXr1Mp0hIiJltH37dmbOnMnPP/8MgIeHB9OmTWPw4MGGy0REpDpKTk7mtddeIz09nc8//xyLxWI6SeS/KigoICYmhnXr1rF9+3aKi4vtr7m7uzN48GCGDRumVZRFRESkVtLglIiIiNRIycnJPPzww2RmZuLq6sqiRYto37696SwRqcaKioqYOXMm69ev1+8lIiLV1OXLl3nppZf45ptv7Mf69OnDiy++iLe3t8EyERGpLpKTk1m0aBFfffWV/dicOXO47bbbDFaJXL/09HTWrVvHunXrOHr06BWvtWnThuHDhzNs2LCrVlITERERqak0OCUiIiI11pEjR5gwYQLZ2dm4uroyZ84cQkNDTWeJSDWUlZXF1KlTSUhIAMDf35+PP/7YcJWIiNyojRs38tprr9m3rKlfvz5TpkwhIiLCcJmIiFR1f/3rX/n8888BaNCgAZMmTWLYsGFacUqqpUOHDrFu3TqioqJIT0+3H69Tpw5hYWGMGDGC0NBQ6tSpY7BSREREpGJpcEpEpAwOHjxIdnY2jRo1onXr1qZzROQ6HDp0iD/96U/2LVkmT57Mgw8+aLhKRKqbxx9/3D40dfvtt/Pqq68aLhIRkZv1888/M3PmTLZv324/FhgYyEsvvUSTJk0MlomISFWWnp7OsGHDGDFiBI8//jhubm6mk0RuWmFhITExMaxatYq4uDh++dGhj48PERERjBgxghYtWhisFBEREakYGpwSESmDsWPHcvjwYUaOHMnzzz9vOkdErtOlS5d45plnSEpKAuC2227jpZdewsXFxXCZiFQX33//PRMmTOD2229n1qxZeppcRKQGiYqKYu7cuWRkZADg6urKE088wX333ae/70VEarGcnBw++eQThg8fTrNmza54LTMzEw8PD0NlIhXrwoULrF69mtWrV3Pu3LkrXgsICGD48OEMGjRI99VEBIDo6Gg2b95Mq1atmDhxoukcEZEb4mA6QERERKSiNWjQgA8++IDbb78dgC1btjBu3DiSk5MNl4lIddGlSxfef/99Zs+erQ/RRURqmCFDhrB8+XIGDhwIQG5uLnPnzuWRRx7h1KlThutERKSyWa1WPvnkE4YNG8YHH3xwzS26NTQlNVnjxo159NFHWbduHW+//TaDBg2yv7Znzx5efPFF+0NF+/fvN1gqIlVBQkICmzZtYsuWLaZTRERumAanREREpNZ45ZVXGDFiBADHjh3jwQcfZNu2bYarRKQqunz58lXHunXrZqBEREQqQ4MGDZg7dy6vvfYaXl5eAOzbt4/77ruPDz74gMLCQsOFIiJSGVJSUoiIiODtt9+2r0R46NAhw1Ui5vTu3ZvXX3+dzZs38/TTT9OuXTugZNB89erVjB8/nsjISL744guys7MN14qICaUPJ7dq1cpwiYjIjdPglIiIiNQaFouF6dOn8/jjjwMlT5E+9dRTvPvuu4bLRKSqKCoq4rXXXiMyMpL09HTTOSIiUsnCw8NZvnw54eHhABQWFrJw4ULGjh3LwYMHDdeJiEhFa968Oe7u7gC0bduW119/ncWLFxuuEjHP09OTMWPGsGzZMhYtWsTw4cNxdXUF4MiRI7z++uvccccdzJgxg3379hmuFZHKVLpKb8uWLQ2XiIjcuDozZsyYYTrienz44YcUFxfTu3dvunTpYjpHRGoxX19fgoKCaN26tekUEblBAQEBdOnShW3btpGfn09iYiJ79uyhf//+ODs7m84TEUPS09N56qmn2Lx5M1lZWeTl5dGnTx/TWSIiUslcXFwIDw+na9euJCQkkJ2dzaVLl1i9ejXZ2dl0794dR0dH05kiIlIO0tLS7MMfUPLAVbNmzejTpw/PP/+8fXUdEfm3Jk2a0L9/f8aMGcP//M//8PPPP3Px4kUKCwv58ccfWb16NdHR0RQVFdGmTRvq1q1rOllEKkh+fj5vv/02ABEREfj6+houEhG5MRabzWYzHXE9QkNDKSgoYMqUKURGRprOERERkRrg7Nmz/OlPf+L48eMANG3alDfeeIMOHToYLhORynb27FkmTJjA+fPnARg9ejTPPvus4SoRETEtNzeXt99+m+XLl1N6C61p06bMmjWLHj16GK4TEZEbUVRUxMaNG1m8eDHOzs588sknppNEqr3jx4/zxRdfsGHDBrKysuzH69aty6BBgxg5ciQBAQEGC0WkoqSkpPDDDz/g6+ur7fpEpNrS4JSIiIjUalarlZkzZ7Jp0yYAnJycmD59OnfddZfhMhGpTEVFRUycOJF9+/bxl7/8RX8HiIjIFQ4cOMALL7xAcnKy/diIESN46qmncHNzM1gmIiJl8dVXX7FgwQLOnTtnP/bhhx/SrVs3g1UiNYfVaiU6Opovv/zyqi372rRpw4gRIxg2bBienp6GCkVERESupq36REREpFZzdHQkPDwcd3d3du3aRWFhIVu3buXSpUuEhITg4OBgOlFEKoGDgwMDBw5kwIAB2p5PRESu0qhRI+655x4cHBzYu3cvxcXFHDp0iLVr19K2bVs9WS0iUk1ER0ezbds2AHx9fZk7dy5du3Y1XCVSczg6OtKhQweGDx/O4MGDcXBw4NSpU+Tl5ZGenk5cXByfffYZx48fx8PDg+bNm5tOFhEREdGKUyIiIiKlEhMTeeaZZ0hPTwfA39+fefPm4ePjY7hMRMpbRkaGnnAVEZEbcurUKV544QX2799vPxYeHs60adPw8vIyWCYiIr906dIlGjRocMWx9PR0nnzySSZMmEC/fv0MlYnULgUFBfZVqBITE694rUWLFowYMYIRI0boOkpERESM0eCUiEgZrFixgtTUVPz8/AgLCzOdIyIVIDU1lcmTJ3Po0CEAvLy8ePPNN7XipUgNsnfvXqZMmcJjjz3G6NGjTeeIiEg1ZLPZ+OKLL3jnnXfIyckBwNPTk6efflrbvYqIGLZ7927+8Y9/sGvXLjZs2KAHJkSqkNOnT7NixQrWrVtnf3ARSlaq6t+/PyNHjqRXr15YLBaDlSJyvZKTk2nTpo3pDBGRm6at+kREyuDll1/m66+/pl69enoqTaSGqlevHsOGDSM9PZ2DBw9itVr56quvcHd3x9/f33SeiNykBQsWMGPGDKxWK3v37uW+++7DycnJdJaIiFQzFouFzp07M3ToUI4dO8aZM2fIy8tj69at7N69m549e+Lu7m46U0SkVomPj+fZZ5/l448/5tSpUxQVFeHh4UH37t1Np4nIv3h6ehISEsKYMWNo164dmZmZ/PTTTxQXF3PixAnWr1/PV199RU5ODm3atMHV1dV0soj8ivDwcBYvXkyLFi1o37696RwRkRvmYDpAREREpKpxcnLiueeeY+bMmTg5OVFYWMi8efN47rnnyM/PN50nIjfowQcf5MMPPwTg1ltv5dNPP6VevXqGq0REpDpr0qQJ8+fP55VXXrFvB7V7925GjRrFP//5T6rJQu8iIjXCxYsX7atHu7m58dBDD2kVQJEqytHRkcGDB7NgwQLWrl3LuHHj8Pb2BuCnn35iwYIF3HnnnUyZMoXY2FiKi4sNF4vIfzpx4gQAeXl5uLm5Ga4REbk5GpwSERER+S/uuusuFi9eTOPGjQHYtGkT48aN4+zZs4bLRORGPPDAAwAMHz6cxYsX07x5c8NFIiJSUwwePJgVK1YQEREBQG5uLnPnzuX3v/89p06dMlwnIlLzZGVlXXVs6NChdOrUiaeeeooNGzbwpz/9iUaNGhmoE5GyaNasGZMmTWL9+vW8/vrrhISEYLFYKCoqIiYmhsmTJzNs2DDef/99Lly4YDpXRP7l2LFj9q+12pSIVHcanBIRERH5FR06dOCzzz4jKCgIgCNHjhAZGcmOHTsMl4lIWUVERDB//nz+8pe/ULduXdM5IiJSw3h4eDBjxgwWLlxI06ZNAdi/fz/3338/H330EUVFRYYLRUSqv5SUFObOncudd95JVFTUVa8vWbKEsWPHamVZkWrI0dGRQYMG8c4777B27VoeeeQRfHx8ADh//jzvv/8+ERERTJ48mZiYGF1biRh29OhRAFxcXOy//4iIVFcWWzVZMzw0NJSCggKmTJlCZGSk6RwRERGpZYqLi5k/fz6LFy8GwGKx8NhjjzFhwoQy/ZygoCASEhIqIlFEfuGLL77A19cXf39/0ykiIlILWa1W3nvvPT799FP71jK33HILL730Eh07djRcJyJS/Rw/fpx33nmHb7/91n6sW7du9q24RaRmKioqYtu2baxatYrvvvvuim2QfXx8GD58OCNHjtTQhogBGzZsYOXKlTg5OTF//nzTOSIiN0WDUyIiIiJlsGXLFl544QWsVisAffv2Zfbs2bi7u//m95auWuXk5KQVq0QqyE8//cT06dPZt28fLVu2ZOnSpTg7O5vOEhGRWurw4cO88MIL9m0sHBwcePDBB3n88cdvaPVDDeGLSG118uRJ7r33XqBkhb8777yTkSNHamsgkVrkwoULrFq1itWrV3P+/Hn7cYvFQq9evbjnnnvo168fjo6OBitFRESkOqozY8aMGaYjrseHH35IcXExvXv3pkuXLqZzREREpJZq27Ytt912Gzt37iQjI4NTp06xadMmQkND8fLy+q/fFxQUZH8qrri4mIKCAnr27FlZ2SK1wubNm3nyySdJSUkBoEmTJvTr14/69esbLhMRkdrKx8eHe+65B1dXV/bu3UthYSF79+4lKioKf39/mjRpct0/q3QI//3338fb2xs/P7+KyhYRMSouLg53d3dcXFzsx7y8vCgqKuLee+9l1qxZ9OnTB29vb4OVIlLZ3NzcCAwMJDIyks6dO5Obm0tKSgrFxcWkpKSwadMmvvzySzIyMmjZsqXuBYiIiMh104pTIiIiIjcgNzeX5557jtjYWKBkL/eXXnqJ22677ZrnBwYGYrFYsNlsWCwW3NzcWLNmDZ6enpWZLVKjvfTSS6xZswaASZMmMW7cOMNFIiIi/5aSksKMGTNISkqyH7v33nt58skncXNz+83vLx3Et1gs1KtXjy+++KJMg1ciIlVZRkYGa9asYcWKFaSkpOh6XkSuS1paGitXrmTVqlWcPXv2iteCg4MZOXIkt912m1ahEhERkV+lFadERMrg4MGDnDx5koKCgl9dWUZEaj4nJyeGDBmCk5MTCQkJFBYWsmnTJnJycggODsbBwcF+blBQEBaLBcA+PFVQUEBxcTEhISGm3oJIjRMYGEhiYiJvvvkmgwYNMp0jIiJyBQ8PD+6++26aNGlCYmIi+fn5HDx4kLVr13LrrbfSokWL//q9vxyastlsFBYWkp6ezsCBAyvxHYiIVIzMzEwGDRrEzp07yczMBMBqtTJ8+HDDZSJS1bm6uhIQEEBkZCTdunXDarVy+vRpiouL+emnn9i8eTPLly8nLS2N5s2bl+sDjEFBQXz44Yf4+vrSqlWrcvu5IiIiUvm04pSISBmMHTuWw4cPM3LkSJ5//nnTOSJSRcTHx/PMM8+QlZUFQPfu3Zk3bx5eXl5XfMhVqvTyq27dumzYsEGDmCI34MSJE9SvXx8fHx/TKSIiImWWlpbGnDlziI6Oth+74447eOaZZ655bVi6eilwxbXlP/7xD3x9fSsnWkSkAk2aNIkdO3bQvXt3Ro0axaBBg3BycjKdJSLVUHp6OqtWrWLVqlWkpKRc8VpAQAAjR44kPDz8pv6O+eX9PhcXFxYtWsStt956s+ki1cbSpUvZv38//v7+PPDAA6ZzRERumsNvnyIiIiIivyY4OJjPP//cfoMkKSmJMWPGXHNoCkpWnbJYLBQUFLB06VITySLVls1m47PPPmPs2LHMnj3bdI6IiMgN8fb25rXXXuOtt96iYcOGAGzcuJFRo0YRFRV1xblBQUFX/Ll01SmAuXPnVk6wiEg5OHDgAG+99RaHDh266rUnnniCZcuW8cEHH9hXdxYRuRFeXl6MHz+eVatWsWDBAm6//Xb7Vn179uzhL3/5C3fccQfz5s0jOTn5hv4bpddiNpsNq9XK5MmTSU1NLbf3IFLVRUdHExUVxd69e02niIiUCw1OiYiIiJSDZs2asXjxYoYOHQrAhQsXfvX80hssy5Ytw2q1VnifSE1w4cIFJk6cyBtvvEF+fj4JCQmcO3fOdJaIiMgN69u3L19++SWjRo0CSlZImD59On/84x9JTU39r4P4UHI9uW/fvqsGrUREqpKsrCwWLFjAiBEj+N3vfseSJUv49NNPrzqvY8eOtGvXzkChiNRkwcHBvPrqq2zcuJHJkyfTunVroGSL0KVLlzJq1Cgefvhh1q1bd93354KCguwPRZYOtJ8/f54nnnjCvt2oSE1WXFxsH4Lu2LGj4RoRkfKhwSkRERGRclK3bl1eeukl/vznP9sHo671IVfpcZvNRmZmJitWrKjMTJFq65VXXiEhIQGAbt26sWzZMpo2bWq4SkRE5Oa4ubkxbdo0Fi1aRMuWRbBRfAAAIABJREFULQHYuXMn99xzD3Dt68lfHps3bx7p6emVEysiUkbu7u588cUX9u2yWrRoQbdu3QxXiUht4+npyYMPPsiKFSt4//33ufPOO6lbty4A+/btY8aMGQwZMoTXX3+d48eP/+rPstls9vt+vzx29OhRHn30UbKysirsfYhUBSdPnrQPGnbo0MFwjYhI+bDY/vNf9yoqNDSUgoICpkyZQmRkpOkcEamlVqxYQWpqKn5+foSFhZnOEZEq6tdWBvil0nMaN27MmjVr7MuGi8i1nTp1irFjx/LII4/wu9/9DgcHPQciIiI1z8KFC/nggw+u69zS68lRo0Yxbdq0Ci4TEfl1KSkppKam0r179yuOv/XWW6SlpXH33Xdftf2oiIgpWVlZrF27lpUrV141LNW5c2dGjhzJkCFDcHFxueK1wMDAq+75/fIByoCAAN59913d55Maa9euXUyZMoXc3Fw2btxo33pcRKQ60+CUiIiISDm63qGpUqXn/uUvf2H48OEVXCdSveTm5uLq6nrFsczMTDw8PAwViYiIVI6yXlM6ODjw2Wef0b59+wouExG5Un5+Pps3b2bVqlXs3r2b9u3bs3TpUtNZIiJlkpSUxNq1a9mwYQP5+fn24y4uLkRERBAREYG/v/9vbqMMJcNTQ4YMYfbs2ZXWL2LC8ePHtc2uiNQYGpwSERERKSc38uRs6c2Wtm3bsmzZsuv+cEykJtuzZw8vvvgiYWFh/PnPfzadIyIiUukCAwOB/77t87X4+fmxePFiXU+KSKUaNmwYZ8+eveLY2rVradasmaEiEZEbl52dzfr16/nyyy85cuTIFa+1a9eOY8eO/eq11i+Hqp544gnGjx9fob0iIiJSPrS3hYiIiEg5upGZdJvNxokTJ4iJiamAIpHq4+eff+b//u//+MMf/sDZs2dZtmwZJ0+eNJ0lIiJSqco6NGWz2bDZbBw4cIDly5dXZJqIyFUGDBgAQOvWrfnTn/5EdHS0hqZEpNpyc3Nj9OjRfP7553z88ccMGzbMvlXf8ePHf/P6zGKx2O8NvvPOO2zZsqXCm0VEROTmacUpERERkXJQ1u1Ufqn0+7p06cKiRYsqoE6kepg0aRI7duwAoHHjxjz//PP06dPHcJWIiEjluZEVTOHf15P169dn7dq1uLu7l3OZiNRm+/btY82aNVit1qu2nkpJSeHChQsEBAQYqhMRqVhWq5VNmzYxc+bM6773V/rRq5OTE/PmzaNv374VnSkiIiI3QStOiYiUwYoVK3jvvffYtm2b6RQRqUICAwPtN05uZib9+++/JzExsRzLRKqXZ555BmdnZ8aNG8fKlSs1NCUiIrXSjVxPll6HXr58mY8//rgCqkSkNlq+fDmjR4/m4YcfZtWqVURFRXHp0qUrzmnRooWGpkSkRnNxcWHYsGFlemCy9LzSBSHi4uIqMlGk0hw5coTo6GjOnTtnOkVEpFxpcEpEpAy+/PJL/v73v/Ptt9+aThGRKsRisdhviJR+aFX6gdf1fPD1y5suixcvrphIkWqgVatWbNiwgUmTJuHs7Gw6R0REpFLdzAqmv7RkyRJSUlLKqUpEarO4uDhOnDgBgKurK6NGjaKoqMhwlYhI5buRVUFLr+mKiop49tln7X+filRnmzdvZtq0aYwaNcp0iohIudLglIiIiMhNSkhIYNKkSQwYMAB3d/f/Okj1awNVpX+OjY3l6NGjlfsGRCrZxYsXmTp1KtHR0Ve95uHhYaBIRETErNKhKeCq68brVXrdWVhYyMyZMysiU0RqsIsXL151bPjw4XTr1o0ZM2awadMmpk2bho+Pj4E6EZHqqfT6LDs7myeffJL09HTTSSI35dChQwD4+fkZLhERKV+OpgNEREREaoJx48YBUFxczIEDB9i9ezfJycmcOnWKH374gcLCwqu+57+tKLB48WJmzZpV4c0ila2oqIjPP/+chQsXYrVa2bdvHyEhIbi7u5tOExERMSohIYGgoKCrtn6+1nbQ19oe+pfXlDabjcTERL766ivuuuuuio8XkWorIyODtWvXsnr1arKzs1m3bh0ODv9+1josLIywsDCDhSIiVcPNrgpqs9k4e/YskyZNYsGCBboPItXW4cOHAejYsaPhEhGR8mWxlfXxNUNCQ0PtewFHRkaazhGRWmrs2LEcPnyYkSNH8vzzz5vOqRVyswr5cV8maefzyL5cSG5WEdXjXy6RfysuLiYrK4u8vDysViuXL1/GarX+1/MtFgs9evSoxEKRynHo0CFycnLsf27WrBnNmjUzWCRSwmIB53oOuNd3wsunLrd29aB+AyfTWVKFHTtwmZ+O55CdWUD25SKKCnWBKuXj7Nmz5OXlUVBQYF91Ki8v75pD+L/0ywGr0g/1nJyc6NKlS2Vki0g1dPr06atWmerQoYM+zK8iHJ0suHk44u7pSMv27rS61c10klRhqWfzSD50mYyfC8i+XIA1p9h0Uo2yZ8+emxqc+s8BeFdXV3x9fcsrT6TSFBUVsXfvXgBat25Nw4YNDReJSGVzqeeAm4cTDXzq0qZTfbyb1DWdVG40OCUiUgYHDx4kOzubRo0a0bp1a9M5NVrKsWy+W3+Bn5JzTaeIiIhILeTTtC7B4T506uFlOkWqiJzLhcR+dZ5DSZkUFVSLWykiIiJSQzg5W/Dv2YDQwY1xrufw298gtcLe7WkkfPMzmWkFplNERESkFvLycaLnIB8692xgOuWmaXBKRESqFGt2EV8vO8Ox/VlXvebm6Ui9+o43tSyyiIiIyLXkZhWSfbmQ4v9YOahZa1eGjGmOl0/NeYJKym7X5ovEfZ161cpSLvXq4O7lhEMdXZ+KiIhI+SkqLObypULyrUVXHHdytjBwRNMa8eGU3LgLKVbWLznNpYtXDkyVrFTmhHO9OobKREREpCazZpfcP/3PBwobNqnLXb9rScOmzobKbp6j6QAREZFSly7m8+V7yWReKtmGwtm1Dv6h3jRt7UbDZq6G60RERKQ2SL9o5fypHH7YmUZWegFnT+by6ZvHuefRVjRrU890nhjw1Sen+XHvZfufOwR40apDfRq3qIdjXa34ICIiIhUn31rEuVM5JB/IJPlAJgV5Nr7+51kunLEycKS2Pa+Njh24zFefpNg/sGzQqC6denrTtJUb9RvoYQ8RERGpeJlp+Zw/lc3BXWmkp+bz8/l8Pvt/xxn+cKtqu8W0VpwSEZEq4dLFfJb+v+NYc4sB6BzqTfewRtRx1IdRIiIiYsahhDR2fX3e/udRE1vTsn31/OVfbszyBcmcPpoDQKMWLvQd1lwfSImIiIgRl87nsm31T6Sn5gPQKcCDO8e2MFwllenw3gzWf3IGAAdHC73vakq7ztpaXERERMw5uvcS2786Z//z3Y+05Ba/+gaLbow+jRYREePyrcWseC+5ZGjKAn2HNyNwYBMNTYmIiIhRnYK8uePBVtRxLNmGbfVHp8n4ueA3vktqiq+XnrEPTbW41Z07xrbW0JSIiIgY06CJK0PHt6FRcxcADu3JZGf0RcNVUlnOn84l6tOfAKjr4sBd41praEpERESMa9+tAXf9vg1OziWf6X71SQo/n8szXFV2+kRaRKQMZs+ezR/+8AeWLFliOqVG+WblT1z+1/Z8PW9vol/6RUREpMpo0sqN2+5rCUBBXjHrl6QYLpLKcPzAZX6IzwCgcQtXBo5qiUMd3UIRERERsxzr1mHwmNZ4+ZQMc2/fcJELKVbDVVLRiotgzaLTFBfZsDhYGDymFQ2auJrOEhEREQGgYTNXwu9vicUCRQU21i0+DdVi37t/010/EZEyOHjwIHv27OHkyZOmU2qM86dzOZCQCUDbzh50CvI2XCQiIiJypWZt3Oje3weAc6dyOZyUYbhIKto3K88C4OpWh4GjSm78iIiIiFQFdZwcuO2+VjjWLblA2brqrOEiqWiJ234mK6PkodPedzXBu6mGpkRERKRqadSiHj0HNwEg7UI+++LSDBeVjQanRETEqC0rSm7uONa10GtwU8M1IiIiItfWJdQHdy8nAGJWnaOosJo9NiXXbU/Mz2SmlXwwFTS4Cc716hguEhEREbmSu5cT3cMaAXDmRC5H9mUaLpKKkptVyI6vLwAlK6He0qWB4SIRERGRa+sY6I13E2cAYr+6QL612HDR9dPglIiIGPPzuTzOnS5ZTrxbXx/quupDKREREamaLA4WAgeVPDWVfbmIEwezDBdJRdm3o+SJuAaN69LW19NwjYiIiMi1+fVqiItbyb20fTsuGa6RinI4KZOCvJKHNoJvb2K4RkREROTXBdzWGIC83GKO7Ks+q/ZrcEpERIw5cyLb/nXrTvpQSkRERKq2lu3dcPjXnPcvr2Ok5rBmF3HpYgEArTU0JSIiIlVcy1vdAThzIgebFkStkVKOl/ze4epWh4bNtEWfiIiIVG3NWrvh5FwyhnTmRK7hmuvnaDpARKQ6+fTTT00n1Chp5/MBcPN0sm99IyIiIlJVOdRxoElLN84mZ5N2Ps90jlSAtAv//v+1eTs3gyUiIiIiv635LfU5kpRBUYGNrPQC6jfQ/bWa5tK/fu9o0d7dcImIiIjIb7M4WGjaxo3Thy9Xq/unWnFKRESMycoseZrf3VM3dURERKR6qO9V8vxRdmah4RKpCKXXp6BrVBEREan63Dz+/Wx89i+uY6TmyPrX7x31dG0qIiIi1YS7Z+n90+pzfarBKRERMcaaXQSAs2sdwyUiIiIi16duvZJf/HOyigyXSEUovT4FcK6nRbpFRESkaqvn/u9hmpxsXZ/WRNacYgBc6+n+qYiIyP9n787Doqr+P4C/URQGFwbFBdlBFMXEfd9x18wtK5fU0qTUXHL7luWeS2mWmZpL5ZZbpua+b6louIUKoqAoYgiCKIsywO8PfozcubMBs13m/XqenriHO3c+cmfOvefczzmHpKFMudx71HQJ3Z8ycYqIiMwmJyf3/yV4NSIiIiKJKFHSBgCQk51j5kjIGPLuT2Fj1jCIiIiI9GKTr08tWzrPpUhf+ZscNrxBJSIiIon4/9uW7GzzhlEQHD5JRFQAt27dQmpqKipVqgRPT09zh0NERERERERERERERERERESFxDk+iIgKYO7cuQgODsbGjRvNHQoREREREREREREREREREREVAROniIiIiIiIiIiIiIiIiIiIiIjI6jBxioiIiIiIiIiIiIiIiIiIiIiIrA4Tp4iIiIiIiIiIiIiIiIiIiIiIyOrYmjsAIiIp6du3LxISElC7dm1zh0JERERERERERERERERERERFwMQpIqIC6Nevn7lDICIiIiIiIiIiIiIiIiIiIgPgUn1ERERERERERERERERERERERGR1mDhFRERERERERERERERERERERERWh4lTRERERERERERERERERERERERkdWzNHQARkZTMnTsXMTExaNOmDQYPHmzucIiIiIiIiIiIiIiIiIiIiKiQmDhFRFQAt27dQkREBDw9Pc0dChERERERERERERERERERERUBl+ojIiIiIiIiIiIiIiIiIiIiIiKrw8QpIiIiIiIiIiIiIiIiIiIiIiKyOkycIiIiIiIiIiIiIiIiIiIiIiIiq2Nr7gCIiKRk+vTpSE1NRaVKlcwdChERERERERERERERERERERUBE6eIiAqgVq1a5g6BiIiIiIiIiIiIiIiIiIiIDIBL9RERERERERERERERERERERERkdVh4hQREREREREREREREREREREREVkdJk4REREREREREREREREREREREZHVsTV3AEREUjJ37lzExMSgTZs2GDx4sLnDISIiIiIiIiIiIiIiIiIiokJi4hQRUQHcunULERER8PT0NHcoREREREREREREREREREREVARcqo+IiIiIiIiIiIiIiIiIiIiIiKwOE6eIiIiIiIiIiIiIiIiIiIiIiMjqMHGKiIiIiIiIiIiIiIiIiIiIiIisjq25AyAikpJNmzaZOwQiIiIiIiIiIiIiIiIiIiIyAM44RUREREREREREREREREREREREVoeJU0REREREREREREREREREREREZHWYOEVERERERERERERERERERERERFbH1twBEBFJya1bt5CamopKlSrB09PT3OEQERERERERERERERERERFRIXHGKSKiApg7dy6Cg4OxceNGc4dCRERERERERERERERERERERcDEKSIiIiIiIiIiIiIiIiIiIiIisjpMnCIiIiIiIiIiIiIiIiIiIiIiIqvDxCkiIiIiIiIiIiIiIiIiIiIiIrI6tuYOgIhISvr27YuEhATUrl3b3KEQERERERERERERERERERFRETBxioioAPr162fuEIiIiIiIiIiIiIiIiIiIiMgAmDhFRERkZWbOnISUlGQAQMmStpgzZyns7e3NHBXl2bRpDUJDLyi3g4M/Q40atcwYEVHxEBJyFlu3/qrc7tz5TXTt+pYZIyoahUKBly8zkJGRAYUiEwqFAtnZWShZ0hYVK1aCnZ2duUPUKisrC6GhF1Ctmjvc3DzMHQ4RmVlxq6OLG54fIuMpTu3znJwcvHz5Ei9fZiAz8xUyMzOhUGQiOzsbMpkDKlashJIlS5o7TGRlZeHVq1d4+TIDr169hEKhQFaWAjk5OShfXg653MncIRKRmcXHP8aCBdOV297efhg7dqoZIyJVxen6SWRJituzifz3fJmZmcjKykJWlgIymQOcnCrC1tayU2UePXqIhIR4PH2agOzsLDg6OkEurwC53AmOjk4WH7/U8K9JRERkZa5evYT09DTldlaWwozRkKp79+7ixo1ryu3k5KdmjIao+Hjy5LHguxUQEGjGaArv+PEDWLjwK537yeVOcHX1QIcOXdGxY0+L60C8fDkEX345HoGBjbBo0Qpzh0NEZlZc6ujiiueHyHiKS/t82LDeiIuL1bmfh4c3/PxqoU+f9+Dn52+CyF579Oghhg/vo3M/mcwB7u5eqFu3Afr2HYiKFSuZIDoisiSpqS8E9z6vXr00YzSkTnG5fhJZmuLybOKHHxZg374/dO7n7FwZvr410KNHPzRp0hI2NjYmiE67589TsGfPNhw7dgCxsTEa95PJHNClSy+0b98FNWsGWETsUlfC3AEQEREREVmKzMxM5OTkmDsMIo0UCv06A5OTk3DjxjUsW7YQQ4f2wrFj+40cWcHs3/8nAODatX/w339xZo6GiIjIcuXk5CAzM9PcYRBplf/htTYxMdE4dmw/xowZgpkzJ+Hp00QjR/aavu289PQ03L59Ezt2bMTAgd2xZs0Pet+DExERWYNXr16ZOwQirfRNeE1IiEdIyFl89dUEjB37PsLDw4wcmXanTx/FkCFvYv36VVqTpoDce9Zdu7Zg3LjhiIi4YaIIizcmThERFcDcuXPx0UcfYePGjeYOhYiIDCg6+g5Wr/4eb7/dERcunDZ3OEQGlZychEWLZgim2janxMQnOHfupHL7xImDZoyGiIjIMiUmJmDHjo348MP++OWX5eYOh8jgzp8/hfnzv7D4pKTt2zdg06bV5g6DiIjIrLKysnD5cggWLPgSb77ZEs+eJZs7JCKDiowMx7Rpo/HkyX9mef/ff1+HefP+p/eAhDwymQN8fWsaKSrrwqX6iIgK4NatW4iIiICnp6e5QyEiIgP5+eel+OOPTcrt7OxsM0ZDVDByuRMGDBgKe3t7lCpVGunpaYiPf4yTJw8jISFesO+cOVOxdu0Osy83cuTIXsH2wYO78c47wzilNBER0f87d+4kZs2arNzm/SlJTVBQd/j7B6B0aTsAwNOnCbh79zbOnj0u2O/69VCsX78SH3wwxhxhYujQYJQrVx52dvbIzHyFxMQnCA0NEc02sHnzOtSuHYjGjVuYJU4iIiJzGz16MKKj7yi3eX9KUhIQEIjWrYNgZ2cPW1tbpKQk49GjWNFyfunpaZg7dxqWLl1n0n7KHTs24NdfV6j9nYuLKxo0aIZq1dyQkpKMp08TcedOuPL72KvX2yhVqpTJYi3OmDhFRERERFYtJeWZuUMgKjRXVw/06zdIVD58+Gj8/vs6bNz4enR8enoarly5iI4de5gyRAGFQoG//tohKIuLi8XNm9cREBBopqiIiIgsy4sXz80dAlGRdOrUA/XrNxGVP3wYg6lTPxYk+B86tMdsiVN9+w6Cvb29oOz994OVS7bkd+bMMSZOERGR1UpKMt3yukSGVr9+Y/Tp856ofPjwT/DNNzMQEnJWWRYeHoa4uFhUq+ZmktjCw8OwevUPovIGDZpi0qQZGgfA3rr1Lw4e3I0uXd4ydohWg0v1ERERERERFTO2trYYPHgk6tSpJyi/e/e2mSLKdeXKRdFMWABw/DiX6yMiIiIq7tzcPDB58kxBWXJyksUt99O0aSsMHjxSUHbr1r9mioaIiIiIjKFcufKYPHmWqPzevTtq9ja8ly9fYtGiGaLyNm06YtasJVpXDahV6w1MmDAdrq7uxgzRqjBxioiIiIiIqBiysbERjfS/cyfCTNHk2r//T7Xlx47tR0ZGhomjISIiIiJTq1Wrrqjs/v0oM0SiXd26DQTbMTHRyMzMNFM0RERERGQM5cqVFw08zb8spTGdOXMUsbExgrI2bTpi2rS5KF26tElioNe4VB8RUQFs2rTJ3CGQiTx/noI//9wMAKhQwRk9e/ZXll+79g8iIm7g5s3rePjwPjw9feHrWwN16zZA8+Zt9X6PjIwMXLv2D+7ejUBkZDhu374JB4cyqFkzAF5evvDx8UNgYCOULFlS72O+evUKISFncPbscdy/H4WkpERUqlQFLi5u8PWtgR49+hXsD/H/oqIicePGVdy5E4GIiBt4/jwF3t7V4eHhDXd3L9Sr1xguLq6FOnZhSPX8AEBY2FWcOHEId+6E4/HjWMhkDvDw8IGHhxe6dOlVoGPlSUiIx5UrFxEVFYmIiBuIjY2Bm5snvLyqw93dE/7+deDvX6dQxzYUQ8S4Y8cGpKWlAgDeeWc47OzsoFAocP16KCIibuDWrX8REXEDlSu7wNe3Jvz8aqJTpzc1NjI2b14LhSITYWFXBOWHDv2Fu3eFySVOThXx5ptvC8qio+/gzJmjyu2AgHpo2LAZMjIycPLkIZw7dxIPH8YgNfU5nJwqwt3dC+7uXgBylK/p0aM/KlZ01vn3e/LkPxw48DrhpFw5R7XTCxvC2bPHERWVOytR+/Zd/z9mICLiBsLDw3DrVhjCw/9FqVKl4etbE97evujYsade/4489+9H4datf3H37m2Eh4chPj4Ovr414etbA15evggIqIeqVasVKO6HD2Nw8uQhXLsWikePHgDIXcbO3d0LLVu2K9Cx8qSnpyM09Dyiom7j9u1biIy8hUqVqsDDwweent7w8qqORo2aF7geMKeyZcuZ7b0TEuJx7txJtb9LT0/DxYtn0aZNRxNHRSQthr4WqsrJyUFY2FXcvRuBO3cicPPmdWRnZ8HXtyZ8fPzg5eWLwMBGBa5LjFFHW+L9D6+hr0nhGmqIGA19zk+cOIQHD6Jx61aYoDw09ALWr18pKLOxscHbbw8VLDOWmvoCf/yxUbmd11bKzs5GaOgFHD26T9lOLFOmHNzcPOHvHwCF4nUySOPGLVGr1hs6/37Z2dn4/fd1yMpSKMv69x8CB4cyOl9bUJGR4Th/Pvceolatusrl0h49eoiwsCuIiLiJGzeu4vnzFPj51YKPT3U0b94Ofn7+er9HYmLC/7d5wxEZGY6oqNtwdfWAr29NeHn5oEaNgAIdDzBO+zwnJwdXrlxEZOQt3LkTgcjIWyhRoiS8vavD09Mbbm6eaNq0NcqUKVvgY5tKTk6OqEwmczBDJAUnpft+IlOQav387Fkyzpw5iosX/1b227i6eqBaNXfUrdsA3t5+BToeYJn1s1TPj7X0bxsjRkP3mScmJmDfvh0AcmeIzO/339ehbFnh59nf/w00adJSUHbhwmncvn1TuZ13z5yYmICDB3fh6tV/lG2QChWc4ebmIfg3urt7o337Llr/bnmOHt2nPBYAtG7dEd7e1fV6bUFJtW1urc8mCspU/ae7dm0RlQ0b9gnvOc2EiVNERERqJCY+waZNa5Xb9es3RalSpTBlSjDi4mIF+yYn/4Nr1/7Bzp2bERTUHaNHT9bZCI6OvoM5c6aKssmB3FGMeerWbYgpU2ahUqUqesU8e/YUhIcLO9mTk5MQGRmO06ePYsuWX5GenqbzWHkyMjLw228rsHPnZtHvEhLicenSOeX2Bx+MRt++g1CqVCm9j19YUjw/r169wk8/fStIfsmNLwlxcbEICTmD7ds36DxOfjk5OTh0aA+++26u6HfJyUkIC7uq3O7UqSdGjPgUcrlTgd6jqAwZ48aNa5Sf32rV3NG6dUfMm/c/hIScER339u2bOHAAOHBgF6ZNmwc3Nw/R8X77baWoDABCQs6Ijunq6iFKnIqMvCX4HPbu/S4qV66KL78cr+ZzmISMjHQkJyfh+vVQZbmDQ1n07z9YbRz5nTx5SPBeTZu2Mlri1KlTR3D6dG5CWELCE0yc+CW2bPkFv/zyk2jfmJhonDgB/P77L/jii/nKTjhNFAoFfv99HTZuXC36XWjoBYSGXlBujx//Bbp1661XzPv27cQPP8wXlSckxOPatX+wd+8OvY6T340b1/DNNzPUnsvIyHDltr9/HYwb9zl8fAresWoKqteEGjVqmSkS4MiRvYLtTp16CsqOHt3HxCkiHQx9LcwvJeUZliyZg/PnT4l+FxcXi7NnjwMAnJ0r4/PPv0ZAQKBeMRu6jrbk+x9eQ3NJ4RpqqBgNfc6PHdsvaGPlf23+e8E83bv3FSROJScnCfZzdfVA+/ZdsXDhV2rridyHGh7444/Xg8Tu3InA7Nnfqf335hcRcQPr169SbstkDnjnneE6X1cYt2/fUP67nJ0r47ffduP69VD8739jRPuSKSehAAAgAElEQVQmJMTj/PlT2LRpLUaO/BR9+w5CiRLaF104e/Y4vv12lqitnJychBs3rim333rrHXzwwRjB31wTY7TP4+MfY+nSeYLve57Y2BicPZv7s1zuhHHjPkeLFoVLfDS26OhIUZmnp48ZItEu/0NeAAgMbKTzs0RkbaRYP9+4cQ2zZ08WJYHkHVO13aoPS62fpXh+rKl/Oz9DxWjoPvMnTx6rvQcFgN27t4rKevUaIEqcOnv2hOB75eNTA7GxDzBjxkS1/1Ynp4qC95TJHNC8eVudn5+MjAx8841wOeAmTVppfU1RSK1tbq3PJvSRkZGBu3dvC8p8fWsa/X2jo+8I2p5A7mxTXHrPfHinT0REpIflyxdhwoQPRQ0MVceO7cf8+V9o3efAgV0IDn5PbVKOquvXQzFy5AC1N8n5hYeH4ZNPBokalaoK0qiMjAzHJ58MUttgU2fduuX45JNB+O+/OL3fw1As/fwkJiZg2rRPRA2Tonj2LBkzZkxU2zBR58iRvRg2rDcuXw4xWAy6GDPGX375CTNnfiZqjKqKjAzHmDFDkJam/2e/sOLjH2Ps2KEaP4d9+ryHHj36Csr27/9T7YhrVceOHRBsd+jQrfCBFsChQ3vw7bez1D78yy89PQ3Tp4/DrVv/atwnISEeU6d+rPaBrzpLl87DnDlT8eLFc437ZGZmYtmyhWof+BZWVlYW1q37ERMnjtBZpwC59e/HHw/Etm2/GSwGQzl9+qigc00mc0DXrvo9SDc0hUKBvXv/EJSNGjVBMLtASMhZJCY+MXVoRJJlyGvhjRvXMHLk2zrvaYDc+nzixBHYuHG11muYMepoKdz/5OE11DKvocaM0ZDn3JBmzZqssZ5o0aIdevd+V1AWEnIWCQnxOo975swxwXZQUHfY2dkVPlA9JSTEY8mSOWof+qpavfoH7Nypeebwly9fYvnybzBnzlS92sq7d2/F2LHvCwbTqGOM9vmJE4fw0UfvqH0oryo5OQmzZk3GrFmToVAodO5vSi9fvsT3338tKBs8eKTFLUUSG/sAa9YsE5S9955xEgOJigsp1M8HDuzCxIkjRElTRSGV+lkK58da+7eNGaMh+8wN5Z9/zqtNmsozePBIwYxTeTOU63L16kXBtouLK2rWDCh8oAVg6W1za302oa+1a5cJ6pU6deqhdm3x0tKGpq492K/fIKO/L2nGGaeIiIj0oNr4DQgIhIeHNx48uCfInAeAS5fOITw8TO30oxcv/o2lS+eJyvNuxjIyMhAeHiYY2ZienoaZMydhw4a/ULlyVdFrw8PDMG6c+g68gIBAuLt74d69uzobnfmlpr7AzJmfiTrMnZ0ro0aN2rC3lyEhIV4wcw6QOxL6+++/xrx5P8DGxkbv9ysqSz4/qakv8OmnQ9U+fPDw8EbNmgFITn6qdmS5NkuXzkNIiLDRKJM5oHbtupDLK+DFi+eIiAgTdAalp6dh9uwp+O233XB0lBfo/QrDmDEmJMQL/qaurh544436SEpKFL1nenoa9u/fKZrZqX37rnj5MgNXrlwUNI68vavDxcVNsK8+S96oLkHWtGkrODlVxIULp5GcnISgoO6wtS0FmcxB+X6xsTEIDw/TuhzKgwf3ROuqN23aWmc8hpJ/VJhM5oAWLdohM/MVrl8PVTtNt7oZCrKzszFr1mTRqG253AkNGzZH1aouiI6+KzoXZ88eR4UKzhg9erLa2L7++nO1S785O1dWNnDVxanNvn1/YOtW8cPRgIBA5exykZHhouTKtWt/RO3agahTp57e72UIWVlZyM7OVo4ETU19gUePHuLAgV3Yt0+YqDR58kw4OVUwaXx5Ll8OEXxng4K6o1y58mjbthMOHtytLD9x4pBes7ARkWGuhUBuJ+rEiSNE5R4e3qhXrzHs7e0REXET1679I/j9hg0/w8PDW+NMccaoo6Vw/5Mfr6G5LOkaauwYi3rO33ijPkqVKo3796MEMcjlTqhdWzyS3N5epjWe2NgYwXECAgLh5VUdN29eQ3T0Hbz11gBUrlwVTZu2Eny3jh8/gAEDhmo8blZWFo4d2y8o03cJFUNQfe+mTVujfHlHRETcED2U3bhxDbp37wcHB/FScJs2rcaePdsEZTKZA+rWbYjq1WsgPv4/hIVdETxsjImJxpw5U7FixWbY2oq71o3RPo+MDMeCBdNF5R4e3vD1rYmcnGw8evRQVE+cO3cSO3ZswLvvmj7hJ39CgEKhQFJSIv799zI2blwj+Ez6+9fR+lkztuzsLOXPGRkZSEx8gjNncmczya9fv0GoX7+JqcMjkhxLrp937dqCFSsWi8plMgfUqVMPcnkF3Lx5Xa+BlHmkVj9b8vmx1v5tY8dY1D5zR0cn5Qxpqm2HBg2aiu5Fq1fXPUvPgQO7lD/L5U6oX78pAODEiYMICAhEjRq10LNnf6xe/b1yv4MHd+ucofzkySOC7a5d3zLZ8wlLbptb87OJ/BQKBXJycmBjY4OcnBw8e5aM6OhIbNu2XpDMJZM5YOLEr0wyy+jNm9cF23K5k+SWNCxumDhFRERUAP36DcK77w5H+fKOyrKrVy9h5sxJggcVf/yxCV98IRy9rVAosHLlEkGZTOaAuXO/F3XAnzhxSNTwXr9+FSZNmiEoy87OxvLl34ji7NVrAEaM+FQw4jc29gGmTAnWa/Twr7+uEO03ZswUdO/eV7C+8rNnyVixYjFOnDioLAsNvYAjR/aic+c3db6PoVna+QGArVt/Ff0t69Sph88//xoVK1ZSlqWnp2POnCl6jVA7c+aYqLHaq9cADBv2sWBKZYVCge3b1+PXX1fke580rF79vdpYDclUMQYGNsL48V+gWrXXiU5xcbGYN2+aYKrbjRtXo3fvdwWdM9OmzQEAfPvtLMFDriFDPkLLlu0L8K8VqlGjNmbOXIyKFZ0B5HbA37t3R7k2erduvQWjyI4c2ac1cUp1NH+XLr0gk2l/SGZocrkTvvxyEWrXrqtsOKanp2PZsgWCjreQkLOIiooULWdz8uRhUUdhUFB3jB//hWB0eUrKM8yZM1XQIbRnzzb06vU23N29BK+/ePFv0WdMLnfCzJmLBX/PnJwcrF+/Eps3r9P574yLixXVqYGBjTBu3OeiaZLPnTuJRYtmCOqWb7+diZUrt+g1/byhhIeHoVu3plr3kckcMHPmt6hXr7GJohLbv184qq1du84AgJYt2wsSpw4d2sPEKaICKsq1EMjtZFU1evRk9Oo1QFAWFRWJ//1vtKDjc926H9G8eVvRMhHGqKOlcP+jDq+hlnMNNVWMRTnn77wzDABw+PBfWLx4trK8ffuuCA7WPDJfF5nMAfPn/6g8vzk5OQgLu6ps53Tt+pbgwcf+/X/i7bff1/iw6ebN64K6IH/CnSlNmjQDbdp0UrZ7c3JysHv3VsGD8fT0NBw7tk+07PajRw9FSXTe3tUxb94PgnaaQqHAunU/CpYzjImJxvHjB0RtXmO0zxUKBRYvniUoc3Fxxbhxn4sSeaKj72Dx4lmCuv+XX35C8+ZtTb4U3vTp43TuExTUHZ9++j+TzFSmSZ8+upfLGjlyHO9PiQrI0urnxMQEtUlTEyZMR5cuvQTXuwsXzmidDSf/+0uxfgYs7/xYc/+2qWIsbJ+5i4srZszIPTfvvNNZcP83ZcrsIg3O69r1LYwZM1XZlhw5cpwylvbtuwoSp0JDLyA+/rHaQctA7r12/r8NALRp06nQsRWWJbbNrfXZhKotW34VJcar8vPzx5dfLkKVKi4mienBg3uCbVdX7Us4kvFxqT4iogIYNGgQGjVqhHnzxDPSUPH3ySeT8NFH4wUNDACoV6+xaMp21WxxADhw4E/RqKWlS9epHbXcvn0XfPnlQkHZkSN7ERUVKSg7efKQ6EHKZ599hdGjJ4s6H11d3fHdd+rXJM8vLOyqaNTQDz/8ijfffFvQYAMAR0c5pk2bg27d+gjK164VTmlvCpZ4fmJjH4g6E7p164OFC1cIGiYAIJPJMGPGt/Dz89fwL8yVkvJM8BAFAIKDJ6pdh97W1hbvvfcBpk6dI4r14UP9R9AVlKli7NChG+bO/V7QGAVyG/UffzxJUJaenoanTxMK+k8pMBcXV3zzzSpl0hQA2NvbC0aLdOrUU/Caffv+QHp6usZjHj0qHBHYoUNXA0WrH2/v6li+fCPq1KknGG0jk8kwduw0wVJrAHDv3l3BdkZGBlatEiYlBgV1x+TJM0VLcpQv74ivv14m+h6sX79KsK0u0bFGjdpYuXKLKAnNxsYGQ4d+jLfeekfrvzMnJwfLli0QlLVo0Q4LF/6kdm35Fi3aYfnyjYKyuLhYnDp1WOv7mMO77w4TPTQ3pSdP/hNMMS6TOSg7kuvWbSjYNyYmGrdv3zJpfERSVtRr4d27t0XT9Y8f/4WoYxYAfHz88OOPGwRlcXGxOHhwl6DMGHW0FO5/1OE11HKuoaaKsajn3Fi+//4Xwfm1sbHBG2/UVz4obty4pSC2uLhY3LhxTePxVBP7u3Z9yySjsvPIZA5YvHg1OnXqKWj32tjYoHfvd9GggTCp/O7dSNVD4Jdflgu2XV09sHjxalE7zdbWFh99NF60pOHatcuQkZEhKDNG+3z79vWC2WednStj2bL1amc/8vaujiVL1sLDw1tQrm6WNXPz9q6OTp16iB7uWZpOnXqiYcNm5g6DSDIstX7esEF4PySTOWDZsvVqZ6Rp1qw1pk8X3jOoI8X62VLPj7X2b5sqxqL2mRtDUFB3TJgwXXAfULGiM9zcPJQ/t2rVQfCa48cPaDzeP/8IZ0sKCAgUtZGNzRLb5tb6bKKw+vYdiPLlTTcT1rNnwhmJq1Z11bAnmQoTp4iIiPTg5+ev9YFBUFB3wXZCQjyysrIEZRs3rhZsd+rUE15evhqP2bx5W8F63gBw9Og+5c+5D1KESzu0adNR6yiTypWrijrrVf3220rB9gcfjNa5HviHH44RHDc5OalAy3oUlSWeHyB3pEd+crkTgoMnqp2SGgDs7OxES8Sp+uuv7YKRQA0bNhN1Qqhq374LAgMbCcpiYqK0vqYoTBXjJ59MEj00zBMQECg6P0+e/Kf1eIbw0Ufjdc5C4OPjJ2qEnj8vXioHyB1BpLpMyxtvNCh6oAUwfPhoODtXVvs7mUwm+n49efJYsH327DFRfTBo0AiNMxiUKlUKffsOFJSdPn0UKSnPlNv79+8UJTpOmDBd60g3Dw/tiUP//ntFMKpKLnfChAnTtU7r7erqjvffHyUoM9UD0IL45ZefMHBgd2zY8DOys7NN/v75Z3QDcuvXvM4xe3t7dOjQTfB71VGCRKRZUa+Fu3dvFWw7O1cWJfjmV6lSFXTr1ltQtm/fTsG2MepoKdz/qMNrqOVcQ00VY1HPuTH07TtQ52wWpUqVwptv9heUqbZt8igUChw+/JegLG8mSVPp2bOf1mUTu3TpJdiOj48TbD969BCnTx8VlL333nDRw578VOuc5OQkXL16UbltjPZ5RkaGYIQ+AHz++dcoV668xteULl0aY8dOE5RFRlpeUnp09B1MmzYaI0cOEI22tyRHjuxFcPB7mDlzElJTX5g7HCKLZ4n1c24ygjCZ4MMPx6BGjVoaj+nm5qnxd4B062dLPD/W3L9tihgN0WduDB98MFrnPqqfx4MHd2vs01L9XGpr0xqLJbbNrfXZRGEtXPgV3nuvq2DwpzGpfnerVjXNTFekmWQSp/JGLZlqPVIiIqKCUNc5npz8VPlzauoL0Y2Q6kMNVSVLlkTPnsLO6/yZ+HfvRoiOOXTox3rHrE5OTo6o0d6xYw+drytXrjzq1hUmc1hS56c5zo9CocDZs8cFvx8x4tMiLz9y506EYFuf9dptbGzQpElLQZkxH0yZKkZdx1QdyZeY+ETr/kUllzuhRQvdSz0AQI8e/QTbBw7sVrvf338LP0NduvQSjTozN9WGf3y8sOEfExMt2G7TpqPamR3ya9myg6gT7PHjR8qfL1w4I/hdp049RUsbFdS9e3cE223adBKNxlOnUaPmgu27d28XKY6CcnX1wPz5P2Lx4tVYsmQNZsz4BmPHTkXfvgNFf8ONG1dj9uwpUCgUJotPoVCIOn/athVOl96ypfB7c+DALrx69crosREVB0W9FuYfJQ/kzlCnqRM1j2rnbHT0HeTk5Ci3jVFHS+H+pzB4DTXdNdRSYtR1zo2he/c+uneC+AHTgQO7kJaWJtrv338vCx6W1KhR2+QzW+r6/qv+nR89eiDYfvjwvmBbLndC27bak79cXFzRtGkrleM+VP5sjPa5atyurh4ICAjU+TrVfWJiopGZmVmkWApq+PBPsGjRCixZsgYLFizHlCmzMGLEWFFssbExGDHibVy9esmk8eWZNWsxvvlmFZYuXYc5c5Zi4sQvMWTIR6I+hPPnT2Hs2KGIjzd+siORlFli/aw6E42Liyu6dhXezxaUVOtnSzw/1tq/bSkx6uozN4agoO4aBxrk16BBU8jlTsrtuLhYhIVdFe2XmvpClDilOluVKVha29yan02o065dZyxc+BOWLFmDb7/9GV98MR/BwRPRvr1wZYf09DTMnDkJ27evN2l8AODgoDkJlUxD+zfOApljhDQREZE+nJ0rC9aLfv48RTnlaf4GYR5v7+o6j6l6Q52/gao6Urxu3YbK6WwLKyEhXtAJDgDffTdXr9deuiTsiHj48D7eeKN+keIxJFOfn//+i1PdHe3addE7Xk2io4XTZG/evFY04lsd1cZ4TIzxEtssJUYnp4qC7efPn2nY0zB8fGrovW/r1kFYuvT1sq/Xr4fi0aOHgumcc3JycOyYcBpqQ3yGDE11hoqUlGTB9oMHwo61/MsWamJnZwd3dy/BVO2PH8cqR4TevStspGsbiaive/eEI52OHNmLuDhx3aDq+fMUwbbq9PLGJpc7iabTzzN48Ej8/vs6bN/+evru8+dP4ejRfeja9S2TxHf5coigE1Qud0Lt2nUF+zRoIFz+JD09DaGh59G8eVuTxEhUnGm7Fubk5IjqLF0jnAH1I/CfPk1ULlNrjDraUu4tDI3XUNNdQy0lRl3n3Bh0jRrP4+HhjYCAQMESfefOnRA9xDt1SvhgqnNn04/o18XR0UmwrfpAVvXc16xZR+MMAfl5efkiJORsvuPEKn82Rvv8/n3h5zY2NgbTp48r1LEeP441aYJbzZoBopkFAODtt9/HjRvX8PXXnwva5998MxO//rrL5Ev31avXRO0DxHffHY7Tp49g4cKvlGWxsTH49dcVmDJllilDJCpWzFE/q95P5Z8BubCkXD9rU1yun1Lo37akGLX1mRuDp6e37p2Qu8xbz579sHHjGmXZ0aP7RIlj+T9bQO5gE22zv5mLqdvm1vxsQh03Nw/Uq9dY7e+GDg3GsmULBDMUr1mzDM2atTFq/azabs//PSTzkFziFBGROdWqVQtlypSBp6f26XrJOjk5VdB4c6PasHR19dBrFkXVG+rY2BgoFArY2tqKRpOoJvEUhroRKqqNMX3lzRZpKUx9flRHYbm4uBa5YyYjI0PQuQDkjiRRHZGiD2OdH0uK0dSN5GrVtM8AkV/ZsuXQpUsvHDq0R1l2/PgBDB48UrkdGRku+Ft6e1cv8owQxlC2rPa/s2qHYqVKVfQ6rrNzZdFDXwB48eK5qPMuf8JZYanORJGenlao+s/Ozq7IsRhKmTJl8cEHY3Dv3l3Bv+WXX5ajQ4duenVwFtX+/X8Ktrt06SX6bjs4OKBFi3Y4d+71kpWHD+9l4hSRAWi7Fj59migqq1hR98hfdUtxxMfHoWJFZ6PU0ZZ0b2FovIYKGfMaaikx6jrnhubi4qpzpHp+3bv3ESROHTiwS5A49erVK5w8eUjwmlatgooeqIFpWzIIEM4UDABVqui3LIbqQ8T8D3uN0z6PFpUVtn1uY2M59V9AQCA+//xrTJw4QlmWkBCPI0f26j1DmrHZ2tqiQ4duSEiIx9q1r5e5OXZsPwYMeB9eXr5mjI5IusxRP6veA7i6Fi0pByi+9XPxuX5afv+2JcWorc/cGKpUqab3vkFBPQSJU4cO7cGoURMEn9WTJw8LXtOhg3AGIUth6ra5tT6bKAwXF1dMnToHH300QNBe3rRpLaZNm2O093V19RC021Vn+SPTs5xPpQ55Dy/zT/9ORGRq06dPx88//4zBgwebOxSSGNWRyroaonkcHeWismfPcm/eVB+kqE6nXBiGnH5Y38azJTDG+TFGw191FFZRGOLzoo4lxWjqJZ4L8lAKEM/wcODALmRlZSm3z5xRHc1f9BkhzOHp0wTBtr7fL9XExCdPcjtxVBv+gLgTrjDyPyQsCkN0whpSiRIlMGjQCEFZcnKSQb+rmjx58h/Onz8lKNM0jX/r1sKHrufOnRQ93CeigtN2LVQ3E6PqbDiaqF6jnzzJXW7MGHW0Jd1bmBqvoYYjhRiNoUSJgi3x3KJFe8F2WNhVxMa+7sC/evWSYHaEpk1b611vmJKudoDqTF8ymUyv45YvL2z/5V8G0xjt8+howy1hos+SOKYUEBCIxo1bCMquXLlopmg069t3kKgsLOyKGSIhKh5MXT9nZWUhMjJc8DvWz5oVl+unFPq3pRCjsRSk/7RaNTfRLOt//31C+XNKyjOEhLxeilwmc0DDhsKlti2Fqdvm1vpsorAcHeXo31/43PfChdNGfc9q1YR/A9XkVDI9yc04xcQpIiKSopIlhR3W+mbUp6WlisrKlCkHIHfEeH45OUVfzlY1TpnMAV99tajAx7GxsYG//xtFjsdUjHF+0tJeCMoNsdywurhmzPgG9vb6dVTk5+lpnBGyUojRUgQEBMLV1UPZ6ExIiMf166GoX78JsrOzRdMct23byRxhFpmdnZ1o+nF9qHYalCuX990Sf++ys7NF32NdVDssZDIHQZz9+w9Gw4bNVF+mkzGnMy8sddNKx8c/1mtJ0qJQ/Qy7unrAx8dPbZuuUSNxx9bp00fQq9cAo8VHZO3U1ZsvX77U6wGIamJj2bLGq6Ot+d6C11DDkUKMlsDBwQE9e/bH3r07lGXHj+/HkCGjAACnTwsT+zt27G7S+AylZElblW39vgOqbTy5/PWSRsZon6s+WGzQoCnefntIgY9TurSd2uXozM3bu7pgdg19ls80NVtbW/j5+QsSL/I/8CciwzJ0/ZyZmSnatzD9c6qzQhX3+lkTqVw/pdC/LYUYLUWXLr1w+XKIcvvgwd3KwaWqiS2dOvU0yezqhmactrl1PpsoCg8PH8F2enoanj9PMdqqFlWrChOnYmNj8OxZstrB+mQakkmcMvWMAURERIakmkGft1yGLomJTwTbcrmTskFdrZq7YOT048fidasLSt3DddVRHcWRMc6P6o2vuhH+BaVuKbiqVV0tavk2KcRoKWxsbNC9ex+sXv29suzw4b2oX78JIiJuCBq+DRs2k+yDOjc3T8G/RXX2DE3i4x8Ltl1ccpcSUjeld1JSYoFHaaom7/j61kBY2FXldtWq1YpN/aeuA+PJk8dq9jQchUKBPXu2CcpiY2PQtWsTvY9x+PBfTJwiMqLKlcUjk5OSEiGTaV+6LT09XZTMk3ffY4w62prvLXgNNRwpxGgpOnfuKUic2rv3D7z33odQKBQ4cmSvYN8mTVqZOjyDUF2iMm9WNl1Ul7HJXz8Zo33u6Sl8eFO2bLli9blVnUXPUkfZlyvnKNj+77+in1siUs/Q9bO9vT3kcifB/dR//8WhVq2CJZqoJvMU9/pZE6lcP6XQvy2FGC1Fs2ZtBIMgbty4hgcP7sHd3Uu0TF+7dupnObd0xmibW+uziaJQN8NzQkK80RKn1LXPd+/egvffDzbK+5FuXKqPiIjIBFRvgpKTk6BQKHS+TjWBJ38mvmpj1RBrILu5CRtt6elpSEzU7wGNlBnj/OQ9oMoTFxer1zG1sbOzEy0PYorltgpCCjHq8urVK5O9V/v2XQXbx48fwPPnKcVmND+Q+9A3P9UOM3WysrLUTNee+52qXLmqaH9DjPr29a0p2H7woOgdCpZC9QE6ADg46LfcU2GFhl4o8lJ7kZHhiI6+Y6CIiEiVnZ2dKGFGn8Sc//4T17l5dbMx6ujicG9RWLyGGo4UYtTGlPenNWsGCJbySE5OwrVr/+Dy5QuC/bp16y2pWTLyUx04o+5eSR3VxB5X1/wPfg3fPld9MH/37u0iH9OSWGqilKqoqOL1dyeyZMaon1VnNdF3sKQ2xb1+1kQq108p9G9LIUZdFArxjG7GYG9vj27degvKjh8/gKdPExEa+vr+1MXFFbVr1zVJTIZmjLa5tT6bKAp1s5+qS6YylBo1akMmcxCUbdq0Fs+eJWt4BRmbZBKniIgswc6dO7Fq1SqcPm3ctW2p+FE3ivvixbM6X3fgwC7Bdv7RKKoZ/pcvhxR5ffSKFZ1FN2uHD+8p0jGlwBjnR9063cePHyhEdEJ+fv6C7f37/7S4xHIpxKhNcvJTk71XxYrOaNWqg6Ds1KnDos9Ks2ZtTBaToal2gp06dUTna/7557yaEVO5CY6lSpUSfb8OHtxdxCjFHZ+HD/+FlJRnGvaWloiIG6Ky6tVrqtnTcFTrx8IyRL1JRJqp1n1//31C52uOHt0n2HZxcVUuV2KsOlrq9xaFxWuo4UghRm30nW3MUN58s79g+8iRfTh9+pigTHUAgJSojsC/du0fnQ8rk5KeigY35H8gZYz2ef4ENiD3wVT+mdOkTKFQ4ObN64IyNzcPDXubT3z8Y9FggLw6lYgMzxj1s+rMPgcP7la7hF9BFOf6WRupXD+l0L8thRh1KepguYLo1KmnYHv//j/x99/HRftIefUqQ7fNrfnZRGHduhUm2JbJHNQOPjIUmUyGYcM+FpXv2LFB72NkZ2cjIyPDkGFZNckkTnHGKSKyBDt37sTq1auZOEUFZmtri8aNWwjKdu3aqoXzZFoAACAASURBVPU1//57BZGR4YKywMCGyp/VTYG6fv2qIkSZSzXOX39dIZmRoIVljPNToYIz5HInwe/Xrl1W5BvZN96oL9i+fDnE4hILpBBjfnlrv+cx9QwEnTu/KdhetmyhoPOhU6eecHAoY9KYDCkwsJFgOzr6Dv7994rW1/zxxybBtqurBypUcFZu+/sLp9U/cmQvoqIiixSn6lT96elpWLt2WZGOaQmSkp5i5crFonLVEWKGFB//GOfPnxKUDRv2MVas2Kzzv65d3xK87vDhv4o8Io6INGvQQLh85s6dm5GWlqpx/9TUF9i+XdiJ17Bhc8G2Mepoqd1bGAqvoYYjhRjzUx3ZfO/eHZP2ibZtK1zm5MSJgzhx4qByWy53Qp069UwWj6F5e/uJHlYeOqQ9ifDAgT9FZfk/V8Zon1er5i5qUy5ZMsekM5AZy9atv4pmKGjbtpOZolEvOzsb3303V1TeokU7M0RDZB2MUT+rDhqKi4vFwYNFG+hTnOtnbaRy/QSk0b8thRjzK19eLtg2xNJv+vLx8RMk7CQnJ+HHHxcJ9mnXrovJ4jEGQ7fNrfnZRGFcuxaKffv+EJTVrdtQw96G07Vrb9F52rZtPX75ZTmys7M1vCpXauoLzJ49BVOnfsy+UwNh4hQRUQFIOWOdzG/48NGC7WvX/sHOnZvV7vvwYQwWLJguKPPz8xfMTOPh4Y2gIOHyXadPH8XPPy/VeAMcGRkuGoGuauTIcaKyuXOn4t69uxpfExMTjZkzJyEkRPcsTZbK0OenRIkSomMmJydh9uzJGqeyTkl5hsjIW1rj7Nq1t2hkx7JlC3HhwhmNr0lJeYYVKxZjw4aftR7bUKQQY36qow/37fvDpFPiNmzYTNRAyq99e2k3/P3964hm1frhh/lqvwc5OTlYv34lrl37R1D+0UfjUaLE66bLwIEfiF47e/Zk3LhxTW0MCoVC54NmHx8/9Os3SFB28OBubNv2m8bGp0KhwO7dW/HVVxORlZWl9fimlpOTg4sX/8aXX44TjQLs1q03SpYsabT3PnJkr6ise/e+8PHx0/mf6ijC5OQkXLly0WixElm7nj3fFl2Dvv/+a7X3kmlpaZg//wtRuWqdbIw6Wmr3FobCa6jhSCHG/FSXaYyLi8XlyyEme39HRznatOmo8ffdu/cx6r2EsTk4OOCDD4RttW3b1ou+P3kuXDiD335bKSjr338wqlRxUW4bo31eqlQpjB8vrHdjY2OwePEsre2Vixf/xsSJI/Ra3tPUEhMT8NtvK9Q+FG/ZsoOaV5hHVFQk5s//QvS9c3aujJo1A8wUFVHxZ4z6uUOHbqKZ5n/8cREOHtyt8Xnjv/9e1hpncayf9SGV6ycgjf5tKcSYn2qS219/bdeZ2GFIqgPt8vP3ryNYAlKKDN02t+ZnEwWRkZGBfft2YsaMiaLftWtn/KR+e3t7vP9+sKh8y5ZfMX/+F0hLU1/XxcY+wPjxH+D8+VMIDw/D5s1rjB2qVbA1dwD6yuvkMWUlTESkikmcVBS+vjUQFNQdx47tV5atWvUdoqIiERTUDZ6evnj+/Blu3ryOVau+EzUAR44cJ3joAQBDhwYLjgfkjjI/d+4kevd+F+7uXqhcuSoePXqIixf/xt69O3TGWblyVYwf/wWWLp2nLIuOvoNRo95F//6D8cYbDeDq6o6MjAw8fHgfYWFXlce9d+8O6tVrDDs7uwL/fczNGOenY8ce+OOPTYiJiVaWhYZewJAhb2LIkI/g4+MHFxc3pKa+wNWrl7Bjx0adDX9bW1t89tkMBAe/pyxLT0/DjBkT0apVB7RuHQQPD2+ULFkSjx49QFRUJLZv36A8btu2nURTihuaFGLMT92SZePGDcOoURPg5uaJuLhYhIVdQUrKM1HHmCHY2tqiS5de2Lr1N9Hv5HIn0WwTUjRs2Mc4e/b1FNoxMdEYO/Z9fPjhWNSoURtyeQVERd3GkSP7RKOU6tZtiGbNWgvKPDy80avXAOzZs01ZFhcXi4kTR6Bbtz6oW7cB3Nw8YGNTArduXcf+/X8iOvqOzjjffz8Y586dRFxcrLJs7dofcfz4QfTp8x48PLxRrpwj4uPj8ODBPezevU05Uv7Ikb1aO3GMJSoqEqtXf4/y5R1RsqQtkpOf4smT/xAZGS4axQ8A3t7VERz8mdHiUSgUgvMCAE2btoajo1zDK4T8/etALncSJHsdO3ZANBKTiAzD3t4eH3wwBkuWzFGWnTx5GI8fP8I77wyFj08NlChRArdv38TWrb/h9u2bgtcPGfIRKlasJCgzRh0ttXsLQ+I11HCkEGMeFxc3yGQOgrbB55+PxdixUxEQUA+pqS9w48ZV3LhxHZMnz0S5cuUNHkOnTj1FS+vkUZ2RSoq6du2NrVt/Uz68Tk9Pw5QpH2P48E9Qr15jVKvmjkePHuCff86LHvLIZA54551homMao33evHlbdOjQTfD9PnnyMEJCzmLw4JGoXr0mKlWqiqSkRDx8eB/nzp1UPkxdt245pkyZVeC/jSHs3r0NYWFX4eBQBhkZ6UhMTEB8fBwuXTqndv9RoyaIlic1hbVrl8HJqQLs7OyRmvoc8fH/4dGjBxqTSadPXyBq9xORYRm6frazs8OoURMwb97/BOXffTcXp04dQZs2HeHm5glHRzkiI2/h1KmjCAnRnACQR6r1c1FJ5fophf5tKcSYn59fLZw8eVi5fePGNXz11QQMGDAUcrkT7t69jbCwq/D0zG1vGFqbNp2wbNlCtb/r3Lmn2nIpMUbb3FqfTagTEnIWCoUC5cqVR1ZWFp4+TUR8/GNcuXJR7b+5R49+6NChm0li69z5TezatUVwnoDcJNLTp48iICAQAQGBkMsrIDr6Dm7evC7q8920aS0aNmyOgIBAk8RcXEkmcSpvFJOljeQmIuvCxCkqqqFDgxEael7wQPjIkb1qZ+fIr0uXXmqTJ6pUccHw4Z/gl19+EpTHxcVixQrx0kz66tr1LZw/f0o0emXHjo3YsWOjxtfFxcVi794dotHcUmHo82Nra4sxY6ZgyhTxWtVFGWHh7V0dI0aMxZo1wuVFzp49Lniwps6aNcswe/aSQr+3vqQQY56aNQPQpk1HwYOhuLhYzJw5SbTvmDFTlWvFG1KHDt3UJk516tTTKO9nau7uXhg8eCQ2blytLEtOTsLixbO1vk4mc0BwsHjEDwAMHPghTp8+IppN6cCBP9VOBa8Pe3t7TJo0E599NlJQHh19R9Bxoc7KlUvQrl0X2NvbF+q9Cys9PU1rvZyfTOaAGTO+NWqMoaEXROekILOm2draok2bToIH+idOHMTo0ZON8lCYiPD/ieMHBCPFw8PDMGvWZK2v8/DwRt++6u/5jFFHS+newpB4DTUcKcSYp3Tp0hgxYqzo4ZC6h0UPH94XLUVoCA0aNBUlMwO5M+16efka/P1MrXTp0hg37nN8+eV4Qblq21qdTz6ZhPLlHUXlxmqfBwdPxOXLwnus9PQ0rF79vdbXHTu2H717v4MaNWoX+r0L6/z5U6KlmzXp0+c99O070MgRqaea8K/NF1/MN8p3jYiEjFE/t24dhIYNmyE09IKg/PLlkCLN6CjF+rmopHT9lEL/thRizNOjRz/8+efvghnTLl06J0qKbtiwmVESp8qXdxT13+Zp1SrI4O9nDoZum1vzswlVkZHhiIwM12vfgIBAjW1pYyhVqhQWLPgJkyePUjsI9saNaxqT+vPI5U6i5d6p4CQzPCIvcYprNBKROfXp0wcjR45E27ZtzR0KSVSVKi5YvXo7mjfX/zP06afTMGHCdI2/f/fd4Zg2ba4hwlOysbHBV199gw8/HFOg10l92npjnJ/AwEb48ccNcHFxNUSISm+//T5mzVqsdYk3dZo3b2PQOLSRQox5Ro2aoFecjx8/Msr7e3n5QiZzEJUXh9H8eYYM+QhffrlQ7b9TnTp16uHnn7fC17eG2t87OVXAqlVbDT4TUZ069bBq1ZYCd2AGBXW36CS33Ifuew1eF6nat2+nqKxp09Zq9tSsVav2ojJdHS9EVHi2trb4+utlGDx4hN6v6dmzP5YtWw8HB/V1urHqaCndWxgSr6GGI4UY83Tt2hsNGjTVuZ/qyGRDsbW1Rd26DUXlqsvqSlmTJi2xcuXvcHX10Gt/udwJixevRufOb2rcxxjtc0dHOVav3l7gv32dOvVEMw9YEn//Oli0aKVJH0wVRlBQd6xbt1Pr8pVEZFiGrp9tbGwwe/Z3GDDgfUOGWWzrZ12kcv2UQv+2FGLMI5PJMHHilzr3u3s3wmgx1KsnHrjcokU7vWc5t3TGaJtb87OJgnJ2rozPPvsKixatROnSpU363hUrOuPbb39Gq1YFX7q6ceMWWLHi92IxuMXcLLdnX0Ve5wQTp4jInHr37m3uEMhEbG1LCbZLltR9ySxdWjg1ruox8pQv74gZM77B3r07cPTofoSHh4n2kcudUKtWXQwdGgxv7+o637t9+y6oXr0m1q79EVevXlI7vWiLFu0watQEjBs3TDASqkSJkmqPaWtriwEDhqJ587Zaj+vh4Q0fHz80adISbdt2NskDBamdHz8/fyxfvhHr1i1HaOh5wfIg+fcJDv4MBw/uFsxwpe0mvVmzNlizZgfWr1+Fc+dOCkb85HF2rgxf35oICKiLzp17wcmpgs54DcmQMdrZ2Qk+g7qWSChVSniONZ3zvBjWrNmBH36Yr3FJErncCc+fP9N4vKJ+9mvVekMw0tHDw1u0ZrwplCpVWmVb899N3e9VX59fq1Yd4OtbE+vW/YibN6+r/Tz4+fmjVasO6N9/iM6/qVzuhNmzv8POnZtx9Og+tUsJyeVO+OCDMcjOzhZMf25np3nGCC8vX3z33Vrs2rUFhw7tUftAUiZzQI0ateHn549OnXqarHGq7XOcRy53goeHD1xdPeDm5oEOHbqhQoWKRo8tIyNDtKRB+/ZdNXbeaBIQUE+0PNHFi3+jWzfehxEZ61poa2uLIUNGoW7dhtiy5VfcuvWv2vu+OnXqoW/fgWjZUpzgqMpYdbQl3//wGmrZ11BjxGjMc25ra4s5c5Zi69ZfsX79KrX7yGQOyMhI13j8onb4+/rWEN0bm2NEv2rdpevvrNrG1baMjbd3dSxfvhEbNqzCpUvn1H4eXFxc0aBBMwwb9rHamTJUGaN9Xr68IyZNmoHWrYOwefNate1UAKhRozZ8fPwQFNQddes20Bmroei6R5XJHFCpUhV4eHjD1dUdderUR+PGLZQzu5uCrs8NkBunu7sX3N29UK2aG1q0aAcfHz8TREckTVKqn21tbfHhh2NRp059bNv2G8LCrqrdb8CA99G6dUeMHfs6yUomK6PxuJZcP0vp/ADW179tjBiN2WcO5M4mtWrVFixYMF3jct6596cZyplaxf2nuq/Hmnh6iu/Jg4JMs5yaKim1za3x2YQ+nzMXF1e4uXnCzc0T3t7V0a5dF5Muf6mqQoWK+PLLhbh06Rz++muHzmVjW7Roh379BqFOnXomirD4s8mRyHpTvXv3xsOHDzFkyBCMGzfO3OEQEZEBbP/pHh7eTYNXrXJo08fN3OGYjUKhQFzcQzx4cA8ymQM8PX2L/IA7Pv4x7t27C1tbW7i4uKFSpSoGafAlJMTj/v0ovHr1Eq6uHnBxcdOr81HKjHF+nj9PQVRUJDIy0lG1ajVUqVLNIMt+PH+egvv3o5CUlIgqVarBzc0DDg6aO3fMQQoxvnjxHHfv3kZKSjIqVHCGs3NlVKjgbPTP+qpVuQ8v84wc+Sn69x9i1Pc0t7zPQ3Ly0/9P8vEs0t85IyMDMTFRSEiIR6VKVeHi4oqyZcsVOc6MjAw8eHAPjx/HwsmpIlxdPUyehEiW4+qZJ7h+JgEOZUti1Kya5g6HDOza309xfOdjwAZ4/3+1zB2OWT158h9iYqKRmZkJDw9vVK1aTWdnsDbGqqOlcG9hDLyGGo4UYnz58iXu34/C48excHSUo2LFyqhYsRJkMplR3/fcuZOCpUEaN26BuXO1Lz8kdXmfh7i4h6hUqQo8PX2KXKcYo32uUCjw+PEjPHgQjdKl7eDm5olKlaoUqZ4macpIVWDb95EAgDeHuaP6G0Wvu8mC5ADfTboJAGjWrSpq1C/YzB7FiaHr57z+vocP76NcOUe4uLihQoWKRU7otNb6WSrXT0Aa/dtSiTEqKhJZWQrlvamTUwWjftafPUvGgAGdlNsymQO2bDlksuW0zcXQbXNrfjYhJampLxAVFYmkpEQ8e5aEkiVt4egoR4UKzvD1rWnyWbEK6ubFRPxzNB4lbW3w6UJp9K9JJnGqX79+uH//PgYOHIiJEy17+l4iItIPE6eKvxcvniMzM9Ngx7O1tUW5cuUNdjxrx/NjWWbNmoxz504qtzds+AuVK1dVu29GRoba0UZFYWkPCKVMoVDg+fMUgx6zXLnyBh/xyM9R4TBxqnhj4lTxx7rPsknlGmotdu/eip9++la5PW3aXLRv30Xj/snJSTBkV7O9vczoyWHWRCrnRypxWgomThVzTJyyCqz3LBvPj+WIjAzHmDGvB5n26NEPn346TeP+7Pu2bFJpm/NzVDhSTJySTK9ByZK50yxmZWWZORIiIiLS16efDkNsbIzBjieTOWDXrlMGO5614/mxHGfPHhckTQUGNtKYNAUAa9cuw5492wwaw5o12+Hu7mXQY1qrc+dOYt68/xn0mOPHf2Hwper4OSIia8S6z7JJ5RpqDR48uIfNm9cKypo1a6Nx/8TEJxg4sLtBY2jfviumTZtj0GNaK6mcH6nESURkKKz3LBvPj+VIS0vFypWLBWUdOnTV+hr2fVs2qbTN+TmyHpJLnFIoFGaOhIis2ZIlSxAeHo4mTZpgxIgR5g6HyOJlZzPh2ZLx/JhfbOwD7NmzDbt2bRGU9+zZT+vrsrOzDR6LMY5praRyfqRyTCIiQ2LdZ9l4fswvJeUZDh/eg40b1whGgHfr1lvr7AjGWNQgJ4fnzlCkcn6kEicRkaGw3rNsPD/ml5mZibNnj2Pz5rWIiYlWlru4uKJ27bpaX8u+b8smlbYfP0fWQzKJU3nrNBpyKjQiooK6c+cOLl++DCcnTotMpI/cWXNcDHY8R0e5wY5FPD/m9NVXE3H9eqja6YgDAxuhdesgra/39PRGYGAjg8ZUtiyXdDAUZ+fKBj8/2mYgKyx+jojIGrHus2xSuYYWR7//vg579/6BhIR40e9kMgcMGqR98JidnT0aNGhq0NUCfHz8DHYsayeV8yOVOImIDIX1nmXj+TGfS5fOYcWKxRpn+hk9egpKlCih9Rjs+7ZsUmmb83NkPSSXOPXq1SszR0JE1izvRozLhhLpZ8KE6eYOgbTg+TGfu3cj1CZN+fvXwdSps2FjY6P19b16DUCvXgOMFR4VUZ069bBo0Qpzh6ETP0dEZI1Y91k2qVxDi6PHjx9pTJqaM2cpKlWqovX15cqVx/z5PxorPCoiqZwfqcRJRGQorPcsG8+P+aSkJGtMmvrkk0lo3LiFzmOw79uySaVtzs+R9ZBc4tTLly/NHAkRWbO8ZUM51T8RERnagAHvY8iQUcr7XiIiIiIic2rVqgOCgyfqTJoiIiIiIjK2GjVqIzh4IgICAs0dChEVQ5JLnOKMU0RkTnmJU5xxioiIisLXtyZcXT3g4uIKf/86aNu2Exwcypg7LCIiIiKyUlWquMDfvw6qVXOHl5cPOnToxoQpIiIiIjILJ6eK8PPzR5Uq1VCtmhvatOkEPz9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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import nest_asyncio\n", - "\n", - "nest_asyncio.apply() # Required for Jupyter Notebook to run async functions\n", - "\n", - "display(\n", - " Image(\n", - " app.get_graph().draw_mermaid_png(\n", - " curve_style=CurveStyle.LINEAR,\n", - " node_colors=NodeStyles(first=\"#ffdfba\", last=\"#baffc9\", default=\"#fad7de\"),\n", - " wrap_label_n_words=9,\n", - " output_file_path=None,\n", - " draw_method=MermaidDrawMethod.PYPPETEER,\n", - " background_color=\"white\",\n", - " padding=10,\n", - " )\n", - " )\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "d821b2f6", - "metadata": { - "ExecuteTime": { - "end_time": "2024-04-18T12:18:30.629629Z", - "start_time": "2024-04-18T12:18:30.620092Z" - } - }, - "source": [ - "**Using Graphviz**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d4234400-75cd-4b13-aeff-828f7fb68ab1", - "metadata": { - "ExecuteTime": { - "end_time": "2024-04-19T11:25:42.057704Z", - "start_time": "2024-04-19T11:25:42.019017Z" - } - }, - "outputs": [], - "source": [ - "%%capture --no-stderr\n", - "%pip install pygraphviz" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "ee026342-f560-4ce0-ab43-1718bd19a366", - "metadata": { - "ExecuteTime": { - "end_time": "2024-04-19T11:25:42.631675Z", - "start_time": "2024-04-19T11:25:42.452377Z" - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "try:\n", - " display(Image(app.get_graph().draw_png()))\n", - "except ImportError:\n", - " print(\n", - " \"You likely need to install dependencies for pygraphviz, see more here https://github.com/pygraphviz/pygraphviz/blob/main/INSTALL.txt\"\n", - " )" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.6" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/docs/docs/how-tos/graph-api.md b/docs/docs/how-tos/graph-api.md new file mode 100644 index 000000000..2e15cacb1 --- /dev/null +++ b/docs/docs/how-tos/graph-api.md @@ -0,0 +1,1877 @@ +# How to use the graph API + +This guide demonstrates the basics of LangGraph's Graph API. It walks through [state](#define-and-update-state), as well as composing common graph structures such as [sequences](#create-a-sequence-of-steps), [branches](#create-branches), and [loops](#create-and-control-loops). It also covers LangGraph's control features, including the [Send API](#map-reduce-and-the-send-api) for map-reduce workflows and the [Command API](#combine-control-flow-and-state-updates-with-command) for combining state updates with "hops" across nodes. + +## Setup + +Install `langgraph`: + +```bash +pip install -U langgraph +``` + +!!! tip "Set up LangSmith for better debugging" + Sign up for [LangSmith](https://smith.langchain.com) to quickly spot issues and improve the performance of your LangGraph projects. LangSmith lets you use trace data to debug, test, and monitor your LLM apps built with LangGraph — read more about how to get started in the [docs](https://docs.smith.langchain.com). + +## Define and update state + +Here we show how to define and update [state](../concepts/low_level.md#state) in LangGraph. We will demonstrate: + +1. How to use state to define a graph's [schema](../concepts/low_level.md#schema) +2. How to use [reducers](../concepts/low_level.md#reducers) to control how state updates are processed. + +### Define state + +[State](../concepts/low_level.md#state) in LangGraph can be a `TypedDict`, `Pydantic` model, or dataclass. Below we will use `TypedDict`. See [this section](#use-pydantic-models-for-graph-state) for detail on using Pydantic. + +By default, graphs will have the same input and output schema, and the state determines that schema. See [this section](#define-input-and-output-schemas) for how to define distinct input and output schemas. + +Let's consider a simple example using [messages](../concepts/low_level.md#messagesstate). This represents a versatile formulation of state for many LLM applications. See our [concepts page](../concepts/low_level.md#working-with-messages-in-graph-state) for more detail. + +```python +from langchain_core.messages import AnyMessage +from typing_extensions import TypedDict + +class State(TypedDict): + messages: list[AnyMessage] + extra_field: int +``` + +This state tracks a list of [message](https://python.langchain.com/docs/concepts/messages/) objects, as well as an extra integer field. + +### Update state + +Let's build an example graph with a single node. Our [node](../concepts/low_level.md#nodes) is just a Python function that reads our graph's state and makes updates to it. The first argument to this function will always be the state: + +```python +from langchain_core.messages import AIMessage + +def node(state: State): + messages = state["messages"] + new_message = AIMessage("Hello!") + return {"messages": messages + [new_message], "extra_field": 10} +``` + +This node simply appends a message to our message list, and populates an extra field. + +!!! important + Nodes should return updates to the state directly, instead of mutating the state. + +Let's next define a simple graph containing this node. We use [StateGraph](../concepts/low_level.md#stategraph) to define a graph that operates on this state. We then use [add_node](../concepts/low_level.md#nodes) populate our graph. + +```python +from langgraph.graph import StateGraph + +builder = StateGraph(State) +builder.add_node(node) +builder.set_entry_point("node") +graph = builder.compile() +``` + +LangGraph provides built-in utilities for visualizing your graph. Let's inspect our graph. See [this section](#visualize-your-graph) for detail on visualization. + +```python +from IPython.display import Image, display + +display(Image(graph.get_graph().draw_mermaid_png())) +``` + +![Simple graph with single node](assets/graph_api_image_1.png) + +In this case, our graph just executes a single node. Let's proceed with a simple invocation: + +```python +from langchain_core.messages import HumanMessage + +result = graph.invoke({"messages": [HumanMessage("Hi")]}) +result +``` +``` +{'messages': [HumanMessage(content='Hi'), AIMessage(content='Hello!')], 'extra_field': 10} +``` + +Note that: + +- We kicked off invocation by updating a single key of the state. +- We receive the entire state in the invocation result. + +For convenience, we frequently inspect the content of [message objects](https://python.langchain.com/docs/concepts/messages/) via pretty-print: + +```python +for message in result["messages"]: + message.pretty_print() +``` +``` +================================ Human Message ================================ + +Hi +================================== Ai Message ================================== + +Hello! +``` + +### Process state updates with reducers + +Each key in the state can have its own independent [reducer](../concepts/low_level.md#reducers) function, which controls how updates from nodes are applied. If no reducer function is explicitly specified then it is assumed that all updates to the key should override it. + +For `TypedDict` state schemas, we can define reducers by annotating the corresponding field of the state with a reducer function. + +In the earlier example, our node updated the `"messages"` key in the state by appending a message to it. Below, we add a reducer to this key, such that updates are automatically appended: + +```python +from typing_extensions import Annotated + +def add(left, right): + """Can also import `add` from the `operator` built-in.""" + return left + right + +class State(TypedDict): + # highlight-next-line + messages: Annotated[list[AnyMessage], add] + extra_field: int +``` + +Now our node can be simplified: + +```python +def node(state: State): + new_message = AIMessage("Hello!") + # highlight-next-line + return {"messages": [new_message], "extra_field": 10} +``` +```python +from langgraph.graph import START + +graph = StateGraph(State).add_node(node).add_edge(START, "node").compile() + +result = graph.invoke({"messages": [HumanMessage("Hi")]}) + +for message in result["messages"]: + message.pretty_print() +``` +``` +================================ Human Message ================================ + +Hi +================================== Ai Message ================================== + +Hello! +``` + +#### MessagesState + +In practice, there are additional considerations for updating lists of messages: + +- We may wish to update an existing message in the state. +- We may want to accept short-hands for [message formats](../concepts/low_level.md#using-messages-in-your-graph), such as [OpenAI format](https://python.langchain.com/docs/concepts/messages.md#openai-format). + +LangGraph includes a built-in reducer `add_messages` that handles these considerations: + +```python +from langgraph.graph.message import add_messages + +class State(TypedDict): + # highlight-next-line + messages: Annotated[list[AnyMessage], add_messages] + extra_field: int + +def node(state: State): + new_message = AIMessage("Hello!") + return {"messages": [new_message], "extra_field": 10} + +graph = StateGraph(State).add_node(node).set_entry_point("node").compile() +``` + +```python +# highlight-next-line +input_message = {"role": "user", "content": "Hi"} + +result = graph.invoke({"messages": [input_message]}) + +for message in result["messages"]: + message.pretty_print() +``` +``` +================================ Human Message ================================ + +Hi +================================== Ai Message ================================== + +Hello! +``` + +This is a versatile representation of state for applications involving [chat models](https://python.langchain.com/docs/concepts/chat_models/). LangGraph includes a pre-built `MessagesState` for convenience, so that we can have: + +```python +from langgraph.graph import MessagesState + +class State(MessagesState): + extra_field: int +``` + +### Define input and output schemas + +By default, `StateGraph` operates with a single schema, and all nodes are expected to communicate using that schema. However, it's also possible to define distinct input and output schemas for a graph. + +When distinct schemas are specified, an internal schema will still be used for communication between nodes. The input schema ensures that the provided input matches the expected structure, while the output schema filters the internal data to return only the relevant information according to the defined output schema. + +Below, we'll see how to define distinct input and output schema. + +```python +from langgraph.graph import StateGraph, START, END +from typing_extensions import TypedDict + +# Define the schema for the input +class InputState(TypedDict): + question: str + +# Define the schema for the output +class OutputState(TypedDict): + answer: str + +# Define the overall schema, combining both input and output +class OverallState(InputState, OutputState): + pass + +# Define the node that processes the input and generates an answer +def answer_node(state: InputState): + # Example answer and an extra key + return {"answer": "bye", "question": state["question"]} + +# Build the graph with input and output schemas specified +builder = StateGraph(OverallState, input_schema=InputState, output_schema=OutputState) +builder.add_node(answer_node) # Add the answer node +builder.add_edge(START, "answer_node") # Define the starting edge +builder.add_edge("answer_node", END) # Define the ending edge +graph = builder.compile() # Compile the graph + +# Invoke the graph with an input and print the result +print(graph.invoke({"question": "hi"})) +``` +``` +{'answer': 'bye'} +``` + +Notice that the output of invoke only includes the output schema. + +### Pass private state between nodes + +In some cases, you may want nodes to exchange information that is crucial for intermediate logic but doesn't need to be part of the main schema of the graph. This private data is not relevant to the overall input/output of the graph and should only be shared between certain nodes. + +Below, we'll create an example sequential graph consisting of three nodes (node_1, node_2 and node_3), where private data is passed between the first two steps (node_1 and node_2), while the third step (node_3) only has access to the public overall state. + +```python +from langgraph.graph import StateGraph, START, END +from typing_extensions import TypedDict + +# The overall state of the graph (this is the public state shared across nodes) +class OverallState(TypedDict): + a: str + +# Output from node_1 contains private data that is not part of the overall state +class Node1Output(TypedDict): + private_data: str + +# The private data is only shared between node_1 and node_2 +def node_1(state: OverallState) -> Node1Output: + output = {"private_data": "set by node_1"} + print(f"Entered node `node_1`:\n\tInput: {state}.\n\tReturned: {output}") + return output + +# Node 2 input only requests the private data available after node_1 +class Node2Input(TypedDict): + private_data: str + +def node_2(state: Node2Input) -> OverallState: + output = {"a": "set by node_2"} + print(f"Entered node `node_2`:\n\tInput: {state}.\n\tReturned: {output}") + return output + +# Node 3 only has access to the overall state (no access to private data from node_1) +def node_3(state: OverallState) -> OverallState: + output = {"a": "set by node_3"} + print(f"Entered node `node_3`:\n\tInput: {state}.\n\tReturned: {output}") + return output + +# Connect nodes in a sequence +# node_2 accepts private data from node_1, whereas +# node_3 does not see the private data. +builder = StateGraph(OverallState).add_sequence([node_1, node_2, node_3]) +builder.add_edge(START, "node_1") +graph = builder.compile() + +# Invoke the graph with the initial state +response = graph.invoke( + { + "a": "set at start", + } +) + +print() +print(f"Output of graph invocation: {response}") +``` +``` +Entered node `node_1`: + Input: {'a': 'set at start'}. + Returned: {'private_data': 'set by node_1'} +Entered node `node_2`: + Input: {'private_data': 'set by node_1'}. + Returned: {'a': 'set by node_2'} +Entered node `node_3`: + Input: {'a': 'set by node_2'}. + Returned: {'a': 'set by node_3'} + +Output of graph invocation: {'a': 'set by node_3'} +``` + +### Use Pydantic models for graph state + +A [StateGraph](https://langchain-ai.github.io/langgraph/reference/graphs.md#langgraph.graph.StateGraph) accepts a `state_schema` argument on initialization that specifies the "shape" of the state that the nodes in the graph can access and update. + +In our examples, we typically use a python-native `TypedDict` for `state_schema`, but `state_schema` can be any [type](https://docs.python.org/3/library/stdtypes.html#type-objects). + +Here, we'll see how a [Pydantic BaseModel](https://docs.pydantic.dev/latest/api/base_model/). can be used for `state_schema` to add run time validation on **inputs**. + +!!! note "Known Limitations" + - Currently, the output of the graph will **NOT** be an instance of a pydantic model. + - Run-time validation only occurs on inputs into nodes, not on the outputs. + - The validation error trace from pydantic does not show which node the error arises in. + +```python +from langgraph.graph import StateGraph, START, END +from typing_extensions import TypedDict +from pydantic import BaseModel + +# The overall state of the graph (this is the public state shared across nodes) +class OverallState(BaseModel): + a: str + +def node(state: OverallState): + return {"a": "goodbye"} + +# Build the state graph +builder = StateGraph(OverallState) +builder.add_node(node) # node_1 is the first node +builder.add_edge(START, "node") # Start the graph with node_1 +builder.add_edge("node", END) # End the graph after node_1 +graph = builder.compile() + +# Test the graph with a valid input +graph.invoke({"a": "hello"}) +``` + +Invoke the graph with an **invalid** input + +```python +try: + graph.invoke({"a": 123}) # Should be a string +except Exception as e: + print("An exception was raised because `a` is an integer rather than a string.") + print(e) +``` +``` +An exception was raised because `a` is an integer rather than a string. +1 validation error for OverallState +a + Input should be a valid string [type=string_type, input_value=123, input_type=int] + For further information visit https://errors.pydantic.dev/2.9/v/string_type +``` + +See below for additional features of Pydantic model state: + +??? example "Serialization Behavior" + + When using Pydantic models as state schemas, it's important to understand how serialization works, especially when: + - Passing Pydantic objects as inputs + - Receiving outputs from the graph + - Working with nested Pydantic models + + Let's see these behaviors in action. + + ```python + from langgraph.graph import StateGraph, START, END + from pydantic import BaseModel + + class NestedModel(BaseModel): + value: str + + class ComplexState(BaseModel): + text: str + count: int + nested: NestedModel + + def process_node(state: ComplexState): + # Node receives a validated Pydantic object + print(f"Input state type: {type(state)}") + print(f"Nested type: {type(state.nested)}") + # Return a dictionary update + return {"text": state.text + " processed", "count": state.count + 1} + + # Build the graph + builder = StateGraph(ComplexState) + builder.add_node("process", process_node) + builder.add_edge(START, "process") + builder.add_edge("process", END) + graph = builder.compile() + + # Create a Pydantic instance for input + input_state = ComplexState(text="hello", count=0, nested=NestedModel(value="test")) + print(f"Input object type: {type(input_state)}") + + # Invoke graph with a Pydantic instance + result = graph.invoke(input_state) + print(f"Output type: {type(result)}") + print(f"Output content: {result}") + + # Convert back to Pydantic model if needed + output_model = ComplexState(**result) + print(f"Converted back to Pydantic: {type(output_model)}") + ``` + +??? example "Runtime Type Coercion" + + Pydantic performs runtime type coercion for certain data types. This can be helpful but also lead to unexpected behavior if you're not aware of it. + + ```python + from langgraph.graph import StateGraph, START, END + from pydantic import BaseModel + + class CoercionExample(BaseModel): + # Pydantic will coerce string numbers to integers + number: int + # Pydantic will parse string booleans to bool + flag: bool + + def inspect_node(state: CoercionExample): + print(f"number: {state.number} (type: {type(state.number)})") + print(f"flag: {state.flag} (type: {type(state.flag)})") + return {} + + builder = StateGraph(CoercionExample) + builder.add_node("inspect", inspect_node) + builder.add_edge(START, "inspect") + builder.add_edge("inspect", END) + graph = builder.compile() + + # Demonstrate coercion with string inputs that will be converted + result = graph.invoke({"number": "42", "flag": "true"}) + + # This would fail with a validation error + try: + graph.invoke({"number": "not-a-number", "flag": "true"}) + except Exception as e: + print(f"\nExpected validation error: {e}") + ``` + +??? example "Working with Message Models" + + When working with LangChain message types in your state schema, there are important considerations for serialization. You should use `AnyMessage` (rather than `BaseMessage`) for proper serialization/deserialization when using message objects over the wire. + + ```python + from langgraph.graph import StateGraph, START, END + from pydantic import BaseModel + from langchain_core.messages import HumanMessage, AIMessage, AnyMessage + from typing import List + + class ChatState(BaseModel): + messages: List[AnyMessage] + context: str + + def add_message(state: ChatState): + return {"messages": state.messages + [AIMessage(content="Hello there!")]} + + builder = StateGraph(ChatState) + builder.add_node("add_message", add_message) + builder.add_edge(START, "add_message") + builder.add_edge("add_message", END) + graph = builder.compile() + + # Create input with a message + initial_state = ChatState( + messages=[HumanMessage(content="Hi")], context="Customer support chat" + ) + + result = graph.invoke(initial_state) + print(f"Output: {result}") + + # Convert back to Pydantic model to see message types + output_model = ChatState(**result) + for i, msg in enumerate(output_model.messages): + print(f"Message {i}: {type(msg).__name__} - {msg.content}") + ``` + +## Add runtime configuration + +Sometimes you want to be able to configure your graph when calling it. For example, you might want to be able to specify what LLM or system prompt to use at runtime, *without polluting the graph state with these parameters*. + +To add runtime configuration: + +1. Specify a schema for your configuration +2. Add the configuration to the function signature for nodes or conditional edges +3. Pass the configuration into the graph. + +See below for a simple example: + +```python +from langchain_core.runnables import RunnableConfig +from langgraph.graph import END, StateGraph, START +from typing_extensions import TypedDict + +# 1. Specify config schema +class ConfigSchema(TypedDict): + my_runtime_value: str + +# 2. Define a graph that accesses the config in a node +class State(TypedDict): + my_state_value: str + +# highlight-next-line +def node(state: State, config: RunnableConfig): + # highlight-next-line + if config["configurable"]["my_runtime_value"] == "a": + return {"my_state_value": 1} + # highlight-next-line + elif config["configurable"]["my_runtime_value"] == "b": + return {"my_state_value": 2} + else: + raise ValueError("Unknown values.") + +# highlight-next-line +builder = StateGraph(State, config_schema=ConfigSchema) +builder.add_node(node) +builder.add_edge(START, "node") +builder.add_edge("node", END) + +graph = builder.compile() + +# 3. Pass in configuration at runtime: +# highlight-next-line +print(graph.invoke({}, {"configurable": {"my_runtime_value": "a"}})) +# highlight-next-line +print(graph.invoke({}, {"configurable": {"my_runtime_value": "b"}})) +``` +``` +{'my_state_value': 1} +{'my_state_value': 2} +``` + +??? example "Extended example: specifying LLM at runtime" + Below we demonstrate a practical example in which we configure what LLM to use at runtime. We will use both OpenAI and Anthropic models. + + ```python + from langchain.chat_models import init_chat_model + from langchain_core.runnables import RunnableConfig + from langgraph.graph import MessagesState + from langgraph.graph import END, StateGraph, START + from typing_extensions import TypedDict + + class ConfigSchema(TypedDict): + model: str + + MODELS = { + "anthropic": init_chat_model("anthropic:claude-3-5-haiku-latest"), + "openai": init_chat_model("openai:gpt-4.1-mini"), + } + + def call_model(state: MessagesState, config: RunnableConfig): + model = config["configurable"].get("model", "anthropic") + model = MODELS[model] + response = model.invoke(state["messages"]) + return {"messages": [response]} + + builder = StateGraph(MessagesState, config_schema=ConfigSchema) + builder.add_node("model", call_model) + builder.add_edge(START, "model") + builder.add_edge("model", END) + + graph = builder.compile() + + # Usage + input_message = {"role": "user", "content": "hi"} + # With no configuration, uses default (Anthropic) + response_1 = graph.invoke({"messages": [input_message]})["messages"][-1] + # Or, can set OpenAI + config = {"configurable": {"model": "openai"}} + response_2 = graph.invoke({"messages": [input_message]}, config=config)["messages"][-1] + + print(response_1.response_metadata["model_name"]) + print(response_2.response_metadata["model_name"]) + ``` + ``` + claude-3-5-haiku-20241022 + gpt-4.1-mini-2025-04-14 + ``` + +??? example "Extended example: specifying model and system message at runtime" + Below we demonstrate a practical example in which we configure two parameters: the LLM and system message to use at runtime. + + ```python + from typing import Optional + from langchain.chat_models import init_chat_model + from langchain_core.messages import SystemMessage + from langchain_core.runnables import RunnableConfig + from langgraph.graph import END, MessagesState, StateGraph, START + from typing_extensions import TypedDict + + class ConfigSchema(TypedDict): + model: Optional[str] + system_message: Optional[str] + + MODELS = { + "anthropic": init_chat_model("anthropic:claude-3-5-haiku-latest"), + "openai": init_chat_model("openai:gpt-4.1-mini"), + } + + def call_model(state: MessagesState, config: RunnableConfig): + model = config["configurable"].get("model", "anthropic") + model = MODELS[model] + messages = state["messages"] + if system_message := config["configurable"].get("system_message"): + messages = [SystemMessage(system_message)] + messages + response = model.invoke(messages) + return {"messages": [response]} + + builder = StateGraph(MessagesState, config_schema=ConfigSchema) + builder.add_node("model", call_model) + builder.add_edge(START, "model") + builder.add_edge("model", END) + + graph = builder.compile() + + # Usage + input_message = {"role": "user", "content": "hi"} + config = {"configurable": {"model": "openai", "system_message": "Respond in Italian."}} + response = graph.invoke({"messages": [input_message]}, config) + for message in response["messages"]: + message.pretty_print() + ``` + ``` + ================================ Human Message ================================ + + hi + ================================== Ai Message ================================== + + Ciao! Come posso aiutarti oggi? + ``` + +## Add retry policies + +There are many use cases where you may wish for your node to have a custom retry policy, for example if you are calling an API, querying a database, or calling an LLM, etc. LangGraph lets you add retry policies to nodes. + +To configure a retry policy, pass the `retry_policy` parameter to the [add_node](https://langchain-ai.github.io/langgraph/reference/graphs.md#langgraph.graph.state.StateGraph.add_node). The `retry_policy` parameter takes in a `RetryPolicy` named tuple object. Below we instantiate a `RetryPolicy` object with the default parameters and associate it with a node: + +```python +from langgraph.pregel import RetryPolicy + +builder.add_node( + "node_name", + node_function, + retry_policy=RetryPolicy(), +) +``` + +By default, the `retry_on` parameter uses the `default_retry_on` function, which retries on any exception except for the following: + +* `ValueError` +* `TypeError` +* `ArithmeticError` +* `ImportError` +* `LookupError` +* `NameError` +* `SyntaxError` +* `RuntimeError` +* `ReferenceError` +* `StopIteration` +* `StopAsyncIteration` +* `OSError` + +In addition, for exceptions from popular http request libraries such as `requests` and `httpx` it only retries on 5xx status codes. + +??? example "Extended example: customizing retry policies" + Consider an example in which we are reading from a SQL database. Below we pass two different retry policies to nodes: + + ```python + import sqlite3 + from typing_extensions import TypedDict + from langchain.chat_models import init_chat_model + from langgraph.graph import END, MessagesState, StateGraph, START + from langgraph.pregel import RetryPolicy + from langchain_community.utilities import SQLDatabase + from langchain_core.messages import AIMessage + + db = SQLDatabase.from_uri("sqlite:///:memory:") + model = init_chat_model("anthropic:claude-3-5-haiku-latest") + + def query_database(state: MessagesState): + query_result = db.run("SELECT * FROM Artist LIMIT 10;") + return {"messages": [AIMessage(content=query_result)]} + + def call_model(state: MessagesState): + response = model.invoke(state["messages"]) + return {"messages": [response]} + + # Define a new graph + builder = StateGraph(MessagesState) + builder.add_node( + "query_database", + query_database, + retry_policy=RetryPolicy(retry_on=sqlite3.OperationalError), + ) + builder.add_node("model", call_model, retry_policy=RetryPolicy(max_attempts=5)) + builder.add_edge(START, "model") + builder.add_edge("model", "query_database") + builder.add_edge("query_database", END) + graph = builder.compile() + ``` + +## Add node caching + +Node caching is useful in cases where you want to avoid repeating operations, like when doing something expensive (either in terms of time or cost). LangGraph lets you add individualized caching policies to nodes in a graph. + +To configure a cache policy, pass the `cache_policy` parameter to the [add_node](https://langchain-ai.github.io/langgraph/reference/graphs.md#langgraph.graph.state.StateGraph.add_node) function. In the following example, a [`CachePolicy`](https://langchain-ai.github.io/langgraph/reference/types/?h=cachepolicy#langgraph.types.CachePolicy) object is instantiated with a time to live of 120 seconds and the default `key_func` generator. Then it is associated with a node: + +```python +from langgraph.types import CachePolicy + +builder.add_node( + "node_name", + node_function, + cache_policy=CachePolicy(ttl=120), +) +``` + +Then, to enable node-level caching for a graph, set the `cache` argument when compiling the graph. The example below uses `InMemoryCache` to set up a graph with in-memory cache, but `SqliteCache` is also available. + +```python +from langgraph.cache.memory import InMemoryCache + +graph = builder.compile(cache=InMemoryCache()) +``` + +## Create a sequence of steps + +!!! info "Prerequisites" + This guide assumes familiarity with the above section on [state](#define-and-update-state). + +Here we demonstrate how to construct a simple sequence of steps. We will show: + +1. How to build a sequential graph +2. Built-in short-hand for constructing similar graphs. + +To add a sequence of nodes, we use the `.add_node` and `.add_edge` methods of our [graph](../concepts/low_level.md#stategraph): + +```python +from langgraph.graph import START, StateGraph + +builder = StateGraph(State) + +# Add nodes +builder.add_node(step_1) +builder.add_node(step_2) +builder.add_node(step_3) + +# Add edges +builder.add_edge(START, "step_1") +builder.add_edge("step_1", "step_2") +builder.add_edge("step_2", "step_3") +``` + +We can also use the built-in shorthand `.add_sequence`: + +```python +builder = StateGraph(State).add_sequence([step_1, step_2, step_3]) +builder.add_edge(START, "step_1") +``` + +??? info "Why split application steps into a sequence with LangGraph?" + LangGraph makes it easy to add an underlying persistence layer to your application. + This allows state to be checkpointed in between the execution of nodes, so your LangGraph nodes govern: + + - How state updates are [checkpointed](../concepts/persistence.md) + - How interruptions are resumed in [human-in-the-loop](../concepts/human_in_the_loop.md) workflows + - How we can "rewind" and branch-off executions using LangGraph's [time travel](../concepts/time-travel.md) features + + They also determine how execution steps are [streamed](../concepts/streaming.md), and how your application is visualized + and debugged using [LangGraph Studio](../concepts/langgraph_studio.md). + +Let's demonstrate an end-to-end example. We will create a sequence of three steps: + +1. Populate a value in a key of the state +2. Update the same value +3. Populate a different value + +Let's first define our [state](../concepts/low_level.md#state). This governs the [schema of the graph](../concepts/low_level.md#schema), and can also specify how to apply updates. See [this section](#process-state-updates-with-reducers) for more detail. + +In our case, we will just keep track of two values: + +```python +from typing_extensions import TypedDict + +class State(TypedDict): + value_1: str + value_2: int +``` + +Our [nodes](../concepts/low_level.md#nodes) are just Python functions that read our graph's state and make updates to it. The first argument to this function will always be the state: + +```python +def step_1(state: State): + return {"value_1": "a"} + +def step_2(state: State): + current_value_1 = state["value_1"] + return {"value_1": f"{current_value_1} b"} + +def step_3(state: State): + return {"value_2": 10} +``` + +!!! note + Note that when issuing updates to the state, each node can just specify the value of the key it wishes to update. + + By default, this will **overwrite** the value of the corresponding key. You can also use [reducers](../concepts/low_level.md#reducers) to control how updates are processed— for example, you can append successive updates to a key instead. See [this section](#process-state-updates-with-reducers) for more detail. + +Finally, we define the graph. We use [StateGraph](../concepts/low_level.md#stategraph) to define a graph that operates on this state. + +We will then use [add_node](../concepts/low_level.md#messagesstate) and [add_edge](../concepts/low_level.md#edges) to populate our graph and define its control flow. + +```python +from langgraph.graph import START, StateGraph + +builder = StateGraph(State) + +# Add nodes +builder.add_node(step_1) +builder.add_node(step_2) +builder.add_node(step_3) + +# Add edges +builder.add_edge(START, "step_1") +builder.add_edge("step_1", "step_2") +builder.add_edge("step_2", "step_3") +``` + +!!! tip "Specifying custom names" + You can specify custom names for nodes using `.add_node`: + + ```python + builder.add_node("my_node", step_1) + ``` + +Note that: + +- `.add_edge` takes the names of nodes, which for functions defaults to `node.__name__`. +- We must specify the entry point of the graph. For this we add an edge with the [START node](../concepts/low_level.md#start-node). +- The graph halts when there are no more nodes to execute. + +We next [compile](../concepts/low_level.md#compiling-your-graph) our graph. This provides a few basic checks on the structure of the graph (e.g., identifying orphaned nodes). If we were adding persistence to our application via a [checkpointer](../concepts/persistence.md), it would also be passed in here. + +```python +graph = builder.compile() +``` + +LangGraph provides built-in utilities for visualizing your graph. Let's inspect our sequence. See [this guide](#visualize-your-graph) for detail on visualization. + +```python +from IPython.display import Image, display + +display(Image(graph.get_graph().draw_mermaid_png())) +``` + +![Sequence of steps graph](assets/graph_api_image_2.png) + +Let's proceed with a simple invocation: + +```python +graph.invoke({"value_1": "c"}) +``` +``` +{'value_1': 'a b', 'value_2': 10} +``` + +Note that: + +- We kicked off invocation by providing a value for a single state key. We must always provide a value for at least one key. +- The value we passed in was overwritten by the first node. +- The second node updated the value. +- The third node populated a different value. + +!!! tip "Built-in shorthand" + `langgraph>=0.2.46` includes a built-in short-hand `add_sequence` for adding node sequences. You can compile the same graph as follows: + + ```python + # highlight-next-line + builder = StateGraph(State).add_sequence([step_1, step_2, step_3]) + builder.add_edge(START, "step_1") + + graph = builder.compile() + + graph.invoke({"value_1": "c"}) + ``` + +## Create branches + +Parallel execution of nodes is essential to speed up overall graph operation. LangGraph offers native support for parallel execution of nodes, which can significantly enhance the performance of graph-based workflows. This parallelization is achieved through fan-out and fan-in mechanisms, utilizing both standard edges and [conditional_edges](https://langchain-ai.github.io/langgraph/reference/graphs.md#langgraph.graph.MessageGraph.add_conditional_edges). Below are some examples showing how to add create branching dataflows that work for you. + +### Run graph nodes in parallel + +In this example, we fan out from `Node A` to `B and C` and then fan in to `D`. With our state, [we specify the reducer add operation](https://langchain-ai.github.io/langgraph/concepts/low_level.md#reducers). This will combine or accumulate values for the specific key in the State, rather than simply overwriting the existing value. For lists, this means concatenating the new list with the existing list. See the above section on [state reducers](#process-state-updates-with-reducers) for more detail on updating state with reducers. + +```python +import operator +from typing import Annotated, Any +from typing_extensions import TypedDict +from langgraph.graph import StateGraph, START, END + +class State(TypedDict): + # The operator.add reducer fn makes this append-only + aggregate: Annotated[list, operator.add] + +def a(state: State): + print(f'Adding "A" to {state["aggregate"]}') + return {"aggregate": ["A"]} + +def b(state: State): + print(f'Adding "B" to {state["aggregate"]}') + return {"aggregate": ["B"]} + +def c(state: State): + print(f'Adding "C" to {state["aggregate"]}') + return {"aggregate": ["C"]} + +def d(state: State): + print(f'Adding "D" to {state["aggregate"]}') + return {"aggregate": ["D"]} + +builder = StateGraph(State) +builder.add_node(a) +builder.add_node(b) +builder.add_node(c) +builder.add_node(d) +builder.add_edge(START, "a") +builder.add_edge("a", "b") +builder.add_edge("a", "c") +builder.add_edge("b", "d") +builder.add_edge("c", "d") +builder.add_edge("d", END) +graph = builder.compile() +``` + +```python +from IPython.display import Image, display + +display(Image(graph.get_graph().draw_mermaid_png())) +``` + +![Parallel execution graph](assets/graph_api_image_3.png) + +With the reducer, you can see that the values added in each node are accumulated. + +```python +graph.invoke({"aggregate": []}, {"configurable": {"thread_id": "foo"}}) +``` +``` +Adding "A" to [] +Adding "B" to ['A'] +Adding "C" to ['A'] +Adding "D" to ['A', 'B', 'C'] +``` + +!!! note + In the above example, nodes `"b"` and `"c"` are executed concurrently in the same [superstep](../concepts/low_level.md#graphs). Because they are in the same step, node `"d"` executes after both `"b"` and `"c"` are finished. + + Importantly, updates from a parallel superstep may not be ordered consistently. If you need a consistent, predetermined ordering of updates from a parallel superstep, you should write the outputs to a separate field in the state together with a value with which to order them. + +??? note "Exception handling?" + LangGraph executes nodes within [supersteps](../concepts/low_level.md#graphs), meaning that while parallel branches are executed in parallel, the entire superstep is **transactional**. If any of these branches raises an exception, **none** of the updates are applied to the state (the entire superstep errors). + + Importantly, when using a [checkpointer](../concepts/persistence.md), results from successful nodes within a superstep are saved, and don't repeat when resumed. + + If you have error-prone (perhaps want to handle flakey API calls), LangGraph provides two ways to address this: + + 1. You can write regular python code within your node to catch and handle exceptions. + 2. You can set a **[retry_policy](../reference/types.md#langgraph.types.RetryPolicy)** to direct the graph to retry nodes that raise certain types of exceptions. Only failing branches are retried, so you needn't worry about performing redundant work. + + Together, these let you perform parallel execution and fully control exception handling. + +### Defer node execution + +Deferring node execution is useful when you want to delay the execution of a node until all other pending tasks are completed. This is particularly relevant when branches have different lengths, which is common in workflows like map-reduce flows. + +The above example showed how to fan-out and fan-in when each path was only one step. But what if one branch had more than one step? Let's add a node `"b_2"` in the `"b"` branch: + +```python +import operator +from typing import Annotated, Any +from typing_extensions import TypedDict +from langgraph.graph import StateGraph, START, END + +class State(TypedDict): + # The operator.add reducer fn makes this append-only + aggregate: Annotated[list, operator.add] + +def a(state: State): + print(f'Adding "A" to {state["aggregate"]}') + return {"aggregate": ["A"]} + +def b(state: State): + print(f'Adding "B" to {state["aggregate"]}') + return {"aggregate": ["B"]} + +def b_2(state: State): + print(f'Adding "B_2" to {state["aggregate"]}') + return {"aggregate": ["B_2"]} + +def c(state: State): + print(f'Adding "C" to {state["aggregate"]}') + return {"aggregate": ["C"]} + +def d(state: State): + print(f'Adding "D" to {state["aggregate"]}') + return {"aggregate": ["D"]} + +builder = StateGraph(State) +builder.add_node(a) +builder.add_node(b) +builder.add_node(b_2) +builder.add_node(c) +# highlight-next-line +builder.add_node(d, defer=True) +builder.add_edge(START, "a") +builder.add_edge("a", "b") +builder.add_edge("a", "c") +builder.add_edge("b", "b_2") +builder.add_edge("b_2", "d") +builder.add_edge("c", "d") +builder.add_edge("d", END) +graph = builder.compile() +``` + +```python +from IPython.display import Image, display + +display(Image(graph.get_graph().draw_mermaid_png())) +``` + +![Deferred execution graph](assets/graph_api_image_4.png) + +```python +graph.invoke({"aggregate": []}) +``` +``` +Adding "A" to [] +Adding "B" to ['A'] +Adding "C" to ['A'] +Adding "B_2" to ['A', 'B', 'C'] +Adding "D" to ['A', 'B', 'C', 'B_2'] +``` + +In the above example, nodes `"b"` and `"c"` are executed concurrently in the same superstep. We set `defer=True` on node `d` so it will not execute until all pending tasks are finished. In this case, this means that `"d"` waits to execute until the entire `"b"` branch is finished. + +### Conditional branching + +If your fan-out should vary at runtime based on the state, you can use [add_conditional_edges](https://langchain-ai.github.io/langgraph/reference/graphs.md#langgraph.graph.StateGraph.add_conditional_edges) to select one or more paths using the graph state. See example below, where node `a` generates a state update that determines the following node. + +```python +import operator +from typing import Annotated, Literal, Sequence +from typing_extensions import TypedDict +from langgraph.graph import StateGraph, START, END + +class State(TypedDict): + aggregate: Annotated[list, operator.add] + # Add a key to the state. We will set this key to determine + # how we branch. + which: str + +def a(state: State): + print(f'Adding "A" to {state["aggregate"]}') + # highlight-next-line + return {"aggregate": ["A"], "which": "c"} + +def b(state: State): + print(f'Adding "B" to {state["aggregate"]}') + return {"aggregate": ["B"]} + +def c(state: State): + print(f'Adding "C" to {state["aggregate"]}') + return {"aggregate": ["C"]} + +builder = StateGraph(State) +builder.add_node(a) +builder.add_node(b) +builder.add_node(c) +builder.add_edge(START, "a") +builder.add_edge("b", END) +builder.add_edge("c", END) + +def conditional_edge(state: State) -> Literal["b", "c"]: + # Fill in arbitrary logic here that uses the state + # to determine the next node + return state["which"] + +# highlight-next-line +builder.add_conditional_edges("a", conditional_edge) + +graph = builder.compile() +``` + +```python +from IPython.display import Image, display + +display(Image(graph.get_graph().draw_mermaid_png())) +``` + +![Conditional branching graph](assets/graph_api_image_5.png) + +```python +result = graph.invoke({"aggregate": []}) +print(result) +``` +``` +Adding "A" to [] +Adding "C" to ['A'] +{'aggregate': ['A', 'C'], 'which': 'c'} +``` + +!!! tip + Your conditional edges can route to multiple destination nodes. For example: + + ```python + def route_bc_or_cd(state: State) -> Sequence[str]: + if state["which"] == "cd": + return ["c", "d"] + return ["b", "c"] + ``` + +## Map-Reduce and the Send API + +LangGraph supports map-reduce and other advanced branching patterns using the Send API. Here is an example of how to use it: + +```python +from langgraph.graph import StateGraph, START, END, Send +from typing_extensions import TypedDict + +class OverallState(TypedDict): + topic: str + subjects: list[str] + jokes: list[str] + best_selected_joke: str + +def generate_topics(state: OverallState): + return {"subjects": ["lions", "elephants", "penguins"]} + +def generate_joke(state: OverallState): + joke_map = { + "lions": "Why don't lions like fast food? Because they can't catch it!", + "elephants": "Why don't elephants use computers? They're afraid of the mouse!", + "penguins": "Why don't penguins like talking to strangers at parties? Because they find it hard to break the ice." + } + return {"jokes": [joke_map[state["subject"]]]} + +def continue_to_jokes(state: OverallState): + return [Send("generate_joke", {"subject": s}) for s in state["subjects"]] + +def best_joke(state: OverallState): + return {"best_selected_joke": "penguins"} + +builder = StateGraph(OverallState) +builder.add_node("generate_topics", generate_topics) +builder.add_node("generate_joke", generate_joke) +builder.add_node("best_joke", best_joke) +builder.add_edge(START, "generate_topics") +builder.add_conditional_edges("generate_topics", continue_to_jokes, ["generate_joke"]) +builder.add_edge("generate_joke", "best_joke") +builder.add_edge("best_joke", END) +builder.add_edge("generate_topics", END) +graph = builder.compile() +``` + +```python +from IPython.display import Image, display + +display(Image(graph.get_graph().draw_mermaid_png())) +``` + +![Map-reduce graph with fanout](assets/graph_api_image_2.png) + +```python +# Call the graph: here we call it to generate a list of jokes +for step in graph.stream({"topic": "animals"}): + print(step) +``` +``` +{'generate_topics': {'subjects': ['lions', 'elephants', 'penguins']}} +{'generate_joke': {'jokes': ["Why don't lions like fast food? Because they can't catch it!"]}} +{'generate_joke': {'jokes': ["Why don't elephants use computers? They're afraid of the mouse!"]}} +{'generate_joke': {'jokes': ['Why don't penguins like talking to strangers at parties? Because they find it hard to break the ice.']}} +{'best_joke': {'best_selected_joke': 'penguins'}} +``` + +## Create and control loops + +When creating a graph with a loop, we require a mechanism for terminating execution. This is most commonly done by adding a [conditional edge](../concepts/low_level.md#conditional-edges) that routes to the [END](../concepts/low_level.md#end-node) node once we reach some termination condition. + +You can also set the graph recursion limit when invoking or streaming the graph. The recursion limit sets the number of [supersteps](../concepts/low_level.md#graphs) that the graph is allowed to execute before it raises an error. Read more about the concept of recursion limits [here](../concepts/low_level.md#recursion-limit). + +Let's consider a simple graph with a loop to better understand how these mechanisms work. + +!!! tip + To return the last value of your state instead of receiving a recursion limit error, see the [next section](#impose-a-recursion-limit). + +When creating a loop, you can include a conditional edge that specifies a termination condition: + +```python +builder = StateGraph(State) +builder.add_node(a) +builder.add_node(b) + +def route(state: State) -> Literal["b", END]: + if termination_condition(state): + return END + else: + return "b" + +builder.add_edge(START, "a") +builder.add_conditional_edges("a", route) +builder.add_edge("b", "a") +graph = builder.compile() +``` + +To control the recursion limit, specify `"recursion_limit"` in the config. This will raise a `GraphRecursionError`, which you can catch and handle: + +```python +from langgraph.errors import GraphRecursionError + +try: + graph.invoke(inputs, {"recursion_limit": 3}) +except GraphRecursionError: + print("Recursion Error") +``` + +Let's define a graph with a simple loop. Note that we use a conditional edge to implement a termination condition. + +```python +import operator +from typing import Annotated, Literal +from typing_extensions import TypedDict +from langgraph.graph import StateGraph, START, END + +class State(TypedDict): + # The operator.add reducer fn makes this append-only + aggregate: Annotated[list, operator.add] + +def a(state: State): + print(f'Node A sees {state["aggregate"]}') + return {"aggregate": ["A"]} + +def b(state: State): + print(f'Node B sees {state["aggregate"]}') + return {"aggregate": ["B"]} + +# Define nodes +builder = StateGraph(State) +builder.add_node(a) +builder.add_node(b) + +# Define edges +def route(state: State) -> Literal["b", END]: + if len(state["aggregate"]) < 7: + return "b" + else: + return END + +builder.add_edge(START, "a") +builder.add_conditional_edges("a", route) +builder.add_edge("b", "a") +graph = builder.compile() +``` + +```python +from IPython.display import Image, display + +display(Image(graph.get_graph().draw_mermaid_png())) +``` + +![Simple loop graph](assets/graph_api_image_3.png) + +This architecture is similar to a [ReAct agent](../agents/overview.md) in which node `"a"` is a tool-calling model, and node `"b"` represents the tools. + +In our `route` conditional edge, we specify that we should end after the `"aggregate"` list in the state passes a threshold length. + +Invoking the graph, we see that we alternate between nodes `"a"` and `"b"` before terminating once we reach the termination condition. + +```python +graph.invoke({"aggregate": []}) +``` +``` +Node A sees [] +Node B sees ['A'] +Node A sees ['A', 'B'] +Node B sees ['A', 'B', 'A'] +Node A sees ['A', 'B', 'A', 'B'] +Node B sees ['A', 'B', 'A', 'B', 'A'] +Node A sees ['A', 'B', 'A', 'B', 'A', 'B'] +``` + +### Impose a recursion limit + +In some applications, we may not have a guarantee that we will reach a given termination condition. In these cases, we can set the graph's [recursion limit](../concepts/low_level.md#recursion-limit). This will raise a `GraphRecursionError` after a given number of [supersteps](../concepts/low_level.md#graphs). We can then catch and handle this exception: + +```python +from langgraph.errors import GraphRecursionError + +try: + graph.invoke({"aggregate": []}, {"recursion_limit": 4}) +except GraphRecursionError: + print("Recursion Error") +``` +``` +Node A sees [] +Node B sees ['A'] +Node C sees ['A', 'B'] +Node D sees ['A', 'B'] +Node A sees ['A', 'B', 'C', 'D'] +Recursion Error +``` + +??? example "Extended example: return state on hitting recursion limit" + + Instead of raising `GraphRecursionError`, we can introduce a new key to the state that keeps track of the number of steps remaining until reaching the recursion limit. We can then use this key to determine if we should end the run. + + LangGraph implements a special `RemainingSteps` annotation. Under the hood, it creates a `ManagedValue` channel -- a state channel that will exist for the duration of our graph run and no longer. + + ```python + import operator + from typing import Annotated, Literal + from typing_extensions import TypedDict + from langgraph.graph import StateGraph, START, END + from langgraph.managed.is_last_step import RemainingSteps + + class State(TypedDict): + aggregate: Annotated[list, operator.add] + remaining_steps: RemainingSteps + + def a(state: State): + print(f'Node A sees {state["aggregate"]}') + return {"aggregate": ["A"]} + + def b(state: State): + print(f'Node B sees {state["aggregate"]}') + return {"aggregate": ["B"]} + + # Define nodes + builder = StateGraph(State) + builder.add_node(a) + builder.add_node(b) + + # Define edges + def route(state: State) -> Literal["b", END]: + if state["remaining_steps"] <= 2: + return END + else: + return "b" + + builder.add_edge(START, "a") + builder.add_conditional_edges("a", route) + builder.add_edge("b", "a") + graph = builder.compile() + + # Test it out + result = graph.invoke({"aggregate": []}, {"recursion_limit": 4}) + print(result) + ``` + ``` + Node A sees [] + Node B sees ['A'] + Node A sees ['A', 'B'] + {'aggregate': ['A', 'B', 'A']} + ``` + +??? example "Extended example: loops with branches" + + To better understand how the recursion limit works, let's consider a more complex example. Below we implement a loop, but one step fans out into two nodes: + + ```python + import operator + from typing import Annotated, Literal + from typing_extensions import TypedDict + from langgraph.graph import StateGraph, START, END + + class State(TypedDict): + aggregate: Annotated[list, operator.add] + + def a(state: State): + print(f'Node A sees {state["aggregate"]}') + return {"aggregate": ["A"]} + + def b(state: State): + print(f'Node B sees {state["aggregate"]}') + return {"aggregate": ["B"]} + + def c(state: State): + print(f'Node C sees {state["aggregate"]}') + return {"aggregate": ["C"]} + + def d(state: State): + print(f'Node D sees {state["aggregate"]}') + return {"aggregate": ["D"]} + + # Define nodes + builder = StateGraph(State) + builder.add_node(a) + builder.add_node(b) + builder.add_node(c) + builder.add_node(d) + + # Define edges + def route(state: State) -> Literal["b", END]: + if len(state["aggregate"]) < 7: + return "b" + else: + return END + + builder.add_edge(START, "a") + builder.add_conditional_edges("a", route) + builder.add_edge("b", "c") + builder.add_edge("b", "d") + builder.add_edge(["c", "d"], "a") + graph = builder.compile() + ``` + + ```python + from IPython.display import Image, display + + display(Image(graph.get_graph().draw_mermaid_png())) + ``` + + ![Complex loop graph with branches](assets/graph_api_image_4.png) + + This graph looks complex, but can be conceptualized as loop of [supersteps](../concepts/low_level.md#graphs): + + 1. Node A + 2. Node B + 3. Nodes C and D + 4. Node A + 5. ... + + We have a loop of four supersteps, where nodes C and D are executed concurrently. + + Invoking the graph as before, we see that we complete two full "laps" before hitting the termination condition: + + ```python + result = graph.invoke({"aggregate": []}) + ``` + ``` + Node A sees [] + Node B sees ['A'] + Node D sees ['A', 'B'] + Node C sees ['A', 'B'] + Node A sees ['A', 'B', 'C', 'D'] + Node B sees ['A', 'B', 'C', 'D', 'A'] + Node D sees ['A', 'B', 'C', 'D', 'A', 'B'] + Node C sees ['A', 'B', 'C', 'D', 'A', 'B'] + Node A sees ['A', 'B', 'C', 'D', 'A', 'B', 'C', 'D'] + ``` + + However, if we set the recursion limit to four, we only complete one lap because each lap is four supersteps: + + ```python + from langgraph.errors import GraphRecursionError + + try: + result = graph.invoke({"aggregate": []}, {"recursion_limit": 4}) + except GraphRecursionError: + print("Recursion Error") + ``` + ``` + Node A sees [] + Node B sees ['A'] + Node C sees ['A', 'B'] + Node D sees ['A', 'B'] + Node A sees ['A', 'B', 'C', 'D'] + Recursion Error + ``` + +## Async + +Using the [async](https://docs.python.org/3/library/asyncio.html) programming paradigm can produce significant performance improvements when running [IO-bound](https://en.wikipedia.org/wiki/I/O_bound) code concurrently (e.g., making concurrent API requests to a chat model provider). + +To convert a `sync` implementation of the graph to an `async` implementation, you will need to: + +1. Update `nodes` use `async def` instead of `def`. +2. Update the code inside to use `await` appropriately. +3. Invoke the graph with `.ainvoke` or `.astream` as desired. + +Because many LangChain objects implement the [Runnable Protocol](https://python.langchain.com/docs/expression_language/interface/) which has `async` variants of all the `sync` methods it's typically fairly quick to upgrade a `sync` graph to an `async` graph. + +See example below. To demonstrate async invocations of underlying LLMs, we will include a chat model: + +{!snippets/chat_model_tabs.md!} + +```python +from langchain.chat_models import init_chat_model +from langgraph.graph import MessagesState, StateGraph + +# highlight-next-line +async def node(state: MessagesState): # (1)! + # highlight-next-line + new_message = await llm.ainvoke(state["messages"]) # (2)! + return {"messages": [new_message]} + +builder = StateGraph(MessagesState).add_node(node).set_entry_point("node") +graph = builder.compile() + +input_message = {"role": "user", "content": "Hello"} +# highlight-next-line +result = await graph.ainvoke({"messages": [input_message]}) # (3)! +``` + +1. Declare nodes to be async functions. +2. Use async invocations when available within the node. +3. Use async invocations on the graph object itself. + +!!! tip "Async streaming" + See the [streaming guide](./streaming.md) for examples of streaming with async. + +## Combine control flow and state updates with `Command` + +It can be useful to combine control flow (edges) and state updates (nodes). For example, you might want to BOTH perform state updates AND decide which node to go to next in the SAME node. LangGraph provides a way to do so by returning a [Command](../reference/types.md#langgraph.types.Command) object from node functions: + +```python +def my_node(state: State) -> Command[Literal["my_other_node"]]: + return Command( + # state update + update={"foo": "bar"}, + # control flow + goto="my_other_node" + ) +``` + +We show an end-to-end example below. Let's create a simple graph with 3 nodes: A, B and C. We will first execute node A, and then decide whether to go to Node B or Node C next based on the output of node A. + +```python +import random +from typing_extensions import TypedDict, Literal +from langgraph.graph import StateGraph, START +from langgraph.types import Command + +# Define graph state +class State(TypedDict): + foo: str + +# Define the nodes + +def node_a(state: State) -> Command[Literal["node_b", "node_c"]]: + print("Called A") + value = random.choice(["a", "b"]) + # this is a replacement for a conditional edge function + if value == "a": + goto = "node_b" + else: + goto = "node_c" + + # note how Command allows you to BOTH update the graph state AND route to the next node + return Command( + # this is the state update + update={"foo": value}, + # this is a replacement for an edge + goto=goto, + ) + +def node_b(state: State): + print("Called B") + return {"foo": state["foo"] + "b"} + +def node_c(state: State): + print("Called C") + return {"foo": state["foo"] + "c"} +``` + +We can now create the `StateGraph` with the above nodes. Notice that the graph doesn't have [conditional edges](../concepts/low_level.md#conditional-edges) for routing! This is because control flow is defined with `Command` inside `node_a`. + +```python +builder = StateGraph(State) +builder.add_edge(START, "node_a") +builder.add_node(node_a) +builder.add_node(node_b) +builder.add_node(node_c) +# NOTE: there are no edges between nodes A, B and C! + +graph = builder.compile() +``` + +!!! important + You might have noticed that we used `Command` as a return type annotation, e.g. `Command[Literal["node_b", "node_c"]]`. This is necessary for the graph rendering and tells LangGraph that `node_a` can navigate to `node_b` and `node_c`. + +```python +from IPython.display import display, Image + +display(Image(graph.get_graph().draw_mermaid_png())) +``` + +![Command-based graph navigation](assets/graph_api_image_6.png) + +If we run the graph multiple times, we'd see it take different paths (A -> B or A -> C) based on the random choice in node A. + +```python +graph.invoke({"foo": ""}) +``` +``` +Called A +Called C +``` + +### Navigate to a node in a parent graph + +If you are using [subgraphs](../concepts/subgraphs.md), you might want to navigate from a node within a subgraph to a different subgraph (i.e. a different node in the parent graph). To do so, you can specify `graph=Command.PARENT` in `Command`: + +```python +def my_node(state: State) -> Command[Literal["my_other_node"]]: + return Command( + update={"foo": "bar"}, + goto="other_subgraph", # where `other_subgraph` is a node in the parent graph + graph=Command.PARENT + ) +``` + +Let's demonstrate this using the above example. We'll do so by changing `node_a` in the above example into a single-node graph that we'll add as a subgraph to our parent graph. + +!!! important "State updates with `Command.PARENT`" + When you send updates from a subgraph node to a parent graph node for a key that's shared by both parent and subgraph [state schemas](../concepts/low_level.md#schema), you **must** define a [reducer](../concepts/low_level.md#reducers) for the key you're updating in the parent graph state. See the example below. + +```python +import operator +from typing_extensions import Annotated + +class State(TypedDict): + # NOTE: we define a reducer here + # highlight-next-line + foo: Annotated[str, operator.add] + +def node_a(state: State): + print("Called A") + value = random.choice(["a", "b"]) + # this is a replacement for a conditional edge function + if value == "a": + goto = "node_b" + else: + goto = "node_c" + + # note how Command allows you to BOTH update the graph state AND route to the next node + return Command( + update={"foo": value}, + goto=goto, + # this tells LangGraph to navigate to node_b or node_c in the parent graph + # NOTE: this will navigate to the closest parent graph relative to the subgraph + # highlight-next-line + graph=Command.PARENT, + ) + +subgraph = StateGraph(State).add_node(node_a).add_edge(START, "node_a").compile() + +def node_b(state: State): + print("Called B") + # NOTE: since we've defined a reducer, we don't need to manually append + # new characters to existing 'foo' value. instead, reducer will append these + # automatically (via operator.add) + # highlight-next-line + return {"foo": "b"} + +def node_c(state: State): + print("Called C") + # highlight-next-line + return {"foo": "c"} + +builder = StateGraph(State) +builder.add_edge(START, "subgraph") +builder.add_node("subgraph", subgraph) +builder.add_node(node_b) +builder.add_node(node_c) + +graph = builder.compile() +``` + +```python +graph.invoke({"foo": ""}) +``` +``` +Called A +Called C +``` + +### Use inside tools + +A common use case is updating graph state from inside a tool. For example, in a customer support application you might want to look up customer information based on their account number or ID in the beginning of the conversation. To update the graph state from the tool, you can return `Command(update={"my_custom_key": "foo", "messages": [...]})` from the tool: + +```python +@tool +def lookup_user_info(tool_call_id: Annotated[str, InjectedToolCallId], config: RunnableConfig): + """Use this to look up user information to better assist them with their questions.""" + user_info = get_user_info(config.get("configurable", {}).get("user_id")) + return Command( + update={ + # update the state keys + "user_info": user_info, + # update the message history + "messages": [ToolMessage("Successfully looked up user information", tool_call_id=tool_call_id)] + } + ) +``` + +!!! important + You MUST include `messages` (or any state key used for the message history) in `Command.update` when returning `Command` from a tool and the list of messages in `messages` MUST contain a `ToolMessage`. This is necessary for the resulting message history to be valid (LLM providers require AI messages with tool calls to be followed by the tool result messages). + +If you are using tools that update state via `Command`, we recommend using prebuilt [`ToolNode`](../reference/agents.md#langgraph.prebuilt.tool_node.ToolNode) which automatically handles tools returning `Command` objects and propagates them to the graph state. If you're writing a custom node that calls tools, you would need to manually propagate `Command` objects returned by the tools as the update from the node. + +## Visualize your graph + +Here we demonstrate how to visualize the graphs you create. + +You can visualize any arbitrary [Graph](https://langchain-ai.github.io/langgraph/reference/graphs/), including [StateGraph](https://langchain-ai.github.io/langgraph/reference/graphs.md#langgraph.graph.state.StateGraph). Let's have some fun by drawing fractals :). + +```python +import random +from typing import Annotated, Literal +from typing_extensions import TypedDict +from langgraph.graph import StateGraph, START, END +from langgraph.graph.message import add_messages + +class State(TypedDict): + messages: Annotated[list, add_messages] + +class MyNode: + def __init__(self, name: str): + self.name = name + def __call__(self, state: State): + return {"messages": [("assistant", f"Called node {self.name}")]} + +def route(state) -> Literal["entry_node", "__end__"]: + if len(state["messages"]) > 10: + return "__end__" + return "entry_node" + +def add_fractal_nodes(builder, current_node, level, max_level): + if level > max_level: + return + # Number of nodes to create at this level + num_nodes = random.randint(1, 3) # Adjust randomness as needed + for i in range(num_nodes): + nm = ["A", "B", "C"][i] + node_name = f"node_{current_node}_{nm}" + builder.add_node(node_name, MyNode(node_name)) + builder.add_edge(current_node, node_name) + # Recursively add more nodes + r = random.random() + if r > 0.2 and level + 1 < max_level: + add_fractal_nodes(builder, node_name, level + 1, max_level) + elif r > 0.05: + builder.add_conditional_edges(node_name, route, node_name) + else: + # End + builder.add_edge(node_name, "__end__") + +def build_fractal_graph(max_level: int): + builder = StateGraph(State) + entry_point = "entry_node" + builder.add_node(entry_point, MyNode(entry_point)) + builder.add_edge(START, entry_point) + add_fractal_nodes(builder, entry_point, 1, max_level) + # Optional: set a finish point if required + builder.add_edge(entry_point, END) # or any specific node + return builder.compile() + +app = build_fractal_graph(3) +``` + +### Mermaid + +We can also convert a graph class into Mermaid syntax. + +```python +print(app.get_graph().draw_mermaid()) +``` +``` +%%{init: {'flowchart': {'curve': 'linear'}}}%% +graph TD; + __start__([

__start__

]):::first + entry_node(entry_node) + node_entry_node_A(node_entry_node_A) + node_entry_node_B(node_entry_node_B) + node_node_entry_node_B_A(node_node_entry_node_B_A) + node_node_entry_node_B_B(node_node_entry_node_B_B) + node_node_entry_node_B_C(node_node_entry_node_B_C) + __end__([

__end__

]):::last + __start__ --> entry_node; + entry_node --> __end__; + entry_node --> node_entry_node_A; + entry_node --> node_entry_node_B; + node_entry_node_B --> node_node_entry_node_B_A; + node_entry_node_B --> node_node_entry_node_B_B; + node_entry_node_B --> node_node_entry_node_B_C; + node_entry_node_A -.-> entry_node; + node_entry_node_A -.-> __end__; + node_node_entry_node_B_A -.-> entry_node; + node_node_entry_node_B_A -.-> __end__; + node_node_entry_node_B_B -.-> entry_node; + node_node_entry_node_B_B -.-> __end__; + node_node_entry_node_B_C -.-> entry_node; + node_node_entry_node_B_C -.-> __end__; + classDef default fill:#f2f0ff,line-height:1.2 + classDef first fill-opacity:0 + classDef last fill:#bfb6fc +``` + +### PNG + +If preferred, we could render the Graph into a `.png`. Here we could use three options: + +- Using Mermaid.ink API (does not require additional packages) +- Using Mermaid + Pyppeteer (requires `pip install pyppeteer`) +- Using graphviz (which requires `pip install graphviz`) + +**Using Mermaid.Ink** + +By default, `draw_mermaid_png()` uses Mermaid.Ink's API to generate the diagram. + +```python +from IPython.display import Image, display +from langchain_core.runnables.graph import CurveStyle, MermaidDrawMethod, NodeStyles + +display(Image(app.get_graph().draw_mermaid_png())) +``` + +![Fractal graph visualization](assets/graph_api_image_5.png) + +**Using Mermaid + Pyppeteer** + +```python +import nest_asyncio + +nest_asyncio.apply() # Required for Jupyter Notebook to run async functions + +display( + Image( + app.get_graph().draw_mermaid_png( + curve_style=CurveStyle.LINEAR, + node_colors=NodeStyles(first="#ffdfba", last="#baffc9", default="#fad7de"), + wrap_label_n_words=9, + output_file_path=None, + draw_method=MermaidDrawMethod.PYPPETEER, + background_color="white", + padding=10, + ) + ) +) +``` + +**Using Graphviz** + +```python +try: + display(Image(app.get_graph().draw_png())) +except ImportError: + print( + "You likely need to install dependencies for pygraphviz, see more here https://github.com/pygraphviz/pygraphviz/blob/main/INSTALL.txt" + ) +``` \ No newline at end of file diff --git a/docs/docs/how-tos/multi_agent.md b/docs/docs/how-tos/multi_agent.md new file mode 100644 index 000000000..5aead8b95 --- /dev/null +++ b/docs/docs/how-tos/multi_agent.md @@ -0,0 +1,580 @@ +# Build multi-agent systems + +A single agent might struggle if it needs to specialize in multiple domains or manage many tools. To tackle this, you can break your agent into smaller, independent agents and composing them into a [multi-agent system](../concepts/multi_agent.md). + +In multi-agent systems, agents need to communicate between each other. They do so via [handoffs](#handoffs) — a primitive that describes which agent to hand control to and the payload to send to that agent. + +This guide covers the following: + +* implementing [handoffs](#handoffs) between agents +* using handoffs and the prebuilt [agent](../agents/agents.md) to [build a custom multi-agent system](#build-a-multi-agent-system) + +To get started with building multi-agent systems, check out LangGraph [prebuilt implementations](#prebuilt-implementations) of two of the most popular multi-agent architectures — [supervisor](../agents/multi-agent.md#supervisor) and [swarm](../agents/multi-agent.md#swarm). + +## Handoffs + +To set up communication between the agents in a multi-agent system you can use [**handoffs**](../concepts/multi_agent.md#handoffs) — a pattern where one agent *hands off* control to another. Handoffs allow you to specify: + +- **destination**: target agent to navigate to (e.g., name of the LangGraph node to go to) +- **payload**: information to pass to that agent (e.g., state update) + +### Create handoffs + +To implement handoffs, you can return `Command` objects from your agent nodes or tools: + +```python +from typing import Annotated +from langchain_core.tools import tool, InjectedToolCallId +from langgraph.prebuilt import create_react_agent, InjectedState +from langgraph.graph import StateGraph, START, MessagesState +from langgraph.types import Command + +def create_handoff_tool(*, agent_name: str, description: str | None = None): + name = f"transfer_to_{agent_name}" + description = description or f"Transfer to {agent_name}" + + @tool(name, description=description) + def handoff_tool( + # highlight-next-line + state: Annotated[MessagesState, InjectedState], # (1)! + # highlight-next-line + tool_call_id: Annotated[str, InjectedToolCallId], + ) -> Command: + tool_message = { + "role": "tool", + "content": f"Successfully transferred to {agent_name}", + "name": name, + "tool_call_id": tool_call_id, + } + return Command( # (2)! + # highlight-next-line + goto=agent_name, # (3)! + # highlight-next-line + update={"messages": state["messages"] + [tool_message]}, # (4)! + # highlight-next-line + graph=Command.PARENT, # (5)! + ) + return handoff_tool +``` + +1. Access the [state](../concepts/low_level.md#state) of the agent that is calling the handoff tool using the [InjectedState][langgraph.prebuilt.InjectedState] annotation. +2. The `Command` primitive allows specifying a state update and a node transition as a single operation, making it useful for implementing handoffs. +3. Name of the agent or node to hand off to. +4. Take the agent's messages and **add** them to the parent's **state** as part of the handoff. The next agent will see the parent state. +5. Indicate to LangGraph that we need to navigate to agent node in a **parent** multi-agent graph. + +!!! tip + + If you want to use tools that return `Command`, you can either use prebuilt [`create_react_agent`][langgraph.prebuilt.chat_agent_executor.create_react_agent] / [`ToolNode`][langgraph.prebuilt.tool_node.ToolNode] components, or implement your own tool-executing node that collects `Command` objects returned by the tools and returns a list of them, e.g.: + + ```python + def call_tools(state): + ... + commands = [tools_by_name[tool_call["name"]].invoke(tool_call) for tool_call in tool_calls] + return commands + ``` + +!!! Important + + This handoff implementation assumes that: + + - each agent receives overall message history (across all agents) in the multi-agent system as its input. If you want more control over agent inputs, see [this section](#control-agent-inputs) + - each agent outputs its internal messages history to the overall message history of the multi-agent system. If you want more control over **how agent outputs are added**, wrap the agent in a separate node function: + + ```python + def call_hotel_assistant(state): + # return agent's final response, + # excluding inner monologue + response = hotel_assistant.invoke(state) + # highlight-next-line + return {"messages": response["messages"][-1]} + ``` + +### Control agent inputs + +You can use the [`Send()`][langgraph.types.Send] primitive to directly send data to the worker agents during the handoff. For example, you can request that the calling agent populate a task description for the next agent: + +```python + +from typing import Annotated +from langchain_core.tools import tool, InjectedToolCallId +from langgraph.prebuilt import InjectedState +from langgraph.graph import StateGraph, START, MessagesState +# highlight-next-line +from langgraph.types import Command, Send + +def create_task_description_handoff_tool( + *, agent_name: str, description: str | None = None +): + name = f"transfer_to_{agent_name}" + description = description or f"Ask {agent_name} for help." + + @tool(name, description=description) + def handoff_tool( + # this is populated by the calling agent + task_description: Annotated[ + str, + "Description of what the next agent should do, including all of the relevant context.", + ], + # these parameters are ignored by the LLM + state: Annotated[MessagesState, InjectedState], + ) -> Command: + task_description_message = {"role": "user", "content": task_description} + agent_input = {**state, "messages": [task_description_message]} + return Command( + # highlight-next-line + goto=[Send(agent_name, agent_input)], + graph=Command.PARENT, + ) + + return handoff_tool +``` + +See the multi-agent [supervisor](../tutorials/multi_agent/agent_supervisor.ipynb#4-create-delegation-tasks) example for a full example of using [`Send()`][langgraph.types.Send] in handoffs. + +## Build a multi-agent system + +You can use handoffs in any agents built with LangGraph. We recommend using the prebuilt [agent](../agents/overview.md) or [`ToolNode`](./tool-calling.md#toolnode), as they natively support handoffs tools returning `Command`. Below is an example of how you can implement a multi-agent system for booking travel using handoffs: + +```python +from langgraph.prebuilt import create_react_agent +from langgraph.graph import StateGraph, START, MessagesState + +def create_handoff_tool(*, agent_name: str, description: str | None = None): + # same implementation as above + ... + return Command(...) + +# Handoffs +transfer_to_hotel_assistant = create_handoff_tool(agent_name="hotel_assistant") +transfer_to_flight_assistant = create_handoff_tool(agent_name="flight_assistant") + +# Define agents +flight_assistant = create_react_agent( + model="anthropic:claude-3-5-sonnet-latest", + # highlight-next-line + tools=[..., transfer_to_hotel_assistant], + # highlight-next-line + name="flight_assistant" +) +hotel_assistant = create_react_agent( + model="anthropic:claude-3-5-sonnet-latest", + # highlight-next-line + tools=[..., transfer_to_flight_assistant], + # highlight-next-line + name="hotel_assistant" +) + +# Define multi-agent graph +multi_agent_graph = ( + StateGraph(MessagesState) + # highlight-next-line + .add_node(flight_assistant) + # highlight-next-line + .add_node(hotel_assistant) + .add_edge(START, "flight_assistant") + .compile() +) +``` + +??? example "Full example: Multi-agent system for booking travel" + + ```python + from typing import Annotated + from langchain_core.messages import convert_to_messages + from langchain_core.tools import tool, InjectedToolCallId + from langgraph.prebuilt import create_react_agent, InjectedState + from langgraph.graph import StateGraph, START, MessagesState + from langgraph.types import Command + + # We'll use `pretty_print_messages` helper to render the streamed agent outputs nicely + + def pretty_print_message(message, indent=False): + pretty_message = message.pretty_repr(html=True) + if not indent: + print(pretty_message) + return + + indented = "\n".join("\t" + c for c in pretty_message.split("\n")) + print(indented) + + + def pretty_print_messages(update, last_message=False): + is_subgraph = False + if isinstance(update, tuple): + ns, update = update + # skip parent graph updates in the printouts + if len(ns) == 0: + return + + graph_id = ns[-1].split(":")[0] + print(f"Update from subgraph {graph_id}:") + print("\n") + is_subgraph = True + + for node_name, node_update in update.items(): + update_label = f"Update from node {node_name}:" + if is_subgraph: + update_label = "\t" + update_label + + print(update_label) + print("\n") + + messages = convert_to_messages(node_update["messages"]) + if last_message: + messages = messages[-1:] + + for m in messages: + pretty_print_message(m, indent=is_subgraph) + print("\n") + + + def create_handoff_tool(*, agent_name: str, description: str | None = None): + name = f"transfer_to_{agent_name}" + description = description or f"Transfer to {agent_name}" + + @tool(name, description=description) + def handoff_tool( + # highlight-next-line + state: Annotated[MessagesState, InjectedState], # (1)! + # highlight-next-line + tool_call_id: Annotated[str, InjectedToolCallId], + ) -> Command: + tool_message = { + "role": "tool", + "content": f"Successfully transferred to {agent_name}", + "name": name, + "tool_call_id": tool_call_id, + } + return Command( # (2)! + # highlight-next-line + goto=agent_name, # (3)! + # highlight-next-line + update={"messages": state["messages"] + [tool_message]}, # (4)! + # highlight-next-line + graph=Command.PARENT, # (5)! + ) + return handoff_tool + + # Handoffs + transfer_to_hotel_assistant = create_handoff_tool( + agent_name="hotel_assistant", + description="Transfer user to the hotel-booking assistant.", + ) + transfer_to_flight_assistant = create_handoff_tool( + agent_name="flight_assistant", + description="Transfer user to the flight-booking assistant.", + ) + + # Simple agent tools + def book_hotel(hotel_name: str): + """Book a hotel""" + return f"Successfully booked a stay at {hotel_name}." + + def book_flight(from_airport: str, to_airport: str): + """Book a flight""" + return f"Successfully booked a flight from {from_airport} to {to_airport}." + + # Define agents + flight_assistant = create_react_agent( + model="anthropic:claude-3-5-sonnet-latest", + # highlight-next-line + tools=[book_flight, transfer_to_hotel_assistant], + prompt="You are a flight booking assistant", + # highlight-next-line + name="flight_assistant" + ) + hotel_assistant = create_react_agent( + model="anthropic:claude-3-5-sonnet-latest", + # highlight-next-line + tools=[book_hotel, transfer_to_flight_assistant], + prompt="You are a hotel booking assistant", + # highlight-next-line + name="hotel_assistant" + ) + + # Define multi-agent graph + multi_agent_graph = ( + StateGraph(MessagesState) + .add_node(flight_assistant) + .add_node(hotel_assistant) + .add_edge(START, "flight_assistant") + .compile() + ) + + # Run the multi-agent graph + for chunk in multi_agent_graph.stream( + { + "messages": [ + { + "role": "user", + "content": "book a flight from BOS to JFK and a stay at McKittrick Hotel" + } + ] + }, + # highlight-next-line + subgraphs=True + ): + pretty_print_messages(chunk) + ``` + + 1. Access agent's state + 2. The `Command` primitive allows specifying a state update and a node transition as a single operation, making it useful for implementing handoffs. + 3. Name of the agent or node to hand off to. + 4. Take the agent's messages and **add** them to the parent's **state** as part of the handoff. The next agent will see the parent state. + 5. Indicate to LangGraph that we need to navigate to agent node in a **parent** multi-agent graph. + +## Multi-turn conversation + +Users might want to engage in a *multi-turn conversation* with one or more agents. To build a system that can handle this, you can create a node that uses an [`interrupt`][langgraph.types.interrupt] to collect user input and routes back to the **active** agent. + +The agents can then be implemented as nodes in a graph that executes agent steps and determines the next action: + +1. **Wait for user input** to continue the conversation, or +2. **Route to another agent** (or back to itself, such as in a loop) via a [handoff](#handoffs) + +```python +def human(state) -> Command[Literal["agent", "another_agent"]]: + """A node for collecting user input.""" + user_input = interrupt(value="Ready for user input.") + + # Determine the active agent. + active_agent = ... + + ... + return Command( + update={ + "messages": [{ + "role": "human", + "content": user_input, + }] + }, + goto=active_agent + ) + +def agent(state) -> Command[Literal["agent", "another_agent", "human"]]: + # The condition for routing/halting can be anything, e.g. LLM tool call / structured output, etc. + goto = get_next_agent(...) # 'agent' / 'another_agent' + if goto: + return Command(goto=goto, update={"my_state_key": "my_state_value"}) + else: + return Command(goto="human") # Go to human node +``` + +??? example "Full example: multi-agent system for travel recommendations" + + In this example, we will build a team of travel assistant agents that can communicate with each other via handoffs. + + We will create 2 agents: + + * travel_advisor: can help with travel destination recommendations. Can ask hotel_advisor for help. + * hotel_advisor: can help with hotel recommendations. Can ask travel_advisor for help. + + ```python + from langchain_anthropic import ChatAnthropic + from langgraph.graph import MessagesState, StateGraph, START + from langgraph.prebuilt import create_react_agent, InjectedState + from langgraph.types import Command, interrupt + from langgraph.checkpoint.memory import MemorySaver + + + model = ChatAnthropic(model="claude-3-5-sonnet-latest") + + class MultiAgentState(MessagesState): + last_active_agent: str + + + # Define travel advisor tools and ReAct agent + travel_advisor_tools = [ + get_travel_recommendations, + make_handoff_tool(agent_name="hotel_advisor"), + ] + travel_advisor = create_react_agent( + model, + travel_advisor_tools, + prompt=( + "You are a general travel expert that can recommend travel destinations (e.g. countries, cities, etc). " + "If you need hotel recommendations, ask 'hotel_advisor' for help. " + "You MUST include human-readable response before transferring to another agent." + ), + ) + + + def call_travel_advisor( + state: MultiAgentState, + ) -> Command[Literal["hotel_advisor", "human"]]: + # You can also add additional logic like changing the input to the agent / output from the agent, etc. + # NOTE: we're invoking the ReAct agent with the full history of messages in the state + response = travel_advisor.invoke(state) + update = {**response, "last_active_agent": "travel_advisor"} + return Command(update=update, goto="human") + + + # Define hotel advisor tools and ReAct agent + hotel_advisor_tools = [ + get_hotel_recommendations, + make_handoff_tool(agent_name="travel_advisor"), + ] + hotel_advisor = create_react_agent( + model, + hotel_advisor_tools, + prompt=( + "You are a hotel expert that can provide hotel recommendations for a given destination. " + "If you need help picking travel destinations, ask 'travel_advisor' for help." + "You MUST include human-readable response before transferring to another agent." + ), + ) + + + def call_hotel_advisor( + state: MultiAgentState, + ) -> Command[Literal["travel_advisor", "human"]]: + response = hotel_advisor.invoke(state) + update = {**response, "last_active_agent": "hotel_advisor"} + return Command(update=update, goto="human") + + + def human_node( + state: MultiAgentState, config + ) -> Command[Literal["hotel_advisor", "travel_advisor", "human"]]: + """A node for collecting user input.""" + + user_input = interrupt(value="Ready for user input.") + active_agent = state["last_active_agent"] + + return Command( + update={ + "messages": [ + { + "role": "human", + "content": user_input, + } + ] + }, + goto=active_agent, + ) + + + builder = StateGraph(MultiAgentState) + builder.add_node("travel_advisor", call_travel_advisor) + builder.add_node("hotel_advisor", call_hotel_advisor) + + # This adds a node to collect human input, which will route + # back to the active agent. + builder.add_node("human", human_node) + + # We'll always start with a general travel advisor. + builder.add_edge(START, "travel_advisor") + + + checkpointer = MemorySaver() + graph = builder.compile(checkpointer=checkpointer) + ``` + + Let's test a multi turn conversation with this application. + + ```python + import uuid + + thread_config = {"configurable": {"thread_id": str(uuid.uuid4())}} + + inputs = [ + # 1st round of conversation, + { + "messages": [ + {"role": "user", "content": "i wanna go somewhere warm in the caribbean"} + ] + }, + # Since we're using `interrupt`, we'll need to resume using the Command primitive. + # 2nd round of conversation, + Command( + resume="could you recommend a nice hotel in one of the areas and tell me which area it is." + ), + # 3rd round of conversation, + Command( + resume="i like the first one. could you recommend something to do near the hotel?" + ), + ] + + for idx, user_input in enumerate(inputs): + print() + print(f"--- Conversation Turn {idx + 1} ---") + print() + print(f"User: {user_input}") + print() + for update in graph.stream( + user_input, + config=thread_config, + stream_mode="updates", + ): + for node_id, value in update.items(): + if isinstance(value, dict) and value.get("messages", []): + last_message = value["messages"][-1] + if isinstance(last_message, dict) or last_message.type != "ai": + continue + print(f"{node_id}: {last_message.content}") + ``` + + ``` + --- Conversation Turn 1 --- + + User: {'messages': [{'role': 'user', 'content': 'i wanna go somewhere warm in the caribbean'}]} + + travel_advisor: Based on the recommendations, Aruba would be an excellent choice for your Caribbean getaway! Aruba is known as "One Happy Island" and offers: + - Year-round warm weather with consistent temperatures around 82°F (28°C) + - Beautiful white sand beaches like Eagle Beach and Palm Beach + - Clear turquoise waters perfect for swimming and snorkeling + - Minimal rainfall and location outside the hurricane belt + - A blend of Caribbean and Dutch culture + - Great dining options and nightlife + - Various water sports and activities + + Would you like me to get some specific hotel recommendations in Aruba for your stay? I can transfer you to our hotel advisor who can help with accommodations. + + --- Conversation Turn 2 --- + + User: Command(resume='could you recommend a nice hotel in one of the areas and tell me which area it is.') + + hotel_advisor: Based on the recommendations, I can suggest two excellent options: + + 1. The Ritz-Carlton, Aruba - Located in Palm Beach + - This luxury resort is situated in the vibrant Palm Beach area + - Known for its exceptional service and amenities + - Perfect if you want to be close to dining, shopping, and entertainment + - Features multiple restaurants, a casino, and a world-class spa + - Located on a pristine stretch of Palm Beach + + 2. Bucuti & Tara Beach Resort - Located in Eagle Beach + - An adults-only boutique resort on Eagle Beach + - Known for being more intimate and peaceful + - Award-winning for its sustainability practices + - Perfect for a romantic getaway or peaceful vacation + - Located on one of the most beautiful beaches in the Caribbean + + Would you like more specific information about either of these properties or their locations? + + --- Conversation Turn 3 --- + + User: Command(resume='i like the first one. could you recommend something to do near the hotel?') + + travel_advisor: Near the Ritz-Carlton in Palm Beach, here are some highly recommended activities: + + 1. Visit the Palm Beach Plaza Mall - Just a short walk from the hotel, featuring shopping, dining, and entertainment + 2. Try your luck at the Stellaris Casino - It's right in the Ritz-Carlton + 3. Take a sunset sailing cruise - Many depart from the nearby pier + 4. Visit the California Lighthouse - A scenic landmark just north of Palm Beach + 5. Enjoy water sports at Palm Beach: + - Jet skiing + - Parasailing + - Snorkeling + - Stand-up paddleboarding + + Would you like more specific information about any of these activities or would you like to know about other options in the area? + ``` + +## Prebuilt implementations + +LangGraph comes with prebuilt implementations of two of the most popular multi-agent architectures: + +- [supervisor](../agents/multi-agent.md#supervisor) — individual agents are coordinated by a central supervisor agent. The supervisor controls all communication flow and task delegation, making decisions about which agent to invoke based on the current context and task requirements. You can use [`langgraph-supervisor`](https://github.com/langchain-ai/langgraph-supervisor-py) library to create a supervisor multi-agent systems. +- [swarm](../agents/multi-agent.md#supervisor) — agents dynamically hand off control to one another based on their specializations. The system remembers which agent was last active, ensuring that on subsequent interactions, the conversation resumes with that agent. You can use [`langgraph-swarm`](https://github.com/langchain-ai/langgraph-swarm-py) library to create a swarm multi-agent systems. \ No newline at end of file diff --git a/docs/docs/how-tos/subgraph.ipynb b/docs/docs/how-tos/subgraph.ipynb deleted file mode 100644 index a16d99216..000000000 --- a/docs/docs/how-tos/subgraph.ipynb +++ /dev/null @@ -1,559 +0,0 @@ -{ - "cells": [ - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Use subgraphs\n", - "\n", - "This guide explains the mechanics of using [subgraphs](../../concepts/subgraphs). A common application of subgraphs is to build [multi-agent](../../concepts/multi_agent) systems.\n", - "\n", - "When adding subgraphs, you need to define how the parent graph and the subgraph communicate:\n", - "\n", - "* [Shared state schemas](#shared-state-schemas) — parent and subgraph have **shared state keys** in their state [schemas](../../concepts/low_level#state)\n", - "* [Different state schemas](#different-state-schemas) — **no shared state keys** in parent and subgraph [schemas](../../concepts/low_level#state)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Setup" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "%%capture --no-stderr\n", - "%pip install -U langgraph" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - "

Set up LangSmith for LangGraph development

\n", - "

\n", - " Sign up for LangSmith to quickly spot issues and improve the performance of your LangGraph projects. LangSmith lets you use trace data to debug, test, and monitor your LLM apps built with LangGraph — read more about how to get started here. \n", - "

\n", - "
" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Shared state schemas\n", - "\n", - "A common case is for the parent graph and subgraph to communicate over a shared state key (channel) in the [schema](../../concepts/low_level#state). For example, in [multi-agent](../../concepts/multi_agent) systems, the agents often communicate over a shared [messages](https://langchain-ai.github.io/langgraph/concepts/low_level/#why-use-messages) key.\n", - "\n", - "If your subgraph shares state keys with the parent graph, you can follow these steps to add it to your graph:\n", - "\n", - "1. Define the subgraph workflow (`subgraph_builder` in the example below) and compile it\n", - "2. Pass compiled subgraph to the `.add_node` method when defining the parent graph workflow\n", - "\n", - "```python\n", - "from typing_extensions import TypedDict\n", - "from langgraph.graph.state import StateGraph, START\n", - "\n", - "class State(TypedDict):\n", - " foo: str\n", - "\n", - "# Subgraph\n", - "\n", - "def subgraph_node_1(state: State):\n", - " return {\"foo\": \"hi! \" + state[\"foo\"]}\n", - "\n", - "subgraph_builder = StateGraph(State)\n", - "subgraph_builder.add_node(subgraph_node_1)\n", - "subgraph_builder.add_edge(START, \"subgraph_node_1\")\n", - "# highlight-next-line\n", - "subgraph = subgraph_builder.compile()\n", - "\n", - "# Parent graph\n", - "\n", - "builder = StateGraph(State)\n", - "# highlight-next-line\n", - "builder.add_node(\"node_1\", subgraph)\n", - "builder.add_edge(START, \"node_1\")\n", - "graph = builder.compile()\n", - "```\n", - "\n", - "??? example \"Full example: shared state schemas\"\n", - "\n", - " ```python\n", - " from typing_extensions import TypedDict\n", - " from langgraph.graph.state import StateGraph, START\n", - "\n", - " # Define subgraph\n", - " class SubgraphState(TypedDict):\n", - " foo: str # (1)! \n", - " bar: str # (2)!\n", - " \n", - " def subgraph_node_1(state: SubgraphState):\n", - " return {\"bar\": \"bar\"}\n", - " \n", - " def subgraph_node_2(state: SubgraphState):\n", - " # note that this node is using a state key ('bar') that is only available in the subgraph\n", - " # and is sending update on the shared state key ('foo')\n", - " return {\"foo\": state[\"foo\"] + state[\"bar\"]}\n", - " \n", - " subgraph_builder = StateGraph(SubgraphState)\n", - " subgraph_builder.add_node(subgraph_node_1)\n", - " subgraph_builder.add_node(subgraph_node_2)\n", - " subgraph_builder.add_edge(START, \"subgraph_node_1\")\n", - " subgraph_builder.add_edge(\"subgraph_node_1\", \"subgraph_node_2\")\n", - " subgraph = subgraph_builder.compile()\n", - " \n", - " # Define parent graph\n", - " class ParentState(TypedDict):\n", - " foo: str\n", - " \n", - " def node_1(state: ParentState):\n", - " return {\"foo\": \"hi! \" + state[\"foo\"]}\n", - " \n", - " builder = StateGraph(ParentState)\n", - " builder.add_node(\"node_1\", node_1)\n", - " # highlight-next-line\n", - " builder.add_node(\"node_2\", subgraph)\n", - " builder.add_edge(START, \"node_1\")\n", - " builder.add_edge(\"node_1\", \"node_2\")\n", - " graph = builder.compile()\n", - " \n", - " for chunk in graph.stream({\"foo\": \"foo\"}):\n", - " print(chunk)\n", - " ```\n", - "\n", - " 1. This key is shared with the parent graph state\n", - " 2. This key is private to the `SubgraphState` and is not visible to the parent graph\n", - " \n", - " ```\n", - " {'node_1': {'foo': 'hi! foo'}}\n", - " {'node_2': {'foo': 'hi! foobar'}}\n", - " ```\n", - "\n", - " ```" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Different state schemas\n", - "\n", - "For more complex systems you might want to define subgraphs that have a **completely different schema** from the parent graph (no shared keys). For example, you might want to keep a private message history for each of the agents in a [multi-agent](../concepts/multi_agent.md) system.\n", - "\n", - "If that's the case for your application, you need to define a node **function that invokes the subgraph**. This function needs to transform the input (parent) state to the subgraph state before invoking the subgraph, and transform the results back to the parent state before returning the state update from the node.\n", - "\n", - "```python\n", - "from typing_extensions import TypedDict\n", - "from langgraph.graph.state import StateGraph, START\n", - "\n", - "class SubgraphState(TypedDict):\n", - " bar: str\n", - "\n", - "# Subgraph\n", - "\n", - "def subgraph_node_1(state: SubgraphState):\n", - " return {\"bar\": \"hi! \" + state[\"bar\"]}\n", - "\n", - "subgraph_builder = StateGraph(SubgraphState)\n", - "subgraph_builder.add_node(subgraph_node_1)\n", - "subgraph_builder.add_edge(START, \"subgraph_node_1\")\n", - "# highlight-next-line\n", - "subgraph = subgraph_builder.compile()\n", - "\n", - "# Parent graph\n", - "\n", - "class State(TypedDict):\n", - " foo: str\n", - "\n", - "def call_subgraph(state: State):\n", - " # highlight-next-line\n", - " subgraph_output = subgraph.invoke({\"bar\": state[\"foo\"]}) # (1)!\n", - " # highlight-next-line\n", - " return {\"foo\": subgraph_output[\"bar\"]} # (2)!\n", - "\n", - "builder = StateGraph(State)\n", - "# highlight-next-line\n", - "builder.add_node(\"node_1\", call_subgraph)\n", - "builder.add_edge(START, \"node_1\")\n", - "graph = builder.compile()\n", - "```\n", - "\n", - "1. Transform the state to the subgraph state\n", - "2. Transform response back to the parent state\n", - "\n", - "??? example \"Full example: different state schemas\"\n", - "\n", - " ```python\n", - " from typing_extensions import TypedDict\n", - " from langgraph.graph.state import StateGraph, START\n", - "\n", - " # Define subgraph\n", - " class SubgraphState(TypedDict):\n", - " # note that none of these keys are shared with the parent graph state\n", - " bar: str\n", - " baz: str\n", - " \n", - " def subgraph_node_1(state: SubgraphState):\n", - " return {\"baz\": \"baz\"}\n", - " \n", - " def subgraph_node_2(state: SubgraphState):\n", - " return {\"bar\": state[\"bar\"] + state[\"baz\"]}\n", - " \n", - " subgraph_builder = StateGraph(SubgraphState)\n", - " subgraph_builder.add_node(subgraph_node_1)\n", - " subgraph_builder.add_node(subgraph_node_2)\n", - " subgraph_builder.add_edge(START, \"subgraph_node_1\")\n", - " subgraph_builder.add_edge(\"subgraph_node_1\", \"subgraph_node_2\")\n", - " subgraph = subgraph_builder.compile()\n", - " \n", - " # Define parent graph\n", - " class ParentState(TypedDict):\n", - " foo: str\n", - " \n", - " def node_1(state: ParentState):\n", - " return {\"foo\": \"hi! \" + state[\"foo\"]}\n", - " \n", - " def node_2(state: ParentState):\n", - " # highlight-next-line\n", - " response = subgraph.invoke({\"bar\": state[\"foo\"]}) # (1)!\n", - " # highlight-next-line\n", - " return {\"foo\": response[\"bar\"]} # (2)!\n", - " \n", - " \n", - " builder = StateGraph(ParentState)\n", - " builder.add_node(\"node_1\", node_1)\n", - " # highlight-next-line\n", - " builder.add_node(\"node_2\", node_2)\n", - " builder.add_edge(START, \"node_1\")\n", - " builder.add_edge(\"node_1\", \"node_2\")\n", - " graph = builder.compile()\n", - " \n", - " for chunk in graph.stream({\"foo\": \"foo\"}, subgraphs=True):\n", - " print(chunk)\n", - " ```\n", - "\n", - " 1. Transform the state to the subgraph state\n", - " 2. Transform response back to the parent state\n", - "\n", - " ```\n", - " ((), {'node_1': {'foo': 'hi! foo'}})\n", - " (('node_2:9c36dd0f-151a-cb42-cbad-fa2f851f9ab7',), {'subgraph_node_1': {'baz': 'baz'}})\n", - " (('node_2:9c36dd0f-151a-cb42-cbad-fa2f851f9ab7',), {'subgraph_node_2': {'bar': 'hi! foobaz'}})\n", - " ((), {'node_2': {'foo': 'hi! foobaz'}})\n", - " ```\n", - "\n", - "??? example \"Full example: different state schemas (two levels of subgraphs)\"\n", - "\n", - " This is an example with two levels of subgraphs: parent -> child -> grandchild.\n", - "\n", - " ```python\n", - " # Grandchild graph\n", - " from typing_extensions import TypedDict\n", - " from langgraph.graph.state import StateGraph, START, END\n", - " \n", - " class GrandChildState(TypedDict):\n", - " my_grandchild_key: str\n", - " \n", - " def grandchild_1(state: GrandChildState) -> GrandChildState:\n", - " # NOTE: child or parent keys will not be accessible here\n", - " return {\"my_grandchild_key\": state[\"my_grandchild_key\"] + \", how are you\"}\n", - " \n", - " \n", - " grandchild = StateGraph(GrandChildState)\n", - " grandchild.add_node(\"grandchild_1\", grandchild_1)\n", - " \n", - " grandchild.add_edge(START, \"grandchild_1\")\n", - " grandchild.add_edge(\"grandchild_1\", END)\n", - " \n", - " grandchild_graph = grandchild.compile()\n", - " \n", - " # Child graph\n", - " class ChildState(TypedDict):\n", - " my_child_key: str\n", - " \n", - " def call_grandchild_graph(state: ChildState) -> ChildState:\n", - " # NOTE: parent or grandchild keys won't be accessible here\n", - " grandchild_graph_input = {\"my_grandchild_key\": state[\"my_child_key\"]} # (1)!\n", - " # highlight-next-line\n", - " grandchild_graph_output = grandchild_graph.invoke(grandchild_graph_input)\n", - " return {\"my_child_key\": grandchild_graph_output[\"my_grandchild_key\"] + \" today?\"} # (2)!\n", - " \n", - " child = StateGraph(ChildState)\n", - " # highlight-next-line\n", - " child.add_node(\"child_1\", call_grandchild_graph) # (3)!\n", - " child.add_edge(START, \"child_1\")\n", - " child.add_edge(\"child_1\", END)\n", - " child_graph = child.compile()\n", - " \n", - " # Parent graph\n", - " class ParentState(TypedDict):\n", - " my_key: str\n", - " \n", - " def parent_1(state: ParentState) -> ParentState:\n", - " # NOTE: child or grandchild keys won't be accessible here\n", - " return {\"my_key\": \"hi \" + state[\"my_key\"]}\n", - " \n", - " def parent_2(state: ParentState) -> ParentState:\n", - " return {\"my_key\": state[\"my_key\"] + \" bye!\"}\n", - " \n", - " def call_child_graph(state: ParentState) -> ParentState:\n", - " child_graph_input = {\"my_child_key\": state[\"my_key\"]} # (4)!\n", - " # highlight-next-line\n", - " child_graph_output = child_graph.invoke(child_graph_input)\n", - " return {\"my_key\": child_graph_output[\"my_child_key\"]} # (5)!\n", - " \n", - " parent = StateGraph(ParentState)\n", - " parent.add_node(\"parent_1\", parent_1)\n", - " # highlight-next-line\n", - " parent.add_node(\"child\", call_child_graph) # (6)!\n", - " parent.add_node(\"parent_2\", parent_2)\n", - " \n", - " parent.add_edge(START, \"parent_1\")\n", - " parent.add_edge(\"parent_1\", \"child\")\n", - " parent.add_edge(\"child\", \"parent_2\")\n", - " parent.add_edge(\"parent_2\", END)\n", - " \n", - " parent_graph = parent.compile()\n", - " \n", - " for chunk in parent_graph.stream({\"my_key\": \"Bob\"}, subgraphs=True):\n", - " print(chunk)\n", - " ```\n", - "\n", - " 1. We're transforming the state from the child state channels (`my_child_key`) to the child state channels (`my_grandchild_key`)\n", - " 2. We're transforming the state from the grandchild state channels (`my_grandchild_key`) back to the child state channels (`my_child_key`)\n", - " 3. We're passing a function here instead of just compiled graph (`grandchild_graph`)\n", - " 4. We're transforming the state from the parent state channels (`my_key`) to the child state channels (`my_child_key`)\n", - " 5. We're transforming the state from the child state channels (`my_child_key`) back to the parent state channels (`my_key`)\n", - " 6. We're passing a function here instead of just a compiled graph (`child_graph`)\n", - "\n", - " ```\n", - " ((), {'parent_1': {'my_key': 'hi Bob'}})\n", - " (('child:2e26e9ce-602f-862c-aa66-1ea5a4655e3b', 'child_1:781bb3b1-3971-84ce-810b-acf819a03f9c'), {'grandchild_1': {'my_grandchild_key': 'hi Bob, how are you'}})\n", - " (('child:2e26e9ce-602f-862c-aa66-1ea5a4655e3b',), {'child_1': {'my_child_key': 'hi Bob, how are you today?'}})\n", - " ((), {'child': {'my_key': 'hi Bob, how are you today?'}})\n", - " ((), {'parent_2': {'my_key': 'hi Bob, how are you today? bye!'}})\n", - " ```" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Add persistence \n", - "\n", - "You only need to **provide the checkpointer when compiling the parent graph**. LangGraph will automatically propagate the checkpointer to the child subgraphs.\n", - "\n", - "```python\n", - "from langgraph.graph import START, StateGraph\n", - "from langgraph.checkpoint.memory import InMemorySaver\n", - "from typing_extensions import TypedDict\n", - "\n", - "class State(TypedDict):\n", - " foo: str\n", - "\n", - "# Subgraph\n", - "\n", - "def subgraph_node_1(state: State):\n", - " return {\"foo\": state[\"foo\"] + \"bar\"}\n", - "\n", - "subgraph_builder = StateGraph(State)\n", - "subgraph_builder.add_node(subgraph_node_1)\n", - "subgraph_builder.add_edge(START, \"subgraph_node_1\")\n", - "# highlight-next-line\n", - "subgraph = subgraph_builder.compile()\n", - "\n", - "# Parent graph\n", - "\n", - "builder = StateGraph(State)\n", - "# highlight-next-line\n", - "builder.add_node(\"node_1\", subgraph)\n", - "builder.add_edge(START, \"node_1\")\n", - "\n", - "checkpointer = InMemorySaver()\n", - "# highlight-next-line\n", - "graph = builder.compile(checkpointer=checkpointer)\n", - "``` \n", - "\n", - "If you want the subgraph to **have its own memory**, you can compile it `with checkpointer=True`. This is useful in [multi-agent](../../concepts/multi_agent) systems, if you want agents to keep track of their internal message histories:\n", - "\n", - "```python\n", - "subgraph_builder = StateGraph(...)\n", - "# highlight-next-line\n", - "subgraph = subgraph_builder.compile(checkpointer=True)\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## View subgraph state\n", - "\n", - "When you enable [persistence](../persistence), you can [inspect the graph state](../persistence#manage-checkpoints) (checkpoint) via `graph.get_state(config)`. To view the subgraph state, you can use `graph.get_state(config, subgraphs=True)`.\n", - "\n", - "!!! important \"Available **only** when interrupted\"\n", - "\n", - " Subgraph state can only be viewed **when the subgraph is interrupted**. Once you resume the graph, you won't be able to access the subgraph state.\n", - "\n", - "??? example \"View interrupted subgraph state\"\n", - "\n", - " ```python\n", - " from langgraph.graph import START, StateGraph\n", - " from langgraph.checkpoint.memory import InMemorySaver\n", - " from langgraph.types import interrupt, Command\n", - " from typing_extensions import TypedDict\n", - " \n", - " class State(TypedDict):\n", - " foo: str\n", - " \n", - " # Subgraph\n", - " \n", - " def subgraph_node_1(state: State):\n", - " # highlight-next-line\n", - " value = interrupt(\"Provide value:\")\n", - " return {\"foo\": state[\"foo\"] + value}\n", - " \n", - " subgraph_builder = StateGraph(State)\n", - " subgraph_builder.add_node(subgraph_node_1)\n", - " subgraph_builder.add_edge(START, \"subgraph_node_1\")\n", - " \n", - " subgraph = subgraph_builder.compile()\n", - " \n", - " # Parent graph\n", - " \n", - " builder = StateGraph(State)\n", - " # highlight-next-line\n", - " builder.add_node(\"node_1\", subgraph)\n", - " builder.add_edge(START, \"node_1\")\n", - " \n", - " checkpointer = InMemorySaver()\n", - " # highlight-next-line\n", - " graph = builder.compile(checkpointer=checkpointer)\n", - " \n", - " config = {\"configurable\": {\"thread_id\": \"1\"}}\n", - " \n", - " graph.invoke({\"foo\": \"\"}, config)\n", - " parent_state = graph.get_state(config)\n", - " # highlight-next-line\n", - " subgraph_state = graph.get_state(config, subgraphs=True).tasks[0].state # (1)!\n", - " \n", - " # resume the subgraph\n", - " graph.invoke(Command(resume=\"bar\"), config)\n", - " ```\n", - " \n", - " 1. This will be available only when the subgraph is interrupted. Once you resume the graph, you won't be able to access the subgraph state." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Stream subgraph outputs\n", - "\n", - "To include outputs from [subgraphs](../concepts/low_level.md#subgraphs) in the streamed outputs, you can set `subgraphs=True` in the `.stream()` method of the parent graph. This will stream outputs from both the parent graph and any subgraphs.\n", - "\n", - "```python\n", - "for chunk in graph.stream(\n", - " {\"foo\": \"foo\"},\n", - " # highlight-next-line\n", - " subgraphs=True, # (1)!\n", - " stream_mode=\"updates\",\n", - "):\n", - " print(chunk)\n", - "```\n", - "\n", - "1. Set `subgraphs=True` to stream outputs from subgraphs.\n", - "\n", - "??? example \"Stream from subgraphs\"\n", - "\n", - " ```python\n", - " from typing_extensions import TypedDict\n", - " from langgraph.graph.state import StateGraph, START\n", - "\n", - " # Define subgraph\n", - " class SubgraphState(TypedDict):\n", - " foo: str\n", - " bar: str\n", - " \n", - " def subgraph_node_1(state: SubgraphState):\n", - " return {\"bar\": \"bar\"}\n", - " \n", - " def subgraph_node_2(state: SubgraphState):\n", - " # note that this node is using a state key ('bar') that is only available in the subgraph\n", - " # and is sending update on the shared state key ('foo')\n", - " return {\"foo\": state[\"foo\"] + state[\"bar\"]}\n", - " \n", - " subgraph_builder = StateGraph(SubgraphState)\n", - " subgraph_builder.add_node(subgraph_node_1)\n", - " subgraph_builder.add_node(subgraph_node_2)\n", - " subgraph_builder.add_edge(START, \"subgraph_node_1\")\n", - " subgraph_builder.add_edge(\"subgraph_node_1\", \"subgraph_node_2\")\n", - " subgraph = subgraph_builder.compile()\n", - " \n", - " # Define parent graph\n", - " class ParentState(TypedDict):\n", - " foo: str\n", - " \n", - " def node_1(state: ParentState):\n", - " return {\"foo\": \"hi! \" + state[\"foo\"]}\n", - " \n", - " builder = StateGraph(ParentState)\n", - " builder.add_node(\"node_1\", node_1)\n", - " # highlight-next-line\n", - " builder.add_node(\"node_2\", subgraph)\n", - " builder.add_edge(START, \"node_1\")\n", - " builder.add_edge(\"node_1\", \"node_2\")\n", - " graph = builder.compile()\n", - "\n", - " for chunk in graph.stream(\n", - " {\"foo\": \"foo\"},\n", - " stream_mode=\"updates\",\n", - " # highlight-next-line\n", - " subgraphs=True, # (1)!\n", - " ):\n", - " print(chunk)\n", - " ```\n", - " \n", - " 1. Set `subgraphs=True` to stream outputs from subgraphs.\n", - "\n", - " ```\n", - " ((), {'node_1': {'foo': 'hi! foo'}})\n", - " (('node_2:e58e5673-a661-ebb0-70d4-e298a7fc28b7',), {'subgraph_node_1': {'bar': 'bar'}})\n", - " (('node_2:e58e5673-a661-ebb0-70d4-e298a7fc28b7',), {'subgraph_node_2': {'foo': 'hi! foobar'}})\n", - " ((), {'node_2': {'foo': 'hi! foobar'}})\n", - " ```" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.3" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/docs/docs/how-tos/subgraph.md b/docs/docs/how-tos/subgraph.md new file mode 100644 index 000000000..9ad820f73 --- /dev/null +++ b/docs/docs/how-tos/subgraph.md @@ -0,0 +1,453 @@ +# Use subgraphs + +This guide explains the mechanics of using [subgraphs](../concepts/subgraphs.md). A common application of subgraphs is to build [multi-agent](../concepts/multi_agent.md) systems. + +When adding subgraphs, you need to define how the parent graph and the subgraph communicate: + +* [Shared state schemas](#shared-state-schemas) — parent and subgraph have **shared state keys** in their state [schemas](../concepts/low_level.md#state) +* [Different state schemas](#different-state-schemas) — **no shared state keys** in parent and subgraph [schemas](../concepts/low_level.md#state) + +## Setup + +```bash +pip install -U langgraph +``` + +!!! tip "Set up LangSmith for LangGraph development" + Sign up for [LangSmith](https://smith.langchain.com) to quickly spot issues and improve the performance of your LangGraph projects. LangSmith lets you use trace data to debug, test, and monitor your LLM apps built with LangGraph — read more about how to get started [here](https://docs.smith.langchain.com). + +## Shared state schemas + +A common case is for the parent graph and subgraph to communicate over a shared state key (channel) in the [schema](../concepts/low_level.md#state). For example, in [multi-agent](../concepts/multi_agent.md) systems, the agents often communicate over a shared [messages](https://langchain-ai.github.io/langgraph/concepts/low_level.md#why-use-messages) key. + +If your subgraph shares state keys with the parent graph, you can follow these steps to add it to your graph: + +1. Define the subgraph workflow (`subgraph_builder` in the example below) and compile it +2. Pass compiled subgraph to the `.add_node` method when defining the parent graph workflow + +```python +from typing_extensions import TypedDict +from langgraph.graph.state import StateGraph, START + +class State(TypedDict): + foo: str + +# Subgraph + +def subgraph_node_1(state: State): + return {"foo": "hi! " + state["foo"]} + +subgraph_builder = StateGraph(State) +subgraph_builder.add_node(subgraph_node_1) +subgraph_builder.add_edge(START, "subgraph_node_1") +subgraph = subgraph_builder.compile() + +# Parent graph + +builder = StateGraph(State) +builder.add_node("node_1", subgraph) +builder.add_edge(START, "node_1") +graph = builder.compile() +``` + +??? example "Full example: shared state schemas" + + ```python + from typing_extensions import TypedDict + from langgraph.graph.state import StateGraph, START + + # Define subgraph + class SubgraphState(TypedDict): + foo: str # (1)! + bar: str # (2)! + + def subgraph_node_1(state: SubgraphState): + return {"bar": "bar"} + + def subgraph_node_2(state: SubgraphState): + # note that this node is using a state key ('bar') that is only available in the subgraph + # and is sending update on the shared state key ('foo') + return {"foo": state["foo"] + state["bar"]} + + subgraph_builder = StateGraph(SubgraphState) + subgraph_builder.add_node(subgraph_node_1) + subgraph_builder.add_node(subgraph_node_2) + subgraph_builder.add_edge(START, "subgraph_node_1") + subgraph_builder.add_edge("subgraph_node_1", "subgraph_node_2") + subgraph = subgraph_builder.compile() + + # Define parent graph + class ParentState(TypedDict): + foo: str + + def node_1(state: ParentState): + return {"foo": "hi! " + state["foo"]} + + builder = StateGraph(ParentState) + builder.add_node("node_1", node_1) + builder.add_node("node_2", subgraph) + builder.add_edge(START, "node_1") + builder.add_edge("node_1", "node_2") + graph = builder.compile() + + for chunk in graph.stream({"foo": "foo"}): + print(chunk) + ``` + + 1. This key is shared with the parent graph state + 2. This key is private to the `SubgraphState` and is not visible to the parent graph + + ``` + {'node_1': {'foo': 'hi! foo'}} + {'node_2': {'foo': 'hi! foobar'}} + ``` + +## Different state schemas + +For more complex systems you might want to define subgraphs that have a **completely different schema** from the parent graph (no shared keys). For example, you might want to keep a private message history for each of the agents in a [multi-agent](../concepts/multi_agent.md) system. + +If that's the case for your application, you need to define a node **function that invokes the subgraph**. This function needs to transform the input (parent) state to the subgraph state before invoking the subgraph, and transform the results back to the parent state before returning the state update from the node. + +```python +from typing_extensions import TypedDict +from langgraph.graph.state import StateGraph, START + +class SubgraphState(TypedDict): + bar: str + +# Subgraph + +def subgraph_node_1(state: SubgraphState): + return {"bar": "hi! " + state["bar"]} + +subgraph_builder = StateGraph(SubgraphState) +subgraph_builder.add_node(subgraph_node_1) +subgraph_builder.add_edge(START, "subgraph_node_1") +subgraph = subgraph_builder.compile() + +# Parent graph + +class State(TypedDict): + foo: str + +def call_subgraph(state: State): + subgraph_output = subgraph.invoke({"bar": state["foo"]}) # (1)! + return {"foo": subgraph_output["bar"]} # (2)! + +builder = StateGraph(State) +builder.add_node("node_1", call_subgraph) +builder.add_edge(START, "node_1") +graph = builder.compile() +``` + +1. Transform the state to the subgraph state +2. Transform response back to the parent state + +??? example "Full example: different state schemas" + + ```python + from typing_extensions import TypedDict + from langgraph.graph.state import StateGraph, START + + # Define subgraph + class SubgraphState(TypedDict): + # note that none of these keys are shared with the parent graph state + bar: str + baz: str + + def subgraph_node_1(state: SubgraphState): + return {"baz": "baz"} + + def subgraph_node_2(state: SubgraphState): + return {"bar": state["bar"] + state["baz"]} + + subgraph_builder = StateGraph(SubgraphState) + subgraph_builder.add_node(subgraph_node_1) + subgraph_builder.add_node(subgraph_node_2) + subgraph_builder.add_edge(START, "subgraph_node_1") + subgraph_builder.add_edge("subgraph_node_1", "subgraph_node_2") + subgraph = subgraph_builder.compile() + + # Define parent graph + class ParentState(TypedDict): + foo: str + + def node_1(state: ParentState): + return {"foo": "hi! " + state["foo"]} + + def node_2(state: ParentState): + response = subgraph.invoke({"bar": state["foo"]}) # (1)! + return {"foo": response["bar"]} # (2)! + + + builder = StateGraph(ParentState) + builder.add_node("node_1", node_1) + builder.add_node("node_2", node_2) + builder.add_edge(START, "node_1") + builder.add_edge("node_1", "node_2") + graph = builder.compile() + + for chunk in graph.stream({"foo": "foo"}, subgraphs=True): + print(chunk) + ``` + + 1. Transform the state to the subgraph state + 2. Transform response back to the parent state + + ``` + ((), {'node_1': {'foo': 'hi! foo'}}) + (('node_2:9c36dd0f-151a-cb42-cbad-fa2f851f9ab7',), {'grandchild_1': {'my_grandchild_key': 'hi Bob, how are you'}}) + (('node_2:9c36dd0f-151a-cb42-cbad-fa2f851f9ab7',), {'grandchild_2': {'bar': 'hi! foobaz'}}) + ((), {'node_2': {'foo': 'hi! foobaz'}}) + ``` + +??? example "Full example: different state schemas (two levels of subgraphs)" + + This is an example with two levels of subgraphs: parent -> child -> grandchild. + + ```python + # Grandchild graph + from typing_extensions import TypedDict + from langgraph.graph.state import StateGraph, START, END + + class GrandChildState(TypedDict): + my_grandchild_key: str + + def grandchild_1(state: GrandChildState) -> GrandChildState: + # NOTE: child or parent keys will not be accessible here + return {"my_grandchild_key": state["my_grandchild_key"] + ", how are you"} + + + grandchild = StateGraph(GrandChildState) + grandchild.add_node("grandchild_1", grandchild_1) + + grandchild.add_edge(START, "grandchild_1") + grandchild.add_edge("grandchild_1", END) + + grandchild_graph = grandchild.compile() + + # Child graph + class ChildState(TypedDict): + my_child_key: str + + def call_grandchild_graph(state: ChildState) -> ChildState: + # NOTE: parent or grandchild keys won't be accessible here + grandchild_graph_input = {"my_grandchild_key": state["my_child_key"]} # (1)! + grandchild_graph_output = grandchild_graph.invoke(grandchild_graph_input) + return {"my_child_key": grandchild_graph_output["my_grandchild_key"] + " today?"} # (2)! + + child = StateGraph(ChildState) + child.add_node("child_1", call_grandchild_graph) # (3)! + child.add_edge(START, "child_1") + child.add_edge("child_1", END) + child_graph = child.compile() + + # Parent graph + class ParentState(TypedDict): + my_key: str + + def parent_1(state: ParentState) -> ParentState: + # NOTE: child or grandchild keys won't be accessible here + return {"my_key": "hi " + state["my_key"]} + + def parent_2(state: ParentState) -> ParentState: + return {"my_key": state["my_key"] + " bye!"} + + def call_child_graph(state: ParentState) -> ParentState: + child_graph_input = {"my_child_key": state["my_key"]} # (4)! + child_graph_output = child_graph.invoke(child_graph_input) + return {"my_key": child_graph_output["my_child_key"]} # (5)! + + parent = StateGraph(ParentState) + parent.add_node("parent_1", parent_1) + parent.add_node("child", call_child_graph) # (6)! + parent.add_node("parent_2", parent_2) + + parent.add_edge(START, "parent_1") + parent.add_edge("parent_1", "child") + parent.add_edge("child", "parent_2") + parent.add_edge("parent_2", END) + + parent_graph = parent.compile() + + for chunk in parent_graph.stream({"my_key": "Bob"}, subgraphs=True): + print(chunk) + ``` + + 1. We're transforming the state from the child state channels (`my_child_key`) to the child state channels (`my_grandchild_key`) + 2. We're transforming the state from the grandchild state channels (`my_grandchild_key`) back to the child state channels (`my_child_key`) + 3. We're passing a function here instead of just compiled graph (`grandchild_graph`) + 4. We're transforming the state from the parent state channels (`my_key`) to the child state channels (`my_child_key`) + 5. We're transforming the state from the child state channels (`my_child_key`) back to the parent state channels (`my_key`) + 6. We're passing a function here instead of just a compiled graph (`child_graph`) + + ``` + ((), {'parent_1': {'my_key': 'hi Bob'}}) + (('child:2e26e9ce-602f-862c-aa66-1ea5a4655e3b', 'child_1:781bb3b1-3971-84ce-810b-acf819a03f9c'), {'grandchild_1': {'my_grandchild_key': 'hi Bob, how are you'}}) + (('child:2e26e9ce-602f-862c-aa66-1ea5a4655e3b',), {'child_1': {'my_child_key': 'hi Bob, how are you today?'}}) + ((), {'child': {'my_key': 'hi Bob, how are you today?'}}) + ((), {'parent_2': {'my_key': 'hi Bob, how are you today? bye!'}}) + ``` + +## Add persistence + +You only need to **provide the checkpointer when compiling the parent graph**. LangGraph will automatically propagate the checkpointer to the child subgraphs. + +```python +from langgraph.graph import START, StateGraph +from langgraph.checkpoint.memory import InMemorySaver +from typing_extensions import TypedDict + +class State(TypedDict): + foo: str + +# Subgraph + +def subgraph_node_1(state: State): + return {"foo": state["foo"] + "bar"} + +subgraph_builder = StateGraph(State) +subgraph_builder.add_node(subgraph_node_1) +subgraph_builder.add_edge(START, "subgraph_node_1") +subgraph = subgraph_builder.compile() + +# Parent graph + +builder = StateGraph(State) +builder.add_node("node_1", subgraph) +builder.add_edge(START, "node_1") + +checkpointer = InMemorySaver() +graph = builder.compile(checkpointer=checkpointer) +``` + +If you want the subgraph to **have its own memory**, you can compile it `with checkpointer=True`. This is useful in [multi-agent](../concepts/multi_agent.md) systems, if you want agents to keep track of their internal message histories: + +```python +subgraph_builder = StateGraph(...) +subgraph = subgraph_builder.compile(checkpointer=True) +``` + +## View subgraph state + +When you enable [persistence](../concepts/persistence.md), you can [inspect the graph state](../concepts/persistence.md#checkpoints) (checkpoint) via `graph.get_state(config)`. To view the subgraph state, you can use `graph.get_state(config, subgraphs=True)`. + +!!! important "Available **only** when interrupted" + + Subgraph state can only be viewed **when the subgraph is interrupted**. Once you resume the graph, you won't be able to access the subgraph state. + +??? example "View interrupted subgraph state" + + ```python + from langgraph.graph import START, StateGraph + from langgraph.checkpoint.memory import InMemorySaver + from langgraph.types import interrupt, Command + from typing_extensions import TypedDict + + class State(TypedDict): + foo: str + + # Subgraph + + def subgraph_node_1(state: State): + value = interrupt("Provide value:") + return {"foo": state["foo"] + value} + + subgraph_builder = StateGraph(State) + subgraph_builder.add_node(subgraph_node_1) + subgraph_builder.add_edge(START, "subgraph_node_1") + + subgraph = subgraph_builder.compile() + + # Parent graph + + builder = StateGraph(State) + builder.add_node("node_1", subgraph) + builder.add_edge(START, "node_1") + + checkpointer = InMemorySaver() + graph = builder.compile(checkpointer=checkpointer) + + config = {"configurable": {"thread_id": "1"}} + + graph.invoke({"foo": ""}, config) + parent_state = graph.get_state(config) + subgraph_state = graph.get_state(config, subgraphs=True).tasks[0].state # (1)! + + # resume the subgraph + graph.invoke(Command(resume="bar"), config) + ``` + + 1. This will be available only when the subgraph is interrupted. Once you resume the graph, you won't be able to access the subgraph state. + +## Stream subgraph outputs + +To include outputs from subgraphs in the streamed outputs, you can set `subgraphs=True` in the `.stream()` method of the parent graph. This will stream outputs from both the parent graph and any subgraphs. + +```python +for chunk in graph.stream( + {"foo": "foo"}, + subgraphs=True, # (1)! + stream_mode="updates", +): + print(chunk) +``` + +1. Set `subgraphs=True` to stream outputs from subgraphs. + +??? example "Stream from subgraphs" + + ```python + from typing_extensions import TypedDict + from langgraph.graph.state import StateGraph, START + + # Define subgraph + class SubgraphState(TypedDict): + foo: str + bar: str + + def subgraph_node_1(state: SubgraphState): + return {"bar": "bar"} + + def subgraph_node_2(state: SubgraphState): + # note that this node is using a state key ('bar') that is only available in the subgraph + # and is sending update on the shared state key ('foo') + return {"foo": state["foo"] + state["bar"]} + + subgraph_builder = StateGraph(SubgraphState) + subgraph_builder.add_node(subgraph_node_1) + subgraph_builder.add_node(subgraph_node_2) + subgraph_builder.add_edge(START, "subgraph_node_1") + subgraph_builder.add_edge("subgraph_node_1", "subgraph_node_2") + subgraph = subgraph_builder.compile() + + # Define parent graph + class ParentState(TypedDict): + foo: str + + def node_1(state: ParentState): + return {"foo": "hi! " + state["foo"]} + + builder = StateGraph(ParentState) + builder.add_node("node_1", node_1) + builder.add_node("node_2", subgraph) + builder.add_edge(START, "node_1") + builder.add_edge("node_1", "node_2") + graph = builder.compile() + + for chunk in graph.stream( + {"foo": "foo"}, + stream_mode="updates", + subgraphs=True, # (1)! + ): + print(chunk) + ``` + + 1. Set `subgraphs=True` to stream outputs from subgraphs. + + ``` + ((), {'node_1': {'foo': 'hi! foo'}}) + (('node_2:e58e5673-a661-ebb0-70d4-e298a7fc28b7',), {'subgraph_node_1': {'bar': 'bar'}}) + (('node_2:e58e5673-a661-ebb0-70d4-e298a7fc28b7',), {'subgraph_node_2': {'foo': 'hi! foobar'}}) + ((), {'node_2': {'foo': 'hi! foobar'}}) + \ No newline at end of file diff --git a/docs/mkdocs.yml b/docs/mkdocs.yml index 34a352fb0..7cfbb246f 100644 --- a/docs/mkdocs.yml +++ b/docs/mkdocs.yml @@ -112,7 +112,7 @@ nav: - LangGraph APIs: - Graph API: - Overview: concepts/low_level.md - - Use the Graph API: how-tos/graph-api.ipynb + - Use the Graph API: how-tos/graph-api.md - Functional API: - Overview: concepts/functional_api.md - Use the Functional API: how-tos/use-functional-api.md @@ -150,12 +150,13 @@ nav: - Use Server API: cloud/how-tos/human_in_the_loop_time_travel.md - Subgraphs: - Overview: concepts/subgraphs.md - - Use subgraphs: how-tos/subgraph.ipynb + - Use subgraphs: how-tos/subgraph.md - Multi-agent: - Overview: concepts/multi_agent.md - Prebuilt implementation: agents/multi-agent.md - - Custom implementation: how-tos/multi_agent.ipynb + - Custom implementation: how-tos/multi_agent.md - MCP: + - Overview: concepts/mcp.md - Use MCP: agents/mcp.md - Server API: concepts/server-mcp.md - Evaluation: @@ -259,9 +260,10 @@ nav: - MCP Adapters: reference/mcp.md - LangGraph Platform: - Server API: cloud/reference/api/api_ref.md + - Control Plane API: cloud/reference/api/api_ref_control_plane.md - CLI: cloud/reference/cli.md - SDK (Python): cloud/reference/sdk/python_sdk_ref.md - - SDK (JS/TS): cloud/reference/sdk/js_ts_sdk_ref.md + - SDK (JS/TS): https://langchain-ai.github.io/langgraphjs/reference/modules/sdk.html - RemoteGraph: reference/remote_graph.md - Environment variables: cloud/reference/env_var.md diff --git a/docs/uv.lock b/docs/uv.lock index 304d238f0..0f4527769 100644 --- a/docs/uv.lock +++ b/docs/uv.lock @@ -2448,7 +2448,7 @@ wheels = [ [[package]] name = "langchain-core" -version = "0.3.60" +version = "0.3.67" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "jsonpatch" }, @@ -2459,9 +2459,9 @@ dependencies = [ { name = "tenacity" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/5b/75/95129aaada92980a002a31e002610a80af3c8967ae7884710372e89cdde0/langchain_core-0.3.60.tar.gz", hash = "sha256:63dd1bdf7939816115399522661ca85a2f3686a61440f2f46ebd86d1b028595b", size = 557456, upload-time = "2025-05-15T15:23:23.642Z" } +sdist = { url = "https://files.pythonhosted.org/packages/c2/40/875af0194024d0006874f061958fa417d3500bbfdc9a57e1bd1c2f4e6ed2/langchain_core-0.3.67.tar.gz", hash = "sha256:2c14aa44a0e78e014e96d7f2f8916ac109d0a0ba87ed67ee25bf7296bed7e7ba", size = 561952, upload-time = "2025-06-30T17:09:35.142Z" } wheels = [ - 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{ name = "langchain-core", specifier = ">=0.3.22" }, + { name = "langchain-core", specifier = ">=0.3.67" }, { name = "langgraph-checkpoint", editable = "../libs/checkpoint" }, ] @@ -2989,7 +2989,7 @@ wheels = [ [[package]] name = "langsmith" -version = "0.3.42" +version = "0.3.45" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "httpx" }, @@ -3000,9 +3000,9 @@ dependencies = [ { name = "requests-toolbelt" }, { name = "zstandard" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/3a/44/fe171c0b0fb0377b191aebf0b7779e0c7b2a53693c6a01ddad737212495d/langsmith-0.3.42.tar.gz", hash = "sha256:2b5cbc450ab808b992362aac6943bb1d285579aa68a3a8be901d30a393458f25", size = 345619, upload-time = "2025-05-03T03:07:17.873Z" } +sdist = { url = "https://files.pythonhosted.org/packages/be/86/b941012013260f95af2e90a3d9415af4a76a003a28412033fc4b09f35731/langsmith-0.3.45.tar.gz", hash = "sha256:1df3c6820c73ed210b2c7bc5cdb7bfa19ddc9126cd03fdf0da54e2e171e6094d", size = 348201, upload-time = "2025-06-05T05:10:28.948Z" } wheels = [ - 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-Copyright (c) 2024 LangChain, Inc. - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. diff --git a/libs/sdk-js/README.md b/libs/sdk-js/README.md index fb47ef3cb..c12e9310e 100644 --- a/libs/sdk-js/README.md +++ b/libs/sdk-js/README.md @@ -1,64 +1 @@ -# LangGraph JS/TS SDK - -This repository contains the JS/TS SDK for interacting with the LangGraph REST API. - -## Quick Start - -To get started with the JS/TS SDK, [install the package](https://www.npmjs.com/package/@langchain/langgraph-sdk) - -```bash -yarn add @langchain/langgraph-sdk -``` - -You will need a running LangGraph API server. If you're running a server locally using `langgraph-cli`, SDK will automatically point at `http://localhost:8123`, otherwise -you would need to specify the server URL when creating a client. - -```js -import { Client } from "@langchain/langgraph-sdk"; - -const client = new Client(); - -// List all assistants -const assistants = await client.assistants.search({ - metadata: null, - offset: 0, - limit: 10, -}); - -// We auto-create an assistant for each graph you register in config. -const agent = assistants[0]; - -// Start a new thread -const thread = await client.threads.create(); - -// Start a streaming run -const messages = [{ role: "human", content: "what's the weather in la" }]; - -const streamResponse = client.runs.stream( - thread["thread_id"], - agent["assistant_id"], - { - input: { messages }, - } -); - -for await (const chunk of streamResponse) { - console.log(chunk); -} -``` - -## Documentation - -To generate documentation, run the following commands: - -1. Generate docs. - - yarn typedoc - -1. Consolidate doc files into one markdown file. - - npx concat-md --decrease-title-levels --ignore=js_ts_sdk_ref.md --start-title-level-at 2 docs > docs/js_ts_sdk_ref.md - -1. Copy `js_ts_sdk_ref.md` to MkDocs directory. - - cp docs/js_ts_sdk_ref.md ../../docs/docs/cloud/reference/sdk/js_ts_sdk_ref.md +This repository has been moved to [langchain-ai/langgraphjs](https://github.com/langchain-ai/langgraphjs/tree/main/libs/sdk). \ No newline at end of file diff --git a/libs/sdk-js/jest.config.js b/libs/sdk-js/jest.config.js deleted file mode 100644 index 10218cfab..000000000 --- a/libs/sdk-js/jest.config.js +++ /dev/null @@ -1,17 +0,0 @@ -/** @type {import('jest').Config} */ -export default { - preset: 'ts-jest', - testEnvironment: 'node', - extensionsToTreatAsEsm: ['.ts'], - moduleNameMapper: { - '^(\\.{1,2}/.*)\\.js$': '$1', - }, - transform: { - '^.+\\.tsx?$': [ - 'ts-jest', - { - useESM: true, - }, - ], - }, -}; diff --git a/libs/sdk-js/langchain.config.js b/libs/sdk-js/langchain.config.js deleted file mode 100644 index 0c8a691cd..000000000 --- a/libs/sdk-js/langchain.config.js +++ /dev/null @@ -1,27 +0,0 @@ -import { resolve, dirname } from "node:path"; -import { fileURLToPath } from "node:url"; - -/** - * @param {string} relativePath - * @returns {string} - */ -function abs(relativePath) { - return resolve(dirname(fileURLToPath(import.meta.url)), relativePath); -} - -export const config = { - internals: [/react/], - entrypoints: { - index: "index", - client: "client", - auth: "auth/index", - react: "react/index", - "react-ui": "react-ui/index", - "react-ui/server": "react-ui/server/index", - }, - tsConfigPath: resolve("./tsconfig.json"), - cjsSource: "./dist-cjs", - cjsDestination: "./dist", - additionalGitignorePaths: ["docs"], - abs, -}; diff --git a/libs/sdk-js/package.json b/libs/sdk-js/package.json deleted file mode 100644 index bc2b2fa5d..000000000 --- a/libs/sdk-js/package.json +++ /dev/null @@ -1,147 +0,0 @@ -{ - "name": "@langchain/langgraph-sdk", - "version": "0.0.89", - "description": "Client library for interacting with the LangGraph API", - "type": "module", - "packageManager": "yarn@1.22.19", - "scripts": { - "clean": "rm -rf dist/ dist-cjs/", - "build": "yarn clean && yarn lc_build --create-entrypoints --pre --tree-shaking", - "prepack": "yarn run build", - "format": "prettier --write src", - "lint": "prettier --check src && tsc --noEmit", - "test": "vitest", - "typedoc": "typedoc && typedoc src/react/index.ts --out docs/react --options typedoc.react.json && typedoc src/auth/index.ts --out docs/auth --options typedoc.auth.json" - }, - "main": "index.js", - "license": "MIT", - "dependencies": { - "@types/json-schema": "^7.0.15", - "p-queue": "^6.6.2", - "p-retry": "4", - "uuid": "^9.0.0" - }, - "devDependencies": { - "@langchain/langgraph-api": "~0.0.41", - "@langchain/core": "^0.3.61", - "@langchain/langgraph": "^0.3.5", - "@langchain/scripts": "^0.1.4", - "@testing-library/dom": "^10.4.0", - "@testing-library/jest-dom": "^6.6.3", - "@testing-library/react": "^16.3.0", - "@testing-library/user-event": "^14.6.1", - "@tsconfig/recommended": "^1.0.2", - "@types/node": "^20.12.12", - "@types/react": "^19.0.8", - "@types/react-dom": "^19.0.3", - "@types/uuid": "^9.0.1", - "@vitejs/plugin-react": "^4.4.1", - "concat-md": "^0.5.1", - "hono": "^4.8.2", - "jsdom": "^26.1.0", - "msw": "^2.8.2", - "prettier": "^3.2.5", - "react": "^19.0.0", - "react-dom": "^19.0.0", - "typedoc": "^0.27.7", - "typedoc-plugin-markdown": "^4.4.2", - "typescript": "^5.4.5", - "vitest": "^3.1.3" - }, - "peerDependencies": { - "@langchain/core": ">=0.2.31 <0.4.0", - "react": "^18 || ^19" - }, - "peerDependenciesMeta": { - "react": { - "optional": true - }, - "@langchain/core": { - "optional": true - } - }, - "exports": { - ".": { - "types": { - "import": "./index.d.ts", - "require": "./index.d.cts", - "default": "./index.d.ts" - }, - "import": "./index.js", - "require": "./index.cjs" - }, - "./client": { - "types": { - "import": "./client.d.ts", - "require": "./client.d.cts", - "default": "./client.d.ts" - }, - "import": "./client.js", - "require": "./client.cjs" - }, - "./auth": { - "types": { - "import": "./auth.d.ts", - "require": "./auth.d.cts", - "default": "./auth.d.ts" - }, - "import": "./auth.js", - "require": "./auth.cjs" - }, - "./react": { - "types": { - "import": "./react.d.ts", - "require": "./react.d.cts", - "default": "./react.d.ts" - }, - "import": "./react.js", - "require": "./react.cjs" - }, - "./react-ui": { - "types": { - "import": "./react-ui.d.ts", - "require": "./react-ui.d.cts", - "default": "./react-ui.d.ts" - }, - "import": "./react-ui.js", - "require": "./react-ui.cjs" - }, - "./react-ui/server": { - "types": { - "import": "./react-ui/server.d.ts", - "require": "./react-ui/server.d.cts", - "default": "./react-ui/server.d.ts" - }, - "import": "./react-ui/server.js", - "require": "./react-ui/server.cjs" - }, - "./package.json": "./package.json" - }, - "files": [ - "dist/", - "index.cjs", - "index.js", - "index.d.ts", - "index.d.cts", - "client.cjs", - "client.js", - "client.d.ts", - "client.d.cts", - "auth.cjs", - "auth.js", - "auth.d.ts", - "auth.d.cts", - "react.cjs", - "react.js", - "react.d.ts", - "react.d.cts", - "react-ui.cjs", - "react-ui.js", - "react-ui.d.ts", - "react-ui.d.cts", - "react-ui/server.cjs", - "react-ui/server.js", - "react-ui/server.d.ts", - "react-ui/server.d.cts" - ] -} diff --git a/libs/sdk-js/src/auth/error.ts b/libs/sdk-js/src/auth/error.ts deleted file mode 100644 index ace6df54c..000000000 --- a/libs/sdk-js/src/auth/error.ts +++ /dev/null @@ -1,80 +0,0 @@ -const HTTP_STATUS_MAPPING: { [key: number]: string } = { - 100: "Continue", - 101: "Switching Protocols", - 102: "Processing", - 103: "Early Hints", - 200: "OK", - 201: "Created", - 202: "Accepted", - 203: "Non-Authoritative Information", - 204: "No Content", - 205: "Reset Content", - 206: "Partial Content", - 207: "Multi-Status", - 208: "Already Reported", - 226: "IM Used", - 300: "Multiple Choices", - 301: "Moved Permanently", - 302: "Found", - 303: "See Other", - 304: "Not Modified", - 305: "Use Proxy", - 307: "Temporary Redirect", - 308: "Permanent Redirect", - 400: "Bad Request", - 401: "Unauthorized", - 402: "Payment Required", - 403: "Forbidden", - 404: "Not Found", - 405: "Method Not Allowed", - 406: "Not Acceptable", - 407: "Proxy Authentication Required", - 408: "Request Timeout", - 409: "Conflict", - 410: "Gone", - 411: "Length Required", - 412: "Precondition Failed", - 413: "Request Entity Too Large", - 414: "Request-URI Too Long", - 415: "Unsupported Media Type", - 416: "Requested Range Not Satisfiable", - 417: "Expectation Failed", - 418: "I'm a Teapot", - 421: "Misdirected Request", - 422: "Unprocessable Entity", - 423: "Locked", - 424: "Failed Dependency", - 425: "Too Early", - 426: "Upgrade Required", - 428: "Precondition Required", - 429: "Too Many Requests", - 431: "Request Header Fields Too Large", - 451: "Unavailable For Legal Reasons", - 500: "Internal Server Error", - 501: "Not Implemented", - 502: "Bad Gateway", - 503: "Service Unavailable", - 504: "Gateway Timeout", - 505: "HTTP Version Not Supported", - 506: "Variant Also Negotiates", - 507: "Insufficient Storage", - 508: "Loop Detected", - 510: "Not Extended", - 511: "Network Authentication Required", -}; - -export class HTTPException extends Error { - status: number; - headers: HeadersInit; - - constructor( - status: number, - options?: { message?: string; headers?: HeadersInit; cause?: unknown }, - ) { - super(options?.message ?? HTTP_STATUS_MAPPING[status] ?? "Unknown error", { - cause: options?.cause, - }); - this.status = status; - this.headers = options?.headers ?? {}; - } -} diff --git a/libs/sdk-js/src/auth/index.ts b/libs/sdk-js/src/auth/index.ts deleted file mode 100644 index c7b1ffb1f..000000000 --- a/libs/sdk-js/src/auth/index.ts +++ /dev/null @@ -1,46 +0,0 @@ -import type { - AuthenticateCallback, - AnyCallback, - CallbackEvent, - OnCallback, - BaseAuthReturn, - ToUserLike, - BaseUser, -} from "./types.js"; - -export class Auth< - TExtra = {}, - TAuthReturn extends BaseAuthReturn = BaseAuthReturn, - TUser extends BaseUser = ToUserLike, -> { - /** - * @internal - * @ignore - */ - "~handlerCache": { - authenticate?: AuthenticateCallback; - callbacks?: Record; - } = {}; - - authenticate( - cb: AuthenticateCallback, - ): Auth { - this["~handlerCache"].authenticate = cb; - return this as unknown as Auth; - } - - on(event: T, callback: OnCallback): this { - this["~handlerCache"].callbacks ??= {}; - const events: string[] = Array.isArray(event) ? event : [event]; - for (const event of events) { - this["~handlerCache"].callbacks[event] = callback as AnyCallback; - } - return this; - } -} - -export type { - Filters as AuthFilters, - EventValueMap as AuthEventValueMap, -} from "./types.js"; -export { HTTPException } from "./error.js"; diff --git a/libs/sdk-js/src/auth/types.ts b/libs/sdk-js/src/auth/types.ts deleted file mode 100644 index cc12c4e5b..000000000 --- a/libs/sdk-js/src/auth/types.ts +++ /dev/null @@ -1,411 +0,0 @@ -type Maybe = T | null | undefined; -type PromiseMaybe = Promise | T; - -interface AssistantConfig { - tags?: Maybe; - recursion_limit?: Maybe; - configurable?: Maybe<{ - thread_id?: Maybe; - thread_ts?: Maybe; - [key: string]: unknown; - }>; -} - -/** - * @inline - */ -interface AssistantCreate { - assistant_id?: Maybe; - metadata?: Maybe>; - config?: Maybe; - if_exists?: Maybe<"raise" | "do_nothing">; - name?: Maybe; - graph_id: string; -} - -/** - * @inline - */ -interface AssistantRead { - assistant_id: string; - metadata?: Maybe>; -} - -/** - * @inline - */ -interface AssistantUpdate { - assistant_id: string; - metadata?: Maybe>; - config?: Maybe; - graph_id?: Maybe; - name?: Maybe; - version?: Maybe; -} - -/** - * @inline - */ -interface AssistantDelete { - assistant_id: string; -} - -/** - * @inline - */ -interface AssistantSearch { - graph_id?: Maybe; - metadata?: Maybe>; - limit?: Maybe; - offset?: Maybe; -} - -/** - * @inline - */ -interface ThreadCreate { - thread_id?: Maybe; - metadata?: Maybe>; - if_exists?: Maybe<"raise" | "do_nothing">; -} - -/** - * @inline - */ -interface ThreadRead { - thread_id?: Maybe; -} - -/** - * @inline - */ -interface ThreadUpdate { - thread_id?: Maybe; - metadata?: Maybe>; - action?: Maybe<"interrupt" | "rollback">; -} - -/** - * @inline - */ -interface ThreadDelete { - thread_id?: Maybe; - run_id?: Maybe; -} - -/** - * @inline - */ -interface ThreadSearch { - thread_id?: Maybe; - status?: Maybe<"idle" | "busy" | "interrupted" | "error" | (string & {})>; - metadata?: Maybe>; - values?: Maybe>; - limit?: Maybe; - offset?: Maybe; -} - -/** - * @inline - */ -interface CronCreate { - payload?: Maybe>; - schedule: string; - cron_id?: Maybe; - thread_id?: Maybe; - user_id?: Maybe; - end_time?: Maybe; -} - -/** - * @inline - */ -interface CronRead { - cron_id: string; -} - -/** - * @inline - */ -interface CronUpdate { - cron_id: string; - payload?: Maybe>; - schedule?: Maybe; -} - -/** - * @inline - */ -interface CronDelete { - cron_id: string; -} - -/** - * @inline - */ -interface CronSearch { - assistant_id?: Maybe; - thread_id?: Maybe; - limit?: Maybe; - offset?: Maybe; -} - -/** - * @inline - */ -interface StorePut { - namespace: string[]; - key: string; - value: Record; -} - -/** - * @inline - */ -interface StoreGet { - namespace: Maybe; - key: string; -} - -/** - * @inline - */ -interface StoreSearch { - namespace?: Maybe; - filter?: Maybe>; - limit?: Maybe; - offset?: Maybe; - query?: Maybe; -} - -/** - * @inline - */ -interface StoreListNamespaces { - namespace?: Maybe; - suffix?: Maybe; - max_depth?: Maybe; - limit?: Maybe; - offset?: Maybe; -} - -/** - * @inline - */ -interface StoreDelete { - namespace?: Maybe; - key: string; -} - -/** - * @inline - */ -interface RunsCreate { - thread_id?: Maybe; - assistant_id: string; - run_id: string; - status: Maybe< - "pending" | "running" | "error" | "success" | "timeout" | "interrupted" - >; - metadata?: Maybe>; - prevent_insert_if_inflight?: Maybe; - multitask_strategy?: Maybe<"interrupt" | "rollback" | "reject" | "enqueue">; - if_not_exists?: Maybe<"reject" | "create">; - after_seconds?: Maybe; - kwargs: Record; -} - -export interface EventValueMap { - ["threads:create"]: ThreadCreate; - ["threads:read"]: ThreadRead; - ["threads:update"]: ThreadUpdate; - ["threads:delete"]: ThreadDelete; - ["threads:search"]: ThreadSearch; - ["threads:create_run"]: RunsCreate; - - ["assistants:create"]: AssistantCreate; - ["assistants:read"]: AssistantRead; - ["assistants:update"]: AssistantUpdate; - ["assistants:delete"]: AssistantDelete; - ["assistants:search"]: AssistantSearch; - - ["crons:create"]: CronCreate; - ["crons:read"]: CronRead; - ["crons:update"]: CronUpdate; - ["crons:delete"]: CronDelete; - ["crons:search"]: CronSearch; - - ["store:put"]: StorePut; - ["store:get"]: StoreGet; - ["store:search"]: StoreSearch; - ["store:list_namespaces"]: StoreListNamespaces; - ["store:delete"]: StoreDelete; -} -interface ResourceType { - threads: - | "threads:create" - | "threads:read" - | "threads:update" - | "threads:delete" - | "threads:search" - | "threads:create_run"; - - assistants: - | "assistants:create" - | "assistants:read" - | "assistants:update" - | "assistants:delete" - | "assistants:search"; - crons: - | "crons:create" - | "crons:read" - | "crons:update" - | "crons:delete" - | "crons:search"; - - store: - | "store:put" - | "store:get" - | "store:search" - | "store:list_namespaces" - | "store:delete"; -} -interface ActionType { - "*:create": "threads:create" | "assistants:create" | "crons:create"; - - "*:read": "threads:read" | "assistants:read" | "crons:read"; - - "*:update": "threads:update" | "assistants:update" | "crons:update"; - - "*:delete": - | "threads:delete" - | "assistants:delete" - | "crons:delete" - | "store:delete"; - - "*:search": - | "threads:search" - | "assistants:search" - | "crons:search" - | "store:search"; - - "*:create_run": "threads:create_run"; - - "*:put": "store:put"; - - "*:get": "store:get"; - - "*:list_namespaces": "store:list_namespaces"; -} - -export type BaseAuthReturn = - | { - is_authenticated?: boolean; - display_name?: string; - identity: string; - permissions: string[]; - } - | string; - -export interface BaseUser { - is_authenticated: boolean; - display_name: string; - identity: string; - permissions: string[]; -} - -export type ToUserLike = T extends string - ? { - is_authenticated: boolean; - display_name: string; - identity: string; - permissions: string[]; - } - : Omit & { - is_authenticated: boolean; - display_name: string; - }; - -type CallbackParameter< - Event extends string = string, - Resource extends string = string, - Action extends string = string, - Value extends unknown = unknown, - TUser extends BaseUser = BaseUser, -> = { - event: Event; - resource: Resource; - action: Action; - value: Value; - user: TUser; - permissions: string[]; -}; - -type ContextMap = { - [EventType in keyof EventValueMap]: CallbackParameter< - EventType, - EventType extends `${infer Resource}:${string}` ? Resource : never, - EventType extends `${string}:${infer Action}` ? Action : never, - EventValueMap[EventType], - BaseUser - >; -}; - -type ActionCallbackParameter< - T extends keyof ActionType, - TUser extends BaseUser = BaseUser, -> = ContextMap[ActionType[T]] & { user: TUser }; -type AuthCallbackParameter< - T extends keyof EventValueMap, - TUser extends BaseUser = BaseUser, -> = ContextMap[T] & { user: TUser }; -type ResourceCallbackParameter< - T extends keyof ResourceType, - TUser extends BaseUser = BaseUser, -> = ContextMap[ResourceType[T]] & { user: TUser }; - -export type Filters = { - [key in TKey]: string | { [op in "$contains" | "$eq"]?: string }; -}; - -export interface AuthenticateCallback { - (request: Request): PromiseMaybe; -} - -type OnKey = keyof ResourceType | keyof ActionType | keyof EventValueMap; - -type OnSingleParameter< - T extends OnKey, - TUser extends BaseUser = BaseUser, -> = T extends keyof ResourceType - ? ResourceCallbackParameter - : T extends keyof ActionType - ? ActionCallbackParameter - : T extends keyof EventValueMap - ? AuthCallbackParameter - : never; - -type OnParameter< - T extends "*" | OnKey | OnKey[], - TUser extends BaseUser = BaseUser, -> = T extends OnKey[] - ? OnSingleParameter - : T extends "*" - ? AuthCallbackParameter - : T extends OnKey - ? OnSingleParameter - : never; - -export type AnyCallback = ( - request: CallbackParameter, -) => void | boolean | Filters; - -export type CallbackEvent = "*" | OnKey | OnKey[]; - -export type OnCallback< - T extends CallbackEvent, - TUser extends BaseUser = BaseUser, - TMetadata extends Record = Record, -> = ( - request: OnParameter, -) => void | boolean | Filters; diff --git a/libs/sdk-js/src/client.ts b/libs/sdk-js/src/client.ts deleted file mode 100644 index ae68bc180..000000000 --- a/libs/sdk-js/src/client.ts +++ /dev/null @@ -1,1699 +0,0 @@ -import { - Assistant, - AssistantGraph, - AssistantSortBy, - AssistantVersion, - CancelAction, - Checkpoint, - Config, - Cron, - CronCreateForThreadResponse, - CronCreateResponse, - CronSortBy, - DefaultValues, - GraphSchema, - Item, - ListNamespaceResponse, - Metadata, - Run, - RunStatus, - SearchItemsResponse, - SortOrder, - Subgraphs, - Thread, - ThreadSortBy, - ThreadState, - ThreadStatus, -} from "./schema.js"; -import type { - Command, - CronsCreatePayload, - OnConflictBehavior, - RunsCreatePayload, - RunsStreamPayload, - RunsWaitPayload, - StreamEvent, -} from "./types.js"; -import type { StreamMode, TypedAsyncGenerator } from "./types.stream.js"; -import { AsyncCaller, AsyncCallerParams } from "./utils/async_caller.js"; -import { getEnvironmentVariable } from "./utils/env.js"; -import { mergeSignals } from "./utils/signals.js"; -import { BytesLineDecoder, SSEDecoder } from "./utils/sse.js"; -import { IterableReadableStream } from "./utils/stream.js"; - -type HeaderValue = string | undefined | null; - -function* iterateHeaders( - headers: HeadersInit | Record, -): IterableIterator<[string, string | null]> { - let iter: Iterable<(HeaderValue | HeaderValue | null[])[]>; - let shouldClear = false; - - if (headers instanceof Headers) { - const entries: [string, string][] = []; - headers.forEach((value, name) => { - entries.push([name, value]); - }); - iter = entries; - } else if (Array.isArray(headers)) { - iter = headers; - } else { - shouldClear = true; - iter = Object.entries(headers ?? {}); - } - - for (let item of iter) { - const name = item[0]; - if (typeof name !== "string") - throw new TypeError( - `Expected header name to be a string, got ${typeof name}`, - ); - const values = Array.isArray(item[1]) ? item[1] : [item[1]]; - let didClear = false; - - for (const value of values) { - if (value === undefined) continue; - - // New object keys should always overwrite older headers - // Yield a null to clear the header in the headers object - // before adding the new value - if (shouldClear && !didClear) { - didClear = true; - yield [name, null]; - } - yield [name, value]; - } - } -} - -function mergeHeaders( - ...headerObjects: ( - | HeadersInit - | Record - | undefined - | null - )[] -) { - const outputHeaders = new Headers(); - for (const headers of headerObjects) { - if (!headers) continue; - for (const [name, value] of iterateHeaders(headers)) { - if (value === null) outputHeaders.delete(name); - else outputHeaders.append(name, value); - } - } - const headerEntries: [string, string][] = []; - outputHeaders.forEach((value, name) => { - headerEntries.push([name, value]); - }); - return Object.fromEntries(headerEntries); -} - -/** - * Get the API key from the environment. - * Precedence: - * 1. explicit argument - * 2. LANGGRAPH_API_KEY - * 3. LANGSMITH_API_KEY - * 4. LANGCHAIN_API_KEY - * - * @param apiKey - Optional API key provided as an argument - * @returns The API key if found, otherwise undefined - */ -export function getApiKey(apiKey?: string): string | undefined { - if (apiKey) { - return apiKey; - } - - const prefixes = ["LANGGRAPH", "LANGSMITH", "LANGCHAIN"]; - - for (const prefix of prefixes) { - const envKey = getEnvironmentVariable(`${prefix}_API_KEY`); - if (envKey) { - // Remove surrounding quotes - return envKey.trim().replace(/^["']|["']$/g, ""); - } - } - - return undefined; -} - -const REGEX_RUN_METADATA = - /(\/threads\/(?.+))?\/runs\/(?.+)/; - -function getRunMetadataFromResponse( - response: Response, -): { run_id: string; thread_id?: string } | undefined { - const contentLocation = response.headers.get("Content-Location"); - if (!contentLocation) return undefined; - - const match = REGEX_RUN_METADATA.exec(contentLocation); - - if (!match?.groups?.run_id) return undefined; - return { - run_id: match.groups.run_id, - thread_id: match.groups.thread_id || undefined, - }; -} - -export type RequestHook = ( - url: URL, - init: RequestInit, -) => Promise | RequestInit; - -export interface ClientConfig { - apiUrl?: string; - apiKey?: string; - callerOptions?: AsyncCallerParams; - timeoutMs?: number; - defaultHeaders?: Record; - onRequest?: RequestHook; -} - -class BaseClient { - protected asyncCaller: AsyncCaller; - - protected timeoutMs: number | undefined; - - protected apiUrl: string; - - protected defaultHeaders: Record; - - protected onRequest?: RequestHook; - - constructor(config?: ClientConfig) { - const callerOptions = { - maxRetries: 4, - maxConcurrency: 4, - ...config?.callerOptions, - }; - - let defaultApiUrl = "http://localhost:8123"; - if ( - !config?.apiUrl && - typeof globalThis === "object" && - globalThis != null - ) { - const fetchSmb = Symbol.for("langgraph_api:fetch"); - const urlSmb = Symbol.for("langgraph_api:url"); - - const global = globalThis as unknown as { - [fetchSmb]?: typeof fetch; - [urlSmb]?: string; - }; - - if (global[fetchSmb]) callerOptions.fetch ??= global[fetchSmb]; - if (global[urlSmb]) defaultApiUrl = global[urlSmb]; - } - - this.asyncCaller = new AsyncCaller(callerOptions); - this.timeoutMs = config?.timeoutMs; - - // default limit being capped by Chrome - // https://github.com/nodejs/undici/issues/1373 - // Regex to remove trailing slash, if present - this.apiUrl = config?.apiUrl?.replace(/\/$/, "") || defaultApiUrl; - this.defaultHeaders = config?.defaultHeaders || {}; - this.onRequest = config?.onRequest; - const apiKey = getApiKey(config?.apiKey); - if (apiKey) { - this.defaultHeaders["x-api-key"] = apiKey; - } - } - - protected prepareFetchOptions( - path: string, - options?: RequestInit & { - json?: unknown; - params?: Record; - timeoutMs?: number | null; - withResponse?: boolean; - }, - ): [url: URL, init: RequestInit] { - const mutatedOptions = { - ...options, - headers: mergeHeaders(this.defaultHeaders, options?.headers), - }; - - if (mutatedOptions.json) { - mutatedOptions.body = JSON.stringify(mutatedOptions.json); - mutatedOptions.headers = mergeHeaders(mutatedOptions.headers, { - "content-type": "application/json", - }); - delete mutatedOptions.json; - } - - if (mutatedOptions.withResponse) { - delete mutatedOptions.withResponse; - } - - let timeoutSignal: AbortSignal | null = null; - if (typeof options?.timeoutMs !== "undefined") { - if (options.timeoutMs != null) { - timeoutSignal = AbortSignal.timeout(options.timeoutMs); - } - } else if (this.timeoutMs != null) { - timeoutSignal = AbortSignal.timeout(this.timeoutMs); - } - - mutatedOptions.signal = mergeSignals(timeoutSignal, mutatedOptions.signal); - const targetUrl = new URL(`${this.apiUrl}${path}`); - - if (mutatedOptions.params) { - for (const [key, value] of Object.entries(mutatedOptions.params)) { - if (value == null) continue; - - let strValue = - typeof value === "string" || typeof value === "number" - ? value.toString() - : JSON.stringify(value); - - targetUrl.searchParams.append(key, strValue); - } - delete mutatedOptions.params; - } - - return [targetUrl, mutatedOptions]; - } - - protected async fetch( - path: string, - options: RequestInit & { - json?: unknown; - params?: Record; - timeoutMs?: number | null; - signal?: AbortSignal; - withResponse: true; - }, - ): Promise<[T, Response]>; - - protected async fetch( - path: string, - options?: RequestInit & { - json?: unknown; - params?: Record; - timeoutMs?: number | null; - signal?: AbortSignal; - withResponse?: false; - }, - ): Promise; - - protected async fetch( - path: string, - options?: RequestInit & { - json?: unknown; - params?: Record; - timeoutMs?: number | null; - signal?: AbortSignal; - withResponse?: boolean; - }, - ): Promise { - const [url, init] = this.prepareFetchOptions(path, options); - - let finalInit = init; - if (this.onRequest) { - finalInit = await this.onRequest(url, init); - } - - const response = await this.asyncCaller.fetch(url, finalInit); - - const body = (() => { - if (response.status === 202 || response.status === 204) { - return undefined as T; - } - return response.json() as Promise; - })(); - - if (options?.withResponse) { - return [await body, response]; - } - - return body; - } -} - -export class CronsClient extends BaseClient { - /** - * - * @param threadId The ID of the thread. - * @param assistantId Assistant ID to use for this cron job. - * @param payload Payload for creating a cron job. - * @returns The created background run. - */ - async createForThread( - threadId: string, - assistantId: string, - payload?: CronsCreatePayload, - ): Promise { - const json: Record = { - schedule: payload?.schedule, - input: payload?.input, - config: payload?.config, - metadata: payload?.metadata, - assistant_id: assistantId, - interrupt_before: payload?.interruptBefore, - interrupt_after: payload?.interruptAfter, - webhook: payload?.webhook, - multitask_strategy: payload?.multitaskStrategy, - if_not_exists: payload?.ifNotExists, - checkpoint_during: payload?.checkpointDuring, - }; - return this.fetch( - `/threads/${threadId}/runs/crons`, - { - method: "POST", - json, - }, - ); - } - - /** - * - * @param assistantId Assistant ID to use for this cron job. - * @param payload Payload for creating a cron job. - * @returns - */ - async create( - assistantId: string, - payload?: CronsCreatePayload, - ): Promise { - const json: Record = { - schedule: payload?.schedule, - input: payload?.input, - config: payload?.config, - metadata: payload?.metadata, - assistant_id: assistantId, - interrupt_before: payload?.interruptBefore, - interrupt_after: payload?.interruptAfter, - webhook: payload?.webhook, - multitask_strategy: payload?.multitaskStrategy, - if_not_exists: payload?.ifNotExists, - checkpoint_during: payload?.checkpointDuring, - }; - return this.fetch(`/runs/crons`, { - method: "POST", - json, - }); - } - - /** - * - * @param cronId Cron ID of Cron job to delete. - */ - async delete(cronId: string): Promise { - await this.fetch(`/runs/crons/${cronId}`, { - method: "DELETE", - }); - } - - /** - * - * @param query Query options. - * @returns List of crons. - */ - async search(query?: { - assistantId?: string; - threadId?: string; - limit?: number; - offset?: number; - sortBy?: CronSortBy; - sortOrder?: SortOrder; - }): Promise { - return this.fetch("/runs/crons/search", { - method: "POST", - json: { - assistant_id: query?.assistantId ?? undefined, - thread_id: query?.threadId ?? undefined, - limit: query?.limit ?? 10, - offset: query?.offset ?? 0, - sort_by: query?.sortBy ?? undefined, - sort_order: query?.sortOrder ?? undefined, - }, - }); - } -} - -export class AssistantsClient extends BaseClient { - /** - * Get an assistant by ID. - * - * @param assistantId The ID of the assistant. - * @returns Assistant - */ - async get(assistantId: string): Promise { - return this.fetch(`/assistants/${assistantId}`); - } - - /** - * Get the JSON representation of the graph assigned to a runnable - * @param assistantId The ID of the assistant. - * @param options.xray Whether to include subgraphs in the serialized graph representation. If an integer value is provided, only subgraphs with a depth less than or equal to the value will be included. - * @returns Serialized graph - */ - async getGraph( - assistantId: string, - options?: { xray?: boolean | number }, - ): Promise { - return this.fetch(`/assistants/${assistantId}/graph`, { - params: { xray: options?.xray }, - }); - } - - /** - * Get the state and config schema of the graph assigned to a runnable - * @param assistantId The ID of the assistant. - * @returns Graph schema - */ - async getSchemas(assistantId: string): Promise { - return this.fetch(`/assistants/${assistantId}/schemas`); - } - - /** - * Get the schemas of an assistant by ID. - * - * @param assistantId The ID of the assistant to get the schema of. - * @param options Additional options for getting subgraphs, such as namespace or recursion extraction. - * @returns The subgraphs of the assistant. - */ - async getSubgraphs( - assistantId: string, - options?: { - namespace?: string; - recurse?: boolean; - }, - ): Promise { - if (options?.namespace) { - return this.fetch( - `/assistants/${assistantId}/subgraphs/${options.namespace}`, - { params: { recurse: options?.recurse } }, - ); - } - return this.fetch(`/assistants/${assistantId}/subgraphs`, { - params: { recurse: options?.recurse }, - }); - } - - /** - * Create a new assistant. - * @param payload Payload for creating an assistant. - * @returns The created assistant. - */ - async create(payload: { - graphId: string; - config?: Config; - metadata?: Metadata; - assistantId?: string; - ifExists?: OnConflictBehavior; - name?: string; - description?: string; - }): Promise { - return this.fetch("/assistants", { - method: "POST", - json: { - graph_id: payload.graphId, - config: payload.config, - metadata: payload.metadata, - assistant_id: payload.assistantId, - if_exists: payload.ifExists, - name: payload.name, - description: payload.description, - }, - }); - } - - /** - * Update an assistant. - * @param assistantId ID of the assistant. - * @param payload Payload for updating the assistant. - * @returns The updated assistant. - */ - async update( - assistantId: string, - payload: { - graphId?: string; - config?: Config; - metadata?: Metadata; - name?: string; - description?: string; - }, - ): Promise { - return this.fetch(`/assistants/${assistantId}`, { - method: "PATCH", - json: { - graph_id: payload.graphId, - config: payload.config, - metadata: payload.metadata, - name: payload.name, - description: payload.description, - }, - }); - } - - /** - * Delete an assistant. - * - * @param assistantId ID of the assistant. - */ - async delete(assistantId: string): Promise { - return this.fetch(`/assistants/${assistantId}`, { - method: "DELETE", - }); - } - - /** - * List assistants. - * @param query Query options. - * @returns List of assistants. - */ - async search(query?: { - graphId?: string; - metadata?: Metadata; - limit?: number; - offset?: number; - sortBy?: AssistantSortBy; - sortOrder?: SortOrder; - }): Promise { - return this.fetch("/assistants/search", { - method: "POST", - json: { - graph_id: query?.graphId ?? undefined, - metadata: query?.metadata ?? undefined, - limit: query?.limit ?? 10, - offset: query?.offset ?? 0, - sort_by: query?.sortBy ?? undefined, - sort_order: query?.sortOrder ?? undefined, - }, - }); - } - - /** - * List all versions of an assistant. - * - * @param assistantId ID of the assistant. - * @returns List of assistant versions. - */ - async getVersions( - assistantId: string, - payload?: { - metadata?: Metadata; - limit?: number; - offset?: number; - }, - ): Promise { - return this.fetch( - `/assistants/${assistantId}/versions`, - { - method: "POST", - json: { - metadata: payload?.metadata ?? undefined, - limit: payload?.limit ?? 10, - offset: payload?.offset ?? 0, - }, - }, - ); - } - - /** - * Change the version of an assistant. - * - * @param assistantId ID of the assistant. - * @param version The version to change to. - * @returns The updated assistant. - */ - async setLatest(assistantId: string, version: number): Promise { - return this.fetch(`/assistants/${assistantId}/latest`, { - method: "POST", - json: { version }, - }); - } -} - -export class ThreadsClient< - TStateType = DefaultValues, - TUpdateType = TStateType, -> extends BaseClient { - /** - * Get a thread by ID. - * - * @param threadId ID of the thread. - * @returns The thread. - */ - async get( - threadId: string, - ): Promise> { - return this.fetch>(`/threads/${threadId}`); - } - - /** - * Create a new thread. - * - * @param payload Payload for creating a thread. - * @returns The created thread. - */ - async create(payload?: { - /** - * Metadata for the thread. - */ - metadata?: Metadata; - /** - * ID of the thread to create. - * - * If not provided, a random UUID will be generated. - */ - threadId?: string; - /** - * How to handle duplicate creation. - * - * @default "raise" - */ - ifExists?: OnConflictBehavior; - /** - * Graph ID to associate with the thread. - */ - graphId?: string; - /** - * Apply a list of supersteps when creating a thread, each containing a sequence of updates. - * - * Used for copying a thread between deployments. - */ - supersteps?: Array<{ - updates: Array<{ values: unknown; command?: Command; asNode: string }>; - }>; - }): Promise> { - return this.fetch>(`/threads`, { - method: "POST", - json: { - metadata: { - ...payload?.metadata, - graph_id: payload?.graphId, - }, - thread_id: payload?.threadId, - if_exists: payload?.ifExists, - supersteps: payload?.supersteps?.map((s) => ({ - updates: s.updates.map((u) => ({ - values: u.values, - command: u.command, - as_node: u.asNode, - })), - })), - }, - }); - } - - /** - * Copy an existing thread - * @param threadId ID of the thread to be copied - * @returns Newly copied thread - */ - async copy(threadId: string): Promise> { - return this.fetch>(`/threads/${threadId}/copy`, { - method: "POST", - }); - } - - /** - * Update a thread. - * - * @param threadId ID of the thread. - * @param payload Payload for updating the thread. - * @returns The updated thread. - */ - async update( - threadId: string, - payload?: { - /** - * Metadata for the thread. - */ - metadata?: Metadata; - }, - ): Promise { - return this.fetch(`/threads/${threadId}`, { - method: "PATCH", - json: { metadata: payload?.metadata }, - }); - } - - /** - * Delete a thread. - * - * @param threadId ID of the thread. - */ - async delete(threadId: string): Promise { - return this.fetch(`/threads/${threadId}`, { - method: "DELETE", - }); - } - - /** - * List threads - * - * @param query Query options - * @returns List of threads - */ - async search(query?: { - /** - * Metadata to filter threads by. - */ - metadata?: Metadata; - /** - * Maximum number of threads to return. - * Defaults to 10 - */ - limit?: number; - /** - * Offset to start from. - */ - offset?: number; - /** - * Thread status to filter on. - */ - status?: ThreadStatus; - /** - * Sort by. - */ - sortBy?: ThreadSortBy; - /** - * Sort order. - * Must be one of 'asc' or 'desc'. - */ - sortOrder?: SortOrder; - }): Promise[]> { - return this.fetch[]>("/threads/search", { - method: "POST", - json: { - metadata: query?.metadata ?? undefined, - limit: query?.limit ?? 10, - offset: query?.offset ?? 0, - status: query?.status, - sort_by: query?.sortBy, - sort_order: query?.sortOrder, - }, - }); - } - - /** - * Get state for a thread. - * - * @param threadId ID of the thread. - * @returns Thread state. - */ - async getState( - threadId: string, - checkpoint?: Checkpoint | string, - options?: { subgraphs?: boolean }, - ): Promise> { - if (checkpoint != null) { - if (typeof checkpoint !== "string") { - return this.fetch>( - `/threads/${threadId}/state/checkpoint`, - { - method: "POST", - json: { checkpoint, subgraphs: options?.subgraphs }, - }, - ); - } - - // deprecated - return this.fetch>( - `/threads/${threadId}/state/${checkpoint}`, - { params: { subgraphs: options?.subgraphs } }, - ); - } - - return this.fetch>(`/threads/${threadId}/state`, { - params: { subgraphs: options?.subgraphs }, - }); - } - - /** - * Add state to a thread. - * - * @param threadId The ID of the thread. - * @returns - */ - async updateState( - threadId: string, - options: { - values: ValuesType; - checkpoint?: Checkpoint; - checkpointId?: string; - asNode?: string; - }, - ): Promise> { - return this.fetch>( - `/threads/${threadId}/state`, - { - method: "POST", - json: { - values: options.values, - checkpoint_id: options.checkpointId, - checkpoint: options.checkpoint, - as_node: options?.asNode, - }, - }, - ); - } - - /** - * Patch the metadata of a thread. - * - * @param threadIdOrConfig Thread ID or config to patch the state of. - * @param metadata Metadata to patch the state with. - */ - async patchState( - threadIdOrConfig: string | Config, - metadata: Metadata, - ): Promise { - let threadId: string; - - if (typeof threadIdOrConfig !== "string") { - if (typeof threadIdOrConfig.configurable?.thread_id !== "string") { - throw new Error( - "Thread ID is required when updating state with a config.", - ); - } - threadId = threadIdOrConfig.configurable.thread_id; - } else { - threadId = threadIdOrConfig; - } - - return this.fetch(`/threads/${threadId}/state`, { - method: "PATCH", - json: { metadata: metadata }, - }); - } - - /** - * Get all past states for a thread. - * - * @param threadId ID of the thread. - * @param options Additional options. - * @returns List of thread states. - */ - async getHistory( - threadId: string, - options?: { - limit?: number; - before?: Config; - checkpoint?: Partial>; - metadata?: Metadata; - }, - ): Promise[]> { - return this.fetch[]>( - `/threads/${threadId}/history`, - { - method: "POST", - json: { - limit: options?.limit ?? 10, - before: options?.before, - metadata: options?.metadata, - checkpoint: options?.checkpoint, - }, - }, - ); - } -} - -export class RunsClient< - TStateType = DefaultValues, - TUpdateType = TStateType, - TCustomEventType = unknown, -> extends BaseClient { - stream< - TStreamMode extends StreamMode | StreamMode[] = StreamMode, - TSubgraphs extends boolean = false, - >( - threadId: null, - assistantId: string, - payload?: Omit< - RunsStreamPayload, - "multitaskStrategy" | "onCompletion" - >, - ): TypedAsyncGenerator< - TStreamMode, - TSubgraphs, - TStateType, - TUpdateType, - TCustomEventType - >; - - stream< - TStreamMode extends StreamMode | StreamMode[] = StreamMode, - TSubgraphs extends boolean = false, - >( - threadId: string, - assistantId: string, - payload?: RunsStreamPayload, - ): TypedAsyncGenerator< - TStreamMode, - TSubgraphs, - TStateType, - TUpdateType, - TCustomEventType - >; - - /** - * Create a run and stream the results. - * - * @param threadId The ID of the thread. - * @param assistantId Assistant ID to use for this run. - * @param payload Payload for creating a run. - */ - async *stream< - TStreamMode extends StreamMode | StreamMode[] = StreamMode, - TSubgraphs extends boolean = false, - >( - threadId: string | null, - assistantId: string, - payload?: RunsStreamPayload, - ): TypedAsyncGenerator< - TStreamMode, - TSubgraphs, - TStateType, - TUpdateType, - TCustomEventType - > { - const json: Record = { - input: payload?.input, - command: payload?.command, - config: payload?.config, - metadata: payload?.metadata, - stream_mode: payload?.streamMode, - stream_subgraphs: payload?.streamSubgraphs, - stream_resumable: payload?.streamResumable, - feedback_keys: payload?.feedbackKeys, - assistant_id: assistantId, - interrupt_before: payload?.interruptBefore, - interrupt_after: payload?.interruptAfter, - checkpoint: payload?.checkpoint, - checkpoint_id: payload?.checkpointId, - webhook: payload?.webhook, - multitask_strategy: payload?.multitaskStrategy, - on_completion: payload?.onCompletion, - on_disconnect: payload?.onDisconnect, - after_seconds: payload?.afterSeconds, - if_not_exists: payload?.ifNotExists, - checkpoint_during: payload?.checkpointDuring, - }; - - const endpoint = - threadId == null ? `/runs/stream` : `/threads/${threadId}/runs/stream`; - - const response = await this.asyncCaller.fetch( - ...this.prepareFetchOptions(endpoint, { - method: "POST", - json, - timeoutMs: null, - signal: payload?.signal, - }), - ); - - const runMetadata = getRunMetadataFromResponse(response); - if (runMetadata) payload?.onRunCreated?.(runMetadata); - - const stream: ReadableStream<{ event: any; data: any }> = ( - response.body || new ReadableStream({ start: (ctrl) => ctrl.close() }) - ) - .pipeThrough(BytesLineDecoder()) - .pipeThrough(SSEDecoder()); - - yield* IterableReadableStream.fromReadableStream(stream); - } - - /** - * Create a run. - * - * @param threadId The ID of the thread. - * @param assistantId Assistant ID to use for this run. - * @param payload Payload for creating a run. - * @returns The created run. - */ - async create( - threadId: string, - assistantId: string, - payload?: RunsCreatePayload, - ): Promise { - const json: Record = { - input: payload?.input, - command: payload?.command, - config: payload?.config, - metadata: payload?.metadata, - stream_mode: payload?.streamMode, - stream_subgraphs: payload?.streamSubgraphs, - stream_resumable: payload?.streamResumable, - assistant_id: assistantId, - interrupt_before: payload?.interruptBefore, - interrupt_after: payload?.interruptAfter, - webhook: payload?.webhook, - checkpoint: payload?.checkpoint, - checkpoint_id: payload?.checkpointId, - multitask_strategy: payload?.multitaskStrategy, - after_seconds: payload?.afterSeconds, - if_not_exists: payload?.ifNotExists, - checkpoint_during: payload?.checkpointDuring, - langsmith_tracer: payload?._langsmithTracer - ? { - project_name: payload?._langsmithTracer?.projectName, - example_id: payload?._langsmithTracer?.exampleId, - } - : undefined, - }; - - const [run, response] = await this.fetch(`/threads/${threadId}/runs`, { - method: "POST", - json, - signal: payload?.signal, - withResponse: true, - }); - - const runMetadata = getRunMetadataFromResponse(response); - if (runMetadata) payload?.onRunCreated?.(runMetadata); - - return run; - } - - /** - * Create a batch of stateless background runs. - * - * @param payloads An array of payloads for creating runs. - * @returns An array of created runs. - */ - async createBatch( - payloads: (RunsCreatePayload & { assistantId: string })[], - ): Promise { - const filteredPayloads = payloads - .map((payload) => ({ ...payload, assistant_id: payload.assistantId })) - .map((payload) => { - return Object.fromEntries( - Object.entries(payload).filter(([_, v]) => v !== undefined), - ); - }); - - return this.fetch("/runs/batch", { - method: "POST", - json: filteredPayloads, - }); - } - - async wait( - threadId: null, - assistantId: string, - payload?: Omit, - ): Promise; - - async wait( - threadId: string, - assistantId: string, - payload?: RunsWaitPayload, - ): Promise; - - /** - * Create a run and wait for it to complete. - * - * @param threadId The ID of the thread. - * @param assistantId Assistant ID to use for this run. - * @param payload Payload for creating a run. - * @returns The last values chunk of the thread. - */ - async wait( - threadId: string | null, - assistantId: string, - payload?: RunsWaitPayload, - ): Promise { - const json: Record = { - input: payload?.input, - command: payload?.command, - config: payload?.config, - metadata: payload?.metadata, - assistant_id: assistantId, - interrupt_before: payload?.interruptBefore, - interrupt_after: payload?.interruptAfter, - checkpoint: payload?.checkpoint, - checkpoint_id: payload?.checkpointId, - webhook: payload?.webhook, - multitask_strategy: payload?.multitaskStrategy, - on_completion: payload?.onCompletion, - on_disconnect: payload?.onDisconnect, - after_seconds: payload?.afterSeconds, - if_not_exists: payload?.ifNotExists, - checkpoint_during: payload?.checkpointDuring, - langsmith_tracer: payload?._langsmithTracer - ? { - project_name: payload?._langsmithTracer?.projectName, - example_id: payload?._langsmithTracer?.exampleId, - } - : undefined, - }; - const endpoint = - threadId == null ? `/runs/wait` : `/threads/${threadId}/runs/wait`; - const [run, response] = await this.fetch(endpoint, { - method: "POST", - json, - timeoutMs: null, - signal: payload?.signal, - withResponse: true, - }); - - const runMetadata = getRunMetadataFromResponse(response); - if (runMetadata) payload?.onRunCreated?.(runMetadata); - - const raiseError = - payload?.raiseError !== undefined ? payload.raiseError : true; - if ( - raiseError && - "__error__" in run && - typeof run.__error__ === "object" && - run.__error__ && - "error" in run.__error__ && - "message" in run.__error__ - ) { - throw new Error(`${run.__error__?.error}: ${run.__error__?.message}`); - } - return run; - } - - /** - * List all runs for a thread. - * - * @param threadId The ID of the thread. - * @param options Filtering and pagination options. - * @returns List of runs. - */ - async list( - threadId: string, - options?: { - /** - * Maximum number of runs to return. - * Defaults to 10 - */ - limit?: number; - - /** - * Offset to start from. - * Defaults to 0. - */ - offset?: number; - - /** - * Status of the run to filter by. - */ - status?: RunStatus; - }, - ): Promise { - return this.fetch(`/threads/${threadId}/runs`, { - params: { - limit: options?.limit ?? 10, - offset: options?.offset ?? 0, - status: options?.status ?? undefined, - }, - }); - } - - /** - * Get a run by ID. - * - * @param threadId The ID of the thread. - * @param runId The ID of the run. - * @returns The run. - */ - async get(threadId: string, runId: string): Promise { - return this.fetch(`/threads/${threadId}/runs/${runId}`); - } - - /** - * Cancel a run. - * - * @param threadId The ID of the thread. - * @param runId The ID of the run. - * @param wait Whether to block when canceling - * @param action Action to take when cancelling the run. Possible values are `interrupt` or `rollback`. Default is `interrupt`. - * @returns - */ - async cancel( - threadId: string, - runId: string, - wait: boolean = false, - action: CancelAction = "interrupt", - ): Promise { - return this.fetch(`/threads/${threadId}/runs/${runId}/cancel`, { - method: "POST", - params: { - wait: wait ? "1" : "0", - action: action, - }, - }); - } - - /** - * Block until a run is done. - * - * @param threadId The ID of the thread. - * @param runId The ID of the run. - * @returns - */ - async join( - threadId: string, - runId: string, - options?: { signal?: AbortSignal }, - ): Promise { - return this.fetch(`/threads/${threadId}/runs/${runId}/join`, { - timeoutMs: null, - signal: options?.signal, - }); - } - - /** - * Stream output from a run in real-time, until the run is done. - * - * @param threadId The ID of the thread. Can be set to `null` | `undefined` for stateless runs. - * @param runId The ID of the run. - * @param options Additional options for controlling the stream behavior: - * - signal: An AbortSignal that can be used to cancel the stream request - * - lastEventId: The ID of the last event received. Can be used to reconnect to a stream without losing events. - * - cancelOnDisconnect: When true, automatically cancels the run if the client disconnects from the stream - * - streamMode: Controls what types of events to receive from the stream (can be a single mode or array of modes) - * Must be a subset of the stream modes passed when creating the run. Background runs default to having the union of all - * stream modes enabled. - * @returns An async generator yielding stream parts. - */ - async *joinStream( - threadId: string | undefined | null, - runId: string, - options?: - | { - signal?: AbortSignal; - cancelOnDisconnect?: boolean; - lastEventId?: string; - streamMode?: StreamMode | StreamMode[]; - } - | AbortSignal, - ): AsyncGenerator<{ id?: string; event: StreamEvent; data: any }> { - const opts = - typeof options === "object" && - options != null && - options instanceof AbortSignal - ? { signal: options } - : options; - - const response = await this.asyncCaller.fetch( - ...this.prepareFetchOptions( - threadId != null - ? `/threads/${threadId}/runs/${runId}/stream` - : `/runs/${runId}/stream`, - { - method: "GET", - timeoutMs: null, - signal: opts?.signal, - headers: opts?.lastEventId - ? { "Last-Event-ID": opts.lastEventId } - : undefined, - params: { - cancel_on_disconnect: opts?.cancelOnDisconnect ? "1" : "0", - stream_mode: opts?.streamMode, - }, - }, - ), - ); - - const stream: ReadableStream<{ event: string; data: any }> = ( - response.body || new ReadableStream({ start: (ctrl) => ctrl.close() }) - ) - .pipeThrough(BytesLineDecoder()) - .pipeThrough(SSEDecoder()); - - yield* IterableReadableStream.fromReadableStream(stream); - } - - /** - * Delete a run. - * - * @param threadId The ID of the thread. - * @param runId The ID of the run. - * @returns - */ - async delete(threadId: string, runId: string): Promise { - return this.fetch(`/threads/${threadId}/runs/${runId}`, { - method: "DELETE", - }); - } -} - -interface APIItem { - namespace: string[]; - key: string; - value: Record; - created_at: string; - updated_at: string; -} -interface APISearchItemsResponse { - items: APIItem[]; -} - -export class StoreClient extends BaseClient { - /** - * Store or update an item. - * - * @param namespace A list of strings representing the namespace path. - * @param key The unique identifier for the item within the namespace. - * @param value A dictionary containing the item's data. - * @param options.index Controls search indexing - null (use defaults), false (disable), or list of field paths to index. - * @param options.ttl Optional time-to-live in minutes for the item, or null for no expiration. - * @returns Promise - * - * @example - * ```typescript - * await client.store.putItem( - * ["documents", "user123"], - * "item456", - * { title: "My Document", content: "Hello World" }, - * { ttl: 60 } // expires in 60 minutes - * ); - * ``` - */ - async putItem( - namespace: string[], - key: string, - value: Record, - options?: { - index?: false | string[] | null; - ttl?: number | null; - }, - ): Promise { - namespace.forEach((label) => { - if (label.includes(".")) { - throw new Error( - `Invalid namespace label '${label}'. Namespace labels cannot contain periods ('.')`, - ); - } - }); - - const payload = { - namespace, - key, - value, - index: options?.index, - ttl: options?.ttl, - }; - - return this.fetch("/store/items", { - method: "PUT", - json: payload, - }); - } - - /** - * Retrieve a single item. - * - * @param namespace A list of strings representing the namespace path. - * @param key The unique identifier for the item. - * @param options.refreshTtl Whether to refresh the TTL on this read operation. If null, uses the store's default behavior. - * @returns Promise - * - * @example - * ```typescript - * const item = await client.store.getItem( - * ["documents", "user123"], - * "item456", - * { refreshTtl: true } - * ); - * console.log(item); - * // { - * // namespace: ["documents", "user123"], - * // key: "item456", - * // value: { title: "My Document", content: "Hello World" }, - * // createdAt: "2024-07-30T12:00:00Z", - * // updatedAt: "2024-07-30T12:00:00Z" - * // } - * ``` - */ - async getItem( - namespace: string[], - key: string, - options?: { - refreshTtl?: boolean | null; - }, - ): Promise { - namespace.forEach((label) => { - if (label.includes(".")) { - throw new Error( - `Invalid namespace label '${label}'. Namespace labels cannot contain periods ('.')`, - ); - } - }); - - const params: Record = { - namespace: namespace.join("."), - key, - }; - - if (options?.refreshTtl !== undefined) { - params.refresh_ttl = options.refreshTtl; - } - - const response = await this.fetch("/store/items", { - params, - }); - - return response - ? { - ...response, - createdAt: response.created_at, - updatedAt: response.updated_at, - } - : null; - } - - /** - * Delete an item. - * - * @param namespace A list of strings representing the namespace path. - * @param key The unique identifier for the item. - * @returns Promise - */ - async deleteItem(namespace: string[], key: string): Promise { - namespace.forEach((label) => { - if (label.includes(".")) { - throw new Error( - `Invalid namespace label '${label}'. Namespace labels cannot contain periods ('.')`, - ); - } - }); - - return this.fetch("/store/items", { - method: "DELETE", - json: { namespace, key }, - }); - } - - /** - * Search for items within a namespace prefix. - * - * @param namespacePrefix List of strings representing the namespace prefix. - * @param options.filter Optional dictionary of key-value pairs to filter results. - * @param options.limit Maximum number of items to return (default is 10). - * @param options.offset Number of items to skip before returning results (default is 0). - * @param options.query Optional search query. - * @param options.refreshTtl Whether to refresh the TTL on items returned by this search. If null, uses the store's default behavior. - * @returns Promise - * - * @example - * ```typescript - * const results = await client.store.searchItems( - * ["documents"], - * { - * filter: { author: "John Doe" }, - * limit: 5, - * refreshTtl: true - * } - * ); - * console.log(results); - * // { - * // items: [ - * // { - * // namespace: ["documents", "user123"], - * // key: "item789", - * // value: { title: "Another Document", author: "John Doe" }, - * // createdAt: "2024-07-30T12:00:00Z", - * // updatedAt: "2024-07-30T12:00:00Z" - * // }, - * // // ... additional items ... - * // ] - * // } - * ``` - */ - async searchItems( - namespacePrefix: string[], - options?: { - filter?: Record; - limit?: number; - offset?: number; - query?: string; - refreshTtl?: boolean | null; - }, - ): Promise { - const payload = { - namespace_prefix: namespacePrefix, - filter: options?.filter, - limit: options?.limit ?? 10, - offset: options?.offset ?? 0, - query: options?.query, - refresh_ttl: options?.refreshTtl, - }; - - const response = await this.fetch( - "/store/items/search", - { - method: "POST", - json: payload, - }, - ); - return { - items: response.items.map((item) => ({ - ...item, - createdAt: item.created_at, - updatedAt: item.updated_at, - })), - }; - } - - /** - * List namespaces with optional match conditions. - * - * @param options.prefix Optional list of strings representing the prefix to filter namespaces. - * @param options.suffix Optional list of strings representing the suffix to filter namespaces. - * @param options.maxDepth Optional integer specifying the maximum depth of namespaces to return. - * @param options.limit Maximum number of namespaces to return (default is 100). - * @param options.offset Number of namespaces to skip before returning results (default is 0). - * @returns Promise - */ - async listNamespaces(options?: { - prefix?: string[]; - suffix?: string[]; - maxDepth?: number; - limit?: number; - offset?: number; - }): Promise { - const payload = { - prefix: options?.prefix, - suffix: options?.suffix, - max_depth: options?.maxDepth, - limit: options?.limit ?? 100, - offset: options?.offset ?? 0, - }; - - return this.fetch("/store/namespaces", { - method: "POST", - json: payload, - }); - } -} - -class UiClient extends BaseClient { - private static promiseCache: Record | undefined> = - {}; - - private static getOrCached(key: string, fn: () => Promise): Promise { - if (UiClient.promiseCache[key] != null) { - return UiClient.promiseCache[key] as Promise; - } - - const promise = fn(); - UiClient.promiseCache[key] = promise; - return promise; - } - - async getComponent(assistantId: string, agentName: string): Promise { - return UiClient["getOrCached"]( - `${this.apiUrl}-${assistantId}-${agentName}`, - async () => { - const response = await this.asyncCaller.fetch( - ...this.prepareFetchOptions(`/ui/${assistantId}`, { - headers: { - Accept: "text/html", - "Content-Type": "application/json", - }, - method: "POST", - json: { name: agentName }, - }), - ); - return response.text(); - }, - ); - } -} - -export class Client< - TStateType = DefaultValues, - TUpdateType = TStateType, - TCustomEventType = unknown, -> { - /** - * The client for interacting with assistants. - */ - public assistants: AssistantsClient; - - /** - * The client for interacting with threads. - */ - public threads: ThreadsClient; - - /** - * The client for interacting with runs. - */ - public runs: RunsClient; - - /** - * The client for interacting with cron runs. - */ - public crons: CronsClient; - - /** - * The client for interacting with the KV store. - */ - public store: StoreClient; - - /** - * The client for interacting with the UI. - * @internal Used by LoadExternalComponent and the API might change in the future. - */ - public "~ui": UiClient; - - /** - * @internal Used to obtain a stable key representing the client. - */ - private "~configHash": string | undefined; - - constructor(config?: ClientConfig) { - this["~configHash"] = (() => - JSON.stringify({ - apiUrl: config?.apiUrl, - apiKey: config?.apiKey, - timeoutMs: config?.timeoutMs, - defaultHeaders: config?.defaultHeaders, - - maxConcurrency: config?.callerOptions?.maxConcurrency, - maxRetries: config?.callerOptions?.maxRetries, - - callbacks: { - onFailedResponseHook: - config?.callerOptions?.onFailedResponseHook != null, - onRequest: config?.onRequest != null, - fetch: config?.callerOptions?.fetch != null, - }, - }))(); - - this.assistants = new AssistantsClient(config); - this.threads = new ThreadsClient(config); - this.runs = new RunsClient(config); - this.crons = new CronsClient(config); - this.store = new StoreClient(config); - this["~ui"] = new UiClient(config); - } -} - -/** - * @internal Used to obtain a stable key representing the client. - */ -export function getClientConfigHash(client: Client): string | undefined { - return client["~configHash"]; -} diff --git a/libs/sdk-js/src/index.ts b/libs/sdk-js/src/index.ts deleted file mode 100644 index 4318bbfc0..000000000 --- a/libs/sdk-js/src/index.ts +++ /dev/null @@ -1,56 +0,0 @@ -export { Client, getApiKey } from "./client.js"; -export type { ClientConfig, RequestHook } from "./client.js"; - -export type { - Assistant, - AssistantBase, - AssistantGraph, - AssistantVersion, - Checkpoint, - Config, - Cron, - CronCreateForThreadResponse, - CronCreateResponse, - DefaultValues, - GraphSchema, - Interrupt, - Item, - ListNamespaceResponse, - Metadata, - Run, - SearchItem, - SearchItemsResponse, - Thread, - ThreadState, - ThreadStatus, - ThreadTask, -} from "./schema.js"; -export { overrideFetchImplementation } from "./singletons/fetch.js"; - -export type { - Command, - OnConflictBehavior, - RunsInvokePayload, -} from "./types.js"; -export type { - AIMessage, - FunctionMessage, - HumanMessage, - Message, - RemoveMessage, - SystemMessage, - ToolMessage, -} from "./types.messages.js"; -export type { - CustomStreamEvent, - DebugStreamEvent, - ErrorStreamEvent, - EventsStreamEvent, - FeedbackStreamEvent, - MessagesStreamEvent, - MessagesTupleStreamEvent, - MetadataStreamEvent, - StreamMode, - UpdatesStreamEvent, - ValuesStreamEvent, -} from "./types.stream.js"; diff --git a/libs/sdk-js/src/react-ui/client.tsx b/libs/sdk-js/src/react-ui/client.tsx deleted file mode 100644 index 1484f491d..000000000 --- a/libs/sdk-js/src/react-ui/client.tsx +++ /dev/null @@ -1,279 +0,0 @@ -"use client"; - -import { useStream } from "../react/index.js"; -import type { UIMessage } from "./types.js"; - -import * as React from "react"; -import * as ReactDOM from "react-dom"; -import * as JsxRuntime from "react/jsx-runtime"; -import type { UseStream } from "../react/stream.js"; - -const UseStreamContext = React.createContext<{ - stream: ReturnType; - meta: unknown; -}>(null!); - -type BagTemplate = { - ConfigurableType?: Record; - InterruptType?: unknown; - CustomEventType?: unknown; - UpdateType?: unknown; - MetaType?: unknown; -}; - -type GetMetaType = Bag extends { MetaType: unknown } - ? Bag["MetaType"] - : unknown; - -interface UseStreamContext< - StateType extends Record = Record, - Bag extends BagTemplate = BagTemplate, -> extends UseStream { - meta?: GetMetaType; -} - -export function useStreamContext< - StateType extends Record = Record, - Bag extends { - ConfigurableType?: Record; - InterruptType?: unknown; - CustomEventType?: unknown; - UpdateType?: unknown; - MetaType?: unknown; - } = BagTemplate, ->(): UseStreamContext { - const ctx = React.useContext(UseStreamContext); - if (!ctx) { - throw new Error( - "useStreamContext must be used within a LoadExternalComponent", - ); - } - - return new Proxy(ctx, { - get(target, prop: keyof UseStreamContext) { - if (prop === "meta") return target.meta; - return target.stream[prop]; - }, - }) as unknown as UseStreamContext; -} - -interface ComponentTarget { - comp: React.FunctionComponent | React.ComponentClass; - target: HTMLElement; -} - -class ComponentStore { - private cache: Record = {}; - private boundCache: Record< - string, - { - subscribe: (onStoreChange: () => void) => () => void; - getSnapshot: () => ComponentTarget | undefined; - } - > = {}; - private callbacks: Record< - string, - (( - comp: React.FunctionComponent | React.ComponentClass, - el: HTMLElement, - ) => void)[] - > = {}; - - respond( - shadowRootId: string, - comp: React.FunctionComponent | React.ComponentClass, - targetElement: HTMLElement, - ) { - this.cache[shadowRootId] = { comp, target: targetElement }; - this.callbacks[shadowRootId]?.forEach((c) => c(comp, targetElement)); - } - - getBoundStore(shadowRootId: string) { - this.boundCache[shadowRootId] ??= { - subscribe: (onStoreChange: () => void) => { - this.callbacks[shadowRootId] ??= []; - this.callbacks[shadowRootId].push(onStoreChange); - return () => { - this.callbacks[shadowRootId] = this.callbacks[shadowRootId].filter( - (c) => c !== onStoreChange, - ); - }; - }, - getSnapshot: () => this.cache[shadowRootId], - }; - - return this.boundCache[shadowRootId]; - } -} - -const COMPONENT_STORE = new ComponentStore(); -const EXT_STORE_SYMBOL = Symbol.for("LGUI_EXT_STORE"); -const REQUIRE_SYMBOL = Symbol.for("LGUI_REQUIRE"); -const REQUIRE_EXTRA_SYMBOL = Symbol.for("LGUI_REQUIRE_EXTRA"); - -interface LoadExternalComponentProps - extends Pick, "style" | "className"> { - /** Stream of the assistant */ - stream: ReturnType; - - /** Namespace of UI components. Defaults to assistant ID. */ - namespace?: string; - - /** UI message to be rendered */ - message: UIMessage; - - /** Additional context to be passed to the child component */ - meta?: unknown; - - /** Fallback to be rendered when the component is loading */ - fallback?: React.ReactNode | Record; - - /** - * Map of components that can be rendered directly without fetching the UI code - * from the server. - */ - components?: Record; -} - -const isIterable = (value: unknown): value is Iterable => - value != null && typeof value === "object" && Symbol.iterator in value; - -const isPromise = (value: unknown): value is Promise => - value != null && - typeof value === "object" && - "then" in value && - typeof value.then === "function"; - -const isReactNode = (value: unknown): value is React.ReactNode => { - if (React.isValidElement(value)) return true; - if (value == null) return true; - if ( - typeof value === "string" || - typeof value === "number" || - typeof value === "bigint" || - typeof value === "boolean" - ) { - return true; - } - - if (isIterable(value)) return true; - if (isPromise(value)) return true; - - return false; -}; - -export function LoadExternalComponent({ - stream, - namespace, - message, - meta, - fallback, - components, - ...props -}: LoadExternalComponentProps) { - const ref = React.useRef(null); - const id = React.useId(); - const shadowRootId = `child-shadow-${id}`; - - const store = React.useMemo( - () => COMPONENT_STORE.getBoundStore(shadowRootId), - [shadowRootId], - ); - const state = React.useSyncExternalStore(store.subscribe, store.getSnapshot); - - const clientComponent = components?.[message.name]; - const hasClientComponent = clientComponent != null; - - const fallbackComponent = isReactNode(fallback) - ? fallback - : typeof fallback === "object" && fallback != null - ? fallback?.[message.name] - : null; - - const uiNamespace = namespace ?? stream.assistantId; - const uiClient = stream.client["~ui"]; - React.useEffect(() => { - if (hasClientComponent) return; - uiClient.getComponent(uiNamespace, message.name).then((html) => { - const dom = ref.current; - if (!dom) return; - const root = dom.shadowRoot ?? dom.attachShadow({ mode: "open" }); - const fragment = document - .createRange() - .createContextualFragment( - html.replace("{{shadowRootId}}", shadowRootId), - ); - root.appendChild(fragment); - }); - }, [uiClient, uiNamespace, message.name, shadowRootId, hasClientComponent]); - - if (hasClientComponent) { - return ( - - {React.createElement(clientComponent, message.props)} - - ); - } - - return ( - <> -
- - - {state?.target != null - ? ReactDOM.createPortal( - React.createElement(state.comp, message.props), - state.target, - ) - : fallbackComponent} - - - ); -} - -declare global { - interface Window { - [EXT_STORE_SYMBOL]: ComponentStore; - [REQUIRE_SYMBOL]: (name: string) => unknown; - [REQUIRE_EXTRA_SYMBOL]: Record; - } -} - -export function experimental_loadShare(name: string, module: unknown) { - if (typeof window === "undefined") return; - - window[REQUIRE_EXTRA_SYMBOL] ??= {}; - window[REQUIRE_EXTRA_SYMBOL][name] = module; -} - -export function bootstrapUiContext() { - if (typeof window === "undefined") { - return; - } - - window[EXT_STORE_SYMBOL] = COMPONENT_STORE; - window[REQUIRE_SYMBOL] = (name: string) => { - if (name === "react") return React; - if (name === "react-dom") return ReactDOM; - if (name === "react/jsx-runtime") return JsxRuntime; - if (name === "@langchain/langgraph-sdk/react") return { useStream }; - if (name === "@langchain/langgraph-sdk/react-ui") { - return { - useStreamContext, - LoadExternalComponent: () => { - throw new Error("Nesting LoadExternalComponent is not supported"); - }, - }; - } - - if ( - window[REQUIRE_EXTRA_SYMBOL] != null && - typeof window[REQUIRE_EXTRA_SYMBOL] === "object" && - name in window[REQUIRE_EXTRA_SYMBOL] - ) { - return window[REQUIRE_EXTRA_SYMBOL][name]; - } - - throw new Error(`Unknown module...: ${name}`); - }; -} diff --git a/libs/sdk-js/src/react-ui/index.ts b/libs/sdk-js/src/react-ui/index.ts deleted file mode 100644 index e63e79d16..000000000 --- a/libs/sdk-js/src/react-ui/index.ts +++ /dev/null @@ -1,15 +0,0 @@ -import { bootstrapUiContext } from "./client.js"; -bootstrapUiContext(); - -export { - useStreamContext, - LoadExternalComponent, - experimental_loadShare, -} from "./client.js"; -export { - uiMessageReducer, - isUIMessage, - isRemoveUIMessage, - type UIMessage, - type RemoveUIMessage, -} from "./types.js"; diff --git a/libs/sdk-js/src/react-ui/server/index.ts b/libs/sdk-js/src/react-ui/server/index.ts deleted file mode 100644 index 45c2c1e78..000000000 --- a/libs/sdk-js/src/react-ui/server/index.ts +++ /dev/null @@ -1,6 +0,0 @@ -export { typedUi } from "./server.js"; -export { - uiMessageReducer, - type UIMessage, - type RemoveUIMessage, -} from "../types.js"; diff --git a/libs/sdk-js/src/react-ui/server/server.ts b/libs/sdk-js/src/react-ui/server/server.ts deleted file mode 100644 index 8eb14d17f..000000000 --- a/libs/sdk-js/src/react-ui/server/server.ts +++ /dev/null @@ -1,99 +0,0 @@ -import { v4 as uuidv4 } from "uuid"; -import type { ComponentPropsWithoutRef, ElementType } from "react"; -import type { RemoveUIMessage, UIMessage } from "../types.js"; - -interface MessageLike { - id?: string; -} - -/** - * Helper to send and persist UI messages. Accepts a map of component names to React components - * as type argument to provide type safety. Will also write to the `options?.stateKey` state. - * - * @param config LangGraphRunnableConfig - * @param options - * @returns - */ -export const typedUi = >( - config: { - writer?: (chunk: unknown) => void; - runId?: string; - metadata?: Record; - tags?: string[]; - runName?: string; - configurable?: { - __pregel_send?: (writes_: [string, unknown][]) => void; - [key: string]: unknown; - }; - }, - options?: { - /** The key to write the UI messages to. Defaults to `ui`. */ - stateKey?: string; - }, -) => { - type PropMap = { [K in keyof Decl]: ComponentPropsWithoutRef }; - let items: (UIMessage | RemoveUIMessage)[] = []; - const stateKey = options?.stateKey ?? "ui"; - - const runId = (config.metadata?.run_id as string | undefined) ?? config.runId; - if (!runId) throw new Error("run_id is required"); - - function handlePush( - message: { - id?: string; - name: K; - props: PropMap[K]; - metadata?: Record; - }, - options?: { message?: MessageLike; merge?: boolean }, - ): UIMessage; - - function handlePush( - message: { - id?: string; - name: K; - props: Partial; - metadata?: Record; - }, - options: { message?: MessageLike; merge: true }, - ): UIMessage>; - - function handlePush( - message: { - id?: string; - name: K; - props: PropMap[K] | Partial; - metadata?: Record; - }, - options?: { message?: MessageLike; merge?: boolean }, - ): UIMessage> { - const evt: UIMessage> = { - type: "ui" as const, - id: message?.id ?? uuidv4(), - name: message?.name, - props: message?.props, - metadata: { - merge: options?.merge || undefined, - run_id: runId, - tags: config.tags, - name: config.runName, - ...message?.metadata, - ...(options?.message ? { message_id: options.message.id } : null), - }, - }; - items.push(evt); - config.writer?.(evt); - config.configurable?.__pregel_send?.([[stateKey, evt]]); - return evt; - } - - const handleDelete = (id: string): RemoveUIMessage => { - const evt: RemoveUIMessage = { type: "remove-ui", id }; - items.push(evt); - config.writer?.(evt); - config.configurable?.__pregel_send?.([[stateKey, evt]]); - return evt; - }; - - return { push: handlePush, delete: handleDelete, items }; -}; diff --git a/libs/sdk-js/src/react-ui/types.ts b/libs/sdk-js/src/react-ui/types.ts deleted file mode 100644 index 42499996d..000000000 --- a/libs/sdk-js/src/react-ui/types.ts +++ /dev/null @@ -1,66 +0,0 @@ -export interface UIMessage< - TName extends string = string, - TProps extends Record = Record, -> { - type: "ui"; - - id: string; - name: TName; - props: TProps; - metadata?: { - merge?: boolean; - run_id?: string; - name?: string; - tags?: string[]; - message_id?: string; - [key: string]: unknown; - }; -} - -export interface RemoveUIMessage { - type: "remove-ui"; - id: string; -} - -export function isUIMessage(message: unknown): message is UIMessage { - if (typeof message !== "object" || message == null) return false; - if (!("type" in message)) return false; - return message.type === "ui"; -} - -export function isRemoveUIMessage( - message: unknown, -): message is RemoveUIMessage { - if (typeof message !== "object" || message == null) return false; - if (!("type" in message)) return false; - return message.type === "remove-ui"; -} - -export function uiMessageReducer( - state: UIMessage[], - update: UIMessage | RemoveUIMessage | (UIMessage | RemoveUIMessage)[], -) { - const events = Array.isArray(update) ? update : [update]; - let newState = state.slice(); - - for (const event of events) { - if (event.type === "remove-ui") { - newState = newState.filter((ui) => ui.id !== event.id); - continue; - } - - const index = state.findIndex((ui) => ui.id === event.id); - if (index !== -1) { - newState[index] = - typeof event.metadata === "object" && - event.metadata != null && - event.metadata.merge - ? { ...event, props: { ...state[index].props, ...event.props } } - : event; - } else { - newState.push(event); - } - } - - return newState; -} diff --git a/libs/sdk-js/src/react/debug.tsx b/libs/sdk-js/src/react/debug.tsx deleted file mode 100644 index b5fc462fc..000000000 --- a/libs/sdk-js/src/react/debug.tsx +++ /dev/null @@ -1,102 +0,0 @@ -import { ThreadState } from "../schema.js"; - -interface Node { - type: "node"; - value: ThreadState; - path: string[]; -} - -interface Fork { - type: "fork"; - items: Array>; -} - -interface Sequence { - type: "sequence"; - items: Array | Fork>; -} - -interface ValidFork { - type: "fork"; - items: Array>; -} - -interface ValidSequence { - type: "sequence"; - items: [Node, ...(Node | ValidFork)[]]; -} - -// forks -export type CheckpointBranchPath = string[]; - -export type MessageBranch = { - current: CheckpointBranchPath; - options: CheckpointBranchPath[]; -}; - -export function DebugSegmentsView(props: { - sequence: ValidSequence; -}) { - const concatContent = (value: ThreadState) => { - let content; - try { - content = value.values?.messages?.at(-1)?.content ?? ""; - } catch { - content = JSON.stringify(value.values); - } - - content = content.replace(/(\n|\r\n)/g, ""); - if (content.length <= 23) return content; - return `${content.slice(0, 10)}...${content.slice(-10)}`; - }; - - return ( -
- {props.sequence.items.map((item, index) => { - if (item.type === "fork") { - return ( -
- {item.items.map((fork, idx) => { - const [first] = fork.items; - return ( -
- - Fork{" "} - - ...{first.path.at(-1)?.slice(-4)} - - -
- -
-
- ); - })} -
- ); - } - - if (item.type === "node") { - return ( -
- 
-                ({item.value.metadata?.step}) ...
-                {item.value.checkpoint.checkpoint_id?.slice(-4)} (
-                {item.value.metadata?.source}): {concatContent(item.value)}
-
- -
- ); - } - - return null; - })} -
- ); -} diff --git a/libs/sdk-js/src/react/index.ts b/libs/sdk-js/src/react/index.ts deleted file mode 100644 index 9b7e22871..000000000 --- a/libs/sdk-js/src/react/index.ts +++ /dev/null @@ -1,6 +0,0 @@ -export { - useStream, - type MessageMetadata, - type UseStream, - type UseStreamOptions, -} from "./stream.js"; diff --git a/libs/sdk-js/src/react/stream.tsx b/libs/sdk-js/src/react/stream.tsx deleted file mode 100644 index 4b7159ee1..000000000 --- a/libs/sdk-js/src/react/stream.tsx +++ /dev/null @@ -1,1264 +0,0 @@ -/* __LC_ALLOW_ENTRYPOINT_SIDE_EFFECTS__ */ -"use client"; - -import { Client, getClientConfigHash, type ClientConfig } from "../client.js"; -import type { - Command, - DisconnectMode, - MultitaskStrategy, - OnCompletionBehavior, -} from "../types.js"; -import type { Message } from "../types.messages.js"; -import type { - Checkpoint, - Config, - Interrupt, - Metadata, - ThreadState, -} from "../schema.js"; -import type { - CustomStreamEvent, - DebugStreamEvent, - ErrorStreamEvent, - EventsStreamEvent, - FeedbackStreamEvent, - MessagesStreamEvent, - MessagesTupleStreamEvent, - MetadataStreamEvent, - StreamMode, - UpdatesStreamEvent, - ValuesStreamEvent, -} from "../types.stream.js"; - -import { - type RefObject, - useCallback, - useEffect, - useMemo, - useRef, - useState, -} from "react"; -import { - type BaseMessageChunk, - type BaseMessage, - coerceMessageLikeToMessage, - convertToChunk, - isBaseMessageChunk, -} from "@langchain/core/messages"; - -class StreamError extends Error { - constructor(data: { error?: string; name?: string; message: string }) { - super(data.message); - this.name = data.name ?? data.error ?? "StreamError"; - } - - static isStructuredError(error: unknown): error is { - error?: string; - name?: string; - message: string; - } { - return typeof error === "object" && error != null && "message" in error; - } -} - -function tryConvertToChunk(message: BaseMessage): BaseMessageChunk | null { - try { - return convertToChunk(message); - } catch { - return null; - } -} - -class MessageTupleManager { - chunks: Record< - string, - { chunk?: BaseMessageChunk | BaseMessage; index?: number } - > = {}; - - constructor() { - this.chunks = {}; - } - - add(serialized: Message): string | null { - // TODO: this is sometimes sent from the API - // figure out how to prevent this or move this to LC.js - if (serialized.type.endsWith("MessageChunk")) { - serialized.type = serialized.type - .slice(0, -"MessageChunk".length) - .toLowerCase() as Message["type"]; - } - - const message = coerceMessageLikeToMessage(serialized); - const chunk = tryConvertToChunk(message); - - const id = (chunk ?? message).id; - if (!id) { - console.warn( - "No message ID found for chunk, ignoring in state", - serialized, - ); - return null; - } - - this.chunks[id] ??= {}; - if (chunk) { - const prev = this.chunks[id].chunk; - this.chunks[id].chunk = - (isBaseMessageChunk(prev) ? prev : null)?.concat(chunk) ?? chunk; - } else { - this.chunks[id].chunk = message; - } - - return id; - } - - clear() { - this.chunks = {}; - } - - get(id: string, defaultIndex: number) { - if (this.chunks[id] == null) return null; - this.chunks[id].index ??= defaultIndex; - - return this.chunks[id]; - } -} - -const toMessageDict = (chunk: BaseMessage): Message => { - const { type, data } = chunk.toDict(); - return { ...data, type } as Message; -}; - -function unique(array: T[]) { - return [...new Set(array)] as T[]; -} - -function findLastIndex(array: T[], predicate: (item: T) => boolean) { - for (let i = array.length - 1; i >= 0; i--) { - if (predicate(array[i])) return i; - } - return -1; -} - -interface Node { - type: "node"; - value: ThreadState; - path: string[]; -} - -interface Fork { - type: "fork"; - items: Array>; -} - -interface Sequence { - type: "sequence"; - items: Array | Fork>; -} - -interface ValidFork { - type: "fork"; - items: Array>; -} - -interface ValidSequence { - type: "sequence"; - items: [Node, ...(Node | ValidFork)[]]; -} - -export type MessageMetadata> = { - /** - * The ID of the message used. - */ - messageId: string; - - /** - * The first thread state the message was seen in. - */ - firstSeenState: ThreadState | undefined; - - /** - * The branch of the message. - */ - branch: string | undefined; - - /** - * The list of branches this message is part of. - * This is useful for displaying branching controls. - */ - branchOptions: string[] | undefined; -}; - -function getBranchSequence>( - history: ThreadState[], -) { - const childrenMap: Record[]> = {}; - - // First pass - collect nodes for each checkpoint - history.forEach((state) => { - const checkpointId = state.parent_checkpoint?.checkpoint_id ?? "$"; - childrenMap[checkpointId] ??= []; - childrenMap[checkpointId].push(state); - }); - - // Second pass - create a tree of sequences - type Task = { id: string; sequence: Sequence; path: string[] }; - const rootSequence: Sequence = { type: "sequence", items: [] }; - const queue: Task[] = [{ id: "$", sequence: rootSequence, path: [] }]; - - const paths: string[][] = []; - - const visited = new Set(); - while (queue.length > 0) { - const task = queue.shift()!; - if (visited.has(task.id)) continue; - visited.add(task.id); - - const children = childrenMap[task.id]; - if (children == null || children.length === 0) continue; - - // If we've encountered a fork (2+ children), push the fork - // to the sequence and add a new sequence for each child - let fork: Fork | undefined; - if (children.length > 1) { - fork = { type: "fork", items: [] }; - task.sequence.items.push(fork); - } - - for (const value of children) { - const id = value.checkpoint.checkpoint_id!; - - let sequence = task.sequence; - let path = task.path; - if (fork != null) { - sequence = { type: "sequence", items: [] }; - fork.items.unshift(sequence); - - path = path.slice(); - path.push(id); - paths.push(path); - } - - sequence.items.push({ type: "node", value, path }); - queue.push({ id, sequence, path }); - } - } - - return { rootSequence, paths }; -} - -const PATH_SEP = ">"; -const ROOT_ID = "$"; - -// Get flat view -function getBranchView>( - sequence: Sequence, - paths: string[][], - branch: string, -) { - const path = branch.split(PATH_SEP); - const pathMap: Record = {}; - - for (const path of paths) { - const parent = path.at(-2) ?? ROOT_ID; - pathMap[parent] ??= []; - pathMap[parent].unshift(path); - } - - const history: ThreadState[] = []; - const branchByCheckpoint: Record< - string, - { branch: string | undefined; branchOptions: string[] | undefined } - > = {}; - - const forkStack = path.slice(); - const queue: (Node | Fork)[] = [...sequence.items]; - - while (queue.length > 0) { - const item = queue.shift()!; - - if (item.type === "node") { - history.push(item.value); - branchByCheckpoint[item.value.checkpoint.checkpoint_id!] = { - branch: item.path.join(PATH_SEP), - branchOptions: (item.path.length > 0 - ? pathMap[item.path.at(-2) ?? ROOT_ID] ?? [] - : [] - ).map((p) => p.join(PATH_SEP)), - }; - } - if (item.type === "fork") { - const forkId = forkStack.shift(); - const index = - forkId != null - ? item.items.findIndex((value) => { - const firstItem = value.items.at(0); - if (!firstItem || firstItem.type !== "node") return false; - return firstItem.value.checkpoint.checkpoint_id === forkId; - }) - : -1; - - const nextItems = item.items.at(index)?.items ?? []; - queue.push(...nextItems); - } - } - - return { history, branchByCheckpoint }; -} - -function fetchHistory>( - client: Client, - threadId: string, -) { - return client.threads.getHistory(threadId, { limit: 1000 }); -} - -function useThreadHistory>( - threadId: string | undefined | null, - client: Client, - clearCallbackRef: RefObject<(() => void) | undefined>, - submittingRef: RefObject, -) { - const [history, setHistory] = useState[]>([]); - - const clientHash = getClientConfigHash(client); - const clientRef = useRef(client); - clientRef.current = client; - - const fetcher = useCallback( - ( - threadId: string | undefined | null, - ): Promise[]> => { - if (threadId != null) { - const client = clientRef.current; - return fetchHistory(client, threadId).then((history) => { - setHistory(history); - return history; - }); - } - - setHistory([]); - clearCallbackRef.current?.(); - return Promise.resolve([]); - }, - [], - ); - - useEffect(() => { - if (submittingRef.current) return; - fetcher(threadId); - }, [fetcher, clientHash, submittingRef, threadId]); - - return { - data: history, - mutate: (mutateId?: string) => fetcher(mutateId ?? threadId), - }; -} - -const useControllableThreadId = (options?: { - threadId?: string | null; - onThreadId?: (threadId: string) => void; -}): [string | null, (threadId: string) => void] => { - const [localThreadId, _setLocalThreadId] = useState( - options?.threadId ?? null, - ); - - const onThreadIdRef = useRef(options?.onThreadId); - onThreadIdRef.current = options?.onThreadId; - - const onThreadId = useCallback((threadId: string) => { - _setLocalThreadId(threadId); - onThreadIdRef.current?.(threadId); - }, []); - - if (!options || !("threadId" in options)) { - return [localThreadId, onThreadId]; - } - - return [options.threadId ?? null, onThreadId]; -}; - -type BagTemplate = { - ConfigurableType?: Record; - InterruptType?: unknown; - CustomEventType?: unknown; - UpdateType?: unknown; -}; - -type GetUpdateType< - Bag extends BagTemplate, - StateType extends Record, -> = Bag extends { UpdateType: unknown } - ? Bag["UpdateType"] - : Partial; - -type GetConfigurableType = Bag extends { - ConfigurableType: Record; -} - ? Bag["ConfigurableType"] - : Record; - -type GetInterruptType = Bag extends { - InterruptType: unknown; -} - ? Bag["InterruptType"] - : unknown; - -type GetCustomEventType = Bag extends { - CustomEventType: unknown; -} - ? Bag["CustomEventType"] - : unknown; - -interface RunCallbackMeta { - run_id: string; - thread_id: string; -} - -export interface UseStreamOptions< - StateType extends Record = Record, - Bag extends BagTemplate = BagTemplate, -> { - /** - * The ID of the assistant to use. - */ - assistantId: string; - - /** - * Client used to send requests. - */ - client?: Client; - - /** - * The URL of the API to use. - */ - apiUrl?: ClientConfig["apiUrl"]; - - /** - * The API key to use. - */ - apiKey?: ClientConfig["apiKey"]; - - /** - * Custom call options, such as custom fetch implementation. - */ - callerOptions?: ClientConfig["callerOptions"]; - - /** - * Default headers to send with requests. - */ - defaultHeaders?: ClientConfig["defaultHeaders"]; - - /** - * Specify the key within the state that contains messages. - * Defaults to "messages". - * - * @default "messages" - */ - messagesKey?: string; - - /** - * Callback that is called when an error occurs. - */ - onError?: (error: unknown, run: RunCallbackMeta | undefined) => void; - - /** - * Callback that is called when the stream is finished. - */ - onFinish?: ( - state: ThreadState, - run: RunCallbackMeta | undefined, - ) => void; - - /** - * Callback that is called when a new stream is created. - */ - onCreated?: (run: RunCallbackMeta) => void; - - /** - * Callback that is called when an update event is received. - */ - onUpdateEvent?: ( - data: UpdatesStreamEvent>["data"], - ) => void; - - /** - * Callback that is called when a custom event is received. - */ - onCustomEvent?: ( - data: CustomStreamEvent>["data"], - options: { - mutate: ( - update: Partial | ((prev: StateType) => Partial), - ) => void; - }, - ) => void; - - /** - * Callback that is called when a metadata event is received. - */ - onMetadataEvent?: (data: MetadataStreamEvent["data"]) => void; - - /** - * Callback that is called when a LangChain event is received. - * @see https://langchain-ai.github.io/langgraph/cloud/how-tos/stream_events/#stream-graph-in-events-mode for more details. - */ - onLangChainEvent?: (data: EventsStreamEvent["data"]) => void; - - /** - * Callback that is called when a debug event is received. - * @internal This API is experimental and subject to change. - */ - onDebugEvent?: (data: DebugStreamEvent["data"]) => void; - - /** - * Callback that is called when the stream is stopped by the user. - * Provides a mutate function to update the stream state immediately - * without requiring a server roundtrip. - * - * @example - * ```typescript - * onStop: ({ mutate }) => { - * mutate((prev) => ({ - * ...prev, - * ui: prev.ui?.map(component => - * component.props.isLoading - * ? { ...component, props: { ...component.props, stopped: true, isLoading: false }} - * : component - * ) - * })); - * } - * ``` - */ - onStop?: (options: { - mutate: ( - update: Partial | ((prev: StateType) => Partial), - ) => void; - }) => void; - - /** - * The ID of the thread to fetch history and current values from. - */ - threadId?: string | null; - - /** - * Callback that is called when the thread ID is updated (ie when a new thread is created). - */ - onThreadId?: (threadId: string) => void; - - /** Will reconnect the stream on mount */ - reconnectOnMount?: boolean | (() => RunMetadataStorage); - - /** - * Initial values to display immediately when loading a thread. - * Useful for displaying cached thread data while official history loads. - * These values will be replaced when official thread data is fetched. - * - * Note: UI components from initialValues will render immediately if they're - * predefined in LoadExternalComponent's components prop, providing instant - * cached UI display without server fetches. - */ - initialValues?: StateType | null; -} - -interface RunMetadataStorage { - getItem(key: `lg:stream:${string}`): string | null; - setItem(key: `lg:stream:${string}`, value: string): void; - removeItem(key: `lg:stream:${string}`): void; -} - -export interface UseStream< - StateType extends Record = Record, - Bag extends BagTemplate = BagTemplate, -> { - /** - * The current values of the thread. - */ - values: StateType; - - /** - * Last seen error from the thread or during streaming. - */ - error: unknown; - - /** - * Whether the stream is currently running. - */ - isLoading: boolean; - - /** - * Stops the stream. - */ - stop: () => void; - - /** - * Create and stream a run to the thread. - */ - submit: ( - values: GetUpdateType | null | undefined, - options?: SubmitOptions>, - ) => void; - - /** - * The current branch of the thread. - */ - branch: string; - - /** - * Set the branch of the thread. - */ - setBranch: (branch: string) => void; - - /** - * Flattened history of thread states of a thread. - */ - history: ThreadState[]; - - /** - * Tree of all branches for the thread. - * @experimental - */ - experimental_branchTree: Sequence; - - /** - * Get the interrupt value for the stream if interrupted. - */ - interrupt: Interrupt> | undefined; - - /** - * Messages inferred from the thread. - * Will automatically update with incoming message chunks. - */ - messages: Message[]; - - /** - * Get the metadata for a message, such as first thread state the message - * was seen in and branch information. - - * @param message - The message to get the metadata for. - * @param index - The index of the message in the thread. - * @returns The metadata for the message. - */ - getMessagesMetadata: ( - message: Message, - index?: number, - ) => MessageMetadata | undefined; - - /** - * LangGraph SDK client used to send request and receive responses. - */ - client: Client; - - /** - * The ID of the assistant to use. - */ - assistantId: string; - - /** - * Join an active stream. - */ - joinStream: ( - runId: string, - lastEventId?: string, - options?: { streamMode?: StreamMode | StreamMode[] }, - ) => Promise; -} - -type ConfigWithConfigurable> = - Config & { configurable?: ConfigurableType }; - -interface SubmitOptions< - StateType extends Record = Record, - ConfigurableType extends Record = Record, -> { - config?: ConfigWithConfigurable; - checkpoint?: Omit | null; - command?: Command; - interruptBefore?: "*" | string[]; - interruptAfter?: "*" | string[]; - metadata?: Metadata; - multitaskStrategy?: MultitaskStrategy; - onCompletion?: OnCompletionBehavior; - onDisconnect?: DisconnectMode; - feedbackKeys?: string[]; - streamMode?: Array; - optimisticValues?: - | Partial - | ((prev: StateType) => Partial); - /** - * Whether or not to stream the nodes of any subgraphs called - * by the assistant. - * @default false - */ - streamSubgraphs?: boolean; - streamResumable?: boolean; - /** - * The ID to use when creating a new thread. When provided, this ID will be used - * for thread creation when threadId is `null` or `undefined`. - * This enables optimistic UI updates where you know the thread ID - * before the thread is actually created. - */ - threadId?: string; -} - -function useStreamValuesState>() { - type Kind = "stream" | "stop"; - type Values = StateType | null; - type Update = Values | ((prev: Values, kind?: Kind) => Values); - type Mutate = Partial | ((prev: StateType) => Partial); - - const [values, setValues] = useState<[values: StateType, kind: Kind] | null>( - null, - ); - - const setStreamValues = useCallback( - (values: Update, kind: Kind = "stream") => { - if (typeof values === "function") { - setValues((prevTuple) => { - const [prevValues, prevKind] = prevTuple ?? [null, "stream"]; - const next = values(prevValues, prevKind); - - if (next == null) return null; - return [next, kind] as [StateType, Kind]; - }); - - return; - } - - if (values == null) setValues(null); - setValues([values, kind] as [StateType, Kind]); - }, - [], - ); - - const mutate = useCallback( - (kind: Kind, serverValues: StateType) => (update: Mutate) => { - setStreamValues((clientValues) => { - const prev = { ...serverValues, ...clientValues }; - const next = typeof update === "function" ? update(prev) : update; - return { ...prev, ...next }; - }, kind); - }, - [setStreamValues], - ); - - return [values?.[0] ?? null, setStreamValues, mutate] as [ - Values, - (update: Update, kind?: Kind) => void, - (kind: Kind, serverValues: StateType) => (update: Mutate) => void, - ]; -} - -export function useStream< - StateType extends Record = Record, - Bag extends { - ConfigurableType?: Record; - InterruptType?: unknown; - CustomEventType?: unknown; - UpdateType?: unknown; - } = BagTemplate, ->(options: UseStreamOptions): UseStream { - type UpdateType = GetUpdateType; - type CustomType = GetCustomEventType; - type InterruptType = GetInterruptType; - type ConfigurableType = GetConfigurableType; - - type EventStreamEvent = - | ValuesStreamEvent - | UpdatesStreamEvent - | CustomStreamEvent - | DebugStreamEvent - | MessagesStreamEvent - | MessagesTupleStreamEvent - | EventsStreamEvent - | MetadataStreamEvent - | ErrorStreamEvent - | FeedbackStreamEvent; - - let { assistantId, messagesKey, onCreated, onError, onFinish } = options; - - const reconnectOnMountRef = useRef(options.reconnectOnMount); - const runMetadataStorage = useMemo(() => { - if (typeof window === "undefined") return null; - const storage = reconnectOnMountRef.current; - if (storage === true) return window.sessionStorage; - if (typeof storage === "function") return storage(); - return null; - }, []); - - messagesKey ??= "messages"; - - const client = useMemo( - () => - options.client ?? - new Client({ - apiUrl: options.apiUrl, - apiKey: options.apiKey, - callerOptions: options.callerOptions, - defaultHeaders: options.defaultHeaders, - }), - [ - options.client, - options.apiKey, - options.apiUrl, - options.callerOptions, - options.defaultHeaders, - ], - ); - - const [threadId, onThreadId] = useControllableThreadId(options); - - const [branch, setBranch] = useState(""); - const [isLoading, setIsLoading] = useState(false); - - const [streamError, setStreamError] = useState(undefined); - const [streamValues, setStreamValues, getMutateFn] = - useStreamValuesState(); - - const messageManagerRef = useRef(new MessageTupleManager()); - const submittingRef = useRef(false); - const abortRef = useRef(null); - - const trackStreamModeRef = useRef< - Array<"values" | "updates" | "events" | "custom" | "messages-tuple"> - >([]); - - const trackStreamMode = useCallback( - (...mode: Exclude[]) => { - for (const m of mode) { - if (!trackStreamModeRef.current.includes(m)) { - trackStreamModeRef.current.push(m); - } - } - }, - [], - ); - - const hasUpdateListener = options.onUpdateEvent != null; - const hasCustomListener = options.onCustomEvent != null; - const hasLangChainListener = options.onLangChainEvent != null; - const hasDebugListener = options.onDebugEvent != null; - - const callbackStreamMode = useMemo(() => { - const modes: Exclude[] = []; - if (hasUpdateListener) modes.push("updates"); - if (hasCustomListener) modes.push("custom"); - if (hasLangChainListener) modes.push("events"); - if (hasDebugListener) modes.push("debug"); - return modes; - }, [ - hasUpdateListener, - hasCustomListener, - hasLangChainListener, - hasDebugListener, - ]); - - const clearCallbackRef = useRef<() => void>(null!); - clearCallbackRef.current = () => { - setStreamError(undefined); - setStreamValues(null); - }; - - // TODO: this should be done on the server to avoid pagination - // TODO: should we permit adapter? SWR / React Query? - // TODO: make this only when branching is expected - const history = useThreadHistory( - threadId, - client, - clearCallbackRef, - submittingRef, - ); - - const getMessages = useMemo(() => { - return (value: StateType) => - Array.isArray(value[messagesKey]) - ? (value[messagesKey] as Message[]) - : []; - }, [messagesKey]); - - const { rootSequence, paths } = getBranchSequence(history.data); - const { history: flatHistory, branchByCheckpoint } = getBranchView( - rootSequence, - paths, - branch, - ); - - const threadHead: ThreadState | undefined = flatHistory.at(-1); - const historyValues = - threadHead?.values ?? options.initialValues ?? ({} as StateType); - - const historyError = (() => { - const error = threadHead?.tasks?.at(-1)?.error; - if (error == null) return undefined; - try { - const parsed = JSON.parse(error) as unknown; - if (StreamError.isStructuredError(parsed)) { - return new StreamError(parsed); - } - - return parsed; - } catch { - // do nothing - } - return error; - })(); - - const messageMetadata = (() => { - const alreadyShown = new Set(); - return getMessages(historyValues).map( - (message, idx): MessageMetadata => { - const messageId = message.id ?? idx; - const firstSeenIdx = findLastIndex(history.data, (state) => - getMessages(state.values) - .map((m, idx) => m.id ?? idx) - .includes(messageId), - ); - - const firstSeen = history.data[firstSeenIdx] as - | ThreadState - | undefined; - - let branch = firstSeen - ? branchByCheckpoint[firstSeen.checkpoint.checkpoint_id!] - : undefined; - - if (!branch?.branch?.length) branch = undefined; - - // serialize branches - const optionsShown = branch?.branchOptions?.flat(2).join(","); - if (optionsShown) { - if (alreadyShown.has(optionsShown)) branch = undefined; - alreadyShown.add(optionsShown); - } - - return { - messageId: messageId.toString(), - firstSeenState: firstSeen, - - branch: branch?.branch, - branchOptions: branch?.branchOptions, - }; - }, - ); - })(); - - const stop = () => { - if (abortRef.current != null) abortRef.current.abort(); - abortRef.current = null; - - if (runMetadataStorage && threadId) { - const runId = runMetadataStorage.getItem(`lg:stream:${threadId}`); - if (runId) client.runs.cancel(threadId, runId); - runMetadataStorage.removeItem(`lg:stream:${threadId}`); - } - - options?.onStop?.({ mutate: getMutateFn("stop", historyValues) }); - }; - - async function consumeStream( - action: (signal: AbortSignal) => Promise<{ - onSuccess: () => Promise[]>; - stream: AsyncGenerator; - getCallbackMeta: () => { thread_id: string; run_id: string } | undefined; - }>, - ) { - let getCallbackMeta: - | (() => { thread_id: string; run_id: string } | undefined) - | undefined; - try { - setIsLoading(true); - setStreamError(undefined); - - submittingRef.current = true; - abortRef.current = new AbortController(); - - const run = await action(abortRef.current.signal); - getCallbackMeta = run.getCallbackMeta; - - let streamError: StreamError | undefined; - for await (const { event, data } of run.stream) { - if (event === "error") { - streamError = new StreamError(data); - break; - } - - if (event === "updates") options.onUpdateEvent?.(data); - if (event === "custom") - options.onCustomEvent?.(data, { - mutate: getMutateFn("stream", historyValues), - }); - if (event === "metadata") options.onMetadataEvent?.(data); - if (event === "events") options.onLangChainEvent?.(data); - if (event === "debug") options.onDebugEvent?.(data); - - if (event === "values") { - if ("__interrupt__" in data) { - // don't update values on interrupt values event - continue; - } - setStreamValues(data); - } - if (event === "messages") { - const [serialized] = data; - - const messageId = messageManagerRef.current.add(serialized); - if (!messageId) { - console.warn( - "Failed to add message to manager, no message ID found", - ); - continue; - } - - setStreamValues((streamValues) => { - const values = { ...historyValues, ...streamValues }; - - // Assumption: we're concatenating the message - const messages = getMessages(values).slice(); - const { chunk, index } = - messageManagerRef.current.get(messageId, messages.length) ?? {}; - - if (!chunk || index == null) return values; - messages[index] = toMessageDict(chunk); - - return { ...values, [messagesKey!]: messages }; - }); - } - } - - // TODO: stream created checkpoints to avoid an unnecessary network request - const result = await run.onSuccess(); - setStreamValues((values, kind) => { - // Do not clear out the user values set on `stop`. - if (kind === "stop") return values; - return null; - }); - if (streamError != null) throw streamError; - - const lastHead = result.at(0); - if (lastHead) onFinish?.(lastHead, getCallbackMeta?.()); - } catch (error) { - if ( - !( - error instanceof Error && - (error.name === "AbortError" || error.name === "TimeoutError") - ) - ) { - console.error(error); - setStreamError(error); - onError?.(error, getCallbackMeta?.()); - } - } finally { - setIsLoading(false); - - // Assumption: messages are already handled, we can clear the manager - messageManagerRef.current.clear(); - submittingRef.current = false; - abortRef.current = null; - } - } - - const joinStream = async ( - runId: string, - lastEventId?: string, - options?: { streamMode?: StreamMode | StreamMode[] }, - ) => { - lastEventId ??= "-1"; - if (!threadId) return; - await consumeStream(async (signal: AbortSignal) => { - const stream = client.runs.joinStream(threadId, runId, { - signal, - lastEventId, - streamMode: options?.streamMode, - }) as AsyncGenerator; - - return { - onSuccess: () => { - runMetadataStorage?.removeItem(`lg:stream:${threadId}`); - return history.mutate(threadId); - }, - stream, - getCallbackMeta: () => ({ thread_id: threadId, run_id: runId }), - }; - }); - }; - - const submit = async ( - values: UpdateType | null | undefined, - submitOptions?: SubmitOptions, - ) => { - await consumeStream(async (signal: AbortSignal) => { - // Unbranch things - const newPath = submitOptions?.checkpoint?.checkpoint_id - ? branchByCheckpoint[submitOptions?.checkpoint?.checkpoint_id]?.branch - : undefined; - - if (newPath != null) setBranch(newPath ?? ""); - - setStreamValues(() => { - if (submitOptions?.optimisticValues != null) { - return { - ...historyValues, - ...(typeof submitOptions.optimisticValues === "function" - ? submitOptions.optimisticValues(historyValues) - : submitOptions.optimisticValues), - }; - } - - return { ...historyValues }; - }); - - let usableThreadId = threadId; - if (!usableThreadId) { - const thread = await client.threads.create({ - threadId: submitOptions?.threadId, - }); - onThreadId(thread.thread_id); - usableThreadId = thread.thread_id; - } - - const streamMode = unique([ - ...(submitOptions?.streamMode ?? []), - ...trackStreamModeRef.current, - ...callbackStreamMode, - ]); - - const checkpoint = - submitOptions?.checkpoint ?? threadHead?.checkpoint ?? undefined; - // @ts-expect-error - if (checkpoint != null) delete checkpoint.thread_id; - let rejoinKey: `lg:stream:${string}` | undefined; - let callbackMeta: RunCallbackMeta | undefined; - const streamResumable = - submitOptions?.streamResumable ?? !!runMetadataStorage; - - const stream = client.runs.stream(usableThreadId, assistantId, { - input: values as Record, - config: submitOptions?.config, - command: submitOptions?.command, - - interruptBefore: submitOptions?.interruptBefore, - interruptAfter: submitOptions?.interruptAfter, - metadata: submitOptions?.metadata, - multitaskStrategy: submitOptions?.multitaskStrategy, - onCompletion: submitOptions?.onCompletion, - onDisconnect: - submitOptions?.onDisconnect ?? - (streamResumable ? "continue" : "cancel"), - - signal, - - checkpoint, - streamMode, - streamSubgraphs: submitOptions?.streamSubgraphs, - streamResumable, - onRunCreated(params) { - callbackMeta = { - run_id: params.run_id, - thread_id: params.thread_id ?? usableThreadId, - }; - - if (runMetadataStorage) { - rejoinKey = `lg:stream:${callbackMeta.thread_id}`; - runMetadataStorage.setItem(rejoinKey, callbackMeta.run_id); - } - onCreated?.(callbackMeta); - }, - }) as AsyncGenerator; - - return { - stream, - getCallbackMeta: () => callbackMeta, - onSuccess: () => { - if (rejoinKey) runMetadataStorage?.removeItem(rejoinKey); - return history.mutate(usableThreadId); - }, - }; - }); - }; - - const reconnectKey = useMemo(() => { - if (!runMetadataStorage || isLoading) return undefined; - if (typeof window === "undefined") return undefined; - const runId = runMetadataStorage?.getItem(`lg:stream:${threadId}`); - if (!runId) return undefined; - return { runId, threadId }; - }, [runMetadataStorage, isLoading, threadId]); - - const shouldReconnect = !!runMetadataStorage; - const reconnectRef = useRef({ threadId, shouldReconnect }); - - const joinStreamRef = useRef(joinStream); - joinStreamRef.current = joinStream; - - useEffect(() => { - // reset shouldReconnect when switching threads - if (reconnectRef.current.threadId !== threadId) { - reconnectRef.current = { threadId, shouldReconnect }; - } - }, [threadId, shouldReconnect]); - - useEffect(() => { - if (reconnectKey && reconnectRef.current.shouldReconnect) { - reconnectRef.current.shouldReconnect = false; - joinStreamRef.current?.(reconnectKey.runId); - } - }, [reconnectKey]); - - const error = streamError ?? historyError; - const values = streamValues ?? historyValues; - - return { - get values() { - trackStreamMode("values"); - return values; - }, - - client, - assistantId, - - error, - isLoading, - - stop, - submit, - - joinStream, - - branch, - setBranch, - - history: flatHistory, - experimental_branchTree: rootSequence, - - get interrupt() { - // Don't show the interrupt if the stream is loading - if (isLoading) return undefined; - - const interrupts = threadHead?.tasks?.at(-1)?.interrupts; - if (interrupts == null || interrupts.length === 0) { - // check if there's a next task present - const next = threadHead?.next ?? []; - if (!next.length || error != null) return undefined; - return { when: "breakpoint" }; - } - - // Return only the current interrupt - return interrupts.at(-1) as Interrupt | undefined; - }, - - get messages() { - trackStreamMode("messages-tuple", "values"); - return getMessages(values); - }, - - getMessagesMetadata( - message: Message, - index?: number, - ): MessageMetadata | undefined { - trackStreamMode("messages-tuple", "values"); - return messageMetadata?.find( - (m) => m.messageId === (message.id ?? index), - ); - }, - }; -} diff --git a/libs/sdk-js/src/schema.ts b/libs/sdk-js/src/schema.ts deleted file mode 100644 index 877cc7a18..000000000 --- a/libs/sdk-js/src/schema.ts +++ /dev/null @@ -1,334 +0,0 @@ -import type { JSONSchema7 } from "json-schema"; - -type Optional = T | null | undefined; - -export type RunStatus = - | "pending" - | "running" - | "error" - | "success" - | "timeout" - | "interrupted"; - -export type ThreadStatus = "idle" | "busy" | "interrupted" | "error"; - -type MultitaskStrategy = "reject" | "interrupt" | "rollback" | "enqueue"; - -export type CancelAction = "interrupt" | "rollback"; - -export type Config = { - /** - * Tags for this call and any sub-calls (eg. a Chain calling an LLM). - * You can use these to filter calls. - */ - tags?: string[]; - - /** - * Maximum number of times a call can recurse. - * If not provided, defaults to 25. - */ - recursion_limit?: number; - - /** - * Runtime values for attributes previously made configurable on this Runnable. - */ - configurable?: { - /** - * ID of the thread - */ - thread_id?: Optional; - - /** - * Timestamp of the state checkpoint - */ - checkpoint_id?: Optional; - - [key: string]: unknown; - }; -}; - -export interface GraphSchema { - /** - * The ID of the graph. - */ - graph_id: string; - - /** - * The schema for the input state. - * Missing if unable to generate JSON schema from graph. - */ - input_schema?: JSONSchema7 | null | undefined; - - /** - * The schema for the output state. - * Missing if unable to generate JSON schema from graph. - */ - output_schema?: JSONSchema7 | null | undefined; - - /** - * The schema for the graph state. - * Missing if unable to generate JSON schema from graph. - */ - state_schema?: JSONSchema7 | null | undefined; - - /** - * The schema for the graph config. - * Missing if unable to generate JSON schema from graph. - */ - config_schema?: JSONSchema7 | null | undefined; -} - -export type Subgraphs = Record; - -export type Metadata = Optional<{ - source?: "input" | "loop" | "update" | (string & {}); - - step?: number; - - writes?: Record | null; - - parents?: Record; - - [key: string]: unknown; -}>; - -export interface AssistantBase { - /** The ID of the assistant. */ - assistant_id: string; - - /** The ID of the graph. */ - graph_id: string; - - /** The assistant config. */ - config: Config; - - /** The time the assistant was created. */ - created_at: string; - - /** The assistant metadata. */ - metadata: Metadata; - - /** The version of the assistant. */ - version: number; - - /** The name of the assistant */ - name: string; - - /** The description of the assistant */ - description?: string; -} - -export interface AssistantVersion extends AssistantBase {} - -export interface Assistant extends AssistantBase { - /** The last time the assistant was updated. */ - updated_at: string; -} - -export interface AssistantGraph { - nodes: Array<{ - id: string | number; - name?: string; - // eslint-disable-next-line @typescript-eslint/no-explicit-any - data?: Record | string; - metadata?: unknown; - }>; - edges: Array<{ - source: string; - target: string; - data?: string; - conditional?: boolean; - }>; -} - -/** - * An interrupt thrown inside a thread. - */ -export interface Interrupt { - value?: TValue; - when: "during" | (string & {}); - resumable?: boolean; - ns?: string[]; -} - -export interface Thread { - /** The ID of the thread. */ - thread_id: string; - - /** The time the thread was created. */ - created_at: string; - - /** The last time the thread was updated. */ - updated_at: string; - - /** The thread metadata. */ - metadata: Metadata; - - /** The status of the thread */ - status: ThreadStatus; - - /** The current state of the thread. */ - values: ValuesType; - - /** Interrupts which were thrown in this thread */ - interrupts: Record>; -} - -export interface Cron { - /** The ID of the cron */ - cron_id: string; - - /** The ID of the assistant */ - assistant_id: string; - - /** The ID of the thread */ - thread_id: Optional; - - /** The end date to stop running the cron. */ - end_time: Optional; - - /** The schedule to run, cron format. */ - schedule: string; - - /** The time the cron was created. */ - created_at: string; - - /** The last time the cron was updated. */ - updated_at: string; - - /** The run payload to use for creating new run. */ - payload: Record; - - /** The user ID of the cron */ - user_id: Optional; - - /** The next run date of the cron */ - next_run_date: Optional; - - /** The metadata of the cron */ - metadata: Record; -} - -export type DefaultValues = Record[] | Record; - -export interface ThreadState { - /** The state values */ - values: ValuesType; - - /** The next nodes to execute. If empty, the thread is done until new input is received */ - next: string[]; - - /** Checkpoint of the thread state */ - checkpoint: Checkpoint; - - /** Metadata for this state */ - metadata: Metadata; - - /** Time of state creation */ - created_at: Optional; - - /** The parent checkpoint. If missing, this is the root checkpoint */ - parent_checkpoint: Optional; - - /** Tasks to execute in this step. If already attempted, may contain an error */ - tasks: Array; -} - -export interface ThreadTask { - id: string; - name: string; - result?: unknown; - error: Optional; - interrupts: Array; - checkpoint: Optional; - state: Optional; -} - -export interface Run { - /** The ID of the run */ - run_id: string; - - /** The ID of the thread */ - thread_id: string; - - /** The assistant that wwas used for this run */ - assistant_id: string; - - /** The time the run was created */ - created_at: string; - - /** The last time the run was updated */ - updated_at: string; - - /** The status of the run. */ - status: RunStatus; - - /** Run metadata */ - metadata: Metadata; - - /** Strategy to handle concurrent runs on the same thread */ - multitask_strategy: Optional; -} - -export type Checkpoint = { - thread_id: string; - checkpoint_ns: string; - checkpoint_id: Optional; - checkpoint_map: Optional>; -}; - -export interface ListNamespaceResponse { - namespaces: string[][]; -} -export interface Item { - namespace: string[]; - key: string; - value: Record; - createdAt: string; - updatedAt: string; -} - -export interface SearchItem extends Item { - score?: number; -} -export interface SearchItemsResponse { - items: SearchItem[]; -} - -export interface CronCreateResponse { - cron_id: string; - assistant_id: string; - thread_id: string | undefined; - user_id: string; - payload: Record; - schedule: string; - next_run_date: string; - end_time: string | undefined; - created_at: string; - updated_at: string; - metadata: Metadata; -} - -export interface CronCreateForThreadResponse - extends Omit { - thread_id: string; -} - -export type AssistantSortBy = - | "assistant_id" - | "graph_id" - | "name" - | "created_at" - | "updated_at"; - -export type ThreadSortBy = "thread_id" | "status" | "created_at" | "updated_at"; - -export type CronSortBy = - | "cron_id" - | "assistant_id" - | "thread_id" - | "created_at" - | "updated_at" - | "next_run_date"; - -export type SortOrder = "asc" | "desc"; diff --git a/libs/sdk-js/src/singletons/fetch.ts b/libs/sdk-js/src/singletons/fetch.ts deleted file mode 100644 index 8ed71b000..000000000 --- a/libs/sdk-js/src/singletons/fetch.ts +++ /dev/null @@ -1,29 +0,0 @@ -// Wrap the default fetch call due to issues with illegal invocations -// in some environments: -// https://stackoverflow.com/questions/69876859/why-does-bind-fix-failed-to-execute-fetch-on-window-illegal-invocation-err -// @ts-expect-error Broad typing to support a range of fetch implementations -const DEFAULT_FETCH_IMPLEMENTATION = (...args: any[]) => fetch(...args); - -const LANGSMITH_FETCH_IMPLEMENTATION_KEY = Symbol.for( - "lg:fetch_implementation", -); - -/** - * Overrides the fetch implementation used for LangSmith calls. - * You should use this if you need to use an implementation of fetch - * other than the default global (e.g. for dealing with proxies). - * @param fetch The new fetch function to use. - */ -export const overrideFetchImplementation = (fetch: (...args: any[]) => any) => { - (globalThis as any)[LANGSMITH_FETCH_IMPLEMENTATION_KEY] = fetch; -}; - -/** - * @internal - */ -export const _getFetchImplementation: () => (...args: any[]) => any = () => { - return ( - (globalThis as any)[LANGSMITH_FETCH_IMPLEMENTATION_KEY] ?? - DEFAULT_FETCH_IMPLEMENTATION - ); -}; diff --git a/libs/sdk-js/src/tests/fetch.test.ts b/libs/sdk-js/src/tests/fetch.test.ts deleted file mode 100644 index dc23b80c5..000000000 --- a/libs/sdk-js/src/tests/fetch.test.ts +++ /dev/null @@ -1,201 +0,0 @@ -import { describe, it, expect, beforeEach, afterEach, vi } from "vitest"; -import { Client } from "../client.js"; -import { overrideFetchImplementation } from "../singletons/fetch.js"; - -describe.each([["global"], ["mocked"]])( - "Client uses %s fetch", - (description: string) => { - let globalFetchMock: ReturnType; - let overriddenFetch: ReturnType; - - let expectedFetchMock: ReturnType; - let unexpectedFetchMock: ReturnType; - - beforeEach(() => { - globalFetchMock = vi.fn(() => - Promise.resolve({ - ok: true, - json: () => - Promise.resolve({ - batch_ingest_config: { - use_multipart_endpoint: true, - }, - }), - text: () => Promise.resolve(""), - headers: new Headers({}), - }), - ); - overriddenFetch = vi.fn(() => - Promise.resolve({ - ok: true, - json: () => - Promise.resolve({ - batch_ingest_config: { - use_multipart_endpoint: true, - }, - }), - text: () => Promise.resolve(""), - headers: new Headers({}), - }), - ); - expectedFetchMock = - description === "mocked" ? overriddenFetch : globalFetchMock; - unexpectedFetchMock = - description === "mocked" ? globalFetchMock : overriddenFetch; - - if (description === "mocked") { - overrideFetchImplementation(overriddenFetch); - } else { - overrideFetchImplementation(globalFetchMock); - } - // Mock global fetch - (globalThis as any).fetch = globalFetchMock; - }); - - afterEach(() => { - vi.restoreAllMocks(); - }); - - describe("createRuns", () => { - it("should create an example with the given input and generation", async () => { - const client = new Client({ apiKey: "test-api-key" }); - - const thread = await client.threads.create(); - expect(expectedFetchMock).toHaveBeenCalledTimes(1); - expect(unexpectedFetchMock).not.toHaveBeenCalled(); - - vi.clearAllMocks(); // Clear all mocks before the next operation - - // Then clear & run the function - await client.runs.create(thread.thread_id, "somegraph", { - input: { foo: "bar" }, - }); - expect(expectedFetchMock).toHaveBeenCalledTimes(1); - expect(unexpectedFetchMock).not.toHaveBeenCalled(); - }); - }); - - describe("header coalescing", () => { - it("should properly merge headers with conflicting name casing", async () => { - const client = new Client({ apiKey: "test-api-key" }); - await (client.threads as any).fetch("/test", { - headers: { "X-Api-Key": "custom-value" }, - }); - expect(expectedFetchMock).toHaveBeenCalledWith( - expect.any(URL), - expect.objectContaining({ - headers: expect.objectContaining({ - "x-api-key": "custom-value", - }), - }), - ); - }); - - it("should properly merge headers from multiple sources", async () => { - const client = new Client({ - apiKey: "test-api-key", - defaultHeaders: { - "x-default": "default-value", - "x-override": "default-value", - }, - }); - - await (client.threads as any).fetch("/test", { - headers: { - "x-custom": "custom-value", - "x-override": "custom-value", - }, - }); - - expect(expectedFetchMock).toHaveBeenCalledWith( - expect.any(URL), - expect.objectContaining({ - headers: expect.objectContaining({ - "x-api-key": "test-api-key", - "x-default": "default-value", - "x-custom": "custom-value", - "x-override": "custom-value", - }), - }), - ); - - vi.clearAllMocks(); - - // Test with null/undefined values - await (client.threads as any).fetch("/test", { - headers: { - "x-null": null, - "x-undefined": undefined, - "x-empty": "", - }, - }); - - expect(expectedFetchMock).toHaveBeenCalledWith( - expect.any(URL), - expect.objectContaining({ - headers: expect.objectContaining({ - "x-api-key": "test-api-key", - "x-default": "default-value", - }), - }), - ); - expect(expectedFetchMock).not.toHaveBeenCalledWith( - expect.any(URL), - expect.objectContaining({ - headers: expect.objectContaining({ - "x-null": null, - "x-undefined": undefined, - }), - }), - ); - }); - - it("should handle Headers object input", async () => { - const client = new Client({ apiKey: "test-api-key" }); - const headers = new Headers(); - headers.append("x-custom", "custom-value"); - headers.append("x-multi", "value1"); - headers.append("x-multi", "value2"); - - await (client.threads as any).fetch("/test", { headers }); - - expect(expectedFetchMock).toHaveBeenCalledWith( - expect.any(URL), - expect.objectContaining({ - headers: expect.objectContaining({ - "x-api-key": "test-api-key", - "x-custom": "custom-value", - "x-multi": "value1, value2", - }), - }), - ); - }); - - it("should handle array of header tuples", async () => { - const client = new Client({ - apiKey: "test-api-key", - defaultHeaders: { - "x-custom": "custom-value", - }, - }); - const headers = [ - ["x-multi", "value1"], - ["x-multi", "value2"], - ]; - - await (client.threads as any).fetch("/test", { headers }); - - expect(expectedFetchMock).toHaveBeenCalledWith( - expect.any(URL), - expect.objectContaining({ - headers: expect.objectContaining({ - "x-api-key": "test-api-key", - "x-custom": "custom-value", - "x-multi": "value1, value2", - }), - }), - ); - }); - }); - }, -); diff --git a/libs/sdk-js/src/tests/sse.test.ts b/libs/sdk-js/src/tests/sse.test.ts deleted file mode 100644 index 1dd6a6d94..000000000 --- a/libs/sdk-js/src/tests/sse.test.ts +++ /dev/null @@ -1,183 +0,0 @@ -import { describe, test, expect } from "vitest"; -import { Readable } from "node:stream"; -import { IterableReadableStream } from "../utils/stream.js"; -import { BytesLineDecoder, SSEDecoder } from "../utils/sse.js"; - -const gather = async (stream: ReadableStream): Promise => { - const results: T[] = []; - const iterator = IterableReadableStream.fromReadableStream(stream); - for await (const chunk of iterator) results.push(chunk); - return results; -}; - -const textEncoder = new TextEncoder(); -const textDecoder = new TextDecoder(); - -describe("BytesLineDecoder", () => { - const createStream = (chunks: Uint8Array[]) => { - return Readable.toWeb(Readable.from(chunks)) as ReadableStream; - }; - - test("handles single line with newline", async () => { - const input = createStream([textEncoder.encode("hello\n")]); - const decoded = input.pipeThrough(BytesLineDecoder()); - const results = await gather(decoded); - - expect(results.length).toBe(1); - expect(textDecoder.decode(results[0])).toBe("hello"); - }); - - test("handles multiple lines", async () => { - const input = createStream([textEncoder.encode("line1\nline2\nline3\n")]); - const decoded = input.pipeThrough(BytesLineDecoder()); - const results = await gather(decoded); - - expect(results.length).toBe(3); - expect(textDecoder.decode(results[0])).toBe("line1"); - expect(textDecoder.decode(results[1])).toBe("line2"); - expect(textDecoder.decode(results[2])).toBe("line3"); - }); - - test("handles split chunks", async () => { - const input = createStream([ - textEncoder.encode("li"), - textEncoder.encode("ne1\nli"), - textEncoder.encode("ne2\n"), - ]); - const decoded = input.pipeThrough(BytesLineDecoder()); - const results = await gather(decoded); - - expect(results.length).toBe(2); - expect(textDecoder.decode(results[0])).toBe("line1"); - expect(textDecoder.decode(results[1])).toBe("line2"); - }); - - test("handles CR LF line endings", async () => { - const input = createStream([textEncoder.encode("line1\r\nline2\r\n")]); - const decoded = input.pipeThrough(BytesLineDecoder()); - const results = await gather(decoded); - - expect(results.length).toBe(2); - expect(textDecoder.decode(results[0])).toBe("line1"); - expect(textDecoder.decode(results[1])).toBe("line2"); - }); - - test("handles split CR LF", async () => { - const input = createStream([ - textEncoder.encode("line1\r"), - textEncoder.encode("\nline2\r\n"), - ]); - const decoded = input.pipeThrough(BytesLineDecoder()); - const results = await gather(decoded); - - expect(results.length).toBe(2); - expect(textDecoder.decode(results[0])).toBe("line1"); - expect(textDecoder.decode(results[1])).toBe("line2"); - }); - - test("handles stale line", async () => { - const input = createStream([textEncoder.encode("hello")]); - const decoded = input.pipeThrough(BytesLineDecoder()); - const results = await gather(decoded); - - expect(results.length).toBe(1); - expect(textDecoder.decode(results[0])).toBe("hello"); - }); -}); - -describe("SSEDecoder", () => { - const createStream = (lines: string[]) => { - return Readable.toWeb( - Readable.from(lines.map((line) => textEncoder.encode(line))), - ) as ReadableStream; - }; - - test("decodes simple event", async () => { - const input = createStream([ - "event: test\n", - 'data: {"message": "hello"}\n', - "\n", - ]); - const decoded = input - .pipeThrough(BytesLineDecoder()) - .pipeThrough(SSEDecoder()); - - const results = await gather(decoded); - expect(results.length).toBe(1); - expect(results[0]).toEqual({ - event: "test", - data: { message: "hello" }, - }); - }); - - test("ignores comments", async () => { - const input = createStream([ - ": this is a comment\n", - "event: test\n", - 'data: {"message": "hello"}\n', - ]); - const decoded = input - .pipeThrough(BytesLineDecoder()) - .pipeThrough(SSEDecoder()); - - const results = await gather(decoded); - expect(results.length).toBe(1); - expect(results[0]).toEqual({ - event: "test", - data: { message: "hello" }, - }); - }); - - test("handles multiple events", async () => { - const input = createStream([ - "event: test1\n", - 'data: {"message": "hello"}\n', - "\n", - "event: test2\n", - 'data: {"message": "world"}\n', - "\n", - ]); - const decoded = input - .pipeThrough(BytesLineDecoder()) - .pipeThrough(SSEDecoder()); - - const results = await gather(decoded); - expect(results.length).toBe(2); - expect(results[0]).toEqual({ - event: "test1", - data: { message: "hello" }, - }); - expect(results[1]).toEqual({ - event: "test2", - data: { message: "world" }, - }); - }); - - test("end event without data", async () => { - const input = createStream(["event: test\n"]); - const decoded = input - .pipeThrough(BytesLineDecoder()) - .pipeThrough(SSEDecoder()); - - const results = await gather(decoded); - expect(results.length).toBe(1); - expect(results[0]).toEqual({ - event: "test", - data: null, - }); - }); - - test("end event without newline", async () => { - const input = createStream(["event: end"]); - const decoded = input - .pipeThrough(BytesLineDecoder()) - .pipeThrough(SSEDecoder()); - - const results = await gather(decoded); - expect(results.length).toBe(1); - expect(results[0]).toEqual({ - event: "end", - data: null, - }); - }); -}); diff --git a/libs/sdk-js/src/tests/stream.test.tsx b/libs/sdk-js/src/tests/stream.test.tsx deleted file mode 100644 index e05dde513..000000000 --- a/libs/sdk-js/src/tests/stream.test.tsx +++ /dev/null @@ -1,450 +0,0 @@ -import "@testing-library/jest-dom/vitest"; - -import { describe, it, expect, beforeEach, afterEach, vi } from "vitest"; -import { render, screen, waitFor } from "@testing-library/react"; -import { userEvent } from "@testing-library/user-event"; -import { setupServer } from "msw/node"; -import { http } from "msw"; -import { useStream } from "../react/stream.js"; -import type { Message } from "../types.messages.js"; - -import { StateGraph, MessagesAnnotation, START } from "@langchain/langgraph"; -import { MemorySaver } from "@langchain/langgraph-checkpoint"; -import { FakeStreamingChatModel } from "@langchain/core/utils/testing"; -import { AIMessage } from "@langchain/core/messages"; -import { createEmbedServer } from "@langchain/langgraph-api/experimental/embed"; -import { randomUUID } from "node:crypto"; -import { useState } from "react"; - -const threads = (() => { - const THREADS: Record< - string, - { thread_id: string; metadata: Record } - > = {}; - - return { - get: async (id: string) => THREADS[id], - put: async ( - threadId: string, - { metadata }: { metadata?: Record }, - ) => { - THREADS[threadId] = { thread_id: threadId, metadata: metadata ?? {} }; - }, - delete: async (threadId: string) => { - delete THREADS[threadId]; - }, - }; -})(); - -const checkpointer = new MemorySaver(); - -const model = new FakeStreamingChatModel({ responses: [new AIMessage("Hey")] }); -const agent = new StateGraph(MessagesAnnotation) - .addNode("agent", async (state: { messages: Message[] }) => { - const response = await model.invoke(state.messages); - return { messages: [response] }; - }) - .addEdge(START, "agent") - .compile(); - -const app = createEmbedServer({ graph: { agent }, checkpointer, threads }); -const server = setupServer(http.all("*", (ctx) => app.fetch(ctx.request))); - -function TestChatComponent() { - const { messages, isLoading, error, submit, stop } = useStream({ - assistantId: "agent", - apiKey: "test-api-key", - }); - - return ( -
-
- {messages.map((msg, i) => ( -
- {typeof msg.content === "string" - ? msg.content - : JSON.stringify(msg.content)} -
- ))} -
-
- {isLoading ? "Loading..." : "Not loading"} -
- {error ?
{String(error)}
: null} - - -
- ); -} - -describe("useStream", () => { - beforeEach(() => server.listen()); - - afterEach(() => { - server.resetHandlers(); - server.close(); - vi.clearAllMocks(); - }); - - it("renders initial state correctly", () => { - render(); - - expect(screen.getByTestId("loading")).toHaveTextContent("Not loading"); - expect(screen.getByTestId("messages")).toBeEmptyDOMElement(); - expect(screen.queryByTestId("error")).not.toBeInTheDocument(); - }); - - it("handles message submission and streaming", async () => { - const user = userEvent.setup(); - - render(); - - // Check loading state - await user.click(screen.getByTestId("submit")); - expect(screen.getByTestId("loading")).toHaveTextContent("Loading..."); - - // Wait for messages to appear - await waitFor(() => { - expect(screen.getByTestId("message-0")).toHaveTextContent("Hello"); - expect(screen.getByTestId("message-1")).toHaveTextContent("Hey"); - }); - - // Check final state - expect(screen.getByTestId("loading")).toHaveTextContent("Not loading"); - }); - - it("handles stop functionality", async () => { - const user = userEvent.setup(); - render(); - - // Start streaming and stop immediately - await user.click(screen.getByTestId("submit")); - await user.click(screen.getByTestId("stop")); - - // Check loading state is reset - await waitFor(() => { - expect(screen.getByTestId("loading")).toHaveTextContent("Not loading"); - }); - }); - - it("displays initial values immediately and clears them when submitting", async () => { - const user = userEvent.setup(); - - function TestCachedComponent() { - const { messages, values, submit } = useStream<{ - messages: Message[]; - }>({ - assistantId: "agent", - apiKey: "test-api-key", - initialValues: { - messages: [ - { id: "cached-1", type: "human", content: "Cached user message" }, - { id: "cached-2", type: "ai", content: "Cached AI response" }, - ], - }, - }); - - return ( -
-
- {messages.map((msg, i) => ( -
- {typeof msg.content === "string" - ? msg.content - : JSON.stringify(msg.content)} -
- ))} -
-
{JSON.stringify(values)}
- -
- ); - } - - render(); - - // Should immediately show cached messages - expect(screen.getByTestId("message-cached-0")).toHaveTextContent( - "Cached user message", - ); - expect(screen.getByTestId("message-cached-1")).toHaveTextContent( - "Cached AI response", - ); - - // Values should include initial values - expect(screen.getByTestId("values")).toHaveTextContent( - "Cached user message", - ); - - // Submitting should clear out the cached messages - await user.click(screen.getByTestId("submit")); - - // Wait for messages to appear - await waitFor(() => { - expect(screen.getByTestId("message-0")).toHaveTextContent("Hello"); - expect(screen.getByTestId("message-1")).toHaveTextContent("Hey"); - }); - }); - - it("accepts newThreadId option without errors", async () => { - const user = userEvent.setup(); - - const spy = vi.fn(); - const predeterminedThreadId = randomUUID(); - - // Test that newThreadId option can be passed without causing errors - function TestNewThreadComponent() { - const stream = useStream<{ messages: Message[] }>({ - assistantId: "agent", - apiKey: "test-api-key", - threadId: null, // Start with no thread - onThreadId: spy, // Mock callback - }); - - return ( -
-
- {stream.isLoading ? "Loading..." : "Not loading"} -
-
- {stream.client ? "Client ready" : "No client"} -
- -
- ); - } - - render(); - - // Should render without errors - expect(screen.getByTestId("loading")).toHaveTextContent("Not loading"); - expect(screen.getByTestId("thread-id")).toHaveTextContent("Client ready"); - - await user.click(screen.getByTestId("submit")); - expect(spy).toHaveBeenCalledWith(predeterminedThreadId); - expect(await threads.get(predeterminedThreadId)).toEqual({ - thread_id: predeterminedThreadId, - metadata: { - graph_id: "agent", - assistant_id: "agent", - }, - }); - }); - - it("onStop callback is called when stop is called", async () => { - const user = userEvent.setup(); - const onStopCallback = vi.fn(); - - function TestComponent() { - const { submit, stop } = useStream({ - assistantId: "agent", - apiKey: "test-api-key", - onStop: onStopCallback, - }); - - return ( -
- - -
- ); - } - - render(); - - // Start a stream and stop it - await user.click(screen.getByTestId("submit")); - await user.click(screen.getByTestId("stop")); - - // Verify onStop was called with mutate function - expect(onStopCallback).toHaveBeenCalledTimes(1); - expect(onStopCallback).toHaveBeenCalledWith( - expect.objectContaining({ - mutate: expect.any(Function), - }), - ); - }); - - it("onStop mutate function updates stream values immediately", async () => { - const user = userEvent.setup(); - - function TestComponent() { - const [stopped, setStopped] = useState(false); - const { submit, stop, messages } = useStream<{ messages: Message[] }>({ - assistantId: "agent", - apiKey: "test-api-key", - onStop: ({ mutate }) => { - setStopped(true); - mutate((prev) => ({ - ...prev, - messages: [ - ...(prev.messages ?? []), - { type: "ai", content: "Stream stopped" }, - ], - })); - }, - }); - - return ( -
-
- {stopped ? "Stopped" : "Not stopped"} -
-
- {messages.map((msg, i) => ( -
- {typeof msg.content === "string" - ? msg.content - : JSON.stringify(msg.content)} -
- ))} -
- - -
- ); - } - - render(); - - // Initial state - expect(screen.getByTestId("stopped-status")).toHaveTextContent( - "Not stopped", - ); - - // Start and stop stream - await user.click(screen.getByTestId("submit")); - await user.click(screen.getByTestId("stop")); - - // Verify state was updated immediately - await waitFor(() => { - expect(screen.getByTestId("stopped-status")).toHaveTextContent("Stopped"); - expect(screen.getByTestId("message-0")).toHaveTextContent( - "Stream stopped", - ); - }); - }); - - it("onStop handles functional updates correctly", async () => { - const user = userEvent.setup(); - - function TestComponent() { - const { submit, stop, values } = useStream({ - assistantId: "agent", - apiKey: "test-api-key", - initialValues: { - counter: 5, - items: ["item1", "item2"], - }, - onStop: ({ mutate }) => { - mutate((prev: any) => ({ - ...prev, - counter: (prev.counter || 0) + 10, - items: [...(prev.items || []), "stopped"], - })); - }, - }); - - return ( -
-
{(values as any).counter}
-
{(values as any).items?.join(", ")}
- - -
- ); - } - - render(); - - // Initial state - expect(screen.getByTestId("counter")).toHaveTextContent("5"); - expect(screen.getByTestId("items")).toHaveTextContent("item1, item2"); - - // Start and stop stream - await user.click(screen.getByTestId("submit")); - await user.click(screen.getByTestId("stop")); - - // Verify functional update was applied correctly - await waitFor(() => { - expect(screen.getByTestId("counter")).toHaveTextContent("15"); - expect(screen.getByTestId("items")).toHaveTextContent( - "item1, item2, stopped", - ); - }); - }); - - it("onStop is not called when stream completes naturally", async () => { - const user = userEvent.setup(); - - const onStopCallback = vi.fn(); - - function TestComponent() { - const { submit } = useStream({ - assistantId: "agent", - apiKey: "test-api-key", - onStop: onStopCallback, - }); - - return ( -
- -
- ); - } - - render(); - - // Start a stream and let it complete naturally - await user.click(screen.getByTestId("submit")); - - // Wait for stream to complete naturally - await waitFor(() => { - expect(onStopCallback).not.toHaveBeenCalled(); - }); - }); -}); diff --git a/libs/sdk-js/src/types.messages.ts b/libs/sdk-js/src/types.messages.ts deleted file mode 100644 index 26b929535..000000000 --- a/libs/sdk-js/src/types.messages.ts +++ /dev/null @@ -1,101 +0,0 @@ -type ImageDetail = "auto" | "low" | "high"; -type MessageContentImageUrl = { - type: "image_url"; - image_url: string | { url: string; detail?: ImageDetail | undefined }; -}; - -type MessageContentText = { type: "text"; text: string }; -type MessageContentComplex = MessageContentText | MessageContentImageUrl; -type MessageContent = string | MessageContentComplex[]; - -/** - * Model-specific additional kwargs, which is passed back to the underlying LLM. - */ -type MessageAdditionalKwargs = Record; - -type BaseMessage = { - additional_kwargs?: MessageAdditionalKwargs | undefined; - content: MessageContent; - id?: string | undefined; - name?: string | undefined; - response_metadata?: Record | undefined; -}; - -export type HumanMessage = BaseMessage & { - type: "human"; - example?: boolean | undefined; -}; - -export type AIMessage = BaseMessage & { - type: "ai"; - example?: boolean | undefined; - tool_calls?: - | { - name: string; - args: { [x: string]: any }; - id?: string | undefined; - type?: "tool_call" | undefined; - }[] - | undefined; - invalid_tool_calls?: - | { - name?: string | undefined; - args?: string | undefined; - id?: string | undefined; - error?: string | undefined; - type?: "invalid_tool_call" | undefined; - }[] - | undefined; - usage_metadata?: - | { - input_tokens: number; - output_tokens: number; - total_tokens: number; - input_token_details?: - | { - audio?: number | undefined; - cache_read?: number | undefined; - cache_creation?: number | undefined; - } - | undefined; - output_token_details?: - | { audio?: number | undefined; reasoning?: number | undefined } - | undefined; - } - | undefined; -}; - -export type ToolMessage = BaseMessage & { - type: "tool"; - status?: "error" | "success" | undefined; - tool_call_id: string; - /** - * Artifact of the Tool execution which is not meant to be sent to the model. - * - * Should only be specified if it is different from the message content, e.g. if only - * a subset of the full tool output is being passed as message content but the full - * output is needed in other parts of the code. - */ - // eslint-disable-next-line @typescript-eslint/no-explicit-any - artifact?: any; -}; - -export type SystemMessage = BaseMessage & { - type: "system"; -}; - -export type FunctionMessage = BaseMessage & { - type: "function"; -}; - -export type RemoveMessage = BaseMessage & { - type: "remove"; -}; - -export type Message = - | HumanMessage - | AIMessage - | ToolMessage - | SystemMessage - | FunctionMessage - | RemoveMessage; diff --git a/libs/sdk-js/src/types.stream.ts b/libs/sdk-js/src/types.stream.ts deleted file mode 100644 index 5d69c2b9f..000000000 --- a/libs/sdk-js/src/types.stream.ts +++ /dev/null @@ -1,231 +0,0 @@ -import type { Message } from "./types.messages.js"; - -/** - * Stream modes - * - "values": Stream only the state values. - * - "messages": Stream complete messages. - * - "messages-tuple": Stream (message chunk, metadata) tuples. - * - "updates": Stream updates to the state. - * - "events": Stream events occurring during execution. - * - "debug": Stream detailed debug information. - * - "custom": Stream custom events. - */ -export type StreamMode = - | "values" - | "messages" - | "updates" - | "events" - | "debug" - | "custom" - | "messages-tuple"; - -type MessageTupleMetadata = { - tags: string[]; - [key: string]: unknown; -}; - -type AsSubgraph = - { - id?: TEvent["id"]; - event: TEvent["event"] | `${TEvent["event"]}|${string}`; - data: TEvent["data"]; - }; - -/** - * Stream event with values after completion of each step. - */ -export type ValuesStreamEvent = { - id?: string; - event: "values"; - data: StateType; -}; - -/** @internal */ -export type SubgraphValuesStreamEvent = AsSubgraph< - ValuesStreamEvent ->; - -/** - * Stream event with message chunks coming from LLM invocations inside nodes. - */ -export type MessagesTupleStreamEvent = { - event: "messages"; - // TODO: add types for message and config, which do not depend on LangChain - // while making sure it's easy to keep them in sync. - data: [message: Message, config: MessageTupleMetadata]; -}; - -/** @internal */ -export type SubgraphMessagesTupleStreamEvent = - AsSubgraph; - -/** - * Metadata stream event with information about the run and thread - */ -export type MetadataStreamEvent = { - id?: string; - event: "metadata"; - data: { run_id: string; thread_id: string }; -}; - -/** - * Stream event with error information. - */ -export type ErrorStreamEvent = { - id?: string; - event: "error"; - data: { error: string; message: string }; -}; - -/** @internal */ -export type SubgraphErrorStreamEvent = AsSubgraph; - -/** - * Stream event with updates to the state after each step. - * The streamed outputs include the name of the node that - * produced the update as well as the update. - */ -export type UpdatesStreamEvent = { - id?: string; - event: "updates"; - data: { [node: string]: UpdateType }; -}; - -/** @internal */ -export type SubgraphUpdatesStreamEvent = AsSubgraph< - UpdatesStreamEvent ->; - -/** - * Streaming custom data from inside the nodes. - */ -export type CustomStreamEvent = { event: "custom"; data: T }; - -/** @internal */ -export type SubgraphCustomStreamEvent = AsSubgraph>; - -type MessagesMetadataStreamEvent = { - id?: string; - event: "messages/metadata"; - data: { [messageId: string]: { metadata: unknown } }; -}; -type MessagesCompleteStreamEvent = { - id?: string; - event: "messages/complete"; - data: Message[]; -}; -type MessagesPartialStreamEvent = { - id?: string; - event: "messages/partial"; - data: Message[]; -}; - -/** - * Message stream event specific to LangGraph Server. - * @deprecated Use `streamMode: "messages-tuple"` instead. - */ -export type MessagesStreamEvent = - | MessagesMetadataStreamEvent - | MessagesCompleteStreamEvent - | MessagesPartialStreamEvent; - -/** @internal */ -export type SubgraphMessagesStreamEvent = - | AsSubgraph - | AsSubgraph - | AsSubgraph; - -/** - * Stream event with detailed debug information. - */ -export type DebugStreamEvent = { id?: string; event: "debug"; data: unknown }; - -/** @internal */ -export type SubgraphDebugStreamEvent = AsSubgraph; - -/** - * Stream event with events occurring during execution. - */ -export type EventsStreamEvent = { - id?: string; - event: "events"; - data: { - event: - | `on_${"chat_model" | "llm" | "chain" | "tool" | "retriever" | "prompt"}_${"start" | "stream" | "end"}` - | (string & {}); - name: string; - tags: string[]; - run_id: string; - metadata: Record; - parent_ids: string[]; - data: unknown; - }; -}; - -/** @internal */ -export type SubgraphEventsStreamEvent = AsSubgraph; - -/** - * Stream event with a feedback key to signed URL map. Set `feedbackKeys` in - * the `RunsStreamPayload` to receive this event. - */ -export type FeedbackStreamEvent = { - id?: string; - event: "feedback"; - data: { [feedbackKey: string]: string }; -}; - -type GetStreamModeMap< - TStreamMode extends StreamMode | StreamMode[], - TStateType = unknown, - TUpdateType = TStateType, - TCustomType = unknown, -> = - | { - values: ValuesStreamEvent; - updates: UpdatesStreamEvent; - custom: CustomStreamEvent; - debug: DebugStreamEvent; - messages: MessagesStreamEvent; - "messages-tuple": MessagesTupleStreamEvent; - events: EventsStreamEvent; - }[TStreamMode extends StreamMode[] ? TStreamMode[number] : TStreamMode] - | ErrorStreamEvent - | MetadataStreamEvent - | FeedbackStreamEvent; - -type GetSubgraphsStreamModeMap< - TStreamMode extends StreamMode | StreamMode[], - TStateType = unknown, - TUpdateType = TStateType, - TCustomType = unknown, -> = - | { - values: SubgraphValuesStreamEvent; - updates: SubgraphUpdatesStreamEvent; - custom: SubgraphCustomStreamEvent; - debug: SubgraphDebugStreamEvent; - messages: SubgraphMessagesStreamEvent; - "messages-tuple": SubgraphMessagesTupleStreamEvent; - events: SubgraphEventsStreamEvent; - }[TStreamMode extends StreamMode[] ? TStreamMode[number] : TStreamMode] - | SubgraphErrorStreamEvent - | MetadataStreamEvent - | FeedbackStreamEvent; - -export type TypedAsyncGenerator< - TStreamMode extends StreamMode | StreamMode[] = [], - TSubgraphs extends boolean = false, - TStateType = unknown, - TUpdateType = TStateType, - TCustomType = unknown, -> = AsyncGenerator< - TSubgraphs extends true - ? GetSubgraphsStreamModeMap< - TStreamMode, - TStateType, - TUpdateType, - TCustomType - > - : GetStreamModeMap ->; diff --git a/libs/sdk-js/src/types.ts b/libs/sdk-js/src/types.ts deleted file mode 100644 index 743f714b3..000000000 --- a/libs/sdk-js/src/types.ts +++ /dev/null @@ -1,209 +0,0 @@ -import { LangChainTracer } from "@langchain/core/tracers/tracer_langchain"; -import { Checkpoint, Config, Metadata } from "./schema.js"; -import { StreamMode } from "./types.stream.js"; - -export type MultitaskStrategy = "reject" | "interrupt" | "rollback" | "enqueue"; -export type OnConflictBehavior = "raise" | "do_nothing"; -export type OnCompletionBehavior = "complete" | "continue"; -export type DisconnectMode = "cancel" | "continue"; -export type StreamEvent = - | "events" - | "metadata" - | "debug" - | "updates" - | "values" - | "messages/partial" - | "messages/metadata" - | "messages/complete" - | "messages" - | (string & {}); - -export interface Send { - node: string; - input: unknown | null; -} - -export interface Command { - /** - * An object to update the thread state with. - */ - update?: Record | [string, unknown][] | null; - - /** - * The value to return from an `interrupt` function call. - */ - resume?: unknown; - - /** - * Determine the next node to navigate to. Can be one of the following: - * - Name(s) of the node names to navigate to next. - * - `Send` command(s) to execute node(s) with provided input. - */ - goto?: Send | Send[] | string | string[]; -} - -export interface RunsInvokePayload { - /** - * Input to the run. Pass `null` to resume from the current state of the thread. - */ - input?: Record | null; - - /** - * Metadata for the run. - */ - metadata?: Metadata; - - /** - * Additional configuration for the run. - */ - config?: Config; - - /** - * Checkpoint ID for when creating a new run. - */ - checkpointId?: string; - - /** - * Checkpoint for when creating a new run. - */ - checkpoint?: Omit; - - /** - * Whether to checkpoint during the run (or only at the end/interruption). - */ - checkpointDuring?: boolean; - - /** - * Interrupt execution before entering these nodes. - */ - interruptBefore?: "*" | string[]; - - /** - * Interrupt execution after leaving these nodes. - */ - interruptAfter?: "*" | string[]; - - /** - * Strategy to handle concurrent runs on the same thread. Only relevant if - * there is a pending/inflight run on the same thread. One of: - * - "reject": Reject the new run. - * - "interrupt": Interrupt the current run, keeping steps completed until now, - and start a new one. - * - "rollback": Cancel and delete the existing run, rolling back the thread to - the state before it had started, then start the new run. - * - "enqueue": Queue up the new run to start after the current run finishes. - */ - multitaskStrategy?: MultitaskStrategy; - - /** - * Abort controller signal to cancel the run. - */ - signal?: AbortController["signal"]; - - /** - * Behavior to handle run completion. Only relevant if - * there is a pending/inflight run on the same thread. One of: - * - "complete": Complete the run. - * - "continue": Continue the run. - */ - onCompletion?: OnCompletionBehavior; - - /** - * Webhook to call when the run is complete. - */ - webhook?: string; - - /** - * Behavior to handle disconnection. Only relevant if - * there is a pending/inflight run on the same thread. One of: - * - "cancel": Cancel the run. - * - "continue": Continue the run. - */ - onDisconnect?: DisconnectMode; - - /** - * The number of seconds to wait before starting the run. - * Use to schedule future runs. - */ - afterSeconds?: number; - - /** - * Behavior if the specified run doesn't exist. Defaults to "reject". - */ - ifNotExists?: "create" | "reject"; - - /** - * One or more commands to invoke the graph with. - */ - command?: Command; - - /** - * Callback when a run is created. - */ - onRunCreated?: (params: { run_id: string; thread_id?: string }) => void; - - /** - * @internal - * For LangSmith tracing purposes only. Not part of the public API. - */ - _langsmithTracer?: LangChainTracer; -} - -export interface RunsStreamPayload< - TStreamMode extends StreamMode | StreamMode[] = [], - TSubgraphs extends boolean = false, -> extends RunsInvokePayload { - /** - * One of `"values"`, `"messages"`, `"messages-tuple"`, `"updates"`, `"events"`, `"debug"`, `"custom"`. - */ - streamMode?: TStreamMode; - - /** - * Stream output from subgraphs. By default, streams only the top graph. - */ - streamSubgraphs?: TSubgraphs; - - /** - * Whether the stream is considered resumable. - * If true, the stream can be resumed and replayed in its entirety even after disconnection. - */ - streamResumable?: boolean; - - /** - * Pass one or more feedbackKeys if you want to request short-lived signed URLs - * for submitting feedback to LangSmith with this key for this run. - */ - feedbackKeys?: string[]; -} - -export interface RunsCreatePayload extends RunsInvokePayload { - /** - * One of `"values"`, `"messages"`, `"messages-tuple"`, `"updates"`, `"events"`, `"debug"`, `"custom"`. - */ - streamMode?: StreamMode | Array; - - /** - * Stream output from subgraphs. By default, streams only the top graph. - */ - streamSubgraphs?: boolean; - - /** - * Whether the stream is considered resumable. - * If true, the stream can be resumed and replayed in its entirety even after disconnection. - */ - streamResumable?: boolean; -} - -export interface CronsCreatePayload extends RunsCreatePayload { - /** - * Schedule for running the Cron Job - */ - schedule: string; -} - -export interface RunsWaitPayload extends RunsStreamPayload { - /** - * Raise errors returned by the run. Default is `true`. - */ - raiseError?: boolean; -} diff --git a/libs/sdk-js/src/utils/async_caller.ts b/libs/sdk-js/src/utils/async_caller.ts deleted file mode 100644 index 5ee431622..000000000 --- a/libs/sdk-js/src/utils/async_caller.ts +++ /dev/null @@ -1,216 +0,0 @@ -import pRetry from "p-retry"; -import PQueueMod from "p-queue"; -import { _getFetchImplementation } from "../singletons/fetch.js"; - -const STATUS_NO_RETRY = [ - 400, // Bad Request - 401, // Unauthorized - 402, // Payment required - 403, // Forbidden - 404, // Not Found - 405, // Method Not Allowed - 406, // Not Acceptable - 407, // Proxy Authentication Required - 408, // Request Timeout - 409, // Conflict - 422, // Unprocessable Entity -]; - -type ResponseCallback = (response?: Response) => Promise; - -export interface AsyncCallerParams { - /** - * The maximum number of concurrent calls that can be made. - * Defaults to `Infinity`, which means no limit. - */ - maxConcurrency?: number; - /** - * The maximum number of retries that can be made for a single call, - * with an exponential backoff between each attempt. Defaults to 6. - */ - maxRetries?: number; - - onFailedResponseHook?: ResponseCallback; - - /** - * Specify a custom fetch implementation. - * - * By default we expect the `fetch` is available in the global scope. - */ - fetch?: typeof fetch | ((...args: any[]) => any); -} - -export interface AsyncCallerCallOptions { - signal?: AbortSignal; -} - -/** - * Do not rely on globalThis.Response, rather just - * do duck typing - */ -function isResponse(x: unknown): x is Response { - if (x == null || typeof x !== "object") return false; - return "status" in x && "statusText" in x && "text" in x; -} - -/** - * Utility error to properly handle failed requests - */ -class HTTPError extends Error { - status: number; - text: string; - - response?: Response; - - constructor(status: number, message: string, response?: Response) { - super(`HTTP ${status}: ${message}`); - this.status = status; - this.text = message; - this.response = response; - } - - static async fromResponse( - response: Response, - options?: { includeResponse?: boolean }, - ): Promise { - try { - return new HTTPError( - response.status, - await response.text(), - options?.includeResponse ? response : undefined, - ); - } catch { - return new HTTPError( - response.status, - response.statusText, - options?.includeResponse ? response : undefined, - ); - } - } -} - -/** - * A class that can be used to make async calls with concurrency and retry logic. - * - * This is useful for making calls to any kind of "expensive" external resource, - * be it because it's rate-limited, subject to network issues, etc. - * - * Concurrent calls are limited by the `maxConcurrency` parameter, which defaults - * to `Infinity`. This means that by default, all calls will be made in parallel. - * - * Retries are limited by the `maxRetries` parameter, which defaults to 5. This - * means that by default, each call will be retried up to 5 times, with an - * exponential backoff between each attempt. - */ -export class AsyncCaller { - protected maxConcurrency: AsyncCallerParams["maxConcurrency"]; - - protected maxRetries: AsyncCallerParams["maxRetries"]; - - private queue: (typeof import("p-queue"))["default"]["prototype"]; - - private onFailedResponseHook?: ResponseCallback; - - private customFetch?: typeof fetch; - - constructor(params: AsyncCallerParams) { - this.maxConcurrency = params.maxConcurrency ?? Infinity; - this.maxRetries = params.maxRetries ?? 4; - - if ("default" in PQueueMod) { - // eslint-disable-next-line @typescript-eslint/no-explicit-any - this.queue = new (PQueueMod.default as any)({ - concurrency: this.maxConcurrency, - }); - } else { - // eslint-disable-next-line @typescript-eslint/no-explicit-any - this.queue = new (PQueueMod as any)({ concurrency: this.maxConcurrency }); - } - this.onFailedResponseHook = params?.onFailedResponseHook; - this.customFetch = params.fetch; - } - - // eslint-disable-next-line @typescript-eslint/no-explicit-any - call Promise>( - callable: T, - ...args: Parameters - ): Promise>> { - const onFailedResponseHook = this.onFailedResponseHook; - return this.queue.add( - () => - pRetry( - () => - callable(...(args as Parameters)).catch(async (error) => { - // eslint-disable-next-line no-instanceof/no-instanceof - if (error instanceof Error) { - throw error; - } else if (isResponse(error)) { - throw await HTTPError.fromResponse(error, { - includeResponse: !!onFailedResponseHook, - }); - } else { - throw new Error(error); - } - }), - { - async onFailedAttempt(error) { - if ( - error.message.startsWith("Cancel") || - error.message.startsWith("TimeoutError") || - error.message.startsWith("AbortError") - ) { - throw error; - } - // eslint-disable-next-line @typescript-eslint/no-explicit-any - if ((error as any)?.code === "ECONNABORTED") { - throw error; - } - - if (error instanceof HTTPError) { - if (STATUS_NO_RETRY.includes(error.status)) { - throw error; - } - if (onFailedResponseHook && error.response) { - await onFailedResponseHook(error.response); - } - } - }, - // If needed we can change some of the defaults here, - // but they're quite sensible. - retries: this.maxRetries, - randomize: true, - }, - ), - { throwOnTimeout: true }, - ); - } - - // eslint-disable-next-line @typescript-eslint/no-explicit-any - callWithOptions Promise>( - options: AsyncCallerCallOptions, - callable: T, - ...args: Parameters - ): Promise>> { - // Note this doesn't cancel the underlying request, - // when available prefer to use the signal option of the underlying call - if (options.signal) { - return Promise.race([ - this.call(callable, ...args), - new Promise((_, reject) => { - options.signal?.addEventListener("abort", () => { - reject(new Error("AbortError")); - }); - }), - ]); - } - return this.call(callable, ...args); - } - - fetch(...args: Parameters): ReturnType { - const fetchFn = - this.customFetch ?? (_getFetchImplementation() as typeof fetch); - return this.call(() => - fetchFn(...args).then((res) => (res.ok ? res : Promise.reject(res))), - ); - } -} diff --git a/libs/sdk-js/src/utils/env.ts b/libs/sdk-js/src/utils/env.ts deleted file mode 100644 index 738c14fd5..000000000 --- a/libs/sdk-js/src/utils/env.ts +++ /dev/null @@ -1,11 +0,0 @@ -export function getEnvironmentVariable(name: string): string | undefined { - // Certain setups (Deno, frontend) will throw an error if you try to access environment variables - try { - return typeof process !== "undefined" - ? // eslint-disable-next-line no-process-env - process.env?.[name] - : undefined; - } catch (e) { - return undefined; - } -} diff --git a/libs/sdk-js/src/utils/signals.ts b/libs/sdk-js/src/utils/signals.ts deleted file mode 100644 index 915753325..000000000 --- a/libs/sdk-js/src/utils/signals.ts +++ /dev/null @@ -1,22 +0,0 @@ -export function mergeSignals(...signals: (AbortSignal | null | undefined)[]) { - const nonZeroSignals = signals.filter( - (signal): signal is AbortSignal => signal != null, - ); - - if (nonZeroSignals.length === 0) return undefined; - if (nonZeroSignals.length === 1) return nonZeroSignals[0]; - - const controller = new AbortController(); - for (const signal of signals) { - if (signal?.aborted) { - controller.abort(signal.reason); - return controller.signal; - } - - signal?.addEventListener("abort", () => controller.abort(signal.reason), { - once: true, - }); - } - - return controller.signal; -} diff --git a/libs/sdk-js/src/utils/sse.ts b/libs/sdk-js/src/utils/sse.ts deleted file mode 100644 index a080922f5..000000000 --- a/libs/sdk-js/src/utils/sse.ts +++ /dev/null @@ -1,175 +0,0 @@ -const CR = "\r".charCodeAt(0); -const LF = "\n".charCodeAt(0); -const NULL = "\0".charCodeAt(0); -const COLON = ":".charCodeAt(0); -const SPACE = " ".charCodeAt(0); - -const TRAILING_NEWLINE = [CR, LF]; - -export function BytesLineDecoder() { - let buffer: Uint8Array[] = []; - let trailingCr = false; - - return new TransformStream({ - start() { - buffer = []; - trailingCr = false; - }, - - transform(chunk, controller) { - // See https://docs.python.org/3/glossary.html#term-universal-newlines - let text = chunk; - - // Handle trailing CR from previous chunk - if (trailingCr) { - text = joinArrays([[CR], text]); - trailingCr = false; - } - - // Check for trailing CR in current chunk - if (text.length > 0 && text.at(-1) === CR) { - trailingCr = true; - text = text.subarray(0, -1); - } - - if (!text.length) return; - const trailingNewline = TRAILING_NEWLINE.includes(text.at(-1)!); - - const lastIdx = text.length - 1; - const { lines } = text.reduce<{ lines: Uint8Array[]; from: number }>( - (acc, cur, idx) => { - if (acc.from > idx) return acc; - - if (cur === CR || cur === LF) { - acc.lines.push(text.subarray(acc.from, idx)); - if (cur === CR && text[idx + 1] === LF) { - acc.from = idx + 2; - } else { - acc.from = idx + 1; - } - } - - if (idx === lastIdx && acc.from <= lastIdx) { - acc.lines.push(text.subarray(acc.from)); - } - - return acc; - }, - { lines: [], from: 0 }, - ); - - if (lines.length === 1 && !trailingNewline) { - buffer.push(lines[0]); - return; - } - - if (buffer.length) { - // Include existing buffer in first line - buffer.push(lines[0]); - lines[0] = joinArrays(buffer); - buffer = []; - } - - if (!trailingNewline) { - // If the last segment is not newline terminated, - // buffer it for the next chunk - if (lines.length) buffer = [lines.pop()!]; - } - - // Enqueue complete lines - for (const line of lines) { - controller.enqueue(line); - } - }, - - flush(controller) { - if (buffer.length) { - controller.enqueue(joinArrays(buffer)); - } - }, - }); -} - -interface StreamPart { - id: string | undefined; - event: string; - data: unknown; -} - -export function SSEDecoder() { - let event = ""; - let data: Uint8Array[] = []; - let lastEventId = ""; - let retry: number | null = null; - - const decoder = new TextDecoder(); - - return new TransformStream({ - transform(chunk, controller) { - // Handle empty line case - if (!chunk.length) { - if (!event && !data.length && !lastEventId && retry == null) return; - - const sse = { - id: lastEventId || undefined, - event, - data: data.length ? decodeArraysToJson(decoder, data) : null, - }; - - // NOTE: as per the SSE spec, do not reset lastEventId - event = ""; - data = []; - retry = null; - - controller.enqueue(sse); - return; - } - - // Ignore comments - if (chunk[0] === COLON) return; - - const sepIdx = chunk.indexOf(COLON); - if (sepIdx === -1) return; - - const fieldName = decoder.decode(chunk.subarray(0, sepIdx)); - let value = chunk.subarray(sepIdx + 1); - if (value[0] === SPACE) value = value.subarray(1); - - if (fieldName === "event") { - event = decoder.decode(value); - } else if (fieldName === "data") { - data.push(value); - } else if (fieldName === "id") { - if (value.indexOf(NULL) === -1) lastEventId = decoder.decode(value); - } else if (fieldName === "retry") { - const retryNum = Number.parseInt(decoder.decode(value)); - if (!Number.isNaN(retryNum)) retry = retryNum; - } - }, - - flush(controller) { - if (event) { - controller.enqueue({ - id: lastEventId || undefined, - event, - data: data.length ? decodeArraysToJson(decoder, data) : null, - }); - } - }, - }); -} - -function joinArrays(data: ArrayLike[]) { - const totalLength = data.reduce((acc, curr) => acc + curr.length, 0); - let merged = new Uint8Array(totalLength); - let offset = 0; - for (const c of data) { - merged.set(c, offset); - offset += c.length; - } - return merged; -} - -function decodeArraysToJson(decoder: TextDecoder, data: ArrayLike[]) { - return JSON.parse(decoder.decode(joinArrays(data))); -} diff --git a/libs/sdk-js/src/utils/stream.ts b/libs/sdk-js/src/utils/stream.ts deleted file mode 100644 index 510204992..000000000 --- a/libs/sdk-js/src/utils/stream.ts +++ /dev/null @@ -1,115 +0,0 @@ -// in this case don't quite match. -type IterableReadableStreamInterface = ReadableStream & AsyncIterable; - -/* - * Support async iterator syntax for ReadableStreams in all environments. - * Source: https://github.com/MattiasBuelens/web-streams-polyfill/pull/122#issuecomment-1627354490 - */ -export class IterableReadableStream - extends ReadableStream - implements IterableReadableStreamInterface -{ - public reader: ReadableStreamDefaultReader; - - ensureReader() { - if (!this.reader) { - this.reader = this.getReader(); - } - } - - async next(): Promise> { - this.ensureReader(); - try { - const result = await this.reader.read(); - if (result.done) { - this.reader.releaseLock(); // release lock when stream becomes closed - return { - done: true, - value: undefined, - }; - } else { - return { - done: false, - value: result.value, - }; - } - } catch (e) { - this.reader.releaseLock(); // release lock when stream becomes errored - throw e; - } - } - - async return(): Promise> { - this.ensureReader(); - // If wrapped in a Node stream, cancel is already called. - if (this.locked) { - const cancelPromise = this.reader.cancel(); // cancel first, but don't await yet - this.reader.releaseLock(); // release lock first - await cancelPromise; // now await it - } - return { done: true, value: undefined }; - } - - // eslint-disable-next-line @typescript-eslint/no-explicit-any - async throw(e: any): Promise> { - this.ensureReader(); - if (this.locked) { - const cancelPromise = this.reader.cancel(); // cancel first, but don't await yet - this.reader.releaseLock(); // release lock first - await cancelPromise; // now await it - } - throw e; - } - - // eslint-disable-next-line @typescript-eslint/ban-ts-comment - // @ts-ignore Not present in Node 18 types, required in latest Node 22 - async [Symbol.asyncDispose]() { - await this.return(); - } - - [Symbol.asyncIterator]() { - return this; - } - - static fromReadableStream(stream: ReadableStream) { - // From https://developer.mozilla.org/en-US/docs/Web/API/Streams_API/Using_readable_streams#reading_the_stream - const reader = stream.getReader(); - return new IterableReadableStream({ - start(controller) { - return pump(); - function pump(): Promise { - return reader.read().then(({ done, value }) => { - // When no more data needs to be consumed, close the stream - if (done) { - controller.close(); - return; - } - // Enqueue the next data chunk into our target stream - controller.enqueue(value); - return pump(); - }); - } - }, - cancel() { - reader.releaseLock(); - }, - }); - } - - static fromAsyncGenerator(generator: AsyncGenerator) { - return new IterableReadableStream({ - async pull(controller) { - const { value, done } = await generator.next(); - // When no more data needs to be consumed, close the stream - if (done) { - controller.close(); - } - // Fix: `else if (value)` will hang the streaming when nullish value (e.g. empty string) is pulled - controller.enqueue(value); - }, - async cancel(reason) { - await generator.return(reason); - }, - }); - } -} diff --git a/libs/sdk-js/tsconfig.cjs.json b/libs/sdk-js/tsconfig.cjs.json deleted file mode 100644 index 6f1705b8b..000000000 --- a/libs/sdk-js/tsconfig.cjs.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - "extends": "./tsconfig.json", - "compilerOptions": { - "module": "CommonJS", - "moduleResolution": "Node", - "declaration": false - }, - "exclude": ["node_modules", "dist", "**/tests"] -} diff --git a/libs/sdk-js/tsconfig.json b/libs/sdk-js/tsconfig.json deleted file mode 100644 index d5c1626ab..000000000 --- a/libs/sdk-js/tsconfig.json +++ /dev/null @@ -1,33 +0,0 @@ -{ - "extends": "@tsconfig/recommended", - "compilerOptions": { - "target": "ES2021", - "lib": ["ES2021", "ES2022.Object", "ES2022.Error", "DOM"], - "module": "NodeNext", - "moduleResolution": "nodenext", - "esModuleInterop": true, - "declaration": true, - "noImplicitReturns": true, - "noFallthroughCasesInSwitch": true, - "noUnusedLocals": true, - "noUnusedParameters": true, - "useDefineForClassFields": true, - "strictPropertyInitialization": false, - "allowJs": true, - "strict": true, - "jsx": "react-jsx", - "outDir": "dist" - }, - "include": ["src/**/*"], - "exclude": ["node_modules", "dist", "coverage"], - "includeVersion": true, - "typedocOptions": { - "entryPoints": ["src/client.ts"], - "readme": "none", - "out": "docs", - "plugin": ["typedoc-plugin-markdown"], - "excludePrivate": true, - "excludeProtected": true, - "excludeExternals": false - } -} diff --git a/libs/sdk-js/typedoc.auth.json b/libs/sdk-js/typedoc.auth.json deleted file mode 100644 index 1cb718f4a..000000000 --- a/libs/sdk-js/typedoc.auth.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "pageTitleTemplates": { - "index": "{projectName}/auth" - } -} diff --git a/libs/sdk-js/typedoc.react.json b/libs/sdk-js/typedoc.react.json deleted file mode 100644 index 6359dac1b..000000000 --- a/libs/sdk-js/typedoc.react.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "pageTitleTemplates": { - "index": "{projectName}/react" - } -} diff --git a/libs/sdk-js/vitest.config.ts b/libs/sdk-js/vitest.config.ts deleted file mode 100644 index 01f2a7fac..000000000 --- a/libs/sdk-js/vitest.config.ts +++ /dev/null @@ -1,11 +0,0 @@ -import react from "@vitejs/plugin-react"; -import { defineConfig } from "vitest/config"; - -export default defineConfig({ - plugins: [react()], - test: { - environment: "jsdom", - globals: true, - include: ["src/**/*.test.ts", "src/**/*.test.tsx"], - }, -}); diff --git a/libs/sdk-js/yarn.lock b/libs/sdk-js/yarn.lock deleted file mode 100644 index 0e4e00cc2..000000000 --- a/libs/sdk-js/yarn.lock +++ /dev/null @@ -1,5259 +0,0 @@ -# THIS IS AN AUTOGENERATED FILE. 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