add overwrite command

fix: Revert "fix(cli): rename studio to debugger (#6246 )" (#6261 )
chore(langgraph): bump langgraph version (#6257 )
2026-08-18 05:35:43 +02:00 · 2025-10-13 16:50:08 -07:00 · 2025-10-09 23:35:36 +00:00 · 2025-10-09 09:39:42 -07:00 · 2025-10-08 12:34:01 -07:00 · 2025-10-08 09:40:26 -07:00
192 changed files with 10826 additions and 4520 deletions
@@ -1,6 +1,9 @@
 blank_issues_enabled: false
 version: 2.1
 contact_links:
+  - name: Documentation
+    url: https://github.com/langchain-ai/docs/issues/new?template=langgraph.yml
+    about: Report an issue related to the LangGraph documentation
  - name: LangChain Forum
    url:  https://forum.langchain.com/
-    about: General community discussions, support, and feature requests
+    about: General community discussions and support
@@ -1,19 +0,0 @@
-name: Documentation
-description: Report an issue related to the LangGraph documentation.
-title: "DOC: <Please write a comprehensive title after the 'DOC: ' prefix>"
-labels: [documentation]
-
-body:
- type: textarea
-  attributes: 
-    label: "Issue with current documentation:"
-    description: >
-      Please make sure to leave a reference to the document/code you're
-      referring to.
-
- type: textarea
-  attributes:
-    label: "Idea or request for content:"
-    description: >
-      Please describe as clearly as possible what topics you think are missing
-      from the current documentation.
@@ -14,12 +14,25 @@ jobs:
        python-version:
          - "3.10"
          - "3.11"
+        example:
+          - name: A
+            workdir: libs/cli/examples
+            tag: langgraph-test-a
+          - name: B
+            workdir: libs/cli/examples/graphs
+            tag: langgraph-test-b
+          - name: C
+            workdir: libs/cli/examples/graphs_reqs_a
+            tag: langgraph-test-c
+          - name: D
+            workdir: libs/cli/examples/graphs_reqs_b
+            tag: langgraph-test-d
    name: "CLI integration test"
    defaults:
      run:
        working-directory: libs/cli
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - name: Get changed files
        id: changed-files
        uses: Ana06/get-changed-files@v2.3.0
@@ -33,57 +46,65 @@ jobs:
          enable-cache: true
          cache-suffix: "cli-integration-test"
          ignore-nothing-to-cache: true
-      - name: Setup env
-        if: steps.changed-files.outputs.all
-        working-directory: libs/cli/examples
-        run: cat .env.example > .env
      - name: Install cli globally
        if: steps.changed-files.outputs.all
        run: pip install -e .
-      - name: Build and test service A
+      - name: Build and test service ${{ matrix.example.name }}
        if: steps.changed-files.outputs.all
-        working-directory: libs/cli/examples
+        working-directory: ${{ matrix.example.workdir }}
        env:
          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
        run: |
-          # The build-arg isn't used; just testing that we accept other args
-          langgraph build -t langgraph-test-a
-          cp .env.example .env
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
-          timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -c langgraph.json -t langgraph-test-a
-      - name: Build and test service B
-        if: steps.changed-files.outputs.all
-        working-directory: libs/cli/examples/graphs
-        env:
-          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
-        run: |
-          langgraph build -t langgraph-test-b
-          cp ../.env.example .env
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
-          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-b
-      - name: Build and test service C
-        if: steps.changed-files.outputs.all
-        working-directory: libs/cli/examples/graphs_reqs_a
-        env:
-          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
-        run: |
-          langgraph build -t langgraph-test-c
-          cp ../.env.example .env
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
-          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-c
-      - name: Build and test service D
-        if: steps.changed-files.outputs.all
-        working-directory: libs/cli/examples/graphs_reqs_b
-        env:
-          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
-        run: |
-          langgraph build -t langgraph-test-d
-          cp ../.env.example .env
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
-          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-d
+          # Build the image for this example
+          langgraph build -t ${{ matrix.example.tag }}
+          # Prepare environment file from local or parent example directory
+          if [ -f .env.example ]; then cp .env.example .env; elif [ -f ../.env.example ]; then cp ../.env.example .env && cp ../.env.example ../.env; fi
+          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; if [ -f ../.env ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> ../.env; fi; fi
+          # Run the integration test using the built tag
+          # Compute repo root to reference the shared script robustly
+          REPO_ROOT=$(git rev-parse --show-toplevel)
+          timeout 60 python "$REPO_ROOT/.github/scripts/run_langgraph_cli_test.py" -t ${{ matrix.example.tag }}

      - name: Build JS service
        if: steps.changed-files.outputs.all
        working-directory: libs/cli/js-examples
        run: |
          langgraph build -t langgraph-test-e
+
+      - name: Build JS monorepo service
+        if: steps.changed-files.outputs.all
+        working-directory: libs/cli/js-monorepo-example
+        run: |
+          langgraph build -t langgraph-test-f -c apps/agent/langgraph.json --build-command "yarn run turbo build" --install-command "yarn install"
+
+      - name: Build Python monorepo service
+        if: steps.changed-files.outputs.all
+        working-directory: libs/cli/python-monorepo-example
+        run: |
+          langgraph build -t langgraph-test-g -c apps/agent/langgraph.json
+          cp apps/agent/.env.example apps/agent/.env
+          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> apps/agent/.env; fi
+          timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-g -c apps/agent/langgraph.json
+
+      - name: Build and test prerelease reqs service
+        if: steps.changed-files.outputs.all
+        working-directory: libs/cli/examples/graph_prerelease_reqs
+        run: |
+          langgraph build -t langgraph-test-h
+          cp ../.env.example .env
+          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
+          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-h
+          LANGGRAPH_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langgraph'); print(v);")
+          if [ "$LANGGRAPH_VERSION" != "1.0.0a2" ]; then
+            exit 1
+          fi
+          LANGCHAIN_OPENAI_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-openai'); print(v);")
+          if [ "$LANGCHAIN_OPENAI_VERSION" != "0.3.0" ]; then
+            exit 1
+          fi
+
+      - name: Build and test prerelease reqs fail service
+        if: steps.changed-files.outputs.all
+        working-directory: libs/cli/examples/graph_prerelease_reqs_fail
+        run: |
+          langgraph build -t langgraph-test-i || [ $? -eq 1 ]
@@ -31,7 +31,7 @@ jobs:
          - "3.12"
    name: "lint #${{ matrix.python-version }}"
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - name: Get changed files
        id: changed-files
        uses: Ana06/get-changed-files@v2.3.0
@@ -25,7 +25,7 @@ jobs:

    name: "test #${{ matrix.python-version }}"
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - name: Set up Python ${{ matrix.python-version }}
        uses: astral-sh/setup-uv@v6
        with:
@@ -23,7 +23,7 @@ jobs:
        working-directory: libs/langgraph
    name: "test #${{ matrix.python-version }}"
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - name: Set up Python ${{ matrix.python-version }}
        uses: astral-sh/setup-uv@v6
        with:
@@ -24,7 +24,7 @@ jobs:
      version: ${{ steps.check-version.outputs.version }}

    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5

      - name: Set up Python $${ env.PYTHON_VERSION }}
        uses: astral-sh/setup-uv@v6
@@ -75,9 +75,9 @@ jobs:
      id-token: write

    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5

-      - uses: actions/download-artifact@v4
+      - uses: actions/download-artifact@v5
        with:
          name: test-dist
          path: ${{ inputs.working-directory }}/dist/
@@ -17,7 +17,7 @@ jobs:
      run:
        working-directory: libs/langgraph
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - run: SHA=$(git rev-parse HEAD) && echo "SHA=$SHA" >> $GITHUB_ENV
      - name: Set up Python 3.11
        uses: astral-sh/setup-uv@v6
@@ -15,7 +15,7 @@ jobs:
      run:
        working-directory: libs/langgraph
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - id: files
        name: Get changed files
        uses: Ana06/get-changed-files@v2.3.0
@@ -57,7 +57,7 @@ jobs:
            echo EOF
          } >> "$GITHUB_OUTPUT"
      - name: Annotation
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
        with:
          script: |
            const file = JSON.parse(`${{ steps.files.outputs.added_modified_renamed }}`)[0]
@@ -27,7 +27,7 @@ jobs:
      python: ${{ steps.filter.outputs.python }}
      deps: ${{ steps.filter.outputs.deps }}
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - uses: dorny/paths-filter@v3
        id: filter
        with:
@@ -100,9 +100,9 @@ jobs:
    name: "Check SDK methods matching"
    runs-on: ubuntu-latest
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - name: Set up Python
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v6
        with:
          python-version: "3.11"
      - name: Run check_sdk_methods script
@@ -118,7 +118,7 @@ jobs:
        python-version:
          - "3.11"
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - name: Set up Python ${{ matrix.python-version }}
        uses: astral-sh/setup-uv@v6
        with:
@@ -21,7 +21,7 @@
    
        steps:
          - name: Checkout
-            uses: actions/checkout@v4
+            uses: actions/checkout@v5
    
          - name: Install Dependencies
            run: |
@@ -28,7 +28,7 @@ jobs:
    outputs:
      changed-files: ${{ steps.changed-files.outputs.added_modified }}
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - name: Get changed files
        id: changed-files
        uses: Ana06/get-changed-files@v2.3.0
@@ -41,7 +41,7 @@ jobs:
    env:
      GITHUB_TOKEN: ${{ secrets.MKDOCS_GITHUB_TOKEN }}
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
        with:
          fetch-depth: 0

@@ -140,7 +140,7 @@ jobs:

      - name: Upload Pages Artifact
        # if: github.ref == 'refs/heads/main'
-        uses: actions/upload-pages-artifact@v3
+        uses: actions/upload-pages-artifact@v4
        with:
          path: ./docs/site/

@@ -19,7 +19,7 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
        with:
          fetch-depth: 0

@@ -36,7 +36,7 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
        with:
          fetch-depth: 1

@@ -12,7 +12,7 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Validate PR Title
-        uses: amannn/action-semantic-pull-request@v5
+        uses: amannn/action-semantic-pull-request@v6
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
        with:
@@ -40,6 +40,7 @@ jobs:
            sdk-py
            docs
            ci
+            deps
          requireScope: false
          ignoreLabels: |
            ignore-lint-pr-title
@@ -26,7 +26,7 @@ jobs:
      tag: ${{ steps.check-version.outputs.tag }}

    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5

      - name: Set up Python
        uses: astral-sh/setup-uv@v6
@@ -87,7 +87,7 @@ jobs:
    outputs:
      release-body: ${{ steps.generate-release-body.outputs.release-body }}
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
        with:
          repository: langchain-ai/langgraph
          path: langgraph
@@ -158,7 +158,7 @@ jobs:
      - test-pypi-publish
    runs-on: ubuntu-latest
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5

      # We explicitly *don't* set up caching here. This ensures our tests are
      # maximally sensitive to catching breakage.
@@ -261,7 +261,7 @@ jobs:
        working-directory: ${{ inputs.working-directory }}

    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5

      - name: Set up Python
        uses: astral-sh/setup-uv@v6
@@ -270,7 +270,7 @@ jobs:
          enable-cache: true
          cache-suffix: "release"

-      - uses: actions/download-artifact@v4
+      - uses: actions/download-artifact@v5
        with:
          name: dist
          path: ${{ inputs.working-directory }}/dist/
@@ -302,7 +302,7 @@ jobs:
        working-directory: ${{ inputs.working-directory }}

    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5

      - name: Set up Python
        uses: astral-sh/setup-uv@v6
@@ -311,7 +311,7 @@ jobs:
          enable-cache: true
          cache-suffix: "release"

-      - uses: actions/download-artifact@v4
+      - uses: actions/download-artifact@v5
        with:
          name: dist
          path: ${{ inputs.working-directory }}/dist/
@@ -28,7 +28,7 @@ jobs:
          - "latest"

    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - name: Set up Python + Poetry
        uses: astral-sh/setup-uv@v6
        with:
@@ -16,7 +16,7 @@ jobs:
    runs-on: ubuntu-latest
    
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      
      - name: Set up uv
        uses: astral-sh/setup-uv@v6
@@ -33,8 +33,8 @@ jobs:
        uses: peter-evans/create-pull-request@v7
        with:
          token: ${{ secrets.GITHUB_TOKEN }}
-          commit-message: "chore[deps]: upgrade dependencies with `uv lock --upgrade`"
-          title: "chore[deps]: upgrade dependencies with `uv lock --upgrade`"
+          commit-message: "chore(deps): upgrade dependencies with `uv lock --upgrade`"
+          title: "chore(deps): upgrade dependencies with `uv lock --upgrade`"
          body: |
            This PR updates the dependencies in all Python packages using `uv lock --upgrade`.
            
@@ -277,9 +277,9 @@ def my_function(arg1: int, arg2: str) -> float:
    Examples:
        This is a section for examples of how to use the function.

-        .. code-block:: python
-
-            my_function(1, "hello")
+        ```python
+        my_function(1, "hello")
+        \```

    Args:
        arg1: This is a description of arg1. We do not need to specify the type since
@@ -71,7 +71,7 @@ While LangGraph can be used standalone, it also integrates seamlessly with any L

 ## Additional resources

- [Guides](https://langchain-ai.github.io/langgraph/how-tos/): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
+- [Guides](https://langchain-ai.github.io/langgraph/guides/): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
 - [Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
 - [Examples](https://langchain-ai.github.io/langgraph/examples/): Guided examples on getting started with LangGraph.
 - [LangChain Forum](https://forum.langchain.com/): Connect with the community and share all of your technical questions, ideas, and feedback.
@@ -1,24 +1,126 @@
-# Setup
+# LangGraph Documentation

-To setup requirements for building docs you can run:
+For more information on contributing to our documentation, see the [Contributing Guide](../CONTRIBUTING.md).

-```bash
-uv sync --group test
+## Structure
+
+The primary documentation is located in the `docs/` directory. This directory contains both the source files for the main documentation as well as the API reference doc build process.
+
+### Main Documentation
+
+Main documentation files are located in `docs/docs/` and are written in Markdown format. The site uses [**MkDocs**](https://www.mkdocs.org/) with the [Material theme](https://squidfunk.github.io/mkdocs-material/) and includes:
+
+- **Concepts**: Core LangGraph concepts and explanations
+- **Tutorials**: Step-by-step learning guides
+- **How-tos**: Task-focused guides for specific use cases
+- **Examples**: Real-world applications and use cases
+- **Jupyter Notebooks**: Interactive tutorials that are automatically converted to markdown
+
+### API Reference
+
+API reference documentation is defined in `docs/docs/reference/`. Each `.md` file outlines the "template" that each page is built from. Reference content is automatically generated from docstrings in the codebase using the **mkdocstrings** plugin. Once generated, the content is plugged into the corresponding markdown file where it is referenced by using manual directives to specify which classes and/or functions are documented:
+
+```markdown
+::: langgraph.graph.state.StateGraph
+    options:
+      show_if_no_docstring: true
+      show_root_heading: true
+      show_root_full_path: false
+      members:
+        - add_node
+        - add_edge
+        - add_conditional_edges
+        - add_sequence
+        - compile
 ```

-## Serving documentation locally
+## Build Process

-To run the documentation server locally you can run:
+Docs are built following these steps:
+
+1. **Content Processing:**
+   - `_scripts/notebook_hooks.py` - Main processing pipeline that:
+     - Converts how-tos/tutorial Jupyter notebooks to markdown using `notebook_convert.py`
+     - Adds automatic API reference links to code blocks using `generate_api_reference_links.py`
+     - Handles conditional rendering for Python/JS versions
+     - Processes highlight comments and custom syntax
+
+2. **API Reference Generation:**
+   - **mkdocstrings** plugin extracts docstrings from Python source code
+   - Manual `::: module.Class` directives in reference pages (`/docs/docs/*`) specify what to document
+   - Cross-references are automatically generated between docs and API
+
+3. **Site Generation:**
+   - **MkDocs** processes all markdown files and generates static HTML
+   - Custom hooks handle redirects and inject additional functionality
+
+4. **Deployment:**
+   - Site is deployed with Vercel
+   - `make build-docs` generates production build (also usable for local testing)
+   - Automatic redirects handle URL changes between versions
+
+### Local Development
+
+For local development, use the Makefile targets:

 ```bash
+# Serve docs locally with hot reloading
 make serve-docs
+
+# Clean build for production testing
+make build-docs
+
+# Serve with clean build
+make serve-clean-docs
 ```

-This will start the documentation server on [http://127.0.0.1:8000/langgraph/](http://127.0.0.1:8000/langgraph/).
+The `serve-docs` command:
+
+- Watches source files for changes
+- Includes dirty builds for faster iteration
+- Serves on [http://127.0.0.1:8000/langgraph/](http://127.0.0.1:8000/langgraph/)
+
+## Standards
+
+**Docstring Format:**
+The API reference uses **Google-style docstrings** with Markdown markup. The `mkdocstrings` plugin processes these to generate documentation.
+
+**Required format:**
+
+```python
+def example_function(param1: str, param2: int = 5) -> bool:
+    """Brief description of the function.
+
+    Longer description can go here. Use Markdown syntax for
+    rich formatting like **bold** and *italic*.
+
+    Args:
+        param1: Description of the first parameter.
+        param2: Description of the second parameter with default value.
+
+    Returns:
+        Description of the return value.
+
+    Raises:
+        ValueError: When param1 is empty.
+        TypeError: When param2 is not an integer.
+
+    !!! warning
+        This function is experimental and may change.
+
+    !!! version-added "Added in version 0.2.0"
+    """
+```
+
+**Special Markers:**
+
+- **MkDocs admonitions**: `!!! warning`, `!!! note`, `!!! version-added`
+- **Code blocks**: Standard markdown ``` syntax
+- **Cross-references**: Automatic linking via `generate_api_reference_links.py`

 ## Execute notebooks

-If you would like to automatically execute all of the notebooks, to mimic the "Run notebooks" GHA, you can run:
+If you would like to automatically execute all of the notebooks, to mimic the "Run notebooks" GitHub action, you can run:

 ```bash
 python _scripts/prepare_notebooks_for_ci.py
@@ -33,8 +135,9 @@ python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
 ```

 `prepare_notebooks_for_ci.py` script will add VCR cassette context manager for each cell in the notebook, so that:
-* when the notebook is run for the first time, cells with network requests will be recorded to a VCR cassette file
-* when the notebook is run subsequently, the cells with network requests will be replayed from the cassettes
+
+- when the notebook is run for the first time, cells with network requests will be recorded to a VCR cassette file
+- when the notebook is run subsequently, the cells with network requests will be replayed from the cassettes

 ## Adding new notebooks

@@ -1,3 +1,5 @@
+"""Generate API reference links for imports in Python code blocks within markdown files."""
+
 import ast
 import importlib
 import logging
@@ -70,8 +72,18 @@ MANUAL_API_REFERENCES_LANGGRAPH = [
    ([], "langgraph.checkpoint.postgres.aio", "AsyncPostgresSaver", "checkpoints"),
    ([], "langgraph.checkpoint.postgres", "PostgresSaver", "checkpoints"),
    # other prebuilts
-    (["langgraph_supervisor"], "langgraph_supervisor.supervisor", "create_supervisor", "supervisor"),
-    (["langgraph_supervisor"], "langgraph_supervisor.handoff", "create_handoff_tool", "supervisor"),
+    (
+        ["langgraph_supervisor"],
+        "langgraph_supervisor.supervisor",
+        "create_supervisor",
+        "supervisor",
+    ),
+    (
+        ["langgraph_supervisor"],
+        "langgraph_supervisor.handoff",
+        "create_handoff_tool",
+        "supervisor",
+    ),
    ([], "langgraph_supervisor.handoff", "create_forward_message_tool", "supervisor"),
    (["langgraph_swarm"], "langgraph_swarm.swarm", "create_swarm", "swarm"),
    (["langgraph_swarm"], "langgraph_swarm.swarm", "add_active_agent_router", "swarm"),
@@ -2108,9 +2108,9 @@ __metadata:
  linkType: hard

 "hono@npm:^4.5.4":
-  version: 4.8.9
-  resolution: "hono@npm:4.8.9"
-  checksum: 10c0/385539d1787fdc747bc869ef0e5ccc9f39cbe40289b94f23eecfc82c6ca440f059704647cd6381a5066d2cf7baa43ab25184c78d44af4c5c98a5c5b07670059e
+  version: 4.9.7
+  resolution: "hono@npm:4.9.7"
+  checksum: 10c0/089184660a9211ea216ab95bafa45260e371651cb019db49828064b7982b0ae61cc3c4715324bfeb9037aa2460c39ffa2c91d84ad0c8d500fa77cbcc7fc07a8f
  languageName: node
  linkType: hard

@@ -1,3 +1,5 @@
+"""Convert Jupyter notebooks to markdown with custom processing."""
+
 import ast
 import os
 import re
@@ -144,13 +144,13 @@ REDIRECT_MAP = {
    "concepts/langgraph_cli.md": "https://docs.langchain.com/langgraph-platform/langgraph-cli",
    "concepts/langgraph_studio.md": "https://docs.langchain.com/langgraph-platform/langgraph-studio",
    "cloud/how-tos/studio/quick_start.md": "https://docs.langchain.com/langgraph-platform/quick-start-studio",
-    "cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langgraph-platform/invoke-studio",
-    "cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langgraph-platform/manage-assistants-studio",
-    "cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langgraph-platform/threads-studio",
-    "cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langgraph-platform/iterate-graph-studio",
-    "cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langgraph-platform/run-evals-studio",
-    "cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langgraph-platform/clone-traces-studio",
-    "cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langgraph-platform/datasets-studio",
+    "cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langgraph-platform/use-studio#run-application",
+    "cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langgraph-platform/use-studio#manage-assistants",
+    "cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langgraph-platform/use-studio#manage-threads",
+    "cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langgraph-platform/observability-studio#iterate-on-prompts",
+    "cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langgraph-platform/observability-studio#run-experiments-over-a-dataset",
+    "cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langgraph-platform/observability-studio#debug-langsmith-traces",
+    "cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langgraph-platform/observability-studio#add-node-to-dataset",
    "concepts/sdk.md": "https://docs.langchain.com/langgraph-platform/sdk",
    "concepts/plans.md": "https://docs.langchain.com/langgraph-platform/plans",
    "concepts/application_structure.md": "https://docs.langchain.com/langgraph-platform/application-structure",
@@ -33,7 +33,7 @@ LangGraph provides three ways to manage context, which combines the mutability a

 **Static runtime context** represents immutable data like user metadata, tools, and database connections that are passed to an application at the start of a run via the `context` argument to `invoke`/`stream`. This data does not change during execution.

-!!! version-added "New in LangGraph v0.6: `context` replaces `config['configurable']`"
+!!! version-added "Added in version 0.6.0: `context` replaces `config['configurable']`"

    Runtime context is now passed to the `context` argument of `invoke`/`stream`,
    which replaces the previous pattern of passing application configuration to `config['configurable']`.
@@ -90,7 +90,7 @@ graph.invoke( # (1)!
    from langgraph.runtime import Runtime

    # highlight-next-line
-    def node(state: State, config: Runtime[ContextSchema]):
+    def node(state: State, runtime: Runtime[ContextSchema]):
        user_name = runtime.context.user_name
        ...
    ```
@@ -211,7 +211,7 @@ output = agent.invoke(
 print(output["messages"][-1].text())
 ```

-!!! version-added "New in LangGraph v0.6"
+!!! version-added "Added in version 0.6.0"

 :::

@@ -351,11 +351,13 @@ If your desired LLM isn't officially supported by LangChain, consider these opti
 :::python

 1. **Implement a custom LangChain chat model**: Create a model conforming to the [LangChain chat model interface](https://python.langchain.com/docs/how_to/custom_chat_model/). This enables full compatibility with LangGraph's agents and workflows but requires understanding of the LangChain framework.
+
   :::

 :::js

 1. **Implement a custom LangChain chat model**: Create a model conforming to the [LangChain chat model interface](https://js.langchain.com/docs/how_to/custom_chat/). This enables full compatibility with LangGraph's agents and workflows but requires understanding of the LangChain framework.
+
   :::

 2. **Direct invocation with custom streaming**: Use your model directly by [adding custom streaming logic](../how-tos/streaming.md#use-with-any-llm) with `StreamWriter`.
@@ -371,6 +373,7 @@ If your desired LLM isn't officially supported by LangChain, consider these opti
 - [Force model to call a specific tool](https://python.langchain.com/docs/how_to/tool_choice/)
 - [All chat model how-to guides](https://python.langchain.com/docs/how_to/#chat-models)
 - [Chat model integrations](https://python.langchain.com/docs/integrations/chat/)
+
  :::

 :::js
@@ -381,4 +384,5 @@ If your desired LLM isn't officially supported by LangChain, consider these opti
 - [Force model to call a specific tool](https://js.langchain.com/docs/how_to/tool_choice/)
 - [All chat model how-to guides](https://js.langchain.com/docs/how_to/#chat-models)
 - [Chat model integrations](https://js.langchain.com/docs/integrations/chat/)
+
  :::
@@ -29,6 +29,10 @@
      "name": "Store",
      "description": "Store is an API for managing persistent key-value store (long-term memory) that is available from any thread."
    },
+    {
+      "name": "A2A",
+      "description": "Agent-to-Agent Protocol related endpoints for exposing assistants as A2A-compliant agents."
+    },
    {
      "name": "MCP",
      "description": "Model Context Protocol related endpoints for exposing an agent as an MCP server."
@@ -1550,6 +1554,29 @@
            },
            "name": "Last-Event-ID",
            "in": "header"
+          },
+          {
+            "required": false,
+            "schema": {
+              "anyOf": [
+                {
+                  "type": "string",
+                  "enum": ["lifecycle", "run_modes", "state_update"]
+                },
+                {
+                  "type": "array",
+                  "items": {
+                    "type": "string",
+                    "enum": ["lifecycle", "run_modes", "state_update"]
+                  }
+                }
+              ],
+              "default": ["run_modes"],
+              "title": "Stream Modes",
+              "description": "Stream modes to control which events are returned. 'lifecycle' returns only run start/end events, 'run_modes' returns all run events (default behavior), 'state_update' returns only state update events."
+            },
+            "name": "stream_modes",
+            "in": "query"
          }
        ],
        "responses": {
@@ -3159,6 +3186,195 @@
        }
      }
    },
+    "/a2a/{assistant_id}": {
+      "post": {
+        "operationId": "post_a2a",
+        "summary": "A2A Post",
+        "description": "Communicate with an assistant using the Agent-to-Agent Protocol.\nSends a JSON-RPC 2.0 message to the assistant.\n\n- **Request**: Provide an object with `jsonrpc`, `id`, `method`, and optional `params`.\n- **Response**: Returns a JSON-RPC response with task information or error.\n\n**Supported Methods:**\n- `message/send`: Send a message to the assistant\n- `tasks/get`: Get the status and result of a task\n\n**Notes:**\n- Supports threaded conversations via thread context\n- Messages can contain text and data parts\n- Tasks run asynchronously and return completion status\n",
+        "parameters": [
+          {
+            "name": "assistant_id",
+            "in": "path",
+            "required": true,
+            "schema": {
+              "type": "string",
+              "format": "uuid"
+            },
+            "description": "The ID of the assistant to communicate with"
+          },
+          {
+            "name": "Accept",
+            "in": "header",
+            "required": true,
+            "schema": {
+              "type": "string",
+              "enum": ["application/json"]
+            },
+            "description": "Must be application/json"
+          }
+        ],
+        "requestBody": {
+          "required": true,
+          "content": {
+            "application/json": {
+              "schema": {
+                "type": "object",
+                "properties": {
+                  "jsonrpc": {
+                    "type": "string",
+                    "enum": ["2.0"],
+                    "description": "JSON-RPC version"
+                  },
+                  "id": {
+                    "type": "string",
+                    "description": "Request identifier"
+                  },
+                  "method": {
+                    "type": "string",
+                    "enum": ["message/send", "tasks/get"],
+                    "description": "The method to invoke"
+                  },
+                  "params": {
+                    "type": "object",
+                    "description": "Method parameters",
+                    "oneOf": [
+                      {
+                        "title": "Message Send Parameters",
+                        "properties": {
+                          "message": {
+                            "type": "object",
+                            "properties": {
+                              "role": {
+                                "type": "string",
+                                "enum": ["user", "assistant"],
+                                "description": "Message role"
+                              },
+                              "parts": {
+                                "type": "array",
+                                "items": {
+                                  "oneOf": [
+                                    {
+                                      "title": "Text Part",
+                                      "type": "object",
+                                      "properties": {
+                                        "kind": {
+                                          "type": "string",
+                                          "enum": ["text"]
+                                        },
+                                        "text": {
+                                          "type": "string"
+                                        }
+                                      },
+                                      "required": ["kind", "text"]
+                                    },
+                                    {
+                                      "title": "Data Part", 
+                                      "type": "object",
+                                      "properties": {
+                                        "kind": {
+                                          "type": "string",
+                                          "enum": ["data"]
+                                        },
+                                        "data": {
+                                          "type": "object"
+                                        }
+                                      },
+                                      "required": ["kind", "data"]
+                                    }
+                                  ]
+                                },
+                                "description": "Message parts"
+                              },
+                              "messageId": {
+                                "type": "string",
+                                "description": "Unique message identifier"
+                              }
+                            },
+                            "required": ["role", "parts", "messageId"]
+                          },
+                          "thread": {
+                            "type": "object",
+                            "properties": {
+                              "threadId": {
+                                "type": "string",
+                                "description": "Thread identifier for conversation context"
+                              }
+                            },
+                            "description": "Optional thread context"
+                          }
+                        },
+                        "required": ["message"]
+                      },
+                      {
+                        "title": "Task Get Parameters",
+                        "properties": {
+                          "taskId": {
+                            "type": "string",
+                            "description": "Task identifier to retrieve"
+                          }
+                        },
+                        "required": ["taskId"]
+                      }
+                    ]
+                  }
+                },
+                "required": ["jsonrpc", "id", "method"]
+              }
+            }
+          }
+        },
+        "responses": {
+          "200": {
+            "description": "JSON-RPC response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "type": "object",
+                  "properties": {
+                    "jsonrpc": {
+                      "type": "string",
+                      "enum": ["2.0"]
+                    },
+                    "id": {
+                      "type": "string"
+                    },
+                    "result": {
+                      "type": "object",
+                      "description": "Success result containing task information or task details"
+                    },
+                    "error": {
+                      "type": "object",
+                      "properties": {
+                        "code": {
+                          "type": "integer"
+                        },
+                        "message": {
+                          "type": "string"
+                        }
+                      },
+                      "description": "Error information if request failed"
+                    }
+                  },
+                  "required": ["jsonrpc", "id"]
+                }
+              }
+            }
+          },
+          "400": {
+            "description": "Bad request - invalid JSON-RPC or missing Accept header"
+          },
+          "404": {
+            "description": "Assistant not found"
+          },
+          "500": {
+            "description": "Internal server error"
+          }
+        },
+        "tags": [
+          "A2A"
+        ]
+      }
+    },
    "/mcp/": {
      "post": {
        "operationId": "post_mcp",
@@ -4413,6 +4629,17 @@
            "title": "Checkpoint During",
            "description": "Whether to checkpoint during the run.",
            "default": false
+          },
+          "durability": {
+            "type": "string",
+            "enum": [
+              "sync",
+              "async",
+              "exit"
+            ],
+            "title": "Durability",
+            "description": "Durability level for the run. Must be one of 'sync', 'async', or 'exit'.",
+            "default": "async"
          }
        },
        "type": "object",
@@ -4649,6 +4876,17 @@
            "title": "Checkpoint During",
            "description": "Whether to checkpoint during the run.",
            "default": false
+          },
+          "durability": {
+            "type": "string",
+            "enum": [
+              "sync",
+              "async",
+              "exit"
+            ],
+            "title": "Durability",
+            "description": "Durability level for the run. Must be one of 'sync', 'async', or 'exit'.",
+            "default": "async"
          }
        },
        "type": "object",
@@ -4777,6 +5015,12 @@
      },
      "ThreadSearchRequest": {
        "properties": {
+          "ids": {
+            "type": "array",
+            "items": {"type": "string", "format": "uuid"},
+            "title": "Ids",
+            "description": "List of thread IDs to include. Others are excluded."
+          },
          "metadata": {
            "type": "object",
            "title": "Metadata",
@@ -5017,11 +5261,30 @@
            "type": "object",
            "title": "Metadata",
            "description": "Metadata to merge with existing thread metadata."
+          },
+          "ttl": {
+            "type": "object",
+            "title": "TTL",
+            "description": "The time-to-live for the thread.",
+            "properties": {
+              "strategy": {
+                "type": "string",
+                "enum": [
+                  "delete"
+                ],
+                "description": "The TTL strategy. 'delete' removes the entire thread.",
+                "default": "delete"
+              },
+              "ttl": {
+                "type": "number",
+                "description": "The time-to-live in minutes from now until thread should be swept."
+              }
+            }
          }
        },
        "type": "object",
        "title": "ThreadPatch",
-        "description": "Payload for creating a thread."
+        "description": "Payload for updating a thread."
      },
      "ThreadStateCheckpointRequest": {
        "properties": {
@@ -483,19 +483,19 @@ The LangGraph CLI requires a JSON configuration file that follows this [schema](

    RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 pip install --no-cache-dir -c /api/constraints.txt langchain_community langchain_anthropic langchain_openai wikipedia scikit-learn

-    ADD ./graphs /deps/__outer_graphs/src
+    ADD ./graphs /deps/outer-graphs/src
    RUN set -ex && \
        for line in '[project]' \
                    'name = "graphs"' \
                    'version = "0.1"' \
                    '[tool.setuptools.package-data]' \
                    '"*" = ["**/*"]'; do \
-            echo "$line" >> /deps/__outer_graphs/pyproject.toml; \
+            echo "$line" >> /deps/outer-graphs/pyproject.toml; \
        done

    RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 pip install --no-cache-dir -c /api/constraints.txt -e /deps/*

-    ENV LANGSERVE_GRAPHS='{"agent": "/deps/__outer_graphs/src/agent.py:graph", "storm": "/deps/__outer_graphs/src/storm.py:graph"}'
+    ENV LANGSERVE_GRAPHS='{"agent": "/deps/outer-graphs/src/agent.py:graph", "storm": "/deps/outer-graphs/src/storm.py:graph"}'
    ```

    ???+ note "Updating your langgraph.json file"
@@ -134,7 +134,7 @@ def update_instructions(state: State, store: BaseStore):
    namespace = ("instructions",)
    current_instructions = store.search(namespace)[0]
    # Memory logic
-    prompt = prompt_template.format(instructions=instructions.value["instructions"], conversation=state["messages"])
+    prompt = prompt_template.format(instructions=current_instructions.value["instructions"], conversation=state["messages"])
    output = llm.invoke(prompt)
    new_instructions = output['new_instructions']
    store.put(("agent_instructions",), "agent_a", {"instructions": new_instructions})
@@ -278,4 +278,4 @@ const items = await store.search(
 ```
 :::

-For more information about the memory store, see the [Persistence](persistence.md#memory-store) guide.
+For more information about the memory store, see the [Persistence](persistence.md#memory-store) guide.
@@ -897,5 +897,5 @@ There are two high-level approaches to achieve that:

 An agent might need to have a different state schema from the rest of the agents. For example, a search agent might only need to keep track of queries and retrieved documents. There are two ways to achieve this in LangGraph:

- Define [subgraph](./subgraphs.md) agents with a separate state schema. If there are no shared state keys (channels) between the subgraph and the parent graph, it's important to [add input / output transformations](../how-tos/subgraph.ipynb#different-state-schemas) so that the parent graph knows how to communicate with the subgraphs.
- Define agent node functions with a [private input state schema](../how-tos/graph-api.ipynb#pass-private-state-between-nodes) that is distinct from the overall graph state schema. This allows passing information that is only needed for executing that particular agent.
+- Define [subgraph](./subgraphs.md) agents with a separate state schema. If there are no shared state keys (channels) between the subgraph and the parent graph, it's important to [add input / output transformations](../how-tos/subgraph.md#different-state-schemas) so that the parent graph knows how to communicate with the subgraphs.
+- Define agent node functions with a [private input state schema](../how-tos/graph-api.md#pass-private-state-between-nodes) that is distinct from the overall graph state schema. This allows passing information that is only needed for executing that particular agent.
@@ -1019,7 +1019,7 @@ console.log(await graph.invoke({}, { configurable: { myRuntimeValue: "b" } }));
    # Usage
    input_message = {"role": "user", "content": "hi"}
    # With no configuration, uses default (Anthropic)
-    response_1 = graph.invoke({"messages": [input_message]})["messages"][-1]
+    response_1 = graph.invoke({"messages": [input_message]}, context=ContextSchema())["messages"][-1]
    # Or, can set OpenAI
    response_2 = graph.invoke({"messages": [input_message]}, context={"model_provider": "openai"})["messages"][-1]

@@ -1205,7 +1205,7 @@ There are many use cases where you may wish for your node to have a custom retry
 To configure a retry policy, pass the `retry_policy` parameter to the [add_node](../reference/graphs.md#langgraph.graph.state.StateGraph.add_node). The `retry_policy` parameter takes in a `RetryPolicy` named tuple object. Below we instantiate a `RetryPolicy` object with the default parameters and associate it with a node:

 ```python
-from langgraph.pregel import RetryPolicy
+from langgraph.types import RetryPolicy

 builder.add_node(
    "node_name",
@@ -1260,7 +1260,7 @@ By default, the retry policy retries on any exception except for the following:
    from typing_extensions import TypedDict
    from langchain.chat_models import init_chat_model
    from langgraph.graph import END, MessagesState, StateGraph, START
-    from langgraph.pregel import RetryPolicy
+    from langgraph.types import RetryPolicy
    from langchain_community.utilities import SQLDatabase
    from langchain_core.messages import AIMessage

@@ -1422,15 +1422,15 @@ const builder = new StateGraph(State)
 :::

 ??? info "Why split application steps into a sequence with LangGraph?"
-LangGraph makes it easy to add an underlying persistence layer to your application.
-This allows state to be checkpointed in between the execution of nodes, so your LangGraph nodes govern:
+    LangGraph makes it easy to add an underlying persistence layer to your application.
+    This allows state to be checkpointed in between the execution of nodes, so your LangGraph nodes govern:

-    - How state updates are [checkpointed](../concepts/persistence.md)
-    - How interruptions are resumed in [human-in-the-loop](../concepts/human_in_the_loop.md) workflows
-    - How we can "rewind" and branch-off executions using LangGraph's [time travel](../concepts/time-travel.md) features
+- How state updates are [checkpointed](../concepts/persistence.md)
+- How interruptions are resumed in [human-in-the-loop](../concepts/human_in_the_loop.md) workflows
+- How we can "rewind" and branch-off executions using LangGraph's [time travel](../concepts/time-travel.md) features

-    They also determine how execution steps are [streamed](../concepts/streaming.md), and how your application is visualized
-    and debugged using [LangGraph Studio](../concepts/langgraph_studio.md).
+They also determine how execution steps are [streamed](../concepts/streaming.md), and how your application is visualized
+and debugged using [LangGraph Studio](../concepts/langgraph_studio.md).

 Let's demonstrate an end-to-end example. We will create a sequence of three steps:

@@ -2110,7 +2110,6 @@ builder.add_edge(START, "generate_topics")
 builder.add_conditional_edges("generate_topics", continue_to_jokes, ["generate_joke"])
 builder.add_edge("generate_joke", "best_joke")
 builder.add_edge("best_joke", END)
-builder.add_edge("generate_topics", END)
 graph = builder.compile()
 ```

@@ -2333,7 +2332,7 @@ from IPython.display import Image, display
 display(Image(graph.get_graph().draw_mermaid_png()))
 ```

-![Simple loop graph](assets/graph_api_image_3.png)
+![Simple loop graph](assets/graph_api_image_7.png)
 :::

 :::js
@@ -3272,7 +3271,7 @@ from langchain_core.runnables.graph import CurveStyle, MermaidDrawMethod, NodeSt
 display(Image(app.get_graph().draw_mermaid_png()))
 ```

-![Fractal graph visualization](assets/graph_api_image_5.png)
+![Fractal graph visualization](assets/graph_api_image_10.png)

 **Using Mermaid + Pyppeteer**

@@ -3320,4 +3319,4 @@ const imageBuffer = new Uint8Array(await image.arrayBuffer());

 await fs.writeFile("graph.png", imageBuffer);
 ```
-:::
+:::
@@ -366,8 +366,8 @@ result = graph.invoke(

 # Resume with mapping of interrupt IDs to values
 resume_map = {
-    i.interrupt_id: f"human input for prompt {i.value}"
-    for i in parent.get_state(thread_config).interrupts
+    i.id: f"edited text for {i.value['text_to_revise']}"
+    for i in graph.get_state(config).interrupts
 }
 print(graph.invoke(Command(resume=resume_map), config=config))
 # > {'text_1': 'edited text for original text 1', 'text_2': 'edited text for original text 2'}
@@ -244,7 +244,7 @@ output = agent.invoke(
 print(output["messages"][-1].text())
 ```

-!!! version-added "New in langgraph>=0.6"
+!!! version-added "Added in version 0.6.0"

 :::

@@ -1948,7 +1948,7 @@ const llmWithTools = llm.bindTools(tools);


    # Conditional edge function to route to the tool node or end based upon whether the LLM made a tool call
-    def should_continue(state: MessagesState) -> Literal["environment", END]:
+    def should_continue(state: MessagesState) -> Literal["Action", END]:
        """Decide if we should continue the loop or stop based upon whether the LLM made a tool call"""

        messages = state["messages"]
@@ -291,7 +291,7 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
    }

    .md-banner {
-      background-color: #CFC9FA;
+      background-color: #FFAE42;
      color: #000000;
    }

@@ -360,5 +360,5 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
 {% endblock %}

 {% block announce %}
-Our new LangChain Academy Course Deep Research with LangGraph is now live! <a href="https://academy.langchain.com/courses/deep-research-with-langgraph/?utm_medium=internal&utm_source=docs&utm_campaign=q3-2025_deep-research-course_co" target="_blank">Enroll for free</a>.
+These docs will be deprecated and removed with the release of LangGraph v1.0 in October 2025. <a href="https://docs.langchain.com/oss/python/langgraph/overview" target="_blank">Visit the v1.0 alpha docs</a>
 {% endblock %}
@@ -7,14 +7,14 @@ name = "langgraph-docs"
 version = "0.0.1"
 description = "LangGraph docs"
 authors = []
-requires-python = "~=3.11"
+requires-python = ">=3.11.0,<4.0.0"
 readme = "README.md"
 license = "MIT"
 dependencies = [
    "aiohappyeyeballs==2.4.3",
-    "hub>=3.0.1,<4",
-    "xxhash>=3.5.0,<4",
-    "black>=25.1.0,<26",
+    "hub>=3.0.1,<4.0.0",
+    "xxhash>=3.5.0,<4.0.0",
+    "black>=25.1.0,<26.0.0",
 ]

 [dependency-groups]
@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.11, <4"
 resolution-markers = [
    "python_full_version >= '3.13' and platform_python_implementation != 'PyPy'",
@@ -2337,7 +2337,7 @@ wheels = [

 [[package]]
 name = "langgraph"
-version = "0.6.2"
+version = "0.6.7"
 source = { editable = "../libs/langgraph" }
 dependencies = [
    { name = "langchain-core" },
@@ -2380,6 +2380,7 @@ dev = [
    { name = "pytest-repeat" },
    { name = "pytest-watcher" },
    { name = "pytest-xdist", extras = ["psutil"] },
+    { name = "redis" },
    { name = "ruff" },
    { name = "syrupy" },
    { name = "types-requests" },
@@ -2413,6 +2414,7 @@ dev = [
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
    { name = "pytest-watcher" },
+    { name = "redis" },
    { name = "ruff" },
 ]

@@ -2643,7 +2645,7 @@ test = [

 [[package]]
 name = "langgraph-prebuilt"
-version = "0.6.2"
+version = "0.6.4"
 source = { editable = "../libs/prebuilt" }
 dependencies = [
    { name = "langchain-core" },
@@ -2674,7 +2676,6 @@ dev = [

 [[package]]
 name = "langgraph-sdk"
-version = "0.2.0"
 source = { editable = "../libs/sdk-py" }
 dependencies = [
    { name = "httpx" },
@@ -5,7 +5,7 @@
   "id": "18526f23",
   "metadata": {},
   "source": [
-    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/persistence_postgres.ipynb"
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/memory/add-memory.md"
   ]
  }
 ],
@@ -707,7 +707,9 @@
    "    \"\"\"\n",
    "    Find all tool calls in the messages returned\n",
    "    \"\"\"\n",
-    "    tool_calls = [tc['name'] for m in messages['messages'] for tc in getattr(m, 'tool_calls', [])]\n",
+    "    tool_calls = [\n",
+    "        tc[\"name\"] for m in messages[\"messages\"] for tc in getattr(m, \"tool_calls\", [])\n",
+    "    ]\n",
    "    return tool_calls\n",
    "\n",
    "\n",
@@ -7,11 +7,6 @@ from contextlib import contextmanager
 from typing import Any

 from langchain_core.runnables import RunnableConfig
-from psycopg import Capabilities, Connection, Cursor, Pipeline
-from psycopg.rows import DictRow, dict_row
-from psycopg.types.json import Jsonb
-from psycopg_pool import ConnectionPool
-
 from langgraph.checkpoint.base import (
    WRITES_IDX_MAP,
    ChannelVersions,
@@ -19,12 +14,17 @@ from langgraph.checkpoint.base import (
    CheckpointMetadata,
    CheckpointTuple,
    get_checkpoint_id,
-    get_checkpoint_metadata,
+    get_serializable_checkpoint_metadata,
 )
+from langgraph.checkpoint.serde.base import SerializerProtocol
+from psycopg import Capabilities, Connection, Cursor, Pipeline
+from psycopg.rows import DictRow, dict_row
+from psycopg.types.json import Jsonb
+from psycopg_pool import ConnectionPool
+
 from langgraph.checkpoint.postgres import _internal
 from langgraph.checkpoint.postgres.base import BasePostgresSaver
 from langgraph.checkpoint.postgres.shallow import ShallowPostgresSaver
-from langgraph.checkpoint.serde.base import SerializerProtocol

 Conn = _internal.Conn  # For backward compatibility

@@ -325,7 +325,7 @@ class PostgresSaver(BasePostgresSaver):
                    checkpoint["id"],
                    checkpoint_id,
                    Jsonb(copy),
-                    Jsonb(get_checkpoint_metadata(config, metadata)),
+                    Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
                ),
            )
        return next_config
@@ -450,7 +450,7 @@ class PostgresSaver(BasePostgresSaver):
            {
                **value["checkpoint"],
                "channel_values": {
-                    **value["checkpoint"].get("channel_values"),
+                    **(value["checkpoint"].get("channel_values") or {}),
                    **self._load_blobs(value["channel_values"]),
                },
            },
@@ -7,11 +7,6 @@ from contextlib import asynccontextmanager
 from typing import Any

 from langchain_core.runnables import RunnableConfig
-from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
-from psycopg.rows import DictRow, dict_row
-from psycopg.types.json import Jsonb
-from psycopg_pool import AsyncConnectionPool
-
 from langgraph.checkpoint.base import (
    WRITES_IDX_MAP,
    ChannelVersions,
@@ -19,12 +14,17 @@ from langgraph.checkpoint.base import (
    CheckpointMetadata,
    CheckpointTuple,
    get_checkpoint_id,
-    get_checkpoint_metadata,
+    get_serializable_checkpoint_metadata,
 )
+from langgraph.checkpoint.serde.base import SerializerProtocol
+from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
+from psycopg.rows import DictRow, dict_row
+from psycopg.types.json import Jsonb
+from psycopg_pool import AsyncConnectionPool
+
 from langgraph.checkpoint.postgres import _ainternal
 from langgraph.checkpoint.postgres.base import BasePostgresSaver
 from langgraph.checkpoint.postgres.shallow import AsyncShallowPostgresSaver
-from langgraph.checkpoint.serde.base import SerializerProtocol

 Conn = _ainternal.Conn  # For backward compatibility

@@ -283,7 +283,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
                    checkpoint["id"],
                    checkpoint_id,
                    Jsonb(copy),
-                    Jsonb(get_checkpoint_metadata(config, metadata)),
+                    Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
                ),
            )
        return next_config
@@ -409,7 +409,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
            {
                **value["checkpoint"],
                "channel_values": {
-                    **value["checkpoint"].get("channel_values"),
+                    **(value["checkpoint"].get("channel_values") or {}),
                    **self._load_blobs(value["channel_values"]),
                },
            },
@@ -1,12 +1,12 @@
 from __future__ import annotations

 import random
+import warnings
 from collections.abc import Sequence
+from importlib.metadata import version as get_version
 from typing import Any, Optional, cast

 from langchain_core.runnables import RunnableConfig
-from psycopg.types.json import Jsonb
-
 from langgraph.checkpoint.base import (
    WRITES_IDX_MAP,
    BaseCheckpointSaver,
@@ -14,9 +14,22 @@ from langgraph.checkpoint.base import (
    get_checkpoint_id,
 )
 from langgraph.checkpoint.serde.types import TASKS
+from psycopg.types.json import Jsonb

 MetadataInput = Optional[dict[str, Any]]

+try:
+    major, minor = get_version("langgraph").split(".")[:2]
+    if int(major) == 0 and int(minor) < 5:
+        warnings.warn(
+            "You're using incompatible versions of langgraph and checkpoint-postgres. Please upgrade langgraph to avoid unexpected behavior.",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+except Exception:
+    # skip version check if running from source
+    pass
+
 """
 To add a new migration, add a new string to the MIGRATIONS list.
 The position of the migration in the list is the version number.
@@ -6,6 +6,16 @@ from contextlib import asynccontextmanager, contextmanager
 from typing import Any, Optional

 from langchain_core.runnables import RunnableConfig
+from langgraph.checkpoint.base import (
+    WRITES_IDX_MAP,
+    ChannelVersions,
+    Checkpoint,
+    CheckpointMetadata,
+    CheckpointTuple,
+    get_serializable_checkpoint_metadata,
+)
+from langgraph.checkpoint.serde.base import SerializerProtocol
+from langgraph.checkpoint.serde.types import TASKS
 from psycopg import (
    AsyncConnection,
    AsyncCursor,
@@ -19,18 +29,8 @@ from psycopg.rows import DictRow, dict_row
 from psycopg.types.json import Jsonb
 from psycopg_pool import AsyncConnectionPool, ConnectionPool

-from langgraph.checkpoint.base import (
-    WRITES_IDX_MAP,
-    ChannelVersions,
-    Checkpoint,
-    CheckpointMetadata,
-    CheckpointTuple,
-    get_checkpoint_metadata,
-)
 from langgraph.checkpoint.postgres import _ainternal, _internal
 from langgraph.checkpoint.postgres.base import BasePostgresSaver
-from langgraph.checkpoint.serde.base import SerializerProtocol
-from langgraph.checkpoint.serde.types import TASKS

 """
 To add a new migration, add a new string to the MIGRATIONS list.
@@ -441,7 +441,7 @@ class ShallowPostgresSaver(BasePostgresSaver):
                    thread_id,
                    checkpoint_ns,
                    Jsonb(copy),
-                    Jsonb(get_checkpoint_metadata(config, metadata)),
+                    Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
                ),
            )
        return next_config
@@ -774,7 +774,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
                    thread_id,
                    checkpoint_ns,
                    Jsonb(copy),
-                    Jsonb(get_checkpoint_metadata(config, metadata)),
+                    Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
                ),
            )
        return next_config
@@ -1,4 +1,4 @@
 from langgraph.store.postgres.aio import AsyncPostgresStore
-from langgraph.store.postgres.base import PostgresStore
+from langgraph.store.postgres.base import PoolConfig, PostgresStore

-__all__ = ["AsyncPostgresStore", "PostgresStore"]
+__all__ = ["AsyncPostgresStore", "PoolConfig", "PostgresStore"]
@@ -8,11 +8,6 @@ from types import TracebackType
 from typing import Any, Callable, cast

 import orjson
-from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
-from psycopg.rows import DictRow, dict_row
-from psycopg_pool import AsyncConnectionPool
-
-from langgraph.checkpoint.postgres import _ainternal
 from langgraph.store.base import (
    GetOp,
    ListNamespacesOp,
@@ -22,6 +17,11 @@ from langgraph.store.base import (
    SearchOp,
 )
 from langgraph.store.base.batch import AsyncBatchedBaseStore
+from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
+from psycopg.rows import DictRow, dict_row
+from psycopg_pool import AsyncConnectionPool
+
+from langgraph.checkpoint.postgres import _ainternal
 from langgraph.store.postgres.base import (
    PLACEHOLDER,
    BasePostgresStore,
@@ -22,14 +22,6 @@ from typing import (
 )

 import orjson
-from psycopg import Capabilities, Connection, Cursor, Pipeline
-from psycopg.rows import DictRow, dict_row
-from psycopg.types.json import Jsonb
-from psycopg_pool import ConnectionPool
-from typing_extensions import TypedDict
-
-from langgraph.checkpoint.postgres import _ainternal as _ainternal
-from langgraph.checkpoint.postgres import _internal as _pg_internal
 from langgraph.store.base import (
    BaseStore,
    GetOp,
@@ -46,6 +38,14 @@ from langgraph.store.base import (
    get_text_at_path,
    tokenize_path,
 )
+from psycopg import Capabilities, Connection, Cursor, Pipeline
+from psycopg.rows import DictRow, dict_row
+from psycopg.types.json import Jsonb
+from psycopg_pool import ConnectionPool
+from typing_extensions import TypedDict
+
+from langgraph.checkpoint.postgres import _ainternal as _ainternal
+from langgraph.checkpoint.postgres import _internal as _pg_internal

 if TYPE_CHECKING:
    from langchain_core.embeddings import Embeddings
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph-checkpoint-postgres"
-version = "2.0.23"
+version = "2.0.25"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 authors = []
 requires-python = ">=3.9"
@@ -12,7 +12,7 @@ readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
 dependencies = [
-  "langgraph-checkpoint>=2.0.21,<3.0.0",
+  "langgraph-checkpoint>=2.1.2,<3.0.0",
  "orjson>=3.10.1",
  "psycopg>=3.2.0",
  "psycopg-pool>=3.2.0",
@@ -6,10 +6,6 @@ from uuid import uuid4

 import pytest
 from langchain_core.runnables import RunnableConfig
-from psycopg import AsyncConnection
-from psycopg.rows import dict_row
-from psycopg_pool import AsyncConnectionPool
-
 from langgraph.checkpoint.base import (
    EXCLUDED_METADATA_KEYS,
    Checkpoint,
@@ -17,11 +13,15 @@ from langgraph.checkpoint.base import (
    create_checkpoint,
    empty_checkpoint,
 )
+from langgraph.checkpoint.serde.types import TASKS
+from psycopg import AsyncConnection
+from psycopg.rows import dict_row
+from psycopg_pool import AsyncConnectionPool
+
 from langgraph.checkpoint.postgres.aio import (
    AsyncPostgresSaver,
    AsyncShallowPostgresSaver,
 )
-from langgraph.checkpoint.serde.types import TASKS
 from tests.conftest import DEFAULT_POSTGRES_URI


@@ -187,13 +187,11 @@ def test_data():
    metadata_1: CheckpointMetadata = {
        "source": "input",
        "step": 2,
-        "writes": {},
        "score": 1,
    }
    metadata_2: CheckpointMetadata = {
        "source": "loop",
        "step": 1,
-        "writes": {"foo": "bar"},
        "score": None,
    }
    metadata_3: CheckpointMetadata = {}
@@ -220,7 +218,6 @@ async def test_combined_metadata(saver_name: str, test_data) -> None:
        metadata: CheckpointMetadata = {
            "source": "loop",
            "step": 1,
-            "writes": {"foo": "bar"},
            "score": None,
        }
        await saver.aput(config, chkpnt, metadata, {})
@@ -246,7 +243,6 @@ async def test_asearch(saver_name: str, test_data) -> None:
        query_1 = {"source": "input"}  # search by 1 key
        query_2 = {
            "step": 1,
-            "writes": {"foo": "bar"},
        }  # search by multiple keys
        query_3: dict[str, Any] = {}  # search by no keys, return all checkpoints
        query_4 = {"source": "update", "step": 1}  # no match
@@ -344,3 +340,34 @@ async def test_pending_sends_migration(saver_name: str) -> None:
            TASKS: ["send-1", "send-2", "send-3"]
        }
        assert TASKS in search_results[0].checkpoint["channel_versions"]
+
+
+@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
+async def test_get_checkpoint_no_channel_values(
+    monkeypatch, saver_name: str, test_data
+) -> None:
+    """Backwards compatibility test that verifies a checkpoint with no channel_values key can be retrieved without throwing an error."""
+    async with _saver(saver_name) as saver:
+        config = {
+            "configurable": {
+                "thread_id": "thread-2",
+                "checkpoint_ns": "",
+                "__super_private_key": "super_private_value",
+            },
+            "metadata": {"run_id": "my_run_id"},
+        }
+        chkpnt: Checkpoint = create_checkpoint(empty_checkpoint(), {}, 1)
+        await saver.aput(config, chkpnt, {}, {})
+
+        load_checkpoint_tuple = saver._load_checkpoint_tuple
+
+        def patched_load_checkpoint_tuple(value):
+            value["checkpoint"].pop("channel_values", None)
+            return load_checkpoint_tuple(value)
+
+        monkeypatch.setattr(
+            saver, "_load_checkpoint_tuple", patched_load_checkpoint_tuple
+        )
+
+        checkpoint = await saver.aget_tuple(config)
+        assert checkpoint.checkpoint["channel_values"] == {}
@@ -12,8 +12,6 @@ from typing import Any

 import pytest
 from langchain_core.embeddings import Embeddings
-from psycopg import AsyncConnection
-
 from langgraph.store.base import (
    GetOp,
    Item,
@@ -21,6 +19,8 @@ from langgraph.store.base import (
    PutOp,
    SearchOp,
 )
+from psycopg import AsyncConnection
+
 from langgraph.store.postgres import AsyncPostgresStore
 from tests.conftest import (
    DEFAULT_URI,
@@ -9,8 +9,6 @@ from uuid import uuid4

 import pytest
 from langchain_core.embeddings import Embeddings
-from psycopg import Connection
-
 from langgraph.store.base import (
    GetOp,
    Item,
@@ -19,6 +17,8 @@ from langgraph.store.base import (
    PutOp,
    SearchOp,
 )
+from psycopg import Connection
+
 from langgraph.store.postgres import PostgresStore
 from tests.conftest import (
    DEFAULT_URI,
@@ -861,3 +861,41 @@ def test_store_ttl(store):
    # Now has been (TTL_SECONDS-2)*2 > TTL_SECONDS + TTL_SECONDS/2
    res = store.search(ns, query="bar", refresh_ttl=False)
    assert len(res) == 0
+
+
+@pytest.mark.parametrize(
+    "vector_type,distance_type",
+    [
+        ("vector", "cosine"),
+        ("vector", "inner_product"),
+        ("halfvec", "cosine"),
+        ("halfvec", "inner_product"),
+    ],
+)
+def test_non_ascii(
+    request: Any,
+    fake_embeddings: CharacterEmbeddings,
+    vector_type: str,
+    distance_type: str,
+) -> None:
+    """Test support for non-ascii characters"""
+    with _create_vector_store(vector_type, distance_type, fake_embeddings) as store:
+        store.put(("user_123", "memories"), "1", {"text": "这是中文"})  # Chinese
+        store.put(
+            ("user_123", "memories"), "2", {"text": "これは日本語です"}
+        )  # Japanese
+        store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"})  # Korean
+        store.put(("user_123", "memories"), "4", {"text": "Это русский"})  # Russian
+        store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"})  # Hindi
+
+        result1 = store.search(("user_123", "memories"), query="这是中文")
+        result2 = store.search(("user_123", "memories"), query="これは日本語です")
+        result3 = store.search(("user_123", "memories"), query="이건 한국어야")
+        result4 = store.search(("user_123", "memories"), query="Это русский")
+        result5 = store.search(("user_123", "memories"), query="यह रूसी है")
+
+        assert result1[0].key == "1"
+        assert result2[0].key == "2"
+        assert result3[0].key == "3"
+        assert result4[0].key == "4"
+        assert result5[0].key == "5"
@@ -7,10 +7,6 @@ from uuid import uuid4

 import pytest
 from langchain_core.runnables import RunnableConfig
-from psycopg import Connection
-from psycopg.rows import dict_row
-from psycopg_pool import ConnectionPool
-
 from langgraph.checkpoint.base import (
    EXCLUDED_METADATA_KEYS,
    Checkpoint,
@@ -18,8 +14,12 @@ from langgraph.checkpoint.base import (
    create_checkpoint,
    empty_checkpoint,
 )
-from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver
 from langgraph.checkpoint.serde.types import TASKS
+from psycopg import Connection
+from psycopg.rows import dict_row
+from psycopg_pool import ConnectionPool
+
+from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver
 from tests.conftest import DEFAULT_POSTGRES_URI


@@ -169,13 +169,11 @@ def test_data():
    metadata_1: CheckpointMetadata = {
        "source": "input",
        "step": 2,
-        "writes": {},
        "score": 1,
    }
    metadata_2: CheckpointMetadata = {
        "source": "loop",
        "step": 1,
-        "writes": {"foo": "bar"},
        "score": None,
    }
    metadata_3: CheckpointMetadata = {}
@@ -202,7 +200,6 @@ def test_combined_metadata(saver_name: str, test_data) -> None:
        metadata: CheckpointMetadata = {
            "source": "loop",
            "step": 1,
-            "writes": {"foo": "bar"},
            "score": None,
        }
        saver.put(config, chkpnt, metadata, {})
@@ -228,7 +225,6 @@ def test_search(saver_name: str, test_data) -> None:
        query_1 = {"source": "input"}  # search by 1 key
        query_2 = {
            "step": 1,
-            "writes": {"foo": "bar"},
        }  # search by multiple keys
        query_3: dict[str, Any] = {}  # search by no keys, return all checkpoints
        query_4 = {"source": "update", "step": 1}  # no match
@@ -332,3 +328,33 @@ def test_pending_sends_migration(saver_name: str) -> None:
            TASKS: ["send-1", "send-2", "send-3"]
        }
        assert TASKS in search_results[0].checkpoint["channel_versions"]
+
+
+@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
+def test_get_checkpoint_no_channel_values(
+    monkeypatch, saver_name: str, test_data
+) -> None:
+    """Backwards compatibility test that verifies a checkpoint with no channel_values key can be retrieved without throwing an error."""
+    with _saver(saver_name) as saver:
+        config = {
+            "configurable": {
+                "thread_id": "thread-2",
+                "checkpoint_ns": "",
+                "__super_private_key": "super_private_value",
+            },
+        }
+        chkpnt: Checkpoint = create_checkpoint(empty_checkpoint(), {}, 1)
+        saver.put(config, chkpnt, {}, {})
+
+        load_checkpoint_tuple = saver._load_checkpoint_tuple
+
+        def patched_load_checkpoint_tuple(value):
+            value["checkpoint"].pop("channel_values", None)
+            return load_checkpoint_tuple(value)
+
+        monkeypatch.setattr(
+            saver, "_load_checkpoint_tuple", patched_load_checkpoint_tuple
+        )
+
+        checkpoint = saver.get_tuple(config)
+        assert checkpoint.checkpoint["channel_values"] == {}
@@ -8,7 +8,6 @@ from contextlib import closing, contextmanager
 from typing import Any, cast

 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import (
    WRITES_IDX_MAP,
    BaseCheckpointSaver,
@@ -21,6 +20,7 @@ from langgraph.checkpoint.base import (
    get_checkpoint_metadata,
 )
 from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
+
 from langgraph.checkpoint.sqlite.utils import search_where

 _AIO_ERROR_MSG = (
@@ -8,7 +8,6 @@ from typing import Any, Callable, TypeVar, cast

 import aiosqlite
 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import (
    WRITES_IDX_MAP,
    BaseCheckpointSaver,
@@ -21,6 +20,7 @@ from langgraph.checkpoint.base import (
    get_checkpoint_metadata,
 )
 from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
+
 from langgraph.checkpoint.sqlite.utils import search_where

 T = TypeVar("T", bound=Callable)
@@ -5,7 +5,6 @@ from collections.abc import Sequence
 from typing import Any

 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import get_checkpoint_id


@@ -11,7 +11,6 @@ from typing import Any, Callable, cast
 import aiosqlite
 import orjson
 import sqlite_vec  # type: ignore[import-untyped]
-
 from langgraph.store.base import (
    GetOp,
    ListNamespacesOp,
@@ -22,6 +21,7 @@ from langgraph.store.base import (
    TTLConfig,
 )
 from langgraph.store.base.batch import AsyncBatchedBaseStore
+
 from langgraph.store.sqlite.base import (
    _PLACEHOLDER,
    BaseSqliteStore,
@@ -507,7 +507,9 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
            results: List to store results in.
            cur: Database cursor.
        """
-        queries, embedding_requests = self._prepare_batch_search_queries(search_ops)
+        prepared_queries, embedding_requests = self._prepare_batch_search_queries(
+            search_ops
+        )

        # Setup dot_product function if it doesn't exist
        if embedding_requests and self.embeddings:
@@ -515,23 +517,60 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
                [query for _, query in embedding_requests]
            )

-            for (idx, _), embedding in zip(embedding_requests, vectors):
-                _params_list: list = queries[idx][1]
-                for i, param in enumerate(_params_list):
-                    if param is _PLACEHOLDER:
-                        _params_list[i] = sqlite_vec.serialize_float32(embedding)
+            for (embed_req_idx, _), embedding in zip(embedding_requests, vectors):
+                # Find the corresponding query in prepared_queries
+                # The embed_req_idx is the original index in search_ops, which should map to prepared_queries
+                if embed_req_idx < len(prepared_queries):
+                    _params_list: list = prepared_queries[embed_req_idx][1]
+                    for i, param in enumerate(_params_list):
+                        if param is _PLACEHOLDER:
+                            _params_list[i] = sqlite_vec.serialize_float32(embedding)
+                else:
+                    logger.warning(
+                        f"Embedding request index {embed_req_idx} out of bounds for prepared_queries."
+                    )

-        for (idx, _), (query, params) in zip(search_ops, queries):
+        for (original_op_idx, _), (query, params, needs_refresh) in zip(
+            search_ops, prepared_queries
+        ):
            await cur.execute(query, params)
            rows = await cur.fetchall()

-            if "score" in query:
+            if needs_refresh and rows and self.ttl_config:
+                keys_to_refresh = []
+                for row_data in rows:
+                    # Assuming row_data[0] is prefix (text), row_data[1] is key (text)
+                    # These are raw text values directly from the DB.
+                    keys_to_refresh.append((row_data[0], row_data[1]))
+
+                if keys_to_refresh:
+                    updates_by_prefix = defaultdict(list)
+                    for prefix_text, key_text in keys_to_refresh:
+                        updates_by_prefix[prefix_text].append(key_text)
+
+                    for prefix_text, key_list in updates_by_prefix.items():
+                        placeholders = ",".join(["?"] * len(key_list))
+                        update_query = f"""
+                            UPDATE store
+                            SET expires_at = DATETIME(CURRENT_TIMESTAMP, '+' || ttl_minutes || ' minutes')
+                            WHERE prefix = ? AND key IN ({placeholders}) AND ttl_minutes IS NOT NULL
+                        """
+                        update_params = (prefix_text, *key_list)
+                        try:
+                            await cur.execute(update_query, update_params)
+                        except Exception as e:
+                            logger.error(
+                                f"Error during TTL refresh update for search: {e}"
+                            )
+
+            # Process rows into items
+            if "score" in query:  # Vector search query
                items = [
                    _row_to_search_item(
-                        _decode_ns_text(row[0]),
+                        _decode_ns_text(row[0]),  # prefix
                        {
-                            "key": row[1],
-                            "value": row[2],
+                            "key": row[1],  # key
+                            "value": row[2],  # value
                            "created_at": row[3],
                            "updated_at": row[4],
                            "expires_at": row[5] if len(row) > 5 else None,
@@ -545,10 +584,10 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
            else:  # Regular search query
                items = [
                    _row_to_search_item(
-                        _decode_ns_text(row[0]),
+                        _decode_ns_text(row[0]),  # prefix
                        {
-                            "key": row[1],
-                            "value": row[2],
+                            "key": row[1],  # key
+                            "value": row[2],  # value
                            "created_at": row[3],
                            "updated_at": row[4],
                            "expires_at": row[5] if len(row) > 5 else None,
@@ -559,7 +598,7 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
                    for row in rows
                ]

-            results[idx] = items
+            results[original_op_idx] = items

    async def _batch_list_namespaces_ops(
        self,
@@ -13,7 +13,6 @@ from typing import Any, Callable, Literal, NamedTuple, cast

 import orjson
 import sqlite_vec  # type: ignore[import-untyped]
-
 from langgraph.store.base import (
    BaseStore,
    GetOp,
@@ -372,13 +371,15 @@ class BaseSqliteStore:
    def _prepare_batch_search_queries(
        self, search_ops: Sequence[tuple[int, SearchOp]]
    ) -> tuple[
-        list[tuple[str, list[None | str | list[float]]]],  # queries, params
+        list[
+            tuple[str, list[None | str | list[float]], bool]
+        ],  # queries, params, needs_refresh
        list[tuple[int, str]],  # idx, query_text pairs to embed
    ]:
        """
-        Build per-SearchOp SQL queries (with optional TTL refresh) plus embedding requests.
+        Build per-SearchOp SQL queries (with optional TTL refresh flag) plus embedding requests.
        Returns:
-        - queries: list of (SQL, param_list)
+        - queries: list of (SQL, param_list, needs_ttl_refresh_flag)
        - embedding_requests: list of (original_index_in_search_ops, text_query)
        """
        queries = []
@@ -519,30 +520,18 @@ class BaseSqliteStore:
                logger.debug(f"Search query: {base_query}")
                logger.debug(f"Search params: {params}")

-            # Handle TTL refresh if requested
-            if (
+            # Determine if TTL refresh is needed
+            needs_ttl_refresh = bool(
                op.refresh_ttl
                and self.ttl_config
                and self.ttl_config.get("refresh_on_read", False)
-            ):
-                final_sql = f"""
-                    WITH search_results AS (
-                        {base_query}
-                    ),
-                    updated AS (
-                        UPDATE store
-                        SET expires_at = DATETIME(CURRENT_TIMESTAMP, '+' || ttl_minutes || ' minutes')
-                        WHERE (prefix, key) IN (SELECT prefix, key FROM search_results)
-                        AND ttl_minutes IS NOT NULL
-                    )
-                    SELECT * FROM search_results
-                """
-                final_params = params[:]  # copy params
-            else:
-                final_sql = base_query
-                final_params = params
+            )

-            queries.append((final_sql, final_params))
+            # The base_query is now the final_sql, and we pass the refresh flag
+            final_sql = base_query
+            final_params = params
+
+            queries.append((final_sql, final_params, needs_ttl_refresh))

        return queries, embedding_requests

@@ -1331,7 +1320,9 @@ class SqliteStore(BaseSqliteStore, BaseStore):
        results: list[Result],
        cur: sqlite3.Cursor,
    ) -> None:
-        queries, embedding_requests = self._prepare_batch_search_queries(search_ops)
+        prepared_queries, embedding_requests = self._prepare_batch_search_queries(
+            search_ops
+        )

        # Setup similarity functions if they don't exist
        if embedding_requests and self.embeddings:
@@ -1341,16 +1332,48 @@ class SqliteStore(BaseSqliteStore, BaseStore):
            )

            # Replace placeholders with actual embeddings
-            for (idx, _), embedding in zip(embedding_requests, embeddings):
-                _params_list: list = queries[idx][1]
-                for i, param in enumerate(_params_list):
-                    if param is _PLACEHOLDER:
-                        _params_list[i] = sqlite_vec.serialize_float32(embedding)
+            for (embed_req_idx, _), embedding in zip(embedding_requests, embeddings):
+                if embed_req_idx < len(prepared_queries):
+                    _params_list: list = prepared_queries[embed_req_idx][1]
+                    for i, param in enumerate(_params_list):
+                        if param is _PLACEHOLDER:
+                            _params_list[i] = sqlite_vec.serialize_float32(embedding)
+                else:
+                    logger.warning(
+                        f"Embedding request index {embed_req_idx} out of bounds for prepared_queries."
+                    )

-        for (idx, _), (query, params) in zip(search_ops, queries):
+        for (original_op_idx, _), (query, params, needs_refresh) in zip(
+            search_ops, prepared_queries
+        ):
            cur.execute(query, params)
            rows = cur.fetchall()

+            if needs_refresh and rows and self.ttl_config:
+                keys_to_refresh = []
+                for row_data in rows:
+                    keys_to_refresh.append((row_data[0], row_data[1]))
+
+                if keys_to_refresh:
+                    updates_by_prefix = defaultdict(list)
+                    for prefix_text, key_text in keys_to_refresh:
+                        updates_by_prefix[prefix_text].append(key_text)
+
+                    for prefix_text, key_list in updates_by_prefix.items():
+                        placeholders = ",".join(["?"] * len(key_list))
+                        update_query = f"""
+                            UPDATE store
+                            SET expires_at = DATETIME(CURRENT_TIMESTAMP, '+' || ttl_minutes || ' minutes')
+                            WHERE prefix = ? AND key IN ({placeholders}) AND ttl_minutes IS NOT NULL
+                        """
+                        update_params = (prefix_text, *key_list)
+                        try:
+                            cur.execute(update_query, update_params)
+                        except Exception as e:
+                            logger.error(
+                                f"Error during TTL refresh update for search: {e}"
+                            )
+
            if "score" in query:  # Vector search query
                items = [
                    _row_to_search_item(
@@ -1385,7 +1408,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
                    for row in rows
                ]

-            results[idx] = items
+            results[original_op_idx] = items

    def _batch_list_namespaces_ops(
        self,
@@ -2,13 +2,13 @@ from typing import Any

 import pytest
 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import (
    Checkpoint,
    CheckpointMetadata,
    create_checkpoint,
    empty_checkpoint,
 )
+
 from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver


@@ -8,7 +8,6 @@ from contextlib import asynccontextmanager
 from typing import Optional, Union, cast

 import pytest
-
 from langgraph.store.base import (
    GetOp,
    Item,
@@ -16,6 +15,7 @@ from langgraph.store.base import (
    PutOp,
    SearchOp,
 )
+
 from langgraph.store.sqlite import AsyncSqliteStore
 from langgraph.store.sqlite.base import SqliteIndexConfig
 from tests.test_store import CharacterEmbeddings
@@ -2,13 +2,13 @@ from typing import Any, cast

 import pytest
 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import (
    Checkpoint,
    CheckpointMetadata,
    create_checkpoint,
    empty_checkpoint,
 )
+
 from langgraph.checkpoint.sqlite import SqliteSaver
 from langgraph.checkpoint.sqlite.utils import _metadata_predicate, search_where

@@ -116,7 +116,17 @@ class TestSqliteSaver:
                search_results_5[1].config["configurable"]["checkpoint_ns"],
            } == {"", "inner"}

-            # TODO: test before and limit params
+            # search with before param
+            search_results_6 = list(saver.list(None, before=search_results_5[1].config))
+            assert len(search_results_6) == 1
+            assert search_results_6[0].config["configurable"]["thread_id"] == "thread-1"
+
+            # search with limit param
+            search_results_7 = list(
+                saver.list({"configurable": {"thread_id": "thread-2"}}, limit=1)
+            )
+            assert len(search_results_7) == 1
+            assert search_results_7[0].config["configurable"]["thread_id"] == "thread-2"

    def test_search_where(self) -> None:
        # call method / assertions
@@ -9,7 +9,6 @@ from typing import Any, Literal, Optional, Union, cast

 import pytest
 from langchain_core.embeddings import Embeddings
-
 from langgraph.store.base import (
    GetOp,
    Item,
@@ -18,6 +17,7 @@ from langgraph.store.base import (
    PutOp,
    SearchOp,
 )
+
 from langgraph.store.sqlite import SqliteStore
 from langgraph.store.sqlite.base import SqliteIndexConfig

@@ -1067,3 +1067,31 @@ def test_sql_injection_vulnerability(store: SqliteStore) -> None:

    with pytest.raises(ValueError, match="Invalid filter key"):
        store.search(("docs",), filter={malicious_key: "dummy"})
+
+
+@pytest.mark.parametrize("distance_type", VECTOR_TYPES)
+def test_non_ascii(
+    fake_embeddings: CharacterEmbeddings,
+    distance_type: str,
+) -> None:
+    """Test support for non-ascii characters"""
+    with create_vector_store(fake_embeddings, distance_type=distance_type) as store:
+        store.put(("user_123", "memories"), "1", {"text": "这是中文"})  # Chinese
+        store.put(
+            ("user_123", "memories"), "2", {"text": "これは日本語です"}
+        )  # Japanese
+        store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"})  # Korean
+        store.put(("user_123", "memories"), "4", {"text": "Это русский"})  # Russian
+        store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"})  # Hindi
+
+        result1 = store.search(("user_123", "memories"), query="这是中文")
+        result2 = store.search(("user_123", "memories"), query="これは日本語です")
+        result3 = store.search(("user_123", "memories"), query="이건 한국어야")
+        result4 = store.search(("user_123", "memories"), query="Это русский")
+        result5 = store.search(("user_123", "memories"), query="यह रूसी है")
+
+        assert result1[0].key == "1"
+        assert result2[0].key == "2"
+        assert result3[0].key == "3"
+        assert result4[0].key == "4"
+        assert result5[0].key == "5"
@@ -7,6 +7,7 @@ import time
 from collections.abc import Generator

 import pytest
+from langgraph.store.base import TTLConfig

 from langgraph.store.sqlite import SqliteStore
 from langgraph.store.sqlite.aio import AsyncSqliteStore
@@ -93,9 +94,13 @@ def test_ttl_sweeper(temp_db_file: str) -> None:
    ttl_seconds = 2
    ttl_minutes = ttl_seconds / 60

+    ttl_config: TTLConfig = {
+        "default_ttl": ttl_minutes,
+        "sweep_interval_minutes": ttl_minutes / 2,
+    }
    with SqliteStore.from_conn_string(
        temp_db_file,
-        ttl={"default_ttl": ttl_minutes, "sweep_interval_minutes": ttl_minutes / 2},
+        ttl=ttl_config,
    ) as store:
        store.setup()

@@ -298,9 +303,14 @@ async def test_async_ttl_sweeper(temp_db_file: str) -> None:
    ttl_seconds = 2
    ttl_minutes = ttl_seconds / 60

+    ttl_config: TTLConfig = {
+        "default_ttl": ttl_minutes,
+        "sweep_interval_minutes": ttl_minutes / 2,
+    }
+
    async with AsyncSqliteStore.from_conn_string(
        temp_db_file,
-        ttl={"default_ttl": ttl_minutes, "sweep_interval_minutes": ttl_minutes / 2},
+        ttl=ttl_config,
    ) as store:
        await store.setup()

@@ -353,3 +363,67 @@ async def test_async_search_with_ttl(temp_db_file: str) -> None:
        # Search after expiration
        results = await store.asearch(("test",), filter={"value": "apple"})
        assert len(results) == 0
+
+
+@pytest.mark.asyncio
+@pytest.mark.flaky(retries=3)
+async def test_async_asearch_refresh_ttl(temp_db_file: str) -> None:
+    """Test TTL refresh on asearch with async API."""
+    ttl_seconds = 4.0  # Increased TTL for less sensitivity to timing
+    ttl_minutes = ttl_seconds / 60.0
+
+    async with AsyncSqliteStore.from_conn_string(
+        temp_db_file, ttl={"default_ttl": ttl_minutes, "refresh_on_read": True}
+    ) as store:
+        await store.setup()
+
+        namespace = ("docs", "user1")
+        # t=0: items put, expire at t=4.0s
+        await store.aput(namespace, "item1", {"text": "content1", "id": 1})
+        await store.aput(namespace, "item2", {"text": "content2", "id": 2})
+
+        # t=3.0s: (after sleep ttl_seconds * 0.75 = 3s)
+        await asyncio.sleep(ttl_seconds * 0.75)
+
+        # Perform asearch with refresh_ttl=True for item1.
+        # item1's TTL should be refreshed. New expiry: t=3.0s + 4.0s = t=7.0s.
+        # item2's TTL is not affected. Expires at t=4.0s.
+        searched_items = await store.asearch(
+            namespace, filter={"id": 1}, refresh_ttl=True
+        )
+        assert len(searched_items) == 1
+        assert searched_items[0].key == "item1"
+
+        # t=5.0s: (after sleep ttl_seconds * 0.5 = 2s more. Total elapsed: 3s + 2s = 5s)
+        await asyncio.sleep(ttl_seconds * 0.5)
+        # At this point:
+        # - item1 (refreshed by asearch) should expire at t=7.0s. Should be ALIVE.
+        # - item2 (original TTL) should have expired at t=4.0s. Should be GONE after sweep.
+
+        await store.sweep_ttl()
+
+        # Check item1 (should exist due to asearch refresh)
+        item1_check1 = await store.aget(namespace, "item1", refresh_ttl=False)
+        assert item1_check1 is not None, (
+            "Item1 should exist after asearch refresh and first sweep"
+        )
+        assert item1_check1.value["text"] == "content1"
+
+        # Check item2 (should be gone)
+        item2_check1 = await store.aget(namespace, "item2", refresh_ttl=False)
+        assert item2_check1 is None, (
+            "Item2 should be gone after its original TTL expired"
+        )
+
+        # t=7.5s: (after sleep ttl_seconds * 0.625 = 2.5s more. Total elapsed: 5s + 2.5s = 7.5s)
+        await asyncio.sleep(ttl_seconds * 0.625)
+        # At this point:
+        # - item1 (refreshed by asearch, expired at t=7.0s) should be GONE after sweep.
+
+        await store.sweep_ttl()
+
+        # Check item1 again (should be gone now)
+        item1_final_check = await store.aget(namespace, "item1", refresh_ttl=False)
+        assert item1_final_check is None, (
+            "Item1 should be gone after its refreshed TTL expired"
+        )
@@ -404,6 +404,16 @@ def get_checkpoint_metadata(
    return metadata


+def get_serializable_checkpoint_metadata(
+    config: RunnableConfig, metadata: CheckpointMetadata
+) -> CheckpointMetadata:
+    """Get checkpoint metadata in a backwards-compatible manner."""
+    checkpoint_metadata = get_checkpoint_metadata(config, metadata)
+    if "writes" in checkpoint_metadata:
+        checkpoint_metadata.pop("writes")
+    return checkpoint_metadata
+
+
 """
 Mapping from error type to error index.
 Regular writes just map to their index in the list of writes being saved.
@@ -238,7 +238,7 @@ def get_text_at_path(obj: Any, path: str | list[str]) -> list[str]:
        - Nested paths in multi-field: "{field1,nested.field2}"
    """
    if not path or path == "$":
-        return [json.dumps(obj, sort_keys=True)]
+        return [json.dumps(obj, sort_keys=True, ensure_ascii=False)]

    tokens = tokenize_path(path) if isinstance(path, str) else path

@@ -249,7 +249,7 @@ def get_text_at_path(obj: Any, path: str | list[str]) -> list[str]:
            elif obj is None:
                return []
            elif isinstance(obj, (list, dict)):
-                return [json.dumps(obj, sort_keys=True)]
+                return [json.dumps(obj, sort_keys=True, ensure_ascii=False)]
            return []

        token = tokens[pos]
@@ -295,7 +295,11 @@ def get_text_at_path(obj: Any, path: str | list[str]) -> list[str]:
                        if isinstance(current_obj, (str, int, float, bool)):
                            results.append(str(current_obj))
                        elif isinstance(current_obj, (list, dict)):
-                            results.append(json.dumps(current_obj, sort_keys=True))
+                            results.append(
+                                json.dumps(
+                                    current_obj, sort_keys=True, ensure_ascii=False
+                                )
+                            )

        # Handle wildcard
        elif token == "*":
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph-checkpoint"
-version = "2.1.1"
+version = "2.1.2"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 authors = []
 requires-python = ">=3.9"
@@ -5,12 +5,13 @@ import time
 import pytest
 import redis

+from langgraph.cache.base import FullKey
 from langgraph.cache.redis import RedisCache


 class TestRedisCache:
    @pytest.fixture(autouse=True)
-    def setup(self):
+    def setup(self) -> None:
        """Set up test Redis client and cache."""
        self.client = redis.Redis(
            host="localhost", port=6379, db=0, decode_responses=False
@@ -20,21 +21,21 @@ class TestRedisCache:
        except redis.ConnectionError:
            pytest.skip("Redis server not available")

-        self.cache = RedisCache(self.client, prefix="test:cache:")
+        self.cache: RedisCache = RedisCache(self.client, prefix="test:cache:")

        # Clean up before each test
        self.client.flushdb()

-    def teardown_method(self):
+    def teardown_method(self) -> None:
        """Clean up after each test."""
        try:
            self.client.flushdb()
        except Exception:
            pass

-    def test_basic_set_and_get(self):
+    def test_basic_set_and_get(self) -> None:
        """Test basic set and get operations."""
-        keys = [(("graph", "node"), "key1")]
+        keys: list[FullKey] = [(("graph", "node"), "key1")]
        values = {keys[0]: ({"result": 42}, None)}

        # Set value
@@ -45,9 +46,9 @@ class TestRedisCache:
        assert len(result) == 1
        assert result[keys[0]] == {"result": 42}

-    def test_batch_operations(self):
+    def test_batch_operations(self) -> None:
        """Test batch set and get operations."""
-        keys = [
+        keys: list[FullKey] = [
            (("graph", "node1"), "key1"),
            (("graph", "node2"), "key2"),
            (("other", "node"), "key3"),
@@ -68,9 +69,9 @@ class TestRedisCache:
        assert result[keys[1]] == {"result": 2}
        assert result[keys[2]] == {"result": 3}

-    def test_ttl_behavior(self):
+    def test_ttl_behavior(self) -> None:
        """Test TTL (time-to-live) functionality."""
-        key = (("graph", "node"), "ttl_key")
+        key: FullKey = (("graph", "node"), "ttl_key")
        values = {key: ({"data": "expires_soon"}, 1)}  # 1 second TTL

        # Set with TTL
@@ -88,10 +89,10 @@ class TestRedisCache:
        result = self.cache.get([key])
        assert len(result) == 0

-    def test_namespace_isolation(self):
+    def test_namespace_isolation(self) -> None:
        """Test that different namespaces are isolated."""
-        key1 = (("graph1", "node"), "same_key")
-        key2 = (("graph2", "node"), "same_key")
+        key1: FullKey = (("graph1", "node"), "same_key")
+        key2: FullKey = (("graph2", "node"), "same_key")

        values = {key1: ({"graph": 1}, None), key2: ({"graph": 2}, None)}

@@ -101,9 +102,12 @@ class TestRedisCache:
        assert result[key1] == {"graph": 1}
        assert result[key2] == {"graph": 2}

-    def test_clear_all(self):
+    def test_clear_all(self) -> None:
        """Test clearing all cached values."""
-        keys = [(("graph", "node1"), "key1"), (("graph", "node2"), "key2")]
+        keys: list[FullKey] = [
+            (("graph", "node1"), "key1"),
+            (("graph", "node2"), "key2"),
+        ]
        values = {keys[0]: ({"result": 1}, None), keys[1]: ({"result": 2}, None)}

        self.cache.set(values)
@@ -119,9 +123,9 @@ class TestRedisCache:
        result = self.cache.get(keys)
        assert len(result) == 0

-    def test_clear_by_namespace(self):
+    def test_clear_by_namespace(self) -> None:
        """Test clearing cached values by namespace."""
-        keys = [
+        keys: list[FullKey] = [
            (("graph1", "node"), "key1"),
            (("graph2", "node"), "key2"),
            (("graph1", "other"), "key3"),
@@ -142,7 +146,7 @@ class TestRedisCache:
        assert len(result) == 1
        assert result[keys[1]] == {"result": 2}

-    def test_empty_operations(self):
+    def test_empty_operations(self) -> None:
        """Test behavior with empty keys/values."""
        # Empty get
        result = self.cache.get([])
@@ -151,14 +155,14 @@ class TestRedisCache:
        # Empty set
        self.cache.set({})  # Should not raise error

-    def test_nonexistent_keys(self):
+    def test_nonexistent_keys(self) -> None:
        """Test getting keys that don't exist."""
-        keys = [(("graph", "node"), "nonexistent")]
+        keys: list[FullKey] = [(("graph", "node"), "nonexistent")]
        result = self.cache.get(keys)
        assert len(result) == 0

    @pytest.mark.asyncio
-    async def test_async_operations(self):
+    async def test_async_operations(self) -> None:
        """Test async set and get operations with sync Redis client."""
        # Create sync Redis client and cache (like main integration tests)
        client = redis.Redis(host="localhost", port=6379, db=1, decode_responses=False)
@@ -167,9 +171,9 @@ class TestRedisCache:
        except Exception:
            pytest.skip("Redis not available")

-        cache = RedisCache(client, prefix="test:async:")
+        cache: RedisCache = RedisCache(client, prefix="test:async:")

-        keys = [(("graph", "node"), "async_key")]
+        keys: list[FullKey] = [(("graph", "node"), "async_key")]
        values = {keys[0]: ({"async": True}, None)}

        # Async set (delegates to sync)
@@ -184,7 +188,7 @@ class TestRedisCache:
        client.flushdb()

    @pytest.mark.asyncio
-    async def test_async_clear(self):
+    async def test_async_clear(self) -> None:
        """Test async clear operations with sync Redis client."""
        # Create sync Redis client and cache (like main integration tests)
        client = redis.Redis(host="localhost", port=6379, db=1, decode_responses=False)
@@ -193,9 +197,9 @@ class TestRedisCache:
        except Exception:
            pytest.skip("Redis not available")

-        cache = RedisCache(client, prefix="test:async:")
+        cache: RedisCache = RedisCache(client, prefix="test:async:")

-        keys = [(("graph", "node"), "key")]
+        keys: list[FullKey] = [(("graph", "node"), "key")]
        values = {keys[0]: ({"data": "test"}, None)}

        await cache.aset(values)
@@ -214,44 +218,44 @@ class TestRedisCache:
        # Cleanup
        client.flushdb()

-    def test_redis_unavailable_get(self):
+    def test_redis_unavailable_get(self) -> None:
        """Test behavior when Redis is unavailable during get operations."""
        # Create cache with non-existent Redis server
        bad_client = redis.Redis(
            host="nonexistent", port=9999, socket_connect_timeout=0.1
        )
-        cache = RedisCache(bad_client, prefix="test:cache:")
+        cache: RedisCache = RedisCache(bad_client, prefix="test:cache:")

-        keys = [(("graph", "node"), "key")]
+        keys: list[FullKey] = [(("graph", "node"), "key")]
        result = cache.get(keys)

        # Should return empty dict when Redis unavailable
        assert result == {}

-    def test_redis_unavailable_set(self):
+    def test_redis_unavailable_set(self) -> None:
        """Test behavior when Redis is unavailable during set operations."""
        # Create cache with non-existent Redis server
        bad_client = redis.Redis(
            host="nonexistent", port=9999, socket_connect_timeout=0.1
        )
-        cache = RedisCache(bad_client, prefix="test:cache:")
+        cache: RedisCache = RedisCache(bad_client, prefix="test:cache:")

-        keys = [(("graph", "node"), "key")]
+        keys: list[FullKey] = [(("graph", "node"), "key")]
        values = {keys[0]: ({"data": "test"}, None)}

        # Should not raise exception when Redis unavailable
        cache.set(values)  # Should silently fail

    @pytest.mark.asyncio
-    async def test_redis_unavailable_async(self):
+    async def test_redis_unavailable_async(self) -> None:
        """Test async behavior when Redis is unavailable."""
        # Create sync cache with non-existent Redis server (like main integration tests)
        bad_client = redis.Redis(
            host="nonexistent", port=9999, socket_connect_timeout=0.1
        )
-        cache = RedisCache(bad_client, prefix="test:cache:")
+        cache: RedisCache = RedisCache(bad_client, prefix="test:cache:")

-        keys = [(("graph", "node"), "key")]
+        keys: list[FullKey] = [(("graph", "node"), "key")]
        values = {keys[0]: ({"data": "test"}, None)}

        # Should return empty dict for get (delegates to sync)
@@ -261,10 +265,10 @@ class TestRedisCache:
        # Should not raise exception for set (delegates to sync)
        await cache.aset(values)  # Should silently fail

-    def test_corrupted_data_handling(self):
+    def test_corrupted_data_handling(self) -> None:
        """Test handling of corrupted data in Redis."""
        # Set some valid data first
-        keys = [(("graph", "node"), "valid_key")]
+        keys: list[FullKey] = [(("graph", "node"), "valid_key")]
        values = {keys[0]: ({"data": "valid"}, None)}
        self.cache.set(values)

@@ -273,33 +277,36 @@ class TestRedisCache:
        self.client.set(corrupted_key, b"invalid:data:format:too:many:colons")

        # Should skip corrupted entry and return only valid ones
-        all_keys = [keys[0], (("graph", "node"), "corrupted_key")]
+        all_keys: list[FullKey] = [keys[0], (("graph", "node"), "corrupted_key")]
        result = self.cache.get(all_keys)

        assert len(result) == 1
        assert result[keys[0]] == {"data": "valid"}

-    def test_key_parsing_edge_cases(self):
+    def test_key_parsing_edge_cases(self) -> None:
        """Test key parsing with edge cases."""
        # Test empty namespace
-        key1 = ((), "empty_ns")
+        key1: FullKey = ((), "empty_ns")
        values = {key1: ({"data": "empty_ns"}, None)}
        self.cache.set(values)
        result = self.cache.get([key1])
        assert result[key1] == {"data": "empty_ns"}

        # Test namespace with special characters
-        key2 = (("graph:with:colons", "node-with-dashes"), "key_with_underscores")
+        key2: FullKey = (
+            ("graph:with:colons", "node-with-dashes"),
+            "key_with_underscores",
+        )
        values = {key2: ({"data": "special_chars"}, None)}
        self.cache.set(values)
        result = self.cache.get([key2])
        assert result[key2] == {"data": "special_chars"}

-    def test_large_data_serialization(self):
+    def test_large_data_serialization(self) -> None:
        """Test handling of large data objects."""
        # Create a large data structure
        large_data = {"large_list": list(range(1000)), "nested": {"data": "x" * 1000}}
-        key = (("graph", "node"), "large_key")
+        key: FullKey = (("graph", "node"), "large_key")
        values = {key: (large_data, None)}

        self.cache.set(values)
@@ -950,8 +950,8 @@ async def test_embed_with_path(fake_embeddings: CharacterEmbeddings) -> None:
    assert results[0].key != results[1].key
    ascore = results[0].score
    bscore = results[1].score
-    assert ascore == bscore
    assert ascore is not None and bscore is not None
+    assert ascore == pytest.approx(bscore, abs=1e-5)

    results = await store.asearch(("test",), query="uuu")
    assert len(results) == 2
@@ -1021,3 +1021,27 @@ async def test_embed_with_path(fake_embeddings: CharacterEmbeddings) -> None:
    assert len(results) == 3
    doc5_result = next(r for r in results if r.key == "doc5")
    assert doc5_result.score is None
+
+
+def test_non_ascii(fake_embeddings: CharacterEmbeddings) -> None:
+    """Test support for non-ascii characters"""
+    store = InMemoryStore(
+        index={"dims": fake_embeddings.dims, "embed": fake_embeddings}
+    )
+    store.put(("user_123", "memories"), "1", {"text": "这是中文"})  # Chinese
+    store.put(("user_123", "memories"), "2", {"text": "これは日本語です"})  # Japanese
+    store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"})  # Korean
+    store.put(("user_123", "memories"), "4", {"text": "Это русский"})  # Russian
+    store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"})  # Hindi
+
+    result1 = store.search(("user_123", "memories"), query="这是中文")
+    result2 = store.search(("user_123", "memories"), query="これは日本語です")
+    result3 = store.search(("user_123", "memories"), query="이건 한국어야")
+    result4 = store.search(("user_123", "memories"), query="Это русский")
+    result5 = store.search(("user_123", "memories"), query="यह रूसी है")
+
+    assert result1[0].key == "1"
+    assert result2[0].key == "2"
+    assert result3[0].key == "3"
+    assert result4[0].key == "4"
+    assert result5[0].key == "5"
@@ -0,0 +1,89 @@
+from collections.abc import Sequence
+from typing import Annotated, Literal, TypedDict
+
+from langchain_community.tools.tavily_search import TavilySearchResults
+from langchain_core.messages import BaseMessage
+from langchain_openai import ChatOpenAI
+from langgraph.graph import END, StateGraph, add_messages
+from langgraph.prebuilt import ToolNode
+
+tools = [TavilySearchResults(max_results=1)]
+
+model_oai = ChatOpenAI(temperature=0)
+
+model_oai = model_oai.bind_tools(tools)
+
+
+class AgentState(TypedDict):
+    messages: Annotated[Sequence[BaseMessage], add_messages]
+
+
+# Define the function that determines whether to continue or not
+def should_continue(state):
+    messages = state["messages"]
+    last_message = messages[-1]
+    # If there are no tool calls, then we finish
+    if not last_message.tool_calls:
+        return "end"
+    # Otherwise if there is, we continue
+    else:
+        return "continue"
+
+
+# Define the function that calls the model
+def call_model(state, config):
+    model = model_oai
+    messages = state["messages"]
+    response = model.invoke(messages)
+    # We return a list, because this will get added to the existing list
+    return {"messages": [response]}
+
+
+# Define the function to execute tools
+tool_node = ToolNode(tools)
+
+
+class ContextSchema(TypedDict):
+    model: Literal["anthropic", "openai"]
+
+
+# Define a new graph
+workflow = StateGraph(AgentState, context_schema=ContextSchema)
+
+# Define the two nodes we will cycle between
+workflow.add_node("agent", call_model)
+workflow.add_node("action", tool_node)
+
+# Set the entrypoint as `agent`
+# This means that this node is the first one called
+workflow.set_entry_point("agent")
+
+# We now add a conditional edge
+workflow.add_conditional_edges(
+    # First, we define the start node. We use `agent`.
+    # This means these are the edges taken after the `agent` node is called.
+    "agent",
+    # Next, we pass in the function that will determine which node is called next.
+    should_continue,
+    # Finally we pass in a mapping.
+    # The keys are strings, and the values are other nodes.
+    # END is a special node marking that the graph should finish.
+    # What will happen is we will call `should_continue`, and then the output of that
+    # will be matched against the keys in this mapping.
+    # Based on which one it matches, that node will then be called.
+    {
+        # If `tools`, then we call the tool node.
+        "continue": "action",
+        # Otherwise we finish.
+        "end": END,
+    },
+)
+
+# We now add a normal edge from `tools` to `agent`.
+# This means that after `tools` is called, `agent` node is called next.
+workflow.add_edge("action", "agent")
+
+# Finally, we compile it!
+# This compiles it into a LangChain Runnable,
+# meaning you can use it as you would any other runnable
+graph = workflow.compile()
@@ -0,0 +1,9 @@
+[project]
+name = "graph-prerelease-reqs-additional-deps"
+version = "0.1.0"
+description = "Test for prerelease stuff"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+  "langgraph==0.6.0"
+]
@@ -0,0 +1,9 @@
+[project]
+name = "graph-prerelease-reqs-zuper-deps"
+version = "0.1.0"
+description = "Test for prerelease stuff"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+  "langchain-openai==0.3.0"
+]
@@ -0,0 +1,13 @@
+{
+    "python_version": "3.12",
+    "dependencies": [
+      ".",
+      "./deps/additional_deps",
+      "./deps/zuper_deps"
+    ],
+    "graphs": {
+      "agent": "./agent.py:graph"
+    },
+    "env": "../.env"
+  }
+  
@@ -0,0 +1,14 @@
+[project]
+name = "graph-prerelease-reqs"
+version = "0.1.0"
+description = "Test for prerelease stuff"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+  "langchain-openai==1.0.0a2",
+  "langgraph==1.0.0a2",
+  "langchain_community>=0.3.0",
+]
+
+[tool.uv]
+prerelease = "allow"
@@ -0,0 +1,89 @@
+from collections.abc import Sequence
+from typing import Annotated, Literal, TypedDict
+
+from langchain_community.tools.tavily_search import TavilySearchResults
+from langchain_core.messages import BaseMessage
+from langchain_openai import ChatOpenAI
+from langgraph.graph import END, StateGraph, add_messages
+from langgraph.prebuilt import ToolNode
+
+tools = [TavilySearchResults(max_results=1)]
+
+model_oai = ChatOpenAI(temperature=0)
+
+model_oai = model_oai.bind_tools(tools)
+
+
+class AgentState(TypedDict):
+    messages: Annotated[Sequence[BaseMessage], add_messages]
+
+
+# Define the function that determines whether to continue or not
+def should_continue(state):
+    messages = state["messages"]
+    last_message = messages[-1]
+    # If there are no tool calls, then we finish
+    if not last_message.tool_calls:
+        return "end"
+    # Otherwise if there is, we continue
+    else:
+        return "continue"
+
+
+# Define the function that calls the model
+def call_model(state, config):
+    model = model_oai
+    messages = state["messages"]
+    response = model.invoke(messages)
+    # We return a list, because this will get added to the existing list
+    return {"messages": [response]}
+
+
+# Define the function to execute tools
+tool_node = ToolNode(tools)
+
+
+class ContextSchema(TypedDict):
+    model: Literal["anthropic", "openai"]
+
+
+# Define a new graph
+workflow = StateGraph(AgentState, context_schema=ContextSchema)
+
+# Define the two nodes we will cycle between
+workflow.add_node("agent", call_model)
+workflow.add_node("action", tool_node)
+
+# Set the entrypoint as `agent`
+# This means that this node is the first one called
+workflow.set_entry_point("agent")
+
+# We now add a conditional edge
+workflow.add_conditional_edges(
+    # First, we define the start node. We use `agent`.
+    # This means these are the edges taken after the `agent` node is called.
+    "agent",
+    # Next, we pass in the function that will determine which node is called next.
+    should_continue,
+    # Finally we pass in a mapping.
+    # The keys are strings, and the values are other nodes.
+    # END is a special node marking that the graph should finish.
+    # What will happen is we will call `should_continue`, and then the output of that
+    # will be matched against the keys in this mapping.
+    # Based on which one it matches, that node will then be called.
+    {
+        # If `tools`, then we call the tool node.
+        "continue": "action",
+        # Otherwise we finish.
+        "end": END,
+    },
+)
+
+# We now add a normal edge from `tools` to `agent`.
+# This means that after `tools` is called, `agent` node is called next.
+workflow.add_edge("action", "agent")
+
+# Finally, we compile it!
+# This compiles it into a LangChain Runnable,
+# meaning you can use it as you would any other runnable
+graph = workflow.compile()
@@ -0,0 +1,11 @@
+{
+    "python_version": "3.12",
+    "dependencies": [
+      "."
+    ],
+    "graphs": {
+      "agent": "./agent.py:graph"
+    },
+    "env": "../.env"
+  }
+  
@@ -0,0 +1,11 @@
+[project]
+name = "graph-prerelease-reqs"
+version = "0.1.0"
+description = "Test for prerelease stuff"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+  "langchain-openai==1.0.0a2",
+  "langgraph==1.0.0a2",
+  "langchain_community>=0.3.0",
+]
@@ -7,6 +7,7 @@ from langchain_core.messages import BaseMessage
 from langchain_openai import ChatOpenAI
 from langgraph.graph import END, StateGraph, add_messages
 from langgraph.prebuilt import ToolNode
+from langgraph.runtime import Runtime

 tools = [TavilySearchResults(max_results=1)]

@@ -17,6 +18,10 @@ model_anth = model_anth.bind_tools(tools)
 model_oai = model_oai.bind_tools(tools)


+class AgentContext(TypedDict):
+    model: Literal["anthropic", "openai"]
+
+
 class AgentState(TypedDict):
    messages: Annotated[Sequence[BaseMessage], add_messages]

@@ -34,8 +39,8 @@ def should_continue(state):


 # Define the function that calls the model
-def call_model(state, config):
-    if config["configurable"].get("model", "anthropic") == "anthropic":
+def call_model(state, runtime: Runtime[AgentContext]):
+    if runtime.context.get("model", "anthropic") == "anthropic":
        model = model_anth
    else:
        model = model_oai
@@ -49,12 +54,8 @@ def call_model(state, config):
 tool_node = ToolNode(tools)


-class ContextSchema(TypedDict):
-    model: Literal["anthropic", "openai"]
-
-
 # Define a new graph
-workflow = StateGraph(AgentState, context_schema=ContextSchema)
+workflow = StateGraph(AgentState, context_schema=AgentContext)

 # Define the two nodes we will cycle between
 workflow.add_node("agent", call_model)
@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
  "python_version": "3.12",
  "dependencies": [
    "langchain_community",
@@ -1,6 +1,6 @@
 from collections.abc import Sequence
 from pathlib import Path
-from typing import Annotated, TypedDict
+from typing import Annotated, Literal, TypedDict

 from langchain_anthropic import ChatAnthropic
 from langchain_community.tools.tavily_search import TavilySearchResults
@@ -8,6 +8,7 @@ from langchain_core.messages import BaseMessage
 from langchain_openai import ChatOpenAI
 from langgraph.graph import END, StateGraph, add_messages
 from langgraph.prebuilt import ToolNode
+from langgraph.runtime import Runtime

 tools = [TavilySearchResults(max_results=1)]

@@ -21,6 +22,10 @@ prompt = open(Path(__file__).parent.parent / "prompt.txt").read()
 subprompt = open(Path(__file__).parent / "subprompt.txt").read()


+class AgentContext(TypedDict):
+    model: Literal["anthropic", "openai"]
+
+
 class AgentState(TypedDict):
    messages: Annotated[Sequence[BaseMessage], add_messages]

@@ -38,8 +43,8 @@ def should_continue(state):


 # Define the function that calls the model
-def call_model(state, config):
-    if config["configurable"].get("model", "anthropic") == "anthropic":
+def call_model(state, runtime: Runtime[AgentContext]):
+    if runtime.context.get("model", "anthropic") == "anthropic":
        model = model_anth
    else:
        model = model_oai
@@ -52,9 +57,8 @@ def call_model(state, config):
 # Define the function to execute tools
 tool_node = ToolNode(tools)

-
 # Define a new graph
-workflow = StateGraph(AgentState)
+workflow = StateGraph(AgentState, context_schema=AgentContext)

 # Define the two nodes we will cycle between
 workflow.add_node("agent", call_model)
@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
  "dependencies": [
    "."
  ],
@@ -1,6 +1,6 @@
 from collections.abc import Sequence
 from pathlib import Path
-from typing import Annotated, TypedDict
+from typing import Annotated, Literal, TypedDict

 from langchain_anthropic import ChatAnthropic
 from langchain_community.tools.tavily_search import TavilySearchResults
@@ -8,6 +8,7 @@ from langchain_core.messages import BaseMessage
 from langchain_openai import ChatOpenAI
 from langgraph.graph import END, StateGraph, add_messages
 from langgraph.prebuilt import ToolNode
+from langgraph.runtime import Runtime

 tools = [TavilySearchResults(max_results=1)]

@@ -21,6 +22,10 @@ prompt = open(Path(__file__).parent.parent / "prompt.txt").read()
 subprompt = open(Path(__file__).parent / "subprompt.txt").read()


+class AgentContext(TypedDict):
+    model: Literal["anthropic", "openai"]
+
+
 class AgentState(TypedDict):
    messages: Annotated[Sequence[BaseMessage], add_messages]

@@ -38,8 +43,8 @@ def should_continue(state):


 # Define the function that calls the model
-def call_model(state, config):
-    if config["configurable"].get("model", "anthropic") == "anthropic":
+def call_model(state, runtime: Runtime[AgentContext]):
+    if runtime.context.get("model", "anthropic") == "anthropic":
        model = model_anth
    else:
        model = model_oai
@@ -54,7 +59,7 @@ tool_node = ToolNode(tools)


 # Define a new graph
-workflow = StateGraph(AgentState)
+workflow = StateGraph(AgentState, context_schema=AgentContext)

 # Define the two nodes we will cycle between
 workflow.add_node("agent", call_model)
@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
  "dependencies": [
    "."
  ],
@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
  "node_version": "20",
  "graphs": {
    "agent": "./src/agent/graph.ts:graph"
@@ -0,0 +1,62 @@
+module.exports = {
+  extends: [
+    "eslint:recommended",
+    "prettier",
+    "plugin:@typescript-eslint/recommended",
+  ],
+  parserOptions: {
+    ecmaVersion: 12,
+    parser: "@typescript-eslint/parser",
+    project: "./tsconfig.json",
+    sourceType: "module",
+  },
+  plugins: ["import", "@typescript-eslint", "no-instanceof"],
+  ignorePatterns: [
+    ".eslintrc.cjs",
+    "scripts",
+    "src/utils/lodash/*",
+    "node_modules",
+    "dist",
+    "dist-cjs",
+    "*.js",
+    "*.cjs",
+    "*.d.ts",
+  ],
+  rules: {
+    "no-process-env": 2,
+    "no-instanceof/no-instanceof": 2,
+    "@typescript-eslint/explicit-module-boundary-types": 0,
+    "@typescript-eslint/no-empty-function": 0,
+    "@typescript-eslint/no-shadow": 0,
+    "@typescript-eslint/no-empty-interface": 0,
+    "@typescript-eslint/no-use-before-define": ["error", "nofunc"],
+    "@typescript-eslint/no-unused-vars": ["warn", { args: "none" }],
+    "@typescript-eslint/no-floating-promises": "error",
+    "@typescript-eslint/no-misused-promises": "error",
+    camelcase: 0,
+    "class-methods-use-this": 0,
+    "import/extensions": [2, "ignorePackages"],
+    "import/no-extraneous-dependencies": [
+      "error",
+      { devDependencies: ["**/*.test.ts"] },
+    ],
+    "import/no-unresolved": 0,
+    "import/prefer-default-export": 0,
+    "keyword-spacing": "error",
+    "max-classes-per-file": 0,
+    "max-len": 0,
+    "no-await-in-loop": 0,
+    "no-bitwise": 0,
+    "no-console": 0,
+    "no-restricted-syntax": 0,
+    "no-shadow": 0,
+    "no-continue": 0,
+    "no-underscore-dangle": 0,
+    "no-use-before-define": 0,
+    "no-useless-constructor": 0,
+    "no-return-await": 0,
+    "consistent-return": 0,
+    "no-else-return": 0,
+    "new-cap": ["error", { properties: false, capIsNew: false }],
+  },
+};
@@ -0,0 +1,7 @@
+{
+  "node_version": "20",
+  "graphs": {
+    "agent": "./src/graph.ts:graph"
+  },
+  "env": "../../.env"
+}
@@ -0,0 +1,18 @@
+{
+  "name": "@js-monorepo-example/agent",
+  "version": "0.0.1",
+  "type": "module",
+  "main": "src/graph.ts",
+  "scripts": {
+    "build": "tsc",
+    "clean": "rm -rf dist"
+  },
+  "dependencies": {
+    "@js-monorepo-example/shared": "*",
+    "@langchain/core": "^0.3.2",
+    "@langchain/langgraph": "^0.2.5"
+  },
+  "devDependencies": {
+    "typescript": "^5.3.3"
+  }
+}
@@ -0,0 +1,47 @@
+/**
+ * Simple LangGraph.js example for monorepo testing
+ */
+import { StateGraph } from "@langchain/langgraph";
+import { RunnableConfig } from "@langchain/core/runnables";
+import { StateAnnotation } from "./state.js";
+import { getGreeting } from "@js-monorepo-example/shared";
+
+/**
+ * Simple node that uses the shared library
+ */
+const callModel = async (
+  state: typeof StateAnnotation.State,
+  _config: RunnableConfig,
+): Promise<typeof StateAnnotation.Update> => {
+  // Use functions from the shared library
+  const greeting = getGreeting();
+
+  return {
+    messages: [
+      {
+        role: "assistant",
+        content: `${greeting}`,
+      },
+    ],
+  };
+};
+
+/**
+ * Simple routing function
+ */
+export const route = (
+  state: typeof StateAnnotation.State,
+): "__end__" | "callModel" => {
+  if (state.messages.length > 0) {
+    return "__end__";
+  }
+  return "callModel";
+};
+
+// Create the graph
+const builder = new StateGraph(StateAnnotation)
+  .addNode("callModel", callModel)
+  .addEdge("__start__", "callModel")
+  .addConditionalEdges("callModel", route);
+
+export const graph = builder.compile();
@@ -0,0 +1,15 @@
+import { BaseMessage, BaseMessageLike } from "@langchain/core/messages";
+import { Annotation, messagesStateReducer } from "@langchain/langgraph";
+
+/**
+ * Simple state annotation for the agent
+ */
+export const StateAnnotation = Annotation.Root({
+  /**
+   * Messages track the primary execution state of the agent.
+   */
+  messages: Annotation<BaseMessage[], BaseMessageLike[]>({
+    reducer: messagesStateReducer,
+    default: () => [],
+  }),
+});
@@ -0,0 +1,9 @@
+{
+  "extends": "../../tsconfig.json",
+  "compilerOptions": {
+    "outDir": "./dist",
+    "rootDir": "./src"
+  },
+  "include": ["src/**/*"],
+  "exclude": ["node_modules", "dist"]
+}
@@ -0,0 +1,14 @@
+{
+  "name": "@js-monorepo-example/shared",
+  "version": "0.0.1",
+  "type": "module",
+  "main": "dist/index.js",
+  "types": "dist/index.d.ts",
+  "scripts": {
+    "build": "tsc",
+    "clean": "rm -rf dist"
+  },
+  "devDependencies": {
+    "typescript": "^5.3.3"
+  }
+}
@@ -0,0 +1,6 @@
+/**
+ * Simple utility functions for monorepo testing
+ */
+export function getGreeting(): string {
+  return "Hello from shared library!";
+}
@@ -0,0 +1,9 @@
+{
+  "extends": "../../tsconfig.json",
+  "compilerOptions": {
+    "outDir": "./dist",
+    "rootDir": "./src"
+  },
+  "include": ["src/**/*"],
+  "exclude": ["node_modules", "dist"]
+}
@@ -0,0 +1,34 @@
+{
+  "name": "js-monorepo-example",
+  "version": "0.0.1",
+  "packageManager": "yarn@1.22.22",
+  "description": "A simple monorepo example for LangGraph integration testing.",
+  "private": true,
+  "workspaces": [
+    "libs/*",
+    "apps/*"
+  ],
+  "type": "module",
+  "scripts": {
+    "build": "turbo build",
+    "clean": "turbo clean",
+    "test": "turbo test",
+    "format": "prettier --write .",
+    "lint": "eslint 'apps/**/*.ts' 'libs/**/*.ts'"
+  },
+  "devDependencies": {
+    "turbo": "^2.5.0",
+    "typescript": "^5.3.3",
+    "@tsconfig/recommended": "^1.0.7",
+    "@eslint/eslintrc": "^3.1.0",
+    "@eslint/js": "^9.9.1",
+    "eslint": "^8.41.0",
+    "eslint-config-prettier": "^8.8.0",
+    "eslint-plugin-import": "^2.27.5",
+    "eslint-plugin-no-instanceof": "^1.0.1",
+    "eslint-plugin-prettier": "^4.2.1",
+    "@typescript-eslint/eslint-plugin": "^5.59.8",
+    "@typescript-eslint/parser": "^5.59.8",
+    "prettier": "^3.3.3"
+  }
+}
@@ -0,0 +1,16 @@
+{
+  "extends": "@tsconfig/recommended",
+  "compilerOptions": {
+    "target": "ES2022",
+    "module": "ESNext",
+    "moduleResolution": "node",
+    "allowSyntheticDefaultImports": true,
+    "esModuleInterop": true,
+    "skipLibCheck": true,
+    "strict": true,
+    "declaration": true,
+    "outDir": "./dist"
+  },
+  "include": ["apps/**/*", "libs/**/*"],
+  "exclude": ["node_modules", "dist"]
+}
@@ -0,0 +1,15 @@
+{
+  "$schema": "https://turbo.build/schema.json",
+  "tasks": {
+    "build": {
+      "dependsOn": ["^build"],
+      "outputs": ["dist/**"]
+    },
+    "clean": {
+      "dependsOn": ["^clean"]
+    },
+    "test": {
+      "dependsOn": ["^test"]
+    }
+  }
+}
@@ -1 +1 @@
-__version__ = "0.4.0"
+__version__ = "0.4.3"
@@ -303,6 +303,8 @@ def _build(
    pull: bool,
    tag: str,
    passthrough: Sequence[str] = (),
+    install_command: Optional[str] = None,
+    build_command: Optional[str] = None,
 ):
    # pull latest images
    if pull:
@@ -322,22 +324,38 @@ def _build(
        "-t",
        tag,
    ]
+    # determine build context: use current directory for JS projects, config parent for Python
+    is_js_project = config_json.get("node_version") and not config_json.get(
+        "python_version"
+    )
+    # build/install commands only apply to JS projects for now
+    # without install/build command, JS projects will follow the old behavior
+    if is_js_project and (build_command or install_command):
+        build_context = str(pathlib.Path.cwd())
+    else:
+        build_context = str(config.parent)
+
    # apply config
    stdin, additional_contexts = langgraph_cli.config.config_to_docker(
-        config, config_json, base_image, api_version
+        config,
+        config_json,
+        base_image,
+        api_version,
+        install_command,
+        build_command,
+        build_context,
    )
    # add additional_contexts
    if additional_contexts:
        for k, v in additional_contexts.items():
            args.extend(["--build-context", f"{k}={v}"])
-    # run docker build
    runner.run(
        subp_exec(
            "docker",
            "build",
            *args,
            *passthrough,
-            str(config.parent),
+            build_context,
            input=stdin,
            verbose=True,
        )
@@ -366,6 +384,14 @@ def _build(
    "\n    --base-image langchain/langgraph-server:0.2  # Pin to a minor version (Python)",
 )
@OPT_API_VERSION
+@click.option(
+    "--install-command",
+    help="Custom install command to run from the build context root. If not provided, auto-detects based on package manager files.",
+)
+@click.option(
+    "--build-command",
+    help="Custom build command to run from the langgraph.json directory. If not provided, uses default build process.",
+)
@click.argument("docker_build_args", nargs=-1, type=click.UNPROCESSED)
@cli.command(
    help="📦 Build LangGraph API server Docker image.",
@@ -381,6 +407,8 @@ def build(
    api_version: Optional[str],
    pull: bool,
    tag: str,
+    install_command: Optional[str],
+    build_command: Optional[str],
 ):
    with Runner() as runner, Progress(message="Pulling...") as set:
        if shutil.which("docker") is None:
@@ -397,6 +425,8 @@ def build(
            pull,
            tag,
            docker_build_args,
+            install_command,
+            build_command,
        )


--- a/Show More
+++ b/Show More