diff --git a/.github/ISSUE_TEMPLATE/config.yml b/.github/ISSUE_TEMPLATE/config.yml index 8ab0b8d23..cd9f8270a 100644 --- a/.github/ISSUE_TEMPLATE/config.yml +++ b/.github/ISSUE_TEMPLATE/config.yml @@ -1,6 +1,9 @@ blank_issues_enabled: false version: 2.1 contact_links: + - name: Documentation + url: https://github.com/langchain-ai/docs/issues/new?template=langgraph.yml + about: Report an issue related to the LangGraph documentation - name: LangChain Forum url: https://forum.langchain.com/ - about: General community discussions, support, and feature requests + about: General community discussions and support diff --git a/.github/ISSUE_TEMPLATE/documentation.yml b/.github/ISSUE_TEMPLATE/documentation.yml deleted file mode 100644 index fa48adb58..000000000 --- a/.github/ISSUE_TEMPLATE/documentation.yml +++ /dev/null @@ -1,19 +0,0 @@ -name: Documentation -description: Report an issue related to the LangGraph documentation. -title: "DOC: " -labels: [documentation] - -body: -- type: textarea - attributes: - label: "Issue with current documentation:" - description: > - Please make sure to leave a reference to the document/code you're - referring to. - -- type: textarea - attributes: - label: "Idea or request for content:" - description: > - Please describe as clearly as possible what topics you think are missing - from the current documentation. \ No newline at end of file diff --git a/.github/workflows/_integration_test.yml b/.github/workflows/_integration_test.yml index b55e23664..b5b1886af 100644 --- a/.github/workflows/_integration_test.yml +++ b/.github/workflows/_integration_test.yml @@ -14,6 +14,19 @@ jobs: python-version: - "3.10" - "3.11" + example: + - name: A + workdir: libs/cli/examples + tag: langgraph-test-a + - name: B + workdir: libs/cli/examples/graphs + tag: langgraph-test-b + - name: C + workdir: libs/cli/examples/graphs_reqs_a + tag: langgraph-test-c + - name: D + workdir: libs/cli/examples/graphs_reqs_b + tag: langgraph-test-d name: "CLI integration test" defaults: run: @@ -33,54 +46,24 @@ jobs: enable-cache: true cache-suffix: "cli-integration-test" ignore-nothing-to-cache: true - - name: Setup env - if: steps.changed-files.outputs.all - working-directory: libs/cli/examples - run: cat .env.example > .env - name: Install cli globally if: steps.changed-files.outputs.all run: pip install -e . - - name: Build and test service A + - name: Build and test service ${{ matrix.example.name }} if: steps.changed-files.outputs.all - working-directory: libs/cli/examples + working-directory: ${{ matrix.example.workdir }} env: LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }} run: | - # The build-arg isn't used; just testing that we accept other args - langgraph build -t langgraph-test-a - cp .env.example .env - if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi - timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -c langgraph.json -t langgraph-test-a - - name: Build and test service B - if: steps.changed-files.outputs.all - working-directory: libs/cli/examples/graphs - env: - LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }} - run: | - langgraph build -t langgraph-test-b - cp ../.env.example .env - if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi - timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-b - - name: Build and test service C - if: steps.changed-files.outputs.all - working-directory: libs/cli/examples/graphs_reqs_a - env: - LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }} - run: | - langgraph build -t langgraph-test-c - cp ../.env.example .env - if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi - timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-c - - name: Build and test service D - if: steps.changed-files.outputs.all - working-directory: libs/cli/examples/graphs_reqs_b - env: - LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }} - run: | - langgraph build -t langgraph-test-d - cp ../.env.example .env - if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi - timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-d + # Build the image for this example + langgraph build -t ${{ matrix.example.tag }} + # Prepare environment file from local or parent example directory + if [ -f .env.example ]; then cp .env.example .env; elif [ -f ../.env.example ]; then cp ../.env.example .env && cp ../.env.example ../.env; fi + if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; if [ -f ../.env ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> ../.env; fi; fi + # Run the integration test using the built tag + # Compute repo root to reference the shared script robustly + REPO_ROOT=$(git rev-parse --show-toplevel) + timeout 60 python "$REPO_ROOT/.github/scripts/run_langgraph_cli_test.py" -t ${{ matrix.example.tag }} - name: Build JS service if: steps.changed-files.outputs.all @@ -111,3 +94,17 @@ jobs: cp ../.env.example .env if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-h + LANGGRAPH_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langgraph'); print(v);") + if [ "$LANGGRAPH_VERSION" != "1.0.0a2" ]; then + exit 1 + fi + LANGCHAIN_OPENAI_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-openai'); print(v);") + if [ "$LANGCHAIN_OPENAI_VERSION" != "0.3.0" ]; then + exit 1 + fi + + - name: Build and test prerelease reqs fail service + if: steps.changed-files.outputs.all + working-directory: libs/cli/examples/graph_prerelease_reqs_fail + run: | + langgraph build -t langgraph-test-i || [ $? -eq 1 ] diff --git a/.github/workflows/_test_release.yml b/.github/workflows/_test_release.yml index 4e88d1c04..483b1e2df 100644 --- a/.github/workflows/_test_release.yml +++ b/.github/workflows/_test_release.yml @@ -76,7 +76,7 @@ jobs: steps: - uses: actions/checkout@v5 - - uses: actions/download-artifact@v4 + - uses: actions/download-artifact@v5 with: name: test-dist path: ${{ inputs.working-directory }}/dist/ diff --git a/.github/workflows/bench.yml b/.github/workflows/bench.yml index 7061e2852..a3c9b8466 100644 --- a/.github/workflows/bench.yml +++ b/.github/workflows/bench.yml @@ -57,7 +57,7 @@ jobs: echo EOF } >> "$GITHUB_OUTPUT" - name: Annotation - uses: actions/github-script@v7 + uses: actions/github-script@v8 with: script: | const file = JSON.parse(`${{ steps.files.outputs.added_modified_renamed }}`)[0] diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index cfa8fd2bc..26024cf8a 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -269,7 +269,7 @@ jobs: enable-cache: true cache-suffix: "release" - - uses: actions/download-artifact@v4 + - uses: actions/download-artifact@v5 with: name: dist path: ${{ inputs.working-directory }}/dist/ @@ -310,7 +310,7 @@ jobs: enable-cache: true cache-suffix: "release" - - uses: actions/download-artifact@v4 + - uses: actions/download-artifact@v5 with: name: dist path: ${{ inputs.working-directory }}/dist/ diff --git a/.github/workflows/uv_lock_ugprade.yml b/.github/workflows/uv_lock_ugprade.yml index 72d31e94a..5bf89fdcd 100644 --- a/.github/workflows/uv_lock_ugprade.yml +++ b/.github/workflows/uv_lock_ugprade.yml @@ -33,8 +33,8 @@ jobs: uses: peter-evans/create-pull-request@v7 with: token: ${{ secrets.GITHUB_TOKEN }} - commit-message: "chore[deps]: upgrade dependencies with `uv lock --upgrade`" - title: "chore[deps]: upgrade dependencies with `uv lock --upgrade`" + commit-message: "chore(deps): upgrade dependencies with `uv lock --upgrade`" + title: "chore(deps): upgrade dependencies with `uv lock --upgrade`" body: | This PR updates the dependencies in all Python packages using `uv lock --upgrade`. diff --git a/docs/README.md b/docs/README.md index 369f196a2..ddbef9d0b 100644 --- a/docs/README.md +++ b/docs/README.md @@ -1,24 +1,126 @@ -# Setup +# LangGraph Documentation -To setup requirements for building docs you can run: +For more information on contributing to our documentation, see the [Contributing Guide](../CONTRIBUTING.md). -```bash -uv sync --group test +## Structure + +The primary documentation is located in the `docs/` directory. This directory contains both the source files for the main documentation as well as the API reference doc build process. + +### Main Documentation + +Main documentation files are located in `docs/docs/` and are written in Markdown format. The site uses [**MkDocs**](https://www.mkdocs.org/) with the [Material theme](https://squidfunk.github.io/mkdocs-material/) and includes: + +- **Concepts**: Core LangGraph concepts and explanations +- **Tutorials**: Step-by-step learning guides +- **How-tos**: Task-focused guides for specific use cases +- **Examples**: Real-world applications and use cases +- **Jupyter Notebooks**: Interactive tutorials that are automatically converted to markdown + +### API Reference + +API reference documentation is defined in `docs/docs/reference/`. Each `.md` file outlines the "template" that each page is built from. Reference content is automatically generated from docstrings in the codebase using the **mkdocstrings** plugin. Once generated, the content is plugged into the corresponding markdown file where it is referenced by using manual directives to specify which classes and/or functions are documented: + +```markdown +::: langgraph.graph.state.StateGraph + options: + show_if_no_docstring: true + show_root_heading: true + show_root_full_path: false + members: + - add_node + - add_edge + - add_conditional_edges + - add_sequence + - compile ``` -## Serving documentation locally +## Build Process -To run the documentation server locally you can run: +Docs are built following these steps: + +1. **Content Processing:** + - `_scripts/notebook_hooks.py` - Main processing pipeline that: + - Converts how-tos/tutorial Jupyter notebooks to markdown using `notebook_convert.py` + - Adds automatic API reference links to code blocks using `generate_api_reference_links.py` + - Handles conditional rendering for Python/JS versions + - Processes highlight comments and custom syntax + +2. **API Reference Generation:** + - **mkdocstrings** plugin extracts docstrings from Python source code + - Manual `::: module.Class` directives in reference pages (`/docs/docs/*`) specify what to document + - Cross-references are automatically generated between docs and API + +3. **Site Generation:** + - **MkDocs** processes all markdown files and generates static HTML + - Custom hooks handle redirects and inject additional functionality + +4. **Deployment:** + - Site is deployed with Vercel + - `make build-docs` generates production build (also usable for local testing) + - Automatic redirects handle URL changes between versions + +### Local Development + +For local development, use the Makefile targets: ```bash +# Serve docs locally with hot reloading make serve-docs + +# Clean build for production testing +make build-docs + +# Serve with clean build +make serve-clean-docs ``` -This will start the documentation server on [http://127.0.0.1:8000/langgraph/](http://127.0.0.1:8000/langgraph/). +The `serve-docs` command: + +- Watches source files for changes +- Includes dirty builds for faster iteration +- Serves on [http://127.0.0.1:8000/langgraph/](http://127.0.0.1:8000/langgraph/) + +## Standards + +**Docstring Format:** +The API reference uses **Google-style docstrings** with Markdown markup. The `mkdocstrings` plugin processes these to generate documentation. + +**Required format:** + +```python +def example_function(param1: str, param2: int = 5) -> bool: + """Brief description of the function. + + Longer description can go here. Use Markdown syntax for + rich formatting like **bold** and *italic*. + + Args: + param1: Description of the first parameter. + param2: Description of the second parameter with default value. + + Returns: + Description of the return value. + + Raises: + ValueError: When param1 is empty. + TypeError: When param2 is not an integer. + + !!! warning + This function is experimental and may change. + + !!! version-added "Added in version 0.2.0" + """ +``` + +**Special Markers:** + +- **MkDocs admonitions**: `!!! warning`, `!!! note`, `!!! version-added` +- **Code blocks**: Standard markdown ``` syntax +- **Cross-references**: Automatic linking via `generate_api_reference_links.py` ## Execute notebooks -If you would like to automatically execute all of the notebooks, to mimic the "Run notebooks" GHA, you can run: +If you would like to automatically execute all of the notebooks, to mimic the "Run notebooks" GitHub action, you can run: ```bash python _scripts/prepare_notebooks_for_ci.py @@ -33,8 +135,9 @@ python _scripts/prepare_notebooks_for_ci.py --comment-install-cells ``` `prepare_notebooks_for_ci.py` script will add VCR cassette context manager for each cell in the notebook, so that: -* when the notebook is run for the first time, cells with network requests will be recorded to a VCR cassette file -* when the notebook is run subsequently, the cells with network requests will be replayed from the cassettes + +- when the notebook is run for the first time, cells with network requests will be recorded to a VCR cassette file +- when the notebook is run subsequently, the cells with network requests will be replayed from the cassettes ## Adding new notebooks diff --git a/docs/_scripts/generate_api_reference_links.py b/docs/_scripts/generate_api_reference_links.py index 1d65516dd..89d614bd5 100644 --- a/docs/_scripts/generate_api_reference_links.py +++ b/docs/_scripts/generate_api_reference_links.py @@ -1,3 +1,5 @@ +"""Generate API reference links for imports in Python code blocks within markdown files.""" + import ast import importlib import logging @@ -70,8 +72,18 @@ MANUAL_API_REFERENCES_LANGGRAPH = [ ([], "langgraph.checkpoint.postgres.aio", "AsyncPostgresSaver", "checkpoints"), ([], "langgraph.checkpoint.postgres", "PostgresSaver", "checkpoints"), # other prebuilts - (["langgraph_supervisor"], "langgraph_supervisor.supervisor", "create_supervisor", "supervisor"), - (["langgraph_supervisor"], "langgraph_supervisor.handoff", "create_handoff_tool", "supervisor"), + ( + ["langgraph_supervisor"], + "langgraph_supervisor.supervisor", + "create_supervisor", + "supervisor", + ), + ( + ["langgraph_supervisor"], + "langgraph_supervisor.handoff", + "create_handoff_tool", + "supervisor", + ), ([], "langgraph_supervisor.handoff", "create_forward_message_tool", "supervisor"), (["langgraph_swarm"], "langgraph_swarm.swarm", "create_swarm", "swarm"), (["langgraph_swarm"], "langgraph_swarm.swarm", "add_active_agent_router", "swarm"), diff --git a/docs/_scripts/js_translation/codeblocks/.yarn/install-state.gz b/docs/_scripts/js_translation/codeblocks/.yarn/install-state.gz index 625ab3e67..372ab66c9 100644 Binary files a/docs/_scripts/js_translation/codeblocks/.yarn/install-state.gz and b/docs/_scripts/js_translation/codeblocks/.yarn/install-state.gz differ diff --git a/docs/_scripts/js_translation/codeblocks/yarn.lock b/docs/_scripts/js_translation/codeblocks/yarn.lock index 2891897a8..3ad966f9f 100644 --- a/docs/_scripts/js_translation/codeblocks/yarn.lock +++ b/docs/_scripts/js_translation/codeblocks/yarn.lock @@ -2108,9 +2108,9 @@ __metadata: linkType: hard "hono@npm:^4.5.4": - version: 4.9.6 - resolution: "hono@npm:4.9.6" - checksum: 10c0/182a144eb3b9e05bd9e43d15af15c93f60d3d747fef6c6904b9993e9db8129ea7fadf6190331d6f76b1bf6dd2b2c3b13efea105236f541ef411397e30475422d + version: 4.9.7 + resolution: "hono@npm:4.9.7" + checksum: 10c0/089184660a9211ea216ab95bafa45260e371651cb019db49828064b7982b0ae61cc3c4715324bfeb9037aa2460c39ffa2c91d84ad0c8d500fa77cbcc7fc07a8f languageName: node linkType: hard diff --git a/docs/_scripts/notebook_convert.py b/docs/_scripts/notebook_convert.py index 41c74f194..1ec3fcec5 100644 --- a/docs/_scripts/notebook_convert.py +++ b/docs/_scripts/notebook_convert.py @@ -1,3 +1,5 @@ +"""Convert Jupyter notebooks to markdown with custom processing.""" + import ast import os import re diff --git a/docs/docs/concepts/multi_agent.md b/docs/docs/concepts/multi_agent.md index 53f8bb3cd..752b8cc6b 100644 --- a/docs/docs/concepts/multi_agent.md +++ b/docs/docs/concepts/multi_agent.md @@ -897,5 +897,5 @@ 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/how-tos/graph-api.md b/docs/docs/how-tos/graph-api.md index 9a64d5cd8..7fbd084c8 100644 --- a/docs/docs/how-tos/graph-api.md +++ b/docs/docs/how-tos/graph-api.md @@ -1019,7 +1019,7 @@ console.log(await graph.invoke({}, { configurable: { myRuntimeValue: "b" } })); # Usage input_message = {"role": "user", "content": "hi"} # With no configuration, uses default (Anthropic) - response_1 = graph.invoke({"messages": [input_message]})["messages"][-1] + response_1 = graph.invoke({"messages": [input_message]}, context=ContextSchema())["messages"][-1] # Or, can set OpenAI response_2 = graph.invoke({"messages": [input_message]}, context={"model_provider": "openai"})["messages"][-1] @@ -2110,7 +2110,6 @@ 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() ``` diff --git a/docs/overrides/main.html b/docs/overrides/main.html index 54909ed89..e2089ffe0 100644 --- a/docs/overrides/main.html +++ b/docs/overrides/main.html @@ -291,7 +291,7 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src= } .md-banner { - background-color: #CFC9FA; + background-color: #FFAE42; color: #000000; } @@ -360,5 +360,5 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src= {% endblock %} {% block announce %} -Our new LangChain Academy Course Deep Research with LangGraph is now live! Enroll for free. +These docs will be deprecated and removed with the release of LangGraph v1.0 in October 2025. Visit the v1.0 alpha docs {% endblock %} diff --git a/docs/pyproject.toml b/docs/pyproject.toml index 72ef5cd1f..7650912db 100644 --- a/docs/pyproject.toml +++ b/docs/pyproject.toml @@ -7,14 +7,14 @@ name = "langgraph-docs" version = "0.0.1" description = "LangGraph docs" authors = [] -requires-python = "~=3.11" +requires-python = ">=3.11.0,<4.0.0" readme = "README.md" license = "MIT" dependencies = [ "aiohappyeyeballs==2.4.3", - "hub>=3.0.1,<4", - "xxhash>=3.5.0,<4", - "black>=25.1.0,<26", + "hub>=3.0.1,<4.0.0", + "xxhash>=3.5.0,<4.0.0", + "black>=25.1.0,<26.0.0", ] [dependency-groups] diff --git a/docs/uv.lock b/docs/uv.lock index 51e596320..000861f33 100644 --- a/docs/uv.lock +++ b/docs/uv.lock @@ -1,5 +1,5 @@ version = 1 -revision = 2 +revision = 3 requires-python = ">=3.11, <4" resolution-markers = [ "python_full_version >= '3.13' and platform_python_implementation != 'PyPy'", @@ -2337,7 +2337,7 @@ wheels = [ [[package]] name = "langgraph" -version = "0.6.2" +version = "0.6.7" source = { editable = "../libs/langgraph" } dependencies = [ { name = "langchain-core" }, @@ -2380,6 +2380,7 @@ dev = [ { name = "pytest-repeat" }, { name = "pytest-watcher" }, { name = "pytest-xdist", extras = ["psutil"] }, + { name = "redis" }, { name = "ruff" }, { name = "syrupy" }, { name = "types-requests" }, @@ -2413,6 +2414,7 @@ dev = [ { name = "pytest-asyncio" }, { name = "pytest-mock" }, { name = "pytest-watcher" }, + { name = "redis" }, { name = "ruff" }, ] @@ -2643,7 +2645,7 @@ test = [ [[package]] name = "langgraph-prebuilt" -version = "0.6.2" +version = "0.6.4" source = { editable = "../libs/prebuilt" } dependencies = [ { name = "langchain-core" }, @@ -2674,7 +2676,6 @@ dev = [ [[package]] name = "langgraph-sdk" -version = "0.2.0" source = { editable = "../libs/sdk-py" } dependencies = [ { name = "httpx" }, diff --git a/examples/persistence_postgres.ipynb b/examples/persistence_postgres.ipynb index ad18f0d57..7081e2ef3 100644 --- a/examples/persistence_postgres.ipynb +++ b/examples/persistence_postgres.ipynb @@ -5,7 +5,7 @@ "id": "18526f23", "metadata": {}, "source": [ - "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/persistence_postgres.ipynb" + "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/memory/add-memory.md" ] } ], diff --git a/libs/checkpoint-postgres/langgraph/checkpoint/postgres/__init__.py b/libs/checkpoint-postgres/langgraph/checkpoint/postgres/__init__.py index de1d0b648..b689df5d5 100644 --- a/libs/checkpoint-postgres/langgraph/checkpoint/postgres/__init__.py +++ b/libs/checkpoint-postgres/langgraph/checkpoint/postgres/__init__.py @@ -7,11 +7,6 @@ from contextlib import contextmanager from typing import Any from langchain_core.runnables import RunnableConfig -from psycopg import Capabilities, Connection, Cursor, Pipeline -from psycopg.rows import DictRow, dict_row -from psycopg.types.json import Jsonb -from psycopg_pool import ConnectionPool - from langgraph.checkpoint.base import ( WRITES_IDX_MAP, ChannelVersions, @@ -21,10 +16,15 @@ from langgraph.checkpoint.base import ( get_checkpoint_id, get_checkpoint_metadata, ) +from langgraph.checkpoint.serde.base import SerializerProtocol +from psycopg import Capabilities, Connection, Cursor, Pipeline +from psycopg.rows import DictRow, dict_row +from psycopg.types.json import Jsonb +from psycopg_pool import ConnectionPool + from langgraph.checkpoint.postgres import _internal from langgraph.checkpoint.postgres.base import BasePostgresSaver from langgraph.checkpoint.postgres.shallow import ShallowPostgresSaver -from langgraph.checkpoint.serde.base import SerializerProtocol Conn = _internal.Conn # For backward compatibility @@ -450,7 +450,7 @@ class PostgresSaver(BasePostgresSaver): { **value["checkpoint"], "channel_values": { - **value["checkpoint"].get("channel_values"), + **(value["checkpoint"].get("channel_values") or {}), **self._load_blobs(value["channel_values"]), }, }, diff --git a/libs/checkpoint-postgres/langgraph/checkpoint/postgres/aio.py b/libs/checkpoint-postgres/langgraph/checkpoint/postgres/aio.py index e7c95c42b..ed36daa4a 100644 --- a/libs/checkpoint-postgres/langgraph/checkpoint/postgres/aio.py +++ b/libs/checkpoint-postgres/langgraph/checkpoint/postgres/aio.py @@ -7,11 +7,6 @@ from contextlib import asynccontextmanager from typing import Any from langchain_core.runnables import RunnableConfig -from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities -from psycopg.rows import DictRow, dict_row -from psycopg.types.json import Jsonb -from psycopg_pool import AsyncConnectionPool - from langgraph.checkpoint.base import ( WRITES_IDX_MAP, ChannelVersions, @@ -21,10 +16,15 @@ from langgraph.checkpoint.base import ( get_checkpoint_id, get_checkpoint_metadata, ) +from langgraph.checkpoint.serde.base import SerializerProtocol +from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities +from psycopg.rows import DictRow, dict_row +from psycopg.types.json import Jsonb +from psycopg_pool import AsyncConnectionPool + from langgraph.checkpoint.postgres import _ainternal from langgraph.checkpoint.postgres.base import BasePostgresSaver from langgraph.checkpoint.postgres.shallow import AsyncShallowPostgresSaver -from langgraph.checkpoint.serde.base import SerializerProtocol Conn = _ainternal.Conn # For backward compatibility @@ -409,7 +409,7 @@ class AsyncPostgresSaver(BasePostgresSaver): { **value["checkpoint"], "channel_values": { - **value["checkpoint"].get("channel_values"), + **(value["checkpoint"].get("channel_values") or {}), **self._load_blobs(value["channel_values"]), }, }, diff --git a/libs/checkpoint-postgres/langgraph/checkpoint/postgres/base.py b/libs/checkpoint-postgres/langgraph/checkpoint/postgres/base.py index 44b8ee397..b1ee5c9ce 100644 --- a/libs/checkpoint-postgres/langgraph/checkpoint/postgres/base.py +++ b/libs/checkpoint-postgres/langgraph/checkpoint/postgres/base.py @@ -5,8 +5,6 @@ from collections.abc import Sequence from typing import Any, Optional, cast from langchain_core.runnables import RunnableConfig -from psycopg.types.json import Jsonb - from langgraph.checkpoint.base import ( WRITES_IDX_MAP, BaseCheckpointSaver, @@ -14,6 +12,7 @@ from langgraph.checkpoint.base import ( get_checkpoint_id, ) from langgraph.checkpoint.serde.types import TASKS +from psycopg.types.json import Jsonb MetadataInput = Optional[dict[str, Any]] diff --git a/libs/checkpoint-postgres/langgraph/checkpoint/postgres/shallow.py b/libs/checkpoint-postgres/langgraph/checkpoint/postgres/shallow.py index 6626332b5..1abcaf96c 100644 --- a/libs/checkpoint-postgres/langgraph/checkpoint/postgres/shallow.py +++ b/libs/checkpoint-postgres/langgraph/checkpoint/postgres/shallow.py @@ -6,6 +6,16 @@ from contextlib import asynccontextmanager, contextmanager from typing import Any, Optional from langchain_core.runnables import RunnableConfig +from langgraph.checkpoint.base import ( + WRITES_IDX_MAP, + ChannelVersions, + Checkpoint, + CheckpointMetadata, + CheckpointTuple, + get_checkpoint_metadata, +) +from langgraph.checkpoint.serde.base import SerializerProtocol +from langgraph.checkpoint.serde.types import TASKS from psycopg import ( AsyncConnection, AsyncCursor, @@ -19,18 +29,8 @@ from psycopg.rows import DictRow, dict_row from psycopg.types.json import Jsonb from psycopg_pool import AsyncConnectionPool, ConnectionPool -from langgraph.checkpoint.base import ( - WRITES_IDX_MAP, - ChannelVersions, - Checkpoint, - CheckpointMetadata, - CheckpointTuple, - get_checkpoint_metadata, -) from langgraph.checkpoint.postgres import _ainternal, _internal from langgraph.checkpoint.postgres.base import BasePostgresSaver -from langgraph.checkpoint.serde.base import SerializerProtocol -from langgraph.checkpoint.serde.types import TASKS """ To add a new migration, add a new string to the MIGRATIONS list. diff --git a/libs/checkpoint-postgres/langgraph/store/postgres/__init__.py b/libs/checkpoint-postgres/langgraph/store/postgres/__init__.py index 47b7836d2..d0432b588 100644 --- a/libs/checkpoint-postgres/langgraph/store/postgres/__init__.py +++ b/libs/checkpoint-postgres/langgraph/store/postgres/__init__.py @@ -1,4 +1,4 @@ from langgraph.store.postgres.aio import AsyncPostgresStore -from langgraph.store.postgres.base import PostgresStore +from langgraph.store.postgres.base import PoolConfig, PostgresStore -__all__ = ["AsyncPostgresStore", "PostgresStore"] +__all__ = ["AsyncPostgresStore", "PoolConfig", "PostgresStore"] diff --git a/libs/checkpoint-postgres/langgraph/store/postgres/aio.py b/libs/checkpoint-postgres/langgraph/store/postgres/aio.py index 65b316d13..c8d481bb5 100644 --- a/libs/checkpoint-postgres/langgraph/store/postgres/aio.py +++ b/libs/checkpoint-postgres/langgraph/store/postgres/aio.py @@ -8,11 +8,6 @@ from types import TracebackType from typing import Any, Callable, cast import orjson -from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities -from psycopg.rows import DictRow, dict_row -from psycopg_pool import AsyncConnectionPool - -from langgraph.checkpoint.postgres import _ainternal from langgraph.store.base import ( GetOp, ListNamespacesOp, @@ -22,6 +17,11 @@ from langgraph.store.base import ( SearchOp, ) from langgraph.store.base.batch import AsyncBatchedBaseStore +from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities +from psycopg.rows import DictRow, dict_row +from psycopg_pool import AsyncConnectionPool + +from langgraph.checkpoint.postgres import _ainternal from langgraph.store.postgres.base import ( PLACEHOLDER, BasePostgresStore, diff --git a/libs/checkpoint-postgres/langgraph/store/postgres/base.py b/libs/checkpoint-postgres/langgraph/store/postgres/base.py index c73d59753..7f16b79a5 100644 --- a/libs/checkpoint-postgres/langgraph/store/postgres/base.py +++ b/libs/checkpoint-postgres/langgraph/store/postgres/base.py @@ -22,14 +22,6 @@ from typing import ( ) import orjson -from psycopg import Capabilities, Connection, Cursor, Pipeline -from psycopg.rows import DictRow, dict_row -from psycopg.types.json import Jsonb -from psycopg_pool import ConnectionPool -from typing_extensions import TypedDict - -from langgraph.checkpoint.postgres import _ainternal as _ainternal -from langgraph.checkpoint.postgres import _internal as _pg_internal from langgraph.store.base import ( BaseStore, GetOp, @@ -46,6 +38,14 @@ from langgraph.store.base import ( get_text_at_path, tokenize_path, ) +from psycopg import Capabilities, Connection, Cursor, Pipeline +from psycopg.rows import DictRow, dict_row +from psycopg.types.json import Jsonb +from psycopg_pool import ConnectionPool +from typing_extensions import TypedDict + +from langgraph.checkpoint.postgres import _ainternal as _ainternal +from langgraph.checkpoint.postgres import _internal as _pg_internal if TYPE_CHECKING: from langchain_core.embeddings import Embeddings diff --git a/libs/checkpoint-postgres/tests/test_async.py b/libs/checkpoint-postgres/tests/test_async.py index fb3af3317..cca805901 100644 --- a/libs/checkpoint-postgres/tests/test_async.py +++ b/libs/checkpoint-postgres/tests/test_async.py @@ -6,10 +6,6 @@ from uuid import uuid4 import pytest from langchain_core.runnables import RunnableConfig -from psycopg import AsyncConnection -from psycopg.rows import dict_row -from psycopg_pool import AsyncConnectionPool - from langgraph.checkpoint.base import ( EXCLUDED_METADATA_KEYS, Checkpoint, @@ -17,11 +13,15 @@ from langgraph.checkpoint.base import ( create_checkpoint, empty_checkpoint, ) +from langgraph.checkpoint.serde.types import TASKS +from psycopg import AsyncConnection +from psycopg.rows import dict_row +from psycopg_pool import AsyncConnectionPool + from langgraph.checkpoint.postgres.aio import ( AsyncPostgresSaver, AsyncShallowPostgresSaver, ) -from langgraph.checkpoint.serde.types import TASKS from tests.conftest import DEFAULT_POSTGRES_URI @@ -344,3 +344,34 @@ async def test_pending_sends_migration(saver_name: str) -> None: TASKS: ["send-1", "send-2", "send-3"] } assert TASKS in search_results[0].checkpoint["channel_versions"] + + +@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"]) +async def test_get_checkpoint_no_channel_values( + monkeypatch, saver_name: str, test_data +) -> None: + """Backwards compatibility test that verifies a checkpoint with no channel_values key can be retrieved without throwing an error.""" + async with _saver(saver_name) as saver: + config = { + "configurable": { + "thread_id": "thread-2", + "checkpoint_ns": "", + "__super_private_key": "super_private_value", + }, + "metadata": {"run_id": "my_run_id"}, + } + chkpnt: Checkpoint = create_checkpoint(empty_checkpoint(), {}, 1) + await saver.aput(config, chkpnt, {}, {}) + + load_checkpoint_tuple = saver._load_checkpoint_tuple + + def patched_load_checkpoint_tuple(value): + value["checkpoint"].pop("channel_values", None) + return load_checkpoint_tuple(value) + + monkeypatch.setattr( + saver, "_load_checkpoint_tuple", patched_load_checkpoint_tuple + ) + + checkpoint = await saver.aget_tuple(config) + assert checkpoint.checkpoint["channel_values"] == {} diff --git a/libs/checkpoint-postgres/tests/test_async_store.py b/libs/checkpoint-postgres/tests/test_async_store.py index 1ea7df1b7..c046be74b 100644 --- a/libs/checkpoint-postgres/tests/test_async_store.py +++ b/libs/checkpoint-postgres/tests/test_async_store.py @@ -12,8 +12,6 @@ from typing import Any import pytest from langchain_core.embeddings import Embeddings -from psycopg import AsyncConnection - from langgraph.store.base import ( GetOp, Item, @@ -21,6 +19,8 @@ from langgraph.store.base import ( PutOp, SearchOp, ) +from psycopg import AsyncConnection + from langgraph.store.postgres import AsyncPostgresStore from tests.conftest import ( DEFAULT_URI, diff --git a/libs/checkpoint-postgres/tests/test_store.py b/libs/checkpoint-postgres/tests/test_store.py index f7c7a1b2c..c59bab617 100644 --- a/libs/checkpoint-postgres/tests/test_store.py +++ b/libs/checkpoint-postgres/tests/test_store.py @@ -9,8 +9,6 @@ from uuid import uuid4 import pytest from langchain_core.embeddings import Embeddings -from psycopg import Connection - from langgraph.store.base import ( GetOp, Item, @@ -19,6 +17,8 @@ from langgraph.store.base import ( PutOp, SearchOp, ) +from psycopg import Connection + from langgraph.store.postgres import PostgresStore from tests.conftest import ( DEFAULT_URI, @@ -861,3 +861,41 @@ def test_store_ttl(store): # Now has been (TTL_SECONDS-2)*2 > TTL_SECONDS + TTL_SECONDS/2 res = store.search(ns, query="bar", refresh_ttl=False) assert len(res) == 0 + + +@pytest.mark.parametrize( + "vector_type,distance_type", + [ + ("vector", "cosine"), + ("vector", "inner_product"), + ("halfvec", "cosine"), + ("halfvec", "inner_product"), + ], +) +def test_non_ascii( + request: Any, + fake_embeddings: CharacterEmbeddings, + vector_type: str, + distance_type: str, +) -> None: + """Test support for non-ascii characters""" + with _create_vector_store(vector_type, distance_type, fake_embeddings) as store: + store.put(("user_123", "memories"), "1", {"text": "这是中文"}) # Chinese + store.put( + ("user_123", "memories"), "2", {"text": "これは日本語です"} + ) # Japanese + store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"}) # Korean + store.put(("user_123", "memories"), "4", {"text": "Это русский"}) # Russian + store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"}) # Hindi + + result1 = store.search(("user_123", "memories"), query="这是中文") + result2 = store.search(("user_123", "memories"), query="これは日本語です") + result3 = store.search(("user_123", "memories"), query="이건 한국어야") + result4 = store.search(("user_123", "memories"), query="Это русский") + result5 = store.search(("user_123", "memories"), query="यह रूसी है") + + assert result1[0].key == "1" + assert result2[0].key == "2" + assert result3[0].key == "3" + assert result4[0].key == "4" + assert result5[0].key == "5" diff --git a/libs/checkpoint-postgres/tests/test_sync.py b/libs/checkpoint-postgres/tests/test_sync.py index e6d2720e4..c8564c4e4 100644 --- a/libs/checkpoint-postgres/tests/test_sync.py +++ b/libs/checkpoint-postgres/tests/test_sync.py @@ -7,10 +7,6 @@ from uuid import uuid4 import pytest from langchain_core.runnables import RunnableConfig -from psycopg import Connection -from psycopg.rows import dict_row -from psycopg_pool import ConnectionPool - from langgraph.checkpoint.base import ( EXCLUDED_METADATA_KEYS, Checkpoint, @@ -18,8 +14,12 @@ from langgraph.checkpoint.base import ( create_checkpoint, empty_checkpoint, ) -from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver from langgraph.checkpoint.serde.types import TASKS +from psycopg import Connection +from psycopg.rows import dict_row +from psycopg_pool import ConnectionPool + +from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver from tests.conftest import DEFAULT_POSTGRES_URI @@ -332,3 +332,33 @@ def test_pending_sends_migration(saver_name: str) -> None: TASKS: ["send-1", "send-2", "send-3"] } assert TASKS in search_results[0].checkpoint["channel_versions"] + + +@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"]) +def test_get_checkpoint_no_channel_values( + monkeypatch, saver_name: str, test_data +) -> None: + """Backwards compatibility test that verifies a checkpoint with no channel_values key can be retrieved without throwing an error.""" + with _saver(saver_name) as saver: + config = { + "configurable": { + "thread_id": "thread-2", + "checkpoint_ns": "", + "__super_private_key": "super_private_value", + }, + } + chkpnt: Checkpoint = create_checkpoint(empty_checkpoint(), {}, 1) + saver.put(config, chkpnt, {}, {}) + + load_checkpoint_tuple = saver._load_checkpoint_tuple + + def patched_load_checkpoint_tuple(value): + value["checkpoint"].pop("channel_values", None) + return load_checkpoint_tuple(value) + + monkeypatch.setattr( + saver, "_load_checkpoint_tuple", patched_load_checkpoint_tuple + ) + + checkpoint = saver.get_tuple(config) + assert checkpoint.checkpoint["channel_values"] == {} diff --git a/libs/checkpoint-postgres/uv.lock b/libs/checkpoint-postgres/uv.lock index efd85491e..3674fd19a 100644 --- a/libs/checkpoint-postgres/uv.lock +++ b/libs/checkpoint-postgres/uv.lock @@ -1,5 +1,5 @@ version = 1 -revision = 2 +revision = 3 requires-python = ">=3.9" [[package]] @@ -13,7 +13,7 @@ wheels = [ [[package]] name = "anyio" -version = "4.9.0" +version = "4.11.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "exceptiongroup", marker = "python_full_version < '3.11'" }, @@ -21,161 +21,102 @@ dependencies = [ { name = "sniffio" }, { name = "typing-extensions", marker = "python_full_version < '3.13'" }, ] -sdist = { url = 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a/libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/aio.py +++ b/libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/aio.py @@ -8,7 +8,6 @@ from typing import Any, Callable, TypeVar, cast import aiosqlite from langchain_core.runnables import RunnableConfig - from langgraph.checkpoint.base import ( WRITES_IDX_MAP, BaseCheckpointSaver, @@ -21,6 +20,7 @@ from langgraph.checkpoint.base import ( get_checkpoint_metadata, ) from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer + from langgraph.checkpoint.sqlite.utils import search_where T = TypeVar("T", bound=Callable) diff --git a/libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/utils.py b/libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/utils.py index 9ab45d289..a3b8b7cec 100644 --- a/libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/utils.py +++ b/libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/utils.py @@ -5,7 +5,6 @@ from collections.abc import Sequence from typing import Any from langchain_core.runnables import RunnableConfig - from langgraph.checkpoint.base import get_checkpoint_id diff --git a/libs/checkpoint-sqlite/langgraph/store/sqlite/aio.py b/libs/checkpoint-sqlite/langgraph/store/sqlite/aio.py index 6be00813b..c850a04c9 100644 --- a/libs/checkpoint-sqlite/langgraph/store/sqlite/aio.py +++ b/libs/checkpoint-sqlite/langgraph/store/sqlite/aio.py @@ -11,7 +11,6 @@ from typing import Any, Callable, cast import aiosqlite import orjson import sqlite_vec # type: ignore[import-untyped] - from langgraph.store.base import ( GetOp, ListNamespacesOp, @@ -22,6 +21,7 @@ from langgraph.store.base import ( TTLConfig, ) from langgraph.store.base.batch import AsyncBatchedBaseStore + from langgraph.store.sqlite.base import ( _PLACEHOLDER, BaseSqliteStore, @@ -507,7 +507,9 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore): results: List to store results in. cur: Database cursor. """ - queries, embedding_requests = self._prepare_batch_search_queries(search_ops) + prepared_queries, embedding_requests = self._prepare_batch_search_queries( + search_ops + ) # Setup dot_product function if it doesn't exist if embedding_requests and self.embeddings: @@ -515,23 +517,60 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore): [query for _, query in embedding_requests] ) - for (idx, _), embedding in zip(embedding_requests, vectors): - _params_list: list = queries[idx][1] - for i, param in enumerate(_params_list): - if param is _PLACEHOLDER: - _params_list[i] = sqlite_vec.serialize_float32(embedding) + for (embed_req_idx, _), embedding in zip(embedding_requests, vectors): + # Find the corresponding query in prepared_queries + # The embed_req_idx is the original index in search_ops, which should map to prepared_queries + if embed_req_idx < len(prepared_queries): + _params_list: list = prepared_queries[embed_req_idx][1] + for i, param in enumerate(_params_list): + if param is _PLACEHOLDER: + _params_list[i] = sqlite_vec.serialize_float32(embedding) + else: + logger.warning( + f"Embedding request index {embed_req_idx} out of bounds for prepared_queries." + ) - for (idx, _), (query, params) in zip(search_ops, queries): + for (original_op_idx, _), (query, params, needs_refresh) in zip( + search_ops, prepared_queries + ): await cur.execute(query, params) rows = await cur.fetchall() - if "score" in query: + if needs_refresh and rows and self.ttl_config: + keys_to_refresh = [] + for row_data in rows: + # Assuming row_data[0] is prefix (text), row_data[1] is key (text) + # These are raw text values directly from the DB. + keys_to_refresh.append((row_data[0], row_data[1])) + + if keys_to_refresh: + updates_by_prefix = defaultdict(list) + for prefix_text, key_text in keys_to_refresh: + updates_by_prefix[prefix_text].append(key_text) + + for prefix_text, key_list in updates_by_prefix.items(): + placeholders = ",".join(["?"] * len(key_list)) + update_query = f""" + UPDATE store + SET expires_at = DATETIME(CURRENT_TIMESTAMP, '+' || ttl_minutes || ' minutes') + WHERE prefix = ? AND key IN ({placeholders}) AND ttl_minutes IS NOT NULL + """ + update_params = (prefix_text, *key_list) + try: + await cur.execute(update_query, update_params) + except Exception as e: + logger.error( + f"Error during TTL refresh update for search: {e}" + ) + + # Process rows into items + if "score" in query: # Vector search query items = [ _row_to_search_item( - _decode_ns_text(row[0]), + _decode_ns_text(row[0]), # prefix { - "key": row[1], - "value": row[2], + "key": row[1], # key + "value": row[2], # value "created_at": row[3], "updated_at": row[4], "expires_at": row[5] if len(row) > 5 else None, @@ -545,10 +584,10 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore): else: # Regular search query items = [ _row_to_search_item( - _decode_ns_text(row[0]), + _decode_ns_text(row[0]), # prefix { - "key": row[1], - "value": row[2], + "key": row[1], # key + "value": row[2], # value "created_at": row[3], "updated_at": row[4], "expires_at": row[5] if len(row) > 5 else None, @@ -559,7 +598,7 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore): for row in rows ] - results[idx] = items + results[original_op_idx] = items async def _batch_list_namespaces_ops( self, diff --git a/libs/checkpoint-sqlite/langgraph/store/sqlite/base.py b/libs/checkpoint-sqlite/langgraph/store/sqlite/base.py index 36e18d334..60f56652a 100644 --- a/libs/checkpoint-sqlite/langgraph/store/sqlite/base.py +++ b/libs/checkpoint-sqlite/langgraph/store/sqlite/base.py @@ -13,7 +13,6 @@ from typing import Any, Callable, Literal, NamedTuple, cast import orjson import sqlite_vec # type: ignore[import-untyped] - from langgraph.store.base import ( BaseStore, GetOp, @@ -372,13 +371,15 @@ class BaseSqliteStore: def _prepare_batch_search_queries( self, search_ops: Sequence[tuple[int, SearchOp]] ) -> tuple[ - list[tuple[str, list[None | str | list[float]]]], # queries, params + list[ + tuple[str, list[None | str | list[float]], bool] + ], # queries, params, needs_refresh list[tuple[int, str]], # idx, query_text pairs to embed ]: """ - Build per-SearchOp SQL queries (with optional TTL refresh) plus embedding requests. + Build per-SearchOp SQL queries (with optional TTL refresh flag) plus embedding requests. Returns: - - queries: list of (SQL, param_list) + - queries: list of (SQL, param_list, needs_ttl_refresh_flag) - embedding_requests: list of (original_index_in_search_ops, text_query) """ queries = [] @@ -519,30 +520,18 @@ class BaseSqliteStore: logger.debug(f"Search query: {base_query}") logger.debug(f"Search params: {params}") - # Handle TTL refresh if requested - if ( + # Determine if TTL refresh is needed + needs_ttl_refresh = bool( op.refresh_ttl and self.ttl_config and self.ttl_config.get("refresh_on_read", False) - ): - final_sql = f""" - WITH search_results AS ( - {base_query} - ), - updated AS ( - UPDATE store - SET expires_at = DATETIME(CURRENT_TIMESTAMP, '+' || ttl_minutes || ' minutes') - WHERE (prefix, key) IN (SELECT prefix, key FROM search_results) - AND ttl_minutes IS NOT NULL - ) - SELECT * FROM search_results - """ - final_params = params[:] # copy params - else: - final_sql = base_query - final_params = params + ) - queries.append((final_sql, final_params)) + # The base_query is now the final_sql, and we pass the refresh flag + final_sql = base_query + final_params = params + + queries.append((final_sql, final_params, needs_ttl_refresh)) return queries, embedding_requests @@ -1331,7 +1320,9 @@ class SqliteStore(BaseSqliteStore, BaseStore): results: list[Result], cur: sqlite3.Cursor, ) -> None: - queries, embedding_requests = self._prepare_batch_search_queries(search_ops) + prepared_queries, embedding_requests = self._prepare_batch_search_queries( + search_ops + ) # Setup similarity functions if they don't exist if embedding_requests and self.embeddings: @@ -1341,16 +1332,48 @@ class SqliteStore(BaseSqliteStore, BaseStore): ) # Replace placeholders with actual embeddings - for (idx, _), embedding in zip(embedding_requests, embeddings): - _params_list: list = queries[idx][1] - for i, param in enumerate(_params_list): - if param is _PLACEHOLDER: - _params_list[i] = sqlite_vec.serialize_float32(embedding) + for (embed_req_idx, _), embedding in zip(embedding_requests, embeddings): + if embed_req_idx < len(prepared_queries): + _params_list: list = prepared_queries[embed_req_idx][1] + for i, param in enumerate(_params_list): + if param is _PLACEHOLDER: + _params_list[i] = sqlite_vec.serialize_float32(embedding) + else: + logger.warning( + f"Embedding request index {embed_req_idx} out of bounds for prepared_queries." + ) - for (idx, _), (query, params) in zip(search_ops, queries): + for (original_op_idx, _), (query, params, needs_refresh) in zip( + search_ops, prepared_queries + ): cur.execute(query, params) rows = cur.fetchall() + if needs_refresh and rows and self.ttl_config: + keys_to_refresh = [] + for row_data in rows: + keys_to_refresh.append((row_data[0], row_data[1])) + + if keys_to_refresh: + updates_by_prefix = defaultdict(list) + for prefix_text, key_text in keys_to_refresh: + updates_by_prefix[prefix_text].append(key_text) + + for prefix_text, key_list in updates_by_prefix.items(): + placeholders = ",".join(["?"] * len(key_list)) + update_query = f""" + UPDATE store + SET expires_at = DATETIME(CURRENT_TIMESTAMP, '+' || ttl_minutes || ' minutes') + WHERE prefix = ? AND key IN ({placeholders}) AND ttl_minutes IS NOT NULL + """ + update_params = (prefix_text, *key_list) + try: + cur.execute(update_query, update_params) + except Exception as e: + logger.error( + f"Error during TTL refresh update for search: {e}" + ) + if "score" in query: # Vector search query items = [ _row_to_search_item( @@ -1385,7 +1408,7 @@ class SqliteStore(BaseSqliteStore, BaseStore): for row in rows ] - results[idx] = items + results[original_op_idx] = items def _batch_list_namespaces_ops( self, diff --git a/libs/checkpoint-sqlite/tests/test_aiosqlite.py b/libs/checkpoint-sqlite/tests/test_aiosqlite.py index 02dedd31a..06d612722 100644 --- a/libs/checkpoint-sqlite/tests/test_aiosqlite.py +++ b/libs/checkpoint-sqlite/tests/test_aiosqlite.py @@ -2,13 +2,13 @@ from typing import Any import pytest from langchain_core.runnables import RunnableConfig - from langgraph.checkpoint.base import ( Checkpoint, CheckpointMetadata, create_checkpoint, empty_checkpoint, ) + from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver diff --git a/libs/checkpoint-sqlite/tests/test_async_store.py b/libs/checkpoint-sqlite/tests/test_async_store.py index ee83d5c81..9a06feceb 100644 --- a/libs/checkpoint-sqlite/tests/test_async_store.py +++ b/libs/checkpoint-sqlite/tests/test_async_store.py @@ -8,7 +8,6 @@ from contextlib import asynccontextmanager from typing import Optional, Union, cast import pytest - from langgraph.store.base import ( GetOp, Item, @@ -16,6 +15,7 @@ from langgraph.store.base import ( PutOp, SearchOp, ) + from langgraph.store.sqlite import AsyncSqliteStore from langgraph.store.sqlite.base import SqliteIndexConfig from tests.test_store import CharacterEmbeddings diff --git a/libs/checkpoint-sqlite/tests/test_sqlite.py b/libs/checkpoint-sqlite/tests/test_sqlite.py index d2159a5ea..062bde23c 100644 --- a/libs/checkpoint-sqlite/tests/test_sqlite.py +++ b/libs/checkpoint-sqlite/tests/test_sqlite.py @@ -2,13 +2,13 @@ from typing import Any, cast import pytest from langchain_core.runnables import RunnableConfig - from langgraph.checkpoint.base import ( Checkpoint, CheckpointMetadata, create_checkpoint, empty_checkpoint, ) + from langgraph.checkpoint.sqlite import SqliteSaver from langgraph.checkpoint.sqlite.utils import _metadata_predicate, search_where @@ -116,7 +116,17 @@ class TestSqliteSaver: search_results_5[1].config["configurable"]["checkpoint_ns"], } == {"", "inner"} - # TODO: test before and limit params + # search with before param + search_results_6 = list(saver.list(None, before=search_results_5[1].config)) + assert len(search_results_6) == 1 + assert search_results_6[0].config["configurable"]["thread_id"] == "thread-1" + + # search with limit param + search_results_7 = list( + saver.list({"configurable": {"thread_id": "thread-2"}}, limit=1) + ) + assert len(search_results_7) == 1 + assert search_results_7[0].config["configurable"]["thread_id"] == "thread-2" def test_search_where(self) -> None: # call method / assertions diff --git a/libs/checkpoint-sqlite/tests/test_store.py b/libs/checkpoint-sqlite/tests/test_store.py index 590394375..ce1bb0127 100644 --- a/libs/checkpoint-sqlite/tests/test_store.py +++ b/libs/checkpoint-sqlite/tests/test_store.py @@ -9,7 +9,6 @@ from typing import Any, Literal, Optional, Union, cast import pytest from langchain_core.embeddings import Embeddings - from langgraph.store.base import ( GetOp, Item, @@ -18,6 +17,7 @@ from langgraph.store.base import ( PutOp, SearchOp, ) + from langgraph.store.sqlite import SqliteStore from langgraph.store.sqlite.base import SqliteIndexConfig @@ -1067,3 +1067,31 @@ def test_sql_injection_vulnerability(store: SqliteStore) -> None: with pytest.raises(ValueError, match="Invalid filter key"): store.search(("docs",), filter={malicious_key: "dummy"}) + + +@pytest.mark.parametrize("distance_type", VECTOR_TYPES) +def test_non_ascii( + fake_embeddings: CharacterEmbeddings, + distance_type: str, +) -> None: + """Test support for non-ascii characters""" + with create_vector_store(fake_embeddings, distance_type=distance_type) as store: + store.put(("user_123", "memories"), "1", {"text": "这是中文"}) # Chinese + store.put( + ("user_123", "memories"), "2", {"text": "これは日本語です"} + ) # Japanese + store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"}) # Korean + store.put(("user_123", "memories"), "4", {"text": "Это русский"}) # Russian + store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"}) # Hindi + + result1 = store.search(("user_123", "memories"), query="这是中文") + result2 = store.search(("user_123", "memories"), query="これは日本語です") + result3 = store.search(("user_123", "memories"), query="이건 한국어야") + result4 = store.search(("user_123", "memories"), query="Это русский") + result5 = store.search(("user_123", "memories"), query="यह रूसी है") + + assert result1[0].key == "1" + assert result2[0].key == "2" + assert result3[0].key == "3" + assert result4[0].key == "4" + assert result5[0].key == "5" diff --git a/libs/checkpoint-sqlite/tests/test_ttl.py b/libs/checkpoint-sqlite/tests/test_ttl.py index 972cc252f..28d43a790 100644 --- a/libs/checkpoint-sqlite/tests/test_ttl.py +++ b/libs/checkpoint-sqlite/tests/test_ttl.py @@ -7,6 +7,7 @@ import time from collections.abc import Generator import pytest +from langgraph.store.base import TTLConfig from langgraph.store.sqlite import SqliteStore from langgraph.store.sqlite.aio import AsyncSqliteStore @@ -93,9 +94,13 @@ def test_ttl_sweeper(temp_db_file: str) -> None: ttl_seconds = 2 ttl_minutes = ttl_seconds / 60 + ttl_config: TTLConfig = { + "default_ttl": ttl_minutes, + "sweep_interval_minutes": ttl_minutes / 2, + } with SqliteStore.from_conn_string( temp_db_file, - ttl={"default_ttl": ttl_minutes, "sweep_interval_minutes": ttl_minutes / 2}, + ttl=ttl_config, ) as store: store.setup() @@ -298,9 +303,14 @@ async def test_async_ttl_sweeper(temp_db_file: str) -> None: ttl_seconds = 2 ttl_minutes = ttl_seconds / 60 + ttl_config: TTLConfig = { + "default_ttl": ttl_minutes, + "sweep_interval_minutes": ttl_minutes / 2, + } + async with AsyncSqliteStore.from_conn_string( temp_db_file, - ttl={"default_ttl": ttl_minutes, "sweep_interval_minutes": ttl_minutes / 2}, + ttl=ttl_config, ) as store: await store.setup() @@ -353,3 +363,67 @@ async def test_async_search_with_ttl(temp_db_file: str) -> None: # Search after expiration results = await store.asearch(("test",), filter={"value": "apple"}) assert len(results) == 0 + + +@pytest.mark.asyncio +@pytest.mark.flaky(retries=3) +async def test_async_asearch_refresh_ttl(temp_db_file: str) -> None: + """Test TTL refresh on asearch with async API.""" + ttl_seconds = 4.0 # Increased TTL for less sensitivity to timing + ttl_minutes = ttl_seconds / 60.0 + + async with AsyncSqliteStore.from_conn_string( + temp_db_file, ttl={"default_ttl": ttl_minutes, "refresh_on_read": True} + ) as store: + await store.setup() + + namespace = ("docs", "user1") + # t=0: items put, expire at t=4.0s + await store.aput(namespace, "item1", {"text": "content1", "id": 1}) + await store.aput(namespace, "item2", {"text": "content2", "id": 2}) + + # t=3.0s: (after sleep ttl_seconds * 0.75 = 3s) + await asyncio.sleep(ttl_seconds * 0.75) + + # Perform asearch with refresh_ttl=True for item1. + # item1's TTL should be refreshed. New expiry: t=3.0s + 4.0s = t=7.0s. + # item2's TTL is not affected. Expires at t=4.0s. + searched_items = await store.asearch( + namespace, filter={"id": 1}, refresh_ttl=True + ) + assert len(searched_items) == 1 + assert searched_items[0].key == "item1" + + # t=5.0s: (after sleep ttl_seconds * 0.5 = 2s more. Total elapsed: 3s + 2s = 5s) + await asyncio.sleep(ttl_seconds * 0.5) + # At this point: + # - item1 (refreshed by asearch) should expire at t=7.0s. Should be ALIVE. + # - item2 (original TTL) should have expired at t=4.0s. Should be GONE after sweep. + + await store.sweep_ttl() + + # Check item1 (should exist due to asearch refresh) + item1_check1 = await store.aget(namespace, "item1", refresh_ttl=False) + assert item1_check1 is not None, ( + "Item1 should exist after asearch refresh and first sweep" + ) + assert item1_check1.value["text"] == "content1" + + # Check item2 (should be gone) + item2_check1 = await store.aget(namespace, "item2", refresh_ttl=False) + assert item2_check1 is None, ( + "Item2 should be gone after its original TTL expired" + ) + + # t=7.5s: (after sleep ttl_seconds * 0.625 = 2.5s more. 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list[str]) -> list[str]: if isinstance(current_obj, (str, int, float, bool)): results.append(str(current_obj)) elif isinstance(current_obj, (list, dict)): - results.append(json.dumps(current_obj, sort_keys=True)) + results.append( + json.dumps( + current_obj, sort_keys=True, ensure_ascii=False + ) + ) # Handle wildcard elif token == "*": diff --git a/libs/checkpoint/tests/test_redis_cache.py b/libs/checkpoint/tests/test_redis_cache.py index bec001e9b..ca1fce09c 100644 --- a/libs/checkpoint/tests/test_redis_cache.py +++ b/libs/checkpoint/tests/test_redis_cache.py @@ -5,12 +5,13 @@ import time import pytest import redis +from langgraph.cache.base import FullKey from langgraph.cache.redis import RedisCache class TestRedisCache: @pytest.fixture(autouse=True) - def setup(self): + def setup(self) -> None: """Set up test Redis client and cache.""" self.client = redis.Redis( host="localhost", port=6379, db=0, decode_responses=False @@ -20,21 +21,21 @@ class TestRedisCache: except redis.ConnectionError: pytest.skip("Redis server not available") - self.cache = RedisCache(self.client, prefix="test:cache:") + self.cache: RedisCache = RedisCache(self.client, prefix="test:cache:") # Clean up before each test self.client.flushdb() - def teardown_method(self): + def teardown_method(self) -> None: """Clean up after each test.""" try: self.client.flushdb() except Exception: pass - def test_basic_set_and_get(self): + def test_basic_set_and_get(self) -> None: """Test basic set and get operations.""" - keys = [(("graph", "node"), "key1")] + keys: list[FullKey] = [(("graph", "node"), "key1")] values = {keys[0]: ({"result": 42}, None)} # Set value @@ -45,9 +46,9 @@ class TestRedisCache: assert len(result) == 1 assert result[keys[0]] == {"result": 42} - def test_batch_operations(self): + def test_batch_operations(self) -> None: """Test batch set and get operations.""" - keys = [ + keys: list[FullKey] = [ (("graph", "node1"), "key1"), (("graph", "node2"), "key2"), (("other", "node"), "key3"), @@ -68,9 +69,9 @@ class TestRedisCache: assert result[keys[1]] == {"result": 2} assert result[keys[2]] == {"result": 3} - def test_ttl_behavior(self): + def test_ttl_behavior(self) -> None: """Test TTL (time-to-live) functionality.""" - key = (("graph", "node"), "ttl_key") + key: FullKey = (("graph", "node"), "ttl_key") values = {key: ({"data": "expires_soon"}, 1)} # 1 second TTL # Set with TTL @@ -88,10 +89,10 @@ class TestRedisCache: result = self.cache.get([key]) assert len(result) == 0 - def test_namespace_isolation(self): + def test_namespace_isolation(self) -> None: """Test that different namespaces are isolated.""" - key1 = (("graph1", "node"), "same_key") - key2 = (("graph2", "node"), "same_key") + key1: FullKey = (("graph1", "node"), "same_key") + key2: FullKey = (("graph2", "node"), "same_key") values = {key1: ({"graph": 1}, None), key2: ({"graph": 2}, None)} @@ -101,9 +102,12 @@ class TestRedisCache: assert result[key1] == {"graph": 1} assert result[key2] == {"graph": 2} - def test_clear_all(self): + def test_clear_all(self) -> None: """Test clearing all cached values.""" - keys = [(("graph", "node1"), "key1"), (("graph", "node2"), "key2")] + keys: list[FullKey] = [ + (("graph", "node1"), "key1"), + (("graph", "node2"), "key2"), + ] values = {keys[0]: ({"result": 1}, None), keys[1]: ({"result": 2}, None)} self.cache.set(values) @@ -119,9 +123,9 @@ class TestRedisCache: result = self.cache.get(keys) assert len(result) == 0 - def test_clear_by_namespace(self): + def test_clear_by_namespace(self) -> None: """Test clearing cached values by namespace.""" - keys = [ + keys: list[FullKey] = [ (("graph1", "node"), "key1"), (("graph2", "node"), "key2"), (("graph1", "other"), "key3"), @@ -142,7 +146,7 @@ class TestRedisCache: assert len(result) == 1 assert result[keys[1]] == {"result": 2} - def test_empty_operations(self): + def test_empty_operations(self) -> None: """Test behavior with empty keys/values.""" # Empty get result = self.cache.get([]) @@ -151,14 +155,14 @@ class TestRedisCache: # Empty set self.cache.set({}) # Should not raise error - def test_nonexistent_keys(self): + def test_nonexistent_keys(self) -> None: """Test getting keys that don't exist.""" - keys = [(("graph", "node"), "nonexistent")] + keys: list[FullKey] = [(("graph", "node"), "nonexistent")] result = self.cache.get(keys) assert len(result) == 0 @pytest.mark.asyncio - async def test_async_operations(self): + async def test_async_operations(self) -> None: """Test async set and get operations with sync Redis client.""" # Create sync Redis client and cache (like main integration tests) client = redis.Redis(host="localhost", port=6379, db=1, decode_responses=False) @@ -167,9 +171,9 @@ class TestRedisCache: except Exception: pytest.skip("Redis not available") - cache = RedisCache(client, prefix="test:async:") + cache: RedisCache = RedisCache(client, prefix="test:async:") - keys = [(("graph", "node"), "async_key")] + keys: list[FullKey] = [(("graph", "node"), "async_key")] values = {keys[0]: ({"async": True}, None)} # Async set (delegates to sync) @@ -184,7 +188,7 @@ class TestRedisCache: client.flushdb() @pytest.mark.asyncio - async def test_async_clear(self): + async def test_async_clear(self) -> None: """Test async clear operations with sync Redis client.""" # Create sync Redis client and cache (like main integration tests) client = redis.Redis(host="localhost", port=6379, db=1, decode_responses=False) @@ -193,9 +197,9 @@ class TestRedisCache: except Exception: pytest.skip("Redis not available") - cache = RedisCache(client, prefix="test:async:") + cache: RedisCache = RedisCache(client, prefix="test:async:") - keys = [(("graph", "node"), "key")] + keys: list[FullKey] = [(("graph", "node"), "key")] values = {keys[0]: ({"data": "test"}, None)} await cache.aset(values) @@ -214,44 +218,44 @@ class TestRedisCache: # Cleanup client.flushdb() - def test_redis_unavailable_get(self): + def test_redis_unavailable_get(self) -> None: """Test behavior when Redis is unavailable during get operations.""" # Create cache with non-existent Redis server bad_client = redis.Redis( host="nonexistent", port=9999, socket_connect_timeout=0.1 ) - cache = RedisCache(bad_client, prefix="test:cache:") + cache: RedisCache = RedisCache(bad_client, prefix="test:cache:") - keys = [(("graph", "node"), "key")] + keys: list[FullKey] = [(("graph", "node"), "key")] result = cache.get(keys) # Should return empty dict when Redis unavailable assert result == {} - def test_redis_unavailable_set(self): + def test_redis_unavailable_set(self) -> None: """Test behavior when Redis is unavailable during set operations.""" # Create cache with non-existent Redis server bad_client = redis.Redis( host="nonexistent", port=9999, socket_connect_timeout=0.1 ) - cache = RedisCache(bad_client, prefix="test:cache:") + cache: RedisCache = RedisCache(bad_client, prefix="test:cache:") - keys = [(("graph", "node"), "key")] + keys: list[FullKey] = [(("graph", "node"), "key")] values = {keys[0]: ({"data": "test"}, None)} # Should not raise exception when Redis unavailable cache.set(values) # Should silently fail @pytest.mark.asyncio - async def test_redis_unavailable_async(self): + async def test_redis_unavailable_async(self) -> None: """Test async behavior when Redis is unavailable.""" # Create sync cache with non-existent Redis server (like main integration tests) bad_client = redis.Redis( host="nonexistent", port=9999, socket_connect_timeout=0.1 ) - cache = RedisCache(bad_client, prefix="test:cache:") + cache: RedisCache = RedisCache(bad_client, prefix="test:cache:") - keys = [(("graph", "node"), "key")] + keys: list[FullKey] = [(("graph", "node"), "key")] values = {keys[0]: ({"data": "test"}, None)} # Should return empty dict for get (delegates to sync) @@ -261,10 +265,10 @@ class TestRedisCache: # Should not raise exception for set (delegates to sync) await cache.aset(values) # Should silently fail - def test_corrupted_data_handling(self): + def test_corrupted_data_handling(self) -> None: """Test handling of corrupted data in Redis.""" # Set some valid data first - keys = [(("graph", "node"), "valid_key")] + keys: list[FullKey] = [(("graph", "node"), "valid_key")] values = {keys[0]: ({"data": "valid"}, None)} self.cache.set(values) @@ -273,33 +277,36 @@ class TestRedisCache: self.client.set(corrupted_key, b"invalid:data:format:too:many:colons") # Should skip corrupted entry and return only valid ones - all_keys = [keys[0], (("graph", "node"), "corrupted_key")] + all_keys: list[FullKey] = [keys[0], (("graph", "node"), "corrupted_key")] result = self.cache.get(all_keys) assert len(result) == 1 assert result[keys[0]] == {"data": "valid"} - def test_key_parsing_edge_cases(self): + def test_key_parsing_edge_cases(self) -> None: """Test key parsing with edge cases.""" # Test empty namespace - key1 = ((), "empty_ns") + key1: FullKey = ((), "empty_ns") values = {key1: ({"data": "empty_ns"}, None)} self.cache.set(values) result = self.cache.get([key1]) assert result[key1] == {"data": "empty_ns"} # Test namespace with special characters - key2 = (("graph:with:colons", "node-with-dashes"), "key_with_underscores") + key2: FullKey = ( + ("graph:with:colons", "node-with-dashes"), + "key_with_underscores", + ) values = {key2: ({"data": "special_chars"}, None)} self.cache.set(values) result = self.cache.get([key2]) assert result[key2] == {"data": "special_chars"} - def test_large_data_serialization(self): + def test_large_data_serialization(self) -> None: """Test handling of large data objects.""" # Create a large data structure large_data = {"large_list": list(range(1000)), "nested": {"data": "x" * 1000}} - key = (("graph", "node"), "large_key") + key: FullKey = (("graph", "node"), "large_key") values = {key: (large_data, None)} self.cache.set(values) diff --git a/libs/checkpoint/tests/test_store.py b/libs/checkpoint/tests/test_store.py index 589eec0e4..38473e59f 100644 --- a/libs/checkpoint/tests/test_store.py +++ b/libs/checkpoint/tests/test_store.py @@ -950,8 +950,8 @@ async def test_embed_with_path(fake_embeddings: CharacterEmbeddings) -> None: assert results[0].key != results[1].key ascore = results[0].score bscore = results[1].score - assert ascore == bscore assert ascore is not None and bscore is not None + assert ascore == pytest.approx(bscore, abs=1e-5) results = await store.asearch(("test",), query="uuu") assert len(results) == 2 @@ -1021,3 +1021,27 @@ async def test_embed_with_path(fake_embeddings: CharacterEmbeddings) -> None: assert len(results) == 3 doc5_result = next(r for r in results if r.key == "doc5") assert doc5_result.score is None + + +def test_non_ascii(fake_embeddings: CharacterEmbeddings) -> None: + """Test support for non-ascii characters""" + store = InMemoryStore( + index={"dims": fake_embeddings.dims, "embed": fake_embeddings} + ) + store.put(("user_123", "memories"), "1", {"text": "这是中文"}) # Chinese + store.put(("user_123", "memories"), "2", {"text": "これは日本語です"}) # Japanese + store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"}) # Korean + store.put(("user_123", "memories"), "4", {"text": "Это русский"}) # Russian + store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"}) # Hindi + + result1 = store.search(("user_123", "memories"), query="这是中文") + result2 = store.search(("user_123", "memories"), query="これは日本語です") + result3 = store.search(("user_123", "memories"), query="이건 한국어야") + result4 = store.search(("user_123", "memories"), query="Это русский") + result5 = store.search(("user_123", "memories"), query="यह रूसी है") + + assert result1[0].key == "1" + assert result2[0].key == "2" + assert result3[0].key == "3" + assert result4[0].key == "4" + assert result5[0].key == "5" diff --git a/libs/checkpoint/uv.lock b/libs/checkpoint/uv.lock index 1454bd275..454c6efe7 100644 --- a/libs/checkpoint/uv.lock +++ b/libs/checkpoint/uv.lock @@ -1,5 +1,5 @@ version = 1 -revision = 2 +revision = 3 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b/libs/cli/examples/graph_prerelease_reqs/agent.py index b33b1a5d3..4801c7c0b 100644 --- a/libs/cli/examples/graph_prerelease_reqs/agent.py +++ b/libs/cli/examples/graph_prerelease_reqs/agent.py @@ -1,7 +1,6 @@ from collections.abc import Sequence from typing import Annotated, Literal, TypedDict -from langchain.chat_models import init_chat_model from langchain_community.tools.tavily_search import TavilySearchResults from langchain_core.messages import BaseMessage from langchain_openai import ChatOpenAI @@ -10,10 +9,8 @@ from langgraph.prebuilt import ToolNode tools = [TavilySearchResults(max_results=1)] -model_anth = init_chat_model("claude-3-7-sonnet-20250219", model_provider="anthropic") model_oai = ChatOpenAI(temperature=0) -model_anth = model_anth.bind_tools(tools) model_oai = model_oai.bind_tools(tools) @@ -35,10 +32,7 @@ def should_continue(state): # Define the function that calls the model def call_model(state, config): - if config["configurable"].get("model", "anthropic") == "anthropic": - model = model_anth - else: - model = model_oai + model = model_oai messages = state["messages"] response = model.invoke(messages) # We return a list, because this will get added to the existing list diff --git a/libs/cli/examples/graph_prerelease_reqs/deps/additional_deps/pyproject.toml b/libs/cli/examples/graph_prerelease_reqs/deps/additional_deps/pyproject.toml new file mode 100644 index 000000000..39e1ee42d --- /dev/null +++ b/libs/cli/examples/graph_prerelease_reqs/deps/additional_deps/pyproject.toml @@ -0,0 +1,9 @@ +[project] +name = "graph-prerelease-reqs-additional-deps" +version = "0.1.0" +description = "Test for prerelease stuff" +readme = "README.md" +requires-python = ">=3.10" +dependencies = [ + "langgraph==0.6.0" +] \ No newline at end of file diff --git a/libs/cli/examples/graph_prerelease_reqs/deps/zuper_deps/pyproject.toml b/libs/cli/examples/graph_prerelease_reqs/deps/zuper_deps/pyproject.toml new file mode 100644 index 000000000..2679347cb --- /dev/null +++ b/libs/cli/examples/graph_prerelease_reqs/deps/zuper_deps/pyproject.toml @@ -0,0 +1,9 @@ +[project] +name = "graph-prerelease-reqs-zuper-deps" +version = "0.1.0" +description = "Test for prerelease stuff" +readme = "README.md" +requires-python = ">=3.10" +dependencies = [ + "langchain-openai==0.3.0" +] \ No newline at end of file diff --git a/libs/cli/examples/graph_prerelease_reqs/langgraph.json b/libs/cli/examples/graph_prerelease_reqs/langgraph.json index 8bc7d8b2c..6d3a7b92b 100644 --- a/libs/cli/examples/graph_prerelease_reqs/langgraph.json +++ b/libs/cli/examples/graph_prerelease_reqs/langgraph.json @@ -1,7 +1,9 @@ { "python_version": "3.12", "dependencies": [ - "." + ".", + "./deps/additional_deps", + "./deps/zuper_deps" ], "graphs": { "agent": "./agent.py:graph" diff --git a/libs/cli/examples/graph_prerelease_reqs/pyproject.toml b/libs/cli/examples/graph_prerelease_reqs/pyproject.toml new file mode 100644 index 000000000..05e5da1d3 --- /dev/null +++ b/libs/cli/examples/graph_prerelease_reqs/pyproject.toml @@ -0,0 +1,14 @@ +[project] +name = "graph-prerelease-reqs" +version = "0.1.0" +description = "Test for prerelease stuff" +readme = "README.md" +requires-python = ">=3.10" +dependencies = [ + "langchain-openai==1.0.0a2", + "langgraph==1.0.0a2", + "langchain_community>=0.3.0", +] + +[tool.uv] +prerelease = "allow" \ No newline at end of file diff --git a/libs/cli/examples/graph_prerelease_reqs/requirements.txt b/libs/cli/examples/graph_prerelease_reqs/requirements.txt deleted file mode 100644 index 92e4c3b5c..000000000 --- a/libs/cli/examples/graph_prerelease_reqs/requirements.txt +++ /dev/null @@ -1,6 +0,0 @@ -requests -langchain_anthropic -langchain_openai -langchain_community -langchain -langgraph==1.0.0a2 \ No newline at end of file diff --git a/libs/cli/examples/graph_prerelease_reqs_fail/agent.py b/libs/cli/examples/graph_prerelease_reqs_fail/agent.py new file mode 100644 index 000000000..4801c7c0b --- /dev/null +++ b/libs/cli/examples/graph_prerelease_reqs_fail/agent.py @@ -0,0 +1,89 @@ +from collections.abc import Sequence +from typing import Annotated, Literal, TypedDict + +from langchain_community.tools.tavily_search import TavilySearchResults +from langchain_core.messages import BaseMessage +from langchain_openai import ChatOpenAI +from langgraph.graph import END, StateGraph, add_messages +from langgraph.prebuilt import ToolNode + +tools = [TavilySearchResults(max_results=1)] + +model_oai = ChatOpenAI(temperature=0) + +model_oai = model_oai.bind_tools(tools) + + +class AgentState(TypedDict): + messages: Annotated[Sequence[BaseMessage], add_messages] + + +# Define the function that determines whether to continue or not +def should_continue(state): + messages = state["messages"] + last_message = messages[-1] + # If there are no tool calls, then we finish + if not last_message.tool_calls: + return "end" + # Otherwise if there is, we continue + else: + return "continue" + + +# Define the function that calls the model +def call_model(state, config): + model = model_oai + messages = state["messages"] + response = model.invoke(messages) + # We return a list, because this will get added to the existing list + return {"messages": [response]} + + +# Define the function to execute tools +tool_node = ToolNode(tools) + + +class ContextSchema(TypedDict): + model: Literal["anthropic", "openai"] + + +# Define a new graph +workflow = StateGraph(AgentState, context_schema=ContextSchema) + +# Define the two nodes we will cycle between +workflow.add_node("agent", call_model) +workflow.add_node("action", tool_node) + +# Set the entrypoint as `agent` +# This means that this node is the first one called +workflow.set_entry_point("agent") + +# We now add a conditional edge +workflow.add_conditional_edges( + # First, we define the start node. We use `agent`. + # This means these are the edges taken after the `agent` node is called. + "agent", + # Next, we pass in the function that will determine which node is called next. + should_continue, + # Finally we pass in a mapping. + # The keys are strings, and the values are other nodes. + # END is a special node marking that the graph should finish. + # What will happen is we will call `should_continue`, and then the output of that + # will be matched against the keys in this mapping. + # Based on which one it matches, that node will then be called. + { + # If `tools`, then we call the tool node. + "continue": "action", + # Otherwise we finish. + "end": END, + }, +) + +# We now add a normal edge from `tools` to `agent`. +# This means that after `tools` is called, `agent` node is called next. +workflow.add_edge("action", "agent") + +# Finally, we compile it! +# This compiles it into a LangChain Runnable, +# meaning you can use it as you would any other runnable +graph = workflow.compile() diff --git a/libs/cli/examples/graph_prerelease_reqs_fail/langgraph.json b/libs/cli/examples/graph_prerelease_reqs_fail/langgraph.json new file mode 100644 index 000000000..8bc7d8b2c --- /dev/null +++ b/libs/cli/examples/graph_prerelease_reqs_fail/langgraph.json @@ -0,0 +1,11 @@ +{ + "python_version": "3.12", + "dependencies": [ + "." + ], + "graphs": { + "agent": "./agent.py:graph" + }, + "env": "../.env" + } + \ No newline at end of file diff --git a/libs/cli/examples/graph_prerelease_reqs_fail/pyproject.toml b/libs/cli/examples/graph_prerelease_reqs_fail/pyproject.toml new file mode 100644 index 000000000..27933649b --- /dev/null +++ b/libs/cli/examples/graph_prerelease_reqs_fail/pyproject.toml @@ -0,0 +1,11 @@ +[project] +name = "graph-prerelease-reqs" +version = "0.1.0" +description = "Test for prerelease stuff" +readme = "README.md" +requires-python = ">=3.10" +dependencies = [ + "langchain-openai==1.0.0a2", + "langgraph==1.0.0a2", + "langchain_community>=0.3.0", +] \ No newline at end of file diff --git a/libs/cli/examples/graphs/langgraph.json b/libs/cli/examples/graphs/langgraph.json index 7ac0e3d67..fce75dd9e 100644 --- a/libs/cli/examples/graphs/langgraph.json +++ b/libs/cli/examples/graphs/langgraph.json @@ -1,4 +1,5 @@ { + "$schema": "https://langgra.ph/schema.json", "python_version": "3.12", "dependencies": [ "langchain_community", diff --git a/libs/cli/examples/graphs_reqs_a/langgraph.json b/libs/cli/examples/graphs_reqs_a/langgraph.json index a550d5823..c6215ae84 100644 --- a/libs/cli/examples/graphs_reqs_a/langgraph.json +++ b/libs/cli/examples/graphs_reqs_a/langgraph.json @@ -1,4 +1,5 @@ { + "$schema": "https://langgra.ph/schema.json", "dependencies": [ "." ], diff --git a/libs/cli/examples/graphs_reqs_b/langgraph.json b/libs/cli/examples/graphs_reqs_b/langgraph.json index a550d5823..c6215ae84 100644 --- a/libs/cli/examples/graphs_reqs_b/langgraph.json +++ b/libs/cli/examples/graphs_reqs_b/langgraph.json @@ -1,4 +1,5 @@ { + "$schema": "https://langgra.ph/schema.json", "dependencies": [ "." ], diff --git a/libs/cli/js-examples/langgraph.json b/libs/cli/js-examples/langgraph.json index ddb17babc..79f2b3673 100644 --- a/libs/cli/js-examples/langgraph.json +++ b/libs/cli/js-examples/langgraph.json @@ -1,4 +1,5 @@ { + "$schema": "https://langgra.ph/schema.json", "node_version": "20", "graphs": { "agent": "./src/agent/graph.ts:graph" diff --git a/libs/cli/langgraph_cli/config.py b/libs/cli/langgraph_cli/config.py index 87d4d5c72..022e99e18 100644 --- a/libs/cli/langgraph_cli/config.py +++ b/libs/cli/langgraph_cli/config.py @@ -18,6 +18,7 @@ DEFAULT_IMAGE_DISTRO = "debian" Distros = Literal["debian", "wolfi", "bullseye", "bookworm"] +MiddlewareOrders = Literal["auth_first", "middleware_first"] class TTLConfig(TypedDict, total=False): @@ -359,6 +360,25 @@ class HttpConfig(TypedDict, total=False): agent's behavior or permissions on a request's headers.""" logging_headers: Optional[ConfigurableHeaderConfig] """Optional. Defines which headers are excluded from logging.""" + middleware_order: Optional[MiddlewareOrders] + """Optional. Defines the order in which to apply server customizations. + + Choices: + - "auth_first": Authentication hooks (custom or default) are evaluated + before custom middleware. + - "middleware_first": Custom middleware is evaluated + before authentication hooks (custom or default). + + Default is `middleware_first`. + """ + enable_custom_route_auth: bool + """Optional. If True, authentication is enabled for custom routes, + not just the routes that are protected by default. + (Routes protected by default include /assistants, /threads, and /runs). + + Default is False. This flag only affects authentication behavior + if `app` is provided and contains custom routes. + """ class Config(TypedDict, total=False): @@ -1256,16 +1276,22 @@ def python_config_to_docker( else: pip_installer = "pip" if pip_installer == "uv": - install_cmd = "uv pip install --system --prerelease=allow" + install_cmd = "uv pip install --system" elif pip_installer == "pip": install_cmd = "pip install" else: raise ValueError(f"Invalid pip_installer: {pip_installer}") # configure pip - pip_install = f"PYTHONDONTWRITEBYTECODE=1 {install_cmd} --no-cache-dir -c /api/constraints.txt" + local_reqs_pip_install = f"PYTHONDONTWRITEBYTECODE=1 {install_cmd} --no-cache-dir -c /api/constraints.txt" + global_reqs_pip_install = f"PYTHONDONTWRITEBYTECODE=1 {install_cmd} --no-cache-dir -c /api/constraints.txt" if config.get("pip_config_file"): - pip_install = f"PIP_CONFIG_FILE=/pipconfig.txt {pip_install}" + local_reqs_pip_install = ( + f"PIP_CONFIG_FILE=/pipconfig.txt {local_reqs_pip_install}" + ) + global_reqs_pip_install = ( + f"PIP_CONFIG_FILE=/pipconfig.txt {global_reqs_pip_install}" + ) pip_config_file_str = ( f"ADD {config['pip_config_file']} /pipconfig.txt" if config.get("pip_config_file") @@ -1282,7 +1308,9 @@ def python_config_to_docker( # Rewrite HTTP app path, so it points to the correct location in the Docker container _update_http_app_path(config_path, config, local_deps) - pip_pkgs_str = f"RUN {pip_install} {' '.join(pypi_deps)}" if pypi_deps else "" + pip_pkgs_str = ( + f"RUN {local_reqs_pip_install} {' '.join(pypi_deps)}" if pypi_deps else "" + ) if local_deps.pip_reqs: pip_reqs_str = os.linesep.join( ( @@ -1292,7 +1320,7 @@ def python_config_to_docker( ) for reqpath, destpath in local_deps.pip_reqs ) - pip_reqs_str += f"{os.linesep}RUN {pip_install} {' '.join('-r ' + r for _, r in local_deps.pip_reqs)}" + pip_reqs_str += f"{os.linesep}RUN {local_reqs_pip_install} {' '.join('-r ' + r for _, r in local_deps.pip_reqs)}" pip_reqs_str = f"""# -- Installing local requirements -- {pip_reqs_str} # -- End of local requirements install --""" @@ -1402,7 +1430,13 @@ ADD {relpath} /deps/{name} installs, "", "# -- Installing all local dependencies --", - f"RUN {pip_install} -e /deps/*", + f"""RUN for dep in /deps/*; do \ + echo "Installing $dep"; \ + if [ -d "$dep" ]; then \ + echo "Installing $dep"; \ + (cd "$dep" && {global_reqs_pip_install} .); \ + fi; \ + done""", "# -- End of local dependencies install --", os.linesep.join(env_vars), "", diff --git a/libs/cli/langgraph_cli/docker.py b/libs/cli/langgraph_cli/docker.py index 614dc6369..17e37d323 100644 --- a/libs/cli/langgraph_cli/docker.py +++ b/libs/cli/langgraph_cli/docker.py @@ -40,7 +40,9 @@ def _parse_version(version: str) -> Version: patch = "0" else: major, minor, patch = parts - return Version(int(major.lstrip("v")), int(minor), int(patch.split("-")[0])) + return Version( + int(major.lstrip("v")), int(minor), int(patch.split("-")[0].split("+")[0]) + ) def check_capabilities(runner) -> DockerCapabilities: diff --git a/libs/cli/python-monorepo-example/apps/agent/langgraph.json b/libs/cli/python-monorepo-example/apps/agent/langgraph.json index a02bcf929..10cf04d1d 100644 --- a/libs/cli/python-monorepo-example/apps/agent/langgraph.json +++ b/libs/cli/python-monorepo-example/apps/agent/langgraph.json @@ -1,4 +1,5 @@ { + "$schema": "https://langgra.ph/schema.json", "dependencies": [".", "../../libs/shared", "../../libs/common"], "graphs": { "agent": "./src/agent/graph.py:graph" diff --git a/libs/cli/schemas/schema.json b/libs/cli/schemas/schema.json index 21dd34a39..1dc83c607 100644 --- a/libs/cli/schemas/schema.json +++ b/libs/cli/schemas/schema.json @@ -577,6 +577,10 @@ "type": "boolean", "description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n" }, + "enable_custom_route_auth": { + "type": "boolean", + "description": "Optional. If True, authentication is enabled for custom routes,\nnot just the routes that are protected by default.\n(Routes protected by default include /assistants, /threads, and /runs).\n\nDefault is False. This flag only affects authentication behavior\nif `app` is provided and contains custom routes.\n" + }, "logging_headers": { "anyOf": [ { @@ -587,6 +591,20 @@ } ], "description": "Optional. Defines which headers are excluded from logging." + }, + "middleware_order": { + "anyOf": [ + { + "enum": [ + "auth_first", + "middleware_first" + ] + }, + { + "type": "null" + } + ], + "description": "Optional. Defines the order in which to apply server customizations.\n" } }, "required": [] diff --git a/libs/cli/schemas/schema.v0.json b/libs/cli/schemas/schema.v0.json index 21dd34a39..1dc83c607 100644 --- a/libs/cli/schemas/schema.v0.json +++ b/libs/cli/schemas/schema.v0.json @@ -577,6 +577,10 @@ "type": "boolean", "description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n" }, + "enable_custom_route_auth": { + "type": "boolean", + "description": "Optional. If True, authentication is enabled for custom routes,\nnot just the routes that are protected by default.\n(Routes protected by default include /assistants, /threads, and /runs).\n\nDefault is False. This flag only affects authentication behavior\nif `app` is provided and contains custom routes.\n" + }, "logging_headers": { "anyOf": [ { @@ -587,6 +591,20 @@ } ], "description": "Optional. Defines which headers are excluded from logging." + }, + "middleware_order": { + "anyOf": [ + { + "enum": [ + "auth_first", + "middleware_first" + ] + }, + { + "type": "null" + } + ], + "description": "Optional. Defines the order in which to apply server customizations.\n" } }, "required": [] diff --git a/libs/cli/tests/unit_tests/cli/test_cli.py b/libs/cli/tests/unit_tests/cli/test_cli.py index 6b1fca6ed..a16e31dcf 100644 --- a/libs/cli/tests/unit_tests/cli/test_cli.py +++ b/libs/cli/tests/unit_tests/cli/test_cli.py @@ -15,7 +15,7 @@ from langgraph_cli.docker import DEFAULT_POSTGRES_URI, DockerCapabilities, Versi from langgraph_cli.util import clean_empty_lines FORMATTED_CLEANUP_LINES = _get_pip_cleanup_lines( - install_cmd="uv pip install --system --prerelease=allow", + install_cmd="uv pip install --system", to_uninstall=("pip", "setuptools", "wheel"), pip_installer="uv", ) @@ -149,7 +149,7 @@ services: COPY --from=cli_1 . /deps/cli_1 # -- End of local package ../../.. -- # -- Installing all local dependencies -- - RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* + RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGSERVE_GRAPHS='{{"agent": "agent.py:graph"}}' {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), " ")} diff --git a/libs/cli/tests/unit_tests/test_config.py b/libs/cli/tests/unit_tests/test_config.py index 3b3efb6ec..733e74dbf 100644 --- a/libs/cli/tests/unit_tests/test_config.py +++ b/libs/cli/tests/unit_tests/test_config.py @@ -20,7 +20,7 @@ from langgraph_cli.config import ( from langgraph_cli.util import clean_empty_lines FORMATTED_CLEANUP_LINES = _get_pip_cleanup_lines( - install_cmd="uv pip install --system --prerelease=allow", + install_cmd="uv pip install --system", to_uninstall=("pip", "setuptools", "wheel"), pip_installer="uv", ) @@ -422,7 +422,7 @@ def test_config_to_docker_simple(): FROM langchain/langgraph-api:3.11 # -- Installing local requirements -- COPY --from=outer-requirements.txt requirements.txt /deps/outer-graphs_reqs_a/graphs_reqs_a/requirements.txt -RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -r /deps/outer-graphs_reqs_a/graphs_reqs_a/requirements.txt +RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -r /deps/outer-graphs_reqs_a/graphs_reqs_a/requirements.txt # -- End of local requirements install -- # -- Adding local package ../../examples -- COPY --from=examples . /deps/examples @@ -456,7 +456,7 @@ RUN set -ex && \\ done # -- End of non-package dependency graphs_reqs_a -- # -- Installing all local dependencies -- -RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* +RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGGRAPH_HTTP='{{"app": "/deps/examples/my_app.py:app"}}' ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}' @@ -512,7 +512,7 @@ RUN set -ex && \\ done # -- End of non-package dependency tests -- # -- Installing all local dependencies -- -RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* +RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGSERVE_GRAPHS='{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}' """ @@ -559,7 +559,7 @@ RUN set -ex && \\ done # -- End of non-package dependency unit_tests -- # -- Installing all local dependencies -- -RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* +RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGSERVE_GRAPHS='{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}' """ @@ -621,7 +621,7 @@ RUN set -ex && \\ done # -- End of non-package dependency graphs -- # -- Installing all local dependencies -- -RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* +RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-graphs/src/agent.py:graph"}}' {FORMATTED_CLEANUP_LINES}\ @@ -657,7 +657,7 @@ dependencies = ["langchain"]""" ADD . /deps/unit_tests # -- End of local package . -- # -- Installing all local dependencies -- -RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* +RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGSERVE_GRAPHS='{"agent": "/deps/unit_tests/graphs/agent.py:graph"}' """ @@ -689,7 +689,7 @@ def test_config_to_docker_end_to_end(): ARG meow ARG foo ADD pipconfig.txt /pipconfig.txt -RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt langchain langchain_openai +RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt langchain langchain_openai # -- Adding non-package dependency graphs -- ADD ./graphs/ /deps/outer-graphs/src RUN set -ex && \\ @@ -705,7 +705,7 @@ RUN set -ex && \\ done # -- End of non-package dependency graphs -- # -- Installing all local dependencies -- -RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* +RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-graphs/src/agent.py:graph"}}' {FORMATTED_CLEANUP_LINES}""" @@ -811,7 +811,7 @@ RUN set -ex && \\ done # -- End of non-package dependency unit_tests -- # -- Installing all local dependencies -- -RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* +RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGGRAPH_UI='{{"agent": "./graphs/agent.ui.jsx"}}' ENV LANGGRAPH_UI_CONFIG='{{"shared": ["nuqs"]}}' @@ -857,7 +857,7 @@ RUN set -ex && \\ done # -- End of non-package dependency unit_tests -- # -- Installing all local dependencies -- -RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* +RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGSERVE_GRAPHS='{{"python": "/deps/outer-unit_tests/unit_tests/multiplatform/python.py:graph", "js": "/deps/outer-unit_tests/unit_tests/multiplatform/js.mts:graph"}}' # -- Installing JS dependencies -- @@ -887,7 +887,7 @@ def test_config_to_docker_pip_installer(): docker_auto, _ = config_to_docker( PATH_TO_CONFIG, config_auto, "langchain/langgraph-api:0.2.47" ) - assert "uv pip install --system --prerelease=allow" in docker_auto + assert "uv pip install --system " in docker_auto assert "rm /usr/bin/uv /usr/bin/uvx" in docker_auto # Test explicit pip setting @@ -895,7 +895,7 @@ def test_config_to_docker_pip_installer(): docker_pip, _ = config_to_docker( PATH_TO_CONFIG, config_pip, "langchain/langgraph-api:0.2.47" ) - assert "uv pip install --system --prerelease=allow" not in docker_pip + assert "uv pip install --system " not in docker_pip assert "pip install" in docker_pip assert "rm /usr/bin/uv" not in docker_pip @@ -904,7 +904,7 @@ def test_config_to_docker_pip_installer(): docker_uv, _ = config_to_docker( PATH_TO_CONFIG, config_uv, "langchain/langgraph-api:0.2.47" ) - assert "uv pip install --system --prerelease=allow" in docker_uv + assert "uv pip install --system " in docker_uv assert "rm /usr/bin/uv /usr/bin/uvx" in docker_uv # Test auto behavior with older image (should use pip) @@ -914,7 +914,7 @@ def test_config_to_docker_pip_installer(): docker_auto_old, _ = config_to_docker( PATH_TO_CONFIG, config_auto_old, "langchain/langgraph-api:0.2.46" ) - assert "uv pip install --system --prerelease=allow" not in docker_auto_old + assert "uv pip install --system " not in docker_auto_old assert "pip install" in docker_auto_old assert "rm /usr/bin/uv" not in docker_auto_old @@ -923,7 +923,7 @@ def test_config_to_docker_pip_installer(): docker_default, _ = config_to_docker( PATH_TO_CONFIG, config_default, "langchain/langgraph-api:0.2.47" ) - assert "uv pip install --system --prerelease=allow" in docker_default + assert "uv pip install --system " in docker_default def test_config_retain_build_tools(): @@ -998,7 +998,7 @@ def test_config_to_compose_simple_config(): done # -- End of non-package dependency unit_tests -- # -- Installing all local dependencies -- - RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* + RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}' {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), " ")} @@ -1039,7 +1039,7 @@ def test_config_to_compose_env_vars(): done # -- End of non-package dependency unit_tests -- # -- Installing all local dependencies -- - RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* + RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}' {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), " ")} @@ -1084,7 +1084,7 @@ def test_config_to_compose_env_file(): done # -- End of non-package dependency unit_tests -- # -- Installing all local dependencies -- - RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* + RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}' {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), " ")} @@ -1122,7 +1122,7 @@ def test_config_to_compose_watch(): done # -- End of non-package dependency unit_tests -- # -- Installing all local dependencies -- - RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* + RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}' {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), " ")} @@ -1169,7 +1169,7 @@ def test_config_to_compose_end_to_end(): done # -- End of non-package dependency unit_tests -- # -- Installing all local dependencies -- - RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/* + RUN for dep in /deps/*; do echo "Installing $dep"; if [ -d "$dep" ]; then echo "Installing $dep"; (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .); fi; done # -- End of local dependencies install -- ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}' {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), " ")} diff --git a/libs/cli/tests/unit_tests/test_docker.py b/libs/cli/tests/unit_tests/test_docker.py index b29118a26..b16d0df14 100644 --- a/libs/cli/tests/unit_tests/test_docker.py +++ b/libs/cli/tests/unit_tests/test_docker.py @@ -1,7 +1,10 @@ +import pytest + from langgraph_cli.docker import ( DEFAULT_POSTGRES_URI, DockerCapabilities, Version, + _parse_version, compose, ) from langgraph_cli.util import clean_empty_lines @@ -363,3 +366,22 @@ services: REDIS_URI: redis://langgraph-redis:6379 POSTGRES_URI: {DEFAULT_POSTGRES_URI}""" assert clean_empty_lines(actual_compose_str) == expected_compose_str + + +@pytest.mark.parametrize( + "input_str,expected", + [ + ("1.2.3", Version(1, 2, 3)), + ("v1.2.3", Version(1, 2, 3)), + ("1.2.3-alpha", Version(1, 2, 3)), + ("1.2.3+1", Version(1, 2, 3)), + ("1.2.3-alpha+build", Version(1, 2, 3)), + ("1.2", Version(1, 2, 0)), + ("1", Version(1, 0, 0)), + ("v28.1.1+1", Version(28, 1, 1)), + ("2.0.0-beta.1+exp.sha.5114f85", Version(2, 0, 0)), + ("v3.4.5-rc1+build.123", Version(3, 4, 5)), + ], +) +def test_parse_version_w_edge_cases(input_str, expected): + assert _parse_version(input_str) == expected diff --git a/libs/cli/tests/unit_tests/test_util.py b/libs/cli/tests/unit_tests/test_util.py new file mode 100644 index 000000000..f4b439959 --- /dev/null +++ b/libs/cli/tests/unit_tests/test_util.py @@ -0,0 +1,188 @@ +from unittest.mock import patch + +from langgraph_cli.util import clean_empty_lines, warn_non_wolfi_distro + + +def test_clean_empty_lines(): + """Test clean_empty_lines function.""" + # Test with empty lines + input_str = "line1\n\nline2\n\nline3" + result = clean_empty_lines(input_str) + assert result == "line1\nline2\nline3" + + # Test with no empty lines + input_str = "line1\nline2\nline3" + result = clean_empty_lines(input_str) + assert result == "line1\nline2\nline3" + + # Test with only empty lines + input_str = "\n\n\n" + result = clean_empty_lines(input_str) + assert result == "" + + # Test empty string + input_str = "" + result = clean_empty_lines(input_str) + assert result == "" + + +def test_warn_non_wolfi_distro_with_debian(capsys): + """Test that warning is shown when image_distro is 'debian'.""" + config = {"image_distro": "debian"} + + warn_non_wolfi_distro(config) + + captured = capsys.readouterr() + assert ( + "⚠️ Security Recommendation: Consider switching to Wolfi Linux for enhanced security." + in captured.out + ) + assert ( + "Wolfi is a security-oriented, minimal Linux distribution designed for containers." + in captured.out + ) + assert ( + 'To switch, add \'"image_distro": "wolfi"\' to your langgraph.json config file.' + in captured.out + ) + + +def test_warn_non_wolfi_distro_with_default_debian(capsys): + """Test that warning is shown when image_distro is missing (defaults to debian).""" + config = {} # No image_distro key, should default to debian + + warn_non_wolfi_distro(config) + + captured = capsys.readouterr() + assert ( + "⚠️ Security Recommendation: Consider switching to Wolfi Linux for enhanced security." + in captured.out + ) + assert ( + "Wolfi is a security-oriented, minimal Linux distribution designed for containers." + in captured.out + ) + assert ( + 'To switch, add \'"image_distro": "wolfi"\' to your langgraph.json config file.' + in captured.out + ) + + +def test_warn_non_wolfi_distro_with_wolfi(capsys): + """Test that no warning is shown when image_distro is 'wolfi'.""" + config = {"image_distro": "wolfi"} + + warn_non_wolfi_distro(config) + + captured = capsys.readouterr() + assert captured.out == "" # No output should be generated + + +def test_warn_non_wolfi_distro_with_other_distro(capsys): + """Test that warning is shown when image_distro is something other than 'wolfi'.""" + config = {"image_distro": "ubuntu"} + + warn_non_wolfi_distro(config) + + captured = capsys.readouterr() + assert ( + "⚠️ Security Recommendation: Consider switching to Wolfi Linux for enhanced security." + in captured.out + ) + assert ( + "Wolfi is a security-oriented, minimal Linux distribution designed for containers." + in captured.out + ) + assert ( + 'To switch, add \'"image_distro": "wolfi"\' to your langgraph.json config file.' + in captured.out + ) + + +def test_warn_non_wolfi_distro_output_formatting(): + """Test that the warning output is properly formatted with colors and empty line.""" + config = {"image_distro": "debian"} + + with patch("click.secho") as mock_secho: + warn_non_wolfi_distro(config) + + # Verify click.secho was called with the correct parameters + expected_calls = [ + ( + ( + "⚠️ Security Recommendation: Consider switching to Wolfi Linux for enhanced security.", + ), + {"fg": "yellow", "bold": True}, + ), + ( + ( + " Wolfi is a security-oriented, minimal Linux distribution designed for containers.", + ), + {"fg": "yellow"}, + ), + ( + ( + ' To switch, add \'"image_distro": "wolfi"\' to your langgraph.json config file.', + ), + {"fg": "yellow"}, + ), + ( + ("",), # Empty line + {}, + ), + ] + + assert mock_secho.call_count == 4 + for i, (expected_args, expected_kwargs) in enumerate(expected_calls): + actual_call = mock_secho.call_args_list[i] + assert actual_call.args == expected_args + assert actual_call.kwargs == expected_kwargs + + +def test_warn_non_wolfi_distro_various_configs(capsys): + """Test warn_non_wolfi_distro with various config scenarios.""" + test_cases = [ + # (config, should_warn, description) + ({"image_distro": "debian"}, True, "explicit debian"), + ({"image_distro": "wolfi"}, False, "explicit wolfi"), + ({}, True, "missing image_distro (defaults to debian)"), + ({"image_distro": "alpine"}, True, "other distro"), + ({"image_distro": "ubuntu"}, True, "ubuntu distro"), + ({"other_config": "value"}, True, "unrelated config keys"), + ] + + for config, should_warn, description in test_cases: + # Clear any previous output + capsys.readouterr() + + warn_non_wolfi_distro(config) + + captured = capsys.readouterr() + if should_warn: + assert "⚠️ Security Recommendation" in captured.out, ( + f"Should warn for {description}" + ) + assert "Wolfi" in captured.out, f"Should mention Wolfi for {description}" + else: + assert captured.out == "", f"Should not warn for {description}" + + +def test_warn_non_wolfi_distro_return_value(): + """Test that warn_non_wolfi_distro returns None.""" + config = {"image_distro": "debian"} + result = warn_non_wolfi_distro(config) + assert result is None + + config = {"image_distro": "wolfi"} + result = warn_non_wolfi_distro(config) + assert result is None + + +def test_warn_non_wolfi_distro_does_not_modify_config(): + """Test that warn_non_wolfi_distro does not modify the input config.""" + original_config = {"image_distro": "debian", "other_key": "value"} + config_copy = original_config.copy() + + warn_non_wolfi_distro(config_copy) + + assert config_copy == original_config # Config should remain unchanged diff --git a/libs/cli/uv.lock b/libs/cli/uv.lock index cc98e61a4..b512402c4 100644 --- a/libs/cli/uv.lock +++ b/libs/cli/uv.lock @@ -1,5 +1,5 @@ version = 1 -revision = 2 +revision = 3 requires-python = ">=3.9" resolution-markers = [ "python_full_version >= '3.11'", @@ -18,16 +18,16 @@ wheels = [ [[package]] name = "anyio" -version = "4.10.0" +version = "4.11.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "idna", marker = "python_full_version >= 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100644 --- a/libs/langgraph/Makefile +++ b/libs/langgraph/Makefile @@ -76,7 +76,7 @@ test: test_parallel: make start-services &&\ make start-dev-server &&\ - uv run pytest -n auto --dist worksteal $(TEST); \ + uv run pytest -n auto --dist worksteal $(TEST) --lf --snapshot-update; \ EXIT_CODE=$$?; \ make stop-services; \ make stop-dev-server; \ diff --git a/libs/langgraph/langgraph/_internal/_runnable.py b/libs/langgraph/langgraph/_internal/_runnable.py index dc88671b1..087fe4e53 100644 --- a/libs/langgraph/langgraph/_internal/_runnable.py +++ b/libs/langgraph/langgraph/_internal/_runnable.py @@ -345,7 +345,7 @@ class RunnableCallable(Runnable): args = (input,) kwargs = {**self.kwargs, **kwargs} - runtime = config[CONF].get(CONFIG_KEY_RUNTIME) + runtime = config.get(CONF, {}).get(CONFIG_KEY_RUNTIME) for kw, (runtime_key, default) in self.func_accepts.items(): # If the kwarg is already set, use the set value @@ -417,7 +417,7 @@ class RunnableCallable(Runnable): args = (input,) kwargs = {**self.kwargs, **kwargs} - runtime = config[CONF].get(CONFIG_KEY_RUNTIME) + runtime = config.get(CONF, {}).get(CONFIG_KEY_RUNTIME) for kw, (runtime_key, default) in self.func_accepts.items(): # If the kwarg has already been set, use the set value diff --git a/libs/langgraph/langgraph/config.py b/libs/langgraph/langgraph/config.py index 86e50b393..71ebdb131 100644 --- a/libs/langgraph/langgraph/config.py +++ b/libs/langgraph/langgraph/config.py @@ -66,14 +66,17 @@ def get_store() -> BaseStore: store = InMemoryStore() store.put(("values",), "foo", {"bar": 2}) + class State(TypedDict): foo: int + def my_node(state: State): my_store = get_store() stored_value = my_store.get(("values",), "foo").value["bar"] return {"foo": stored_value + 1} + graph = ( StateGraph(State) .add_node(my_node) @@ -85,7 +88,7 @@ def get_store() -> BaseStore: ``` ```pycon - {'foo': 3} + {"foo": 3} ``` Example: Using with functional API @@ -97,16 +100,19 @@ def get_store() -> BaseStore: store = InMemoryStore() store.put(("values",), "foo", {"bar": 2}) + @task def my_task(value: int): my_store = get_store() stored_value = my_store.get(("values",), "foo").value["bar"] return stored_value + 1 + @entrypoint(store=store) def workflow(value: int): return my_task(value).result() + workflow.invoke(1) ``` @@ -134,14 +140,17 @@ def get_stream_writer() -> StreamWriter: from langgraph.graph import StateGraph, START from langgraph.config import get_stream_writer + class State(TypedDict): foo: int + def my_node(state: State): my_stream_writer = get_stream_writer() my_stream_writer({"custom_data": "Hello!"}) return {"foo": state["foo"] + 1} + graph = ( StateGraph(State) .add_node(my_node) @@ -154,7 +163,7 @@ def get_stream_writer() -> StreamWriter: ``` ```pycon - {'custom_data': 'Hello!'} + {"custom_data": "Hello!"} ``` Example: Using with functional API @@ -162,22 +171,25 @@ def get_stream_writer() -> StreamWriter: from langgraph.func import entrypoint, task from langgraph.config import get_stream_writer + @task def my_task(value: int): my_stream_writer = get_stream_writer() my_stream_writer({"custom_data": "Hello!"}) return value + 1 + @entrypoint(store=store) def workflow(value: int): return my_task(value).result() + for chunk in workflow.stream(1, stream_mode="custom"): print(chunk) ``` ```pycon - {'custom_data': 'Hello!'} + {"custom_data": "Hello!"} ``` """ runtime = get_config()[CONF][CONFIG_KEY_RUNTIME] diff --git a/libs/langgraph/langgraph/func/__init__.py b/libs/langgraph/langgraph/func/__init__.py index 9e4106855..bd1d8e9a6 100644 --- a/libs/langgraph/langgraph/func/__init__.py +++ b/libs/langgraph/langgraph/func/__init__.py @@ -1,7 +1,5 @@ from __future__ import annotations -import asyncio -import concurrent.futures import functools import inspect import warnings @@ -49,7 +47,7 @@ __all__ = ("task", "entrypoint") class _TaskFunction(Generic[P, T]): def __init__( self, - func: Callable[P, T], + func: Callable[P, Awaitable[T]] | Callable[P, T], *, retry_policy: Sequence[RetryPolicy], cache_policy: CachePolicy[Callable[P, str | bytes]] | None = None, @@ -60,7 +58,7 @@ class _TaskFunction(Generic[P, T]): # handle class methods # NOTE: we're modifying the instance method to avoid modifying # the original class method in case it's shared across multiple tasks - instance_method = functools.partial(func.__func__, func.__self__) # type: ignore [attr-defined] + instance_method = functools.partial(func.__func__, func.__self__) # type: ignore [union-attr] instance_method.__name__ = name # type: ignore [attr-defined] func = instance_method else: @@ -95,6 +93,7 @@ class _TaskFunction(Generic[P, T]): @overload def task( + __func_or_none__: None = None, *, name: str | None = None, retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None, @@ -107,9 +106,11 @@ def task( @overload -def task( - __func_or_none__: Callable[P, Awaitable[T]] | Callable[P, T], -) -> _TaskFunction[P, T]: ... +def task(__func_or_none__: Callable[P, Awaitable[T]]) -> _TaskFunction[P, T]: ... + + +@overload +def task(__func_or_none__: Callable[P, T]) -> _TaskFunction[P, T]: ... def task( @@ -149,16 +150,19 @@ def task( ```python from langgraph.func import entrypoint, task + @task def add_one(a: int) -> int: return a + 1 + @entrypoint() def add_one(numbers: list[int]) -> list[int]: futures = [add_one(n) for n in numbers] results = [f.result() for f in futures] return results + # Call the entrypoint add_one.invoke([1, 2, 3]) # Returns [2, 3, 4] ``` @@ -168,15 +172,18 @@ def task( import asyncio from langgraph.func import entrypoint, task + @task async def add_one(a: int) -> int: return a + 1 + @entrypoint() async def add_one(numbers: list[int]) -> list[int]: futures = [add_one(n) for n in numbers] return asyncio.gather(*futures) + # Call the entrypoint await add_one.ainvoke([1, 2, 3]) # Returns [2, 3, 4] ``` @@ -200,7 +207,7 @@ def task( def decorator( func: Callable[P, Awaitable[T]] | Callable[P, T], - ) -> Callable[P, concurrent.futures.Future[T]] | Callable[P, asyncio.Future[T]]: + ) -> Callable[P, SyncAsyncFuture[T]]: return _TaskFunction( func, retry_policy=retry_policies, cache_policy=cache_policy, name=name ) @@ -341,15 +348,13 @@ class entrypoint(Generic[ContextT]): from langgraph.func import entrypoint + @entrypoint(checkpointer=InMemorySaver()) def my_workflow(input_data: str, previous: Optional[str] = None) -> str: return "world" - config = { - "configurable": { - "thread_id": "some_thread" - } - } + + config = {"configurable": {"thread_id": "some_thread"}} my_workflow.invoke("hello", config) ``` @@ -366,19 +371,21 @@ class entrypoint(Generic[ContextT]): from langgraph.func import entrypoint + @entrypoint(checkpointer=InMemorySaver()) - def my_workflow(number: int, *, previous: Any = None) -> entrypoint.final[int, int]: + def my_workflow( + number: int, + *, + previous: Any = None, + ) -> entrypoint.final[int, int]: previous = previous or 0 # This will return the previous value to the caller, saving # 2 * number to the checkpoint, which will be used in the next invocation # for the `previous` parameter. return entrypoint.final(value=previous, save=2 * number) - config = { - "configurable": { - "thread_id": "some_thread" - } - } + + config = {"configurable": {"thread_id": "some_thread"}} my_workflow.invoke(3, config) # 0 (previous was None) my_workflow.invoke(1, config) # 6 (previous was 3 * 2 from the previous invocation) @@ -433,19 +440,21 @@ class entrypoint(Generic[ContextT]): from langgraph.checkpoint.memory import InMemorySaver from langgraph.func import entrypoint + @entrypoint(checkpointer=InMemorySaver()) - def my_workflow(number: int, *, previous: Any = None) -> entrypoint.final[int, int]: + def my_workflow( + number: int, + *, + previous: Any = None, + ) -> entrypoint.final[int, int]: previous = previous or 0 # This will return the previous value to the caller, saving # 2 * number to the checkpoint, which will be used in the next invocation # for the `previous` parameter. return entrypoint.final(value=previous, save=2 * number) - config = { - "configurable": { - "thread_id": "1" - } - } + + config = {"configurable": {"thread_id": "1"}} my_workflow.invoke(3, config) # 0 (previous was None) my_workflow.invoke(1, config) # 6 (previous was 3 * 2 from the previous invocation) diff --git a/libs/langgraph/langgraph/graph/message.py b/libs/langgraph/langgraph/graph/message.py index 9070aaa69..9afa151c0 100644 --- a/libs/langgraph/langgraph/graph/message.py +++ b/libs/langgraph/langgraph/graph/message.py @@ -92,6 +92,7 @@ def add_messages( Example: ```python title="Basic usage" from langchain_core.messages import AIMessage, HumanMessage + msgs1 = [HumanMessage(content="Hello", id="1")] msgs2 = [AIMessage(content="Hi there!", id="2")] add_messages(msgs1, msgs2) @@ -110,9 +111,11 @@ def add_messages( from typing_extensions import TypedDict from langgraph.graph import StateGraph + class State(TypedDict): messages: Annotated[list, add_messages] + builder = StateGraph(State) builder.add_node("chatbot", lambda state: {"messages": [("assistant", "Hello")]}) builder.set_entry_point("chatbot") @@ -127,30 +130,35 @@ def add_messages( from typing_extensions import TypedDict from langgraph.graph import StateGraph, add_messages + class State(TypedDict): - messages: Annotated[list, add_messages(format='langchain-openai')] + messages: Annotated[list, add_messages(format="langchain-openai")] + def chatbot_node(state: State) -> list: - return {"messages": [ - { - "role": "user", - "content": [ - { - "type": "text", - "text": "Here's an image:", - "cache_control": {"type": "ephemeral"}, - }, - { - "type": "image", - "source": { - "type": "base64", - "media_type": "image/jpeg", - "data": "1234", + return { + "messages": [ + { + "role": "user", + "content": [ + { + "type": "text", + "text": "Here's an image:", + "cache_control": {"type": "ephemeral"}, }, - }, - ] - }, - ]} + { + "type": "image", + "source": { + "type": "base64", + "media_type": "image/jpeg", + "data": "1234", + }, + }, + ], + }, + ] + } + builder = StateGraph(State) builder.add_node("chatbot", chatbot_node) diff --git a/libs/langgraph/langgraph/graph/state.py b/libs/langgraph/langgraph/graph/state.py index c6be1109c..ad5c1fc8b 100644 --- a/libs/langgraph/langgraph/graph/state.py +++ b/libs/langgraph/langgraph/graph/state.py @@ -141,25 +141,31 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]): from langgraph.graph import StateGraph from langgraph.runtime import Runtime + def reducer(a: list, b: int | None) -> list: if b is not None: return a + [b] return a + class State(TypedDict): x: Annotated[list, reducer] + class Context(TypedDict): r: float + graph = StateGraph(state_schema=State, context_schema=Context) + def node(state: State, runtime: Runtime[Context]) -> dict: r = runtime.context.get("r", 1.0) x = state["x"][-1] next_value = x * r * (1 - x) return {"x": next_value} + graph.add_node("A", node) graph.set_entry_point("A") graph.set_finish_point("A") @@ -385,12 +391,15 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]): from langchain_core.runnables import RunnableConfig from langgraph.graph import START, StateGraph + class State(TypedDict): x: int + def my_node(state: State, config: RunnableConfig) -> State: return {"x": state["x"] + 1} + builder = StateGraph(State) builder.add_node(my_node) # node name will be 'my_node' builder.add_edge(START, "my_node") @@ -1360,10 +1369,14 @@ def _get_channel( def _is_field_channel(typ: type[Any]) -> BaseChannel | None: if hasattr(typ, "__metadata__"): meta = typ.__metadata__ - if len(meta) >= 1 and isinstance(meta[-1], BaseChannel): - return meta[-1] - elif len(meta) >= 1 and isclass(meta[-1]) and issubclass(meta[-1], BaseChannel): - return meta[-1](typ.__origin__ if hasattr(typ, "__origin__") else typ) + # Search through all annotated medata to find channel annotations + for item in meta: + if isinstance(item, BaseChannel): + return item + elif isclass(item) and issubclass(item, BaseChannel): + # ex, Annotated[int, EphemeralValue, SomeOtherAnnotation] + # would return EphemeralValue(int) + return item(typ.__origin__ if hasattr(typ, "__origin__") else typ) return None diff --git a/libs/langgraph/langgraph/graph/ui.py b/libs/langgraph/langgraph/graph/ui.py index f2fe5a1c2..3d2229968 100644 --- a/libs/langgraph/langgraph/graph/ui.py +++ b/libs/langgraph/langgraph/graph/ui.py @@ -82,6 +82,8 @@ def push_ui_message( message: Optional message object to associate with the UI message. state_key: Key in the graph state where the UI messages are stored. Defaults to "ui". + merge: Whether to merge props with existing UI message (True) or replace + them (False). Defaults to False. Returns: The created UI message. @@ -186,7 +188,7 @@ def ui_message_reducer( messages = ui_message_reducer( [{"type": "ui", "id": "1", "name": "Chat", "props": {}}], - {"type": "remove-ui", "id": "1"} + {"type": "remove-ui", "id": "1"}, ) """ diff --git a/libs/langgraph/langgraph/pregel/_call.py b/libs/langgraph/langgraph/pregel/_call.py index 5956160aa..ba723e512 100644 --- a/libs/langgraph/langgraph/pregel/_call.py +++ b/libs/langgraph/langgraph/pregel/_call.py @@ -7,7 +7,7 @@ import functools import inspect import sys import types -from collections.abc import Generator, Sequence +from collections.abc import Awaitable, Generator, Sequence from typing import Any, Callable, Generic, TypeVar, cast from langchain_core.runnables import Runnable @@ -251,7 +251,7 @@ class SyncAsyncFuture(Generic[T], concurrent.futures.Future[T]): def call( - func: Callable[P, T], + func: Callable[P, Awaitable[T]] | Callable[P, T], *args: Any, retry_policy: Sequence[RetryPolicy] | None = None, cache_policy: CachePolicy | None = None, diff --git a/libs/langgraph/langgraph/pregel/_draw.py b/libs/langgraph/langgraph/pregel/_draw.py index 2d3390d53..922450df9 100644 --- a/libs/langgraph/langgraph/pregel/_draw.py +++ b/libs/langgraph/langgraph/pregel/_draw.py @@ -2,7 +2,7 @@ from __future__ import annotations from collections import defaultdict from collections.abc import Mapping, Sequence -from typing import Any, cast +from typing import Any, NamedTuple, cast from langchain_core.runnables.config import RunnableConfig from langchain_core.runnables.graph import Graph, Node @@ -10,6 +10,7 @@ from langgraph.checkpoint.base import BaseCheckpointSaver from langgraph._internal._constants import CONF, CONFIG_KEY_SEND, INPUT from langgraph.channels.base import BaseChannel +from langgraph.channels.last_value import LastValueAfterFinish from langgraph.constants import END, START from langgraph.managed.base import ManagedValueSpec from langgraph.pregel._algo import ( @@ -25,6 +26,19 @@ from langgraph.pregel._write import ChannelWrite from langgraph.types import All, Checkpointer +class Edge(NamedTuple): + source: str + target: str + conditional: bool + data: str | None + + +class TriggerEdge(NamedTuple): + source: str + conditional: bool + data: str | None + + def draw_graph( config: RunnableConfig, *, @@ -49,7 +63,7 @@ def draw_graph( The graph for this Pregel instance. """ # (src, dest, is_conditional, label) - edges: set[tuple[str, str, bool, str | None]] = set() + edges: set[Edge] = set() step = -1 checkpoint = empty_checkpoint() @@ -63,8 +77,9 @@ def draw_graph( checkpoint, ) static_seen: set[Any] = set() - sources: dict[str, set[tuple[str, bool, str | None]]] = {} - step_sources: dict[str, set[tuple[str, bool, str | None]]] = {} + sources: dict[str, set[TriggerEdge]] = {} + step_sources: dict[str, set[TriggerEdge]] = {} + static_declared_writes: dict[str, set[TriggerEdge]] = defaultdict(set) # remove node mappers nodes = { k: v.copy(update={"mapper": None}) if v.mapper is not None else v @@ -123,32 +138,36 @@ def draw_graph( # END writes are not written, but become edges directly for t in writes: if t[0] == END: - edges.add((task.name, t[0], True, t[2])) + edges.add(Edge(task.name, t[0], True, t[2])) writes = [t for t in writes if t[0] != END] conditionals.update( {(task.name, t[0], t[1] or None): t[2] for t in writes} ) + # record static writes for edge creation + for t in writes: + static_declared_writes[task.name].add( + TriggerEdge(t[0], True, t[2]) + ) task.config[CONF][CONFIG_KEY_SEND]([t[:2] for t in writes]) # collect sources - step_sources = { - task.name: { - ( + step_sources = {} + for task in tasks.values(): + task_edges = { + TriggerEdge( w[0], (task.name, w[0], w[1] or None) in conditionals, conditionals.get((task.name, w[0], w[1] or None)), ) for w in task.writes } - for task in tasks.values() - } + task_edges |= static_declared_writes.get(task.name, set()) + step_sources[task.name] = task_edges sources.update(step_sources) # invert triggers - trigger_to_sources: dict[str, set[tuple[str, bool, str | None]]] = defaultdict( - set - ) + trigger_to_sources: dict[str, set[TriggerEdge]] = defaultdict(set) for src, triggers in sources.items(): for trigger, cond, label in triggers: - trigger_to_sources[trigger].add((src, cond, label)) + trigger_to_sources[trigger].add(TriggerEdge(src, cond, label)) # apply writes updated_channels = apply_writes( checkpoint, channels, tasks.values(), get_next_version, trigger_to_nodes @@ -170,26 +189,39 @@ def draw_graph( trigger_to_nodes=trigger_to_nodes, updated_channels=updated_channels, ) + # collect deferred nodes + deferred_nodes: set[str] = set() + edges_to_deferred_nodes: set[Edge] = set() + for channel, item in channels.items(): + if isinstance(item, LastValueAfterFinish): + deferred_node = channel.split(":", 2)[-1] + deferred_nodes.add(deferred_node) # collect edges for task in tasks.values(): added = False for trigger in task.triggers: for src, cond, label in sorted(trigger_to_sources[trigger]): - edges.add((src, task.name, cond, label)) + # record edge to be reviewed later + if task.name in deferred_nodes: + edges_to_deferred_nodes.add(Edge(src, task.name, cond, label)) + edges.add(Edge(src, task.name, cond, label)) # if the edge is from this step, skip adding the implicit edges if (trigger, cond, label) in step_sources.get(src, set()): added = True else: - sources[src].discard((trigger, cond, label)) + sources[src].discard(TriggerEdge(trigger, cond, label)) # if no edges from this step, add implicit edges from all previous tasks if not added: for src in step_sources: - edges.add((src, task.name, True, None)) + edges.add(Edge(src, task.name, True, None)) + # assemble the graph graph = Graph() # add nodes for name, node in nodes.items(): metadata = dict(node.metadata or {}) + if name in deferred_nodes: + metadata["defer"] = True if name in interrupt_before_nodes and name in interrupt_after_nodes: metadata["__interrupt"] = "before,after" elif name in interrupt_before_nodes: @@ -215,10 +247,11 @@ def draw_graph( termini = {d for _, d, _, _ in edges if d != END}.difference( s for s, _, _, _ in edges ) + end_edge_exists = any(d == END for _, d, _, _ in edges) if termini: for src in sorted(termini): add_edge(graph, src, END) - elif len(step_sources) == 1: + elif len(step_sources) == 1 and not end_edge_exists: for src in sorted(step_sources): add_edge(graph, src, END, conditional=True) # replace subgraphs diff --git a/libs/langgraph/langgraph/pregel/_loop.py b/libs/langgraph/langgraph/pregel/_loop.py index 248eb3ba0..023ac5545 100644 --- a/libs/langgraph/langgraph/pregel/_loop.py +++ b/libs/langgraph/langgraph/pregel/_loop.py @@ -242,7 +242,9 @@ class PregelLoop: self.interrupt_before = interrupt_before self.manager = manager self.is_nested = CONFIG_KEY_TASK_ID in self.config.get(CONF, {}) - self.skip_done_tasks = CONFIG_KEY_CHECKPOINT_ID not in config[CONF] + self.skip_done_tasks = CONFIG_KEY_CHECKPOINT_ID not in config[CONF] or ( + CONFIG_KEY_RESUMING in self.config[CONF] and self.is_nested + ) self._migrate_checkpoint = migrate_checkpoint self.trigger_to_nodes = trigger_to_nodes self.retry_policy = retry_policy @@ -568,6 +570,36 @@ class PregelLoop: if task := tasks.get(tid): task.writes.append((k, v)) + def _pending_interrupts(self) -> set[str]: + """Return the set of interrupt ids that are pending without corresponding resume values.""" + # mapping of task ids to interrupt ids + pending_interrupts: dict[str, str] = {} + + # set of resume task ids + pending_resumes: set[str] = set() + + for task_id, write_type, value in self.checkpoint_pending_writes: + if write_type == INTERRUPT: + # interrupts is always a list, but there should only be one element + pending_interrupts[task_id] = value[0].id + elif write_type == RESUME: + pending_resumes.add(task_id) + + resumed_interrupt_ids = { + pending_interrupts[task_id] + for task_id in pending_resumes + if task_id in pending_interrupts + } + + # Keep only interrupts whose interrupt_id is not resumed + hanging_interrupts: set[str] = { + interrupt_id + for interrupt_id in pending_interrupts.values() + if interrupt_id not in resumed_interrupt_ids + } + + return hanging_interrupts + def _first( self, *, input_keys: str | Sequence[str], updated_channels: set[str] | None ) -> set[str] | None: @@ -590,16 +622,24 @@ class PregelLoop: # map command to writes if isinstance(self.input, Command): - if resume_is_map := ( - (resume := self.input.resume) is not None - and isinstance(resume, dict) - and all(is_xxh3_128_hexdigest(k) for k in resume) - ): - self.config[CONF][CONFIG_KEY_RESUME_MAP] = self.input.resume - if resume is not None and not self.checkpointer: - raise RuntimeError( - "Cannot use Command(resume=...) without checkpointer" - ) + if (resume := self.input.resume) is not None: + if not self.checkpointer: + raise RuntimeError( + "Cannot use Command(resume=...) without checkpointer" + ) + + if resume_is_map := ( + isinstance(resume, dict) + and all(is_xxh3_128_hexdigest(k) for k in resume) + ): + self.config[CONF][CONFIG_KEY_RESUME_MAP] = resume + else: + if len(self._pending_interrupts()) > 1: + raise RuntimeError( + "When there are multiple pending interrupts, you must specify the interrupt id when resuming. " + "Docs: https://docs.langchain.com/oss/python/langgraph/add-human-in-the-loop#resume-multiple-interrupts-with-one-invocation." + ) + writes: defaultdict[str, list[tuple[str, Any]]] = defaultdict(list) # group writes by task ID for tid, c, v in map_command(cmd=self.input): @@ -866,7 +906,11 @@ class PregelLoop: ) } ] - self._emit("updates", lambda: iter(interrupts)) + stream_modes = self.stream.modes if self.stream else [] + if "updates" in stream_modes: + self._emit("updates", lambda: iter(interrupts)) + elif "values" in stream_modes: + self._emit("values", lambda: iter(interrupts)) elif writes[0][0] != ERROR: self._emit( "updates", diff --git a/libs/langgraph/langgraph/pregel/debug.py b/libs/langgraph/langgraph/pregel/debug.py index 1591431d7..507fd587a 100644 --- a/libs/langgraph/langgraph/pregel/debug.py +++ b/libs/langgraph/langgraph/pregel/debug.py @@ -48,7 +48,7 @@ class CheckpointTask(TypedDict): name: str error: str | None interrupts: list[dict] - state: RunnableConfig | None + state: StateSnapshot | RunnableConfig | None class CheckpointPayload(TypedDict): diff --git a/libs/langgraph/langgraph/pregel/main.py b/libs/langgraph/langgraph/pregel/main.py index a47ff3f4b..7ccbf54e7 100644 --- a/libs/langgraph/langgraph/pregel/main.py +++ b/libs/langgraph/langgraph/pregel/main.py @@ -3,15 +3,24 @@ from __future__ import annotations import asyncio import concurrent import concurrent.futures +import contextlib import queue import warnings import weakref from collections import defaultdict, deque -from collections.abc import AsyncIterator, Iterator, Mapping, Sequence +from collections.abc import AsyncIterator, Awaitable, Iterator, Mapping, Sequence from dataclasses import is_dataclass from functools import partial from inspect import isclass -from typing import Any, Callable, Generic, Optional, Union, cast, get_type_hints +from typing import ( + Any, + Callable, + Generic, + Optional, + Union, + cast, + get_type_hints, +) from uuid import UUID, uuid5 from langchain_core.globals import get_debug @@ -377,7 +386,7 @@ class Pregel( However, for **advanced** use cases, Pregel can be used directly. If you're not sure whether you need to use Pregel directly, then the answer is probably no - – you should use the Graph API or Functional API instead. These are higher-level + - you should use the Graph API or Functional API instead. These are higher-level interfaces that will compile down to Pregel under the hood. Here are some examples to give you a sense of how it works: @@ -479,7 +488,7 @@ class Pregel( ``` ```pycon - {'c': ['foofoo', 'foofoofoofoo']} + {"c": ["foofoo", "foofoofoofoo"]} ``` Example: Using a BinaryOperatorAggregate channel @@ -507,6 +516,7 @@ class Pregel( else: return update + app = Pregel( nodes={"node1": node1, "node2": node2}, channels={ @@ -515,7 +525,7 @@ class Pregel( "c": BinaryOperatorAggregate(str, operator=reducer), }, input_channels=["a"], - output_channels=["c"] + output_channels=["c"], ) app.invoke({"a": "foo"}) @@ -535,7 +545,8 @@ class Pregel( from langgraph.pregel import Pregel, NodeBuilder, ChannelWriteEntry example_node = ( - NodeBuilder().subscribe_only("value") + NodeBuilder() + .subscribe_only("value") .do(lambda x: x + x if len(x) < 10 else None) .write_to(ChannelWriteEntry(channel="value", skip_none=True)) ) @@ -546,7 +557,7 @@ class Pregel( "value": EphemeralValue(str), }, input_channels=["value"], - output_channels=["value"] + output_channels=["value"], ) app.invoke({"value": "a"}) @@ -2612,6 +2623,7 @@ class Pregel( if subgraphs: loop.config[CONF][CONFIG_KEY_STREAM] = loop.stream # enable concurrent streaming + get_waiter: Callable[[], concurrent.futures.Future[None]] | None = None if ( self.stream_eager or subgraphs @@ -2634,8 +2646,6 @@ class Pregel( else: return waiter - else: - get_waiter = None # type: ignore[assignment] # Similarly to Bulk Synchronous Parallel / Pregel model # computation proceeds in steps, while there are channel updates. # Channel updates from step N are only visible in step N+1 @@ -2916,45 +2926,77 @@ class Pregel( stream_put, stream_modes ) # enable concurrent streaming + get_waiter: Callable[[], asyncio.Task[None]] | None = None + _cleanup_waiter: Callable[[], Awaitable[None]] | None = None if ( self.stream_eager or subgraphs or "messages" in stream_modes or "custom" in stream_modes ): + # Keep a single waiter task alive; ensure cleanup on exit. + waiter: asyncio.Task[None] | None = None def get_waiter() -> asyncio.Task[None]: - return aioloop.create_task(stream.wait()) + nonlocal waiter + if waiter is None or waiter.done(): + waiter = aioloop.create_task(stream.wait()) + + def _clear(t: asyncio.Task[None]) -> None: + nonlocal waiter + if waiter is t: + waiter = None + + waiter.add_done_callback(_clear) + return waiter + + async def _cleanup_waiter() -> None: + """Wake pending waiter and/or cancel+await to avoid pending tasks.""" + nonlocal waiter + # Try to wake via semaphore like SyncPregelLoop + with contextlib.suppress(Exception): + if hasattr(stream, "_count"): + stream._count.release() + t = waiter + waiter = None + if t is not None and not t.done(): + t.cancel() + with contextlib.suppress(asyncio.CancelledError): + await t - else: - get_waiter = None # type: ignore[assignment] # Similarly to Bulk Synchronous Parallel / Pregel model # computation proceeds in steps, while there are channel updates # channel updates from step N are only visible in step N+1 # channels are guaranteed to be immutable for the duration of the step, # with channel updates applied only at the transition between steps - while loop.tick(): - for task in await loop.amatch_cached_writes(): - loop.output_writes(task.id, task.writes, cached=True) - async for _ in runner.atick( - [t for t in loop.tasks.values() if not t.writes], - timeout=self.step_timeout, - get_waiter=get_waiter, - schedule_task=loop.aaccept_push, - ): - # emit output - for o in _output( - stream_mode, - print_mode, - subgraphs, - stream.get_nowait, - asyncio.QueueEmpty, + try: + while loop.tick(): + for task in await loop.amatch_cached_writes(): + loop.output_writes(task.id, task.writes, cached=True) + async for _ in runner.atick( + [t for t in loop.tasks.values() if not t.writes], + timeout=self.step_timeout, + get_waiter=get_waiter, + schedule_task=loop.aaccept_push, ): - yield o - loop.after_tick() - # wait for checkpoint - if durability_ == "sync": - await cast(asyncio.Future, loop._put_checkpoint_fut) + # emit output + for o in _output( + stream_mode, + print_mode, + subgraphs, + stream.get_nowait, + asyncio.QueueEmpty, + ): + yield o + loop.after_tick() + # wait for checkpoint + if durability_ == "sync": + await cast(asyncio.Future, loop._put_checkpoint_fut) + finally: + # ensure waiter doesn't remain pending on cancel/shutdown + if _cleanup_waiter is not None: + await _cleanup_waiter() + # emit output for o in _output( stream_mode, diff --git a/libs/langgraph/langgraph/pregel/remote.py b/libs/langgraph/langgraph/pregel/remote.py index 81c303b56..7135a44d7 100644 --- a/libs/langgraph/langgraph/pregel/remote.py +++ b/libs/langgraph/langgraph/pregel/remote.py @@ -1,5 +1,6 @@ from __future__ import annotations +import logging from collections.abc import AsyncIterator, Iterator, Sequence from dataclasses import asdict from typing import ( @@ -7,6 +8,7 @@ from typing import ( Literal, cast, ) +from uuid import UUID import langsmith as ls from langchain_core.runnables import RunnableConfig @@ -61,6 +63,8 @@ from langgraph.types import ( StreamMode, ) +logger = logging.getLogger(__name__) + __all__ = ("RemoteGraph", "RemoteException") _CONF_DROPLIST = frozenset( @@ -75,7 +79,7 @@ _CONF_DROPLIST = frozenset( def _sanitize_config_value(v: Any) -> Any: """Recursively sanitize a config value to ensure it contains only primitives.""" - if isinstance(v, (str, int, float, bool)): + if isinstance(v, (str, int, float, bool, UUID)): return v elif isinstance(v, dict): sanitized_dict = {} @@ -950,6 +954,7 @@ class RemoteGraph(PregelProtocol): try: return chunk except UnboundLocalError: + logger.warning("No events received from remote graph") return None async def ainvoke( @@ -990,6 +995,7 @@ class RemoteGraph(PregelProtocol): try: return chunk except UnboundLocalError: + logger.warning("No events received from remote graph") return None diff --git a/libs/langgraph/langgraph/types.py b/libs/langgraph/langgraph/types.py index 76e81860b..330dc3639 100644 --- a/libs/langgraph/langgraph/types.py +++ b/libs/langgraph/langgraph/types.py @@ -296,12 +296,10 @@ class Send: >>> class OverallState(TypedDict): ... subjects: list[str] ... jokes: Annotated[list[str], operator.add] - ... >>> from langgraph.types import Send >>> from langgraph.graph import END, START >>> def continue_to_jokes(state: OverallState): - ... return [Send("generate_joke", {"subject": s}) for s in state['subjects']] - ... + ... return [Send("generate_joke", {"subject": s}) for s in state["subjects"]] >>> from langgraph.graph import StateGraph >>> builder = StateGraph(OverallState) >>> builder.add_node("generate_joke", lambda state: {"jokes": [f"Joke about {state['subject']}"]}) diff --git a/libs/langgraph/pyproject.toml b/libs/langgraph/pyproject.toml index 674a91cb9..55ef5808c 100644 --- a/libs/langgraph/pyproject.toml +++ b/libs/langgraph/pyproject.toml @@ -75,14 +75,6 @@ target-version = "py39" [tool.ruff.lint.per-file-ignores] "tests/bench/*" = ["UP006", "UP007"] -[tool.ruff.format] -quote-style = "double" -indent-style = "space" -skip-magic-trailing-comma = false -line-ending = "auto" -docstring-code-format = false -docstring-code-line-length = "dynamic" - [tool.ruff.lint.flake8-tidy-imports.banned-api] "typing.TypedDict".msg = "Use typing_extensions.TypedDict instead." diff --git a/libs/langgraph/tests/__snapshots__/test_large_cases.ambr b/libs/langgraph/tests/__snapshots__/test_large_cases.ambr index 1a0a5ac2a..fffc7dae0 100644 --- a/libs/langgraph/tests/__snapshots__/test_large_cases.ambr +++ b/libs/langgraph/tests/__snapshots__/test_large_cases.ambr @@ -88,10 +88,10 @@ ''' # --- # name: test_message_graph[memory] - '{"$defs": {"AIMessage": {"additionalProperties": true, "description": "Message from an AI.\\n\\nAIMessage is returned from a chat model as a response to a prompt.\\n\\nThis message represents the output of the model and consists of both\\nthe raw output as returned by the model together standardized fields\\n(e.g., tool calls, usage metadata) added by the LangChain framework.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ai", "default": "ai", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}}, "required": ["content"], "title": "AIMessage", "type": "object"}, "AIMessageChunk": {"additionalProperties": true, "description": "Message chunk from an AI.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "AIMessageChunk", "default": "AIMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}, "tool_call_chunks": {"default": [], "items": {"$ref": "#/$defs/ToolCallChunk"}, "title": "Tool Call Chunks", "type": "array"}, "chunk_position": {"anyOf": [{"const": "last", "type": "string"}, {"type": "null"}], "default": null, "title": "Chunk Position"}}, "required": ["content"], "title": "AIMessageChunk", "type": "object"}, "ChatMessage": {"additionalProperties": true, "description": "Message that can be assigned an arbitrary speaker (i.e. role).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "chat", "default": "chat", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessage", "type": "object"}, "ChatMessageChunk": {"additionalProperties": true, "description": "Chat Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ChatMessageChunk", "default": "ChatMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessageChunk", "type": "object"}, "FunctionMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\nFunctionMessage are an older version of the ToolMessage schema, and\\ndo not contain the tool_call_id field.\\n\\nThe tool_call_id field is used to associate the tool call request with the\\ntool call response. This is useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "function", "default": "function", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessage", "type": "object"}, "FunctionMessageChunk": {"additionalProperties": true, "description": "Function Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "FunctionMessageChunk", "default": "FunctionMessageChunk", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessageChunk", "type": "object"}, "HumanMessage": {"additionalProperties": true, "description": "Message from a human.\\n\\nHumanMessages are messages that are passed in from a human to the model.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import HumanMessage, SystemMessage\\n\\n messages = [\\n SystemMessage(\\n content=\\"You are a helpful assistant! Your name is Bob.\\"\\n ),\\n HumanMessage(\\n content=\\"What is your name?\\"\\n )\\n ]\\n\\n # Instantiate a chat model and invoke it with the messages\\n model = ...\\n print(model.invoke(messages))", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "human", "default": "human", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}}, "required": ["content"], "title": "HumanMessage", "type": "object"}, "HumanMessageChunk": {"additionalProperties": true, "description": "Human Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "HumanMessageChunk", "default": "HumanMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}}, "required": ["content"], "title": "HumanMessageChunk", "type": "object"}, "InputTokenDetails": {"description": "Breakdown of input token counts.\\n\\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"audio\\": 10,\\n \\"cache_creation\\": 200,\\n \\"cache_read\\": 100,\\n }\\n\\n.. versionadded:: 0.3.9\\n\\nMay also hold extra provider-specific keys.", "properties": {"audio": {"title": "Audio", "type": "integer"}, "cache_creation": {"title": "Cache Creation", "type": "integer"}, "cache_read": {"title": "Cache Read", "type": "integer"}}, "title": "InputTokenDetails", "type": "object"}, "InvalidToolCall": {"description": "Allowance for errors made by LLM.\\n\\nHere we add an ``error`` key to surface errors made during generation\\n(e.g., invalid JSON arguments.)", "properties": {"type": {"const": "invalid_tool_call", "title": "Type", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "error": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Error"}, "index": {"anyOf": [{"type": "integer"}, {"type": "string"}], "title": "Index"}, "extras": {"additionalProperties": true, "title": "Extras", "type": "object"}}, "required": ["type", "id", "name", "args", "error"], "title": "InvalidToolCall", "type": "object"}, "OutputTokenDetails": {"description": "Breakdown of output token counts.\\n\\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"audio\\": 10,\\n \\"reasoning\\": 200,\\n }\\n\\n.. versionadded:: 0.3.9", "properties": {"audio": {"title": "Audio", "type": "integer"}, "reasoning": {"title": "Reasoning", "type": "integer"}}, "title": "OutputTokenDetails", "type": "object"}, "SystemMessage": {"additionalProperties": true, "description": "Message for priming AI behavior.\\n\\nThe system message is usually passed in as the first of a sequence\\nof input messages.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import HumanMessage, SystemMessage\\n\\n messages = [\\n SystemMessage(\\n content=\\"You are a helpful assistant! Your name is Bob.\\"\\n ),\\n HumanMessage(\\n content=\\"What is your name?\\"\\n )\\n ]\\n\\n # Define a chat model and invoke it with the messages\\n print(model.invoke(messages))", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "system", "default": "system", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessage", "type": "object"}, "SystemMessageChunk": {"additionalProperties": true, "description": "System Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "SystemMessageChunk", "default": "SystemMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessageChunk", "type": "object"}, "ToolCall": {"description": "Represents a request to call a tool.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"name\\": \\"foo\\",\\n \\"args\\": {\\"a\\": 1},\\n \\"id\\": \\"123\\"\\n }\\n\\n This represents a request to call the tool named \\"foo\\" with arguments {\\"a\\": 1}\\n and an identifier of \\"123\\".", "properties": {"name": {"title": "Name", "type": "string"}, "args": {"additionalProperties": true, "title": "Args", "type": "object"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "type": {"const": "tool_call", "title": "Type", "type": "string"}}, "required": ["name", "args", "id"], "title": "ToolCall", "type": "object"}, "ToolCallChunk": {"description": "A chunk of a tool call (e.g., as part of a stream).\\n\\nWhen merging ToolCallChunks (e.g., via AIMessageChunk.__add__),\\nall string attributes are concatenated. Chunks are only merged if their\\nvalues of `index` are equal and not None.\\n\\nExample:\\n\\n.. code-block:: python\\n\\n left_chunks = [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":\', index=0)]\\n right_chunks = [ToolCallChunk(name=None, args=\'1}\', index=0)]\\n\\n (\\n AIMessageChunk(content=\\"\\", tool_call_chunks=left_chunks)\\n + AIMessageChunk(content=\\"\\", tool_call_chunks=right_chunks)\\n ).tool_call_chunks == [ToolCallChunk(name=\'foo\', args=\'{\\"a\\":1}\', index=0)]", "properties": {"name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "index": {"anyOf": [{"type": "integer"}, {"type": "null"}], "title": "Index"}, "type": {"const": "tool_call_chunk", "title": "Type", "type": "string"}}, "required": ["name", "args", "id", "index"], "title": "ToolCallChunk", "type": "object"}, "ToolMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\nToolMessages contain the result of a tool invocation. Typically, the result\\nis encoded inside the `content` field.\\n\\nExample: A ToolMessage representing a result of 42 from a tool call with id\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import ToolMessage\\n\\n ToolMessage(content=\'42\', tool_call_id=\'call_Jja7J89XsjrOLA5r!MEOW!SL\')\\n\\n\\nExample: A ToolMessage where only part of the tool output is sent to the model\\n and the full output is passed in to artifact.\\n\\n .. versionadded:: 0.2.17\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import ToolMessage\\n\\n tool_output = {\\n \\"stdout\\": \\"From the graph we can see that the correlation between x and y is ...\\",\\n \\"stderr\\": None,\\n \\"artifacts\\": {\\"type\\": \\"image\\", \\"base64_data\\": \\"/9j/4gIcSU...\\"},\\n }\\n\\n ToolMessage(\\n content=tool_output[\\"stdout\\"],\\n artifact=tool_output,\\n tool_call_id=\'call_Jja7J89XsjrOLA5r!MEOW!SL\',\\n )\\n\\nThe tool_call_id field is used to associate the tool call request with the\\ntool call response. This is useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "tool", "default": "tool", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessage", "type": "object"}, "ToolMessageChunk": {"additionalProperties": true, "description": "Tool Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ToolMessageChunk", "default": "ToolMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessageChunk", "type": "object"}, "UsageMetadata": {"description": "Usage metadata for a message, such as token counts.\\n\\nThis is a standard representation of token usage that is consistent across models.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"input_tokens\\": 350,\\n \\"output_tokens\\": 240,\\n \\"total_tokens\\": 590,\\n \\"input_token_details\\": {\\n \\"audio\\": 10,\\n \\"cache_creation\\": 200,\\n \\"cache_read\\": 100,\\n },\\n \\"output_token_details\\": {\\n \\"audio\\": 10,\\n \\"reasoning\\": 200,\\n }\\n }\\n\\n.. versionchanged:: 0.3.9\\n\\n Added ``input_token_details`` and ``output_token_details``.", "properties": {"input_tokens": {"title": "Input Tokens", "type": "integer"}, "output_tokens": {"title": "Output Tokens", "type": "integer"}, "total_tokens": {"title": "Total Tokens", "type": "integer"}, "input_token_details": {"$ref": "#/$defs/InputTokenDetails"}, "output_token_details": {"$ref": "#/$defs/OutputTokenDetails"}}, "required": ["input_tokens", "output_tokens", "total_tokens"], "title": "UsageMetadata", "type": "object"}}, "default": null, "items": {"oneOf": [{"$ref": "#/$defs/AIMessage"}, {"$ref": "#/$defs/HumanMessage"}, {"$ref": "#/$defs/ChatMessage"}, {"$ref": "#/$defs/SystemMessage"}, {"$ref": "#/$defs/FunctionMessage"}, {"$ref": "#/$defs/ToolMessage"}, {"$ref": "#/$defs/AIMessageChunk"}, {"$ref": "#/$defs/HumanMessageChunk"}, {"$ref": "#/$defs/ChatMessageChunk"}, {"$ref": "#/$defs/SystemMessageChunk"}, {"$ref": "#/$defs/FunctionMessageChunk"}, {"$ref": "#/$defs/ToolMessageChunk"}]}, "title": "LangGraphInput", "type": "array"}' + '{"$defs": {"AIMessage": {"additionalProperties": true, "description": "Message from an AI.\\n\\nAIMessage is returned from a chat model as a response to a prompt.\\n\\nThis message represents the output of the model and consists of both\\nthe raw output as returned by the model together standardized fields\\n(e.g., tool calls, usage metadata) added by the LangChain framework.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ai", "default": "ai", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}}, "required": ["content"], "title": "AIMessage", "type": "object"}, "AIMessageChunk": {"additionalProperties": true, "description": "Message chunk from an AI.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "AIMessageChunk", "default": "AIMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}, "tool_call_chunks": {"default": [], "items": {"$ref": "#/$defs/ToolCallChunk"}, "title": "Tool Call Chunks", "type": "array"}}, "required": ["content"], "title": "AIMessageChunk", "type": "object"}, "ChatMessage": {"additionalProperties": true, "description": "Message that can be assigned an arbitrary speaker (i.e. role).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "chat", "default": "chat", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessage", "type": "object"}, "ChatMessageChunk": {"additionalProperties": true, "description": "Chat Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ChatMessageChunk", "default": "ChatMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessageChunk", "type": "object"}, "FunctionMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\nFunctionMessage are an older version of the ToolMessage schema, and\\ndo not contain the tool_call_id field.\\n\\nThe tool_call_id field is used to associate the tool call request with the\\ntool call response. This is useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "function", "default": "function", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessage", "type": "object"}, "FunctionMessageChunk": {"additionalProperties": true, "description": "Function Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "FunctionMessageChunk", "default": "FunctionMessageChunk", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessageChunk", "type": "object"}, "HumanMessage": {"additionalProperties": true, "description": "Message from a human.\\n\\nHumanMessages are messages that are passed in from a human to the model.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import HumanMessage, SystemMessage\\n\\n messages = [\\n SystemMessage(content=\\"You are a helpful assistant! Your name is Bob.\\"),\\n HumanMessage(content=\\"What is your name?\\"),\\n ]\\n\\n # Instantiate a chat model and invoke it with the messages\\n model = ...\\n print(model.invoke(messages))", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "human", "default": "human", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}}, "required": ["content"], "title": "HumanMessage", "type": "object"}, "HumanMessageChunk": {"additionalProperties": true, "description": "Human Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "HumanMessageChunk", "default": "HumanMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}}, "required": ["content"], "title": "HumanMessageChunk", "type": "object"}, "InputTokenDetails": {"description": "Breakdown of input token counts.\\n\\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"audio\\": 10,\\n \\"cache_creation\\": 200,\\n \\"cache_read\\": 100,\\n }\\n\\n.. versionadded:: 0.3.9\\n\\nMay also hold extra provider-specific keys.", "properties": {"audio": {"title": "Audio", "type": "integer"}, "cache_creation": {"title": "Cache Creation", "type": "integer"}, "cache_read": {"title": "Cache Read", "type": "integer"}}, "title": "InputTokenDetails", "type": "object"}, "InvalidToolCall": {"description": "Allowance for errors made by LLM.\\n\\nHere we add an `error` key to surface errors made during generation\\n(e.g., invalid JSON arguments.)", "properties": {"name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "error": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Error"}, "type": {"const": "invalid_tool_call", "title": "Type", "type": "string"}}, "required": ["name", "args", "id", "error"], "title": "InvalidToolCall", "type": "object"}, "OutputTokenDetails": {"description": "Breakdown of output token counts.\\n\\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"audio\\": 10,\\n \\"reasoning\\": 200,\\n }\\n\\n.. versionadded:: 0.3.9", "properties": {"audio": {"title": "Audio", "type": "integer"}, "reasoning": {"title": "Reasoning", "type": "integer"}}, "title": "OutputTokenDetails", "type": "object"}, "SystemMessage": {"additionalProperties": true, "description": "Message for priming AI behavior.\\n\\nThe system message is usually passed in as the first of a sequence\\nof input messages.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import HumanMessage, SystemMessage\\n\\n messages = [\\n SystemMessage(content=\\"You are a helpful assistant! Your name is Bob.\\"),\\n HumanMessage(content=\\"What is your name?\\"),\\n ]\\n\\n # Define a chat model and invoke it with the messages\\n print(model.invoke(messages))", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "system", "default": "system", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessage", "type": "object"}, "SystemMessageChunk": {"additionalProperties": true, "description": "System Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "SystemMessageChunk", "default": "SystemMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessageChunk", "type": "object"}, "ToolCall": {"description": "Represents a request to call a tool.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\"name\\": \\"foo\\", \\"args\\": {\\"a\\": 1}, \\"id\\": \\"123\\"}\\n\\n This represents a request to call the tool named \\"foo\\" with arguments {\\"a\\": 1}\\n and an identifier of \\"123\\".", "properties": {"name": {"title": "Name", "type": "string"}, "args": {"additionalProperties": true, "title": "Args", "type": "object"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "type": {"const": "tool_call", "title": "Type", "type": "string"}}, "required": ["name", "args", "id"], "title": "ToolCall", "type": "object"}, "ToolCallChunk": {"description": "A chunk of a tool call (e.g., as part of a stream).\\n\\nWhen merging ToolCallChunks (e.g., via AIMessageChunk.__add__),\\nall string attributes are concatenated. Chunks are only merged if their\\nvalues of `index` are equal and not None.\\n\\nExample:\\n\\n.. code-block:: python\\n\\n left_chunks = [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":\', index=0)]\\n right_chunks = [ToolCallChunk(name=None, args=\\"1}\\", index=0)]\\n\\n (\\n AIMessageChunk(content=\\"\\", tool_call_chunks=left_chunks)\\n + AIMessageChunk(content=\\"\\", tool_call_chunks=right_chunks)\\n ).tool_call_chunks == [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":1}\', index=0)]", "properties": {"name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "index": {"anyOf": [{"type": "integer"}, {"type": "null"}], "title": "Index"}, "type": {"const": "tool_call_chunk", "title": "Type", "type": "string"}}, "required": ["name", "args", "id", "index"], "title": "ToolCallChunk", "type": "object"}, "ToolMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\nToolMessages contain the result of a tool invocation. Typically, the result\\nis encoded inside the `content` field.\\n\\nExample: A ToolMessage representing a result of 42 from a tool call with id\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import ToolMessage\\n\\n ToolMessage(content=\\"42\\", tool_call_id=\\"call_Jja7J89XsjrOLA5r!MEOW!SL\\")\\n\\n\\nExample: A ToolMessage where only part of the tool output is sent to the model\\n and the full output is passed in to artifact.\\n\\n .. versionadded:: 0.2.17\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import ToolMessage\\n\\n tool_output = {\\n \\"stdout\\": \\"From the graph we can see that the correlation between \\"\\n \\"x and y is ...\\",\\n \\"stderr\\": None,\\n \\"artifacts\\": {\\"type\\": \\"image\\", \\"base64_data\\": \\"/9j/4gIcSU...\\"},\\n }\\n\\n ToolMessage(\\n content=tool_output[\\"stdout\\"],\\n artifact=tool_output,\\n tool_call_id=\\"call_Jja7J89XsjrOLA5r!MEOW!SL\\",\\n )\\n\\nThe tool_call_id field is used to associate the tool call request with the\\ntool call response. This is useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "tool", "default": "tool", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessage", "type": "object"}, "ToolMessageChunk": {"additionalProperties": true, "description": "Tool Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ToolMessageChunk", "default": "ToolMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessageChunk", "type": "object"}, "UsageMetadata": {"description": "Usage metadata for a message, such as token counts.\\n\\nThis is a standard representation of token usage that is consistent across models.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"input_tokens\\": 350,\\n \\"output_tokens\\": 240,\\n \\"total_tokens\\": 590,\\n \\"input_token_details\\": {\\n \\"audio\\": 10,\\n \\"cache_creation\\": 200,\\n \\"cache_read\\": 100,\\n },\\n \\"output_token_details\\": {\\n \\"audio\\": 10,\\n \\"reasoning\\": 200,\\n },\\n }\\n\\n.. versionchanged:: 0.3.9\\n\\n Added ``input_token_details`` and ``output_token_details``.", "properties": {"input_tokens": {"title": "Input Tokens", "type": "integer"}, "output_tokens": {"title": "Output Tokens", "type": "integer"}, "total_tokens": {"title": "Total Tokens", "type": "integer"}, "input_token_details": {"$ref": "#/$defs/InputTokenDetails"}, "output_token_details": {"$ref": "#/$defs/OutputTokenDetails"}}, "required": ["input_tokens", "output_tokens", "total_tokens"], "title": "UsageMetadata", "type": "object"}}, "default": null, "items": {"oneOf": [{"$ref": "#/$defs/AIMessage"}, {"$ref": "#/$defs/HumanMessage"}, {"$ref": "#/$defs/ChatMessage"}, {"$ref": "#/$defs/SystemMessage"}, {"$ref": "#/$defs/FunctionMessage"}, {"$ref": "#/$defs/ToolMessage"}, {"$ref": "#/$defs/AIMessageChunk"}, {"$ref": "#/$defs/HumanMessageChunk"}, {"$ref": "#/$defs/ChatMessageChunk"}, {"$ref": "#/$defs/SystemMessageChunk"}, {"$ref": "#/$defs/FunctionMessageChunk"}, {"$ref": "#/$defs/ToolMessageChunk"}]}, "title": "LangGraphInput", "type": "array"}' # --- # name: test_message_graph[memory].1 - '{"$defs": {"AIMessage": {"additionalProperties": true, "description": "Message from an AI.\\n\\nAIMessage is returned from a chat model as a response to a prompt.\\n\\nThis message represents the output of the model and consists of both\\nthe raw output as returned by the model together standardized fields\\n(e.g., tool calls, usage metadata) added by the LangChain framework.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ai", "default": "ai", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}}, "required": ["content"], "title": "AIMessage", "type": "object"}, "AIMessageChunk": {"additionalProperties": true, "description": "Message chunk from an AI.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "AIMessageChunk", "default": "AIMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}, "tool_call_chunks": {"default": [], "items": {"$ref": "#/$defs/ToolCallChunk"}, "title": "Tool Call Chunks", "type": "array"}, "chunk_position": {"anyOf": [{"const": "last", "type": "string"}, {"type": "null"}], "default": null, "title": "Chunk Position"}}, "required": ["content"], "title": "AIMessageChunk", "type": "object"}, "ChatMessage": {"additionalProperties": true, "description": "Message that can be assigned an arbitrary speaker (i.e. role).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "chat", "default": "chat", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessage", "type": "object"}, "ChatMessageChunk": {"additionalProperties": true, "description": "Chat Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ChatMessageChunk", "default": "ChatMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessageChunk", "type": "object"}, "FunctionMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\nFunctionMessage are an older version of the ToolMessage schema, and\\ndo not contain the tool_call_id field.\\n\\nThe tool_call_id field is used to associate the tool call request with the\\ntool call response. This is useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "function", "default": "function", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessage", "type": "object"}, "FunctionMessageChunk": {"additionalProperties": true, "description": "Function Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "FunctionMessageChunk", "default": "FunctionMessageChunk", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessageChunk", "type": "object"}, "HumanMessage": {"additionalProperties": true, "description": "Message from a human.\\n\\nHumanMessages are messages that are passed in from a human to the model.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import HumanMessage, SystemMessage\\n\\n messages = [\\n SystemMessage(\\n content=\\"You are a helpful assistant! Your name is Bob.\\"\\n ),\\n HumanMessage(\\n content=\\"What is your name?\\"\\n )\\n ]\\n\\n # Instantiate a chat model and invoke it with the messages\\n model = ...\\n print(model.invoke(messages))", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "human", "default": "human", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}}, "required": ["content"], "title": "HumanMessage", "type": "object"}, "HumanMessageChunk": {"additionalProperties": true, "description": "Human Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "HumanMessageChunk", "default": "HumanMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}}, "required": ["content"], "title": "HumanMessageChunk", "type": "object"}, "InputTokenDetails": {"description": "Breakdown of input token counts.\\n\\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"audio\\": 10,\\n \\"cache_creation\\": 200,\\n \\"cache_read\\": 100,\\n }\\n\\n.. versionadded:: 0.3.9\\n\\nMay also hold extra provider-specific keys.", "properties": {"audio": {"title": "Audio", "type": "integer"}, "cache_creation": {"title": "Cache Creation", "type": "integer"}, "cache_read": {"title": "Cache Read", "type": "integer"}}, "title": "InputTokenDetails", "type": "object"}, "InvalidToolCall": {"description": "Allowance for errors made by LLM.\\n\\nHere we add an ``error`` key to surface errors made during generation\\n(e.g., invalid JSON arguments.)", "properties": {"type": {"const": "invalid_tool_call", "title": "Type", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "error": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Error"}, "index": {"anyOf": [{"type": "integer"}, {"type": "string"}], "title": "Index"}, "extras": {"additionalProperties": true, "title": "Extras", "type": "object"}}, "required": ["type", "id", "name", "args", "error"], "title": "InvalidToolCall", "type": "object"}, "OutputTokenDetails": {"description": "Breakdown of output token counts.\\n\\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"audio\\": 10,\\n \\"reasoning\\": 200,\\n }\\n\\n.. versionadded:: 0.3.9", "properties": {"audio": {"title": "Audio", "type": "integer"}, "reasoning": {"title": "Reasoning", "type": "integer"}}, "title": "OutputTokenDetails", "type": "object"}, "SystemMessage": {"additionalProperties": true, "description": "Message for priming AI behavior.\\n\\nThe system message is usually passed in as the first of a sequence\\nof input messages.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import HumanMessage, SystemMessage\\n\\n messages = [\\n SystemMessage(\\n content=\\"You are a helpful assistant! Your name is Bob.\\"\\n ),\\n HumanMessage(\\n content=\\"What is your name?\\"\\n )\\n ]\\n\\n # Define a chat model and invoke it with the messages\\n print(model.invoke(messages))", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "system", "default": "system", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessage", "type": "object"}, "SystemMessageChunk": {"additionalProperties": true, "description": "System Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "SystemMessageChunk", "default": "SystemMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessageChunk", "type": "object"}, "ToolCall": {"description": "Represents a request to call a tool.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"name\\": \\"foo\\",\\n \\"args\\": {\\"a\\": 1},\\n \\"id\\": \\"123\\"\\n }\\n\\n This represents a request to call the tool named \\"foo\\" with arguments {\\"a\\": 1}\\n and an identifier of \\"123\\".", "properties": {"name": {"title": "Name", "type": "string"}, "args": {"additionalProperties": true, "title": "Args", "type": "object"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "type": {"const": "tool_call", "title": "Type", "type": "string"}}, "required": ["name", "args", "id"], "title": "ToolCall", "type": "object"}, "ToolCallChunk": {"description": "A chunk of a tool call (e.g., as part of a stream).\\n\\nWhen merging ToolCallChunks (e.g., via AIMessageChunk.__add__),\\nall string attributes are concatenated. Chunks are only merged if their\\nvalues of `index` are equal and not None.\\n\\nExample:\\n\\n.. code-block:: python\\n\\n left_chunks = [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":\', index=0)]\\n right_chunks = [ToolCallChunk(name=None, args=\'1}\', index=0)]\\n\\n (\\n AIMessageChunk(content=\\"\\", tool_call_chunks=left_chunks)\\n + AIMessageChunk(content=\\"\\", tool_call_chunks=right_chunks)\\n ).tool_call_chunks == [ToolCallChunk(name=\'foo\', args=\'{\\"a\\":1}\', index=0)]", "properties": {"name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "index": {"anyOf": [{"type": "integer"}, {"type": "null"}], "title": "Index"}, "type": {"const": "tool_call_chunk", "title": "Type", "type": "string"}}, "required": ["name", "args", "id", "index"], "title": "ToolCallChunk", "type": "object"}, "ToolMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\nToolMessages contain the result of a tool invocation. Typically, the result\\nis encoded inside the `content` field.\\n\\nExample: A ToolMessage representing a result of 42 from a tool call with id\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import ToolMessage\\n\\n ToolMessage(content=\'42\', tool_call_id=\'call_Jja7J89XsjrOLA5r!MEOW!SL\')\\n\\n\\nExample: A ToolMessage where only part of the tool output is sent to the model\\n and the full output is passed in to artifact.\\n\\n .. versionadded:: 0.2.17\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import ToolMessage\\n\\n tool_output = {\\n \\"stdout\\": \\"From the graph we can see that the correlation between x and y is ...\\",\\n \\"stderr\\": None,\\n \\"artifacts\\": {\\"type\\": \\"image\\", \\"base64_data\\": \\"/9j/4gIcSU...\\"},\\n }\\n\\n ToolMessage(\\n content=tool_output[\\"stdout\\"],\\n artifact=tool_output,\\n tool_call_id=\'call_Jja7J89XsjrOLA5r!MEOW!SL\',\\n )\\n\\nThe tool_call_id field is used to associate the tool call request with the\\ntool call response. This is useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "tool", "default": "tool", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessage", "type": "object"}, "ToolMessageChunk": {"additionalProperties": true, "description": "Tool Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ToolMessageChunk", "default": "ToolMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessageChunk", "type": "object"}, "UsageMetadata": {"description": "Usage metadata for a message, such as token counts.\\n\\nThis is a standard representation of token usage that is consistent across models.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"input_tokens\\": 350,\\n \\"output_tokens\\": 240,\\n \\"total_tokens\\": 590,\\n \\"input_token_details\\": {\\n \\"audio\\": 10,\\n \\"cache_creation\\": 200,\\n \\"cache_read\\": 100,\\n },\\n \\"output_token_details\\": {\\n \\"audio\\": 10,\\n \\"reasoning\\": 200,\\n }\\n }\\n\\n.. versionchanged:: 0.3.9\\n\\n Added ``input_token_details`` and ``output_token_details``.", "properties": {"input_tokens": {"title": "Input Tokens", "type": "integer"}, "output_tokens": {"title": "Output Tokens", "type": "integer"}, "total_tokens": {"title": "Total Tokens", "type": "integer"}, "input_token_details": {"$ref": "#/$defs/InputTokenDetails"}, "output_token_details": {"$ref": "#/$defs/OutputTokenDetails"}}, "required": ["input_tokens", "output_tokens", "total_tokens"], "title": "UsageMetadata", "type": "object"}}, "default": null, "items": {"oneOf": [{"$ref": "#/$defs/AIMessage"}, {"$ref": "#/$defs/HumanMessage"}, {"$ref": "#/$defs/ChatMessage"}, {"$ref": "#/$defs/SystemMessage"}, {"$ref": "#/$defs/FunctionMessage"}, {"$ref": "#/$defs/ToolMessage"}, {"$ref": "#/$defs/AIMessageChunk"}, {"$ref": "#/$defs/HumanMessageChunk"}, {"$ref": "#/$defs/ChatMessageChunk"}, {"$ref": "#/$defs/SystemMessageChunk"}, {"$ref": "#/$defs/FunctionMessageChunk"}, {"$ref": "#/$defs/ToolMessageChunk"}]}, "title": "LangGraphOutput", "type": "array"}' + '{"$defs": {"AIMessage": {"additionalProperties": true, "description": "Message from an AI.\\n\\nAIMessage is returned from a chat model as a response to a prompt.\\n\\nThis message represents the output of the model and consists of both\\nthe raw output as returned by the model together standardized fields\\n(e.g., tool calls, usage metadata) added by the LangChain framework.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ai", "default": "ai", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}}, "required": ["content"], "title": "AIMessage", "type": "object"}, "AIMessageChunk": {"additionalProperties": true, "description": "Message chunk from an AI.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "AIMessageChunk", "default": "AIMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}, "tool_calls": {"default": [], "items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"default": [], "items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}, "tool_call_chunks": {"default": [], "items": {"$ref": "#/$defs/ToolCallChunk"}, "title": "Tool Call Chunks", "type": "array"}}, "required": ["content"], "title": "AIMessageChunk", "type": "object"}, "ChatMessage": {"additionalProperties": true, "description": "Message that can be assigned an arbitrary speaker (i.e. role).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "chat", "default": "chat", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessage", "type": "object"}, "ChatMessageChunk": {"additionalProperties": true, "description": "Chat Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ChatMessageChunk", "default": "ChatMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessageChunk", "type": "object"}, "FunctionMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\nFunctionMessage are an older version of the ToolMessage schema, and\\ndo not contain the tool_call_id field.\\n\\nThe tool_call_id field is used to associate the tool call request with the\\ntool call response. This is useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "function", "default": "function", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessage", "type": "object"}, "FunctionMessageChunk": {"additionalProperties": true, "description": "Function Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "FunctionMessageChunk", "default": "FunctionMessageChunk", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessageChunk", "type": "object"}, "HumanMessage": {"additionalProperties": true, "description": "Message from a human.\\n\\nHumanMessages are messages that are passed in from a human to the model.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import HumanMessage, SystemMessage\\n\\n messages = [\\n SystemMessage(content=\\"You are a helpful assistant! Your name is Bob.\\"),\\n HumanMessage(content=\\"What is your name?\\"),\\n ]\\n\\n # Instantiate a chat model and invoke it with the messages\\n model = ...\\n print(model.invoke(messages))", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "human", "default": "human", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}}, "required": ["content"], "title": "HumanMessage", "type": "object"}, "HumanMessageChunk": {"additionalProperties": true, "description": "Human Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "HumanMessageChunk", "default": "HumanMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "example": {"default": false, "title": "Example", "type": "boolean"}}, "required": ["content"], "title": "HumanMessageChunk", "type": "object"}, "InputTokenDetails": {"description": "Breakdown of input token counts.\\n\\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"audio\\": 10,\\n \\"cache_creation\\": 200,\\n \\"cache_read\\": 100,\\n }\\n\\n.. versionadded:: 0.3.9\\n\\nMay also hold extra provider-specific keys.", "properties": {"audio": {"title": "Audio", "type": "integer"}, "cache_creation": {"title": "Cache Creation", "type": "integer"}, "cache_read": {"title": "Cache Read", "type": "integer"}}, "title": "InputTokenDetails", "type": "object"}, "InvalidToolCall": {"description": "Allowance for errors made by LLM.\\n\\nHere we add an `error` key to surface errors made during generation\\n(e.g., invalid JSON arguments.)", "properties": {"name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "error": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Error"}, "type": {"const": "invalid_tool_call", "title": "Type", "type": "string"}}, "required": ["name", "args", "id", "error"], "title": "InvalidToolCall", "type": "object"}, "OutputTokenDetails": {"description": "Breakdown of output token counts.\\n\\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"audio\\": 10,\\n \\"reasoning\\": 200,\\n }\\n\\n.. versionadded:: 0.3.9", "properties": {"audio": {"title": "Audio", "type": "integer"}, "reasoning": {"title": "Reasoning", "type": "integer"}}, "title": "OutputTokenDetails", "type": "object"}, "SystemMessage": {"additionalProperties": true, "description": "Message for priming AI behavior.\\n\\nThe system message is usually passed in as the first of a sequence\\nof input messages.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import HumanMessage, SystemMessage\\n\\n messages = [\\n SystemMessage(content=\\"You are a helpful assistant! Your name is Bob.\\"),\\n HumanMessage(content=\\"What is your name?\\"),\\n ]\\n\\n # Define a chat model and invoke it with the messages\\n print(model.invoke(messages))", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "system", "default": "system", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessage", "type": "object"}, "SystemMessageChunk": {"additionalProperties": true, "description": "System Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "SystemMessageChunk", "default": "SystemMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessageChunk", "type": "object"}, "ToolCall": {"description": "Represents a request to call a tool.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\"name\\": \\"foo\\", \\"args\\": {\\"a\\": 1}, \\"id\\": \\"123\\"}\\n\\n This represents a request to call the tool named \\"foo\\" with arguments {\\"a\\": 1}\\n and an identifier of \\"123\\".", "properties": {"name": {"title": "Name", "type": "string"}, "args": {"additionalProperties": true, "title": "Args", "type": "object"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "type": {"const": "tool_call", "title": "Type", "type": "string"}}, "required": ["name", "args", "id"], "title": "ToolCall", "type": "object"}, "ToolCallChunk": {"description": "A chunk of a tool call (e.g., as part of a stream).\\n\\nWhen merging ToolCallChunks (e.g., via AIMessageChunk.__add__),\\nall string attributes are concatenated. Chunks are only merged if their\\nvalues of `index` are equal and not None.\\n\\nExample:\\n\\n.. code-block:: python\\n\\n left_chunks = [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":\', index=0)]\\n right_chunks = [ToolCallChunk(name=None, args=\\"1}\\", index=0)]\\n\\n (\\n AIMessageChunk(content=\\"\\", tool_call_chunks=left_chunks)\\n + AIMessageChunk(content=\\"\\", tool_call_chunks=right_chunks)\\n ).tool_call_chunks == [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":1}\', index=0)]", "properties": {"name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "index": {"anyOf": [{"type": "integer"}, {"type": "null"}], "title": "Index"}, "type": {"const": "tool_call_chunk", "title": "Type", "type": "string"}}, "required": ["name", "args", "id", "index"], "title": "ToolCallChunk", "type": "object"}, "ToolMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\nToolMessages contain the result of a tool invocation. Typically, the result\\nis encoded inside the `content` field.\\n\\nExample: A ToolMessage representing a result of 42 from a tool call with id\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import ToolMessage\\n\\n ToolMessage(content=\\"42\\", tool_call_id=\\"call_Jja7J89XsjrOLA5r!MEOW!SL\\")\\n\\n\\nExample: A ToolMessage where only part of the tool output is sent to the model\\n and the full output is passed in to artifact.\\n\\n .. versionadded:: 0.2.17\\n\\n .. code-block:: python\\n\\n from langchain_core.messages import ToolMessage\\n\\n tool_output = {\\n \\"stdout\\": \\"From the graph we can see that the correlation between \\"\\n \\"x and y is ...\\",\\n \\"stderr\\": None,\\n \\"artifacts\\": {\\"type\\": \\"image\\", \\"base64_data\\": \\"/9j/4gIcSU...\\"},\\n }\\n\\n ToolMessage(\\n content=tool_output[\\"stdout\\"],\\n artifact=tool_output,\\n tool_call_id=\\"call_Jja7J89XsjrOLA5r!MEOW!SL\\",\\n )\\n\\nThe tool_call_id field is used to associate the tool call request with the\\ntool call response. This is useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "tool", "default": "tool", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessage", "type": "object"}, "ToolMessageChunk": {"additionalProperties": true, "description": "Tool Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ToolMessageChunk", "default": "ToolMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessageChunk", "type": "object"}, "UsageMetadata": {"description": "Usage metadata for a message, such as token counts.\\n\\nThis is a standard representation of token usage that is consistent across models.\\n\\nExample:\\n\\n .. code-block:: python\\n\\n {\\n \\"input_tokens\\": 350,\\n \\"output_tokens\\": 240,\\n \\"total_tokens\\": 590,\\n \\"input_token_details\\": {\\n \\"audio\\": 10,\\n \\"cache_creation\\": 200,\\n \\"cache_read\\": 100,\\n },\\n \\"output_token_details\\": {\\n \\"audio\\": 10,\\n \\"reasoning\\": 200,\\n },\\n }\\n\\n.. versionchanged:: 0.3.9\\n\\n Added ``input_token_details`` and ``output_token_details``.", "properties": {"input_tokens": {"title": "Input Tokens", "type": "integer"}, "output_tokens": {"title": "Output Tokens", "type": "integer"}, "total_tokens": {"title": "Total Tokens", "type": "integer"}, "input_token_details": {"$ref": "#/$defs/InputTokenDetails"}, "output_token_details": {"$ref": "#/$defs/OutputTokenDetails"}}, "required": ["input_tokens", "output_tokens", "total_tokens"], "title": "UsageMetadata", "type": "object"}}, "default": null, "items": {"oneOf": [{"$ref": "#/$defs/AIMessage"}, {"$ref": "#/$defs/HumanMessage"}, {"$ref": "#/$defs/ChatMessage"}, {"$ref": "#/$defs/SystemMessage"}, {"$ref": "#/$defs/FunctionMessage"}, {"$ref": "#/$defs/ToolMessage"}, {"$ref": "#/$defs/AIMessageChunk"}, {"$ref": "#/$defs/HumanMessageChunk"}, {"$ref": "#/$defs/ChatMessageChunk"}, {"$ref": "#/$defs/SystemMessageChunk"}, {"$ref": "#/$defs/FunctionMessageChunk"}, {"$ref": "#/$defs/ToolMessageChunk"}]}, "title": "LangGraphOutput", "type": "array"}' # --- # name: test_message_graph[memory].2 ''' diff --git a/libs/langgraph/tests/__snapshots__/test_pregel.ambr b/libs/langgraph/tests/__snapshots__/test_pregel.ambr index 5167d8924..d3808a63a 100644 --- a/libs/langgraph/tests/__snapshots__/test_pregel.ambr +++ b/libs/langgraph/tests/__snapshots__/test_pregel.ambr @@ -307,6 +307,99 @@ ''' # --- +# name: test_get_graph_nonterminal_last_step_source + ''' + { + "edges": [ + { + "source": "__start__", + "target": "human" + }, + { + "conditional": true, + "source": "chatbot", + "target": "human" + }, + { + "conditional": true, + "source": "chatbot", + "target": "tools" + }, + { + "conditional": true, + "source": "human", + "target": "__end__" + }, + { + "conditional": true, + "source": "human", + "target": "chatbot" + }, + { + "source": "tools", + "target": "chatbot" + } + ], + "nodes": [ + { + "data": { + "id": [ + "langgraph", + "_internal", + "_runnable", + "RunnableCallable" + ], + "name": "__start__" + }, + "id": "__start__", + "type": "runnable" + }, + { + "data": { + "id": [ + "langgraph", + "_internal", + "_runnable", + "RunnableCallable" + ], + "name": "chatbot" + }, + "id": "chatbot", + "type": "runnable" + }, + { + "data": { + "id": [ + "langgraph", + "_internal", + "_runnable", + "RunnableCallable" + ], + "name": "tools" + }, + "id": "tools", + "type": "runnable" + }, + { + "data": { + "id": [ + "langgraph", + "_internal", + "_runnable", + "RunnableCallable" + ], + "name": "human" + }, + "id": "human", + "type": "runnable" + }, + { + "id": "__end__" + } + ] + } + ''' +# --- # name: test_get_graph_root_channel ''' { diff --git a/libs/langgraph/tests/example_app/langgraph.json b/libs/langgraph/tests/example_app/langgraph.json index 5509e0d68..5d0a88e41 100644 --- a/libs/langgraph/tests/example_app/langgraph.json +++ b/libs/langgraph/tests/example_app/langgraph.json @@ -1,5 +1,5 @@ { - "$schema": "https://raw.githubusercontent.com/langchain-ai/langgraph/refs/heads/main/libs/cli/schemas/schema.json", + "$schema": "https://langgra.ph/schema.json", "graphs": { "app": "tests/example_app/example_graph.py:app" }, diff --git a/libs/langgraph/tests/test_pregel.py b/libs/langgraph/tests/test_pregel.py index 5b23beedc..e7e0cd42a 100644 --- a/libs/langgraph/tests/test_pregel.py +++ b/libs/langgraph/tests/test_pregel.py @@ -3445,6 +3445,73 @@ def test_stream_buffering_single_node(sync_checkpointer: BaseCheckpointSaver) -> ] +def test_nested_graph_resume_reuses_cached_task_writes( + sync_checkpointer: BaseCheckpointSaver, +) -> None: + # Reproduces issue where a helper @task inside a nested graph re-executes + # on resume instead of reusing cached writes. Ensures it runs only once. + counter_parent = 0 + counter_sub = 0 + + @task + def get_time_parent() -> float: + nonlocal counter_parent + counter_parent += 1 + return time.time() + + @task + def get_time_subgraph() -> float: + nonlocal counter_sub + counter_sub += 1 + return time.time() + + class State(TypedDict): + state_counter: int + + # Subgraph that calls a helper task and then interrupts + sub = StateGraph(State) + + def human_node(_: State): + _ = get_time_subgraph().result() + interrupt("what is your name?") + + sub.add_node("human_node", human_node) + sub.set_entry_point("human_node") + sub.set_finish_point("human_node") + subgraph = sub.compile(checkpointer=sync_checkpointer) + + # Parent graph that calls a helper task and interrupts, then enters subgraph + parent = StateGraph(State) + + def parent_node(_: State): + _ = get_time_parent().result() + interrupt("what is your parent name?") + + parent.add_node("parent_node", parent_node) + parent.add_node("subgraph", subgraph) + parent.add_edge(START, "parent_node") + parent.add_edge("parent_node", "subgraph") + parent.add_edge("subgraph", END) + graph = parent.compile(checkpointer=sync_checkpointer) + + cfg_parent = {"configurable": {"thread_id": str(uuid.uuid4())}} + + # First run – interrupts in parent node + for _ in graph.stream({"state_counter": 1}, cfg_parent): + pass + + # Resume 1 – proceeds into subgraph, interrupts there + for _ in graph.stream(Command(resume="resume-1"), cfg_parent): + pass + + # Resume 2 – completes without re-running subgraph helper task + for _ in graph.stream(Command(resume="resume-2"), cfg_parent): + pass + + assert counter_parent == 1 + assert counter_sub == 1 + + def test_nested_graph_interrupts_parallel( sync_checkpointer: BaseCheckpointSaver, durability: Durability ) -> None: @@ -7222,7 +7289,11 @@ def test_parallel_interrupts(sync_checkpointer: BaseCheckpointSaver) -> None: # get human input and resume if len(current_interrupts) > 0: - current_input = Command(resume=f"Resume #{invokes}") + # we resume one at a time to preserve original test behavior, + # but we could also resume all at once if we wanted + # with a single dict mapping of interrupt ids to resume values + resume = {current_interrupts[0].id: f"Resume #{invokes}"} + current_input = Command(resume=resume) # not more human input required, must be completed else: @@ -7383,7 +7454,11 @@ def test_parallel_interrupts_double(sync_checkpointer: BaseCheckpointSaver) -> N # get human input and resume if len(current_interrupts) > 0: - current_input = Command(resume=f"Resume #{invokes}") + # we resume one at a time to preserve original test behavior, + # but we could also resume all at once if we wanted + # with a single dict mapping of interrupt ids to resume values + resume = {current_interrupts[0].id: f"Resume #{invokes}"} + current_input = Command(resume=resume) # not more human input required, must be completed else: @@ -8333,3 +8408,111 @@ def test_subgraph_streaming_sync() -> None: assert result["last_chunk"].content == "today." assert result["num_chunks"] == 9 + + +def test_get_graph_nonterminal_last_step_source(snapshot: SnapshotAssertion) -> None: + class State(TypedDict): + messages: list[str] + + def chatbot_node(state: State) -> State: + return {"messages": state["messages"] + ["chatbot"]} + + def tools_node(state: State) -> State: + return {"messages": state["messages"] + ["tools"]} + + def human_node(state: State) -> State: + return {"messages": state["messages"] + ["human"]} + + def tools_condition(_: State) -> str: + return "tools" + + def end_condition(_: State) -> str: + return "chatbot" + + workflow = StateGraph(State) + workflow.add_node("chatbot", chatbot_node) + workflow.add_node("tools", tools_node) + workflow.add_node("human", human_node) + + workflow.add_edge(START, "human") + workflow.add_edge("tools", "chatbot") + + workflow.add_conditional_edges( + "chatbot", tools_condition, {"tools": "tools", "human": "human"} + ) + workflow.add_conditional_edges( + "human", end_condition, {"chatbot": "chatbot", END: END} + ) + + app = workflow.compile() + graph = app.get_graph() + graph_json = graph.to_json() + + assert json.dumps(graph_json, indent=2, sort_keys=True) == snapshot + + +def test_null_resume_disallowed_with_multiple_interrupts( + sync_checkpointer: BaseCheckpointSaver, +) -> None: + class State(TypedDict): + text_1: str + text_2: str + + def human_node_1(state: State): + value = interrupt({"text_to_revise": state["text_1"]}) + return {"text_1": value} + + def human_node_2(state: State): + value = interrupt({"text_to_revise": state["text_2"]}) + return {"text_2": value} + + graph_builder = StateGraph(State) + graph_builder.add_node("human_node_1", human_node_1) + graph_builder.add_node("human_node_2", human_node_2) + + # Add both nodes in parallel from START + graph_builder.add_edge(START, "human_node_1") + graph_builder.add_edge(START, "human_node_2") + + checkpointer = InMemorySaver() + graph = graph_builder.compile(checkpointer=checkpointer) + + thread_id = str(uuid.uuid4()) + config: RunnableConfig = {"configurable": {"thread_id": thread_id}} + graph.invoke( + {"text_1": "original text 1", "text_2": "original text 2"}, config=config + ) + + resume_map = { + i.id: f"resume for prompt: {i.value['text_to_revise']}" + for i in graph.get_state(config).interrupts + } + with pytest.raises( + RuntimeError, + match="When there are multiple pending interrupts, you must specify the interrupt id when resuming.", + ): + graph.invoke(Command(resume="singular resume"), config=config) + + assert graph.invoke(Command(resume=resume_map), config=config) == { + "text_1": "resume for prompt: original text 1", + "text_2": "resume for prompt: original text 2", + } + + +def test_interrupt_stream_mode_values(): + """Test that interrupts are surfaced when steam_mode='values'""" + + class State(TypedDict): + human_input: str + + def human_input_node(state: State) -> Command: + human_input = interrupt("interrupt") + return Command(update={"human_input": human_input}) + + builder = StateGraph(State) + builder.add_node(human_input_node) + builder.add_edge(START, "human_input_node") + app = builder.compile() + + result = [*app.stream(State(), stream_mode="values")] + assert "__interrupt__" in result[-1] diff --git a/libs/langgraph/tests/test_pregel_async.py b/libs/langgraph/tests/test_pregel_async.py index 5b4a1f3ad..8002ca68c 100644 --- a/libs/langgraph/tests/test_pregel_async.py +++ b/libs/langgraph/tests/test_pregel_async.py @@ -41,6 +41,7 @@ from syrupy import SnapshotAssertion from typing_extensions import NotRequired, TypedDict from langgraph._internal._constants import CONFIG_KEY_NODE_FINISHED, ERROR, PULL +from langgraph._internal._queue import AsyncQueue from langgraph.channels.binop import BinaryOperatorAggregate from langgraph.channels.last_value import LastValue from langgraph.channels.topic import Topic @@ -9107,3 +9108,106 @@ async def test_subgraph_streaming_async() -> None: assert result["last_chunk"].content == "today." assert result["num_chunks"] == 9 + + +@NEEDS_CONTEXTVARS +async def test_null_resume_disallowed_with_multiple_interrupts( + async_checkpointer: BaseCheckpointSaver, +) -> None: + class State(TypedDict): + text_1: str + text_2: str + + async def human_node_1(state: State): + value = interrupt(state["text_1"]) + return {"text_1": value} + + async def human_node_2(state: State): + value = interrupt(state["text_2"]) + return {"text_2": value} + + graph_builder = StateGraph(State) + graph_builder.add_node("human_node_1", human_node_1) + graph_builder.add_node("human_node_2", human_node_2) + + # Add both nodes in parallel from START + graph_builder.add_edge(START, "human_node_1") + graph_builder.add_edge(START, "human_node_2") + + checkpointer = InMemorySaver() + graph = graph_builder.compile(checkpointer=checkpointer) + + thread_id = str(uuid.uuid4()) + config: RunnableConfig = {"configurable": {"thread_id": thread_id}} + await graph.ainvoke( + {"text_1": "original text 1", "text_2": "original text 2"}, config=config + ) + + resume_map = { + i.id: f"resume for prompt: {i.value}" + for i in (await graph.aget_state(config)).interrupts + } + with pytest.raises( + RuntimeError, + match="When there are multiple pending interrupts, you must specify the interrupt id when resuming.", + ): + await graph.ainvoke(Command(resume="singular resume"), config=config) + + assert await graph.ainvoke(Command(resume=resume_map), config=config) == { + "text_1": "resume for prompt: original text 1", + "text_2": "resume for prompt: original text 2", + } + + +async def test_astream_waiter_cleanup_on_cancel( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Test that AsyncPregelLoop cleans up waiter tasks after cancellation.""" + + recorded_tasks: list[asyncio.Task[None]] = [] + finished_tasks: list[asyncio.Task[None]] = [] + + original_wait = AsyncQueue.wait + + async def tracked_wait(self: AsyncQueue) -> None: + task = asyncio.current_task() + assert task is not None + recorded_tasks.append(task) + try: + await original_wait(self) + finally: + finished_tasks.append(task) + + monkeypatch.setattr(AsyncQueue, "wait", tracked_wait) + + class State(TypedDict, total=False): + count: int + + async def slow_node(state: State) -> State: + await asyncio.sleep(0.05) + state = dict(state) + state["count"] = state.get("count", 0) + 1 + await asyncio.sleep(0.1) + return state + + builder = StateGraph(State) + builder.add_node("slow", slow_node) + builder.add_edge(START, "slow") + builder.add_edge("slow", END) + graph = builder.compile() + + async def consumer() -> None: + async for _ in graph.astream({"msg": "hi"}, stream_mode="messages"): + await asyncio.sleep(0.01) + + task = asyncio.create_task(consumer()) + await asyncio.sleep(0.05) + task.cancel() + with pytest.raises(asyncio.CancelledError): + await task + + await asyncio.sleep(0.05) + + assert recorded_tasks, "expected stream.wait() task to be created" + assert set(finished_tasks) == set(recorded_tasks) + assert all(t.done() for t in recorded_tasks) diff --git a/libs/langgraph/tests/test_runnable.py b/libs/langgraph/tests/test_runnable.py index 02e19b56a..e7d1950ce 100644 --- a/libs/langgraph/tests/test_runnable.py +++ b/libs/langgraph/tests/test_runnable.py @@ -394,3 +394,21 @@ def test_config_injection() -> None: assert RunnableCallable(func_untyped).invoke( "test", config={"tags": ["test"], "configurable": {}} ) == ["test"] + + +def test_config_ensured() -> None: + def func(input: str, config: RunnableConfig) -> None: + assert input == "test" + assert config is not None + assert config.get("configurable") is not None + + RunnableCallable(func).invoke("test") + + +async def test_config_ensured_async() -> None: + async def func(input: str, config: RunnableConfig) -> None: + assert input == "test" + assert config is not None + assert config.get("configurable") is not None + + await RunnableCallable(func).ainvoke("test") diff --git a/libs/langgraph/tests/test_state.py b/libs/langgraph/tests/test_state.py index 67988ef09..6b484383c 100644 --- a/libs/langgraph/tests/test_state.py +++ b/libs/langgraph/tests/test_state.py @@ -2,7 +2,7 @@ import inspect import operator import warnings from dataclasses import dataclass, field -from typing import Annotated, Any, Optional +from typing import Annotated, Any, Optional, Union from typing import Annotated as Annotated2 import pytest @@ -11,7 +11,13 @@ from pydantic import BaseModel from typing_extensions import NotRequired, Required, TypedDict from langgraph.channels.binop import BinaryOperatorAggregate -from langgraph.graph.state import StateGraph, _get_node_name, _warn_invalid_state_schema +from langgraph.channels.ephemeral_value import EphemeralValue +from langgraph.graph.state import ( + StateGraph, + _get_node_name, + _is_field_channel, + _warn_invalid_state_schema, +) class State(BaseModel): @@ -335,3 +341,33 @@ def 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isinstance(user, types.StudioUser) or isinstance(user, dict) - and user.get("kind") == "StudioUser" + and user.get("kind") == "StudioUser" # ty: ignore[invalid-argument-type] ) diff --git a/libs/sdk-py/langgraph_sdk/auth/types.py b/libs/sdk-py/langgraph_sdk/auth/types.py index 4a7912ea3..097af5a2a 100644 --- a/libs/sdk-py/langgraph_sdk/auth/types.py +++ b/libs/sdk-py/langgraph_sdk/auth/types.py @@ -58,7 +58,14 @@ Values: """ FilterType = typing.Union[ - dict[str, typing.Union[str, dict[typing.Literal["$eq", "$contains"], str]]], + dict[ + str, + typing.Union[ + str, + dict[typing.Literal["$eq", "$contains"], str], + dict[typing.Literal["$contains"], list[str]], + ], + ], dict[str, str], ] """Response type for authorization handlers. @@ -66,24 +73,33 @@ FilterType = typing.Union[ Supports exact matches and operators: - Exact match shorthand: {"field": "value"} - Exact match: {"field": {"$eq": "value"}} - - Contains: {"field": {"$contains": "value"}} + - Contains (membership): {"field": {"$contains": "value"}} + - Contains (subset containment): {"field": {"$contains": ["value1", "value2"]}} + +Subset containment is only supported by newer versions of the LangGraph dev server; +install langgraph-runtime-inmem >= 0.14.1 to use this filter variant. ???+ example "Examples" Simple exact match filter for the resource owner: ```python filter = {"owner": "user-abcd123"} ``` - + Explicit version of the exact match filter: ```python filter = {"owner": {"$eq": "user-abcd123"}} ``` - - Containment: + + Containment (membership of a single element): ```python filter = {"participants": {"$contains": "user-abcd123"}} ``` + Containment (subset containment; all values must be present, but order doesn't matter): + ```python + filter = {"participants": {"$contains": ["user-abcd123", "user-efgh456"]}} + ``` + Combining filters (treated as a logical `AND`): ```python filter = {"owner": "user-abcd123", "participants": {"$contains": "user-efgh456"}} diff --git a/libs/sdk-py/langgraph_sdk/client.py b/libs/sdk-py/langgraph_sdk/client.py index 71d256fce..f08d7b1fc 100644 --- a/libs/sdk-py/langgraph_sdk/client.py +++ b/libs/sdk-py/langgraph_sdk/client.py @@ -31,6 +31,7 @@ import httpx import orjson import langgraph_sdk +from langgraph_sdk.errors import _araise_for_status_typed, _raise_for_status_typed from langgraph_sdk.schema import ( All, Assistant, @@ -310,15 +311,7 @@ class HttpClient: r = await self.client.get(path, params=params, headers=headers) if on_response: on_response(r) - try: - r.raise_for_status() - except httpx.HTTPStatusError as e: - body = (await r.aread()).decode() - if sys.version_info >= (3, 11): - e.add_note(body) - else: - logger.error(f"Error from langgraph-api: {body}", exc_info=e) - raise e + await _araise_for_status_typed(r) return await _adecode_json(r) async def post( @@ -343,15 +336,7 @@ class HttpClient: ) if on_response: on_response(r) - try: - r.raise_for_status() - except httpx.HTTPStatusError as e: - body = (await r.aread()).decode() - if sys.version_info >= (3, 11): - e.add_note(body) - else: - logger.error(f"Error from langgraph-api: {body}", exc_info=e) - raise e + await _araise_for_status_typed(r) return await _adecode_json(r) async def put( @@ -372,15 +357,7 @@ class HttpClient: ) if on_response: on_response(r) - try: - r.raise_for_status() - except httpx.HTTPStatusError as e: - body = (await r.aread()).decode() - if sys.version_info >= (3, 11): - e.add_note(body) - else: - logger.error(f"Error from langgraph-api: {body}", exc_info=e) - raise e + await _araise_for_status_typed(r) return await _adecode_json(r) async def patch( @@ -401,15 +378,7 @@ class HttpClient: ) if on_response: on_response(r) - try: - r.raise_for_status() - except httpx.HTTPStatusError as e: - body = (await r.aread()).decode() - if sys.version_info >= (3, 11): - e.add_note(body) - else: - logger.error(f"Error from langgraph-api: {body}", exc_info=e) - raise e + await _araise_for_status_typed(r) return await _adecode_json(r) async def delete( @@ -427,15 +396,55 @@ class HttpClient: ) if on_response: on_response(r) - try: - r.raise_for_status() - except httpx.HTTPStatusError as e: - body = (await r.aread()).decode() - if sys.version_info >= (3, 11): - e.add_note(body) - else: - logger.error(f"Error from langgraph-api: {body}", exc_info=e) - raise e + await _araise_for_status_typed(r) + + async def request_reconnect( + self, + path: str, + method: str, + *, + json: dict[str, Any] | None = None, + params: QueryParamTypes | None = None, + headers: Mapping[str, str] | None = None, + on_response: Callable[[httpx.Response], None] | None = None, + reconnect_limit: int = 5, + ) -> Any: + """Send a request that automatically reconnects to Location header.""" + request_headers, content = await _aencode_json(json) + if headers: + request_headers.update(headers) + async with self.client.stream( + method, path, headers=request_headers, content=content, params=params + ) as r: + if on_response: + on_response(r) + try: + r.raise_for_status() + except httpx.HTTPStatusError as e: + body = (await r.aread()).decode() + if sys.version_info >= (3, 11): + e.add_note(body) + else: + logger.error(f"Error from langgraph-api: {body}", exc_info=e) + raise e + loc = r.headers.get("location") + if reconnect_limit <= 0 or not loc: + return await _adecode_json(r) + try: + return await _adecode_json(r) + except httpx.HTTPError: + warnings.warn( + f"Request failed, attempting reconnect to Location: {loc}", + stacklevel=2, + ) + await r.aclose() + return await self.request_reconnect( + loc, + "GET", + headers=request_headers, + # don't pass on_response so it's only called once + reconnect_limit=reconnect_limit - 1, + ) async def stream( self, @@ -455,34 +464,86 @@ class HttpClient: if headers: request_headers.update(headers) - async with self.client.stream( - method, path, headers=request_headers, content=content, params=params - ) as res: - if on_response: - on_response(res) - # check status - try: - res.raise_for_status() - except httpx.HTTPStatusError as e: - body = (await res.aread()).decode() - if sys.version_info >= (3, 11): - e.add_note(body) + reconnect_headers = { + key: value + for key, value in request_headers.items() + if key.lower() not in {"content-length", "content-type"} + } + + last_event_id: str | None = None + reconnect_path: str | None = None + reconnect_attempts = 0 + max_reconnect_attempts = 5 + + while True: + current_headers = dict( + request_headers if reconnect_path is None else reconnect_headers + ) + if last_event_id is not None: + current_headers["Last-Event-ID"] = last_event_id + + current_method = method if reconnect_path is None else "GET" + current_content = content if reconnect_path is None else None + current_params = params if reconnect_path is None else None + + retry = False + async with self.client.stream( + current_method, + reconnect_path or path, + headers=current_headers, + content=current_content, + params=current_params, + ) as res: + if reconnect_path is None and on_response: + on_response(res) + # check status + await _araise_for_status_typed(res) + # check content type + content_type = res.headers.get("content-type", "").partition(";")[0] + if "text/event-stream" not in content_type: + raise httpx.TransportError( + "Expected response header Content-Type to contain 'text/event-stream', " + f"got {content_type!r}" + ) + + reconnect_location = res.headers.get("location") + if reconnect_location: + reconnect_path = reconnect_location + + # parse SSE + decoder = SSEDecoder() + try: + async for line in aiter_lines_raw(res): + sse = decoder.decode(line=line.rstrip(b"\n")) + if sse is not None: + if decoder.last_event_id is not None: + last_event_id = decoder.last_event_id + if sse.event or sse.data is not None: + yield sse + except httpx.HTTPError: + # httpx.TransportError inherits from HTTPError, so transient + # disconnects during streaming land here. + if reconnect_path is None: + raise + retry = True else: - logger.error(f"Error from langgraph-api: {body}", exc_info=e) - raise e - # check content type - content_type = res.headers.get("content-type", "").partition(";")[0] - if "text/event-stream" not in content_type: - raise httpx.TransportError( - "Expected response header Content-Type to contain 'text/event-stream', " - f"got {content_type!r}" - ) - # parse SSE - decoder = SSEDecoder() - async for line in aiter_lines_raw(res): - sse = decoder.decode(line=line.rstrip(b"\n")) - if sse is not None: - yield sse + if sse := decoder.decode(b""): + if decoder.last_event_id is not None: + last_event_id = decoder.last_event_id + if sse.event or sse.data is not None: + # decoder.decode(b"") flushes the in-flight event and may + # return an empty placeholder when there is no pending + # message. Skip these no-op events so the stream doesn't + # emit a trailing blank item after reconnects. + yield sse + if retry: + reconnect_attempts += 1 + if reconnect_attempts > max_reconnect_attempts: + raise httpx.TransportError( + "Exceeded maximum SSE reconnection attempts" + ) + continue + break async def _aencode_json(json: Any) -> tuple[dict[str, str], bytes | None]: @@ -2473,8 +2534,9 @@ class RunsClient: if on_run_created and (metadata := _get_run_metadata_from_response(res)): on_run_created(metadata) - response = await self.http.post( + response = await self.http.request_reconnect( endpoint, + "POST", json={k: v for k, v in payload.items() if v is not None}, params=params, headers=headers, @@ -2619,12 +2681,20 @@ class RunsClient: } if params: query_params.update(params) - return await self.http.post( - f"/threads/{thread_id}/runs/{run_id}/cancel", - json=None, - params=query_params, - headers=headers, - ) + if wait: + return await self.http.request_reconnect( + f"/threads/{thread_id}/runs/{run_id}/cancel", + "POST", + params=query_params, + headers=headers, + ) + else: + return await self.http.post( + f"/threads/{thread_id}/runs/{run_id}/cancel", + json=None, + params=query_params, + headers=headers, + ) async def join( self, @@ -2656,8 +2726,11 @@ class RunsClient: ``` """ # noqa: E501 - return await self.http.get( - f"/threads/{thread_id}/runs/{run_id}/join", headers=headers, params=params + return await self.http.request_reconnect( + f"/threads/{thread_id}/runs/{run_id}/join", + "GET", + headers=headers, + params=params, ) def join_stream( @@ -3502,15 +3575,7 @@ class SyncHttpClient: r = self.client.get(path, params=params, headers=headers) if on_response: on_response(r) - try: - r.raise_for_status() - except httpx.HTTPStatusError as e: - body = r.read().decode() - if sys.version_info >= (3, 11): - e.add_note(body) - else: - logger.error(f"Error from langgraph-api: {body}", exc_info=e) - raise e + _raise_for_status_typed(r) return _decode_json(r) def post( @@ -3534,15 +3599,7 @@ class SyncHttpClient: ) if on_response: on_response(r) - try: - r.raise_for_status() - except httpx.HTTPStatusError as e: - body = r.read().decode() - if sys.version_info >= (3, 11): - e.add_note(body) - else: - logger.error(f"Error from langgraph-api: {body}", exc_info=e) - raise e + _raise_for_status_typed(r) return _decode_json(r) def put( @@ -3564,15 +3621,7 @@ class SyncHttpClient: ) if on_response: on_response(r) - try: - r.raise_for_status() - except httpx.HTTPStatusError as e: - body = r.read().decode() - if sys.version_info >= (3, 11): - e.add_note(body) - else: - logger.error(f"Error from langgraph-api: {body}", exc_info=e) - raise e + _raise_for_status_typed(r) return _decode_json(r) def patch( @@ -3593,15 +3642,7 @@ class SyncHttpClient: ) if on_response: on_response(r) - try: - r.raise_for_status() - except httpx.HTTPStatusError as e: - body = r.read().decode() - if sys.version_info >= (3, 11): - e.add_note(body) - else: - logger.error(f"Error from langgraph-api: {body}", exc_info=e) - raise e + _raise_for_status_typed(r) return _decode_json(r) def delete( @@ -3619,15 +3660,55 @@ class SyncHttpClient: ) if on_response: on_response(r) - try: - r.raise_for_status() - except httpx.HTTPStatusError as e: - body = r.read().decode() - if sys.version_info >= (3, 11): - e.add_note(body) - else: - logger.error(f"Error from langgraph-api: {body}", exc_info=e) - raise e + _raise_for_status_typed(r) + + def request_reconnect( + self, + path: str, + method: str, + *, + json: dict[str, Any] | None = None, + params: QueryParamTypes | None = None, + headers: Mapping[str, str] | None = None, + on_response: Callable[[httpx.Response], None] | None = None, + reconnect_limit: int = 5, + ) -> Any: + """Send a request that automatically reconnects to Location header.""" + request_headers, content = _encode_json(json) + if headers: + request_headers.update(headers) + with self.client.stream( + method, path, headers=request_headers, content=content, params=params + ) as r: + if on_response: + on_response(r) + try: + r.raise_for_status() + except httpx.HTTPStatusError as e: + body = r.read().decode() + if sys.version_info >= (3, 11): + e.add_note(body) + else: + logger.error(f"Error from langgraph-api: {body}", exc_info=e) + raise e + loc = r.headers.get("location") + if reconnect_limit <= 0 or not loc: + return _decode_json(r) + try: + return _decode_json(r) + except httpx.HTTPError: + warnings.warn( + f"Request failed, attempting reconnect to Location: {loc}", + stacklevel=2, + ) + r.close() + return self.request_reconnect( + loc, + "GET", + headers=request_headers, + # don't pass on_response so it's only called once + reconnect_limit=reconnect_limit - 1, + ) def stream( self, @@ -3640,39 +3721,92 @@ class SyncHttpClient: on_response: Callable[[httpx.Response], None] | None = None, ) -> Iterator[StreamPart]: """Stream the results of a request using SSE.""" - request_headers, content = _encode_json(json) + if json is not None: + request_headers, content = _encode_json(json) + else: + request_headers, content = {}, None request_headers["Accept"] = "text/event-stream" request_headers["Cache-Control"] = "no-store" if headers: request_headers.update(headers) - with self.client.stream( - method, path, headers=request_headers, content=content, params=params - ) as res: - if on_response: - on_response(res) - # check status - try: - res.raise_for_status() - except httpx.HTTPStatusError as e: - body = (res.read()).decode() - if sys.version_info >= (3, 11): - e.add_note(body) + + reconnect_headers = { + key: value + for key, value in request_headers.items() + if key.lower() not in {"content-length", "content-type"} + } + + last_event_id: str | None = None + reconnect_path: str | None = None + reconnect_attempts = 0 + max_reconnect_attempts = 5 + + while True: + current_headers = dict( + request_headers if reconnect_path is None else reconnect_headers + ) + if last_event_id is not None: + current_headers["Last-Event-ID"] = last_event_id + + current_method = method if reconnect_path is None else "GET" + current_content = content if reconnect_path is None else None + current_params = params if reconnect_path is None else None + + retry = False + with self.client.stream( + current_method, + reconnect_path or path, + headers=current_headers, + content=current_content, + params=current_params, + ) as res: + if reconnect_path is None and on_response: + on_response(res) + # check status + _raise_for_status_typed(res) + # check content type + content_type = res.headers.get("content-type", "").partition(";")[0] + if "text/event-stream" not in content_type: + raise httpx.TransportError( + "Expected response header Content-Type to contain 'text/event-stream', " + f"got {content_type!r}" + ) + + reconnect_location = res.headers.get("location") + if reconnect_location: + reconnect_path = reconnect_location + + decoder = SSEDecoder() + try: + for line in iter_lines_raw(res): + sse = decoder.decode(line.rstrip(b"\n")) + if sse is not None: + if decoder.last_event_id is not None: + last_event_id = decoder.last_event_id + if sse.event or sse.data is not None: + yield sse + except httpx.HTTPError: + # httpx.TransportError inherits from HTTPError, so transient + # disconnects during streaming land here. + if reconnect_path is None: + raise + retry = True else: - logger.error(f"Error from langgraph-api: {body}", exc_info=e) - raise e - # check content type - content_type = res.headers.get("content-type", "").partition(";")[0] - if "text/event-stream" not in content_type: - raise httpx.TransportError( - "Expected response header Content-Type to contain 'text/event-stream', " - f"got {content_type!r}" - ) - # parse SSE - decoder = SSEDecoder() - for line in iter_lines_raw(res): - sse = decoder.decode(line.rstrip(b"\n")) - if sse is not None: - yield sse + if sse := decoder.decode(b""): + if decoder.last_event_id is not None: + last_event_id = decoder.last_event_id + if sse.event or sse.data is not None: + # See async stream implementation for rationale on + # skipping empty flush events. + yield sse + if retry: + reconnect_attempts += 1 + if reconnect_attempts > max_reconnect_attempts: + raise httpx.TransportError( + "Exceeded maximum SSE reconnection attempts" + ) + continue + break def _encode_json(json: Any) -> tuple[dict[str, str], bytes]: @@ -5633,8 +5767,9 @@ class SyncRunsClient: endpoint = ( f"/threads/{thread_id}/runs/wait" if thread_id is not None else "/runs/wait" ) - return self.http.post( + return self.http.request_reconnect( endpoint, + "POST", json={k: v for k, v in payload.items() if v is not None}, params=params, headers=headers, @@ -5757,11 +5892,25 @@ class SyncRunsClient: ``` """ # noqa: E501 + query_params = { + "wait": 1 if wait else 0, + "action": action, + } + if params: + query_params.update(params) + if wait: + return self.http.request_reconnect( + f"/threads/{thread_id}/runs/{run_id}/cancel", + "POST", + json=None, + params=query_params, + headers=headers, + ) return self.http.post( - f"/threads/{thread_id}/runs/{run_id}/cancel?wait={1 if wait else 0}&action={action}", + f"/threads/{thread_id}/runs/{run_id}/cancel", json=None, + params=query_params, headers=headers, - params=params, ) def join( @@ -5794,8 +5943,11 @@ class SyncRunsClient: ``` """ # noqa: E501 - return self.http.get( - f"/threads/{thread_id}/runs/{run_id}/join", headers=headers, params=params + return self.http.request_reconnect( + f"/threads/{thread_id}/runs/{run_id}/join", + "GET", + headers=headers, + params=params, ) def join_stream( diff --git a/libs/sdk-py/langgraph_sdk/errors.py b/libs/sdk-py/langgraph_sdk/errors.py new file mode 100644 index 000000000..3b793cd68 --- /dev/null +++ b/libs/sdk-py/langgraph_sdk/errors.py @@ -0,0 +1,222 @@ +from __future__ import annotations + +import logging +import sys +from typing import Any, Literal, cast + +import httpx +import orjson + +logger = logging.getLogger(__name__) + + +class LangGraphError(Exception): + pass + + +class APIError(httpx.HTTPStatusError, LangGraphError): + message: str + request: httpx.Request + + body: object | None + code: str | None + param: str | None + type: str | None + + def __init__( + self, message: str, response: httpx.Response, *, body: object | None + ) -> None: + httpx.HTTPStatusError.__init__( + self, message, request=response.request, response=response + ) + LangGraphError.__init__(self) + + self.request = response.request + self.message = message + self.body = body + + if isinstance(body, dict): + b = cast(dict[str, Any], body) + # Best-effort extraction of common fields if present + code_val = b.get("code") + self.code = code_val if isinstance(code_val, str) else None + param_val = b.get("param") + self.param = param_val if isinstance(param_val, str) else None + t = b.get("type") + self.type = t if isinstance(t, str) else None + else: + self.code = None + self.param = None + self.type = None + + +class APIResponseValidationError(APIError): + response: httpx.Response + status_code: int + + def __init__( + self, + response: httpx.Response, + body: object | None, + *, + message: str | None = None, + ) -> None: + super().__init__( + message or "Data returned by API invalid for expected schema.", + response, + body=body, + ) + self.response = response + self.status_code = response.status_code + + +class APIStatusError(APIError): + response: httpx.Response + status_code: int + request_id: str | None + + def __init__( + self, message: str, *, response: httpx.Response, body: object | None + ) -> None: + super().__init__(message, response, body=body) + self.response = response + self.status_code = response.status_code + self.request_id = response.headers.get("x-request-id") + + +class APIConnectionError(APIError): + def __init__( + self, *, message: str = "Connection error.", request: httpx.Request + ) -> None: + super().__init__(message, request, body=None) + + +class APITimeoutError(APIConnectionError): + def __init__(self, request: httpx.Request) -> None: + super().__init__(message="Request timed out.", request=request) + + +class BadRequestError(APIStatusError): + status_code: Literal[400] = 400 + + +class AuthenticationError(APIStatusError): + status_code: Literal[401] = 401 + + +class PermissionDeniedError(APIStatusError): + status_code: Literal[403] = 403 + + +class NotFoundError(APIStatusError): + status_code: Literal[404] = 404 + + +class ConflictError(APIStatusError): + status_code: Literal[409] = 409 + + +class UnprocessableEntityError(APIStatusError): + status_code: Literal[422] = 422 + + +class RateLimitError(APIStatusError): + status_code: Literal[429] = 429 + + +class InternalServerError(APIStatusError): + pass + + +def _extract_error_message(body: object | None, fallback: str) -> str: + if isinstance(body, dict): + b = cast(dict[str, Any], body) + for key in ("message", "detail", "error"): + val = b.get(key) + if isinstance(val, str) and val: + return val + # Sometimes errors are structured like {"error": {"message": "..."}} + err = b.get("error") + if isinstance(err, dict): + e = cast(dict[str, Any], err) + for key in ("message", "detail"): + val = e.get(key) + if isinstance(val, str) and val: + return val + return fallback + + +async def _adecode_error_body(r: httpx.Response) -> object | None: + try: + data = await r.aread() + except Exception: + return None + if not data: + return None + try: + return orjson.loads(data) + except Exception: + try: + return data.decode() + except Exception: + return None + + +def _decode_error_body(r: httpx.Response) -> object | None: + try: + data = r.read() + except Exception: + return None + if not data: + return None + try: + return orjson.loads(data) + except Exception: + try: + return data.decode() + except Exception: + return None + + +def _map_status_error(response: httpx.Response, body: object | None) -> APIStatusError: + status = response.status_code + reason = response.reason_phrase or "HTTP Error" + message = _extract_error_message(body, f"{status} {reason}") + if status == 400: + return BadRequestError(message, response=response, body=body) + if status == 401: + return AuthenticationError(message, response=response, body=body) + if status == 403: + return PermissionDeniedError(message, response=response, body=body) + if status == 404: + return NotFoundError(message, response=response, body=body) + if status == 409: + return ConflictError(message, response=response, body=body) + if status == 422: + return UnprocessableEntityError(message, response=response, body=body) + if status == 429: + return RateLimitError(message, response=response, body=body) + if 500 <= status: + return InternalServerError(message, response=response, body=body) + return APIStatusError(message, response=response, body=body) + + +async def _araise_for_status_typed(r: httpx.Response) -> None: + if r.status_code < 400: + return + body = await _adecode_error_body(r) + err = _map_status_error(r, body) + # Log for older Python versions without Exception notes + if not (sys.version_info >= (3, 11)): + logger.error(f"Error from langgraph-api: {getattr(err, 'message', '')}") + raise err + + +def _raise_for_status_typed(r: httpx.Response) -> None: + if r.status_code < 400: + return + body = _decode_error_body(r) + err = _map_status_error(r, body) + if not (sys.version_info >= (3, 11)): + logger.error(f"Error from langgraph-api: {getattr(err, 'message', '')}") + raise err diff --git a/libs/sdk-py/langgraph_sdk/sse.py b/libs/sdk-py/langgraph_sdk/sse.py index 42484df45..01bb333ac 100644 --- a/libs/sdk-py/langgraph_sdk/sse.py +++ b/libs/sdk-py/langgraph_sdk/sse.py @@ -81,6 +81,12 @@ class SSEDecoder: self._last_event_id = "" self._retry: int | None = None + @property + def last_event_id(self) -> str | None: + """Return the last event identifier that was seen.""" + + return self._last_event_id or None + def decode(self, line: bytes) -> StreamPart | None: # See: https://html.spec.whatwg.org/multipage/server-sent-events.html#event-stream-interpretation # 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The length of the plan depends on the question.\n\nYou have access to the following documentation sources:\n- Conceptual docs\n- Integration docs\n- How-to guides\n\nYou do not need to specify where you want to research for all steps of the plan, but it's sometimes helpful.","generate_queries_system_prompt":"Generate 3 search queries to search for to answer the user's question.\n\nThese search queries should be diverse in nature - do not generate repetitive ones.","checkpoint_id":"1f09269f-1e57-6141-8002-9f0597d5daea"}},"values":{"messages":[{"content":"hi","additional_kwargs":{},"response_metadata":{},"type":"human","name":null,"id":"7aae7cba-94b6-4218-8747-4f0f66a34000","example":false},{"content":"Hello! I'm here to help you with any questions you might have about LangChain. Is there something specific you'd like to know about this framework for developing applications powered by large language models?","additional_kwargs":{},"response_metadata":{"model_name":"claude-3-5-haiku-20241022","stop_reason":"end_turn","stop_sequence":null},"type":"ai","name":null,"id":"run--824c9553-e992-40d0-a7a4-1396c088a28c","example":false,"tool_calls":[],"invalid_tool_calls":[],"usage_metadata":{"input_tokens":3003,"output_tokens":44,"total_tokens":3047,"input_token_details":{"cache_creation":0,"cache_read":0}}}],"steps":[],"documents":[{"id":null,"metadata":{"language":"en","title":"Introduction | 🦜️🔗 Langchain","changefreq":"weekly","description":"LangChain is a framework for developing applications powered by large language models (LLMs).","priority":"0.5","source":"https://js.langchain.com/docs/introduction","loc":"https://js.langchain.com/docs/introduction","lastmod":null,"uuid":"feabcd8c-edd5-5221-ba28-30ac81c1a391"},"page_content":"Introduction | 🦜️🔗 Langchain","type":"Document"},{"id":null,"metadata":{"language":"en","title":"LangChain v0.3 | 🦜️🔗 Langchain","changefreq":"weekly","priority":"0.5","description":"Last updated: 07.08.25","source":"https://js.langchain.com/docs/versions/v0_3/","loc":"https://js.langchain.com/docs/versions/v0_3/","lastmod":null,"uuid":"57aa0c97-cd76-55b6-b034-3466be0e5093"},"page_content":"LangChain v0.3 | 🦜️🔗 Langchain","type":"Document"},{"id":null,"metadata":{"language":"en","title":"LangChain v0.2 | 🦜️🔗 Langchain","changefreq":"weekly","priority":"0.5","description":"LangChain v0.2 was released in May 2024. 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This can include Python REPLs, embeddings, search engines, and more. LangChain provides a large collection of common utils to use in your application.\\\\nChains: Chains go beyond just a single LLM call, and are sequences of calls (whether to an LLM or a different utility). LangChain provides a standard interface for chains, lots of integrations with other tools, and end-to-end chains for common applications.\\\\nIndexes: Language models are often more powerful when combined with your own text data - this module covers best practices for doing exactly that.\\\\nAgents: Agents involve an LLM making decisions about which Actions to take, taking that Action, seeing an Observation, and repeating that until done. LangChain provides a standard interface for agents, a selection of agents to choose from, and examples of end to end agents.\\\\nMemory: Memory is the concept of persisting state between calls of a chain/agent. LangChain provides a standard interface for memory, a collection of memory implementations, and examples of chains/agents that use memory.\\\\nChat: Chat models are a variation on Language Models that expose a different API - rather than working with raw text, they work with messages. LangChain provides a standard interface for working with them and doing all the same things as above.\\\\n\\\\n\\\\n\\\\n\\\\n\\\\nUse Cases#\\\\nThe above modules can be used in a variety of ways. LangChain also provides guidance and assistance in this. Below are some of the common use cases LangChain supports.\\\\n\\\\nAgents: Agents are systems that use a language model to interact with other tools. These can be used to do more grounded question/answering, interact with APIs, or even take actions.\\\\nChatbots: Since language models are good at producing text, that makes them ideal for creating chatbots.\\\\nData Augmented Generation: Data Augmented Generation involves specific types of chains that first interact with an external datasource to fetch data to use in the generation step. Examples of this include summarization of long pieces of text and question/answering over specific data sources.\\\\nQuestion Answering: Answering questions over specific documents, only utilizing the information in those documents to construct an answer. A type of Data Augmented Generation.\\\\nSummarization: Summarizing longer documents into shorter, more condensed chunks of information. A type of Data Augmented Generation.\\\\nQuerying Tabular Data: If you want to understand how to use LLMs to query data that is stored in a tabular format (csvs, SQL, dataframes, etc) you should read this page.\\\\nEvaluation: Generative models are notoriously hard to evaluate with traditional metrics. One new way of evaluating them is using language models themselves to do the evaluation. LangChain provides some prompts/chains for assisting in this.\\\\nGenerate similar examples: Generating similar examples to a given input. This is a common use case for many applications, and LangChain provides some prompts/chains for assisting in this.\\\\nCompare models: Experimenting with different prompts, models, and chains is a big part of developing the best possible application. The ModelLaboratory makes it easy to do so.\\\\n\\\\n\\\\n\\\\n\\\\n\\\\nReference Docs#\\\\nAll of LangChain’s reference documentation, in one place. Full documentation on all methods, classes, installation methods, and integration setups for LangChain.\\\\n\\\\nReference Documentation\\\\n\\\\n\\\\n\\\\n\\\\n\\\\nLangChain Ecosystem#\\\\nGuides for how other companies/products can be used with LangChain\\\\n\\\\nLangChain Ecosystem\\\\n\\\\n\\\\n\\\\n\\\\n\\\\nAdditional Resources#\\\\nAdditional collection of resources we think may be useful as you develop your application!\\\\n\\\\nLangChainHub: The LangChainHub is a place to share and explore other prompts, chains, and agents.\\\\nGlossary: A glossary of all related terms, papers, methods, etc. Whether implemented in LangChain or not!\\\\nGallery: A collection of our favorite projects that use LangChain. Useful for","type":"Document"}],"answer":"Hello! I'm here to help you with any questions you might have about LangChain. Is there something specific you'd like to know about this framework for developing applications powered by large language models?","query":"hi"},"metadata":{"source":"loop","step":3,"parents":{}},"next":[],"tasks":[],"checkpoint":{"checkpoint_id":"1f09269f-38a3-68bf-8003-0693e2e87d63","thread_id":"23c8ebb7-3500-4f73-9b02-ab2184201bdf","checkpoint_ns":""},"parent_checkpoint":{"checkpoint_id":"1f09269f-1e57-6141-8002-9f0597d5daea","thread_id":"23c8ebb7-3500-4f73-9b02-ab2184201bdf","checkpoint_ns":""}}} + diff --git a/libs/sdk-py/tests/test_client_stream.py b/libs/sdk-py/tests/test_client_stream.py new file mode 100644 index 000000000..4237f89af --- /dev/null +++ b/libs/sdk-py/tests/test_client_stream.py @@ -0,0 +1,248 @@ +from __future__ import annotations + +from collections.abc import Iterator, Sequence +from pathlib import Path + +import httpx +import pytest + +from langgraph_sdk.client import HttpClient, SyncHttpClient +from langgraph_sdk.schema import StreamPart +from langgraph_sdk.sse import BytesLike, BytesLineDecoder, SSEDecoder + +with open(Path(__file__).parent / "fixtures" / "response.txt", "rb") as f: + RESPONSE_PAYLOAD = f.read() + + +class AsyncListByteStream(httpx.AsyncByteStream): + def __init__(self, chunks: Sequence[bytes], exc: Exception | None = None) -> None: + self._chunks = list(chunks) + self._exc = exc + + async def __aiter__(self): # type: ignore[override] + for chunk in self._chunks: + yield chunk + if self._exc is not None: + raise self._exc + + async def aclose(self) -> None: + return None + + +class ListByteStream(httpx.ByteStream): + def __init__(self, chunks: Sequence[bytes], exc: Exception | None = None) -> None: + self._chunks = list(chunks) + self._exc = exc + + def __iter__(self): # type: ignore[override] + yield from self._chunks + if self._exc is not None: + raise self._exc + + def close(self) -> None: + return None + + +def iter_lines_raw(payload: list[bytes]) -> Iterator[BytesLike]: + decoder = BytesLineDecoder() + for part in payload: + yield from decoder.decode(part) + yield from decoder.flush() + + +def test_stream_see(): + for groups in ( + [RESPONSE_PAYLOAD], + RESPONSE_PAYLOAD.splitlines(keepends=True), + ): + parts: list[StreamPart] = [] + + decoder = SSEDecoder() + for line in iter_lines_raw(groups): + sse = decoder.decode(line=line.rstrip(b"\n")) + if sse is not None: + parts.append(sse) + if sse := decoder.decode(b""): + parts.append(sse) + + assert decoder.decode(b"") is None + assert len(parts) == 79 + + +@pytest.mark.asyncio +async def test_http_client_stream_flushes_trailing_event(): + payload = b'event: foo\ndata: {"bar": 1}\n' + + async def handler(request: httpx.Request) -> httpx.Response: + assert request.headers["accept"] == "text/event-stream" + assert request.headers["cache-control"] == "no-store" + return httpx.Response( + 200, + headers={"Content-Type": "text/event-stream"}, + content=payload, + ) + + transport = httpx.MockTransport(handler) + async with httpx.AsyncClient( + transport=transport, base_url="https://example.com" + ) as client: + http_client = HttpClient(client) + parts = [part async for part in http_client.stream("/stream", "GET")] + + assert parts == [StreamPart(event="foo", data={"bar": 1})] + + +def test_sync_http_client_stream_recovers_after_disconnect(): + reconnect_path = "/reconnect" + first_chunks = [ + b"id: 1\n", + b"event: values\n", + b'data: {"step": 1}\n\n', + ] + second_chunks = [ + b"id: 2\n", + b"event: values\n", + b'data: {"step": 2}\n\n', + b"event: end\n", + b"data: null\n\n", + ] + call_count = 0 + + def handler(request: httpx.Request) -> httpx.Response: + nonlocal call_count + call_count += 1 + if call_count == 1: + assert request.method == "POST" + assert request.url.path == "/stream" + assert request.headers["accept"] == "text/event-stream" + assert request.headers["cache-control"] == "no-store" + assert "last-event-id" not in { + k.lower(): v for k, v in request.headers.items() + } + assert request.read() + return httpx.Response( + 200, + headers={ + "Content-Type": "text/event-stream", + "Location": reconnect_path, + }, + stream=ListByteStream( + first_chunks, + httpx.RemoteProtocolError("incomplete chunked read"), + ), + ) + if call_count == 2: + assert request.method == "GET" + assert request.url.path == reconnect_path + assert request.headers["Last-Event-ID"] == "1" + assert request.read() == b"" + return httpx.Response( + 200, + headers={"Content-Type": "text/event-stream"}, + stream=ListByteStream(second_chunks), + ) + raise AssertionError("unexpected request") + + transport = httpx.MockTransport(handler) + with httpx.Client(transport=transport, base_url="https://example.com") as client: + http_client = SyncHttpClient(client) + parts = list(http_client.stream("/stream", "POST", json={"payload": "value"})) + + assert call_count == 2 + assert parts == [ + StreamPart(event="values", data={"step": 1}), + StreamPart(event="values", data={"step": 2}), + StreamPart(event="end", data=None), + ] + + +@pytest.mark.asyncio +async def test_http_client_stream_recovers_after_disconnect(): + reconnect_path = "/reconnect" + first_chunks = [ + b"id: 1\n", + b"event: values\n", + b'data: {"step": 1}\n\n', + ] + second_chunks = [ + b"id: 2\n", + b"event: values\n", + b'data: {"step": 2}\n\n', + b"event: end\n", + b"data: null\n\n", + ] + call_count = 0 + + async def handler(request: httpx.Request) -> httpx.Response: + nonlocal call_count + call_count += 1 + if call_count == 1: + assert request.method == "POST" + assert request.url.path == "/stream" + assert request.headers["accept"] == "text/event-stream" + assert request.headers["cache-control"] == "no-store" + assert "last-event-id" not in { + k.lower(): v for k, v in request.headers.items() + } + assert await request.aread() + return httpx.Response( + 200, + headers={ + "Content-Type": "text/event-stream", + "Location": reconnect_path, + }, + stream=AsyncListByteStream( + first_chunks, + httpx.RemoteProtocolError("incomplete chunked read"), + ), + ) + if call_count == 2: + assert request.method == "GET" + assert request.url.path == reconnect_path + assert request.headers["Last-Event-ID"] == "1" + assert await request.aread() == b"" + return httpx.Response( + 200, + headers={"Content-Type": "text/event-stream"}, + stream=AsyncListByteStream(second_chunks), + ) + raise AssertionError("unexpected request") + + transport = httpx.MockTransport(handler) + async with httpx.AsyncClient( + transport=transport, base_url="https://example.com" + ) as client: + http_client = HttpClient(client) + parts = [ + part + async for part in http_client.stream( + "/stream", "POST", json={"payload": "value"} + ) + ] + + assert call_count == 2 + assert parts == [ + StreamPart(event="values", data={"step": 1}), + StreamPart(event="values", data={"step": 2}), + StreamPart(event="end", data=None), + ] + + +def test_sync_http_client_stream_flushes_trailing_event(): + payload = b'event: foo\ndata: {"bar": 1}\n' + + def handler(request: httpx.Request) -> httpx.Response: + assert request.headers["accept"] == "text/event-stream" + assert request.headers["cache-control"] == "no-store" + return httpx.Response( + 200, + headers={"Content-Type": "text/event-stream"}, + content=payload, + ) + + transport = httpx.MockTransport(handler) + with httpx.Client(transport=transport, base_url="https://example.com") as client: + http_client = SyncHttpClient(client) + parts = list(http_client.stream("/stream", "GET")) + + assert parts == [StreamPart(event="foo", data={"bar": 1})] diff --git a/libs/sdk-py/tests/test_errors.py b/libs/sdk-py/tests/test_errors.py new file mode 100644 index 000000000..9238cb1fd --- /dev/null +++ b/libs/sdk-py/tests/test_errors.py @@ -0,0 +1,108 @@ +from __future__ import annotations + +from typing import cast + +import httpx +import orjson +import pytest + +from langgraph_sdk.errors import ( + APIStatusError, + AuthenticationError, + BadRequestError, + ConflictError, + InternalServerError, + NotFoundError, + PermissionDeniedError, + RateLimitError, + UnprocessableEntityError, + _raise_for_status_typed, +) + + +def make_response( + status: int, + *, + json_body: dict | None = None, + text_body: str | None = None, + headers: dict[str, str] | None = None, +) -> httpx.Response: + request = httpx.Request("GET", "https://example.com/test") + content: bytes | None + if json_body is not None: + content = orjson.dumps(json_body) + elif text_body is not None: + content = text_body.encode() + else: + content = b"" + return httpx.Response( + status, headers=headers or {}, content=content, request=request + ) + + +@pytest.mark.parametrize( + "status,exc_type", + [ + (400, BadRequestError), + (401, AuthenticationError), + (403, PermissionDeniedError), + (404, NotFoundError), + (409, ConflictError), + (422, UnprocessableEntityError), + (429, RateLimitError), + (500, InternalServerError), + (503, InternalServerError), # any 5xx + (418, APIStatusError), # unmapped 4xx falls back to base type + ], +) +def test_raise_for_status_typed_maps_exceptions_and_sets_status_code( + status: int, exc_type: type[APIStatusError] +) -> None: + r = make_response( + status, json_body={"message": "boom", "code": "abc", "param": "p", "type": "t"} + ) + + with pytest.raises(exc_type) as ei: + _raise_for_status_typed(r) + + err = cast(APIStatusError, ei.value) + assert err.status_code == status + # response attribute should be present and match + assert err.response.status_code == status + + +def test_request_id_is_extracted_when_present() -> None: + r = make_response( + 404, json_body={"detail": "missing"}, headers={"x-request-id": "req-123"} + ) + with pytest.raises(NotFoundError) as ei: + _raise_for_status_typed(r) + err = cast(APIStatusError, ei.value) + # request_id only exists on APIStatusError subclasses + assert err.request_id == "req-123" + + +def test_non_json_body_does_not_break_mapping() -> None: + r = make_response(429, text_body="Too many requests") + with pytest.raises(RateLimitError) as ei: + _raise_for_status_typed(r) + err = cast(APIStatusError, ei.value) + assert err.status_code == 429 + + +def test_field_extraction_from_json_body() -> None: + r = make_response( + 400, + json_body={ + "message": "Invalid parameter", + "code": "invalid_param", + "param": "limit", + "type": "invalid_request_error", + }, + ) + with pytest.raises(BadRequestError) as ei: + _raise_for_status_typed(r) + err = cast(APIStatusError, ei.value) + assert err.code == "invalid_param" + assert err.param == "limit" + assert err.type == "invalid_request_error" diff --git a/libs/sdk-py/uv.lock b/libs/sdk-py/uv.lock index 70565bd05..8d7cb86e2 100644 --- a/libs/sdk-py/uv.lock +++ b/libs/sdk-py/uv.lock @@ -1,10 +1,10 @@ version = 1 -revision = 2 +revision = 3 requires-python = ">=3.9" [[package]] name = "anyio" -version = "4.10.0" +version = "4.11.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "exceptiongroup", marker = "python_full_version < '3.11'" }, @@ -12,9 +12,9 @@ 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