feat(sdk): bump to 0.0.46

2026-09-10 11:47:51 +02:00 · 2025-02-25 18:28:22 +01:00
95 changed files with 3096 additions and 7696 deletions
@@ -39,7 +39,6 @@ jobs:
              - 'libs/checkpoint-sqlite/**'
              - 'libs/checkpoint-postgres/**'
              - 'libs/scheduler-kafka/**'
-              - 'libs/prebuilt/**'
            sdk-js:
              - 'libs/sdk-js/**'

@@ -57,7 +56,6 @@ jobs:
            "libs/checkpoint-sqlite",
            "libs/checkpoint-postgres",
            "libs/scheduler-kafka",
-            "libs/prebuilt",
          ]
    if: needs.changes.outputs.python == 'true'
    uses: ./.github/workflows/_lint.yml
@@ -76,7 +74,6 @@ jobs:
            "libs/checkpoint",
            "libs/checkpoint-sqlite",
            "libs/checkpoint-postgres",
-            "libs/prebuilt",
          ]
    if: needs.changes.outputs.python == 'true'
    uses: ./.github/workflows/_test.yml
@@ -114,42 +111,6 @@ jobs:
      - name: Run check_sdk_methods script
        run: python .github/scripts/check_sdk_methods.py

-  check-schema:
-    needs: changes
-    if: needs.changes.outputs.python == 'true'
-    name: "Check CLI schema hasn't changed #${{ matrix.python-version }}"
-    runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        python-version:
-          - "3.11"
-    steps:
-      - uses: actions/checkout@v4
-      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
-        with:
-          python-version: "3.11"
-          poetry-version: ${{ env.POETRY_VERSION }}
-          cache-key: schema-check-cli
-      - name: Install CLI dependencies
-        run: |
-          cd libs/cli
-          poetry install
-      - name: Generate schema and check for changes
-        run: |
-          cd libs/cli
-          # Create a temporary copy of the current schema
-          cp schemas/schema.json schemas/schema.current.json
-          # Generate new schema
-          poetry run python generate_schema.py
-          # Compare the new schema with the original
-          if ! diff -q schemas/schema.json schemas/schema.current.json > /dev/null; then
-            echo "Error: Langgraph.json configuration schema has changed. Please run 'poetry run python generate_schema.py' in the libs/cli directory and commit the changes."
-            diff schemas/schema.json schemas/schema.current.json
-            exit 1
-          fi
-          echo "Schema check passed - no changes detected"
-
  integration-test:
    needs: changes
    if: needs.changes.outputs.python == 'true'
@@ -216,8 +177,6 @@ jobs:
        test,
        test-langgraph,
        test-scheduler-kafka,
-        check-sdk-methods,
-        check-schema,
        integration-test,
        test-js,
      ]
@@ -195,11 +195,7 @@ jobs:
              "$PKG_NAME==$VERSION" \
          )

-          if [[ "$PKG_NAME" == *prebuilt* ]]; then
-            poetry run pip install langgraph
-          fi
-
-          if [[ "$PKG_NAME" == *checkpoint* || "$PKG_NAME" == *prebuilt* ]]; then
+          if [[ "$PKG_NAME" == *checkpoint* ]]; then
            # since checkpoint packages are namespace packages, import them with . convention
            # i.e. import langgraph.checkpoint or langgraph.checkpoint.sqlite
            IMPORT_NAME="$(echo "$PKG_NAME" | sed s/-/./g)"
@@ -83,18 +83,14 @@ def generate_markdown(resolved_packages: List[ResolvedPackage], language: str) -
        resolved_packages, key=lambda p: p["weekly_downloads"] or 0, reverse=True
    )
    rows = [
-        "| Name | GitHub URL | Description | Weekly Downloads | Stars |",
-        "| --- | --- | --- | --- | --- |",
+        "| Name | GitHub URL | Description | Weekly Downloads |",
+        "| --- | --- | --- | --- |",
    ]
    for package in sorted_packages:
        name = f"**{package['name']}**"
        repo_url = f"[{package['repo']}](https://github.com/{package['repo']})"
-        stars_badge = (
-            f"https://img.shields.io/github/stars/{package['repo']}?style=social"
-        )
-        stars = f"![GitHub stars]({stars_badge})"
        downloads = package["weekly_downloads"] or "-"
-        row = f"| {name} | {repo_url} | {package['description']} | {downloads} | {stars}"
+        row = f"| {name} | {repo_url} | {package['description']} | {downloads} |"
        rows.append(row)
    markdown_content = MARKDOWN.format(
        library_list="\n".join(rows), langgraph_url=langgraph_url
@@ -2,13 +2,13 @@
 packages:
  - name: "trustcall"
    repo: "hinthornw/trustcall"
-    description: "Tenacious tool calling built on LangGraph."
+    description: "Tenacious tool calling built on LangGraph"
  - name: "breeze-agent"
    repo: "andrestorres123/breeze-agent"
-    description: "A streamlined research system built inspired on STORM and built on LangGraph."
+    description: "A streamlined research system built inspired on STORM and built on LangGraph"
  - name: "langgraph-supervisor"
-    repo: "langchain-ai/langgraph-supervisor-py"
-    description: "Build supervisor multi-agent systems with LangGraph."
+    repo: "langchain-ai/langgraph-supervisor"
+    description: "Build supervisor multi-agent systems with LangGraph"
  - name: "langmem"
    repo: "langchain-ai/langmem"
    description: "Build agents that learn and adapt from interactions over time."
@@ -18,15 +18,3 @@ packages:
  - name: "open-deep-research"
    repo: "langchain-ai/open_deep_research"
    description: "Open source assistant for iterative web research and report writing."
-  - name: "langgraph-swarm"
-    repo: "langchain-ai/langgraph-swarm-py"
-    description: "Build swarm-style multi-agent systems using LangGraph."
-  - name: "delve-taxonomy-generator"
-    repo: "andrestorres123/delve"
-    description: "A taxonomy generator for unstructured data"
-  - name: "nodeology"
-    repo: "xyin-anl/Nodeology"
-    description: "Enable researcher to build scientific workflows easily with simplified interface."
-  - name: "langgraph-bigtool"
-    repo: "langchain-ai/langgraph-bigtool"
-    description: "Build LangGraph agents with large numbers of tools."
@@ -1,4 +1,4 @@
-# 🦜🕸️ Companies using LangGraph
+# 🦜🕸️ LangGraph Adopters

 This list of companies using LangGraph and their success stories is compiled from public sources. If your company uses LangGraph, we'd love for you to share your story and add it to the list. You’re also welcome to contribute updates based on publicly available information from other companies, such as blog posts or press releases.

@@ -9,7 +9,6 @@ This list of companies using LangGraph and their success stories is compiled fro
 | [AppFolio](https://www.appfolio.com/) | Real Estate | Copilot for domain-specific task | [Case study, 2024](https://blog.langchain.dev/customers-appfolio/) |
 | [Athena Intelligence](https://www.athenaintel.com/) | Software & Technology (GenAI Native) | Research & summarization | [Case study, 2024](https://blog.langchain.dev/customers-athena-intelligence/) |
 | [Captide](https://www.captide.co/) | Software & Technology (GenAI Native) | Data extraction | [Case study, 2025](https://blog.langchain.dev/how-captide-is-redefining-equity-research-with-agentic-workflows-built-on-langgraph-and-langsmith/) |
-| [Cisco Outshift](https://outshift.cisco.com/) | Software & Technology | DevOps | [Blog post, 2025](https://outshift.cisco.com/blog/build-react-agent-application-for-devops-tasks-using-rest-apis) |
 | [Elastic](https://www.elastic.co/) | Software & Technology | Copilot for domain-specific task | [Blog post, 2025](https://www.elastic.co/blog/elastic-security-generative-ai-features) |
 | [GitLab](https://about.gitlab.com/) | Software & Technology | Code generation | [Duo workflow docs](https://handbook.gitlab.com/handbook/engineering/architecture/design-documents/duo_workflow/) |
 | [Infor](https://infor.com/) | Software & Technology | GenAI embedded product experiences; customer support; copilot | [Case study, 2025](https://blog.langchain.dev/customers-infor/) |
@@ -17,7 +17,7 @@ This guide explains how to add semantic search to your LangGraph deployment's cr
    ...
    "store": {
        "index": {
-            "embed": "openai:text-embedding-3-small",
+            "embed": "openai:text-embeddings-3-small",
            "dims": 1536,
            "fields": ["$"]
        }
@@ -27,7 +27,7 @@ This guide explains how to add semantic search to your LangGraph deployment's cr

 This configuration:

- Uses OpenAI's text-embedding-3-small model for generating embeddings
+- Uses OpenAI's text-embeddings-3-small model for generating embeddings
 - Sets the embedding dimension to 1536 (matching the model's output)
 - Indexes all fields in your stored data (`["$"]` means index everything, or specify specific fields like `["text", "metadata.title"]`)

@@ -36,20 +36,21 @@ Dependencies can optionally be specified in one of the following files: `pyproje
 The dependencies below will be included in the image, you can also use them in your code, as long as with a compatible version range:

 ```
-langgraph>=0.2.56,<0.4.0
-langgraph-sdk>=0.1.53
-langgraph-checkpoint>=2.0.15,<3.0
+langgraph>=0.2.56,<0.3.0
+langgraph-checkpoint>=2.0.5,<3.0
 langchain-core>=0.2.38,<0.4.0
 langsmith>=0.1.63
 orjson>=3.9.7
 httpx>=0.25.0
 tenacity>=8.0.0
 uvicorn>=0.26.0
-sse-starlette>=2.1.0,<2.2.0
+sse-starlette>=2.1.0
 uvloop>=0.18.0
 httptools>=0.5.0
-jsonschema-rs>=0.20.0
+jsonschema-rs>=0.16.3
+croniter>=1.0.1
 structlog>=23.1.0
+redis>=5.0.0,<6.0.0
 ```

 Example `requirements.txt` file:
@@ -36,20 +36,21 @@ Dependencies can optionally be specified in one of the following files: `pyproje
 The dependencies below will be included in the image, you can also use them in your code, as long as with a compatible version range:

 ```
-langgraph>=0.2.56,<0.4.0
-langgraph-sdk>=0.1.53
-langgraph-checkpoint>=2.0.15,<3.0
+langgraph>=0.2.56,<0.3.0
+langgraph-checkpoint>=2.0.5,<3.0
 langchain-core>=0.2.38,<0.4.0
 langsmith>=0.1.63
 orjson>=3.9.7
 httpx>=0.25.0
 tenacity>=8.0.0
 uvicorn>=0.26.0
-sse-starlette>=2.1.0,<2.2.0
+sse-starlette>=2.1.0
 uvloop>=0.18.0
 httptools>=0.5.0
-jsonschema-rs>=0.20.0
+jsonschema-rs>=0.16.3
+croniter>=1.0.1
 structlog>=23.1.0
+redis>=5.0.0,<6.0.0
 ```

 Example `pyproject.toml` file:
@@ -1,10 +1,10 @@
-# Test LangGraph Platform Deployment
+# Test Cloud Deployment

-The LangGraph Studio UI connects directly to LangGraph Platform deployments.
+The LangGraph Studio UI connects directly to LangGraph Cloud deployments.

 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...

-1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Platform deployments.
+1. In the left-hand navigation panel, select `LangGraph Cloud`. The `LangGraph Cloud` view contains a list of existing LangGraph Cloud deployments.
 1. Select an existing deployment to test with LangGraph Studio.
 1. In the top-right corner, select `Open LangGraph Studio`.
 1. [Invoke an assistant](./invoke_studio.md) or [view an existing thread](./threads_studio.md).
@@ -1,6 +1,6 @@
 # LangGraph CLI

-The LangGraph command line interface includes commands to build and run a LangGraph Cloud API server locally in [Docker](https://www.docker.com/). For development and testing, you can use the CLI to deploy a local API server.
+The LangGraph command line interface includes commands to build and run a LangGraph Cloud API server locally in [Docker](https://www.docker.com/). For development and testing, you can use the CLI to deploy a local API server as an alternative to the [Studio desktop app](../../concepts/langgraph_studio.md).

 ## Installation

@@ -2,12 +2,6 @@

 The LangGraph Cloud Server supports specific environment variables for configuring a deployment.

-## `DD_API_KEY`
-
-Specify `DD_API_KEY` (your [Datadog API Key](https://docs.datadoghq.com/account_management/api-app-keys/)) to automatically enable Datadog tracing for the deployment. Specify other [`DD_*` environment variables](https://ddtrace.readthedocs.io/en/stable/configuration.html) to configure the tracing instrumentation.
-
-If `DD_API_KEY` is specified, the application process is wrapped in the [`ddtrace-run` command](https://ddtrace.readthedocs.io/en/stable/installation_quickstart.html). Other `DD_*` environment variables (e.g. `DD_SITE`, `DD_ENV`, `DD_SERVICE`, `DD_TRACE_ENABLED`) are typically needed to properly configure the tracing instrumentation. See [`DD_*` environment variables](https://ddtrace.readthedocs.io/en/stable/configuration.html) for more details.
-
 ## `LANGCHAIN_TRACING_SAMPLING_RATE`

 Sampling rate for traces sent to LangSmith. Valid values: Any float between `0` and `1`.
@@ -36,7 +36,7 @@ LangGraph is a stateful, orchestration framework that brings added control to ag
 | Concurrency Control | Simple threading                                          | Supports double-texting                                                                                |
 | Scheduling          | None                                                      | Cron scheduling                                                                                        |
 | Monitoring          | None                                                      | Integrated with LangSmith for observability                                                            |
-| IDE integration     | LangGraph Studio                                          | LangGraph Studio                                                                                       |
+| IDE integration     | LangGraph Studio for Desktop                              | LangGraph Studio for Desktop & Cloud                                                                   |

 ## What are my deployment options for LangGraph Platform?

@@ -62,9 +62,3 @@ Yes! You can use LangGraph with any LLMs. The main reason we use LLMs that suppo
 ## Does LangGraph work with OSS LLMs?

 Yes! LangGraph is totally ambivalent to what LLMs are used under the hood. The main reason we use closed LLMs in most of the tutorials is that they seamlessly support tool calling, while OSS LLMs often don't. But tool calling is not necessary (see [this section](#does-langgraph-work-with-llms-that-dont-support-tool-calling)) so you can totally use LangGraph with OSS LLMs.
-
-## Can I use LangGraph Studio without logging to LangSmith
-
-Yes! You can use the [development version of LangGraph Server](../tutorials/langgraph-platform/local-server.md) to run the backend locally.
-This will connect to the studio frontend hosted as part of LangSmith.
-If you set an environment variable of `LANGSMITH_TRACING=false` then no traces will be sent to LangSmith.
@@ -4,7 +4,7 @@
    - [LangGraph Platform](./langgraph_platform.md)
    - [LangGraph Server](./langgraph_server.md)

-The LangGraph CLI is a multi-platform command-line tool for building and running the [LangGraph API server](./langgraph_server.md) locally. The resulting server includes all API endpoints for your graph's runs, threads, assistants, etc. as well as the other services required to run your agent, including a managed database for checkpointing and storage.
+The LangGraph CLI is a multi-platform command-line tool for building and running the [LangGraph API server](./langgraph_server.md) locally. This offers an alternative to the [LangGraph Studio desktop app](./langgraph_studio.md) for developing and testing agents across all major operating systems (Linux, Windows, MacOS). The resulting server includes all API endpoints for your graph's runs, threads, assistants, etc. as well as the other services required to run your agent, including a managed database for checkpointing and storage.

 ## Installation

@@ -7,7 +7,7 @@

 LangGraph Studio offers a new way to develop LLM applications by providing a specialized agent IDE that enables visualization, interaction, and debugging of complex agentic applications.

-With visual graphs and the ability to edit state, you can better understand agent workflows and iterate faster. LangGraph Studio integrates with LangSmith allowing you to collaborate with teammates to debug failure modes.
+With visual graphs and the ability to edit state, you can better understand agent workflows and iterate faster. LangGraph Studio integrates with LangSmith allowing you to  collaborate with teammates to debug failure modes.

 ![](img/lg_studio.png)

@@ -15,7 +15,7 @@ With visual graphs and the ability to edit state, you can better understand agen

 The key features of LangGraph Studio are:

- Visualize your graphs
+- Visualizes your graph
 - Test your graph by running it from the UI
 - Debug your agent by [modifying its state and rerunning](human_in_the_loop.md)
 - Create and manage [assistants](assistants.md)
@@ -23,54 +23,86 @@ The key features of LangGraph Studio are:
 - View and manage [long term memory](memory.md)
 - Add node input/outputs to [LangSmith](https://smith.langchain.com/) datasets for testing

-## Getting started
+## Types

-There are two ways to connect your LangGraph app with the studio:
+### Development server with web UI

-### Deployed Application
-
-If you have deployed your LangGraph application on LangGraph Platform, you can access the studio as part of that deployment. To do so, navigate to the deployment in LangGraph Platform within the LangSmith UI and click the "LangGraph Studio" button.
-
-### Local Development Server
-
-If you have a LangGraph application that is [running locally in-memory](../tutorials/langgraph-platform/local-server.md), you can connect it to LangGraph Studio in the browser within LangSmith.
-
-By default, starting the local server with `langgraph dev` will run the server at `http://127.0.0.1:2024` and automatically open Studio in your browser. However, you can also manually connect to Studio by either:
-
-1. In LangGraph Platform, clicking the "LangGraph Studio" button and entering the server URL in the dialog that appears.
-
-   or
-
-2. Navigating to the URL in your browser:
+You can [run a local in-memory development server](../tutorials/langgraph-platform/local-server.md) that can be used to connect a local LangGraph app with a web version of the studio.
+For example, if you start the local server with `langgraph dev` (running at `http://127.0.0.1:2024` by default), you can connect to the studio by navigating to:

 ```
 https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024
 ```

-## Related
+See [instructions here](../cloud/reference/cli.md#dev) for more information.

-For more information please see the following:
+The web UI version of the studio will connect to your locally running server — your agent is still running locally and never leaves your device.

- [LangGraph Studio how-to guides](../how-tos/index.md#langgraph-studio)
- [LangGraph CLI Documentation](../cloud/reference/cli.md)
+### Cloud studio

-## LangGraph Studio FAQs
+If you have deployed your LangGraph application on LangGraph Platform (Cloud), you can access the studio as part of that
+
+### Desktop app
+
+LangGraph Studio is available as a [desktop app](https://studio.langchain.com/) for MacOS users.
+
+While in Beta, LangGraph Studio is available for free to all [LangSmith](https://smith.langchain.com/) users on any plan tier.
+
+## Studio FAQs

 ### Why is my project failing to start?

-A project may fail to start if the configuration file is defined incorrectly, or if required environment variables are missing. See [here](../cloud/reference/cli.md#configuration-file) for how your configuration file should be defined.
+There are a few reasons that your project might fail to start, here are some of the most common ones.
+
+#### Docker issues (desktop only)
+
+LangGraph Studio (desktop) requires Docker Desktop version 4.24 or higher. Please make sure you have a version of Docker installed that satisfies that requirement and also make sure you have the Docker Desktop app up and running before trying to use LangGraph Studio. In addition, make sure you have docker-compose updated to version 2.22.0 or higher.
+
+#### Configuration or environment issues
+
+Another reason your project might fail to start is because your configuration file is defined incorrectly, or you are missing required environment variables.
+
+!!! Important "Note (desktop only)"
+
+    LangGraph Studio Desktop automatically populates `LANGCHAIN_*` environment variables for license verification and tracing, regardless of the contents of the `.env` file. All other environment variables defined in `.env` will be read as normal.
+
+#### Incorrect data region (desktop only)
+
+If you receive a license verification error when attempting to start the LangGraph Server, you may be logged into the incorrect LangSmith data region. Ensure that you're logged into the correct LangSmith data region and ensure that the LangSmith account has access to LangGraph platform.
+
+1. In the top right-hand corner, click the user icon and select `Logout`.
+1. At the login screen, click the `Data Region` dropdown menu and select the appropriate data region. Then click `Login to LangSmith`.

 ### How does interrupt work?

 When you select the `Interrupts` dropdown and select a node to interrupt the graph will pause execution before and after (unless the node goes straight to `END`) that node has run. This means that you will be able to both edit the state before the node is ran and the state after the node has ran. This is intended to allow developers more fine-grained control over the behavior of a node and make it easier to observe how the node is behaving. You will not be able to edit the state after the node has ran if the node is the final node in the graph.

-For more information on interrupts and human in the loop, see [here](./human_in_the_loop.md).
+### How do I reload the app?  (desktop only)

-### Why are extra edges showing up in my graph?
+If you would like to reload the app, don't use Command+R as you might normally do. Instead, close and reopen the app for a full refresh.
+
+### How does automatic rebuilding work?  (desktop only)
+
+One of the key features of LangGraph Studio is that it automatically rebuilds your image when you change the source code. This allows for a super fast development and testing cycle which makes it easy to iterate on your graph. There are two different ways that LangGraph rebuilds your image: either by editing the image or completely rebuilding it.
+
+#### Rebuilds from source code changes
+
+If you modified the source code only (no configuration or dependency changes!) then the image does not require a full rebuild, and LangGraph Studio will only update the relevant parts. The UI status in the bottom left will switch from `Online` to `Stopping` temporarily while the image gets edited. The logs will be shown as this process is happening, and after the image has been edited the status will change back to `Online` and you will be able to run your graph with the modified code!
+
+
+#### Rebuilds from configuration or dependency changes
+
+If you edit your graph configuration file (`langgraph.json`) or the dependencies (either `pyproject.toml` or `requirements.txt`) then the entire image will be rebuilt. This will cause the UI to switch away from the graph view and start showing the logs of the new image building process. This can take a minute or two, and once it is done your updated image will be ready to use!
+
+### Why is my graph taking so long to startup?  (desktop only)
+
+The LangGraph Studio interacts with a local LangGraph API server. To stay aligned with ongoing updates, the LangGraph API requires regular rebuilding. As a result, you may occasionally experience slight delays when starting up your project.
+
+## Why are extra edges showing up in my graph?

 If you don't define your conditional edges carefully, you might notice extra edges appearing in your graph. This is because without proper definition, LangGraph Studio assumes the conditional edge could access all other nodes. In order for this to not be the case, you need to be explicit about how you define the nodes the conditional edge routes to. There are two ways you can do this:

-#### Solution 1: Include a path map
+### Solution 1: Include a path map

 The first way to solve this is to add path maps to your conditional edges. A path map is just a dictionary or array that maps the possible outputs of your router function with the names of the nodes that each output corresponds to. The path map is passed as the third argument to the `add_conditional_edges` function like so:

@@ -88,7 +120,7 @@ The first way to solve this is to add path maps to your conditional edges. A pat

 In this case, the routing function returns either True or False, which map to `node_b` and `node_c` respectively.

-#### Solution 2: Update the typing of the router (Python only)
+### Solution 2: Update the typing of the router (Python only)

 Instead of passing a path map, you can also be explicit about the typing of your routing function by specifying the nodes it can map to using the `Literal` python definition. Here is an example of how to define a routing function in that way:

@@ -100,48 +132,9 @@ def routing_function(state: GraphState) -> Literal["node_b","node_c"]:
        return "node_c"
 ```

-### Studio Desktop FAQs

-!!! warning "Deprecation Warning"
-    In order to support a wider range of platforms and users, we now recommend following the above instructions to connect to LangGraph Studio using the development server instead of the desktop app.
+## Related

-The LangGraph Studio Desktop App is a standalone application that allows you to connect to your LangGraph application and visualize and interact with your graph. It is available for MacOS only and requires Docker to be installed.
+For more information please see the following:

-#### Why is my project failing to start?
-
-In addition to the reasons listed above, for the desktop app there are a few more reasons that your project might fail to start:
-
-!!! Important "Note "
-
-    LangGraph Studio Desktop automatically populates `LANGCHAIN_*` environment variables for license verification and tracing, regardless of the contents of the `.env` file. All other environment variables defined in `.env` will be read as normal.
-
-##### Docker issues
-
-LangGraph Studio (desktop) requires Docker Desktop version 4.24 or higher. Please make sure you have a version of Docker installed that satisfies that requirement and also make sure you have the Docker Desktop app up and running before trying to use LangGraph Studio. In addition, make sure you have docker-compose updated to version 2.22.0 or higher.
-
-##### Incorrect data region
-
-If you receive a license verification error when attempting to start the LangGraph Server, you may be logged into the incorrect LangSmith data region. Ensure that you're logged into the correct LangSmith data region and ensure that the LangSmith account has access to LangGraph platform.
-
-1. In the top right-hand corner, click the user icon and select `Logout`.
-1. At the login screen, click the `Data Region` dropdown menu and select the appropriate data region. Then click `Login to LangSmith`.
-
-### How do I reload the app?
-
-If you would like to reload the app, don't use Command+R as you might normally do. Instead, close and reopen the app for a full refresh.
-
-### How does automatic rebuilding work?
-
-One of the key features of LangGraph Studio is that it automatically rebuilds your image when you change the source code. This allows for a super fast development and testing cycle which makes it easy to iterate on your graph. There are two different ways that LangGraph rebuilds your image: either by editing the image or completely rebuilding it.
-
-#### Rebuilds from source code changes
-
-If you modified the source code only (no configuration or dependency changes!) then the image does not require a full rebuild, and LangGraph Studio will only update the relevant parts. The UI status in the bottom left will switch from `Online` to `Stopping` temporarily while the image gets edited. The logs will be shown as this process is happening, and after the image has been edited the status will change back to `Online` and you will be able to run your graph with the modified code!
-
-#### Rebuilds from configuration or dependency changes
-
-If you edit your graph configuration file (`langgraph.json`) or the dependencies (either `pyproject.toml` or `requirements.txt`) then the entire image will be rebuilt. This will cause the UI to switch away from the graph view and start showing the logs of the new image building process. This can take a minute or two, and once it is done your updated image will be ready to use!
-
-### Why is my graph taking so long to startup?
-
-The LangGraph Studio interacts with a local LangGraph API server. To stay aligned with ongoing updates, the LangGraph API requires regular rebuilding. As a result, you may occasionally experience slight delays when starting up your project.
+*  [LangGraph Studio how-to guides](../how-tos/index.md#langgraph-studio)
@@ -310,7 +310,7 @@ graph.add_conditional_edges(START, routing_function, {True: "node_b", False: "no

 ## `Send`

-By default, `Nodes` and `Edges` are defined ahead of time and operate on the same shared state. However, there can be cases where the exact edges are not known ahead of time and/or you may want different versions of `State` to exist at the same time. A common example of this is with [map-reduce](https://langchain-ai.github.io/langgraph/how-tos/map-reduce/) design patterns. In this design pattern, a first node may generate a list of objects, and you may want to apply some other node to all those objects. The number of objects may be unknown ahead of time (meaning the number of edges may not be known) and the input `State` to the downstream `Node` should be different (one for each generated object).
+By default, `Nodes` and `Edges` are defined ahead of time and operate on the same shared state. However, there can be cases where the exact edges are not known ahead of time and/or you may want different versions of `State` to exist at the same time. A common example of this is with `map-reduce` design patterns. In this design pattern, a first node may generate a list of objects, and you may want to apply some other node to all those objects. The number of objects may be unknown ahead of time (meaning the number of edges may not be known) and the input `State` to the downstream `Node` should be different (one for each generated object).

 To support this design pattern, LangGraph supports returning [`Send`][langgraph.types.Send] objects from conditional edges. `Send` takes two arguments: first is the name of the node, and second is the state to pass to that node.

@@ -71,7 +71,7 @@ If you navigate to `localhost:2024/hello` in your browser (2024 is the default d

 ## Deploying

-You can deploy this app as-is to the managed langgraph cloud or to your self-hosted platform.
+You can deploy this app as-is to the managed langgraph cloud or to your self-hsoted platform.

 ## Next steps

@@ -59,10 +59,12 @@ LangGraph makes it easy to manage conversation [memory](../concepts/memory.md) i
 [Human-in-the-loop](../concepts/human_in_the_loop.md) functionality allows
 you to involve humans in the decision-making process of your graph. These how-to guides show how to implement human-in-the-loop workflows in your graph.

+
 Key workflows:

 - [How to wait for user input](human_in_the_loop/wait-user-input.ipynb): A basic example that shows how to implement a human-in-the-loop workflow in your graph using the `interrupt` function.
 - [How to review tool calls](human_in_the_loop/review-tool-calls.ipynb): Incorporate human-in-the-loop for reviewing/editing/accepting tool call requests before they executed using the `interrupt` function.
+ 

 Other methods:

@@ -288,9 +290,10 @@ Graph execution can take a while, and sometimes users may change their mind abou

 LangGraph Studio is a built-in UI for visualizing, testing, and debugging your agents.

- [How to connect to a LangGraph Platform deployment](../cloud/how-tos/test_deployment.md)
+- [How to connect to a LangGraph Cloud deployment](../cloud/how-tos/test_deployment.md)
 - [How to connect to a local dev server](../how-tos/local-studio.md)
 - [How to connect to a local deployment (Docker)](../cloud/how-tos/test_local_deployment.md)
+- [How to test your graph in LangGraph Studio (MacOS only)](../cloud/how-tos/invoke_studio.md)
 - [How to interact with threads in LangGraph Studio](../cloud/how-tos/threads_studio.md)
 - [How to add nodes as dataset examples in LangGraph Studio](../cloud/how-tos/datasets_studio.md)
 - [How to engineer prompts in LangGraph Studio](../cloud/how-tos/iterate_graph_studio.md)
@@ -309,4 +312,4 @@ These are the guides for resolving common errors you may find while building wit

 These guides provide troubleshooting information for errors that are specific to the LangGraph Platform.

- [INVALID_LICENSE](../troubleshooting/errors/INVALID_LICENSE.md)
+- [INVALID_LICENSE](../troubleshooting/errors/INVALID_LICENSE.md)
@@ -1,6 +1,15 @@
 # How to connect a local agent to LangGraph Studio

-This guide shows you how to connect your local agent to [LangGraph Studio](../concepts/langgraph_studio.md) for visualization, interaction, and debugging using the development server.
+This guide shows you how to connect your local agent to [LangGraph Studio](../concepts/langgraph_studio.md) for visualization, interaction, and debugging.
+
+## Connection Options
+
+There are two ways to connect your local agent to LangGraph Studio:
+
+- [Development Server](../concepts/langgraph_studio.md#development-server-with-web-ui): Python package, all platforms, no Docker
+- [LangGraph Desktop](../concepts/langgraph_studio.md#desktop-app): Application, Mac only, requires Docker
+
+In this guide we will cover how to use the development server as that is generally an easier and better experience.

 ## Setup your application

@@ -15,8 +24,9 @@ You will need to make sure to install the `inmem` extras.

 ???+ note "Minimum version"

-The minimum version to use the `inmem` extra with `langgraph-cli` is `0.1.55`.
-Python 3.11 or higher is required.
+  The minimum version to use the `inmem` extra with `langgraph-cli` is `0.1.55`.
+  Python 3.11 or higher is required.
+  

 ```shell
 pip install -U "langgraph-cli[inmem]"
@@ -31,7 +41,7 @@ pip install -U "langgraph-cli[inmem]"
   langgraph dev
   ```

-This will look for the `langgraph.json` file in your current directory.
+This will look for the `langgraph.json` file in your current directory. 
 In there, it will find the paths to the graph(s), and start those up.
 It will then automatically connect to the cloud-hosted studio.

@@ -79,4 +89,4 @@ Then attach your preferred debugger:
    2. Click + and select "Python Debug Server"
    3. Set IDE host name: `localhost`
    4. Set port: `5678` (or the port number you chose in the previous step)
-    5. Click "OK" and start debugging
+    5. Click "OK" and start debugging
@@ -184,7 +184,7 @@ As noted in the [Anthropic blog](https://www.anthropic.com/research/building-eff

    See our lesson on Prompt Chaining [here](https://github.com/langchain-ai/langchain-academy/blob/main/module-1/chain.ipynb).

-=== "Functional API"
+=== "Functional API (beta)"

    ```python
    from langgraph.func import entrypoint, task
@@ -335,7 +335,7 @@ With parallelization, LLMs work simultaneously on a task:

    See our lesson on parallelization [here](https://github.com/langchain-ai/langchain-academy/blob/main/module-1/simple-graph.ipynb).

-=== "Functional API"
+=== "Functional API (beta)"

    ```python
    @task
@@ -524,7 +524,7 @@ Routing classifies an input and directs it to a followup task. As noted in the [

    [Here](https://langchain-ai.github.io/langgraph/tutorials/rag/langgraph_adaptive_rag_local/) is RAG workflow that routes questions. See our video [here](https://www.youtube.com/watch?v=bq1Plo2RhYI).

-=== "Functional API"
+=== "Functional API (beta)"

    ```python
    from typing_extensions import Literal
@@ -761,7 +761,7 @@ With orchestrator-worker, an orchestrator breaks down a task and delegates each
    [Here](https://github.com/langchain-ai/report-mAIstro) is a project that uses orchestrator-worker for report planning and writing. See our video [here](https://www.youtube.com/watch?v=wSxZ7yFbbas).


-=== "Functional API"
+=== "Functional API (beta)"

    ```python
    from typing import List
@@ -952,7 +952,7 @@ In the evaluator-optimizer workflow, one LLM call generates a response while ano

    [Here](https://langchain-ai.github.io/langgraph/tutorials/rag/langgraph_adaptive_rag_local/) is a RAG workflow that grades answers for hallucinations or errors. See our video [here](https://www.youtube.com/watch?v=bq1Plo2RhYI).

-=== "Functional API"
+=== "Functional API (beta)"

    ```python
    # Schema for structured output to use in evaluation
@@ -1161,7 +1161,7 @@ llm_with_tools = llm.bind_tools(tools)

    [Here](https://github.com/langchain-ai/memory-agent) is a project that uses a tool calling agent to create / store long-term memories.

-=== "Functional API"
+=== "Functional API (beta)"

    ```python
    from langgraph.graph import add_messages
@@ -1270,4 +1270,4 @@ LangGraph provides several ways to stream workflow / agent outputs or intermedia

 ### Deployment

-LangGraph provides an easy on-ramp for deployment, observability, and evaluation. See [module 6](https://github.com/langchain-ai/langchain-academy/tree/main/module-6) of LangChain Academy.
+LangGraph provides an easy on-ramp for deployment, observability, and evaluation. See [module 6](https://github.com/langchain-ai/langchain-academy/tree/main/module-6) of LangChain Academy.
@@ -359,7 +359,7 @@ nav:
    - Resources:
      # NOTE: prebuilt.md is auto-generated by `make build-prebuilt`
      - Prebuilt Agents: prebuilt.md
-      - Companies using LangGraph: adopters.md
+      - Adopters: adopters.md
      - FAQ: concepts/faq.md
      - Troubleshooting:
          - Troubleshooting: troubleshooting/errors/index.md
@@ -169,15 +169,15 @@ files = [

 [[package]]
 name = "anthropic"
-version = "0.47.2"
+version = "0.45.2"
 description = "The official Python library for the anthropic API"
 optional = false
 python-versions = ">=3.8"
 groups = ["test"]
 markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
 files = [
-    {file = "anthropic-0.47.2-py3-none-any.whl", hash = "sha256:61b712a56308fce69f04d92ba0230ab2bc187b5bce17811d400843a8976bb67f"},
-    {file = "anthropic-0.47.2.tar.gz", hash = "sha256:452f4ca0c56ffab8b6ce9928bf8470650f88106a7001b250895eb65c54cfa44c"},
+    {file = "anthropic-0.45.2-py3-none-any.whl", hash = "sha256:ecd746f7274451dfcb7e1180571ead624c7e1195d1d46cb7c70143d2aedb4d35"},
+    {file = "anthropic-0.45.2.tar.gz", hash = "sha256:32a18b9ecd12c91b2be4cae6ca2ab46a06937b5aa01b21308d97a6d29794fb5e"},
 ]

 [package.dependencies]
@@ -1299,7 +1299,7 @@ version = "0.7.1"
 description = "XML bomb protection for Python stdlib modules"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
-groups = ["docs"]
+groups = ["docs", "test"]
 markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
 files = [
    {file = "defusedxml-0.7.1-py2.py3-none-any.whl", hash = "sha256:a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61"},
@@ -3288,20 +3288,21 @@ together = ["langchain-together"]

 [[package]]
 name = "langchain-anthropic"
-version = "0.3.8"
+version = "0.2.4"
 description = "An integration package connecting AnthropicMessages and LangChain"
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["test"]
 markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
 files = [
-    {file = "langchain_anthropic-0.3.8-py3-none-any.whl", hash = "sha256:05a70f51500d3c4e0f3e463730e193a25b6244e06b3bda3d7b2ec21d83d081ae"},
-    {file = "langchain_anthropic-0.3.8.tar.gz", hash = "sha256:1932977b8105744739ffdcb39861b041b73ae93846d0896a775fcea9a29e4b2b"},
+    {file = "langchain_anthropic-0.2.4-py3-none-any.whl", hash = "sha256:bcb6c2d0df4a67aff52816621079d6e743b260911caccf313a72b33b7edece6f"},
+    {file = "langchain_anthropic-0.2.4.tar.gz", hash = "sha256:0382d4c7b5236839b703f7b72b3e06de4bb5be99104b193f719adbe34c49562b"},
 ]

 [package.dependencies]
-anthropic = ">=0.47.0,<1"
-langchain-core = ">=0.3.39,<1.0.0"
+anthropic = ">=0.30.0,<1"
+defusedxml = ">=0.7.1,<0.8.0"
+langchain-core = ">=0.3.15,<0.4.0"
 pydantic = ">=2.7.4,<3.0.0"

 [[package]]
@@ -3356,15 +3357,15 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"

 [[package]]
 name = "langchain-core"
-version = "0.3.40"
+version = "0.3.34"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["docs", "test"]
 markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
 files = [
-    {file = "langchain_core-0.3.40-py3-none-any.whl", hash = "sha256:9f31358741f10a13db8531e8288b8a5ae91904018c5c2e6f739d6645a98fca03"},
-    {file = "langchain_core-0.3.40.tar.gz", hash = "sha256:893a238b38491967c804662c1ec7c3e6ebaf223d1125331249c3cf3862ff2746"},
+    {file = "langchain_core-0.3.34-py3-none-any.whl", hash = "sha256:a057ebeddd2158d3be14bde341b25640ddf958b6989bd6e47160396f5a8202ae"},
+    {file = "langchain_core-0.3.34.tar.gz", hash = "sha256:26504cf1e8e6c310adad907b890d4e3c147581cfa7434114f6dc1134fe4bc6d3"},
 ]

 [package.dependencies]
@@ -3473,19 +3474,19 @@ ollama = ">=0.4.4,<1"

 [[package]]
 name = "langchain-openai"
-version = "0.3.7"
+version = "0.3.4"
 description = "An integration package connecting OpenAI and LangChain"
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["test"]
 markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
 files = [
-    {file = "langchain_openai-0.3.7-py3-none-any.whl", hash = "sha256:0aefc7bdf8e7398d41e09c4313cace816df6438f2aa93d34f79523487310f0da"},
-    {file = "langchain_openai-0.3.7.tar.gz", hash = "sha256:b8b51a3aaa1cc3bda060651ea41145f7728219e8a7150b5404fb1e8446de9cef"},
+    {file = "langchain_openai-0.3.4-py3-none-any.whl", hash = "sha256:58d0c014620eb92f4f46ff9daf584c2a7794896b1379eb85ad7be8d9f3493b61"},
+    {file = "langchain_openai-0.3.4.tar.gz", hash = "sha256:c6645745a1d1bf19f21ea6fa473a746bd464053ff57ce563215e6165a0c4b9f1"},
 ]

 [package.dependencies]
-langchain-core = ">=0.3.39,<1.0.0"
+langchain-core = ">=0.3.34,<1.0.0"
 openai = ">=1.58.1,<2.0.0"
 tiktoken = ">=0.7,<1"

@@ -3507,17 +3508,17 @@ langchain-core = ">=0.3.34,<1.0.0"

 [[package]]
 name = "langgraph"
-version = "0.3.0"
+version = "0.2.71"
 description = "Building stateful, multi-actor applications with LLMs"
 optional = false
 python-versions = ">=3.9.0,<4.0"
-groups = ["docs"]
+groups = ["docs", "test"]
 markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
 files = []
 develop = true

 [package.dependencies]
-langchain-core = ">=0.1,<0.4"
+langchain-core = ">=0.2.43,<0.4.0,!=0.3.0,!=0.3.1,!=0.3.2,!=0.3.3,!=0.3.4,!=0.3.5,!=0.3.6,!=0.3.7,!=0.3.8,!=0.3.9,!=0.3.10,!=0.3.11,!=0.3.12,!=0.3.13,!=0.3.14,!=0.3.15,!=0.3.16,!=0.3.17,!=0.3.18,!=0.3.19,!=0.3.20,!=0.3.21,!=0.3.22"
 langgraph-checkpoint = "^2.0.10"
 langgraph-sdk = "^0.1.42"

@@ -3527,7 +3528,7 @@ url = "../libs/langgraph"

 [[package]]
 name = "langgraph-checkpoint"
-version = "2.0.16"
+version = "2.0.13"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 optional = false
 python-versions = "^3.9.0,<4.0"
@@ -3546,25 +3547,26 @@ url = "../libs/checkpoint"

 [[package]]
 name = "langgraph-checkpoint-mongodb"
-version = "0.1.1"
+version = "0.1.0"
 description = "Library with a MongoDB implementation of LangGraph checkpoint saver."
 optional = false
-python-versions = ">=3.9"
+python-versions = "<4.0.0,>=3.9.0"
 groups = ["test"]
 markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
 files = [
-    {file = "langgraph_checkpoint_mongodb-0.1.1-py3-none-any.whl", hash = "sha256:1ff2c3cb2a9139c38ea9cf398659b8b32d6bbfcc4999713b62014431477c5ac5"},
-    {file = "langgraph_checkpoint_mongodb-0.1.1.tar.gz", hash = "sha256:350d347b0458fb7977231ac1295095bef512458ee0debe09fd394d913b8d89d3"},
+    {file = "langgraph_checkpoint_mongodb-0.1.0-py3-none-any.whl", hash = "sha256:52f20956b36e0275ff805a1eea1db4c1a7e5e0ffe0a1ade65969004fa1654703"},
+    {file = "langgraph_checkpoint_mongodb-0.1.0.tar.gz", hash = "sha256:3165c134ad5c82a3fe02fef04c81dcd48a3f5d031e07a9d1cb84457241f76793"},
 ]

 [package.dependencies]
-langgraph-checkpoint = ">=2.0.0"
+langgraph = ">=0.2.38,<0.3.0"
+langgraph-checkpoint = ">=2.0.0,<3.0.0"
 motor = ">3.5.0"
-pymongo = ">=4.9,<4.12"
+pymongo = ">=4.9.0,<4.10.0"

 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "2.0.15"
+version = "2.0.14"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 optional = false
 python-versions = "^3.9.0,<4.0"
@@ -3574,7 +3576,7 @@ files = []
 develop = true

 [package.dependencies]
-langgraph-checkpoint = "^2.0.15"
+langgraph-checkpoint = "^2.0.10"
 orjson = ">=3.10.1"
 psycopg = "^3.2.0"
 psycopg-pool = "^3.2.0"
@@ -3585,7 +3587,7 @@ url = "../libs/checkpoint-postgres"

 [[package]]
 name = "langgraph-checkpoint-sqlite"
-version = "2.0.5"
+version = "2.0.4"
 description = "Library with a SQLite implementation of LangGraph checkpoint saver."
 optional = false
 python-versions = "^3.9.0"
@@ -3595,40 +3597,20 @@ files = []
 develop = true

 [package.dependencies]
-aiosqlite = ">=0.20,<0.22"
-langgraph-checkpoint = "^2.0.15"
+aiosqlite = "^0.20.0"
+langgraph-checkpoint = "^2.0.10"

 [package.source]
 type = "directory"
 url = "../libs/checkpoint-sqlite"

-[[package]]
-name = "langgraph-prebuilt"
-version = "1.0.0"
-description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
-optional = false
-python-versions = "^3.9.0,<4.0"
-groups = ["docs"]
-markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
-files = []
-develop = true
-
-[package.dependencies]
-langchain-core = ">=0.2.43,<0.4.0,!=0.3.0,!=0.3.1,!=0.3.2,!=0.3.3,!=0.3.4,!=0.3.5,!=0.3.6,!=0.3.7,!=0.3.8,!=0.3.9,!=0.3.10,!=0.3.11,!=0.3.12,!=0.3.13,!=0.3.14,!=0.3.15,!=0.3.16,!=0.3.17,!=0.3.18,!=0.3.19,!=0.3.20,!=0.3.21,!=0.3.22"
-langgraph = ">=0.3,<0.4"
-langgraph-checkpoint = "^2.0.10"
-
-[package.source]
-type = "directory"
-url = "../libs/prebuilt"
-
 [[package]]
 name = "langgraph-sdk"
-version = "0.1.53"
+version = "0.1.51"
 description = "SDK for interacting with LangGraph API"
 optional = false
 python-versions = "^3.9.0,<4.0"
-groups = ["docs"]
+groups = ["docs", "test"]
 markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
 files = []
 develop = true
@@ -5957,6 +5939,7 @@ python-versions = ">=3.8"
 groups = ["test"]
 markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
 files = [
+    {file = "pyasn1-0.6.1-py3-none-any.whl", hash = "sha256:0d632f46f2ba09143da3a8afe9e33fb6f92fa2320ab7e886e2d0f7672af84629"},
    {file = "pyasn1-0.6.1.tar.gz", hash = "sha256:6f580d2bdd84365380830acf45550f2511469f673cb4a5ae3857a3170128b034"},
 ]

@@ -5969,6 +5952,7 @@ python-versions = ">=3.8"
 groups = ["test"]
 markers = "python_version <= \"3.11\" or python_version >= \"3.12\""
 files = [
+    {file = "pyasn1_modules-0.4.1-py3-none-any.whl", hash = "sha256:49bfa96b45a292b711e986f222502c1c9a5e1f4e568fc30e2574a6c7d07838fd"},
    {file = "pyasn1_modules-0.4.1.tar.gz", hash = "sha256:c28e2dbf9c06ad61c71a075c7e0f9fd0f1b0bb2d2ad4377f240d33ac2ab60a7c"},
 ]

@@ -8650,4 +8634,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = "^3.10"
-content-hash = "ac9af57c6abaddd1f181551a7bb8194ef3e4491391a0f2dc71417d68e85cb5b3"
+content-hash = "06debb82135affdb2baf1fdcc028c062c236121508d787588cd0de1db2da11e4"
@@ -13,7 +13,6 @@ hub = "^3.0.1"

 [tool.poetry.group.docs.dependencies]
 langgraph = { path = "../libs/langgraph/", develop = true }
-langgraph-prebuilt = {path = "../libs/prebuilt", develop = true}
 langgraph-checkpoint = { path = "../libs/checkpoint/", develop = true }
 langgraph-checkpoint-sqlite = { path = "../libs/checkpoint-sqlite", develop = true }
 langgraph-checkpoint-postgres = { path = "../libs/checkpoint-postgres", develop = true }
@@ -41,8 +40,8 @@ langchain-cohere = "^0.4.2"

 [tool.poetry.group.test.dependencies]
 langchain = "^0.3.8"
-langchain-openai = "^0.3.7"
-langchain-anthropic = "^0.3.8"
+langchain-openai = "^0.3.0"
+langchain-anthropic = "^0.2.1"
 langchain-nomic = "^0.1.3"
 langchain-fireworks = "^0.2.0"
 langchain-community = "^0.3.0"
@@ -20,7 +20,7 @@ from langgraph.store.base import (
 )
 from langgraph.store.base.batch import AsyncBatchedBaseStore
 from langgraph.store.postgres.base import (
-    PLACEHOLDER,
+    _PLACEHOLDER,
    BasePostgresStore,
    PoolConfig,
    PostgresIndexConfig,
@@ -360,7 +360,7 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
            for (idx, _), vector in zip(embedding_requests, vectors):
                _paramslist = queries[idx][1]
                for i in range(len(_paramslist)):
-                    if _paramslist[i] is PLACEHOLDER:
+                    if _paramslist[i] is _PLACEHOLDER:
                        _paramslist[i] = vector

        for (idx, _), (query, params) in zip(search_ops, queries):
@@ -370,7 +370,7 @@ class BasePostgresStore(Generic[C]):
            if op.query and self.index_config:
                embedding_requests.append((idx, op.query))

-                score_operator, post_operator = get_distance_operator(self)
+                score_operator, post_operator = _get_distance_operator(self)
                vector_type = (
                    cast(PostgresIndexConfig, self.index_config)
                    .get("ann_index_config", {})
@@ -430,10 +430,10 @@ class BasePostgresStore(Generic[C]):
                    OFFSET %s
                """
                params = [
-                    PLACEHOLDER,  # Vector placeholder
+                    _PLACEHOLDER,  # Vector placeholder
                    *ns_args,
                    *filter_params,
-                    PLACEHOLDER,
+                    _PLACEHOLDER,
                    expanded_limit,
                    op.limit,
                    op.offset,
@@ -828,7 +828,7 @@ class PostgresStore(BaseStore, BasePostgresStore[_pg_internal.Conn]):
            for (idx, _), embedding in zip(embedding_requests, embeddings):
                _paramslist = queries[idx][1]
                for i in range(len(_paramslist)):
-                    if _paramslist[i] is PLACEHOLDER:
+                    if _paramslist[i] is _PLACEHOLDER:
                        _paramslist[i] = embedding

        for (idx, _), (query, params) in zip(search_ops, queries):
@@ -1055,7 +1055,7 @@ def _decode_ns_bytes(namespace: Union[str, bytes, list]) -> tuple[str, ...]:
    return tuple(namespace.split("."))


-def get_distance_operator(store: Any) -> tuple[str, str]:
+def _get_distance_operator(store: Any) -> tuple[str, str]:
    """Get the distance operator and score expression based on config."""
    # Note: Today, we are not using ANN indices due to restrictions
    # on PGVector's support for mixing vector and non-vector filters
@@ -1121,4 +1121,4 @@ def _ensure_index_config(
    return embeddings, index_config


-PLACEHOLDER = object()
+_PLACEHOLDER = object()
@@ -1,23 +1,23 @@
-# This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.0.0 and should not be changed by hand.

 [[package]]
 name = "aiosqlite"
-version = "0.21.0"
+version = "0.20.0"
 description = "asyncio bridge to the standard sqlite3 module"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "aiosqlite-0.21.0-py3-none-any.whl", hash = "sha256:2549cf4057f95f53dcba16f2b64e8e2791d7e1adedb13197dd8ed77bb226d7d0"},
-    {file = "aiosqlite-0.21.0.tar.gz", hash = "sha256:131bb8056daa3bc875608c631c678cda73922a2d4ba8aec373b19f18c17e7aa3"},
+    {file = "aiosqlite-0.20.0-py3-none-any.whl", hash = "sha256:36a1deaca0cac40ebe32aac9977a6e2bbc7f5189f23f4a54d5908986729e5bd6"},
+    {file = "aiosqlite-0.20.0.tar.gz", hash = "sha256:6d35c8c256637f4672f843c31021464090805bf925385ac39473fb16eaaca3d7"},
 ]

 [package.dependencies]
 typing_extensions = ">=4.0"

 [package.extras]
-dev = ["attribution (==1.7.1)", "black (==24.3.0)", "build (>=1.2)", "coverage[toml] (==7.6.10)", "flake8 (==7.0.0)", "flake8-bugbear (==24.12.12)", "flit (==3.10.1)", "mypy (==1.14.1)", "ufmt (==2.5.1)", "usort (==1.0.8.post1)"]
-docs = ["sphinx (==8.1.3)", "sphinx-mdinclude (==0.6.1)"]
+dev = ["attribution (==1.7.0)", "black (==24.2.0)", "coverage[toml] (==7.4.1)", "flake8 (==7.0.0)", "flake8-bugbear (==24.2.6)", "flit (==3.9.0)", "mypy (==1.8.0)", "ufmt (==2.3.0)", "usort (==1.0.8.post1)"]
+docs = ["sphinx (==7.2.6)", "sphinx-mdinclude (==0.5.3)"]

 [[package]]
 name = "annotated-types"
@@ -1043,4 +1043,4 @@ watchmedo = ["PyYAML (>=3.10)"]
 [metadata]
 lock-version = "2.1"
 python-versions = "^3.9.0"
-content-hash = "21896b8d3d283d95bc3988aa93f06faf5c47dadc2a8822e5a35672b9cb054693"
+content-hash = "e6d3ca9bce723c05f4c5ae9dc4bee872f7581b7763680b34112f1d280f5a9b0a"
@@ -11,7 +11,7 @@ packages = [{ include = "langgraph" }]
 [tool.poetry.dependencies]
 python = "^3.9.0"
 langgraph-checkpoint = "^2.0.15"
-aiosqlite = ">=0.20,<0.22"
+aiosqlite = "^0.20.0"

 [tool.poetry.group.dev.dependencies]
 ruff = "^0.6.2"
@@ -487,12 +487,7 @@ def _msgpack_ext_hook(code: int, data: bytes) -> Any:
            except Exception:
                return cls.construct(**tup[2])
        except Exception:
-            # for pydantic objects we can't find/reconstruct
-            # let's return the kwargs dict instead
-            try:
-                return tup[2]
-            except NameError:
-                return
+            return
    elif code == EXT_PYDANTIC_V2:
        try:
            tup = msgpack.unpackb(
@@ -505,12 +500,7 @@ def _msgpack_ext_hook(code: int, data: bytes) -> Any:
            except Exception:
                return cls.model_construct(**tup[2])
        except Exception:
-            # for pydantic objects we can't find/reconstruct
-            # let's return the kwargs dict instead
-            try:
-                return tup[2]
-            except NameError:
-                return
+            return


 def _msgpack_enc(data: Any) -> bytes:
@@ -166,13 +166,6 @@ class GetOp(NamedTuple):
        "doc456"  # For a document
        ```
    """
-    refresh_ttl: bool = True
-    """Whether to refresh TTLs for the returned item.
-
-    If no TTL was specified for the original item(s),
-    or if TTL support is not enabled for your adapter,
-    this argument is ignored.
-    """


 class SearchOp(NamedTuple):
@@ -267,13 +260,6 @@ class SearchOp(NamedTuple):
        - "technical documentation about REST APIs"
        - "machine learning papers from 2023"
    """
-    refresh_ttl: bool = True
-    """Whether to refresh TTLs for the returned item.
-
-    If no TTL was specified for the original item(s),
-    or if TTL support is not enabled for your adapter,
-    this argument is ignored.
-    """


 # Type representing a namespace path that can include wildcards
@@ -477,15 +463,6 @@ class PutOp(NamedTuple):
        ]
        ```
    """
-    ttl: Optional[float] = None
-    """Controls the TTL (time-to-live) for the item in minutes.
-
-    If provided, and if the store you are using supports this feature, the item
-    will expire this many minutes after it was last accessed. The expiration timer
-    refreshes on both read operations (get/search) and write operations (put/update).
-    When the TTL expires, the item will be scheduled for deletion on a best-effort basis.
-    Defaults to None (no expiration).
-    """


 Op = Union[GetOp, SearchOp, PutOp, ListNamespacesOp]
@@ -635,13 +612,8 @@ class BaseStore(ABC):
        by providing an `index` configuration at creation time. Without this
        configuration, semantic search is disabled and any `index` arguments
        to storage operations will have no effect.
-
-        Similarly, TTL (time-to-live) support is disabled by default.
-        Subclasses must explicitly set `supports_ttl = True` to enable this feature.
    """

-    supports_ttl = False
-
    __slots__ = ("__weakref__",)

    @abstractmethod
@@ -668,21 +640,17 @@ class BaseStore(ABC):
            The order of results matches the order of input operations.
        """

-    def get(
-        self, namespace: tuple[str, ...], key: str, *, refresh_ttl: bool = True
-    ) -> Optional[Item]:
+    def get(self, namespace: tuple[str, ...], key: str) -> Optional[Item]:
        """Retrieve a single item.

        Args:
            namespace: Hierarchical path for the item.
            key: Unique identifier within the namespace.
-            refresh_ttl: Whether to refresh TTLs for the returned item.
-                If no TTL is specified, this argument is ignored.

        Returns:
            The retrieved item or None if not found.
        """
-        return self.batch([GetOp(namespace, key, refresh_ttl)])[0]
+        return self.batch([GetOp(namespace, key)])[0]

    def search(
        self,
@@ -693,7 +661,6 @@ class BaseStore(ABC):
        filter: Optional[dict[str, Any]] = None,
        limit: int = 10,
        offset: int = 0,
-        refresh_ttl: bool = True,
    ) -> list[SearchItem]:
        """Search for items within a namespace prefix.

@@ -703,8 +670,6 @@ class BaseStore(ABC):
            filter: Key-value pairs to filter results.
            limit: Maximum number of items to return.
            offset: Number of items to skip before returning results.
-            refresh_ttl: Whether to refresh TTLs for the returned items.
-                If no TTL is specified, this argument is ignored.

        Returns:
            List of items matching the search criteria.
@@ -742,9 +707,7 @@ class BaseStore(ABC):
            Note: Natural language search support depends on your store implementation
            and requires proper embedding configuration.
        """
-        return self.batch(
-            [SearchOp(namespace_prefix, filter, limit, offset, query, refresh_ttl)]
-        )[0]
+        return self.batch([SearchOp(namespace_prefix, filter, limit, offset, query)])[0]

    def put(
        self,
@@ -752,8 +715,6 @@ class BaseStore(ABC):
        key: str,
        value: dict[str, Any],
        index: Optional[Union[Literal[False], list[str]]] = None,
-        *,
-        ttl: Optional[float] = None,
    ) -> None:
        """Store or update an item in the store.

@@ -774,20 +735,12 @@ class BaseStore(ABC):
                    - Nested fields: "metadata.title"
                    - Array access: "chapters[*].content" (each indexed separately)
                    - Specific indices: "authors[0].name"
-            ttl: Time to live in minutes. Support for this argument depends on your store adapter.
-                If specified, the item will expire after this many minutes from when it was last accessed.
-                None means no expiration. Expired runs will be deleted opportunistically.
-                By default, the expiration timer refreshes on both read operations (get/search)
-                and write operations (put/update), whenever the item is included in the operation.

        Note:
            Indexing support depends on your store implementation.
            If you do not initialize the store with indexing capabilities,
            the `index` parameter will be ignored.

-            Similarly, TTL support depends on the specific store implementation.
-            Some implementations may not support expiration of items.
-
        ???+ example "Examples"
            Store item. Indexing depends on how you configure the store.
            ```python
@@ -806,12 +759,7 @@ class BaseStore(ABC):
            ```
        """
        _validate_namespace(namespace)
-        if ttl is not None and not self.supports_ttl:
-            raise NotImplementedError(
-                f"TTL is not supported by {self.__class__.__name__}. "
-                f"Use a store implementation that supports TTL or set ttl=None."
-            )
-        self.batch([PutOp(namespace, key, value, index=index, ttl=ttl)])
+        self.batch([PutOp(namespace, key, value, index=index)])

    def delete(self, namespace: tuple[str, ...], key: str) -> None:
        """Delete an item.
@@ -820,7 +768,7 @@ class BaseStore(ABC):
            namespace: Hierarchical path for the item.
            key: Unique identifier within the namespace.
        """
-        self.batch([PutOp(namespace, key, None, ttl=None)])
+        self.batch([PutOp(namespace, key, None)])

    def list_namespaces(
        self,
@@ -875,9 +823,7 @@ class BaseStore(ABC):
        )
        return self.batch([op])[0]

-    async def aget(
-        self, namespace: tuple[str, ...], key: str, *, refresh_ttl: bool = True
-    ) -> Optional[Item]:
+    async def aget(self, namespace: tuple[str, ...], key: str) -> Optional[Item]:
        """Asynchronously retrieve a single item.

        Args:
@@ -887,7 +833,7 @@ class BaseStore(ABC):
        Returns:
            The retrieved item or None if not found.
        """
-        return (await self.abatch([GetOp(namespace, key, refresh_ttl)]))[0]
+        return (await self.abatch([GetOp(namespace, key)]))[0]

    async def asearch(
        self,
@@ -898,7 +844,6 @@ class BaseStore(ABC):
        filter: Optional[dict[str, Any]] = None,
        limit: int = 10,
        offset: int = 0,
-        refresh_ttl: bool = True,
    ) -> list[SearchItem]:
        """Asynchronously search for items within a namespace prefix.

@@ -908,9 +853,6 @@ class BaseStore(ABC):
            filter: Key-value pairs to filter results.
            limit: Maximum number of items to return.
            offset: Number of items to skip before returning results.
-            refresh_ttl: Whether to refresh TTLs for the returned items.
-                Defaults to True. If no TTL is specified, this argument
-                is ignored.

        Returns:
            List of items matching the search criteria.
@@ -950,7 +892,7 @@ class BaseStore(ABC):
        """
        return (
            await self.abatch(
-                [SearchOp(namespace_prefix, filter, limit, offset, query, refresh_ttl)]
+                [SearchOp(namespace_prefix, filter, limit, offset, query)]
            )
        )[0]

@@ -960,8 +902,6 @@ class BaseStore(ABC):
        key: str,
        value: dict[str, Any],
        index: Optional[Union[Literal[False], list[str]]] = None,
-        *,
-        ttl: Optional[float] = None,
    ) -> None:
        """Asynchronously store or update an item in the store.

@@ -982,20 +922,12 @@ class BaseStore(ABC):
                    - Nested fields: "metadata.title"
                    - Array access: "chapters[*].content" (each indexed separately)
                    - Specific indices: "authors[0].name"
-            ttl: Time to live in minutes. Support for this argument depends on your store adapter.
-                If specified, the item will expire after this many minutes from when it was last accessed.
-                None means no expiration. Expired runs will be deleted opportunistically.
-                By default, the expiration timer refreshes on both read operations (get/search)
-                and write operations (put/update), whenever the item is included in the operation.

        Note:
            Indexing support depends on your store implementation.
            If you do not initialize the store with indexing capabilities,
            the `index` parameter will be ignored.

-            Similarly, TTL support depends on the specific store implementation.
-            Some implementations may not support expiration of items.
-
        ???+ example "Examples"
            Store item. Indexing depends on how you configure the store.
            ```python
@@ -1022,12 +954,7 @@ class BaseStore(ABC):
            ```
        """
        _validate_namespace(namespace)
-        if ttl is not None and not self.supports_ttl:
-            raise NotImplementedError(
-                f"TTL is not supported by {self.__class__.__name__}. "
-                f"Use a store implementation that supports TTL or set ttl=None."
-            )
-        await self.abatch([PutOp(namespace, key, value, index=index, ttl=ttl)])
+        await self.abatch([PutOp(namespace, key, value, index=index)])

    async def adelete(self, namespace: tuple[str, ...], key: str) -> None:
        """Asynchronously delete an item.
@@ -65,11 +65,13 @@ class AsyncBatchedBaseStore(BaseStore):
            pass

    async def aget(
-        self, namespace: tuple[str, ...], key: str, *, refresh_ttl: bool = True
+        self,
+        namespace: tuple[str, ...],
+        key: str,
    ) -> Optional[Item]:
        assert not self._task.done()
        fut = self._loop.create_future()
-        self._aqueue.put_nowait((fut, GetOp(namespace, key, refresh_ttl=refresh_ttl)))
+        self._aqueue.put_nowait((fut, GetOp(namespace, key)))
        return await fut

    async def asearch(
@@ -81,22 +83,11 @@ class AsyncBatchedBaseStore(BaseStore):
        filter: Optional[dict[str, Any]] = None,
        limit: int = 10,
        offset: int = 0,
-        refresh_ttl: bool = True,
    ) -> list[SearchItem]:
        assert not self._task.done()
        fut = self._loop.create_future()
        self._aqueue.put_nowait(
-            (
-                fut,
-                SearchOp(
-                    namespace_prefix,
-                    filter,
-                    limit,
-                    offset,
-                    query,
-                    refresh_ttl=refresh_ttl,
-                ),
-            )
+            (fut, SearchOp(namespace_prefix, filter, limit, offset, query))
        )
        return await fut

@@ -106,13 +97,11 @@ class AsyncBatchedBaseStore(BaseStore):
        key: str,
        value: dict[str, Any],
        index: Optional[Union[Literal[False], list[str]]] = None,
-        *,
-        ttl: Optional[float] = None,
    ) -> None:
        assert not self._task.done()
        _validate_namespace(namespace)
        fut = self._loop.create_future()
-        self._aqueue.put_nowait((fut, PutOp(namespace, key, value, index, ttl=ttl)))
+        self._aqueue.put_nowait((fut, PutOp(namespace, key, value, index)))
        return await fut

    async def adelete(
@@ -157,10 +146,12 @@ class AsyncBatchedBaseStore(BaseStore):

    @_check_loop
    def get(
-        self, namespace: tuple[str, ...], key: str, *, refresh_ttl: bool = True
+        self,
+        namespace: tuple[str, ...],
+        key: str,
    ) -> Optional[Item]:
        return asyncio.run_coroutine_threadsafe(
-            self.aget(namespace, key=key, refresh_ttl=refresh_ttl), self._loop
+            self.aget(namespace, key=key), self._loop
        ).result()

    @_check_loop
@@ -173,16 +164,10 @@ class AsyncBatchedBaseStore(BaseStore):
        filter: Optional[dict[str, Any]] = None,
        limit: int = 10,
        offset: int = 0,
-        refresh_ttl: bool = True,
    ) -> list[SearchItem]:
        return asyncio.run_coroutine_threadsafe(
            self.asearch(
-                namespace_prefix,
-                query=query,
-                filter=filter,
-                limit=limit,
-                offset=offset,
-                refresh_ttl=refresh_ttl,
+                namespace_prefix, query=query, filter=filter, limit=limit, offset=offset
            ),
            self._loop,
        ).result()
@@ -194,12 +179,10 @@ class AsyncBatchedBaseStore(BaseStore):
        key: str,
        value: dict[str, Any],
        index: Optional[Union[Literal[False], list[str]]] = None,
-        *,
-        ttl: Optional[float] = None,
    ) -> None:
        _validate_namespace(namespace)
        asyncio.run_coroutine_threadsafe(
-            self.aput(namespace, key=key, value=value, index=index, ttl=ttl), self._loop
+            self.aput(namespace, key=key, value=value, index=index), self._loop
        ).result()

    @_check_loop
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-checkpoint"
-version = "2.0.17"
+version = "2.0.16"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 authors = []
 license = "MIT"
@@ -148,8 +148,8 @@ async def test_async_batch_store(mocker: MockerFixture) -> None:
    assert abatch.call_count == 1
    assert [tuple(c.args[0]) for c in abatch.call_args_list] == [
        (
-            GetOp(("a",), "b", refresh_ttl=True),
-            GetOp(("c",), "d", refresh_ttl=True),
+            GetOp(("a",), "b"),
+            GetOp(("c",), "d"),
        ),
    ]

@@ -467,8 +467,8 @@ async def test_async_batch_store_deduplication(mocker: MockerFixture) -> None:
    assert len(abatch.call_args_list) == 1
    ops = list(abatch.call_args_list[0].args[1])
    assert len(ops) == 2
-    assert GetOp(("test",), "same", refresh_ttl=True) in ops
-    assert GetOp(("test",), "different", refresh_ttl=True) in ops
+    assert GetOp(("test",), "same") in ops
+    assert GetOp(("test",), "different") in ops

    abatch.reset_mock()

@@ -1,226 +0,0 @@
-#!/usr/bin/env python3
-"""
-Script to generate a JSON schema for the langgraph-cli Config class.
-
-This script creates a schema.json file that can be referenced in langgraph.json files
-to provide IDE autocompletion and validation.
-"""
-
-import inspect
-import json
-import textwrap
-from pathlib import Path
-
-import msgspec
-
-from langgraph_cli.config import (
-    AuthConfig,
-    Config,
-    CorsConfig,
-    HttpConfig,
-    IndexConfig,
-    SecurityConfig,
-    StoreConfig,
-)
-
-
-def add_descriptions_to_schema(schema, cls):
-    """Add docstring descriptions to the schema properties."""
-    if schema.get("description"):
-        schema["description"] = inspect.cleandoc(schema["description"])
-    elif class_doc := inspect.getdoc(cls):
-        schema["description"] = inspect.cleandoc(class_doc)
-    # Get attribute docstrings from the class
-    attr_docs = {}
-
-    # Also check class annotations for docstrings
-    source_lines = inspect.getsourcelines(cls)[0]
-    current_attr = None
-    docstring_lines = []
-
-    for line in source_lines:
-        line = line.strip()
-
-        # Check for attribute definition (TypedDict style)
-        if ":" in line and not line.startswith("#") and not line.startswith('"""'):
-            parts = line.split(":", 1)
-            if len(parts) == 2 and parts[0].strip().isidentifier():
-                # If we were collecting a docstring, save it for the previous attribute
-                if current_attr and docstring_lines:
-                    attr_docs[current_attr] = "\n".join(docstring_lines).strip('"')
-                    docstring_lines = []
-
-                current_attr = parts[0].strip()
-
-        # Check for docstring after attribute
-        elif line.startswith('"""') and current_attr:
-            # Start or end of a docstring
-            if len(line) > 3 and line.endswith('"""'):
-                # Single line docstring
-                attr_docs[current_attr] = line.strip('"')
-                current_attr = None
-            elif docstring_lines:
-                # End of multi-line docstring
-                docstring_lines.append(line.rstrip('"'))
-                attr_docs[current_attr] = "\n".join(docstring_lines).strip('"')
-                docstring_lines = []
-                current_attr = None
-            else:
-                # Start of multi-line docstring
-                docstring_lines.append(line.lstrip('"'))
-
-        # Continue multi-line docstring
-        elif docstring_lines and current_attr:
-            docstring_lines.append(line.strip('"'))
-
-    # Add the last docstring if there is one
-    if current_attr and docstring_lines:
-        attr_docs[current_attr] = "\n".join(docstring_lines).strip('"')
-
-    # Add descriptions to properties
-    if "properties" in schema:
-        for prop_name, prop_schema in schema["properties"].items():
-            # First try to get from attribute docstrings
-            if prop_name in attr_docs and "description" not in prop_schema:
-                prop_schema["description"] = textwrap.dedent(attr_docs[prop_name])
-            # Fall back to class docstring parsing
-            elif class_doc:
-                for line in class_doc.split("\n"):
-                    if line.strip().startswith(
-                        f"{prop_name}:"
-                    ) or line.strip().startswith(f'"{prop_name}"'):
-                        description = line.split(":", 1)[1].strip()
-                        if description and "description" not in prop_schema:
-                            prop_schema["description"] = description
-                            break
-
-    # Recursively process nested definitions
-    if "$defs" in schema:
-        for def_name, def_schema in schema["$defs"].items():
-            # Find the class that corresponds to this definition
-            for potential_cls in [
-                Config,
-                StoreConfig,
-                IndexConfig,
-                AuthConfig,
-                SecurityConfig,
-                HttpConfig,
-                CorsConfig,
-            ]:
-                if potential_cls.__name__ == def_name:
-                    add_descriptions_to_schema(def_schema, potential_cls)
-                    break
-
-    return schema
-
-
-def generate_schema():
-    """Generate a JSON schema for the Config class using msgspec."""
-    # Generate the basic schema
-    schema = msgspec.json.schema(Config)
-
-    # Add title and description
-    schema["title"] = "LangGraph CLI Configuration"
-    schema["description"] = "Configuration schema for langgraph-cli"
-
-    # Add docstring descriptions
-    schema = add_descriptions_to_schema(schema, Config)
-
-    # Add constraint that only one of python_version or node_version should be specified
-    config_schema = schema["$defs"]["Config"]
-
-    # Create two subschemas: one with python_version and one with node_version
-    # Define properties specific to Python projects
-    python_specific_props = ["python_version", "pip_config_file"]
-    # Define properties specific to Node.js projects
-    node_specific_props = ["node_version"]
-    # Define properties common to both project types
-    common_props = [
-        k
-        for k in config_schema["properties"]
-        if k not in python_specific_props and k not in node_specific_props
-    ]
-
-    # Create Python schema with python_version and pip_config_file
-    python_schema = {
-        "type": "object",
-        "properties": {
-            # Include Python-specific properties
-            **{k: config_schema["properties"][k].copy() for k in python_specific_props},
-            # Include common properties
-            **{k: config_schema["properties"][k].copy() for k in common_props},
-        },
-        "required": ["dependencies", "graphs"],
-    }
-
-    # Add enum constraint for python_version
-    if "python_version" in python_schema["properties"]:
-        python_schema["properties"]["python_version"]["enum"] = ["3.11", "3.12"]
-
-    # Create Node.js schema with node_version
-    node_schema = {
-        "type": "object",
-        "properties": {
-            # Include Node-specific properties
-            **{k: config_schema["properties"][k].copy() for k in node_specific_props},
-            # Include common properties
-            **{k: config_schema["properties"][k].copy() for k in common_props},
-        },
-        "required": ["node_version", "graphs"],
-    }
-
-    # Add enum constraint for node_version
-    if "node_version" in node_schema["properties"]:
-        node_schema["properties"]["node_version"]["anyOf"] = [
-            {"type": "string", "enum": ["20"]},
-            {"type": "null"},
-        ]
-
-    # Replace the Config schema with a oneOf constraint
-    config_schema["oneOf"] = [python_schema, node_schema]
-
-    # Remove the properties field as it's now defined in the oneOf subschemas
-    if "properties" in config_schema:
-        del config_schema["properties"]
-
-    return schema
-
-
-def main():
-    """Generate the schema and write it to a file."""
-    schema = generate_schema()
-
-    # Add versioning to the schema
-    import importlib.metadata
-
-    try:
-        version = importlib.metadata.version("langgraph_cli").split(".")
-        schema_version = f"v{version[0]}"
-    except importlib.metadata.PackageNotFoundError:
-        schema_version = "v1"
-
-    # Add version to schema
-    schema["version"] = schema_version
-
-    config_dir = Path(__file__).parent / "schemas"
-
-    # Create versioned schema file
-    versioned_path = config_dir / f"schema.{schema_version}.json"
-    with open(versioned_path, "w") as f:
-        json.dump(schema, f, indent=2)
-
-    # Also create a latest version
-    latest_path = config_dir / "schema.json"
-    with open(latest_path, "w") as f:
-        json.dump(schema, f, indent=2)
-
-    print(f"Schema written to {versioned_path} and {latest_path}")
-    print(
-        f"You can now add '$schema: https://raw.githubusercontent.com/langchain-ai/langgraph/refs/heads/main/libs/cli/schemas/schema.json'"
-        f" or '$schema: https://raw.githubusercontent.com/langchain-ai/langgraph/refs/heads/main/libs/cli/schemas/schema.{schema_version}.json'"
-        " to your langgraph.json files"
-    )
-
-
-if __name__ == "__main__":
-    main()
@@ -3,7 +3,7 @@ import os
 import pathlib
 import textwrap
 from collections import Counter
-from typing import Any, NamedTuple, Optional, TypedDict, Union
+from typing import NamedTuple, Optional, TypedDict, Union

 import click

@@ -12,18 +12,12 @@ MIN_PYTHON_VERSION = "3.11"


 class IndexConfig(TypedDict, total=False):
-    """Configuration for indexing documents for semantic search in the store.
-
-    This governs how text is converted into embeddings and stored for vector-based lookups.
-    """
+    """Configuration for indexing documents for semantic search in the store."""

    dims: int
-    """Required. Dimensionality of the embedding vectors you will store.
+    """Number of dimensions in the embedding vectors.
    
-    Must match the output dimension of your selected embedding model or custom embed function.
-    If mismatched, you will likely encounter shape/size errors when inserting or querying vectors.
-    
-    Common embedding model output dimensions:
+    Common embedding models have the following dimensions:
        - openai:text-embedding-3-large: 3072
        - openai:text-embedding-3-small: 1536
        - openai:text-embedding-ada-002: 1536
@@ -34,123 +28,42 @@ class IndexConfig(TypedDict, total=False):
    """

    embed: str
-    """Required. Identifier or reference to the embedding model or a custom embedding function.
+    """Optional model (string) to generate embeddings from text or path to model or function.
    
-    The format can vary:
-      - "<provider>:<model_name>" for recognized providers (e.g., "openai:text-embedding-3-large")
-      - "path/to/module.py:function_name" for your own local embedding function
-      - "my_custom_embed" if it's a known alias in your system
-
-     Examples:
+    Examples:
        - "openai:text-embedding-3-large"
        - "cohere:embed-multilingual-v3.0"
-        - "src/app.py:embeddings"
-    
-    Note: Must return embeddings of dimension `dims`.
+        - "src/app.py:embeddings
    """

    fields: Optional[list[str]]
-    """Optional. List of JSON fields to extract before generating embeddings.
+    """Fields to extract text from for embedding generation.
    
-    Defaults to ["$"], which means the entire JSON object is embedded as one piece of text.
-    If you provide multiple fields (e.g. ["title", "content"]), each is extracted and embedded separately,
-    often saving token usage if you only care about certain parts of the data.
-    
-    Example:
-        fields=["title", "abstract", "author.biography"]
+    Defaults to the root ["$"], which embeds the json object as a whole.
    """


 class StoreConfig(TypedDict, total=False):
-    """Configuration for the built-in long-term memory store.
-
-    This store can optionally perform semantic search. If you omit `index`,
-    the store will just handle traditional (non-embedded) data without vector lookups.
-    """
-
-    index: Optional[IndexConfig]
-    """Optional. Defines the vector-based semantic search configuration.
-    
-    If provided, the store will:
-      - Generate embeddings according to `index.embed`
-      - Enforce the embedding dimension given by `index.dims`
-      - Embed only specified JSON fields (if any) from `index.fields`
-    
-    If omitted, no vector index is initialized.
-    """
+    embed: Optional[IndexConfig]
+    """Configuration for vector embeddings in store."""


 class SecurityConfig(TypedDict, total=False):
-    """Configuration for OpenAPI security definitions and requirements.
-
-    Useful for specifying global or path-level authentication and authorization flows
-    (e.g., OAuth2, API key headers, etc.).
-    """
-
-    securitySchemes: dict[str, dict[str, Any]]
-    """Required. Dict describing each security scheme recognized by your OpenAPI spec.
-    
-    Keys are scheme names (e.g. "OAuth2", "ApiKeyAuth") and values are their definitions.
-    Example:
-        {
-            "OAuth2": {
-                "type": "oauth2",
-                "flows": {
-                    "password": {
-                        "tokenUrl": "/token",
-                        "scopes": {"read": "Read data", "write": "Write data"}
-                    }
-                }
-            }
-        }
-    """
-    security: list[dict[str, list[str]]]
-    """Optional. Global security requirements across all endpoints.
-    
-    Each element in the list maps a security scheme (e.g. "OAuth2") to a list of scopes (e.g. ["read", "write"]).
-    Example:
-        [
-            {"OAuth2": ["read", "write"]},
-            {"ApiKeyAuth": []}
-        ]
-    """
+    securitySchemes: dict
+    security: list
    # path => {method => security}
-    paths: dict[str, dict[str, list[dict[str, list[str]]]]]
-    """Optional. Path-specific security overrides.
-    
-    Keys are path templates (e.g., "/items/{item_id}"), mapping to:
-      - Keys that are HTTP methods (e.g., "GET", "POST"),
-      - Values are lists of security definitions (just like `security`) for that method.
-    
-    Example:
-        {
-            "/private_data": {
-                "GET": [{"OAuth2": ["read"]}],
-                "POST": [{"OAuth2": ["write"]}]
-            }
-        }
-    """
+    paths: dict[str, dict[str, list]]


 class AuthConfig(TypedDict, total=False):
-    """Configuration for custom authentication logic and how it integrates into the OpenAPI spec."""
-
    path: str
-    """Required. Path to an instance of the Auth() class that implements custom authentication.
-    
-    Format: "path/to/file.py:my_auth"
-    """
+    """Path to the authentication function in a Python file."""
    disable_studio_auth: bool
-    """Optional. Whether to disable LangSmith API-key authentication for requests originating the Studio. 
-    
-    Defaults to False, meaning that if a particular header is set, the server will verify the `x-api-key` header
-    value is a valid API key for the deployment's workspace. If True, all requests will go through your custom
-    authentication logic, regardless of origin of the request.
-    """
+    """Whether to disable auth when connecting from the LangSmith Studio."""
    openapi: SecurityConfig
-    """Required. Detailed security configuration that merges into your deployment's OpenAPI spec.
-    
-    Example (OAuth2):
+    """The schema to use for updating the openapi spec.
+
+    Example:
        {
            "securitySchemes": {
                "OAuth2": {
@@ -158,185 +71,88 @@ class AuthConfig(TypedDict, total=False):
                    "flows": {
                        "password": {
                            "tokenUrl": "/token",
-                            "scopes": {"me": "Read user info", "items": "Manage items"}
+                            "scopes": {
+                                "me": "Read information about the current user",
+                                "items": "Access to create and manage items"
+                            }
                        }
                    }
                }
            },
            "security": [
-                {"OAuth2": ["me"]}
+                {"OAuth2": ["me"]}  # Default security requirement for all endpoints
            ]
        }
    """


 class CorsConfig(TypedDict, total=False):
-    """Specifies Cross-Origin Resource Sharing (CORS) rules for your server.
-
-    If omitted, defaults are typically very restrictive (often no cross-origin requests).
-    Configure carefully if you want to allow usage from browsers hosted on other domains.
-    """
-
    allow_origins: list[str]
-    """Optional. List of allowed origins (e.g., "https://example.com").
-    
-    Default is often an empty list (no external origins). 
-    Use "*" only if you trust all origins, as that bypasses most restrictions.
-    """
    allow_methods: list[str]
-    """Optional. HTTP methods permitted for cross-origin requests (e.g. ["GET", "POST"]).
-    
-    Default might be ["GET", "POST", "OPTIONS"] depending on your server framework.
-    """
    allow_headers: list[str]
-    """Optional. HTTP headers that can be used in cross-origin requests (e.g. ["Content-Type", "Authorization"])."""
    allow_credentials: bool
-    """Optional. If True, cross-origin requests can include credentials (cookies, auth headers).
-    
-    Default False to avoid accidentally exposing secured endpoints to untrusted sites.
-    """
    allow_origin_regex: str
-    """Optional. A regex pattern for matching allowed origins, used if you have dynamic subdomains.
-    
-    Example: "^https://.*\.mycompany\.com$"
-    """
    expose_headers: list[str]
-    """Optional. List of headers that browsers are allowed to read from the response in cross-origin contexts."""
    max_age: int
-    """Optional. How many seconds the browser may cache preflight responses.
-    
-    Default might be 600 (10 minutes). Larger values reduce preflight requests but can cause stale configurations.
-    """


 class HttpConfig(TypedDict, total=False):
-    """Configuration for the built-in HTTP server that powers your deployment's routes and endpoints."""
-
    app: str
-    """Optional. Import path to a custom Starlette/FastAPI application to mount.
-    
-    Format: "path/to/module.py:app_var"
-    If provided, it can override or extend the default routes.
-    """
+    """Import path for a custom Starlette/FastAPI app to mount"""
    disable_assistants: bool
-    """Optional. If True, /assistants routes are removed from the server.
-    
-    Default is False (meaning /assistants is enabled).
-    """
+    """Disable /assistants routes"""
    disable_threads: bool
-    """Optional. If True, /threads routes are removed.
-    
-    Default is False.
-    """
+    """Disable /threads routes"""
    disable_runs: bool
-    """Optional. If True, /runs routes are removed.
-    
-    Default is False.
-    """
+    """Disable /runs routes"""
    disable_store: bool
-    """Optional. If True, /store routes are removed, disabling direct store interactions via HTTP.
-    
-    Default is False.
-    """
+    """Disable /store routes"""
    disable_meta: bool
-    """Optional. If True, all meta endpoints (/ok, /info, /metrics, /docs) are disabled.
-    
-    Default is False.
-    """
+    """Disable /ok, /info, /metrics, and /docs routes"""
    cors: Optional[CorsConfig]
-    """Optional. Defines CORS restrictions. If omitted, no special rules are set and 
-    cross-origin behavior depends on default server settings.
-    """
+    """Cross-Origin Resource Sharing (CORS) configuration"""


 class Config(TypedDict, total=False):
-    """Top-level config for langgraph-cli or similar deployment tooling."""
+    """Configuration for langgraph-cli."""

    python_version: str
-    """Optional. Python version in 'major.minor' format (e.g. '3.11'). 
-    Must be at least 3.11 or greater for this deployment to function properly.
-    """
+    """Python version to use."""

    node_version: Optional[str]
-    """Optional. Node.js version as a major version (e.g. '20'), if your deployment needs Node.
-    Must be >= 20 if provided.
-    """
+    """Node.js version to use."""

    pip_config_file: Optional[str]
-    """Optional. Path to a pip config file (e.g., "/etc/pip.conf" or "pip.ini") for controlling
-    package installation (custom indices, credentials, etc.).
-    
-    Only relevant if Python dependencies are installed via pip. If omitted, default pip settings are used.
-    """
+    """Path to a pip configuration file."""

    dockerfile_lines: list[str]
-    """Optional. Additional Docker instructions that will be appended to your base Dockerfile.
-    
-    Useful for installing OS packages, setting environment variables, etc. 
-    Example:
-        dockerfile_lines=[
-            "RUN apt-get update && apt-get install -y libmagic-dev",
-            "ENV MY_CUSTOM_VAR=hello_world"
-        ]
-    """
+    """Additional lines to add to the Dockerfile."""

    dependencies: list[str]
-    """List of Python dependencies to install, either from PyPI or local paths.
-    
-    Examples:
-      - "." or "./src" if you have a local Python package
-      - str (aka "anthropic") for a PyPI package
-      - "git+https://github.com/org/repo.git@main" for a Git-based package
-    Defaults to an empty list, meaning no additional packages installed beyond your base environment.
-    """
+    """Additional Python dependencies to install."""

    graphs: dict[str, str]
-    """Optional. Named definitions of graphs, each pointing to a Python object.
-
-    
-    Graphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context
-    managers that accept a single configuration argument (of type RunnableConfig) and return a pregel object
-    (instance of Stategraph, etc.).
-    
-    Keys are graph names, values are "path/to/file.py:object_name".
-    Example:
-        {
-            "mygraph": "graphs/my_graph.py:graph_definition",
-            "anothergraph": "graphs/another.py:get_graph"
-        }
-    """
+    """Mapping of graph names to their definitions."""

    env: Union[dict[str, str], str]
-    """Optional. Environment variables to set for your deployment.
-    
-    - If given as a dict, keys are variable names and values are their values.
-    - If given as a string, it must be a path to a file containing lines in KEY=VALUE format.
-    
-    Example as a dict:
-        env={"API_TOKEN": "abc123", "DEBUG": "true"}
-    Example as a file path:
-        env=".env"
+    """Environment variables to set.
+
+    If a dictionary is provided, the keys are environment variable names
+    and the values are the corresponding environment variable values.
+
+    If a string is provided, it is interpreted as a path to a file containing
+    environment variables in the format KEY=VALUE, with one environment variable
+    per line.
    """

    store: Optional[StoreConfig]
-    """Optional. Configuration for the built-in long-term memory store, including semantic search indexing.
-    
-    If omitted, no vector index is set up (the object store will still be present, however).
-    """
+    """Configuration for vector embeddings in store."""

    auth: Optional[AuthConfig]
-    """Optional. Custom authentication config, including the path to your Python auth logic and 
-    the OpenAPI security definitions it uses.
-    """
+    """Configuration for authentication."""

    http: Optional[HttpConfig]
-    """Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed
-    and how cross-origin requests are handled.
-    """
-
-    ui: Optional[dict[str, str]]
-    """Optional. Named definitions of UI components emitted by the agent, each pointing to a JS/TS file.
-    """
+    """Configuration for HTTP server."""


 def _parse_version(version_str: str) -> tuple[int, int]:
@@ -373,7 +189,6 @@ def validate_config(config: Config) -> Config:
            "store": config.get("store"),
            "auth": config.get("auth"),
            "http": config.get("http"),
-            "ui": config.get("ui"),
        }
        if config.get("node_version")
        else {
@@ -386,7 +201,6 @@ def validate_config(config: Config) -> Config:
            "store": config.get("store"),
            "auth": config.get("auth"),
            "http": config.get("http"),
-            "ui": config.get("ui"),
        }
    )

@@ -873,11 +687,9 @@ def python_config_to_docker(
    pip_pkgs_str = f"RUN {pip_install} {' '.join(pypi_deps)}" if pypi_deps else ""
    if local_deps.pip_reqs:
        pip_reqs_str = os.linesep.join(
-            (
-                f"COPY --from=__outer_{reqpath.name} requirements.txt {destpath}"
-                if reqpath.parent in local_deps.additional_contexts
-                else f"ADD {reqpath.relative_to(config_path.parent)} {destpath}"
-            )
+            f"COPY --from=__outer_{reqpath.name} requirements.txt {destpath}"
+            if reqpath.parent in local_deps.additional_contexts
+            else f"ADD {reqpath.relative_to(config_path.parent)} {destpath}"
            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)}'
@@ -912,15 +724,13 @@ RUN set -ex && \\
    )

    local_pkgs_str = os.linesep.join(
-        (
-            f"""# -- Adding local package {relpath} --
+        f"""# -- Adding local package {relpath} --
 COPY --from={name} . /deps/{name}
 # -- End of local package {relpath} --"""
-            if fullpath in local_deps.additional_contexts
-            else f"""# -- Adding local package {relpath} --
+        if fullpath in local_deps.additional_contexts
+        else f"""# -- Adding local package {relpath} --
 ADD {relpath} /deps/{name}
 # -- End of local package {relpath} --"""
-        )
        for fullpath, (relpath, name) in local_deps.real_pkgs.items()
    )

@@ -1035,7 +845,6 @@ ADD . {faux_path}
 RUN cd {faux_path} && {install_cmd}
 {env_additional_config}
 ENV LANGSERVE_GRAPHS='{json.dumps(config["graphs"])}'
-{f"ENV LANGGRAPH_UI='{json.dumps(config['ui'])}'" if config.get("ui") else ""}

 WORKDIR {faux_path}

@@ -446,47 +446,54 @@ files = [

 [[package]]
 name = "jsonschema-rs"
-version = "0.20.0"
+version = "0.25.1"
 description = "A high-performance JSON Schema validator for Python"
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "jsonschema_rs-0.20.0-cp310-cp310-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:d4b12f8aaec5037529fd11e5f71032cb53d44e8e2236bb7c3fb35e6efc7ce7f2"},
-    {file = "jsonschema_rs-0.20.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:25d512c47c5c391020c9fc4223f270cf42fbdd39b2906dbc894fe0205168b8f8"},
-    {file = "jsonschema_rs-0.20.0-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:5e4d449a8c2d67c774b8719964cf4dc8eb453a6c665ddf0815780dbcc46a31be"},
-    {file = "jsonschema_rs-0.20.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:60e14bd30306f300d194d6053a8b7dc3723bac20edc2c27db055e45bcc02687c"},
-    {file = "jsonschema_rs-0.20.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2ea9cd8058c6d8ace05fd60a4e11d5bd933f4c21d55c4cccb2bdb6faba9b0319"},
-    {file = "jsonschema_rs-0.20.0-cp310-none-win32.whl", hash = "sha256:ef3198e43addd93619242a30ba40962521b384d68c05507fc680b549d95f7cc0"},
-    {file = "jsonschema_rs-0.20.0-cp310-none-win_amd64.whl", hash = "sha256:ab5a5c6b7282242c64bfc812c10d72dcbd9f5fe083cf81ae94de3cc2da7f0e1e"},
-    {file = "jsonschema_rs-0.20.0-cp311-cp311-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:2f76153d57c8c3778829e14867dd6479eaba17f56e2ba42da82494663200b37a"},
-    {file = "jsonschema_rs-0.20.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:1a2b24871ade985580a3f10cfde2a52673823163813fe311abffb30e0aeb4181"},
-    {file = "jsonschema_rs-0.20.0-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:6bf5afaa6e80aa59fae06ca92efb1f8e29b2679f8f8884585272f7c100f04c69"},
-    {file = "jsonschema_rs-0.20.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42d180b318653184eb69d9641dfded6b2d59c88db8fb82012d3d20e1582af5cd"},
-    {file = "jsonschema_rs-0.20.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7aa67bf6338fbce3a2a3f9f408413aad7a72593ed73c846bc2667a20b747327f"},
-    {file = "jsonschema_rs-0.20.0-cp311-none-win32.whl", hash = "sha256:55c255ca6ee44177b7b5c773a8edb25af34be0d6a454e602be92cc183d6dcbe7"},
-    {file = "jsonschema_rs-0.20.0-cp311-none-win_amd64.whl", hash = "sha256:3b6effefdef590854522517b84081214b46a8fba9a5d60c538c6f1ff819609c5"},
-    {file = "jsonschema_rs-0.20.0-cp312-cp312-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:8b9d044ecdef9a15e350a35e950c9797c804f185b547bcb56bb91fef9bf31827"},
-    {file = "jsonschema_rs-0.20.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:d43b6a65c159f7aed82dca846f93a4c5ffd013ff0c87a5668a645a81792c8001"},
-    {file = "jsonschema_rs-0.20.0-cp312-cp312-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:9a6500934be21fe64bd65d9e75a67941b675091b8e2154df0a04f5b57073b8bf"},
-    {file = "jsonschema_rs-0.20.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:41e42c80eed641a848ee38039291e6ca90e61de1a0b695e706894b175f45c741"},
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 [[package]]
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-
-[package.dependencies]
-langchain-core = ">=0.2.43,<0.3.0 || >0.3.0,<0.3.1 || >0.3.1,<0.3.2 || >0.3.2,<0.3.3 || >0.3.3,<0.3.4 || >0.3.4,<0.3.5 || >0.3.5,<0.3.6 || >0.3.6,<0.3.7 || >0.3.7,<0.3.8 || >0.3.8,<0.3.9 || >0.3.9,<0.3.10 || >0.3.10,<0.3.11 || >0.3.11,<0.3.12 || >0.3.12,<0.3.13 || >0.3.13,<0.3.14 || >0.3.14,<0.3.15 || >0.3.15,<0.3.16 || >0.3.16,<0.3.17 || >0.3.17,<0.3.18 || >0.3.18,<0.3.19 || >0.3.19,<0.3.20 || >0.3.20,<0.3.21 || >0.3.21,<0.3.22 || >0.3.22,<0.4.0"
-langgraph-checkpoint = ">=2.0.10,<3.0.0"
-
 [[package]]
 name = "langgraph-sdk"
 version = "0.1.53"
@@ -609,19 +600,18 @@ orjson = ">=3.10.1"

 [[package]]
 name = "langsmith"
-version = "0.3.11"
+version = "0.3.8"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langsmith-0.3.11-py3-none-any.whl", hash = "sha256:0cca22737ef07d3b038a437c141deda37e00add56022582680188b681bec095e"},
-    {file = "langsmith-0.3.11.tar.gz", hash = "sha256:ddf29d24352e99de79c9618aaf95679214324e146c5d3d9475a7ddd2870018b1"},
+    {file = "langsmith-0.3.8-py3-none-any.whl", hash = "sha256:fbb9dd97b0f090219447fca9362698d07abaeda1da85aa7cc6ec6517b36581b1"},
+    {file = "langsmith-0.3.8.tar.gz", hash = "sha256:97f9bebe0b7cb0a4f278e6ff30ae7d5ededff3883b014442ec6d7d575b02a0f1"},
 ]

 [package.dependencies]
 httpx = ">=0.23.0,<1"
 orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""}
-packaging = ">=23.2"
 pydantic = [
    {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
@@ -707,58 +697,6 @@ files = [
    {file = "msgpack-1.1.0.tar.gz", hash = "sha256:dd432ccc2c72b914e4cb77afce64aab761c1137cc698be3984eee260bcb2896e"},
 ]

-[[package]]
-name = "msgspec"
-version = "0.19.0"
-description = "A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML."
-optional = false
-python-versions = ">=3.9"
-files = [
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-    {file = "msgspec-0.19.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0553bbc77662e5708fe66aa75e7bd3e4b0f209709c48b299afd791d711a93c36"},
-    {file = "msgspec-0.19.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fe2c4bf29bf4e89790b3117470dea2c20b59932772483082c468b990d45fb947"},
-    {file = "msgspec-0.19.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:00e87ecfa9795ee5214861eab8326b0e75475c2e68a384002aa135ea2a27d909"},
-    {file = "msgspec-0.19.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:3c4ec642689da44618f68c90855a10edbc6ac3ff7c1d94395446c65a776e712a"},
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-    {file = "msgspec-0.19.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ca06aa08e39bf57e39a258e1996474f84d0dd8130d486c00bec26d797b8c5446"},
-    {file = "msgspec-0.19.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:e695dad6897896e9384cf5e2687d9ae9feaef50e802f93602d35458e20d1fb19"},
-    {file = "msgspec-0.19.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:3be5c02e1fee57b54130316a08fe40cca53af92999a302a6054cd451700ea7db"},
-    {file = "msgspec-0.19.0-cp39-cp39-win_amd64.whl", hash = "sha256:0684573a821be3c749912acf5848cce78af4298345cb2d7a8b8948a0a5a27cfe"},
-    {file = "msgspec-0.19.0.tar.gz", hash = "sha256:604037e7cd475345848116e89c553aa9a233259733ab51986ac924ab1b976f8e"},
-]
-
-[package.extras]
-dev = ["attrs", "coverage", "eval-type-backport", "furo", "ipython", "msgpack", "mypy", "pre-commit", "pyright", "pytest", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "tomli", "tomli_w"]
-doc = ["furo", "ipython", "sphinx", "sphinx-copybutton", "sphinx-design"]
-test = ["attrs", "eval-type-backport", "msgpack", "pytest", "pyyaml", "tomli", "tomli_w"]
-toml = ["tomli", "tomli_w"]
-yaml = ["pyyaml"]
-
 [[package]]
 name = "mypy"
 version = "1.15.0"
@@ -1340,13 +1278,13 @@ examples = ["fastapi"]

 [[package]]
 name = "starlette"
-version = "0.46.0"
+version = "0.45.3"
 description = "The little ASGI library that shines."
 optional = true
 python-versions = ">=3.9"
 files = [
-    {file = "starlette-0.46.0-py3-none-any.whl", hash = "sha256:913f0798bd90ba90a9156383bcf1350a17d6259451d0d8ee27fc0cf2db609038"},
-    {file = "starlette-0.46.0.tar.gz", hash = "sha256:b359e4567456b28d473d0193f34c0de0ed49710d75ef183a74a5ce0499324f50"},
+    {file = "starlette-0.45.3-py3-none-any.whl", hash = "sha256:dfb6d332576f136ec740296c7e8bb8c8a7125044e7c6da30744718880cdd059d"},
+    {file = "starlette-0.45.3.tar.gz", hash = "sha256:2cbcba2a75806f8a41c722141486f37c28e30a0921c5f6fe4346cb0dcee1302f"},
 ]

 [package.dependencies]
@@ -1357,18 +1295,18 @@ full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart

 [[package]]
 name = "structlog"
-version = "23.3.0"
+version = "24.4.0"
 description = "Structured Logging for Python"
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "structlog-23.3.0-py3-none-any.whl", hash = "sha256:d6922a88ceabef5b13b9eda9c4043624924f60edbb00397f4d193bd754cde60a"},
-    {file = "structlog-23.3.0.tar.gz", hash = "sha256:24b42b914ac6bc4a4e6f716e82ac70d7fb1e8c3b1035a765591953bfc37101a5"},
+    {file = "structlog-24.4.0-py3-none-any.whl", hash = "sha256:597f61e80a91cc0749a9fd2a098ed76715a1c8a01f73e336b746504d1aad7610"},
+    {file = "structlog-24.4.0.tar.gz", hash = "sha256:b27bfecede327a6d2da5fbc96bd859f114ecc398a6389d664f62085ee7ae6fc4"},
 ]

 [package.extras]
-dev = ["structlog[tests,typing]"]
-docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-mermaid", "sphinxext-opengraph", "twisted"]
+dev = ["freezegun (>=0.2.8)", "mypy (>=1.4)", "pretend", "pytest (>=6.0)", "pytest-asyncio (>=0.17)", "rich", "simplejson", "twisted"]
+docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-mermaid", "sphinxext-opengraph", "twisted"]
 tests = ["freezegun (>=0.2.8)", "pretend", "pytest (>=6.0)", "pytest-asyncio (>=0.17)", "simplejson"]
 typing = ["mypy (>=1.4)", "rich", "twisted"]

@@ -1717,4 +1655,4 @@ inmem = ["langgraph-api", "python-dotenv"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9.0,<4.0"
-content-hash = "d0e2bdcb600ad031867413025fcc58bb162609209359d63ca99a77060cf8cbb4"
+content-hash = "48e374a559e6d8339c82b5271dea910f8ddfb6baf8436153ca54faefb8b2b220"
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-cli"
-version = "0.1.75"
+version = "0.1.73"
 description = "CLI for interacting with LangGraph API"
 authors = []
 license = "MIT"
@@ -14,7 +14,7 @@ langgraph = "langgraph_cli.cli:cli"
 [tool.poetry.dependencies]
 python = "^3.9.0,<4.0"
 click = "^8.1.7"
-langgraph-api = { version = ">=0.0.27,<0.1.0", optional = true, python = ">=3.11,<4.0" }
+langgraph-api = { version = ">=0.0.26,<0.1.0", optional = true, python = ">=3.11,<4.0" }
 python-dotenv = { version = ">=0.8.0", optional = true }

 [tool.poetry.group.dev.dependencies]
@@ -25,7 +25,6 @@ pytest-asyncio = "^0.21.1"
 pytest-mock = "^3.11.1"
 pytest-watch = "^4.2.0"
 mypy = "^1.10.0"
-msgspec = "^0.19.0"

 [tool.poetry.extras]
 inmem = ["langgraph-api", "python-dotenv"]
@@ -1,438 +0,0 @@
-{
-  "$ref": "#/$defs/Config",
-  "$defs": {
-    "Config": {
-      "title": "Config",
-      "description": "Top-level config for langgraph-cli or similar deployment tooling.",
-      "type": "object",
-      "required": [],
-      "oneOf": [
-        {
-          "type": "object",
-          "properties": {
-            "python_version": {
-              "type": "string",
-              "description": "Optional. Python version in 'major.minor' format (e.g. '3.11').\nMust be at least 3.11 or greater for this deployment to function properly.\n",
-              "enum": [
-                "3.11",
-                "3.12"
-              ]
-            },
-            "pip_config_file": {
-              "anyOf": [
-                {
-                  "type": "string"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Path to a pip config file (e.g., \"/etc/pip.conf\" or \"pip.ini\") for controlling\npackage installation (custom indices, credentials, etc.).\n\nOnly relevant if Python dependencies are installed via pip. If omitted, default pip settings are used.\n"
-            },
-            "auth": {
-              "anyOf": [
-                {
-                  "$ref": "#/$defs/AuthConfig"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Custom authentication config, including the path to your Python auth logic and\nthe OpenAPI security definitions it uses.\n"
-            },
-            "dependencies": {
-              "type": "array",
-              "items": {
-                "type": "string"
-              },
-              "description": "List of Python dependencies to install, either from PyPI or local paths.\n"
-            },
-            "dockerfile_lines": {
-              "type": "array",
-              "items": {
-                "type": "string"
-              },
-              "description": "Optional. Additional Docker instructions that will be appended to your base Dockerfile.\n\nUseful for installing OS packages, setting environment variables, etc."
-            },
-            "env": {
-              "anyOf": [
-                {
-                  "type": "object",
-                  "additionalProperties": {
-                    "type": "string"
-                  }
-                },
-                {
-                  "type": "string"
-                }
-              ],
-              "description": "Optional. Environment variables to set for your deployment.\n\n- If given as a dict, keys are variable names and values are their values.\n- If given as a string, it must be a path to a file containing lines in KEY=VALUE format.\n\nenv=\".env\n"
-            },
-            "graphs": {
-              "type": "object",
-              "additionalProperties": {
-                "type": "string"
-              },
-              "description": "Optional. Named definitions of graphs, each pointing to a Python object.\n\n\nGraphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context\nmanagers that accept a single configuration argument (of type RunnableConfig) and return a pregel object\n(instance of Stategraph, etc.).\n"
-            },
-            "http": {
-              "anyOf": [
-                {
-                  "$ref": "#/$defs/HttpConfig"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed\nand how cross-origin requests are handled.\n"
-            },
-            "store": {
-              "anyOf": [
-                {
-                  "$ref": "#/$defs/StoreConfig"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Configuration for the built-in long-term memory store, including semantic search indexing.\n\nIf omitted, no vector index is set up (the object store will still be present, however).\n"
-            },
-            "ui": {
-              "anyOf": [
-                {
-                  "type": "object",
-                  "additionalProperties": {
-                    "type": "string"
-                  }
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Named definitions of UI components emitted by the agent, each pointing to a JS/TS file.\n"
-            }
-          },
-          "required": [
-            "dependencies",
-            "graphs"
-          ]
-        },
-        {
-          "type": "object",
-          "properties": {
-            "node_version": {
-              "anyOf": [
-                {
-                  "type": "string",
-                  "enum": [
-                    "20"
-                  ]
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Node.js version as a major version (e.g. '20'), if your deployment needs Node.\nMust be >= 20 if provided.\n"
-            },
-            "auth": {
-              "anyOf": [
-                {
-                  "$ref": "#/$defs/AuthConfig"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Custom authentication config, including the path to your Python auth logic and\nthe OpenAPI security definitions it uses.\n"
-            },
-            "dependencies": {
-              "type": "array",
-              "items": {
-                "type": "string"
-              },
-              "description": "List of Python dependencies to install, either from PyPI or local paths.\n"
-            },
-            "dockerfile_lines": {
-              "type": "array",
-              "items": {
-                "type": "string"
-              },
-              "description": "Optional. Additional Docker instructions that will be appended to your base Dockerfile.\n\nUseful for installing OS packages, setting environment variables, etc."
-            },
-            "env": {
-              "anyOf": [
-                {
-                  "type": "object",
-                  "additionalProperties": {
-                    "type": "string"
-                  }
-                },
-                {
-                  "type": "string"
-                }
-              ],
-              "description": "Optional. Environment variables to set for your deployment.\n\n- If given as a dict, keys are variable names and values are their values.\n- If given as a string, it must be a path to a file containing lines in KEY=VALUE format.\n\nenv=\".env\n"
-            },
-            "graphs": {
-              "type": "object",
-              "additionalProperties": {
-                "type": "string"
-              },
-              "description": "Optional. Named definitions of graphs, each pointing to a Python object.\n\n\nGraphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context\nmanagers that accept a single configuration argument (of type RunnableConfig) and return a pregel object\n(instance of Stategraph, etc.).\n"
-            },
-            "http": {
-              "anyOf": [
-                {
-                  "$ref": "#/$defs/HttpConfig"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed\nand how cross-origin requests are handled.\n"
-            },
-            "store": {
-              "anyOf": [
-                {
-                  "$ref": "#/$defs/StoreConfig"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Configuration for the built-in long-term memory store, including semantic search indexing.\n\nIf omitted, no vector index is set up (the object store will still be present, however).\n"
-            },
-            "ui": {
-              "anyOf": [
-                {
-                  "type": "object",
-                  "additionalProperties": {
-                    "type": "string"
-                  }
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Named definitions of UI components emitted by the agent, each pointing to a JS/TS file.\n"
-            }
-          },
-          "required": [
-            "node_version",
-            "graphs"
-          ]
-        }
-      ]
-    },
-    "AuthConfig": {
-      "title": "AuthConfig",
-      "description": "Configuration for custom authentication logic and how it integrates into the OpenAPI spec.",
-      "type": "object",
-      "properties": {
-        "disable_studio_auth": {
-          "type": "boolean",
-          "description": "Optional. Whether to disable LangSmith API-key authentication for requests originating the Studio.\n\nDefaults to False, meaning that if a particular header is set, the server will verify the `x-api-key` header\nvalue is a valid API key for the deployment's workspace. If True, all requests will go through your custom\nauthentication logic, regardless of origin of the request.\n"
-        },
-        "openapi": {
-          "$ref": "#/$defs/SecurityConfig",
-          "description": "Required. Detailed security configuration that merges into your deployment's OpenAPI spec.\n\n{\n}\n}\n}\n},\n]\n}\n"
-        },
-        "path": {
-          "type": "string",
-          "description": "Required. Path to an instance of the Auth() class that implements custom authentication.\n"
-        }
-      },
-      "required": []
-    },
-    "SecurityConfig": {
-      "title": "SecurityConfig",
-      "description": "Configuration for OpenAPI security definitions and requirements.\n\nUseful for specifying global or path-level authentication and authorization flows\n(e.g., OAuth2, API key headers, etc.).",
-      "type": "object",
-      "properties": {
-        "paths": {
-          "type": "object",
-          "additionalProperties": {
-            "type": "object",
-            "additionalProperties": {
-              "type": "array",
-              "items": {
-                "type": "object",
-                "additionalProperties": {
-                  "type": "array",
-                  "items": {
-                    "type": "string"
-                  }
-                }
-              }
-            }
-          },
-          "description": "Optional. Path-specific security overrides.\n\n- Keys that are HTTP methods (e.g., \"GET\", \"POST\"),\n- Values are lists of security definitions (just like `security`) for that method.\n"
-        },
-        "security": {
-          "type": "array",
-          "items": {
-            "type": "object",
-            "additionalProperties": {
-              "type": "array",
-              "items": {
-                "type": "string"
-              }
-            }
-          },
-          "description": "Optional. Global security requirements across all endpoints.\n\nEach element in the list maps a security scheme (e.g. \"OAuth2\") to a list of scopes (e.g. [\"read\", \"write\"])."
-        },
-        "securitySchemes": {
-          "type": "object",
-          "additionalProperties": {
-            "type": "object"
-          },
-          "description": "Required. Dict describing each security scheme recognized by your OpenAPI spec.\n\nKeys are scheme names (e.g. \"OAuth2\", \"ApiKeyAuth\") and values are their definitions."
-        }
-      },
-      "required": []
-    },
-    "HttpConfig": {
-      "title": "HttpConfig",
-      "description": "Configuration for the built-in HTTP server that powers your deployment's routes and endpoints.",
-      "type": "object",
-      "properties": {
-        "app": {
-          "type": "string",
-          "description": "Optional. Import path to a custom Starlette/FastAPI application to mount.\n"
-        },
-        "cors": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/CorsConfig"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Optional. Defines CORS restrictions. If omitted, no special rules are set and\ncross-origin behavior depends on default server settings.\n"
-        },
-        "disable_assistants": {
-          "type": "boolean",
-          "description": "Optional. If True, /assistants routes are removed from the server.\n\nDefault is False (meaning /assistants is enabled).\n"
-        },
-        "disable_meta": {
-          "type": "boolean",
-          "description": "Optional. If True, all meta endpoints (/ok, /info, /metrics, /docs) are disabled.\n\nDefault is False.\n"
-        },
-        "disable_runs": {
-          "type": "boolean",
-          "description": "Optional. If True, /runs routes are removed.\n\nDefault is False.\n"
-        },
-        "disable_store": {
-          "type": "boolean",
-          "description": "Optional. If True, /store routes are removed, disabling direct store interactions via HTTP.\n\nDefault is False.\n"
-        },
-        "disable_threads": {
-          "type": "boolean",
-          "description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n"
-        }
-      },
-      "required": []
-    },
-    "CorsConfig": {
-      "title": "CorsConfig",
-      "description": "Specifies Cross-Origin Resource Sharing (CORS) rules for your server.\n\nIf omitted, defaults are typically very restrictive (often no cross-origin requests).\nConfigure carefully if you want to allow usage from browsers hosted on other domains.",
-      "type": "object",
-      "properties": {
-        "allow_credentials": {
-          "type": "boolean",
-          "description": "Optional. If True, cross-origin requests can include credentials (cookies, auth headers).\n\nDefault False to avoid accidentally exposing secured endpoints to untrusted sites.\n"
-        },
-        "allow_headers": {
-          "type": "array",
-          "items": {
-            "type": "string"
-          },
-          "description": "Optional. HTTP headers that can be used in cross-origin requests (e.g. [\"Content-Type\", \"Authorization\"])."
-        },
-        "allow_methods": {
-          "type": "array",
-          "items": {
-            "type": "string"
-          },
-          "description": "Optional. HTTP methods permitted for cross-origin requests (e.g. [\"GET\", \"POST\"]).\n\nDefault might be [\"GET\", \"POST\", \"OPTIONS\"] depending on your server framework.\n"
-        },
-        "allow_origin_regex": {
-          "type": "string",
-          "description": "Optional. A regex pattern for matching allowed origins, used if you have dynamic subdomains.\n"
-        },
-        "allow_origins": {
-          "type": "array",
-          "items": {
-            "type": "string"
-          },
-          "description": "Optional. List of allowed origins (e.g., \"https://example.com\").\n\nDefault is often an empty list (no external origins).\nUse \"*\" only if you trust all origins, as that bypasses most restrictions.\n"
-        },
-        "expose_headers": {
-          "type": "array",
-          "items": {
-            "type": "string"
-          },
-          "description": "Optional. List of headers that browsers are allowed to read from the response in cross-origin contexts."
-        },
-        "max_age": {
-          "type": "integer",
-          "description": "Optional. How many seconds the browser may cache preflight responses.\n\nDefault might be 600 (10 minutes). Larger values reduce preflight requests but can cause stale configurations.\n"
-        }
-      },
-      "required": []
-    },
-    "StoreConfig": {
-      "title": "StoreConfig",
-      "description": "Configuration for the built-in long-term memory store.\n\nThis store can optionally perform semantic search. If you omit `index`,\nthe store will just handle traditional (non-embedded) data without vector lookups.",
-      "type": "object",
-      "properties": {
-        "index": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/IndexConfig"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Optional. Defines the vector-based semantic search configuration.\n\n- Generate embeddings according to `index.embed`\n- Enforce the embedding dimension given by `index.dims`\n- Embed only specified JSON fields (if any) from `index.fields`\n\nIf omitted, no vector index is initialized.\n"
-        }
-      },
-      "required": []
-    },
-    "IndexConfig": {
-      "title": "IndexConfig",
-      "description": "Configuration for indexing documents for semantic search in the store.\n\nThis governs how text is converted into embeddings and stored for vector-based lookups.",
-      "type": "object",
-      "properties": {
-        "dims": {
-          "type": "integer",
-          "description": "Required. Dimensionality of the embedding vectors you will store.\n\nMust match the output dimension of your selected embedding model or custom embed function.\nIf mismatched, you will likely encounter shape/size errors when inserting or querying vectors.\n\n"
-        },
-        "embed": {
-          "type": "string",
-          "description": "Required. Identifier or reference to the embedding model or a custom embedding function.\n\n- \"my_custom_embed\" if it's a known alias in your system\n"
-        },
-        "fields": {
-          "anyOf": [
-            {
-              "type": "array",
-              "items": {
-                "type": "string"
-              }
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Optional. List of JSON fields to extract before generating embeddings.\n\nDefaults to [\"$\"], which means the entire JSON object is embedded as one piece of text.\nIf you provide multiple fields (e.g. [\"title\", \"content\"]), each is extracted and embedded separately,\noften saving token usage if you only care about certain parts of the data.\n"
-        }
-      },
-      "required": []
-    }
-  },
-  "title": "LangGraph CLI Configuration",
-  "description": "Configuration schema for langgraph-cli",
-  "version": "v0"
-}
@@ -1,438 +0,0 @@
-{
-  "$ref": "#/$defs/Config",
-  "$defs": {
-    "Config": {
-      "title": "Config",
-      "description": "Top-level config for langgraph-cli or similar deployment tooling.",
-      "type": "object",
-      "required": [],
-      "oneOf": [
-        {
-          "type": "object",
-          "properties": {
-            "python_version": {
-              "type": "string",
-              "description": "Optional. Python version in 'major.minor' format (e.g. '3.11').\nMust be at least 3.11 or greater for this deployment to function properly.\n",
-              "enum": [
-                "3.11",
-                "3.12"
-              ]
-            },
-            "pip_config_file": {
-              "anyOf": [
-                {
-                  "type": "string"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Path to a pip config file (e.g., \"/etc/pip.conf\" or \"pip.ini\") for controlling\npackage installation (custom indices, credentials, etc.).\n\nOnly relevant if Python dependencies are installed via pip. If omitted, default pip settings are used.\n"
-            },
-            "auth": {
-              "anyOf": [
-                {
-                  "$ref": "#/$defs/AuthConfig"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Custom authentication config, including the path to your Python auth logic and\nthe OpenAPI security definitions it uses.\n"
-            },
-            "dependencies": {
-              "type": "array",
-              "items": {
-                "type": "string"
-              },
-              "description": "List of Python dependencies to install, either from PyPI or local paths.\n"
-            },
-            "dockerfile_lines": {
-              "type": "array",
-              "items": {
-                "type": "string"
-              },
-              "description": "Optional. Additional Docker instructions that will be appended to your base Dockerfile.\n\nUseful for installing OS packages, setting environment variables, etc."
-            },
-            "env": {
-              "anyOf": [
-                {
-                  "type": "object",
-                  "additionalProperties": {
-                    "type": "string"
-                  }
-                },
-                {
-                  "type": "string"
-                }
-              ],
-              "description": "Optional. Environment variables to set for your deployment.\n\n- If given as a dict, keys are variable names and values are their values.\n- If given as a string, it must be a path to a file containing lines in KEY=VALUE format.\n\nenv=\".env\n"
-            },
-            "graphs": {
-              "type": "object",
-              "additionalProperties": {
-                "type": "string"
-              },
-              "description": "Optional. Named definitions of graphs, each pointing to a Python object.\n\n\nGraphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context\nmanagers that accept a single configuration argument (of type RunnableConfig) and return a pregel object\n(instance of Stategraph, etc.).\n"
-            },
-            "http": {
-              "anyOf": [
-                {
-                  "$ref": "#/$defs/HttpConfig"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed\nand how cross-origin requests are handled.\n"
-            },
-            "store": {
-              "anyOf": [
-                {
-                  "$ref": "#/$defs/StoreConfig"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Configuration for the built-in long-term memory store, including semantic search indexing.\n\nIf omitted, no vector index is set up (the object store will still be present, however).\n"
-            },
-            "ui": {
-              "anyOf": [
-                {
-                  "type": "object",
-                  "additionalProperties": {
-                    "type": "string"
-                  }
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Named definitions of UI components emitted by the agent, each pointing to a JS/TS file.\n"
-            }
-          },
-          "required": [
-            "dependencies",
-            "graphs"
-          ]
-        },
-        {
-          "type": "object",
-          "properties": {
-            "node_version": {
-              "anyOf": [
-                {
-                  "type": "string",
-                  "enum": [
-                    "20"
-                  ]
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Node.js version as a major version (e.g. '20'), if your deployment needs Node.\nMust be >= 20 if provided.\n"
-            },
-            "auth": {
-              "anyOf": [
-                {
-                  "$ref": "#/$defs/AuthConfig"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Custom authentication config, including the path to your Python auth logic and\nthe OpenAPI security definitions it uses.\n"
-            },
-            "dependencies": {
-              "type": "array",
-              "items": {
-                "type": "string"
-              },
-              "description": "List of Python dependencies to install, either from PyPI or local paths.\n"
-            },
-            "dockerfile_lines": {
-              "type": "array",
-              "items": {
-                "type": "string"
-              },
-              "description": "Optional. Additional Docker instructions that will be appended to your base Dockerfile.\n\nUseful for installing OS packages, setting environment variables, etc."
-            },
-            "env": {
-              "anyOf": [
-                {
-                  "type": "object",
-                  "additionalProperties": {
-                    "type": "string"
-                  }
-                },
-                {
-                  "type": "string"
-                }
-              ],
-              "description": "Optional. Environment variables to set for your deployment.\n\n- If given as a dict, keys are variable names and values are their values.\n- If given as a string, it must be a path to a file containing lines in KEY=VALUE format.\n\nenv=\".env\n"
-            },
-            "graphs": {
-              "type": "object",
-              "additionalProperties": {
-                "type": "string"
-              },
-              "description": "Optional. Named definitions of graphs, each pointing to a Python object.\n\n\nGraphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context\nmanagers that accept a single configuration argument (of type RunnableConfig) and return a pregel object\n(instance of Stategraph, etc.).\n"
-            },
-            "http": {
-              "anyOf": [
-                {
-                  "$ref": "#/$defs/HttpConfig"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed\nand how cross-origin requests are handled.\n"
-            },
-            "store": {
-              "anyOf": [
-                {
-                  "$ref": "#/$defs/StoreConfig"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Configuration for the built-in long-term memory store, including semantic search indexing.\n\nIf omitted, no vector index is set up (the object store will still be present, however).\n"
-            },
-            "ui": {
-              "anyOf": [
-                {
-                  "type": "object",
-                  "additionalProperties": {
-                    "type": "string"
-                  }
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Named definitions of UI components emitted by the agent, each pointing to a JS/TS file.\n"
-            }
-          },
-          "required": [
-            "node_version",
-            "graphs"
-          ]
-        }
-      ]
-    },
-    "AuthConfig": {
-      "title": "AuthConfig",
-      "description": "Configuration for custom authentication logic and how it integrates into the OpenAPI spec.",
-      "type": "object",
-      "properties": {
-        "disable_studio_auth": {
-          "type": "boolean",
-          "description": "Optional. Whether to disable LangSmith API-key authentication for requests originating the Studio.\n\nDefaults to False, meaning that if a particular header is set, the server will verify the `x-api-key` header\nvalue is a valid API key for the deployment's workspace. If True, all requests will go through your custom\nauthentication logic, regardless of origin of the request.\n"
-        },
-        "openapi": {
-          "$ref": "#/$defs/SecurityConfig",
-          "description": "Required. Detailed security configuration that merges into your deployment's OpenAPI spec.\n\n{\n}\n}\n}\n},\n]\n}\n"
-        },
-        "path": {
-          "type": "string",
-          "description": "Required. Path to an instance of the Auth() class that implements custom authentication.\n"
-        }
-      },
-      "required": []
-    },
-    "SecurityConfig": {
-      "title": "SecurityConfig",
-      "description": "Configuration for OpenAPI security definitions and requirements.\n\nUseful for specifying global or path-level authentication and authorization flows\n(e.g., OAuth2, API key headers, etc.).",
-      "type": "object",
-      "properties": {
-        "paths": {
-          "type": "object",
-          "additionalProperties": {
-            "type": "object",
-            "additionalProperties": {
-              "type": "array",
-              "items": {
-                "type": "object",
-                "additionalProperties": {
-                  "type": "array",
-                  "items": {
-                    "type": "string"
-                  }
-                }
-              }
-            }
-          },
-          "description": "Optional. Path-specific security overrides.\n\n- Keys that are HTTP methods (e.g., \"GET\", \"POST\"),\n- Values are lists of security definitions (just like `security`) for that method.\n"
-        },
-        "security": {
-          "type": "array",
-          "items": {
-            "type": "object",
-            "additionalProperties": {
-              "type": "array",
-              "items": {
-                "type": "string"
-              }
-            }
-          },
-          "description": "Optional. Global security requirements across all endpoints.\n\nEach element in the list maps a security scheme (e.g. \"OAuth2\") to a list of scopes (e.g. [\"read\", \"write\"])."
-        },
-        "securitySchemes": {
-          "type": "object",
-          "additionalProperties": {
-            "type": "object"
-          },
-          "description": "Required. Dict describing each security scheme recognized by your OpenAPI spec.\n\nKeys are scheme names (e.g. \"OAuth2\", \"ApiKeyAuth\") and values are their definitions."
-        }
-      },
-      "required": []
-    },
-    "HttpConfig": {
-      "title": "HttpConfig",
-      "description": "Configuration for the built-in HTTP server that powers your deployment's routes and endpoints.",
-      "type": "object",
-      "properties": {
-        "app": {
-          "type": "string",
-          "description": "Optional. Import path to a custom Starlette/FastAPI application to mount.\n"
-        },
-        "cors": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/CorsConfig"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Optional. Defines CORS restrictions. If omitted, no special rules are set and\ncross-origin behavior depends on default server settings.\n"
-        },
-        "disable_assistants": {
-          "type": "boolean",
-          "description": "Optional. If True, /assistants routes are removed from the server.\n\nDefault is False (meaning /assistants is enabled).\n"
-        },
-        "disable_meta": {
-          "type": "boolean",
-          "description": "Optional. If True, all meta endpoints (/ok, /info, /metrics, /docs) are disabled.\n\nDefault is False.\n"
-        },
-        "disable_runs": {
-          "type": "boolean",
-          "description": "Optional. If True, /runs routes are removed.\n\nDefault is False.\n"
-        },
-        "disable_store": {
-          "type": "boolean",
-          "description": "Optional. If True, /store routes are removed, disabling direct store interactions via HTTP.\n\nDefault is False.\n"
-        },
-        "disable_threads": {
-          "type": "boolean",
-          "description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n"
-        }
-      },
-      "required": []
-    },
-    "CorsConfig": {
-      "title": "CorsConfig",
-      "description": "Specifies Cross-Origin Resource Sharing (CORS) rules for your server.\n\nIf omitted, defaults are typically very restrictive (often no cross-origin requests).\nConfigure carefully if you want to allow usage from browsers hosted on other domains.",
-      "type": "object",
-      "properties": {
-        "allow_credentials": {
-          "type": "boolean",
-          "description": "Optional. If True, cross-origin requests can include credentials (cookies, auth headers).\n\nDefault False to avoid accidentally exposing secured endpoints to untrusted sites.\n"
-        },
-        "allow_headers": {
-          "type": "array",
-          "items": {
-            "type": "string"
-          },
-          "description": "Optional. HTTP headers that can be used in cross-origin requests (e.g. [\"Content-Type\", \"Authorization\"])."
-        },
-        "allow_methods": {
-          "type": "array",
-          "items": {
-            "type": "string"
-          },
-          "description": "Optional. HTTP methods permitted for cross-origin requests (e.g. [\"GET\", \"POST\"]).\n\nDefault might be [\"GET\", \"POST\", \"OPTIONS\"] depending on your server framework.\n"
-        },
-        "allow_origin_regex": {
-          "type": "string",
-          "description": "Optional. A regex pattern for matching allowed origins, used if you have dynamic subdomains.\n"
-        },
-        "allow_origins": {
-          "type": "array",
-          "items": {
-            "type": "string"
-          },
-          "description": "Optional. List of allowed origins (e.g., \"https://example.com\").\n\nDefault is often an empty list (no external origins).\nUse \"*\" only if you trust all origins, as that bypasses most restrictions.\n"
-        },
-        "expose_headers": {
-          "type": "array",
-          "items": {
-            "type": "string"
-          },
-          "description": "Optional. List of headers that browsers are allowed to read from the response in cross-origin contexts."
-        },
-        "max_age": {
-          "type": "integer",
-          "description": "Optional. How many seconds the browser may cache preflight responses.\n\nDefault might be 600 (10 minutes). Larger values reduce preflight requests but can cause stale configurations.\n"
-        }
-      },
-      "required": []
-    },
-    "StoreConfig": {
-      "title": "StoreConfig",
-      "description": "Configuration for the built-in long-term memory store.\n\nThis store can optionally perform semantic search. If you omit `index`,\nthe store will just handle traditional (non-embedded) data without vector lookups.",
-      "type": "object",
-      "properties": {
-        "index": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/IndexConfig"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Optional. Defines the vector-based semantic search configuration.\n\n- Generate embeddings according to `index.embed`\n- Enforce the embedding dimension given by `index.dims`\n- Embed only specified JSON fields (if any) from `index.fields`\n\nIf omitted, no vector index is initialized.\n"
-        }
-      },
-      "required": []
-    },
-    "IndexConfig": {
-      "title": "IndexConfig",
-      "description": "Configuration for indexing documents for semantic search in the store.\n\nThis governs how text is converted into embeddings and stored for vector-based lookups.",
-      "type": "object",
-      "properties": {
-        "dims": {
-          "type": "integer",
-          "description": "Required. Dimensionality of the embedding vectors you will store.\n\nMust match the output dimension of your selected embedding model or custom embed function.\nIf mismatched, you will likely encounter shape/size errors when inserting or querying vectors.\n\n"
-        },
-        "embed": {
-          "type": "string",
-          "description": "Required. Identifier or reference to the embedding model or a custom embedding function.\n\n- \"my_custom_embed\" if it's a known alias in your system\n"
-        },
-        "fields": {
-          "anyOf": [
-            {
-              "type": "array",
-              "items": {
-                "type": "string"
-              }
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Optional. List of JSON fields to extract before generating embeddings.\n\nDefaults to [\"$\"], which means the entire JSON object is embedded as one piece of text.\nIf you provide multiple fields (e.g. [\"title\", \"content\"]), each is extracted and embedded separately,\noften saving token usage if you only care about certain parts of the data.\n"
-        }
-      },
-      "required": []
-    }
-  },
-  "title": "LangGraph CLI Configuration",
-  "description": "Configuration schema for langgraph-cli",
-  "version": "v0"
-}
@@ -33,7 +33,6 @@ def test_validate_config():
        "store": None,
        "auth": None,
        "http": None,
-        "ui": None,
        **expected_config,
    }
    actual_config = validate_config(expected_config)
@@ -53,7 +52,6 @@ def test_validate_config():
        "store": None,
        "auth": None,
        "http": None,
-        "ui": None,
    }
    actual_config = validate_config(expected_config)
    assert actual_config == expected_config
@@ -469,7 +467,6 @@ def test_config_to_docker_nodejs():
                "node_version": "20",
                "graphs": graphs,
                "dockerfile_lines": ["ARG meow", "ARG foo"],
-                "ui": {"agent": "./graphs/agent.ui.jsx"},
            }
        ),
        "langchain/langgraphjs-api",
@@ -480,7 +477,6 @@ ARG foo
 ADD . /deps/unit_tests
 RUN cd /deps/unit_tests && npm i
 ENV LANGSERVE_GRAPHS='{"agent": "./graphs/agent.js:graph"}'
-ENV LANGGRAPH_UI='{"agent": "./graphs/agent.ui.jsx"}'
 WORKDIR /deps/unit_tests
 RUN (test ! -f /api/langgraph_api/js/build.mts && echo "Prebuild script not found, skipping") || tsx /api/langgraph_api/js/build.mts"""

@@ -36,31 +36,23 @@ from langgraph.types import _DC_KWARGS, RetryPolicy, StreamMode

@overload
 def task(
-    *,
-    name: Optional[str] = None,
-    retry: Optional[RetryPolicy] = None,
-) -> Callable[
-    [Union[Callable[P, Awaitable[T]], Callable[P, T]]],
-    Callable[P, SyncAsyncFuture[T]],
-]: ...
+    *, name: Optional[str] = None, retry: Optional[RetryPolicy] = None
+) -> Callable[[Callable[P, T]], Callable[P, SyncAsyncFuture[T]]]: ...


@overload
 def task(
-    __func_or_none__: Union[Callable[P, Awaitable[T]], Callable[P, T]],
+    __func_or_none__: Callable[P, T],
 ) -> Callable[P, SyncAsyncFuture[T]]: ...


 def task(
-    __func_or_none__: Optional[Union[Callable[P, Awaitable[T]], Callable[P, T]]] = None,
+    __func_or_none__: Optional[Union[Callable[P, T], Callable[P, Awaitable[T]]]] = None,
    *,
    name: Optional[str] = None,
    retry: Optional[RetryPolicy] = None,
 ) -> Union[
-    Callable[
-        [Union[Callable[P, Awaitable[T]], Callable[P, T]]],
-        Callable[P, SyncAsyncFuture[T]],
-    ],
+    Callable[[Callable[P, T]], Callable[P, SyncAsyncFuture[T]]],
    Callable[P, SyncAsyncFuture[T]],
 ]:
    """Define a LangGraph task using the `task` decorator.
@@ -353,7 +345,7 @@ class entrypoint:
        value: R
        """Value to return. A value will always be returned even if it is None."""
        save: S
-        """The value for the state for the next checkpoint.
+        """The value for the state for the next checkpoint. 

        A value will always be saved even if it is None.
        """
@@ -1,6 +1,7 @@
 """langgraph.prebuilt exposes a higher-level API for creating and executing agents and tools."""

 from langgraph.prebuilt.chat_agent_executor import create_react_agent
+from langgraph.prebuilt.tool_executor import ToolExecutor, ToolInvocation
 from langgraph.prebuilt.tool_node import (
    InjectedState,
    InjectedStore,
@@ -11,6 +12,8 @@ from langgraph.prebuilt.tool_validator import ValidationNode

 __all__ = [
    "create_react_agent",
+    "ToolExecutor",
+    "ToolInvocation",
    "ToolNode",
    "tools_condition",
    "ValidationNode",
@@ -22,7 +22,6 @@ from langchain_core.runnables import (
    Runnable,
    RunnableBinding,
    RunnableConfig,
-    RunnableSequence,
 )
 from langchain_core.tools import BaseTool
 from pydantic import BaseModel
@@ -33,6 +32,7 @@ from langgraph.graph import END, StateGraph
 from langgraph.graph.graph import CompiledGraph
 from langgraph.graph.message import add_messages
 from langgraph.managed import IsLastStep, RemainingSteps
+from langgraph.prebuilt.tool_executor import ToolExecutor
 from langgraph.prebuilt.tool_node import ToolNode
 from langgraph.store.base import BaseStore
 from langgraph.types import Checkpointer, Send
@@ -68,6 +68,13 @@ StateSchemaType = Type[StateSchema]

 PROMPT_RUNNABLE_NAME = "Prompt"

+MessagesModifier = Union[
+    SystemMessage,
+    str,
+    Callable[[Sequence[BaseMessage]], LanguageModelInput],
+    Runnable[Sequence[BaseMessage], LanguageModelInput],
+]
+
 Prompt = Union[
    SystemMessage,
    str,
@@ -112,20 +119,43 @@ def _get_prompt_runnable(prompt: Optional[Prompt]) -> Runnable:
    return prompt_runnable


+def _convert_messages_modifier_to_prompt(
+    messages_modifier: MessagesModifier,
+) -> Prompt:
+    prompt: Prompt
+    if isinstance(messages_modifier, (str, SystemMessage)):
+        return messages_modifier
+    elif callable(messages_modifier):
+
+        def prompt(state: AgentState) -> Sequence[BaseMessage]:
+            return messages_modifier(state["messages"])
+
+        return prompt
+    elif isinstance(messages_modifier, Runnable):
+        prompt = (lambda state: state["messages"]) | messages_modifier
+        return prompt
+    raise ValueError(
+        f"Got unexpected type for `messages_modifier`: {type(messages_modifier)}"
+    )
+
+
 def _convert_modifier_to_prompt(func: F) -> F:
-    """Decorator that converts state_modifier kwarg to prompt kwarg."""
+    """Decorator that converts state_modifier/messages_modifier kwargs to prompt kwarg."""

    @functools.wraps(func)
    def wrapper(*args: Any, **kwargs: Any) -> Any:
        prompt = kwargs.get("prompt")
        state_modifier = kwargs.pop("state_modifier", None)
-        if sum(p is not None for p in (prompt, state_modifier)) > 1:
+        messages_modifier = kwargs.pop("messages_modifier", None)
+        if sum(p is not None for p in (prompt, state_modifier, messages_modifier)) > 1:
            raise ValueError(
-                "Expected only one of (prompt, state_modifier), got multiple values"
+                "Expected only one of prompt, state_modifier, or messages_modifier, got multiple values"
            )

        if state_modifier is not None:
            prompt = state_modifier
+        elif messages_modifier is not None:
+            prompt = _convert_messages_modifier_to_prompt(messages_modifier)

        kwargs["prompt"] = prompt
        return func(*args, **kwargs)
@@ -134,16 +164,6 @@ def _convert_modifier_to_prompt(func: F) -> F:


 def _should_bind_tools(model: LanguageModelLike, tools: Sequence[BaseTool]) -> bool:
-    if isinstance(model, RunnableSequence):
-        model = next(
-            (
-                step
-                for step in model.steps
-                if isinstance(step, (RunnableBinding, BaseChatModel))
-            ),
-            model,
-        )
-
    if not isinstance(model, RunnableBinding):
        return True

@@ -179,16 +199,6 @@ def _should_bind_tools(model: LanguageModelLike, tools: Sequence[BaseTool]) -> b

 def _get_model(model: LanguageModelLike) -> BaseChatModel:
    """Get the underlying model from a RunnableBinding or return the model itself."""
-    if isinstance(model, RunnableSequence):
-        model = next(
-            (
-                step
-                for step in model.steps
-                if isinstance(step, (RunnableBinding, BaseChatModel))
-            ),
-            model,
-        )
-
    if isinstance(model, RunnableBinding):
        model = model.bound

@@ -234,7 +244,7 @@ def _validate_chat_history(
@_convert_modifier_to_prompt
 def create_react_agent(
    model: Union[str, LanguageModelLike],
-    tools: Union[Sequence[BaseTool], ToolNode],
+    tools: Union[ToolExecutor, Sequence[BaseTool], ToolNode],
    *,
    prompt: Optional[Prompt] = None,
    response_format: Optional[
@@ -254,7 +264,7 @@ def create_react_agent(

    Args:
        model: The `LangChain` chat model that supports tool calling.
-        tools: A list of tools or a ToolNode instance.
+        tools: A list of tools, a ToolExecutor, or a ToolNode instance.
            If an empty list is provided, the agent will consist of a single LLM node without tool calling.
        prompt: An optional prompt for the LLM. Can take a few different forms:

@@ -263,6 +273,8 @@ def create_react_agent(
            - Callable: This function should take in full graph state and the output is then passed to the language model.
            - Runnable: This runnable should take in full graph state and the output is then passed to the language model.

+            !!! Note
+                Prior to `v0.2.68`, the prompt was set using `state_modifier` / `messages_modifier` parameters.
        response_format: An optional schema for the final agent output.

            If provided, output will be formatted to match the given schema and returned in the 'structured_response' state key.
@@ -605,7 +617,10 @@ def create_react_agent(
            else AgentState
        )

-    if isinstance(tools, ToolNode):
+    if isinstance(tools, ToolExecutor):
+        tool_classes: Sequence[BaseTool] = tools.tools
+        tool_node = ToolNode(tool_classes)
+    elif isinstance(tools, ToolNode):
        tool_classes = list(tools.tools_by_name.values())
        tool_node = tools
    else:
@@ -0,0 +1,134 @@
+from typing import Any, Callable, Sequence, Union
+
+from langchain_core.load.serializable import Serializable
+from langchain_core.runnables import RunnableConfig
+from langchain_core.tools import BaseTool
+from langchain_core.tools import tool as create_tool
+
+from langgraph._api.deprecation import deprecated
+from langgraph.utils.runnable import RunnableCallable
+
+INVALID_TOOL_MSG_TEMPLATE = (
+    "{requested_tool_name} is not a valid tool, "
+    "try one of [{available_tool_names_str}]."
+)
+
+
+@deprecated("0.2.0", "langgraph.prebuilt.ToolNode", removal="0.3.0")
+class ToolInvocationInterface:
+    """Interface for invoking a tool.
+
+    Attributes:
+        tool (str): The name of the tool to invoke.
+        tool_input (Union[str, dict]): The input to pass to the tool.
+
+    """
+
+    tool: str
+    tool_input: Union[str, dict]
+
+
+@deprecated("0.2.0", "langgraph.prebuilt.ToolNode", removal="0.3.0")
+class ToolInvocation(Serializable):
+    """Information about how to invoke a tool.
+
+    Attributes:
+        tool (str): The name of the Tool to execute.
+        tool_input (Union[str, dict]): The input to pass in to the Tool.
+
+    Examples:
+        Basic usage:
+        ```pycon
+        >>> invocation = ToolInvocation(
+        ...    tool="search",
+        ...     tool_input="What is the capital of France?"
+        ... )
+        ```
+    """
+
+    tool: str
+    tool_input: Union[str, dict]
+
+
+@deprecated("0.2.0", "langgraph.prebuilt.ToolNode", removal="0.3.0")
+class ToolExecutor(RunnableCallable):
+    """Executes a tool invocation.
+
+    Args:
+        tools (Sequence[BaseTool]): A sequence of tools that can be invoked.
+        invalid_tool_msg_template (str, optional): The template for the error message
+            when an invalid tool is requested. Defaults to INVALID_TOOL_MSG_TEMPLATE.
+
+    Examples:
+        Basic usage:
+
+        ```pycon
+        >>> from langchain_core.tools import tool
+        >>> from langgraph.prebuilt.tool_executor import ToolExecutor, ToolInvocation
+        ...
+        ...
+        >>> @tool
+        ... def search(query: str) -> str:
+        ...     \"\"\"Search engine.\"\"\"
+        ...     return f"Searching for: {query}"
+        ...
+        ...
+        >>> tools = [search]
+        >>> executor = ToolExecutor(tools)
+        ...
+        >>> invocation = ToolInvocation(tool="search", tool_input="What is the capital of France?")
+        >>> result = executor.invoke(invocation)
+        >>> print(result)
+        "Searching for: What is the capital of France?"
+        ```
+        Handling invalid tool:
+
+        ```pycon
+        >>> invocation = ToolInvocation(
+        ...     tool="nonexistent", tool_input="What is the capital of France?"
+        ... )
+        >>> result = executor.invoke(invocation)
+        >>> print(result)
+        "nonexistent is not a valid tool, try one of [search]."
+        ```
+    """
+
+    def __init__(
+        self,
+        tools: Sequence[Union[BaseTool, Callable]],
+        *,
+        invalid_tool_msg_template: str = INVALID_TOOL_MSG_TEMPLATE,
+    ) -> None:
+        super().__init__(self._execute, afunc=self._aexecute, trace=False)
+        tools_ = [
+            tool if isinstance(tool, BaseTool) else create_tool(tool) for tool in tools
+        ]
+        self.tools = tools_
+        self.tool_map = {t.name: t for t in tools_}
+        self.invalid_tool_msg_template = invalid_tool_msg_template
+
+    def _execute(
+        self, tool_invocation: ToolInvocationInterface, config: RunnableConfig
+    ) -> Any:
+        if tool_invocation.tool not in self.tool_map:
+            return self.invalid_tool_msg_template.format(
+                requested_tool_name=tool_invocation.tool,
+                available_tool_names_str=", ".join([t.name for t in self.tools]),
+            )
+        else:
+            tool = self.tool_map[tool_invocation.tool]
+            output = tool.invoke(tool_invocation.tool_input, config)
+            return output
+
+    async def _aexecute(
+        self, tool_invocation: ToolInvocationInterface, config: RunnableConfig
+    ) -> Any:
+        if tool_invocation.tool not in self.tool_map:
+            return self.invalid_tool_msg_template.format(
+                requested_tool_name=tool_invocation.tool,
+                available_tool_names_str=", ".join([t.name for t in self.tools]),
+            )
+        else:
+            tool = self.tool_map[tool_invocation.tool]
+            output = await tool.ainvoke(tool_invocation.tool_input, config)
+            return output
@@ -29,7 +29,6 @@ from langchain_core.runnables import (
 )
 from langchain_core.runnables.config import get_executor_for_config
 from langchain_core.tools import BaseTool, create_schema_from_function
-from langchain_core.utils.pydantic import is_basemodel_subclass
 from pydantic import BaseModel, ValidationError
 from pydantic.v1 import BaseModel as BaseModelV1
 from pydantic.v1 import ValidationError as ValidationErrorV1
@@ -79,7 +78,7 @@ class ValidationNode(RunnableCallable):
        >>> from typing_extensions import TypedDict
        ...
        >>> from langchain_anthropic import ChatAnthropic
-        >>> from pydantic import BaseModel, field_validator
+        >>> from pydantic import BaseModel, validator
        ...
        >>> from langgraph.graph import END, START, StateGraph
        >>> from langgraph.prebuilt import ValidationNode
@@ -89,15 +88,18 @@ class ValidationNode(RunnableCallable):
        >>> class SelectNumber(BaseModel):
        ...     a: int
        ...
-        ...     @field_validator("a")
+        ...     @validator("a")
        ...     def a_must_be_meaningful(cls, v):
        ...         if v != 37:
        ...             raise ValueError("Only 37 is allowed")
        ...         return v
        ...
        ...
-        >>> builder = StateGraph(Annotated[list, add_messages])
-        >>> llm = ChatAnthropic(model="claude-3-5-haiku-latest").bind_tools([SelectNumber])
+        >>> class State(TypedDict):
+        ...     messages: Annotated[list, add_messages]
+        ...
+        >>> builder = StateGraph(State)
+        >>> llm = ChatAnthropic(model="claude-3-haiku-20240307").bind_tools([SelectNumber])
        >>> builder.add_node("model", llm)
        >>> builder.add_node("validation", ValidationNode([SelectNumber]))
        >>> builder.add_edge(START, "model")
@@ -175,13 +177,6 @@ class ValidationNode(RunnableCallable):
                    raise ValueError(
                        f"Tool {schema.name} does not have an args_schema defined."
                    )
-                elif not isinstance(
-                    schema.args_schema, type
-                ) or not is_basemodel_subclass(schema.args_schema):
-                    raise ValueError(
-                        "Validation node only works with tools that have a pydantic BaseModel args_schema. "
-                        f"Got {schema.name} with args_schema: {schema.args_schema}."
-                    )
                self.schemas_by_name[schema.name] = schema.args_schema
            elif isinstance(schema, type) and issubclass(
                schema, (BaseModel, BaseModelV1)
@@ -18,7 +18,6 @@ from typing import (
    Type,
    Union,
    cast,
-    get_type_hints,
    overload,
 )
 from uuid import UUID, uuid5
@@ -120,7 +119,7 @@ from langgraph.utils.config import (
    recast_checkpoint_ns,
 )
 from langgraph.utils.fields import get_enhanced_type_hints
-from langgraph.utils.pydantic import create_model, is_supported_by_pydantic
+from langgraph.utils.pydantic import create_model
 from langgraph.utils.queue import AsyncQueue, SyncQueue  # type: ignore[attr-defined]

 WriteValue = Union[Callable[[Input], Output], Any]
@@ -610,36 +609,6 @@ class Pregel(PregelProtocol):
            ]
        ]

-    def config_schema(
-        self, *, include: Optional[Sequence[str]] = None
-    ) -> Type[BaseModel]:
-        # If the config type is not set explicitly, we will try to infer it.
-        # If the config type is provided, but isn't directly supported by pydantic
-        # (e.g., vanilla python class), we will also delegate to the parent class,
-        # which handles cases where Pydantic doesn't support the type.
-        if self.config_type is None or not is_supported_by_pydantic(self.config_type):
-            return super().config_schema(include=include)
-
-        include = include or []
-        fields = {
-            "configurable": (self.config_type, None),
-            **{
-                field_name: (field_type, None)
-                for field_name, field_type in get_type_hints(RunnableConfig).items()
-                if field_name in [i for i in include if i != "configurable"]
-            },
-        }
-        return create_model(self.get_name("Config"), field_definitions=fields)
-
-    def get_config_jsonschema(
-        self, *, include: Optional[Sequence[str]] = None
-    ) -> Dict[str, Any]:
-        schema = self.config_schema(include=include)
-        if hasattr(schema, "model_json_schema"):
-            return schema.model_json_schema()
-        else:
-            return schema.schema()
-
    @property
    def InputType(self) -> Any:
        if isinstance(self.input_channels, str):
@@ -665,7 +634,7 @@ class Pregel(PregelProtocol):

    def get_input_jsonschema(
        self, config: Optional[RunnableConfig] = None
-    ) -> Dict[str, Any]:
+    ) -> Dict[All, Any]:
        schema = self.get_input_schema(config)
        if hasattr(schema, "model_json_schema"):
            return schema.model_json_schema()
@@ -697,7 +666,7 @@ class Pregel(PregelProtocol):

    def get_output_jsonschema(
        self, config: Optional[RunnableConfig] = None
-    ) -> Dict[str, Any]:
+    ) -> Dict[All, Any]:
        schema = self.get_output_schema(config)
        if hasattr(schema, "model_json_schema"):
            return schema.model_json_schema()
@@ -1002,12 +971,6 @@ class Pregel(PregelProtocol):
                raise ValueError(f"Subgraph {recast} not found")

        config = merge_configs(self.config, config) if self.config else config
-        if self.checkpointer is True:
-            ns = cast(str, config[CONF][CONFIG_KEY_CHECKPOINT_NS])
-            config = merge_configs(
-                config, {CONF: {CONFIG_KEY_CHECKPOINT_NS: recast_checkpoint_ns(ns)}}
-            )
-
        saved = checkpointer.get_tuple(config)
        return self._prepare_state_snapshot(
            config,
@@ -1041,12 +1004,6 @@ class Pregel(PregelProtocol):
                raise ValueError(f"Subgraph {recast} not found")

        config = merge_configs(self.config, config) if self.config else config
-        if self.checkpointer is True:
-            ns = cast(str, config[CONF][CONFIG_KEY_CHECKPOINT_NS])
-            config = merge_configs(
-                config, {CONF: {CONFIG_KEY_CHECKPOINT_NS: recast_checkpoint_ns(ns)}}
-            )
-
        saved = await checkpointer.aget_tuple(config)
        return await self._aprepare_state_snapshot(
            config,
@@ -1954,7 +1911,9 @@ class Pregel(PregelProtocol):
            # set up subgraph checkpointing
            if self.checkpointer is True:
                ns = cast(str, config[CONF][CONFIG_KEY_CHECKPOINT_NS])
-                config[CONF][CONFIG_KEY_CHECKPOINT_NS] = recast_checkpoint_ns(ns)
+                config[CONF][CONFIG_KEY_CHECKPOINT_NS] = NS_SEP.join(
+                    part.split(NS_END)[0] for part in ns.split(NS_SEP)
+                )
            # set up messages stream mode
            if "messages" in stream_modes:
                run_manager.inheritable_handlers.append(
@@ -2242,7 +2201,9 @@ class Pregel(PregelProtocol):
            # set up subgraph checkpointing
            if self.checkpointer is True:
                ns = cast(str, config[CONF][CONFIG_KEY_CHECKPOINT_NS])
-                config[CONF][CONFIG_KEY_CHECKPOINT_NS] = recast_checkpoint_ns(ns)
+                config[CONF][CONFIG_KEY_CHECKPOINT_NS] = NS_SEP.join(
+                    part.split(NS_END)[0] for part in ns.split(NS_SEP)
+                )
            # set up messages stream mode
            if "messages" in stream_modes:
                run_manager.inheritable_handlers.append(
@@ -2,6 +2,7 @@ import asyncio
 import concurrent.futures
 from collections import defaultdict, deque
 from contextlib import AsyncExitStack, ExitStack
+from dataclasses import replace
 from inspect import signature
 from types import TracebackType
 from typing import (
@@ -54,7 +55,6 @@ from langgraph.constants import (
    ERROR,
    INPUT,
    INTERRUPT,
-    MISSING,
    NS_SEP,
    NULL_TASK_ID,
    PUSH,
@@ -67,6 +67,7 @@ from langgraph.errors import (
    EmptyInputError,
    GraphDelegate,
    GraphInterrupt,
+    ParentCommand,
 )
 from langgraph.managed.base import (
    ManagedValueMapping,
@@ -402,7 +403,6 @@ class PregelLoop(LoopProtocol):
            self.status = "interrupt_before"
            raise GraphInterrupt()
        elif all(task.writes for task in self.tasks.values()):
-            # finish superstep
            writes = [w for t in self.tasks.values() for w in t.writes]
            # debug flag
            if self.debug:
@@ -451,9 +451,6 @@ class PregelLoop(LoopProtocol):
            ):
                self.status = "interrupt_after"
                raise GraphInterrupt()
-
-            # unset resuming flag
-            self.config[CONF].pop(CONFIG_KEY_RESUMING, None)
        else:
            return False

@@ -565,13 +562,7 @@ class PregelLoop(LoopProtocol):
        is_resuming = bool(self.checkpoint["channel_versions"]) and bool(
            configurable.get(
                CONFIG_KEY_RESUMING,
-                self.input is None
-                or isinstance(self.input, Command)
-                or (
-                    not self.is_nested
-                    and self.config.get("metadata", {}).get("run_id")
-                    == self.checkpoint_metadata.get("run_id", MISSING)
-                ),
+                self.input is None or isinstance(self.input, Command),
            )
        )

@@ -747,6 +738,15 @@ class PregelLoop(LoopProtocol):
        exc_value: Optional[BaseException],
        traceback: Optional[TracebackType],
    ) -> Optional[bool]:
+        # add current state to parent command
+        if isinstance(exc_value, ParentCommand):
+            cmd = exc_value.args[0]
+            state = (
+                [(self.output_keys, read_channels(self.channels, self.output_keys))]
+                if isinstance(self.output_keys, str)
+                else list(read_channels(self.channels, self.output_keys).items())
+            )
+            exc_value.args = (replace(cmd, update=[*state, *cmd._update_as_tuples()]),)
        # suppress interrupt
        suppress = isinstance(exc_value, GraphInterrupt) and not self.is_nested
        if suppress:
@@ -127,16 +127,6 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
                tuple(cast(str, metadata["langgraph_checkpoint_ns"]).split(NS_SEP)),
                metadata,
            )
-            if isinstance(inputs, dict):
-                for key, value in inputs.items():
-                    if isinstance(value, BaseMessage):
-                        if value.id is not None:
-                            self.seen.add(value.id)
-                    elif isinstance(value, Sequence) and not isinstance(value, str):
-                        for item in value:
-                            if isinstance(item, BaseMessage):
-                                if item.id is not None:
-                                    self.seen.add(item.id)

    def on_chain_end(
        self,
@@ -32,17 +32,11 @@ def validate_graph(

    for chan in subscribed_channels:
        if chan not in channels:
-            raise ValueError(
-                f"Subscribed channel '{chan}' not "
-                f"in known channels: '{repr(sorted(channels))[:100]}'"
-            )
+            raise ValueError(f"Subscribed channel '{chan}' not in 'channels'")

    if isinstance(input_channels, str):
        if input_channels not in channels:
-            raise ValueError(
-                f"Input channel '{input_channels}' not "
-                f"in known channels: '{repr(sorted(channels))[:100]}'"
-            )
+            raise ValueError(f"Input channel '{input_channels}' not in 'channels'")
        if input_channels not in subscribed_channels:
            raise ValueError(
                f"Input channel {input_channels} is not subscribed to by any node"
@@ -50,13 +44,10 @@ def validate_graph(
    else:
        for chan in input_channels:
            if chan not in channels:
-                raise ValueError(
-                    f"Input channel '{chan}' not in '{repr(sorted(channels))[:100]}'"
-                )
+                raise ValueError(f"Input channel '{chan}' not in 'channels'")
        if all(chan not in subscribed_channels for chan in input_channels):
            raise ValueError(
-                f"None of the input channels {input_channels} "
-                f"are subscribed to by any node"
+                f"None of the input channels {input_channels} are subscribed to by any node"
            )

    all_output_channels = set[str]()
@@ -71,10 +62,7 @@ def validate_graph(

    for chan in all_output_channels:
        if chan not in channels:
-            raise ValueError(
-                f"Output channel '{chan}' not "
-                f"in known channels: '{repr(sorted(channels))[:100]}'"
-            )
+            raise ValueError(f"Output channel '{chan}' not in 'channels'")

    if interrupt_after_nodes != "*":
        for n in interrupt_after_nodes:
@@ -1,9 +1,5 @@
-import sys
-import typing
-from dataclasses import is_dataclass
 from typing import Any, Dict, Optional, Union

-import typing_extensions
 from pydantic import BaseModel
 from pydantic.v1 import BaseModel as BaseModelV1

@@ -39,31 +35,3 @@ def create_model(
            v1_kwargs["__root__"] = root

        return create_model(model_name, **v1_kwargs, **(field_definitions or {}))
-
-
-def is_supported_by_pydantic(type_: Any) -> bool:
-    """Check if a given "complex" type is supported by pydantic.
-
-    This will return False for primitive types like int, str, etc.
-
-    The check is meant for container types like dataclasses, TypedDicts, etc.
-    """
-    if is_dataclass(type_):
-        return True
-
-    # Pydantic does not support mixing .v1 and root namespaces, so
-    # we only check for BaseModel (not pydantic.v1.BaseModel).
-    if isinstance(type_, type) and issubclass(type_, BaseModel):
-        return True
-
-    if hasattr(type_, "__orig_bases__"):
-        for base in type_.__orig_bases__:
-            if base is typing_extensions.TypedDict:
-                return True
-            elif base is typing.TypedDict:  # noqa: TID251
-                # ignoring TID251 since it's OK to use typing.TypedDict in this case.
-                # Pydantic supports typing.TypedDict from Python 3.12
-                # For older versions, only typing_extensions.TypedDict is supported.
-                if sys.version_info >= (3, 12):
-                    return True
-    return False
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.0.0 and should not be changed by hand.

 [[package]]
 name = "aiosqlite"
@@ -1348,7 +1348,7 @@ typing-extensions = ">=4.7"

 [[package]]
 name = "langgraph-checkpoint"
-version = "2.0.16"
+version = "2.0.10"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 optional = false
 python-versions = "^3.9.0,<4.0"
@@ -1366,7 +1366,7 @@ url = "../checkpoint"

 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "2.0.15"
+version = "2.0.12"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 optional = false
 python-versions = "^3.9.0,<4.0"
@@ -1375,7 +1375,7 @@ files = []
 develop = true

 [package.dependencies]
-langgraph-checkpoint = "^2.0.15"
+langgraph-checkpoint = "^2.0.10"
 orjson = ">=3.10.1"
 psycopg = "^3.2.0"
 psycopg-pool = "^3.2.0"
@@ -1386,7 +1386,7 @@ url = "../checkpoint-postgres"

 [[package]]
 name = "langgraph-checkpoint-sqlite"
-version = "2.0.5"
+version = "2.0.3"
 description = "Library with a SQLite implementation of LangGraph checkpoint saver."
 optional = false
 python-versions = "^3.9.0"
@@ -1395,34 +1395,16 @@ files = []
 develop = true

 [package.dependencies]
-aiosqlite = ">=0.20,<0.22"
-langgraph-checkpoint = "^2.0.15"
+aiosqlite = "^0.20.0"
+langgraph-checkpoint = "^2.0.10"

 [package.source]
 type = "directory"
 url = "../checkpoint-sqlite"

-[[package]]
-name = "langgraph-prebuilt"
-version = "0.1.1"
-description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
-optional = false
-python-versions = "^3.9.0,<4.0"
-groups = ["main", "dev"]
-files = []
-develop = true
-
-[package.dependencies]
-langchain-core = ">=0.2.43,<0.4.0,!=0.3.0,!=0.3.1,!=0.3.2,!=0.3.3,!=0.3.4,!=0.3.5,!=0.3.6,!=0.3.7,!=0.3.8,!=0.3.9,!=0.3.10,!=0.3.11,!=0.3.12,!=0.3.13,!=0.3.14,!=0.3.15,!=0.3.16,!=0.3.17,!=0.3.18,!=0.3.19,!=0.3.20,!=0.3.21,!=0.3.22"
-langgraph-checkpoint = "^2.0.10"
-
-[package.source]
-type = "directory"
-url = "../prebuilt"
-
 [[package]]
 name = "langgraph-sdk"
-version = "0.1.53"
+version = "0.1.51"
 description = "SDK for interacting with LangGraph API"
 optional = false
 python-versions = "^3.9.0,<4.0"
@@ -3509,4 +3491,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.9.0,<4.0"
-content-hash = "eb85f0bcc0e8a715ef38afb58cf888f7c2ee8579ea6ed94900244365f24cddd9"
+content-hash = "caf943b02b6913c05d15c37fda6d216669f789e2a059b7e8e2490b2bdcd23e0e"
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph"
-version = "0.3.5"
+version = "0.2.74"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 license = "MIT"
@@ -9,10 +9,9 @@ repository = "https://www.github.com/langchain-ai/langgraph"

 [tool.poetry.dependencies]
 python = ">=3.9.0,<4.0"
-langchain-core = ">=0.1,<0.4"
+langchain-core = ">=0.2.43,<0.4.0,!=0.3.0,!=0.3.1,!=0.3.2,!=0.3.3,!=0.3.4,!=0.3.5,!=0.3.6,!=0.3.7,!=0.3.8,!=0.3.9,!=0.3.10,!=0.3.11,!=0.3.12,!=0.3.13,!=0.3.14,!=0.3.15,!=0.3.16,!=0.3.17,!=0.3.18,!=0.3.19,!=0.3.20,!=0.3.21,!=0.3.22"
 langgraph-checkpoint = "^2.0.10"
 langgraph-sdk = "^0.1.42"
-langgraph-prebuilt = ">=0.1.1,<0.2"

 [tool.poetry.group.dev.dependencies]
 pytest = "^8.3.2"
@@ -27,7 +26,6 @@ ruff = "^0.6.2"
 jupyter = "^1.0.0"
 pytest-xdist = {extras = ["psutil"], version = "^3.6.1"}
 pytest-repeat = "^0.9.3"
-langgraph-prebuilt = {path = "../prebuilt", develop = true}
 langgraph-checkpoint = {path = "../checkpoint", develop = true}
 langgraph-checkpoint-sqlite = {path = "../checkpoint-sqlite", develop = true}
 langgraph-checkpoint-postgres = {path = "../checkpoint-postgres", develop = true}
@@ -1217,426 +1217,6 @@
    'type': 'object',
  })
 # ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[memory]
-  '''
-  graph TD;
-  	__start__ --> rewrite_query;
-  	analyzer_one --> retriever_one;
-  	qa --> __end__;
-  	retriever_one --> qa;
-  	retriever_two --> qa;
-  	rewrite_query --> analyzer_one;
-  	rewrite_query -.-> retriever_two;
-  
-  '''
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[memory].1
-  dict({
-    '$defs': dict({
-      'InnerObject': dict({
-        'properties': dict({
-          'yo': dict({
-            'title': 'Yo',
-            'type': 'integer',
-          }),
-        }),
-        'required': list([
-          'yo',
-        ]),
-        'title': 'InnerObject',
-        'type': 'object',
-      }),
-    }),
-    'properties': dict({
-      'inner': dict({
-        '$ref': '#/$defs/InnerObject',
-      }),
-      'query': dict({
-        'title': 'Query',
-        'type': 'string',
-      }),
-    }),
-    'required': list([
-      'query',
-      'inner',
-    ]),
-    'title': 'Input',
-    'type': 'object',
-  })
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[memory].2
-  dict({
-    'properties': dict({
-      'answer': dict({
-        'title': 'Answer',
-        'type': 'string',
-      }),
-      'docs': dict({
-        'items': dict({
-          'type': 'string',
-        }),
-        'title': 'Docs',
-        'type': 'array',
-      }),
-    }),
-    'required': list([
-      'answer',
-      'docs',
-    ]),
-    'title': 'Output',
-    'type': 'object',
-  })
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres]
-  '''
-  graph TD;
-  	__start__ --> rewrite_query;
-  	analyzer_one --> retriever_one;
-  	qa --> __end__;
-  	retriever_one --> qa;
-  	retriever_two --> qa;
-  	rewrite_query --> analyzer_one;
-  	rewrite_query -.-> retriever_two;
-  
-  '''
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres].1
-  dict({
-    '$defs': dict({
-      'InnerObject': dict({
-        'properties': dict({
-          'yo': dict({
-            'title': 'Yo',
-            'type': 'integer',
-          }),
-        }),
-        'required': list([
-          'yo',
-        ]),
-        'title': 'InnerObject',
-        'type': 'object',
-      }),
-    }),
-    'properties': dict({
-      'inner': dict({
-        '$ref': '#/$defs/InnerObject',
-      }),
-      'query': dict({
-        'title': 'Query',
-        'type': 'string',
-      }),
-    }),
-    'required': list([
-      'query',
-      'inner',
-    ]),
-    'title': 'Input',
-    'type': 'object',
-  })
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres].2
-  dict({
-    'properties': dict({
-      'answer': dict({
-        'title': 'Answer',
-        'type': 'string',
-      }),
-      'docs': dict({
-        'items': dict({
-          'type': 'string',
-        }),
-        'title': 'Docs',
-        'type': 'array',
-      }),
-    }),
-    'required': list([
-      'answer',
-      'docs',
-    ]),
-    'title': 'Output',
-    'type': 'object',
-  })
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_pipe]
-  '''
-  graph TD;
-  	__start__ --> rewrite_query;
-  	analyzer_one --> retriever_one;
-  	qa --> __end__;
-  	retriever_one --> qa;
-  	retriever_two --> qa;
-  	rewrite_query --> analyzer_one;
-  	rewrite_query -.-> retriever_two;
-  
-  '''
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_pipe].1
-  dict({
-    '$defs': dict({
-      'InnerObject': dict({
-        'properties': dict({
-          'yo': dict({
-            'title': 'Yo',
-            'type': 'integer',
-          }),
-        }),
-        'required': list([
-          'yo',
-        ]),
-        'title': 'InnerObject',
-        'type': 'object',
-      }),
-    }),
-    'properties': dict({
-      'inner': dict({
-        '$ref': '#/$defs/InnerObject',
-      }),
-      'query': dict({
-        'title': 'Query',
-        'type': 'string',
-      }),
-    }),
-    'required': list([
-      'query',
-      'inner',
-    ]),
-    'title': 'Input',
-    'type': 'object',
-  })
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_pipe].2
-  dict({
-    'properties': dict({
-      'answer': dict({
-        'title': 'Answer',
-        'type': 'string',
-      }),
-      'docs': dict({
-        'items': dict({
-          'type': 'string',
-        }),
-        'title': 'Docs',
-        'type': 'array',
-      }),
-    }),
-    'required': list([
-      'answer',
-      'docs',
-    ]),
-    'title': 'Output',
-    'type': 'object',
-  })
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_pool]
-  '''
-  graph TD;
-  	__start__ --> rewrite_query;
-  	analyzer_one --> retriever_one;
-  	qa --> __end__;
-  	retriever_one --> qa;
-  	retriever_two --> qa;
-  	rewrite_query --> analyzer_one;
-  	rewrite_query -.-> retriever_two;
-  
-  '''
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_pool].1
-  dict({
-    '$defs': dict({
-      'InnerObject': dict({
-        'properties': dict({
-          'yo': dict({
-            'title': 'Yo',
-            'type': 'integer',
-          }),
-        }),
-        'required': list([
-          'yo',
-        ]),
-        'title': 'InnerObject',
-        'type': 'object',
-      }),
-    }),
-    'properties': dict({
-      'inner': dict({
-        '$ref': '#/$defs/InnerObject',
-      }),
-      'query': dict({
-        'title': 'Query',
-        'type': 'string',
-      }),
-    }),
-    'required': list([
-      'query',
-      'inner',
-    ]),
-    'title': 'Input',
-    'type': 'object',
-  })
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_pool].2
-  dict({
-    'properties': dict({
-      'answer': dict({
-        'title': 'Answer',
-        'type': 'string',
-      }),
-      'docs': dict({
-        'items': dict({
-          'type': 'string',
-        }),
-        'title': 'Docs',
-        'type': 'array',
-      }),
-    }),
-    'required': list([
-      'answer',
-      'docs',
-    ]),
-    'title': 'Output',
-    'type': 'object',
-  })
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_shallow]
-  '''
-  graph TD;
-  	__start__ --> rewrite_query;
-  	analyzer_one --> retriever_one;
-  	qa --> __end__;
-  	retriever_one --> qa;
-  	retriever_two --> qa;
-  	rewrite_query --> analyzer_one;
-  	rewrite_query -.-> retriever_two;
-  
-  '''
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_shallow].1
-  dict({
-    '$defs': dict({
-      'InnerObject': dict({
-        'properties': dict({
-          'yo': dict({
-            'title': 'Yo',
-            'type': 'integer',
-          }),
-        }),
-        'required': list([
-          'yo',
-        ]),
-        'title': 'InnerObject',
-        'type': 'object',
-      }),
-    }),
-    'properties': dict({
-      'inner': dict({
-        '$ref': '#/$defs/InnerObject',
-      }),
-      'query': dict({
-        'title': 'Query',
-        'type': 'string',
-      }),
-    }),
-    'required': list([
-      'query',
-      'inner',
-    ]),
-    'title': 'Input',
-    'type': 'object',
-  })
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_shallow].2
-  dict({
-    'properties': dict({
-      'answer': dict({
-        'title': 'Answer',
-        'type': 'string',
-      }),
-      'docs': dict({
-        'items': dict({
-          'type': 'string',
-        }),
-        'title': 'Docs',
-        'type': 'array',
-      }),
-    }),
-    'required': list([
-      'answer',
-      'docs',
-    ]),
-    'title': 'Output',
-    'type': 'object',
-  })
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[sqlite]
-  '''
-  graph TD;
-  	__start__ --> rewrite_query;
-  	analyzer_one --> retriever_one;
-  	qa --> __end__;
-  	retriever_one --> qa;
-  	retriever_two --> qa;
-  	rewrite_query --> analyzer_one;
-  	rewrite_query -.-> retriever_two;
-  
-  '''
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[sqlite].1
-  dict({
-    '$defs': dict({
-      'InnerObject': dict({
-        'properties': dict({
-          'yo': dict({
-            'title': 'Yo',
-            'type': 'integer',
-          }),
-        }),
-        'required': list([
-          'yo',
-        ]),
-        'title': 'InnerObject',
-        'type': 'object',
-      }),
-    }),
-    'properties': dict({
-      'inner': dict({
-        '$ref': '#/$defs/InnerObject',
-      }),
-      'query': dict({
-        'title': 'Query',
-        'type': 'string',
-      }),
-    }),
-    'required': list([
-      'query',
-      'inner',
-    ]),
-    'title': 'Input',
-    'type': 'object',
-  })
-# ---
-# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[sqlite].2
-  dict({
-    'properties': dict({
-      'answer': dict({
-        'title': 'Answer',
-        'type': 'string',
-      }),
-      'docs': dict({
-        'items': dict({
-          'type': 'string',
-        }),
-        'title': 'Docs',
-        'type': 'array',
-      }),
-    }),
-    'required': list([
-      'answer',
-      'docs',
-    ]),
-    'title': 'Output',
-    'type': 'object',
-  })
-# ---
 # name: test_in_one_fan_out_state_graph_waiting_edge_via_branch[memory]
  '''
  graph TD;
@@ -1948,7 +1528,7 @@
  '''
 # ---
 # name: test_state_graph_w_config_inherited_state_keys
-  '{"$defs": {"Config": {"properties": {"tools": {"items": {"type": "string"}, "title": "Tools", "type": "array"}}, "title": "Config", "type": "object"}}, "properties": {"configurable": {"$ref": "#/$defs/Config", "default": null}}, "title": "LangGraphConfig", "type": "object"}'
+  '{"$defs": {"Configurable": {"properties": {"tools": {"default": null, "items": {"type": "string"}, "title": "Tools", "type": "array"}}, "title": "Configurable", "type": "object"}}, "properties": {"configurable": {"$ref": "#/$defs/Configurable", "default": null}}, "title": "LangGraphConfig", "type": "object"}'
 # ---
 # name: test_state_graph_w_config_inherited_state_keys.1
  '{"$defs": {"AgentAction": {"description": "Represents a request to execute an action by an agent.\\n\\nThe action consists of the name of the tool to execute and the input to pass\\nto the tool. The log is used to pass along extra information about the action.", "properties": {"tool": {"title": "Tool", "type": "string"}, "tool_input": {"anyOf": [{"type": "string"}, {"type": "object"}], "title": "Tool Input"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentAction", "default": "AgentAction", "enum": ["AgentAction"], "title": "Type", "type": "string"}}, "required": ["tool", "tool_input", "log"], "title": "AgentAction", "type": "object"}, "AgentFinish": {"description": "Final return value of an ActionAgent.\\n\\nAgents return an AgentFinish when they have reached a stopping condition.", "properties": {"return_values": {"title": "Return Values", "type": "object"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentFinish", "default": "AgentFinish", "enum": ["AgentFinish"], "title": "Type", "type": "string"}}, "required": ["return_values", "log"], "title": "AgentFinish", "type": "object"}}, "properties": {"input": {"title": "Input", "type": "string"}, "agent_outcome": {"anyOf": [{"$ref": "#/$defs/AgentAction"}, {"$ref": "#/$defs/AgentFinish"}, {"type": "null"}], "default": null, "title": "Agent Outcome"}, "intermediate_steps": {"default": null, "items": {"maxItems": 2, "minItems": 2, "prefixItems": [{"$ref": "#/$defs/AgentAction"}, {"type": "string"}], "type": "array"}, "title": "Intermediate Steps", "type": "array"}}, "required": ["input"], "title": "LangGraphInput", "type": "object"}'
@@ -10,7 +10,7 @@ import warnings
 from collections import Counter, deque
 from concurrent.futures import ThreadPoolExecutor
 from contextlib import contextmanager
-from dataclasses import dataclass, field
+from dataclasses import dataclass
 from random import randrange
 from typing import (
    Annotated,
@@ -275,61 +275,6 @@ def test_checkpoint_errors() -> None:
        graph.invoke("", {"configurable": {"thread_id": "thread-1"}})


-def test_config_json_schema() -> None:
-    """Test that config json schema is generated properly."""
-    chain = Channel.subscribe_to("input") | Channel.write_to("output")
-
-    @dataclass
-    class Foo:
-        x: int
-        y: str = field(default="foo")
-
-    app = Pregel(
-        nodes={
-            "one": chain,
-        },
-        channels={
-            "ephemeral": EphemeralValue(Any),
-            "input": LastValue(int),
-            "output": LastValue(int),
-        },
-        input_channels=["input", "ephemeral"],
-        output_channels="output",
-        config_type=Foo,
-    )
-
-    assert app.get_config_jsonschema() == {
-        "$defs": {
-            "Foo": {
-                "properties": {
-                    "x": {
-                        "title": "X",
-                        "type": "integer",
-                    },
-                    "y": {
-                        "default": "foo",
-                        "title": "Y",
-                        "type": "string",
-                    },
-                },
-                "required": [
-                    "x",
-                ],
-                "title": "Foo",
-                "type": "object",
-            },
-        },
-        "properties": {
-            "configurable": {
-                "$ref": "#/$defs/Foo",
-                "default": None,
-            },
-        },
-        "title": "LangGraphConfig",
-        "type": "object",
-    }
-
-
 def test_node_schemas_custom_output() -> None:
    class State(TypedDict):
        hello: str
@@ -1499,7 +1444,7 @@ def test_imp_task(request: pytest.FixtureRequest, checkpointer_name: str) -> Non
    checkpointer = request.getfixturevalue(f"checkpointer_{checkpointer_name}")
    mapper_calls = 0

-    class Configurable:
+    class Config:
        model: str

    @task()
@@ -1509,7 +1454,7 @@ def test_imp_task(request: pytest.FixtureRequest, checkpointer_name: str) -> Non
        time.sleep(input / 100)
        return str(input) * 2

-    @entrypoint(checkpointer=checkpointer, config_schema=Configurable)
+    @entrypoint(checkpointer=checkpointer, config_schema=Config)
    def graph(input: list[int]) -> list[str]:
        futures = [mapper(i) for i in input]
        mapped = [f.result() for f in futures]
@@ -2894,139 +2839,6 @@ def test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic2(
        }


-@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_SYNC)
-def test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input(
-    snapshot: SnapshotAssertion,
-    mocker: MockerFixture,
-    request: pytest.FixtureRequest,
-    checkpointer_name: str,
-) -> None:
-    from pydantic import BaseModel
-
-    checkpointer = request.getfixturevalue(f"checkpointer_{checkpointer_name}")
-
-    def sorted_add(
-        x: list[str], y: Union[list[str], list[tuple[str, str]]]
-    ) -> list[str]:
-        if isinstance(y[0], tuple):
-            for rem, _ in y:
-                x.remove(rem)
-            y = [t[1] for t in y]
-        return sorted(operator.add(x, y))
-
-    class InnerObject(BaseModel):
-        yo: int
-
-    class QueryModel(BaseModel):
-        query: str
-
-    class State(QueryModel):
-        inner: InnerObject
-        answer: Optional[str] = None
-        docs: Annotated[list[str], sorted_add]
-
-    class StateUpdate(BaseModel):
-        query: Optional[str] = None
-        answer: Optional[str] = None
-        docs: Optional[list[str]] = None
-
-    class Input(QueryModel):
-        inner: InnerObject
-
-    class Output(BaseModel):
-        answer: str
-        docs: list[str]
-
-    def rewrite_query(data: State) -> State:
-        return {"query": f"query: {data.query}"}
-
-    def analyzer_one(data: State) -> State:
-        return StateUpdate(query=f"analyzed: {data.query}")
-
-    def retriever_one(data: State) -> State:
-        return {"docs": ["doc1", "doc2"]}
-
-    def retriever_two(data: State) -> State:
-        time.sleep(0.1)
-        return {"docs": ["doc3", "doc4"]}
-
-    def qa(data: State) -> State:
-        return {"answer": ",".join(data.docs)}
-
-    def decider(data: State) -> str:
-        assert isinstance(data, State)
-        return "retriever_two"
-
-    workflow = StateGraph(State, input=Input, output=Output)
-
-    workflow.add_node("rewrite_query", rewrite_query)
-    workflow.add_node("analyzer_one", analyzer_one)
-    workflow.add_node("retriever_one", retriever_one)
-    workflow.add_node("retriever_two", retriever_two)
-    workflow.add_node("qa", qa)
-
-    workflow.set_entry_point("rewrite_query")
-    workflow.add_edge("rewrite_query", "analyzer_one")
-    workflow.add_edge("analyzer_one", "retriever_one")
-    workflow.add_conditional_edges(
-        "rewrite_query", decider, {"retriever_two": "retriever_two"}
-    )
-    workflow.add_edge(["retriever_one", "retriever_two"], "qa")
-    workflow.set_finish_point("qa")
-
-    app = workflow.compile()
-
-    assert app.invoke(
-        Input(query="what is weather in sf", inner=InnerObject(yo=1))
-    ) == {
-        "docs": ["doc1", "doc2", "doc3", "doc4"],
-        "answer": "doc1,doc2,doc3,doc4",
-    }
-
-    assert [
-        *app.stream(Input(query="what is weather in sf", inner=InnerObject(yo=1)))
-    ] == [
-        {"rewrite_query": {"query": "query: what is weather in sf"}},
-        {"analyzer_one": {"query": "analyzed: query: what is weather in sf"}},
-        {"retriever_two": {"docs": ["doc3", "doc4"]}},
-        {"retriever_one": {"docs": ["doc1", "doc2"]}},
-        {"qa": {"answer": "doc1,doc2,doc3,doc4"}},
-    ]
-
-    app_w_interrupt = workflow.compile(
-        checkpointer=checkpointer,
-        interrupt_after=["retriever_one"],
-    )
-    config = {"configurable": {"thread_id": "1"}}
-
-    assert [
-        c
-        for c in app_w_interrupt.stream(
-            Input(query="what is weather in sf", inner=InnerObject(yo=1)), config
-        )
-    ] == [
-        {"rewrite_query": {"query": "query: what is weather in sf"}},
-        {"analyzer_one": {"query": "analyzed: query: what is weather in sf"}},
-        {"retriever_two": {"docs": ["doc3", "doc4"]}},
-        {"retriever_one": {"docs": ["doc1", "doc2"]}},
-        {"__interrupt__": ()},
-    ]
-
-    assert [c for c in app_w_interrupt.stream(None, config)] == [
-        {"qa": {"answer": "doc1,doc2,doc3,doc4"}},
-    ]
-
-    assert app_w_interrupt.update_state(
-        config, {"docs": ["doc5"]}, as_node="rewrite_query"
-    ) == {
-        "configurable": {
-            "thread_id": "1",
-            "checkpoint_id": AnyStr(),
-            "checkpoint_ns": "",
-        }
-    }
-
-
@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_SYNC)
 def test_in_one_fan_out_state_graph_waiting_edge_plus_regular(
    request: pytest.FixtureRequest, checkpointer_name: str
@@ -3093,24 +2905,14 @@ def test_in_one_fan_out_state_graph_waiting_edge_plus_regular(
        "answer": "doc1,doc2,doc3,doc4",
    }

-    assert [*app.stream({"query": "what is weather in sf"})] in (
-        [
-            {"rewrite_query": {"query": "query: what is weather in sf"}},
-            {"qa": {"answer": ""}},
-            {"analyzer_one": {"query": "analyzed: query: what is weather in sf"}},
-            {"retriever_two": {"docs": ["doc3", "doc4"]}},
-            {"retriever_one": {"docs": ["doc1", "doc2"]}},
-            {"qa": {"answer": "doc1,doc2,doc3,doc4"}},
-        ],
-        [
-            {"rewrite_query": {"query": "query: what is weather in sf"}},
-            {"analyzer_one": {"query": "analyzed: query: what is weather in sf"}},
-            {"qa": {"answer": ""}},
-            {"retriever_two": {"docs": ["doc3", "doc4"]}},
-            {"retriever_one": {"docs": ["doc1", "doc2"]}},
-            {"qa": {"answer": "doc1,doc2,doc3,doc4"}},
-        ],
-    )
+    assert [*app.stream({"query": "what is weather in sf"})] == [
+        {"rewrite_query": {"query": "query: what is weather in sf"}},
+        {"qa": {"answer": ""}},
+        {"analyzer_one": {"query": "analyzed: query: what is weather in sf"}},
+        {"retriever_two": {"docs": ["doc3", "doc4"]}},
+        {"retriever_one": {"docs": ["doc1", "doc2"]}},
+        {"qa": {"answer": "doc1,doc2,doc3,doc4"}},
+    ]

    app_w_interrupt = workflow.compile(
        checkpointer=checkpointer,
@@ -3569,59 +3371,6 @@ def test_subgraph_checkpoint_true(
    ]


-@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_SYNC)
-def test_subgraph_checkpoint_true_interrupt(
-    request: pytest.FixtureRequest, checkpointer_name: str
-) -> None:
-    checkpointer = request.getfixturevalue("checkpointer_" + checkpointer_name)
-
-    # Define subgraph
-    class SubgraphState(TypedDict):
-        # note that none of these keys are shared with the parent graph state
-        bar: str
-        baz: str
-
-    def subgraph_node_1(state: SubgraphState):
-        baz_value = interrupt("Provide baz value")
-        return {"baz": baz_value}
-
-    def subgraph_node_2(state: SubgraphState):
-        return {"bar": state["bar"] + state["baz"]}
-
-    subgraph_builder = StateGraph(SubgraphState)
-    subgraph_builder.add_node(subgraph_node_1)
-    subgraph_builder.add_node(subgraph_node_2)
-    subgraph_builder.add_edge(START, "subgraph_node_1")
-    subgraph_builder.add_edge("subgraph_node_1", "subgraph_node_2")
-    subgraph = subgraph_builder.compile(checkpointer=True)
-
-    class ParentState(TypedDict):
-        foo: str
-
-    def node_1(state: ParentState):
-        return {"foo": "hi! " + state["foo"]}
-
-    def node_2(state: ParentState):
-        response = subgraph.invoke({"bar": state["foo"]})
-        return {"foo": response["bar"]}
-
-    builder = StateGraph(ParentState)
-    builder.add_node("node_1", node_1)
-    builder.add_node("node_2", node_2)
-    builder.add_edge(START, "node_1")
-    builder.add_edge("node_1", "node_2")
-
-    checkpointer = MemorySaver()
-    graph = builder.compile(checkpointer=checkpointer)
-    config = {"configurable": {"thread_id": "1"}}
-
-    assert graph.invoke({"foo": "foo"}, config) == {"foo": "hi! foo"}
-    assert graph.get_state(config, subgraphs=True).tasks[0].state.values == {
-        "bar": "hi! foo"
-    }
-    assert graph.invoke(Command(resume="baz"), config) == {"foo": "hi! foobaz"}
-
-
@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_SYNC)
 def test_stream_subgraphs_during_execution(
    request: pytest.FixtureRequest, checkpointer_name: str
@@ -5081,6 +4830,13 @@ def test_parent_command(request: pytest.FixtureRequest, checkpointer_name: str)
            "source": "loop",
            "writes": {
                "alice": {
+                    "messages": [
+                        _AnyIdHumanMessage(
+                            content="get user name",
+                            additional_kwargs={},
+                            response_metadata={},
+                        ),
+                    ],
                    "user_name": "Meow",
                }
            },
@@ -6420,6 +6176,151 @@ def test_multiple_subgraphs_checkpointer(
    ]


+def test_merging_updates_command_parent():
+    # simple reducer
+    def append_unique(left, right):
+        combined = list(left)
+        for item in right:
+            if item in combined:
+                continue
+            else:
+                combined.append(item)
+        return combined
+
+    class State(TypedDict):
+        foo: str
+        bar: Annotated[list[str], append_unique]
+
+    # Define subgraph
+    def subgraph_node_1(state: State):
+        return Command(
+            goto="subgraph_node_2",
+            update={
+                "foo": "foo",
+                "bar": ["subgraph_node_1"],
+            },
+        )
+
+    def subgraph_node_2(state: State):
+        return Command(
+            goto="node_3",
+            update={"bar": ["subgraph_node_2"]},
+            graph=Command.PARENT,
+        )
+
+    subgraph_builder = StateGraph(State)
+    subgraph_builder.add_node(subgraph_node_1)
+    subgraph_builder.add_node(subgraph_node_2)
+    subgraph_builder.add_edge(START, "subgraph_node_1")
+
+    # Define main graph
+    def node_1(state: State):
+        return Command(
+            goto="node_2",
+            update={"bar": ["node_1"]},
+        )
+
+    def node_3(state: State, store):
+        return Command(
+            update={"bar": ["node_3"]},
+        )
+
+    main_builder = StateGraph(State)
+    main_builder.add_node("node_1", node_1)
+    main_builder.add_node("node_2", subgraph_builder.compile())
+    main_builder.add_node("node_3", node_3)
+    main_builder.add_edge(START, "node_1")
+    main_builder.add_edge("node_2", "node_3")
+    main_graph = main_builder.compile()
+
+    assert main_graph.invoke({"foo": ""}) == {
+        "foo": "foo",
+        "bar": ["node_1", "subgraph_node_1", "subgraph_node_2", "node_3"],
+    }
+
+    assert list(
+        main_graph.stream({"foo": ""}, stream_mode="updates", subgraphs=True)
+    ) == [
+        ((), {"node_1": {"bar": ["node_1"]}}),
+        (
+            (AnyStr("node_2:"),),
+            {"subgraph_node_1": {"foo": "foo", "bar": ["subgraph_node_1"]}},
+        ),
+        (
+            (),
+            {
+                "node_2": [
+                    {"foo": "foo"},
+                    {"bar": ["node_1", "subgraph_node_1"]},
+                    {"bar": ["subgraph_node_2"]},
+                ]
+            },
+        ),
+        ((), {"node_3": {"bar": ["node_3"]}}),
+    ]
+
+
+def test_merging_non_overlapping_updates_command_parent():
+    # simple reducer
+    def append_unique(left, right):
+        combined = list(left)
+        for item in right:
+            if item in combined:
+                continue
+            else:
+                combined.append(item)
+        return combined
+
+    class State(TypedDict):
+        foo: Annotated[list, append_unique]
+
+    # Define subgraph
+    def subgraph_node_1(state: State):
+        return Command(
+            goto="subgraph_node_2",
+            update={
+                "foo": ["bar"],
+                "bar": ["subgraph_node_1"],
+            },
+        )
+
+    def subgraph_node_2(state: State):
+        return Command(
+            goto="node_3",
+            update={"bar": ["subgraph_node_2"]},
+            graph=Command.PARENT,
+        )
+
+    subgraph_builder = StateGraph(State)
+    subgraph_builder.add_node(subgraph_node_1)
+    subgraph_builder.add_node(subgraph_node_2)
+    subgraph_builder.add_edge(START, "subgraph_node_1")
+
+    # Define main graph
+    def node_1(state: State):
+        return Command(
+            goto="node_2",
+            update={"foo": ["foo"]},
+        )
+
+    def node_3(state: State, store):
+        return Command(
+            update={"foo": ["baz"]},
+        )
+
+    main_builder = StateGraph(State)
+    main_builder.add_node("node_1", node_1)
+    main_builder.add_node("node_2", subgraph_builder.compile())
+    main_builder.add_node("node_3", node_3)
+    main_builder.add_edge(START, "node_1")
+    main_builder.add_edge("node_2", "node_3")
+    main_graph = main_builder.compile()
+
+    assert main_graph.invoke({"foo": []}) == {
+        "foo": ["foo", "bar", "baz"],
+    }
+
+
 def test_entrypoint_output_schema_with_return_and_save() -> None:
    """Test output schema inference with entrypoint.final."""

@@ -6687,194 +6588,3 @@ def test_get_stream_writer() -> None:
            },
        ),
    ]
-
-
-def test_stream_messages_dedupe_inputs() -> None:
-    from langchain_core.messages import AIMessage
-
-    def call_model(state):
-        return {"messages": AIMessage("hi", id="1")}
-
-    def route(state):
-        return Command(goto="node_2", graph=Command.PARENT)
-
-    subgraph = (
-        StateGraph(MessagesState)
-        .add_node(call_model)
-        .add_node(route)
-        .add_edge(START, "call_model")
-        .add_edge("call_model", "route")
-        .compile()
-    )
-
-    graph = (
-        StateGraph(MessagesState)
-        .add_node("node_1", subgraph)
-        .add_node("node_2", lambda state: state)
-        .add_edge(START, "node_1")
-        .compile()
-    )
-
-    chunks = [
-        chunk
-        for ns, chunk in graph.stream(
-            {"messages": "hi"}, stream_mode="messages", subgraphs=True
-        )
-    ]
-
-    assert len(chunks) == 1
-    assert chunks[0][0] == AIMessage("hi", id="1")
-    assert chunks[0][1]["langgraph_node"] == "call_model"
-
-
-@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_SYNC)
-def test_stream_messages_dedupe_state(
-    request: pytest.FixtureRequest, checkpointer_name: str
-) -> None:
-    from langchain_core.messages import AIMessage
-
-    checkpointer = request.getfixturevalue(f"checkpointer_{checkpointer_name}")
-    to_emit = [AIMessage("bye", id="1"), AIMessage("bye again", id="2")]
-
-    def call_model(state):
-        return {"messages": to_emit.pop(0)}
-
-    def route(state):
-        return Command(goto="node_2", graph=Command.PARENT)
-
-    subgraph = (
-        StateGraph(MessagesState)
-        .add_node(call_model)
-        .add_node(route)
-        .add_edge(START, "call_model")
-        .add_edge("call_model", "route")
-        .compile()
-    )
-
-    graph = (
-        StateGraph(MessagesState)
-        .add_node("node_1", subgraph)
-        .add_node("node_2", lambda state: state)
-        .add_edge(START, "node_1")
-        .compile(checkpointer=checkpointer)
-    )
-
-    thread1 = {"configurable": {"thread_id": "1"}}
-
-    chunks = [
-        chunk
-        for ns, chunk in graph.stream(
-            {"messages": "hi"}, thread1, stream_mode="messages", subgraphs=True
-        )
-    ]
-
-    assert len(chunks) == 1
-    assert chunks[0][0] == AIMessage("bye", id="1")
-    assert chunks[0][1]["langgraph_node"] == "call_model"
-
-    chunks = [
-        chunk
-        for ns, chunk in graph.stream(
-            {"messages": "hi again"},
-            thread1,
-            stream_mode="messages",
-            subgraphs=True,
-        )
-    ]
-
-    assert len(chunks) == 1
-    assert chunks[0][0] == AIMessage("bye again", id="2")
-    assert chunks[0][1]["langgraph_node"] == "call_model"
-
-
-@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_SYNC)
-def test_interrupt_subgraph_reenter_checkpointer_true(
-    request: pytest.FixtureRequest, checkpointer_name: str
-) -> None:
-    checkpointer = request.getfixturevalue(f"checkpointer_{checkpointer_name}")
-
-    class SubgraphState(TypedDict):
-        foo: str
-        bar: str
-
-    class ParentState(TypedDict):
-        foo: str
-        counter: int
-
-    called = []
-    bar_values = []
-
-    def subnode_1(state: SubgraphState):
-        called.append("subnode_1")
-        bar_values.append(state.get("bar"))
-        return {"foo": "subgraph_1"}
-
-    def subnode_2(state: SubgraphState):
-        called.append("subnode_2")
-        value = interrupt("Provide value")
-        value += "baz"
-        return {"foo": "subgraph_2", "bar": value}
-
-    subgraph = (
-        StateGraph(SubgraphState)
-        .add_node(subnode_1)
-        .add_node(subnode_2)
-        .add_edge(START, "subnode_1")
-        .add_edge("subnode_1", "subnode_2")
-        .compile(checkpointer=True)
-    )
-
-    def call_subgraph(state: ParentState):
-        called.append("call_subgraph")
-        return subgraph.invoke(state)
-
-    def node(state: ParentState):
-        called.append("parent")
-        if state["counter"] < 1:
-            return Command(
-                goto="call_subgraph", update={"counter": state["counter"] + 1}
-            )
-
-        return {"foo": state["foo"] + "|" + "parent"}
-
-    parent = (
-        StateGraph(ParentState)
-        .add_node(call_subgraph)
-        .add_node(node)
-        .add_edge(START, "call_subgraph")
-        .add_edge("call_subgraph", "node")
-        .compile(checkpointer=checkpointer)
-    )
-
-    config = {"configurable": {"thread_id": "1"}}
-    assert parent.invoke({"foo": "", "counter": 0}, config) == {"foo": "", "counter": 0}
-    assert parent.invoke(Command(resume="bar"), config) == {
-        "foo": "subgraph_2",
-        "counter": 1,
-    }
-    assert parent.invoke(Command(resume="qux"), config) == {
-        "foo": "subgraph_2|parent",
-        "counter": 1,
-    }
-    assert called == [
-        "call_subgraph",
-        "subnode_1",
-        "subnode_2",
-        "call_subgraph",
-        "subnode_2",
-        "parent",
-        "call_subgraph",
-        "subnode_1",
-        "subnode_2",
-        "call_subgraph",
-        "subnode_2",
-        "parent",
-    ]
-
-    # invoke parent again (new turn)
-    assert parent.invoke({"foo": "meow", "counter": 0}, config) == {
-        "foo": "meow",
-        "counter": 0,
-    }
-    # confirm that we preserve the state values from the previous invocation
-    assert bar_values == [None, "barbaz", "quxbaz"]
@@ -6148,6 +6148,13 @@ async def test_parent_command(checkpointer_name: str) -> None:
                "source": "loop",
                "writes": {
                    "alice": {
+                        "messages": [
+                            _AnyIdHumanMessage(
+                                content="get user name",
+                                additional_kwargs={},
+                                response_metadata={},
+                            ),
+                        ],
                        "user_name": "Meow",
                    }
                },
@@ -7275,7 +7282,9 @@ async def test_multiple_subgraphs_mixed_state_graph(

@NEEDS_CONTEXTVARS
@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_ASYNC)
-async def test_multiple_subgraphs_checkpointer(checkpointer_name: str) -> None:
+async def test_multiple_subgraphs_checkpointer(
+    request: pytest.FixtureRequest, checkpointer_name: str
+) -> None:
    async with awith_checkpointer(checkpointer_name) as checkpointer:

        class SubgraphState(TypedDict):
@@ -7504,196 +7513,3 @@ async def test_tags_stream_mode_messages() -> None:
            },
        )
    ]
-
-
-async def test_stream_messages_dedupe_inputs() -> None:
-    from langchain_core.messages import AIMessage
-
-    async def call_model(state):
-        return {"messages": AIMessage("hi", id="1")}
-
-    async def route(state):
-        return Command(goto="node_2", graph=Command.PARENT)
-
-    subgraph = (
-        StateGraph(MessagesState)
-        .add_node(call_model)
-        .add_node(route)
-        .add_edge(START, "call_model")
-        .add_edge("call_model", "route")
-        .compile()
-    )
-
-    graph = (
-        StateGraph(MessagesState)
-        .add_node("node_1", subgraph)
-        .add_node("node_2", lambda state: state)
-        .add_edge(START, "node_1")
-        .compile()
-    )
-
-    chunks = [
-        chunk
-        async for ns, chunk in graph.astream(
-            {"messages": "hi"}, stream_mode="messages", subgraphs=True
-        )
-    ]
-
-    assert len(chunks) == 1
-    assert chunks[0][0] == AIMessage("hi", id="1")
-    assert chunks[0][1]["langgraph_node"] == "call_model"
-
-
-@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_ASYNC)
-async def test_stream_messages_dedupe_state(checkpointer_name: str) -> None:
-    async with awith_checkpointer(checkpointer_name) as checkpointer:
-        from langchain_core.messages import AIMessage
-
-        to_emit = [AIMessage("bye", id="1"), AIMessage("bye again", id="2")]
-
-        async def call_model(state):
-            return {"messages": to_emit.pop(0)}
-
-        async def route(state):
-            return Command(goto="node_2", graph=Command.PARENT)
-
-        subgraph = (
-            StateGraph(MessagesState)
-            .add_node(call_model)
-            .add_node(route)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", "route")
-            .compile()
-        )
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("node_1", subgraph)
-            .add_node("node_2", lambda state: state)
-            .add_edge(START, "node_1")
-            .compile(checkpointer=checkpointer)
-        )
-
-        thread1 = {"configurable": {"thread_id": "1"}}
-
-        chunks = [
-            chunk
-            async for ns, chunk in graph.astream(
-                {"messages": "hi"}, thread1, stream_mode="messages", subgraphs=True
-            )
-        ]
-
-        assert len(chunks) == 1
-        assert chunks[0][0] == AIMessage("bye", id="1")
-        assert chunks[0][1]["langgraph_node"] == "call_model"
-
-        chunks = [
-            chunk
-            async for ns, chunk in graph.astream(
-                {"messages": "hi again"},
-                thread1,
-                stream_mode="messages",
-                subgraphs=True,
-            )
-        ]
-
-        assert len(chunks) == 1
-        assert chunks[0][0] == AIMessage("bye again", id="2")
-        assert chunks[0][1]["langgraph_node"] == "call_model"
-
-
-@NEEDS_CONTEXTVARS
-@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_ASYNC)
-async def test_interrupt_subgraph_reenter_checkpointer_true(
-    checkpointer_name: str,
-) -> None:
-    async with awith_checkpointer(checkpointer_name) as checkpointer:
-
-        class SubgraphState(TypedDict):
-            foo: str
-            bar: str
-
-        class ParentState(TypedDict):
-            foo: str
-            counter: int
-
-        called = []
-        bar_values = []
-
-        async def subnode_1(state: SubgraphState):
-            called.append("subnode_1")
-            bar_values.append(state.get("bar"))
-            return {"foo": "subgraph_1"}
-
-        async def subnode_2(state: SubgraphState):
-            called.append("subnode_2")
-            value = interrupt("Provide value")
-            value += "baz"
-            return {"foo": "subgraph_2", "bar": value}
-
-        subgraph = (
-            StateGraph(SubgraphState)
-            .add_node(subnode_1)
-            .add_node(subnode_2)
-            .add_edge(START, "subnode_1")
-            .add_edge("subnode_1", "subnode_2")
-            .compile(checkpointer=True)
-        )
-
-        async def call_subgraph(state: ParentState):
-            called.append("call_subgraph")
-            return await subgraph.ainvoke(state)
-
-        async def node(state: ParentState):
-            called.append("parent")
-            if state["counter"] < 1:
-                return Command(
-                    goto="call_subgraph", update={"counter": state["counter"] + 1}
-                )
-
-            return {"foo": state["foo"] + "|" + "parent"}
-
-        parent = (
-            StateGraph(ParentState)
-            .add_node(call_subgraph)
-            .add_node(node)
-            .add_edge(START, "call_subgraph")
-            .add_edge("call_subgraph", "node")
-            .compile(checkpointer=checkpointer)
-        )
-
-        config = {"configurable": {"thread_id": "1"}}
-        assert await parent.ainvoke({"foo": "", "counter": 0}, config) == {
-            "foo": "",
-            "counter": 0,
-        }
-        assert await parent.ainvoke(Command(resume="bar"), config) == {
-            "foo": "subgraph_2",
-            "counter": 1,
-        }
-        assert await parent.ainvoke(Command(resume="qux"), config) == {
-            "foo": "subgraph_2|parent",
-            "counter": 1,
-        }
-        assert called == [
-            "call_subgraph",
-            "subnode_1",
-            "subnode_2",
-            "call_subgraph",
-            "subnode_2",
-            "parent",
-            "call_subgraph",
-            "subnode_1",
-            "subnode_2",
-            "call_subgraph",
-            "subnode_2",
-            "parent",
-        ]
-
-        # invoke parent again (new turn)
-        assert await parent.ainvoke({"foo": "meow", "counter": 0}, config) == {
-            "foo": "meow",
-            "counter": 0,
-        }
-        # confirm that we preserve the state values from the previous invocation
-        assert bar_values == [None, "barbaz", "quxbaz"]
@@ -1,43 +0,0 @@
-import sys
-import typing
-
-import pydantic
-import typing_extensions
-
-from langgraph.utils.pydantic import is_supported_by_pydantic
-
-
-def test_is_supported_by_pydantic() -> None:
-    """Test if types are supported by pydantic."""
-
-    class TypedDictExtensions(typing_extensions.TypedDict):
-        x: int
-
-    assert is_supported_by_pydantic(TypedDictExtensions) is True
-
-    class VanillaClass:
-        x: int
-
-    assert is_supported_by_pydantic(VanillaClass) is False
-
-    class BuiltinTypedDict(typing.TypedDict):  # noqa: TID251
-        x: int
-
-    if sys.version_info >= (3, 12):
-        assert is_supported_by_pydantic(BuiltinTypedDict) is True
-    else:
-        assert is_supported_by_pydantic(BuiltinTypedDict) is False
-
-    class PydanticModel(pydantic.BaseModel):
-        x: int
-
-    assert is_supported_by_pydantic(PydanticModel) is True
-
-    if hasattr(pydantic, "v1"):
-
-        class PydanticModelV1(pydantic.v1.BaseModel):
-            x: int
-
-        assert is_supported_by_pydantic(PydanticModelV1) is False
-
-    assert is_supported_by_pydantic(int) is False
@@ -1,21 +0,0 @@
-MIT License
-
-Copyright (c) 2024 LangChain, Inc.
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
@@ -1,78 +0,0 @@
-.PHONY: all format lint test test_watch integration_tests spell_check spell_fix benchmark profile
-
-# Default target executed when no arguments are given to make.
-all: help
-
-######################
-# TESTING AND COVERAGE
-######################
-
-start-postgres:
-	docker compose -f tests/compose-postgres.yml up -V --force-recreate --wait --remove-orphans
-
-stop-postgres:
-	docker compose -f tests/compose-postgres.yml down -v
-
-TEST ?= .
-
-test:
-	make start-postgres && poetry run pytest $(TEST); \
-	EXIT_CODE=$$?; \
-	make stop-postgres; \
-	exit $$EXIT_CODE
-
-test_watch:
-	make start-postgres && poetry run ptw $(TEST); \
-	EXIT_CODE=$$?; \
-	make stop-postgres; \
-	exit $$EXIT_CODE
-
-######################
-# LINTING AND FORMATTING
-######################
-
-# Define a variable for Python and notebook files.
-PYTHON_FILES=.
-MYPY_CACHE=.mypy_cache
-lint format: PYTHON_FILES=.
-lint_diff format_diff: PYTHON_FILES=$(shell git diff --name-only --relative --diff-filter=d main . | grep -E '\.py$$|\.ipynb$$')
-lint_package: PYTHON_FILES=langgraph
-lint_tests: PYTHON_FILES=tests
-lint_tests: MYPY_CACHE=.mypy_cache_test
-
-lint lint_diff lint_package lint_tests:
-	poetry run ruff check .
-	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
-	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff check --select I $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE)
-	[ "$(PYTHON_FILES)" = "" ] || poetry run mypy langgraph --cache-dir $(MYPY_CACHE)
-
-format format_diff:
-	poetry run ruff format $(PYTHON_FILES)
-	poetry run ruff check --select I --fix $(PYTHON_FILES)
-
-spell_check:
-	poetry run codespell --toml pyproject.toml
-
-spell_fix:
-	poetry run codespell --toml pyproject.toml -w
-
-
-######################
-# HELP
-######################
-
-help:
-	@echo '===================='
-	@echo '-- DOCUMENTATION --'
-	
-	@echo '-- LINTING --'
-	@echo 'format                       - run code formatters'
-	@echo 'lint                         - run linters'
-	@echo 'spell_check               	- run codespell on the project'
-	@echo 'spell_fix               		- run codespell on the project and fix the errors'
-	@echo '-- TESTS --'
-	@echo 'coverage                     - run unit tests and generate coverage report'
-	@echo 'test                         - run unit tests'
-	@echo 'test TEST_FILE=<test_file>   - run all tests in file'
-	@echo 'test_watch                   - run unit tests in watch mode'
@@ -1,117 +0,0 @@
-# LangGraph Prebuilt
-
-This library defines high-level APIs for creating and executing LangGraph agents and tools.
-
-> [!IMPORTANT]
-> This library is meant to be bundled with `langgraph`, don't install it directly
-
-## Agents
-
-`langgraph-prebuilt` provides an [implementation](https://langchain-ai.github.io/langgraph/reference/prebuilt/#langgraph.prebuilt.chat_agent_executor.create_react_agent) of a tool-calling [ReAct-style](https://langchain-ai.github.io/langgraph/concepts/agentic_concepts/#react-implementation) agent - `create_react_agent`:
-
-```bash
-pip install langchain-anthropic
-```
-
-```python
-from langchain_anthropic import ChatAnthropic
-from langgraph.prebuilt import create_react_agent
-
-# Define the tools for the agent to use
-def search(query: str):
-    """Call to surf the web."""
-    # This is a placeholder, but don't tell the LLM that...
-    if "sf" in query.lower() or "san francisco" in query.lower():
-        return "It's 60 degrees and foggy."
-    return "It's 90 degrees and sunny."
-
-tools = [search]
-model = ChatAnthropic(model="claude-3-7-sonnet-latest")
-
-app = create_react_agent(model, tools)
-# run the agent
-app.invoke(
-    {"messages": [{"role": "user", "content": "what is the weather in sf"}]},
-)
-```
-
-## Tools
-
-### ToolNode
-
-`langgraph-prebuilt` provides an [implementation](https://langchain-ai.github.io/langgraph/reference/prebuilt/#langgraph.prebuilt.tool_node.ToolNode) of a node that executes tool calls - `ToolNode`:
-
-```python
-from langgraph.prebuilt import ToolNode
-from langchain_core.messages import AIMessage
-
-def search(query: str):
-    """Call to surf the web."""
-    # This is a placeholder, but don't tell the LLM that...
-    if "sf" in query.lower() or "san francisco" in query.lower():
-        return "It's 60 degrees and foggy."
-    return "It's 90 degrees and sunny."
-
-tool_node = ToolNode([search])
-tool_calls = [{"name": "search", "args": {"query": "what is the weather in sf"}, "id": "1"}]
-ai_message = AIMessage(content="", tool_calls=tool_calls)
-# execute tool call
-tool_node.invoke({"messages": [ai_message]})
-```
-
-### ValidationNode
-
-`langgraph-prebuilt` provides an [implementation](https://langchain-ai.github.io/langgraph/reference/prebuilt/#langgraph.prebuilt.tool_validator.ValidationNode) of a node that validates tool calls against a pydantic schema - `ValidationNode`:
-
-```python
-from pydantic import BaseModel, field_validator
-from langgraph.prebuilt import ValidationNode
-from langchain_core.messages import AIMessage
-
-
-class SelectNumber(BaseModel):
-    a: int
-
-    @field_validator("a")
-    def a_must_be_meaningful(cls, v):
-        if v != 37:
-            raise ValueError("Only 37 is allowed")
-        return v
-
-validation_node = ValidationNode([SelectNumber])
-validation_node.invoke({
-    "messages": [AIMessage("", tool_calls=[{"name": "SelectNumber", "args": {"a": 42}, "id": "1"}])]
-})
-```
-
-## Agent Inbox
-
-The library contains schemas for using the [Agent Inbox](https://github.com/langchain-ai/agent-inbox) with LangGraph agents. Learn more about how to use Agent Inbox [here](https://github.com/langchain-ai/agent-inbox#interrupts).
-
-```python
-from langgraph.types import interrupt
-from langgraph.prebuilt.interrupt import HumanInterrupt, HumanResponse
-
-def my_graph_function():
-    # Extract the last tool call from the `messages` field in the state
-    tool_call = state["messages"][-1].tool_calls[0]
-    # Create an interrupt
-    request: HumanInterrupt = {
-        "action_request": {
-            "action": tool_call['name'],
-            "args": tool_call['args']
-        },
-        "config": {
-            "allow_ignore": True,
-            "allow_respond": True,
-            "allow_edit": False,
-            "allow_accept": False
-        },
-        "description": _generate_email_markdown(state) # Generate a detailed markdown description.
-    }
-    # Send the interrupt request inside a list, and extract the first response
-    response = interrupt([request])[0]
-    if response['type'] == "response":
-        # Do something with the response
-    ...
-```
@@ -1,62 +0,0 @@
-[tool.poetry]
-name = "langgraph-prebuilt"
-version = "0.1.2"
-description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
-authors = []
-license = "MIT"
-readme = "README.md"
-repository = "https://www.github.com/langchain-ai/langgraph"
-packages = [{ include = "langgraph" }]
-
-[tool.poetry.dependencies]
-python = "^3.9.0,<4.0"
-langgraph-checkpoint = "^2.0.10"
-langchain-core = ">=0.2.43,<0.4.0,!=0.3.0,!=0.3.1,!=0.3.2,!=0.3.3,!=0.3.4,!=0.3.5,!=0.3.6,!=0.3.7,!=0.3.8,!=0.3.9,!=0.3.10,!=0.3.11,!=0.3.12,!=0.3.13,!=0.3.14,!=0.3.15,!=0.3.16,!=0.3.17,!=0.3.18,!=0.3.19,!=0.3.20,!=0.3.21,!=0.3.22"
-
-[tool.poetry.group.dev.dependencies]
-ruff = "^0.6.2"
-codespell = "^2.2.0"
-pytest = "^7.2.1"
-pytest-asyncio = "^0.21.1"
-pytest-mock = "^3.11.1"
-pytest-watcher = "^0.4.1"
-mypy = "^1.10.0"
-langgraph = {path = "../langgraph", develop = true}
-langgraph-checkpoint = {path = "../checkpoint", develop = true}
-langgraph-checkpoint-sqlite = {path = "../checkpoint-sqlite", develop = true}
-langgraph-checkpoint-postgres = {path = "../checkpoint-postgres", develop = true}
-
-[tool.pytest.ini_options]
-# --strict-markers will raise errors on unknown marks.
-# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks
-#
-# https://docs.pytest.org/en/7.1.x/reference/reference.html
-# --strict-config       any warnings encountered while parsing the `pytest`
-#                       section of the configuration file raise errors.
-addopts = "--strict-markers --strict-config --durations=5 -vv"
-asyncio_mode = "auto"
-
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
-
-[tool.ruff]
-lint.select = [ "E", "F", "I", "TID251" ]
-lint.ignore = [ "E501" ]
-
-[tool.pytest-watcher]
-now = true
-delay = 0.1
-runner_args = ["--ff", "-v", "--tb", "short"]
-patterns = ["*.py"]
-
-[tool.mypy]
-# https://mypy.readthedocs.io/en/stable/config_file.html
-disallow_untyped_defs = "True"
-explicit_package_bases = "True"
-warn_no_return = "False"
-warn_unused_ignores = "True"
-warn_redundant_casts = "True"
-allow_redefinition = "True"
-disable_error_code = "typeddict-item, return-value"
@@ -1,86 +0,0 @@
-import re
-from typing import Any, Sequence, Union
-
-from typing_extensions import Self
-
-
-class FloatBetween(float):
-    def __new__(cls, min_value: float, max_value: float) -> Self:
-        return super().__new__(cls, min_value)
-
-    def __init__(self, min_value: float, max_value: float) -> None:
-        super().__init__()
-        self.min_value = min_value
-        self.max_value = max_value
-
-    def __eq__(self, other: object) -> bool:
-        return (
-            isinstance(other, float)
-            and other >= self.min_value
-            and other <= self.max_value
-        )
-
-    def __hash__(self) -> int:
-        return hash((float(self), self.min_value, self.max_value))
-
-
-class AnyStr(str):
-    def __init__(self, prefix: Union[str, re.Pattern] = "") -> None:
-        super().__init__()
-        self.prefix = prefix
-
-    def __eq__(self, other: object) -> bool:
-        return isinstance(other, str) and (
-            other.startswith(self.prefix)
-            if isinstance(self.prefix, str)
-            else self.prefix.match(other)
-        )
-
-    def __hash__(self) -> int:
-        return hash((str(self), self.prefix))
-
-
-class AnyDict(dict):
-    def __init__(self, *args, **kwargs) -> None:
-        super().__init__(*args, **kwargs)
-
-    def __eq__(self, other: object) -> bool:
-        if not isinstance(other, dict) or len(self) != len(other):
-            return False
-        for k, v in self.items():
-            if kk := next((kk for kk in other if kk == k), None):
-                if v == other[kk]:
-                    continue
-                else:
-                    return False
-        else:
-            return True
-
-
-class AnyVersion:
-    def __init__(self) -> None:
-        super().__init__()
-
-    def __eq__(self, other: object) -> bool:
-        return isinstance(other, (str, int, float))
-
-    def __hash__(self) -> int:
-        return hash(str(self))
-
-
-class UnsortedSequence:
-    def __init__(self, *values: Any) -> None:
-        self.seq = values
-
-    def __eq__(self, value: object) -> bool:
-        return (
-            isinstance(value, Sequence)
-            and len(self.seq) == len(value)
-            and all(a in value for a in self.seq)
-        )
-
-    def __hash__(self) -> int:
-        return hash(frozenset(self.seq))
-
-    def __repr__(self) -> str:
-        return repr(self.seq)
@@ -1,17 +0,0 @@
-name: langgraph-tests
-services:
-  postgres-test:
-    image: postgres:16
-    ports:
-      - "5442:5432"
-    environment:
-      POSTGRES_DB: postgres
-      POSTGRES_USER: postgres
-      POSTGRES_PASSWORD: postgres
-    healthcheck:
-      test: pg_isready -U postgres
-      start_period: 10s
-      timeout: 1s
-      retries: 5
-      interval: 60s
-      start_interval: 1s
@@ -1,448 +0,0 @@
-import sys
-from contextlib import asynccontextmanager
-from typing import AsyncIterator, Optional
-from uuid import UUID, uuid4
-
-import pytest
-from langchain_core import __version__ as core_version
-from packaging import version
-from psycopg import AsyncConnection, Connection
-from psycopg_pool import AsyncConnectionPool, ConnectionPool
-from pytest_mock import MockerFixture
-
-from langgraph.checkpoint.base import BaseCheckpointSaver
-from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver
-from langgraph.checkpoint.postgres.aio import (
-    AsyncPostgresSaver,
-    AsyncShallowPostgresSaver,
-)
-from langgraph.checkpoint.sqlite import SqliteSaver
-from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
-from langgraph.store.base import BaseStore
-from langgraph.store.memory import InMemoryStore
-from langgraph.store.postgres import AsyncPostgresStore, PostgresStore
-
-pytest.register_assert_rewrite("tests.memory_assert")
-
-DEFAULT_POSTGRES_URI = "postgres://postgres:postgres@localhost:5442/"
-# TODO: fix this once core is released
-IS_LANGCHAIN_CORE_030_OR_GREATER = version.parse(core_version) >= version.parse(
-    "0.3.0.dev0"
-)
-
-
-@pytest.fixture
-def anyio_backend():
-    return "asyncio"
-
-
-@pytest.fixture()
-def deterministic_uuids(mocker: MockerFixture) -> MockerFixture:
-    side_effect = (
-        UUID(f"00000000-0000-4000-8000-{i:012}", version=4) for i in range(10000)
-    )
-    return mocker.patch("uuid.uuid4", side_effect=side_effect)
-
-
-# checkpointer fixtures
-
-
-@pytest.fixture(scope="function")
-def checkpointer_memory():
-    from tests.memory_assert import MemorySaverAssertImmutable
-
-    yield MemorySaverAssertImmutable()
-
-
-@pytest.fixture(scope="function")
-def checkpointer_sqlite():
-    with SqliteSaver.from_conn_string(":memory:") as checkpointer:
-        yield checkpointer
-
-
-@asynccontextmanager
-async def _checkpointer_sqlite_aio():
-    async with AsyncSqliteSaver.from_conn_string(":memory:") as checkpointer:
-        yield checkpointer
-
-
-@pytest.fixture(scope="function")
-def checkpointer_postgres():
-    database = f"test_{uuid4().hex[:16]}"
-    # create unique db
-    with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-        conn.execute(f"CREATE DATABASE {database}")
-    try:
-        # yield checkpointer
-        with PostgresSaver.from_conn_string(
-            DEFAULT_POSTGRES_URI + database
-        ) as checkpointer:
-            checkpointer.setup()
-            yield checkpointer
-    finally:
-        # drop unique db
-        with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-            conn.execute(f"DROP DATABASE {database}")
-
-
-@pytest.fixture(scope="function")
-def checkpointer_postgres_shallow():
-    database = f"test_{uuid4().hex[:16]}"
-    # create unique db
-    with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-        conn.execute(f"CREATE DATABASE {database}")
-    try:
-        # yield checkpointer
-        with ShallowPostgresSaver.from_conn_string(
-            DEFAULT_POSTGRES_URI + database
-        ) as checkpointer:
-            checkpointer.setup()
-            yield checkpointer
-    finally:
-        # drop unique db
-        with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-            conn.execute(f"DROP DATABASE {database}")
-
-
-@pytest.fixture(scope="function")
-def checkpointer_postgres_pipe():
-    database = f"test_{uuid4().hex[:16]}"
-    # create unique db
-    with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-        conn.execute(f"CREATE DATABASE {database}")
-    try:
-        # yield checkpointer
-        with PostgresSaver.from_conn_string(
-            DEFAULT_POSTGRES_URI + database
-        ) as checkpointer:
-            checkpointer.setup()
-            # setup can't run inside pipeline because of implicit transaction
-            with checkpointer.conn.pipeline() as pipe:
-                checkpointer.pipe = pipe
-                yield checkpointer
-    finally:
-        # drop unique db
-        with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-            conn.execute(f"DROP DATABASE {database}")
-
-
-@pytest.fixture(scope="function")
-def checkpointer_postgres_pool():
-    database = f"test_{uuid4().hex[:16]}"
-    # create unique db
-    with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-        conn.execute(f"CREATE DATABASE {database}")
-    try:
-        # yield checkpointer
-        with ConnectionPool(
-            DEFAULT_POSTGRES_URI + database, max_size=10, kwargs={"autocommit": True}
-        ) as pool:
-            checkpointer = PostgresSaver(pool)
-            checkpointer.setup()
-            yield checkpointer
-    finally:
-        # drop unique db
-        with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-            conn.execute(f"DROP DATABASE {database}")
-
-
-@asynccontextmanager
-async def _checkpointer_postgres_aio():
-    if sys.version_info < (3, 10):
-        pytest.skip("Async Postgres tests require Python 3.10+")
-    database = f"test_{uuid4().hex[:16]}"
-    # create unique db
-    async with await AsyncConnection.connect(
-        DEFAULT_POSTGRES_URI, autocommit=True
-    ) as conn:
-        await conn.execute(f"CREATE DATABASE {database}")
-    try:
-        # yield checkpointer
-        async with AsyncPostgresSaver.from_conn_string(
-            DEFAULT_POSTGRES_URI + database
-        ) as checkpointer:
-            await checkpointer.setup()
-            yield checkpointer
-    finally:
-        # drop unique db
-        async with await AsyncConnection.connect(
-            DEFAULT_POSTGRES_URI, autocommit=True
-        ) as conn:
-            await conn.execute(f"DROP DATABASE {database}")
-
-
-@asynccontextmanager
-async def _checkpointer_postgres_aio_shallow():
-    if sys.version_info < (3, 10):
-        pytest.skip("Async Postgres tests require Python 3.10+")
-    database = f"test_{uuid4().hex[:16]}"
-    # create unique db
-    async with await AsyncConnection.connect(
-        DEFAULT_POSTGRES_URI, autocommit=True
-    ) as conn:
-        await conn.execute(f"CREATE DATABASE {database}")
-    try:
-        # yield checkpointer
-        async with AsyncShallowPostgresSaver.from_conn_string(
-            DEFAULT_POSTGRES_URI + database
-        ) as checkpointer:
-            await checkpointer.setup()
-            yield checkpointer
-    finally:
-        # drop unique db
-        async with await AsyncConnection.connect(
-            DEFAULT_POSTGRES_URI, autocommit=True
-        ) as conn:
-            await conn.execute(f"DROP DATABASE {database}")
-
-
-@asynccontextmanager
-async def _checkpointer_postgres_aio_pipe():
-    if sys.version_info < (3, 10):
-        pytest.skip("Async Postgres tests require Python 3.10+")
-    database = f"test_{uuid4().hex[:16]}"
-    # create unique db
-    async with await AsyncConnection.connect(
-        DEFAULT_POSTGRES_URI, autocommit=True
-    ) as conn:
-        await conn.execute(f"CREATE DATABASE {database}")
-    try:
-        # yield checkpointer
-        async with AsyncPostgresSaver.from_conn_string(
-            DEFAULT_POSTGRES_URI + database
-        ) as checkpointer:
-            await checkpointer.setup()
-            # setup can't run inside pipeline because of implicit transaction
-            async with checkpointer.conn.pipeline() as pipe:
-                checkpointer.pipe = pipe
-                yield checkpointer
-    finally:
-        # drop unique db
-        async with await AsyncConnection.connect(
-            DEFAULT_POSTGRES_URI, autocommit=True
-        ) as conn:
-            await conn.execute(f"DROP DATABASE {database}")
-
-
-@asynccontextmanager
-async def _checkpointer_postgres_aio_pool():
-    if sys.version_info < (3, 10):
-        pytest.skip("Async Postgres tests require Python 3.10+")
-    database = f"test_{uuid4().hex[:16]}"
-    # create unique db
-    async with await AsyncConnection.connect(
-        DEFAULT_POSTGRES_URI, autocommit=True
-    ) as conn:
-        await conn.execute(f"CREATE DATABASE {database}")
-    try:
-        # yield checkpointer
-        async with AsyncConnectionPool(
-            DEFAULT_POSTGRES_URI + database, max_size=10, kwargs={"autocommit": True}
-        ) as pool:
-            checkpointer = AsyncPostgresSaver(pool)
-            await checkpointer.setup()
-            yield checkpointer
-    finally:
-        # drop unique db
-        async with await AsyncConnection.connect(
-            DEFAULT_POSTGRES_URI, autocommit=True
-        ) as conn:
-            await conn.execute(f"DROP DATABASE {database}")
-
-
-@asynccontextmanager
-async def awith_checkpointer(
-    checkpointer_name: Optional[str],
-) -> AsyncIterator[BaseCheckpointSaver]:
-    if checkpointer_name is None:
-        yield None
-    elif checkpointer_name == "memory":
-        from tests.memory_assert import MemorySaverAssertImmutable
-
-        yield MemorySaverAssertImmutable()
-    elif checkpointer_name == "sqlite_aio":
-        async with _checkpointer_sqlite_aio() as checkpointer:
-            yield checkpointer
-    elif checkpointer_name == "postgres_aio":
-        async with _checkpointer_postgres_aio() as checkpointer:
-            yield checkpointer
-    elif checkpointer_name == "postgres_aio_shallow":
-        async with _checkpointer_postgres_aio_shallow() as checkpointer:
-            yield checkpointer
-    elif checkpointer_name == "postgres_aio_pipe":
-        async with _checkpointer_postgres_aio_pipe() as checkpointer:
-            yield checkpointer
-    elif checkpointer_name == "postgres_aio_pool":
-        async with _checkpointer_postgres_aio_pool() as checkpointer:
-            yield checkpointer
-    else:
-        raise NotImplementedError(f"Unknown checkpointer: {checkpointer_name}")
-
-
-@asynccontextmanager
-async def _store_postgres_aio():
-    if sys.version_info < (3, 10):
-        pytest.skip("Async Postgres tests require Python 3.10+")
-    database = f"test_{uuid4().hex[:16]}"
-    async with await AsyncConnection.connect(
-        DEFAULT_POSTGRES_URI, autocommit=True
-    ) as conn:
-        await conn.execute(f"CREATE DATABASE {database}")
-    try:
-        async with AsyncPostgresStore.from_conn_string(
-            DEFAULT_POSTGRES_URI + database
-        ) as store:
-            await store.setup()
-            yield store
-    finally:
-        async with await AsyncConnection.connect(
-            DEFAULT_POSTGRES_URI, autocommit=True
-        ) as conn:
-            await conn.execute(f"DROP DATABASE {database}")
-
-
-@asynccontextmanager
-async def _store_postgres_aio_pipe():
-    if sys.version_info < (3, 10):
-        pytest.skip("Async Postgres tests require Python 3.10+")
-    database = f"test_{uuid4().hex[:16]}"
-    async with await AsyncConnection.connect(
-        DEFAULT_POSTGRES_URI, autocommit=True
-    ) as conn:
-        await conn.execute(f"CREATE DATABASE {database}")
-    try:
-        async with AsyncPostgresStore.from_conn_string(
-            DEFAULT_POSTGRES_URI + database
-        ) as store:
-            await store.setup()  # Run in its own transaction
-        async with AsyncPostgresStore.from_conn_string(
-            DEFAULT_POSTGRES_URI + database, pipeline=True
-        ) as store:
-            yield store
-    finally:
-        async with await AsyncConnection.connect(
-            DEFAULT_POSTGRES_URI, autocommit=True
-        ) as conn:
-            await conn.execute(f"DROP DATABASE {database}")
-
-
-@asynccontextmanager
-async def _store_postgres_aio_pool():
-    if sys.version_info < (3, 10):
-        pytest.skip("Async Postgres tests require Python 3.10+")
-    database = f"test_{uuid4().hex[:16]}"
-    async with await AsyncConnection.connect(
-        DEFAULT_POSTGRES_URI, autocommit=True
-    ) as conn:
-        await conn.execute(f"CREATE DATABASE {database}")
-    try:
-        async with AsyncPostgresStore.from_conn_string(
-            DEFAULT_POSTGRES_URI + database,
-            pool_config={"max_size": 10},
-        ) as store:
-            await store.setup()
-            yield store
-    finally:
-        async with await AsyncConnection.connect(
-            DEFAULT_POSTGRES_URI, autocommit=True
-        ) as conn:
-            await conn.execute(f"DROP DATABASE {database}")
-
-
-@pytest.fixture(scope="function")
-def store_postgres():
-    database = f"test_{uuid4().hex[:16]}"
-    # create unique db
-    with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-        conn.execute(f"CREATE DATABASE {database}")
-    try:
-        # yield store
-        with PostgresStore.from_conn_string(DEFAULT_POSTGRES_URI + database) as store:
-            store.setup()
-            yield store
-    finally:
-        # drop unique db
-        with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-            conn.execute(f"DROP DATABASE {database}")
-
-
-@pytest.fixture(scope="function")
-def store_postgres_pipe():
-    database = f"test_{uuid4().hex[:16]}"
-    # create unique db
-    with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-        conn.execute(f"CREATE DATABASE {database}")
-    try:
-        # yield store
-        with PostgresStore.from_conn_string(DEFAULT_POSTGRES_URI + database) as store:
-            store.setup()  # Run in its own transaction
-        with PostgresStore.from_conn_string(
-            DEFAULT_POSTGRES_URI + database, pipeline=True
-        ) as store:
-            yield store
-    finally:
-        # drop unique db
-        with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-            conn.execute(f"DROP DATABASE {database}")
-
-
-@pytest.fixture(scope="function")
-def store_postgres_pool():
-    database = f"test_{uuid4().hex[:16]}"
-    # create unique db
-    with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-        conn.execute(f"CREATE DATABASE {database}")
-    try:
-        # yield store
-        with PostgresStore.from_conn_string(
-            DEFAULT_POSTGRES_URI + database, pool_config={"max_size": 10}
-        ) as store:
-            store.setup()
-            yield store
-    finally:
-        # drop unique db
-        with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
-            conn.execute(f"DROP DATABASE {database}")
-
-
-@pytest.fixture(scope="function")
-def store_in_memory():
-    yield InMemoryStore()
-
-
-@asynccontextmanager
-async def awith_store(store_name: Optional[str]) -> AsyncIterator[BaseStore]:
-    if store_name is None:
-        yield None
-    elif store_name == "in_memory":
-        yield InMemoryStore()
-    elif store_name == "postgres_aio":
-        async with _store_postgres_aio() as store:
-            yield store
-    elif store_name == "postgres_aio_pipe":
-        async with _store_postgres_aio_pipe() as store:
-            yield store
-    elif store_name == "postgres_aio_pool":
-        async with _store_postgres_aio_pool() as store:
-            yield store
-    else:
-        raise NotImplementedError(f"Unknown store {store_name}")
-
-
-ALL_CHECKPOINTERS_SYNC = [
-    "memory",
-    "sqlite",
-    "postgres",
-    "postgres_pipe",
-    "postgres_pool",
-    "postgres_shallow",
-]
-
-ALL_CHECKPOINTERS_ASYNC = [
-    "memory",
-    "sqlite_aio",
-    "postgres_aio",
-    "postgres_aio_pipe",
-    "postgres_aio_pool",
-    "postgres_aio_shallow",
-]
@@ -1,134 +0,0 @@
-import asyncio
-import os
-import tempfile
-from collections import defaultdict
-from functools import partial
-from typing import Any, Optional
-
-from langchain_core.runnables import RunnableConfig
-
-from langgraph.checkpoint.base import (
-    ChannelVersions,
-    Checkpoint,
-    CheckpointMetadata,
-    CheckpointTuple,
-    SerializerProtocol,
-    copy_checkpoint,
-)
-from langgraph.checkpoint.memory import InMemorySaver, PersistentDict
-
-
-class NoopSerializer(SerializerProtocol):
-    def loads_typed(self, data: tuple[str, bytes]) -> Any:
-        return data[1]
-
-    def dumps_typed(self, obj: Any) -> tuple[str, bytes]:
-        return "type", obj
-
-
-class MemorySaverAssertImmutable(InMemorySaver):
-    storage_for_copies: defaultdict[str, dict[str, dict[str, Checkpoint]]]
-
-    def __init__(
-        self,
-        *,
-        serde: Optional[SerializerProtocol] = None,
-        put_sleep: Optional[float] = None,
-    ) -> None:
-        _, filename = tempfile.mkstemp()
-        super().__init__(
-            serde=serde, factory=partial(PersistentDict, filename=filename)
-        )
-        self.storage_for_copies = defaultdict(lambda: defaultdict(dict))
-        self.put_sleep = put_sleep
-        self.stack.callback(os.remove, filename)
-
-    def put(
-        self,
-        config: dict,
-        checkpoint: Checkpoint,
-        metadata: CheckpointMetadata,
-        new_versions: ChannelVersions,
-    ) -> None:
-        if self.put_sleep:
-            import time
-
-            time.sleep(self.put_sleep)
-        # assert checkpoint hasn't been modified since last written
-        thread_id = config["configurable"]["thread_id"]
-        checkpoint_ns = config["configurable"]["checkpoint_ns"]
-        if saved := super().get(config):
-            assert (
-                self.serde.loads_typed(
-                    self.storage_for_copies[thread_id][checkpoint_ns][saved["id"]]
-                )
-                == saved
-            )
-        self.storage_for_copies[thread_id][checkpoint_ns][checkpoint["id"]] = (
-            self.serde.dumps_typed(copy_checkpoint(checkpoint))
-        )
-        # call super to write checkpoint
-        return super().put(config, checkpoint, metadata, new_versions)
-
-
-class MemorySaverAssertCheckpointMetadata(InMemorySaver):
-    """This custom checkpointer is for verifying that a run's configurable
-    fields are merged with the previous checkpoint config for each step in
-    the run. This is the desired behavior. Because the checkpointer's (a)put()
-    method is called for each step, the implementation of this checkpointer
-    should produce a side effect that can be asserted.
-    """
-
-    def put(
-        self,
-        config: RunnableConfig,
-        checkpoint: Checkpoint,
-        metadata: CheckpointMetadata,
-        new_versions: ChannelVersions,
-    ) -> None:
-        """The implementation of put() merges config["configurable"] (a run's
-        configurable fields) with the metadata field. The state of the
-        checkpoint metadata can be asserted to confirm that the run's
-        configurable fields were merged with the previous checkpoint config.
-        """
-        configurable = config["configurable"].copy()
-
-        # remove checkpoint_id to make testing simpler
-        checkpoint_id = configurable.pop("checkpoint_id", None)
-        thread_id = config["configurable"]["thread_id"]
-        checkpoint_ns = config["configurable"]["checkpoint_ns"]
-        self.storage[thread_id][checkpoint_ns].update(
-            {
-                checkpoint["id"]: (
-                    self.serde.dumps_typed(checkpoint),
-                    # merge configurable fields and metadata
-                    self.serde.dumps_typed({**configurable, **metadata}),
-                    checkpoint_id,
-                )
-            }
-        )
-        return {
-            "configurable": {
-                "thread_id": config["configurable"]["thread_id"],
-                "checkpoint_id": checkpoint["id"],
-            }
-        }
-
-    async def aput(
-        self,
-        config: RunnableConfig,
-        checkpoint: Checkpoint,
-        metadata: CheckpointMetadata,
-        new_versions: ChannelVersions,
-    ) -> RunnableConfig:
-        return await asyncio.get_running_loop().run_in_executor(
-            None, self.put, config, checkpoint, metadata, new_versions
-        )
-
-
-class MemorySaverNoPending(InMemorySaver):
-    def get_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
-        result = super().get_tuple(config)
-        if result:
-            return CheckpointTuple(result.config, result.checkpoint, result.metadata)
-        return result
@@ -1,50 +0,0 @@
-"""Redefined messages as a work-around for pydantic issue with AnyStr.
-
-The code below creates version of pydantic models
-that will work in unit tests with AnyStr as id field
-Please note that the `id` field is assigned AFTER the model is created
-to workaround an issue with pydantic ignoring the __eq__ method on
-subclassed strings.
-"""
-
-from typing import Any
-
-from langchain_core.documents import Document
-from langchain_core.messages import AIMessage, AIMessageChunk, HumanMessage, ToolMessage
-
-from tests.any_str import AnyStr
-
-
-def _AnyIdDocument(**kwargs: Any) -> Document:
-    """Create a document with an id field."""
-    message = Document(**kwargs)
-    message.id = AnyStr()
-    return message
-
-
-def _AnyIdAIMessage(**kwargs: Any) -> AIMessage:
-    """Create ai message with an any id field."""
-    message = AIMessage(**kwargs)
-    message.id = AnyStr()
-    return message
-
-
-def _AnyIdAIMessageChunk(**kwargs: Any) -> AIMessageChunk:
-    """Create ai message with an any id field."""
-    message = AIMessageChunk(**kwargs)
-    message.id = AnyStr()
-    return message
-
-
-def _AnyIdHumanMessage(**kwargs: Any) -> HumanMessage:
-    """Create a human message with an any id field."""
-    message = HumanMessage(**kwargs)
-    message.id = AnyStr()
-    return message
-
-
-def _AnyIdToolMessage(**kwargs: Any) -> ToolMessage:
-    """Create a tool message with an any id field."""
-    message = ToolMessage(**kwargs)
-    message.id = AnyStr()
-    return message
@@ -1,98 +0,0 @@
-from typing import (
-    Any,
-    Callable,
-    Dict,
-    List,
-    Literal,
-    Optional,
-    Sequence,
-    Type,
-    Union,
-)
-
-from langchain_core.callbacks import CallbackManagerForLLMRun
-from langchain_core.language_models import BaseChatModel, LanguageModelInput
-from langchain_core.messages import (
-    AIMessage,
-    BaseMessage,
-    ToolCall,
-)
-from langchain_core.outputs import ChatGeneration, ChatResult
-from langchain_core.runnables import Runnable, RunnableLambda
-from langchain_core.tools import BaseTool
-from pydantic import BaseModel
-
-from langgraph.prebuilt.chat_agent_executor import StructuredResponse
-
-
-class FakeToolCallingModel(BaseChatModel):
-    tool_calls: Optional[list[list[ToolCall]]] = None
-    structured_response: Optional[StructuredResponse] = None
-    index: int = 0
-    tool_style: Literal["openai", "anthropic"] = "openai"
-
-    def _generate(
-        self,
-        messages: List[BaseMessage],
-        stop: Optional[List[str]] = None,
-        run_manager: Optional[CallbackManagerForLLMRun] = None,
-        **kwargs: Any,
-    ) -> ChatResult:
-        """Top Level call"""
-        messages_string = "-".join([m.content for m in messages])
-        tool_calls = (
-            self.tool_calls[self.index % len(self.tool_calls)]
-            if self.tool_calls
-            else []
-        )
-        message = AIMessage(
-            content=messages_string, id=str(self.index), tool_calls=tool_calls.copy()
-        )
-        self.index += 1
-        return ChatResult(generations=[ChatGeneration(message=message)])
-
-    @property
-    def _llm_type(self) -> str:
-        return "fake-tool-call-model"
-
-    def with_structured_output(
-        self, schema: Type[BaseModel]
-    ) -> Runnable[LanguageModelInput, StructuredResponse]:
-        if self.structured_response is None:
-            raise ValueError("Structured response is not set")
-
-        return RunnableLambda(lambda x: self.structured_response)
-
-    def bind_tools(
-        self,
-        tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
-        **kwargs: Any,
-    ) -> Runnable[LanguageModelInput, BaseMessage]:
-        if len(tools) == 0:
-            raise ValueError("Must provide at least one tool")
-
-        tool_dicts = []
-        for tool in tools:
-            if not isinstance(tool, BaseTool):
-                raise TypeError(
-                    "Only BaseTool is supported by FakeToolCallingModel.bind_tools"
-                )
-
-            # NOTE: this is a simplified tool spec for testing purposes only
-            if self.tool_style == "openai":
-                tool_dicts.append(
-                    {
-                        "type": "function",
-                        "function": {
-                            "name": tool.name,
-                        },
-                    }
-                )
-            elif self.tool_style == "anthropic":
-                tool_dicts.append(
-                    {
-                        "name": tool.name,
-                    }
-                )
-
-        return self.bind(tools=tool_dicts)
@@ -1,81 +0,0 @@
-from typing import Any
-
-import pytest
-from langchain_core.messages import AIMessage
-from langchain_core.tools import tool as dec_tool
-from pydantic import BaseModel
-from pydantic.v1 import BaseModel as BaseModelV1
-
-from langgraph.prebuilt import ValidationNode
-
-pytestmark = pytest.mark.anyio
-
-
-def my_function(some_val: int, some_other_val: str) -> str:
-    return f"{some_val} - {some_other_val}"
-
-
-class MyModel(BaseModel):
-    some_val: int
-    some_other_val: str
-
-
-class MyModelV1(BaseModelV1):
-    some_val: int
-    some_other_val: str
-
-
-@dec_tool
-def my_tool(some_val: int, some_other_val: str) -> str:
-    """Cool."""
-    return f"{some_val} - {some_other_val}"
-
-
-@pytest.mark.parametrize(
-    "tool_schema",
-    [
-        my_function,
-        MyModel,
-        MyModelV1,
-        my_tool,
-    ],
-)
-@pytest.mark.parametrize("use_message_key", [True, False])
-async def test_validation_node(tool_schema: Any, use_message_key: bool):
-    validation_node = ValidationNode([tool_schema])
-    tool_name = getattr(tool_schema, "name", getattr(tool_schema, "__name__", None))
-    inputs = [
-        AIMessage(
-            "hi?",
-            tool_calls=[
-                {
-                    "name": tool_name,
-                    "args": {"some_val": 1, "some_other_val": "foo"},
-                    "id": "some 0",
-                },
-                {
-                    "name": tool_name,
-                    # Wrong type for some_val
-                    "args": {"some_val": "bar", "some_other_val": "foo"},
-                    "id": "some 1",
-                },
-            ],
-        ),
-    ]
-    if use_message_key:
-        inputs = {"messages": inputs}
-    result = await validation_node.ainvoke(inputs)
-    if use_message_key:
-        result = result["messages"]
-
-    def check_results(messages: list):
-        assert len(messages) == 2
-        assert all(m.type == "tool" for m in messages)
-        assert not messages[0].additional_kwargs.get("is_error")
-        assert messages[1].additional_kwargs.get("is_error")
-
-    check_results(result)
-    result_sync = validation_node.invoke(inputs)
-    if use_message_key:
-        result_sync = result_sync["messages"]
-    check_results(result_sync)
@@ -10,14 +10,6 @@ react.cjs
 react.js
 react.d.ts
 react.d.cts
-react-ui.cjs
-react-ui.js
-react-ui.d.ts
-react-ui.d.cts
-react-ui/server.cjs
-react-ui/server.js
-react-ui/server.d.ts
-react-ui/server.d.cts
 node_modules
 dist
 .yarn
@@ -11,13 +11,7 @@ function abs(relativePath) {

 export const config = {
  internals: [/react/],
-  entrypoints: {
-    index: "index",
-    client: "client",
-    react: "react/index",
-    "react-ui": "react-ui/index",
-    "react-ui/server": "react-ui/server/index",
-  },
+  entrypoints: { index: "index", client: "client", react: "react/index" },
  tsConfigPath: resolve("./tsconfig.json"),
  cjsSource: "./dist-cjs",
  cjsDestination: "./dist",
@@ -1,13 +1,13 @@
 {
  "name": "@langchain/langgraph-sdk",
-  "version": "0.0.49",
+  "version": "0.0.46",
  "description": "Client library for interacting with the LangGraph API",
  "type": "module",
  "packageManager": "yarn@1.22.19",
  "scripts": {
    "clean": "rm -rf dist/ dist-cjs/",
    "build": "yarn clean && yarn lc_build --create-entrypoints --pre --tree-shaking",
-    "prepack": "yarn run build",
+    "prepublish": "yarn run build",
    "format": "prettier --write src",
    "lint": "prettier --check src && tsc --noEmit",
    "test": "NODE_OPTIONS=--experimental-vm-modules jest --testPathIgnorePatterns=\\.int\\.test.ts",
@@ -29,8 +29,7 @@
    "@types/jest": "^29.5.12",
    "@types/node": "^20.12.12",
    "@types/uuid": "^9.0.1",
-    "@types/react": "^19.0.8",
-    "@types/react-dom": "^19.0.3",
+    "@types/react": "18.3.2",
    "concat-md": "^0.5.1",
    "jest": "^29.7.0",
    "prettier": "^3.2.5",
@@ -38,8 +37,7 @@
    "typedoc": "^0.27.7",
    "typedoc-plugin-markdown": "^4.4.2",
    "typescript": "^5.4.5",
-    "react": "^19.0.0",
-    "react-dom": "^19.0.0"
+    "react": "^18.3.1"
  },
  "peerDependencies": {
    "react": "^18 || ^19",
@@ -81,24 +79,6 @@
      "import": "./react.js",
      "require": "./react.cjs"
    },
-    "./react-ui": {
-      "types": {
-        "import": "./react-ui.d.ts",
-        "require": "./react-ui.d.cts",
-        "default": "./react-ui.d.ts"
-      },
-      "import": "./react-ui.js",
-      "require": "./react-ui.cjs"
-    },
-    "./react-ui/server": {
-      "types": {
-        "import": "./react-ui/server.d.ts",
-        "require": "./react-ui/server.d.cts",
-        "default": "./react-ui/server.d.ts"
-      },
-      "import": "./react-ui/server.js",
-      "require": "./react-ui/server.cjs"
-    },
    "./package.json": "./package.json"
  },
  "files": [
@@ -114,14 +94,6 @@
    "react.cjs",
    "react.js",
    "react.d.ts",
-    "react.d.cts",
-    "react-ui.cjs",
-    "react-ui.js",
-    "react-ui.d.ts",
-    "react-ui.d.cts",
-    "react-ui/server.cjs",
-    "react-ui/server.js",
-    "react-ui/server.d.ts",
-    "react-ui/server.d.cts"
+    "react.d.cts"
  ]
 }
@@ -1088,28 +1088,12 @@ export class StoreClient extends BaseClient {
   * @param namespace A list of strings representing the namespace path.
   * @param key The unique identifier for the item within the namespace.
   * @param value A dictionary containing the item's data.
-   * @param options.index Controls search indexing - null (use defaults), false (disable), or list of field paths to index.
-   * @param options.ttl Optional time-to-live in minutes for the item, or null for no expiration.
   * @returns Promise<void>
-   *
-   * @example
-   * ```typescript
-   * await client.store.putItem(
-   *   ["documents", "user123"],
-   *   "item456",
-   *   { title: "My Document", content: "Hello World" },
-   *   { ttl: 60 } // expires in 60 minutes
-   * );
-   * ```
   */
  async putItem(
    namespace: string[],
    key: string,
    value: Record<string, any>,
-    options?: {
-      index?: false | string[] | null;
-      ttl?: number | null;
-    },
  ): Promise<void> {
    namespace.forEach((label) => {
      if (label.includes(".")) {
@@ -1123,8 +1107,6 @@ export class StoreClient extends BaseClient {
      namespace,
      key,
      value,
-      index: options?.index,
-      ttl: options?.ttl,
    };

    return this.fetch<void>("/store/items", {
@@ -1138,33 +1120,9 @@ export class StoreClient extends BaseClient {
   *
   * @param namespace A list of strings representing the namespace path.
   * @param key The unique identifier for the item.
-   * @param options.refreshTtl Whether to refresh the TTL on this read operation. If null, uses the store's default behavior.
   * @returns Promise<Item>
-   *
-   * @example
-   * ```typescript
-   * const item = await client.store.getItem(
-   *   ["documents", "user123"],
-   *   "item456",
-   *   { refreshTtl: true }
-   * );
-   * console.log(item);
-   * // {
-   * //   namespace: ["documents", "user123"],
-   * //   key: "item456",
-   * //   value: { title: "My Document", content: "Hello World" },
-   * //   createdAt: "2024-07-30T12:00:00Z",
-   * //   updatedAt: "2024-07-30T12:00:00Z"
-   * // }
-   * ```
   */
-  async getItem(
-    namespace: string[],
-    key: string,
-    options?: {
-      refreshTtl?: boolean | null;
-    },
-  ): Promise<Item | null> {
+  async getItem(namespace: string[], key: string): Promise<Item | null> {
    namespace.forEach((label) => {
      if (label.includes(".")) {
        throw new Error(
@@ -1173,17 +1131,8 @@ export class StoreClient extends BaseClient {
      }
    });

-    const params: Record<string, any> = {
-      namespace: namespace.join("."),
-      key,
-    };
-
-    if (options?.refreshTtl !== undefined) {
-      params.refresh_ttl = options.refreshTtl;
-    }
-
    const response = await this.fetch<APIItem>("/store/items", {
-      params,
+      params: { namespace: namespace.join("."), key },
    });

    return response
@@ -1225,33 +1174,7 @@ export class StoreClient extends BaseClient {
   * @param options.limit Maximum number of items to return (default is 10).
   * @param options.offset Number of items to skip before returning results (default is 0).
   * @param options.query Optional search query.
-   * @param options.refreshTtl Whether to refresh the TTL on items returned by this search. If null, uses the store's default behavior.
   * @returns Promise<SearchItemsResponse>
-   *
-   * @example
-   * ```typescript
-   * const results = await client.store.searchItems(
-   *   ["documents"],
-   *   {
-   *     filter: { author: "John Doe" },
-   *     limit: 5,
-   *     refreshTtl: true
-   *   }
-   * );
-   * console.log(results);
-   * // {
-   * //   items: [
-   * //     {
-   * //       namespace: ["documents", "user123"],
-   * //       key: "item789",
-   * //       value: { title: "Another Document", author: "John Doe" },
-   * //       createdAt: "2024-07-30T12:00:00Z",
-   * //       updatedAt: "2024-07-30T12:00:00Z"
-   * //     },
-   * //     // ... additional items ...
-   * //   ]
-   * // }
-   * ```
   */
  async searchItems(
    namespacePrefix: string[],
@@ -1260,7 +1183,6 @@ export class StoreClient extends BaseClient {
      limit?: number;
      offset?: number;
      query?: string;
-      refreshTtl?: boolean | null;
    },
  ): Promise<SearchItemsResponse> {
    const payload = {
@@ -1269,7 +1191,6 @@ export class StoreClient extends BaseClient {
      limit: options?.limit ?? 10,
      offset: options?.offset ?? 0,
      query: options?.query,
-      refresh_ttl: options?.refreshTtl,
    };

    const response = await this.fetch<APISearchItemsResponse>(
@@ -1,7 +1,6 @@
 export { Client } from "./client.js";

 export type {
-  AssistantBase,
  Assistant,
  AssistantVersion,
  AssistantGraph,
@@ -1,251 +0,0 @@
-import { useStream } from "../react/index.js";
-import type { UIMessage } from "./types.js";
-
-import * as React from "react";
-import * as ReactDOM from "react-dom";
-import * as JsxRuntime from "react/jsx-runtime";
-import type { UseStream } from "../react/stream.js";
-
-const UseStreamContext = React.createContext<{
-  stream: ReturnType<typeof useStream>;
-  meta: unknown;
-}>(null!);
-
-type BagTemplate = {
-  ConfigurableType?: Record<string, unknown>;
-  InterruptType?: unknown;
-  CustomEventType?: unknown;
-  UpdateType?: unknown;
-  MetaType?: unknown;
-};
-
-type GetMetaType<Bag extends BagTemplate> = Bag extends { MetaType: unknown }
-  ? Bag["MetaType"]
-  : unknown;
-
-interface UseStreamContext<
-  StateType extends Record<string, unknown> = Record<string, unknown>,
-  Bag extends BagTemplate = BagTemplate,
-> extends UseStream<StateType, Bag> {
-  meta?: GetMetaType<Bag>;
-}
-
-export function useStreamContext<
-  StateType extends Record<string, unknown> = Record<string, unknown>,
-  Bag extends {
-    ConfigurableType?: Record<string, unknown>;
-    InterruptType?: unknown;
-    CustomEventType?: unknown;
-    UpdateType?: unknown;
-    MetaType?: unknown;
-  } = BagTemplate,
->(): UseStreamContext<StateType, Bag> {
-  const ctx = React.useContext(UseStreamContext);
-  if (!ctx) {
-    throw new Error(
-      "useStreamContext must be used within a LoadExternalComponent",
-    );
-  }
-
-  return new Proxy(ctx, {
-    get(target, prop: keyof UseStreamContext<StateType, Bag>) {
-      if (prop === "meta") return target.meta;
-      return target.stream[prop];
-    },
-  }) as unknown as UseStreamContext<StateType, Bag>;
-}
-
-interface ComponentTarget {
-  comp: React.FunctionComponent | React.ComponentClass;
-  target: HTMLElement;
-}
-
-class ComponentStore {
-  private cache: Record<string, ComponentTarget> = {};
-  private boundCache: Record<
-    string,
-    {
-      subscribe: (onStoreChange: () => void) => () => void;
-      getSnapshot: () => ComponentTarget | undefined;
-    }
-  > = {};
-  private callbacks: Record<
-    string,
-    ((
-      comp: React.FunctionComponent | React.ComponentClass,
-      el: HTMLElement,
-    ) => void)[]
-  > = {};
-
-  respond(
-    shadowRootId: string,
-    comp: React.FunctionComponent | React.ComponentClass,
-    targetElement: HTMLElement,
-  ) {
-    this.cache[shadowRootId] = { comp, target: targetElement };
-    this.callbacks[shadowRootId]?.forEach((c) => c(comp, targetElement));
-  }
-
-  getBoundStore(shadowRootId: string) {
-    this.boundCache[shadowRootId] ??= {
-      subscribe: (onStoreChange: () => void) => {
-        this.callbacks[shadowRootId] ??= [];
-        this.callbacks[shadowRootId].push(onStoreChange);
-        return () => {
-          this.callbacks[shadowRootId] = this.callbacks[shadowRootId].filter(
-            (c) => c !== onStoreChange,
-          );
-        };
-      },
-      getSnapshot: () => this.cache[shadowRootId],
-    };
-
-    return this.boundCache[shadowRootId];
-  }
-}
-
-const COMPONENT_STORE = new ComponentStore();
-const COMPONENT_PROMISE_CACHE: Record<string, Promise<string> | undefined> = {};
-
-const EXT_STORE_SYMBOL = Symbol.for("LGUI_EXT_STORE");
-const REQUIRE_SYMBOL = Symbol.for("LGUI_REQUIRE");
-
-interface LoadExternalComponentProps
-  extends Pick<React.HTMLAttributes<HTMLDivElement>, "style" | "className"> {
-  /** API URL of the LangGraph Platform */
-  apiUrl?: string;
-
-  /** ID of the assistant */
-  assistantId: string;
-
-  /** Stream of the assistant */
-  stream: ReturnType<typeof useStream>;
-
-  /** UI message to be rendered */
-  message: UIMessage;
-
-  /** Additional context to be passed to the child component */
-  meta?: unknown;
-
-  /** Fallback to be rendered when the component is loading */
-  fallback?: React.ReactNode;
-
-  /**
-   * Map of components that can be rendered directly without fetching the UI code
-   * from the server.
-   */
-  components?: Record<string, React.FunctionComponent | React.ComponentClass>;
-}
-
-function fetchComponent(
-  apiUrl: string,
-  assistantId: string,
-  agentName: string,
-): Promise<string> {
-  const cacheKey = `${apiUrl}-${assistantId}-${agentName}`;
-  if (COMPONENT_PROMISE_CACHE[cacheKey] != null) {
-    return COMPONENT_PROMISE_CACHE[cacheKey] as Promise<string>;
-  }
-
-  const request: Promise<string> = fetch(`${apiUrl}/ui/${assistantId}`, {
-    headers: { Accept: "text/html", "Content-Type": "application/json" },
-    method: "POST",
-    body: JSON.stringify({ name: agentName }),
-  }).then((a) => a.text());
-
-  COMPONENT_PROMISE_CACHE[cacheKey] = request;
-  return request;
-}
-
-export function LoadExternalComponent({
-  apiUrl = "http://localhost:2024",
-  assistantId,
-  stream,
-  message,
-  meta,
-  fallback,
-  components,
-  ...props
-}: LoadExternalComponentProps) {
-  const ref = React.useRef<HTMLDivElement>(null);
-  const id = React.useId();
-  const shadowRootId = `child-shadow-${id}`;
-
-  const store = React.useMemo(
-    () => COMPONENT_STORE.getBoundStore(shadowRootId),
-    [shadowRootId],
-  );
-  const state = React.useSyncExternalStore(store.subscribe, store.getSnapshot);
-
-  const clientComponent = components?.[message.name];
-  const hasClientComponent = clientComponent != null;
-
-  React.useEffect(() => {
-    if (hasClientComponent) return;
-    fetchComponent(apiUrl, assistantId, message.name).then((html) => {
-      const dom = ref.current;
-      if (!dom) return;
-      const root = dom.shadowRoot ?? dom.attachShadow({ mode: "open" });
-      const fragment = document
-        .createRange()
-        .createContextualFragment(
-          html.replace("{{shadowRootId}}", shadowRootId),
-        );
-      root.appendChild(fragment);
-    });
-  }, [apiUrl, assistantId, message.name, shadowRootId, hasClientComponent]);
-
-  if (hasClientComponent) {
-    return React.createElement(clientComponent, message.content);
-  }
-
-  return (
-    <>
-      <div id={shadowRootId} ref={ref} {...props} />
-
-      <UseStreamContext.Provider value={{ stream, meta }}>
-        {state?.target != null
-          ? ReactDOM.createPortal(
-              React.createElement(state.comp, message.content),
-              state.target,
-            )
-          : fallback}
-      </UseStreamContext.Provider>
-    </>
-  );
-}
-
-declare global {
-  interface Window {
-    [EXT_STORE_SYMBOL]: ComponentStore;
-    [REQUIRE_SYMBOL]: (name: string) => unknown;
-  }
-}
-
-export function bootstrapUiContext() {
-  if (typeof window === "undefined") {
-    console.warn(
-      "Attempting to bootstrap UI context outside of browser environment. " +
-        "Avoid importing from `@langchain/langgraph-sdk/react-ui` in server context.",
-    );
-    return;
-  }
-
-  window[EXT_STORE_SYMBOL] = COMPONENT_STORE;
-  window[REQUIRE_SYMBOL] = (name: string) => {
-    if (name === "react") return React;
-    if (name === "react-dom") return ReactDOM;
-    if (name === "react/jsx-runtime") return JsxRuntime;
-    if (name === "@langchain/langgraph-sdk/react") return { useStream };
-    if (name === "@langchain/langgraph-sdk/react-ui") {
-      return {
-        useStreamContext,
-        LoadExternalComponent: () => {
-          throw new Error("Nesting LoadExternalComponent is not supported");
-        },
-      };
-    }
-
-    throw new Error(`Unknown module...: ${name}`);
-  };
-}
@@ -1,5 +0,0 @@
-import { bootstrapUiContext } from "./client.js";
-bootstrapUiContext();
-
-export { useStreamContext, LoadExternalComponent } from "./client.js";
-export type { UIMessage, RemoveUIMessage } from "./types.js";
@@ -1,6 +0,0 @@
-export { typedUi } from "./server.js";
-export {
-  uiMessageReducer,
-  type UIMessage,
-  type RemoveUIMessage,
-} from "../types.js";
@@ -1,49 +0,0 @@
-import { v4 as uuidv4 } from "uuid";
-import type { ComponentPropsWithoutRef, ElementType } from "react";
-import type { RemoveUIMessage, UIMessage } from "../types.js";
-
-export const typedUi = <Decl extends Record<string, ElementType>>(config: {
-  writer?: (chunk: unknown) => void;
-  runId?: string;
-  metadata?: Record<string, unknown>;
-  tags?: string[];
-  runName?: string;
-}) => {
-  type PropMap = { [K in keyof Decl]: ComponentPropsWithoutRef<Decl[K]> };
-  let collect: (UIMessage | RemoveUIMessage)[] = [];
-
-  const runId = (config.metadata?.run_id as string | undefined) ?? config.runId;
-  if (!runId) throw new Error("run_id is required");
-
-  const metadata = {
-    ...config.metadata,
-    tags: config.tags,
-    name: config.runName,
-    run_id: runId,
-  };
-
-  const create = <K extends keyof PropMap & string>(
-    name: K,
-    props: PropMap[K],
-  ): UIMessage => ({
-    type: "ui" as const,
-    id: uuidv4(),
-    name,
-    content: props,
-    additional_kwargs: metadata,
-  });
-
-  const remove = (id: string): RemoveUIMessage => ({ type: "remove-ui", id });
-
-  return {
-    create,
-    remove,
-
-    collect,
-    write: <K extends keyof PropMap & string>(name: K, props: PropMap[K]) => {
-      const evt: UIMessage = create(name, props);
-      collect.push(evt);
-      config.writer?.(evt);
-    },
-  };
-};
@@ -1,40 +0,0 @@
-export interface UIMessage {
-  type: "ui";
-
-  id: string;
-  name: string;
-  content: Record<string, unknown>;
-  additional_kwargs: {
-    run_id: string;
-    [key: string]: unknown;
-  };
-}
-
-export interface RemoveUIMessage {
-  type: "remove-ui";
-  id: string;
-}
-
-export function uiMessageReducer(
-  state: UIMessage[],
-  update: UIMessage | RemoveUIMessage | (UIMessage | RemoveUIMessage)[],
-) {
-  const events = Array.isArray(update) ? update : [update];
-  let newState = state.slice();
-
-  for (const event of events) {
-    if (event.type === "remove-ui") {
-      newState = newState.filter((ui) => ui.id !== event.id);
-      continue;
-    }
-
-    const index = state.findIndex((ui) => ui.id === event.id);
-    if (index !== -1) {
-      newState[index] = event;
-    } else {
-      newState.push(event);
-    }
-  }
-
-  return newState;
-}
@@ -366,11 +366,11 @@ const useControllableThreadId = (options?: {
    onThreadIdRef.current?.(threadId);
  }, []);

-  if (!options || !("threadId" in options)) {
+  if (typeof options?.threadId === "undefined") {
    return [localThreadId, onThreadId];
  }

-  return [options.threadId ?? null, onThreadId];
+  return [options.threadId, onThreadId];
 };

 type BagTemplate = {
@@ -424,16 +424,6 @@ interface UseStreamOptions<
   */
  apiKey?: ClientConfig["apiKey"];

-  /**
-   * Custom call options, such as custom fetch implementation.
-   */
-  callerOptions?: ClientConfig["callerOptions"];
-
-  /**
-   * Default headers to send with requests.
-   */
-  defaultHeaders?: ClientConfig["defaultHeaders"];
-
  /**
   * Specify the key within the state that contains messages.
   * Defaults to "messages".
@@ -482,7 +472,7 @@ interface UseStreamOptions<
  onThreadId?: (threadId: string) => void;
 }

-export interface UseStream<
+interface UseStream<
  StateType extends Record<string, unknown> = Record<string, unknown>,
  Bag extends BagTemplate = BagTemplate,
 > {
@@ -613,19 +603,8 @@ export function useStream<
  messagesKey ??= "messages";

  const client = useMemo(
-    () =>
-      new Client({
-        apiUrl: options.apiUrl,
-        apiKey: options.apiKey,
-        callerOptions: options.callerOptions,
-        defaultHeaders: options.defaultHeaders,
-      }),
-    [
-      options.apiKey,
-      options.apiUrl,
-      options.callerOptions,
-      options.defaultHeaders,
-    ],
+    () => new Client({ apiUrl: options.apiUrl, apiKey: options.apiKey }),
+    [options.apiKey, options.apiUrl],
  );
  const [threadId, onThreadId] = useControllableThreadId(options);

@@ -644,12 +623,9 @@ export function useStream<
  >([]);

  const trackStreamMode = useCallback(
-    (...mode: Exclude<StreamMode, "debug" | "messages">[]) => {
-      for (const m of mode) {
-        if (!trackStreamModeRef.current.includes(m)) {
-          trackStreamModeRef.current.push(m);
-        }
-      }
+    (mode: Exclude<StreamMode, "debug" | "messages">) => {
+      if (!trackStreamModeRef.current.includes(mode))
+        trackStreamModeRef.current.push(mode);
    },
    [],
  );
@@ -932,7 +908,7 @@ export function useStream<
    },

    get messages() {
-      trackStreamMode("messages-tuple", "values");
+      trackStreamMode("messages-tuple");
      return getMessages(values);
    },

@@ -940,7 +916,7 @@ export function useStream<
      message: Message,
      index?: number,
    ): MessageMetadata<StateType> | undefined {
-      trackStreamMode("messages-tuple", "values");
+      trackStreamMode("messages-tuple");
      return messageMetadata?.find(
        (m) => m.messageId === (message.id ?? index),
      );
@@ -110,9 +110,6 @@ export interface AssistantBase {

  /** The version of the assistant. */
  version: number;
-
-  /** The name of the assistant */
-  name: string;
 }

 export interface AssistantVersion extends AssistantBase {}
@@ -120,6 +117,9 @@ export interface AssistantVersion extends AssistantBase {}
 export interface Assistant extends AssistantBase {
  /** The last time the assistant was updated. */
  updated_at: string;
+
+  /** The name of the assistant */
+  name: string;
 }

 export interface AssistantGraph {
@@ -1005,16 +1005,17 @@
  resolved "https://registry.yarnpkg.com/@types/normalize-package-data/-/normalize-package-data-2.4.4.tgz#56e2cc26c397c038fab0e3a917a12d5c5909e901"
  integrity sha512-37i+OaWTh9qeK4LSHPsyRC7NahnGotNuZvjLSgcPzblpHB3rrCJxAOgI5gCdKm7coonsaX1Of0ILiTcnZjbfxA==

-"@types/react-dom@^19.0.3":
-  version "19.0.3"
-  resolved "https://registry.yarnpkg.com/@types/react-dom/-/react-dom-19.0.3.tgz#0804dfd279a165d5a0ad8b53a5b9e65f338050a4"
-  integrity sha512-0Knk+HJiMP/qOZgMyNFamlIjw9OFCsyC2ZbigmEEyXXixgre6IQpm/4V+r3qH4GC1JPvRJKInw+on2rV6YZLeA==
+"@types/prop-types@*":
+  version "15.7.14"
+  resolved "https://registry.yarnpkg.com/@types/prop-types/-/prop-types-15.7.14.tgz#1433419d73b2a7ebfc6918dcefd2ec0d5cd698f2"
+  integrity sha512-gNMvNH49DJ7OJYv+KAKn0Xp45p8PLl6zo2YnvDIbTd4J6MER2BmWN49TG7n9LvkyihINxeKW8+3bfS2yDC9dzQ==

-"@types/react@^19.0.8":
-  version "19.0.9"
-  resolved "https://registry.yarnpkg.com/@types/react/-/react-19.0.9.tgz#675255eb7d978bdaf71f9d08f6b740d41b0b7f32"
-  integrity sha512-FedNTYgmMwSZmD1Sru/W1gJKuiYCN/3SuBkmZkcxX+FpO5zL76B22A9YNfAKg4HQO3Neh/30AiynP6BELdU0qQ==
+"@types/react@18.3.2":
+  version "18.3.2"
+  resolved "https://registry.yarnpkg.com/@types/react/-/react-18.3.2.tgz#462ae4904973bc212fa910424d901e3d137dbfcd"
+  integrity sha512-Btgg89dAnqD4vV7R3hlwOxgqobUQKgx3MmrQRi0yYbs/P0ym8XozIAlkqVilPqHQwXs4e9Tf63rrCgl58BcO4w==
  dependencies:
+    "@types/prop-types" "*"
    csstype "^3.0.2"

 "@types/retry@0.12.0":
@@ -2895,7 +2896,7 @@ js-tiktoken@^1.0.12:
  dependencies:
    base64-js "^1.5.1"

-js-tokens@^4.0.0:
+"js-tokens@^3.0.0 || ^4.0.0", js-tokens@^4.0.0:
  version "4.0.0"
  resolved "https://registry.yarnpkg.com/js-tokens/-/js-tokens-4.0.0.tgz#19203fb59991df98e3a287050d4647cdeaf32499"
  integrity sha512-RdJUflcE3cUzKiMqQgsCu06FPu9UdIJO0beYbPhHN4k6apgJtifcoCtT9bcxOpYBtpD2kCM6Sbzg4CausW/PKQ==
@@ -2990,6 +2991,13 @@ longest-streak@^2.0.0:
  resolved "https://registry.yarnpkg.com/longest-streak/-/longest-streak-2.0.4.tgz#b8599957da5b5dab64dee3fe316fa774597d90e4"
  integrity sha512-vM6rUVCVUJJt33bnmHiZEvr7wPT78ztX7rojL+LW51bHtLh6HTjx84LA5W4+oa6aKEJA7jJu5LR6vQRBpA5DVg==

+loose-envify@^1.1.0:
+  version "1.4.0"
+  resolved "https://registry.yarnpkg.com/loose-envify/-/loose-envify-1.4.0.tgz#71ee51fa7be4caec1a63839f7e682d8132d30caf"
+  integrity sha512-lyuxPGr/Wfhrlem2CL/UcnUc1zcqKAImBDzukY7Y5F/yQiNdko6+fRLevlw1HgMySw7f611UIY408EtxRSoK3Q==
+  dependencies:
+    js-tokens "^3.0.0 || ^4.0.0"
+
 lru-cache@^10.2.0:
  version "10.4.3"
  resolved "https://registry.yarnpkg.com/lru-cache/-/lru-cache-10.4.3.tgz#410fc8a17b70e598013df257c2446b7f3383f119"
@@ -3632,22 +3640,17 @@ quick-lru@^4.0.1:
  resolved "https://registry.yarnpkg.com/quick-lru/-/quick-lru-4.0.1.tgz#5b8878f113a58217848c6482026c73e1ba57727f"
  integrity sha512-ARhCpm70fzdcvNQfPoy49IaanKkTlRWF2JMzqhcJbhSFRZv7nPTvZJdcY7301IPmvW+/p0RgIWnQDLJxifsQ7g==

-react-dom@^19.0.0:
-  version "19.0.0"
-  resolved "https://registry.yarnpkg.com/react-dom/-/react-dom-19.0.0.tgz#43446f1f01c65a4cd7f7588083e686a6726cfb57"
-  integrity sha512-4GV5sHFG0e/0AD4X+ySy6UJd3jVl1iNsNHdpad0qhABJ11twS3TTBnseqsKurKcsNqCEFeGL3uLpVChpIO3QfQ==
-  dependencies:
-    scheduler "^0.25.0"
-
 react-is@^18.0.0:
  version "18.3.1"
  resolved "https://registry.yarnpkg.com/react-is/-/react-is-18.3.1.tgz#e83557dc12eae63a99e003a46388b1dcbb44db7e"
  integrity sha512-/LLMVyas0ljjAtoYiPqYiL8VWXzUUdThrmU5+n20DZv+a+ClRoevUzw5JxU+Ieh5/c87ytoTBV9G1FiKfNJdmg==

-react@^19.0.0:
-  version "19.0.0"
-  resolved "https://registry.yarnpkg.com/react/-/react-19.0.0.tgz#6e1969251b9f108870aa4bff37a0ce9ddfaaabdd"
-  integrity sha512-V8AVnmPIICiWpGfm6GLzCR/W5FXLchHop40W4nXBmdlEceh16rCN8O8LNWm5bh5XUX91fh7KpA+W0TgMKmgTpQ==
+react@^18.3.1:
+  version "18.3.1"
+  resolved "https://registry.yarnpkg.com/react/-/react-18.3.1.tgz#49ab892009c53933625bd16b2533fc754cab2891"
+  integrity sha512-wS+hAgJShR0KhEvPJArfuPVN1+Hz1t0Y6n5jLrGQbkb4urgPE/0Rve+1kMB1v/oWgHgm4WIcV+i7F2pTVj+2iQ==
+  dependencies:
+    loose-envify "^1.1.0"

 read-pkg-up@^7.0.1:
  version "7.0.1"
@@ -3837,11 +3840,6 @@ safe-regex-test@^1.0.3:
    es-errors "^1.3.0"
    is-regex "^1.1.4"

-scheduler@^0.25.0:
-  version "0.25.0"
-  resolved "https://registry.yarnpkg.com/scheduler/-/scheduler-0.25.0.tgz#336cd9768e8cceebf52d3c80e3dcf5de23e7e015"
-  integrity sha512-xFVuu11jh+xcO7JOAGJNOXld8/TcEHK/4CituBUeUb5hqxJLj9YuemAEuvm9gQ/+pgXYfbQuqAkiYu+u7YEsNA==
-
 "semver@2 || 3 || 4 || 5":
  version "5.7.2"
  resolved "https://registry.yarnpkg.com/semver/-/semver-5.7.2.tgz#48d55db737c3287cd4835e17fa13feace1c41ef8"
@@ -388,9 +388,7 @@ class AssistantsClient:
                'created_at': '2024-06-25T17:10:33.109781+00:00',
                'updated_at': '2024-06-25T17:10:33.109781+00:00',
                'config': {},
-                'metadata': {'created_by': 'system'},
-                'version': 1,
-                'name': 'my_assistant'
+                'metadata': {'created_by': 'system'}
            }

        """  # noqa: E501
@@ -744,7 +742,7 @@ class AssistantsClient:
            offset: The number of versions to skip.

        Returns:
-            list[AssistantVersion]: A list of assistant versions.
+            list[Assistant]: A list of assistants.

        Example Usage:

@@ -1739,8 +1737,8 @@ class RunsClient:

        Example Usage:

-            await client.runs.list(
-                thread_id="thread_id",
+            await client.runs.delete(
+                thread_id="thread_id_to_delete",
                limit=5,
                offset=5,
            )
@@ -2129,7 +2127,6 @@ class StoreClient:
        key: str,
        value: dict[str, Any],
        index: Optional[Union[Literal[False], list[str]]] = None,
-        ttl: Optional[int] = None,
    ) -> None:
        """Store or update an item.

@@ -2138,7 +2135,6 @@ class StoreClient:
            key: The unique identifier for the item within the namespace.
            value: A dictionary containing the item's data.
            index: Controls search indexing - None (use defaults), False (disable), or list of field paths to index.
-            ttl: Optional time-to-live in minutes for the item, or None for no expiration.

        Returns:
            None
@@ -2156,29 +2152,15 @@ class StoreClient:
                raise ValueError(
                    f"Invalid namespace label '{label}'. Namespace labels cannot contain periods ('.')."
                )
-        payload = {
-            "namespace": namespace,
-            "key": key,
-            "value": value,
-            "index": index,
-            "ttl": ttl,
-        }
+        payload = {"namespace": namespace, "key": key, "value": value, "index": index}
        await self.http.put("/store/items", json=payload)

-    async def get_item(
-        self,
-        namespace: Sequence[str],
-        /,
-        key: str,
-        *,
-        refresh_ttl: Optional[bool] = None,
-    ) -> Item:
+    async def get_item(self, namespace: Sequence[str], /, key: str) -> Item:
        """Retrieve a single item.

        Args:
            key: The unique identifier for the item.
            namespace: Optional list of strings representing the namespace path.
-            refresh_ttl: Whether to refresh the TTL on this read operation. If None, uses the store's default behavior.

        Returns:
            Item: The retrieved item.
@@ -2206,10 +2188,9 @@ class StoreClient:
                raise ValueError(
                    f"Invalid namespace label '{label}'. Namespace labels cannot contain periods ('.')."
                )
-        params = {"namespace": ".".join(namespace), "key": key}
-        if refresh_ttl is not None:
-            params["refresh_ttl"] = refresh_ttl
-        return await self.http.get("/store/items", params=params)
+        return await self.http.get(
+            "/store/items", params={"namespace": ".".join(namespace), "key": key}
+        )

    async def delete_item(self, namespace: Sequence[str], /, key: str) -> None:
        """Delete an item.
@@ -2240,7 +2221,6 @@ class StoreClient:
        limit: int = 10,
        offset: int = 0,
        query: Optional[str] = None,
-        refresh_ttl: Optional[bool] = None,
    ) -> SearchItemsResponse:
        """Search for items within a namespace prefix.

@@ -2250,7 +2230,6 @@ class StoreClient:
            limit: Maximum number of items to return (default is 10).
            offset: Number of items to skip before returning results (default is 0).
            query: Optional query for natural language search.
-            refresh_ttl: Whether to refresh the TTL on items returned by this search. If None, uses the store's default behavior.

        Returns:
            List[Item]: A list of items matching the search criteria.
@@ -2289,7 +2268,6 @@ class StoreClient:
            "limit": limit,
            "offset": offset,
            "query": query,
-            "refresh_ttl": refresh_ttl,
        }

        return await self.http.post("/store/items/search", json=_provided_vals(payload))
@@ -2539,7 +2517,7 @@ def encode_json(json: Any) -> tuple[dict[str, str], bytes]:

 def decode_json(r: httpx.Response) -> Any:
    body = r.read()
-    return orjson.loads(body) if body else None
+    return orjson.loads(body if body else None)


 class SyncAssistantsClient:
@@ -3903,8 +3881,8 @@ class SyncRunsClient:

        Example Usage:

-            client.runs.list(
-                thread_id="thread_id",
+            client.runs.delete(
+                thread_id="thread_id_to_delete",
                limit=5,
                offset=5,
            )
@@ -4274,7 +4252,6 @@ class SyncStoreClient:
        key: str,
        value: dict[str, Any],
        index: Optional[Union[Literal[False], list[str]]] = None,
-        ttl: Optional[int] = None,
    ) -> None:
        """Store or update an item.

@@ -4283,7 +4260,7 @@ class SyncStoreClient:
            key: The unique identifier for the item within the namespace.
            value: A dictionary containing the item's data.
            index: Controls search indexing - None (use defaults), False (disable), or list of field paths to index.
-            ttl: Optional time-to-live in minutes for the item, or None for no expiration.
+
        Returns:
            None

@@ -4305,24 +4282,15 @@ class SyncStoreClient:
            "key": key,
            "value": value,
            "index": index,
-            "ttl": ttl,
        }
        self.http.put("/store/items", json=payload)

-    def get_item(
-        self,
-        namespace: Sequence[str],
-        /,
-        key: str,
-        *,
-        refresh_ttl: Optional[bool] = None,
-    ) -> Item:
+    def get_item(self, namespace: Sequence[str], /, key: str) -> Item:
        """Retrieve a single item.

        Args:
            key: The unique identifier for the item.
            namespace: Optional list of strings representing the namespace path.
-            refresh_ttl: Whether to refresh the TTL on this read operation. If None, uses the store's default behavior.

        Returns:
            Item: The retrieved item.
@@ -4351,10 +4319,9 @@ class SyncStoreClient:
                    f"Invalid namespace label '{label}'. Namespace labels cannot contain periods ('.')."
                )

-        params = {"key": key, "namespace": ".".join(namespace)}
-        if refresh_ttl is not None:
-            params["refresh_ttl"] = refresh_ttl
-        return self.http.get("/store/items", params=params)
+        return self.http.get(
+            "/store/items", params={"key": key, "namespace": ".".join(namespace)}
+        )

    def delete_item(self, namespace: Sequence[str], /, key: str) -> None:
        """Delete an item.
@@ -4383,7 +4350,6 @@ class SyncStoreClient:
        limit: int = 10,
        offset: int = 0,
        query: Optional[str] = None,
-        refresh_ttl: Optional[bool] = None,
    ) -> SearchItemsResponse:
        """Search for items within a namespace prefix.

@@ -4393,7 +4359,6 @@ class SyncStoreClient:
            limit: Maximum number of items to return (default is 10).
            offset: Number of items to skip before returning results (default is 0).
            query: Optional query for natural language search.
-            refresh_ttl: Whether to refresh the TTL on items returned by this search. If None, uses the store's default behavior.

        Returns:
            List[Item]: A list of items matching the search criteria.
@@ -4432,7 +4397,6 @@ class SyncStoreClient:
            "limit": limit,
            "offset": offset,
            "query": query,
-            "refresh_ttl": refresh_ttl,
        }
        return self.http.post("/store/items/search", json=_provided_vals(payload))

@@ -169,8 +169,6 @@ class AssistantBase(TypedDict):
    """The assistant metadata."""
    version: int
    """The version of the assistant"""
-    name: str
-    """The name of the assistant"""


 class AssistantVersion(AssistantBase):
@@ -184,6 +182,8 @@ class Assistant(AssistantBase):

    updated_at: datetime
    """The last time the assistant was updated."""
+    name: str
+    """The name of the assistant"""


 class Interrupt(TypedDict, total=False):
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-sdk"
-version = "0.1.55"
+version = "0.1.53"
 description = "SDK for interacting with LangGraph API"
 authors = []
 license = "MIT"