Update OpenAPI spec from LangGraph API v0.4.39

some of these changes were obvious, and some were less obvious. In a few
spots, it felt like a judgement call if we should be saying LangSmith
Deployment of LangGraph Server. But hopefully either works.

.github/ISSUE_TEMPLATE/config.yml

@@ -1,6 +1,9 @@
 blank_issues_enabled: false
 version: 2.1
 contact_links:
+  - name: Documentation
+    url: https://github.com/langchain-ai/docs/issues/new?template=langgraph.yml
+    about: Report an issue related to the LangGraph documentation
   - name: LangChain Forum
     url:  https://forum.langchain.com/
-    about: General community discussions, support, and feature requests
+    about: General community discussions and support

.github/ISSUE_TEMPLATE/documentation.yml

@@ -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.

.github/workflows/_integration_test.yml

@@ -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
@@ -27,63 +40,71 @@ jobs:
           filter: "libs/cli/**"
       - name: Set up Python ${{ matrix.python-version }}
         if: steps.changed-files.outputs.all
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ matrix.python-version }}
           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
+          # Build the image for this example
-          langgraph build -t langgraph-test-a
+          langgraph build -t ${{ matrix.example.tag }}
-          cp .env.example .env
+          # Prepare environment file from local or parent example directory
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
+          if [ -f .env.example ]; then cp .env.example .env; elif [ -f ../.env.example ]; then cp ../.env.example .env && cp ../.env.example ../.env; fi
-          timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -c langgraph.json -t langgraph-test-a
+          if [ -n "${{ 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
-      - name: Build and test service B
+          # Run the integration test using the built tag
-        if: steps.changed-files.outputs.all
+          # Compute repo root to reference the shared script robustly
-        working-directory: libs/cli/examples/graphs
+          REPO_ROOT=$(git rev-parse --show-toplevel)
-        env:
+          timeout 60 python "$REPO_ROOT/.github/scripts/run_langgraph_cli_test.py" -t ${{ matrix.example.tag }}
-          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
 
       - 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 ]

.github/workflows/_lint.yml

@@ -31,7 +31,7 @@ jobs:
           - "3.12"
     name: "lint #${{ matrix.python-version }}"
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - name: Get changed files
         id: changed-files
         uses: Ana06/get-changed-files@v2.3.0
@@ -39,7 +39,7 @@ jobs:
           filter: "${{ inputs.working-directory }}/**"
       - name: Set up Python ${{ matrix.python-version }}
         if: steps.changed-files.outputs.all
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ matrix.python-version }}
           enable-cache: true

.github/workflows/_test.yml

@@ -25,9 +25,9 @@ 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
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ matrix.python-version }}
           enable-cache: true

.github/workflows/_test_langgraph.yml

@@ -23,9 +23,9 @@ 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
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ matrix.python-version }}
           enable-cache: true

.github/workflows/_test_release.yml

@@ -24,10 +24,10 @@ 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
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           enable-cache: true
@@ -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/

.github/workflows/baseline.yml

@@ -17,10 +17,10 @@ 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
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: "3.11"
           enable-cache: true

.github/workflows/bench.yml

@@ -15,14 +15,14 @@ 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
         with:
           format: json
       - name: Set up Python 3.11
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: "3.11"
           enable-cache: true
@@ -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]

.github/workflows/ci.yml

@@ -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
@@ -118,9 +118,9 @@ 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
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: "3.11"
           enable-cache: true

.github/workflows/codespell.yml

@@ -21,7 +21,7 @@
     
         steps:
           - name: Checkout
-            uses: actions/checkout@v4
+            uses: actions/checkout@v5
     
           - name: Install Dependencies
             run: |

.github/workflows/deploy_docs.yml

@@ -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
@@ -41,12 +41,12 @@ jobs:
     env:
       GITHUB_TOKEN: ${{ secrets.MKDOCS_GITHUB_TOKEN }}
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
         with:
           fetch-depth: 0
 
       - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: "3.12"
           enable-cache: true
@@ -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/
 

.github/workflows/link_check.yml

@@ -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
 

.github/workflows/pr_lint.yml

@@ -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

.github/workflows/release.yml

@@ -26,10 +26,10 @@ 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
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           enable-cache: true
@@ -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.
@@ -174,7 +174,7 @@ jobs:
       #   used in the real world.
 
       - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           enable-cache: true
@@ -261,16 +261,16 @@ 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
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           enable-cache: true
           cache-suffix: "release"
 
-      - uses: actions/download-artifact@v4
+      - uses: actions/download-artifact@v5
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/
@@ -302,16 +302,16 @@ 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
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           enable-cache: true
           cache-suffix: "release"
 
-      - uses: actions/download-artifact@v4
+      - uses: actions/download-artifact@v5
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/

.github/workflows/run_notebooks.yml

@@ -28,9 +28,9 @@ jobs:
           - "latest"
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - name: Set up Python + Poetry
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: "3.11"
           enable-cache: true

.github/workflows/uv_lock_ugprade.yml

@@ -16,10 +16,10 @@ jobs:
     runs-on: ubuntu-latest
     
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       
       - name: Set up uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           # use minimum supported Python version
           python-version: "3.9"
@@ -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`"
+          commit-message: "chore(deps): upgrade dependencies with `uv lock --upgrade`"
-          title: "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`.
             

AGENTS.md

@@ -28,7 +28,7 @@ Below is a high-level overview:
 - **langgraph** – core framework for building stateful, multi-actor agents.
 - **prebuilt** – high-level APIs for creating and running agents and tools.
 - **sdk-js** – JS/TS SDK for interacting with the LangGraph REST API.
-- **sdk-py** – Python SDK for the LangGraph Platform API.
+- **sdk-py** – Python SDK for the LangGraph Server API.
 
 ### Dependency map
 

CONTRIBUTING.md

@@ -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
+        ```python
-
+        my_function(1, "hello")
-            my_function(1, "hello")
+        \```
 
     Args:
         arg1: This is a description of arg1. We do not need to specify the type since

README.md

@@ -63,7 +63,7 @@ LangGraph provides low-level supporting infrastructure for *any* long-running, s
 While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents. To improve your LLM application development, pair LangGraph with:
 
 - [LangSmith](http://www.langchain.com/langsmith) — Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
-- [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
+- [LangSmith Deployment](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
 - [LangChain](https://python.langchain.com/docs/introduction/) – Provides integrations and composable components to streamline LLM application development.
 
 > [!NOTE]
@@ -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.

docs/README.md

@@ -1,24 +1,126 @@
-# Setup
+# LangGraph Documentation
 
-To setup requirements for building docs you can run:
+For more information on contributing to our documentation, see the [Contributing Guide](../CONTRIBUTING.md).
 
-```bash
+## Structure
-uv sync --group test
+
+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
 

docs/_scripts/generate_api_reference_links.py

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

docs/_scripts/js_translation/codeblocks/yarn.lock

@@ -2108,9 +2108,9 @@ __metadata:
   linkType: hard
 
 "hono@npm:^4.5.4":
-  version: 4.8.9
+  version: 4.9.7
-  resolution: "hono@npm:4.8.9"
+  resolution: "hono@npm:4.9.7"
-  checksum: 10c0/385539d1787fdc747bc869ef0e5ccc9f39cbe40289b94f23eecfc82c6ca440f059704647cd6381a5066d2cf7baa43ab25184c78d44af4c5c98a5c5b07670059e
+  checksum: 10c0/089184660a9211ea216ab95bafa45260e371651cb019db49828064b7982b0ae61cc3c4715324bfeb9037aa2460c39ffa2c91d84ad0c8d500fa77cbcc7fc07a8f
   languageName: node
   linkType: hard
 

docs/_scripts/notebook_convert.py

@@ -1,3 +1,5 @@
+"""Convert Jupyter notebooks to markdown with custom processing."""
+
 import ast
 import os
 import re

docs/_scripts/notebook_hooks.py

@@ -88,12 +88,12 @@ REDIRECT_MAP = {
     "cloud/how-tos/human_in_the_loop_user_input.md": "cloud/how-tos/add-human-in-the-loop.md",
     "concepts/platform_architecture.md": "concepts/langgraph_cloud#architecture",
     # cloud streaming redirects
-    "cloud/how-tos/stream_values.md": "https://docs.langchain.com/langgraph-platform/streaming",
+    "cloud/how-tos/stream_values.md": "https://docs.langchain.com/langsmith/streaming",
-    "cloud/how-tos/stream_updates.md": "https://docs.langchain.com/langgraph-platform/streaming",
+    "cloud/how-tos/stream_updates.md": "https://docs.langchain.com/langsmith/streaming",
-    "cloud/how-tos/stream_messages.md": "https://docs.langchain.com/langgraph-platform/streaming",
+    "cloud/how-tos/stream_messages.md": "https://docs.langchain.com/langsmith/streaming",
-    "cloud/how-tos/stream_events.md": "https://docs.langchain.com/langgraph-platform/streaming",
+    "cloud/how-tos/stream_events.md": "https://docs.langchain.com/langsmith/streaming",
-    "cloud/how-tos/stream_debug.md": "https://docs.langchain.com/langgraph-platform/streaming",
+    "cloud/how-tos/stream_debug.md": "https://docs.langchain.com/langsmith/streaming",
-    "cloud/how-tos/stream_multiple.md": "https://docs.langchain.com/langgraph-platform/streaming",
+    "cloud/how-tos/stream_multiple.md": "https://docs.langchain.com/langsmith/streaming",
     "cloud/concepts/streaming.md": "concepts/streaming.md",
     "agents/streaming.md": "how-tos/streaming.md",
     # prebuilt redirects
@@ -129,83 +129,83 @@ REDIRECT_MAP = {
     "how-tos/human_in_the_loop/edit-graph-state.ipynb": "how-tos/human_in_the_loop/time-travel.md",
 
     # LGP mintlify migration redirects
-    "tutorials/auth/getting_started.md": "https://docs.langchain.com/langgraph-platform/auth",
+    "tutorials/auth/getting_started.md": "https://docs.langchain.com/langsmith/auth",
-    "tutorials/auth/resource_auth.md": "https://docs.langchain.com/langgraph-platform/resource-auth",
+    "tutorials/auth/resource_auth.md": "https://docs.langchain.com/langsmith/resource-auth",
-    "tutorials/auth/add_auth_server.md": "https://docs.langchain.com/langgraph-platform/add-auth-server",
+    "tutorials/auth/add_auth_server.md": "https://docs.langchain.com/langsmith/add-auth-server",
-    "how-tos/use-remote-graph.md": "https://docs.langchain.com/langgraph-platform/use-remote-graph",
+    "how-tos/use-remote-graph.md": "https://docs.langchain.com/langsmith/use-remote-graph",
-    "how-tos/autogen-integration.md": "https://docs.langchain.com/langgraph-platform/autogen-integration",
+    "how-tos/autogen-integration.md": "https://docs.langchain.com/langsmith/autogen-integration",
-    "cloud/how-tos/use_stream_react.md": "https://docs.langchain.com/langgraph-platform/use-stream-react",
+    "cloud/how-tos/use_stream_react.md": "https://docs.langchain.com/langsmith/use-stream-react",
-    "cloud/how-tos/generative_ui_react.md": "https://docs.langchain.com/langgraph-platform/generative-ui-react",
+    "cloud/how-tos/generative_ui_react.md": "https://docs.langchain.com/langsmith/generative-ui-react",
-    "concepts/langgraph_platform.md": "https://docs.langchain.com/langgraph-platform/index",
+    "concepts/langgraph_platform.md": "https://docs.langchain.com/langsmith/deployments",
-    "concepts/langgraph_components.md": "https://docs.langchain.com/langgraph-platform/components",
+    "concepts/langgraph_components.md": "https://docs.langchain.com/langsmith/components",
-    "concepts/langgraph_server.md": "https://docs.langchain.com/langgraph-platform/langgraph-server",
+    "concepts/langgraph_server.md": "https://docs.langchain.com/langsmith/langgraph-server",
-    "concepts/langgraph_data_plane.md": "https://docs.langchain.com/langgraph-platform/data-plane",
+    "concepts/langgraph_data_plane.md": "https://docs.langchain.com/langsmith/data-plane",
-    "concepts/langgraph_control_plane.md": "https://docs.langchain.com/langgraph-platform/control-plane",
+    "concepts/langgraph_control_plane.md": "https://docs.langchain.com/langsmith/control-plane",
-    "concepts/langgraph_cli.md": "https://docs.langchain.com/langgraph-platform/langgraph-cli",
+    "concepts/langgraph_cli.md": "https://docs.langchain.com/langsmith/langgraph-cli",
-    "concepts/langgraph_studio.md": "https://docs.langchain.com/langgraph-platform/langgraph-studio",
+    "concepts/langgraph_studio.md": "https://docs.langchain.com/langsmith/studio",
-    "cloud/how-tos/studio/quick_start.md": "https://docs.langchain.com/langgraph-platform/quick-start-studio",
+    "cloud/how-tos/studio/quick_start.md": "https://docs.langchain.com/langsmith/quick-start-studio",
-    "cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langgraph-platform/invoke-studio",
+    "cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langsmith/use-studio#run-application",
-    "cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langgraph-platform/manage-assistants-studio",
+    "cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langsmith/use-studio#manage-assistants",
-    "cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langgraph-platform/threads-studio",
+    "cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langsmith/use-studio#manage-threads",
-    "cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langgraph-platform/iterate-graph-studio",
+    "cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langsmith/observability-studio#iterate-on-prompts",
-    "cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langgraph-platform/run-evals-studio",
+    "cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langsmith/observability-studio#run-experiments-over-a-dataset",
-    "cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langgraph-platform/clone-traces-studio",
+    "cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langsmith/observability-studio#debug-langsmith-traces",
-    "cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langgraph-platform/datasets-studio",
+    "cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langsmith/observability-studio#add-node-to-dataset",
-    "concepts/sdk.md": "https://docs.langchain.com/langgraph-platform/sdk",
+    "concepts/sdk.md": "https://docs.langchain.com/langsmith/sdk",
-    "concepts/plans.md": "https://docs.langchain.com/langgraph-platform/plans",
+    "concepts/plans.md": "https://langchain.com/pricing",
-    "concepts/application_structure.md": "https://docs.langchain.com/langgraph-platform/application-structure",
+    "concepts/application_structure.md": "https://docs.langchain.com/langsmith/application-structure",
-    "concepts/scalability_and_resilience.md": "https://docs.langchain.com/langgraph-platform/scalability-and-resilience",
+    "concepts/scalability_and_resilience.md": "https://docs.langchain.com/langsmith/scalability-and-resilience",
-    "concepts/auth.md": "https://docs.langchain.com/langgraph-platform/auth",
+    "concepts/auth.md": "https://docs.langchain.com/langsmith/authentication-methods",
-    "how-tos/auth/custom_auth.md": "https://docs.langchain.com/langgraph-platform/custom-auth",
+    "how-tos/auth/custom_auth.md": "https://docs.langchain.com/langsmith/custom-auth",
-    "how-tos/auth/openapi_security.md": "https://docs.langchain.com/langgraph-platform/openapi-security",
+    "how-tos/auth/openapi_security.md": "https://docs.langchain.com/langsmith/openapi-security",
-    "concepts/assistants.md": "https://docs.langchain.com/langgraph-platform/assistants",
+    "concepts/assistants.md": "https://docs.langchain.com/langsmith/assistants",
-    "cloud/how-tos/configuration_cloud.md": "https://docs.langchain.com/langgraph-platform/configuration-cloud",
+    "cloud/how-tos/configuration_cloud.md": "https://docs.langchain.com/langsmith/cloud",
-    "cloud/how-tos/use_threads.md": "https://docs.langchain.com/langgraph-platform/use-threads",
+    "cloud/how-tos/use_threads.md": "https://docs.langchain.com/langsmith/use-threads",
-    "cloud/how-tos/background_run.md": "https://docs.langchain.com/langgraph-platform/background-run",
+    "cloud/how-tos/background_run.md": "https://docs.langchain.com/langsmith/background-run",
-    "cloud/how-tos/same-thread.md": "https://docs.langchain.com/langgraph-platform/same-thread",
+    "cloud/how-tos/same-thread.md": "https://docs.langchain.com/langsmith/same-thread",
-    "cloud/how-tos/stateless_runs.md": "https://docs.langchain.com/langgraph-platform/stateless-runs",
+    "cloud/how-tos/stateless_runs.md": "https://docs.langchain.com/langsmith/stateless-runs",
-    "cloud/how-tos/configurable_headers.md": "https://docs.langchain.com/langgraph-platform/configurable-headers",
+    "cloud/how-tos/configurable_headers.md": "https://docs.langchain.com/langsmith/configurable-headers",
-    "concepts/double_texting.md": "https://docs.langchain.com/langgraph-platform/double-texting",
+    "concepts/double_texting.md": "https://docs.langchain.com/langsmith/double-texting",
-    "cloud/how-tos/interrupt_concurrent.md": "https://docs.langchain.com/langgraph-platform/interrupt-concurrent",
+    "cloud/how-tos/interrupt_concurrent.md": "https://docs.langchain.com/langsmith/interrupt-concurrent",
-    "cloud/how-tos/rollback_concurrent.md": "https://docs.langchain.com/langgraph-platform/rollback-concurrent",
+    "cloud/how-tos/rollback_concurrent.md": "https://docs.langchain.com/langsmith/rollback-concurrent",
-    "cloud/how-tos/reject_concurrent.md": "https://docs.langchain.com/langgraph-platform/reject-concurrent",
+    "cloud/how-tos/reject_concurrent.md": "https://docs.langchain.com/langsmith/reject-concurrent",
-    "cloud/how-tos/enqueue_concurrent.md": "https://docs.langchain.com/langgraph-platform/enqueue-concurrent",
+    "cloud/how-tos/enqueue_concurrent.md": "https://docs.langchain.com/langsmith/enqueue-concurrent",
-    "cloud/concepts/webhooks.md": "https://docs.langchain.com/langgraph-platform/use-webhooks",
+    "cloud/concepts/webhooks.md": "https://docs.langchain.com/langsmith/use-webhooks",
-    "cloud/how-tos/webhooks.md": "https://docs.langchain.com/langgraph-platform/use-webhooks",
+    "cloud/how-tos/webhooks.md": "https://docs.langchain.com/langsmith/use-webhooks",
-    "cloud/concepts/cron_jobs.md": "https://docs.langchain.com/langgraph-platform/cron-jobs",
+    "cloud/concepts/cron_jobs.md": "https://docs.langchain.com/langsmith/cron-jobs",
-    "cloud/how-tos/cron_jobs.md": "https://docs.langchain.com/langgraph-platform/cron-jobs",
+    "cloud/how-tos/cron_jobs.md": "https://docs.langchain.com/langsmith/cron-jobs",
-    "how-tos/http/custom_lifespan.md": "https://docs.langchain.com/langgraph-platform/custom-lifespan",
+    "how-tos/http/custom_lifespan.md": "https://docs.langchain.com/langsmith/custom-lifespan",
-    "how-tos/http/custom_middleware.md": "https://docs.langchain.com/langgraph-platform/custom-middleware",
+    "how-tos/http/custom_middleware.md": "https://docs.langchain.com/langsmith/custom-middleware",
-    "how-tos/http/custom_routes.md": "https://docs.langchain.com/langgraph-platform/custom-routes",
+    "how-tos/http/custom_routes.md": "https://docs.langchain.com/langsmith/custom-routes",
-    "cloud/concepts/data_storage_and_privacy.md": "https://docs.langchain.com/langgraph-platform/data-storage-and-privacy",
+    "cloud/concepts/data_storage_and_privacy.md": "https://docs.langchain.com/langsmith/data-storage-and-privacy",
-    "cloud/deployment/semantic_search.md": "https://docs.langchain.com/langgraph-platform/semantic-search",
+    "cloud/deployment/semantic_search.md": "https://docs.langchain.com/langsmith/semantic-search",
-    "how-tos/ttl/configure_ttl.md": "https://docs.langchain.com/langgraph-platform/configure-ttl",
+    "how-tos/ttl/configure_ttl.md": "https://docs.langchain.com/langsmith/configure-ttl",
-    "concepts/deployment_options.md": "https://docs.langchain.com/langgraph-platform/deployment-options",
+    "concepts/deployment_options.md": "https://docs.langchain.com/langsmith/hosting",
-    "cloud/quick_start.md": "https://docs.langchain.com/langgraph-platform/deployment-quickstart",
+    "cloud/quick_start.md": "https://docs.langchain.com/langsmith/deployment-quickstart",
-    "cloud/deployment/setup.md": "https://docs.langchain.com/langgraph-platform/setup-app-requirements-txt",
+    "cloud/deployment/setup.md": "https://docs.langchain.com/langsmith/setup-app-requirements-txt",
-    "cloud/deployment/setup_pyproject.md": "https://docs.langchain.com/langgraph-platform/setup-pyproject",
+    "cloud/deployment/setup_pyproject.md": "https://docs.langchain.com/langsmith/setup-pyproject",
-    "cloud/deployment/setup_javascript.md": "https://docs.langchain.com/langgraph-platform/setup-javascript",
+    "cloud/deployment/setup_javascript.md": "https://docs.langchain.com/langsmith/setup-javascript",
-    "cloud/deployment/custom_docker.md": "https://docs.langchain.com/langgraph-platform/custom-docker",
+    "cloud/deployment/custom_docker.md": "https://docs.langchain.com/langsmith/custom-docker",
-    "cloud/deployment/graph_rebuild.md": "https://docs.langchain.com/langgraph-platform/graph-rebuild",
+    "cloud/deployment/graph_rebuild.md": "https://docs.langchain.com/langsmith/graph-rebuild",
-    "concepts/langgraph_cloud.md": "https://docs.langchain.com/langgraph-platform/cloud",
+    "concepts/langgraph_cloud.md": "https://docs.langchain.com/langsmith/cloud",
-    "concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/hybrid",
+    "concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/hybrid",
-    "concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/self-hosted",
+    "concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/self-hosted",
-    "concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langgraph-platform/self-hosted#standalone-server",
+    "concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langsmith/self-hosted#standalone-server",
-    "cloud/deployment/cloud.md": "https://docs.langchain.com/langgraph-platform/cloud",
+    "cloud/deployment/cloud.md": "https://docs.langchain.com/langsmith/cloud",
-    "cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-hybrid",
+    "cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/deploy-hybrid",
-    "cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-self-hosted-full-platform",
+    "cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/deploy-self-hosted-full-platform",
-    "cloud/deployment/standalone_container.md": "https://docs.langchain.com/langgraph-platform/deploy-standalone-server",
+    "cloud/deployment/standalone_container.md": "https://docs.langchain.com/langsmith/deploy-standalone-server",
-    "concepts/server-mcp.md": "https://docs.langchain.com/langgraph-platform/server-mcp",
+    "concepts/server-mcp.md": "https://docs.langchain.com/langsmith/server-mcp",
-    "cloud/how-tos/human_in_the_loop_time_travel.md": "https://docs.langchain.com/langgraph-platform/human-in-the-loop-time-travel",
+    "cloud/how-tos/human_in_the_loop_time_travel.md": "https://docs.langchain.com/langsmith/human-in-the-loop-time-travel",
-    "cloud/how-tos/add-human-in-the-loop.md": "https://docs.langchain.com/langgraph-platform/add-human-in-the-loop",
+    "cloud/how-tos/add-human-in-the-loop.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
-    "cloud/deployment/egress.md": "https://docs.langchain.com/langgraph-platform/env-var",
+    "cloud/deployment/egress.md": "https://docs.langchain.com/langsmith/env-var",
-    "cloud/how-tos/streaming.md": "https://docs.langchain.com/langgraph-platform/streaming",
+    "cloud/how-tos/streaming.md": "https://docs.langchain.com/langsmith/streaming",
-    "cloud/reference/api/api_ref.md": "https://docs.langchain.com/langgraph-platform/server-api-ref",
+    "cloud/reference/api/api_ref.md": "https://docs.langchain.com/langsmith/server-api-ref",
-    "cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langgraph-platform/langgraph-server-changelog",
+    "cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langsmith/langgraph-server-changelog",
-    "cloud/reference/api/api_ref_control_plane.md": "https://docs.langchain.com/langgraph-platform/api-ref-control-plane",
+    "cloud/reference/api/api_ref_control_plane.md": "https://docs.langchain.com/langsmith/api-ref-control-plane",
-    "cloud/reference/cli.md": "https://docs.langchain.com/langgraph-platform/cli",
+    "cloud/reference/cli.md": "https://docs.langchain.com/langsmith/cli",
-    "cloud/reference/env_var.md": "https://docs.langchain.com/langgraph-platform/env-var",
+    "cloud/reference/env_var.md": "https://docs.langchain.com/langsmith/env-var",
-    "troubleshooting/studio.md": "https://docs.langchain.com/langgraph-platform/troubleshooting-studio",
+    "troubleshooting/studio.md": "https://docs.langchain.com/langsmith/troubleshooting-studio",
 }
 
 

docs/docs/agents/context.md

@@ -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
         ...
     ```

docs/docs/agents/models.md

@@ -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/)
+
   :::

docs/docs/cloud/reference/api/openapi.json

@@ -1,7 +1,7 @@
 {
   "openapi": "3.1.0",
   "info": {
-    "title": "LangGraph Platform",
+    "title": "LangSmith Deployment",
     "version": "0.1.0"
   },
   "tags": [
@@ -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."
@@ -3182,6 +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",
@@ -4822,6 +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",
@@ -5062,11 +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": {

docs/docs/cloud/reference/cli.md

@@ -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"

docs/docs/concepts/low_level.md

@@ -1040,7 +1040,7 @@ def node_a(state: State, runtime: Runtime[ContextSchema]):
     ...
 ```
 
-See [this guide](../how-tos/graph-api.ipynb#add-runtime-configuration) for a full breakdown on configuration.
+See [this guide](../how-tos/graph-api.md#add-runtime-configuration) for a full breakdown on configuration.
 :::
 
 :::js

docs/docs/concepts/memory.md

@@ -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.

docs/docs/concepts/multi_agent.md

@@ -897,5 +897,5 @@ There are two high-level approaches to achieve that:
 
 An agent might need to have a different state schema from the rest of the agents. For example, a search agent might only need to keep track of queries and retrieved documents. There are two ways to achieve this in LangGraph:
 
-- Define [subgraph](./subgraphs.md) agents with a separate state schema. If there are no shared state keys (channels) between the subgraph and the parent graph, it's important to [add input / output transformations](../how-tos/subgraph.ipynb#different-state-schemas) so that the parent graph knows how to communicate with the subgraphs.
+- Define [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.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 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.

docs/docs/how-tos/graph-api.md

@@ -1019,7 +1019,7 @@ console.log(await graph.invoke({}, { configurable: { myRuntimeValue: "b" } }));
     # Usage
     input_message = {"role": "user", "content": "hi"}
     # With no configuration, uses default (Anthropic)
-    response_1 = graph.invoke({"messages": [input_message]})["messages"][-1]
+    response_1 = graph.invoke({"messages": [input_message]}, context=ContextSchema())["messages"][-1]
     # Or, can set OpenAI
     response_2 = graph.invoke({"messages": [input_message]}, context={"model_provider": "openai"})["messages"][-1]
 
@@ -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.
+    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:
+    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 state updates are [checkpointed](../concepts/persistence.md)
-    - How interruptions are resumed in [human-in-the-loop](../concepts/human_in_the_loop.md) workflows
+- 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 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
+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).
+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);
 ```
-:::
+:::

docs/docs/how-tos/human_in_the_loop/add-human-in-the-loop.md

@@ -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}"
+    i.id: f"edited text for {i.value['text_to_revise']}"
-    for i in parent.get_state(thread_config).interrupts
+    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'}

docs/docs/how-tos/tool-calling.md

@@ -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"
 
 :::
 

docs/docs/tutorials/auth/getting_started.md

@@ -68,7 +68,7 @@ The server will start and open the studio in your browser:
 > - 📚 API Docs: http://127.0.0.1:2024/docs
 >
 > This in-memory server is designed for development and testing.
-> For production use, please use LangGraph Platform.
+> For production use, please use LangSmith Deployment.
 ```
 
 If you were to self-host this on the public internet, anyone could access it!

docs/docs/tutorials/workflows.md

@@ -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"]

docs/overrides/main.html

@@ -291,7 +291,7 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
     }
 
     .md-banner {
-      background-color: #CFC9FA;
+      background-color: #FFAE42;
       color: #000000;
     }
 
@@ -360,5 +360,5 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
 {% endblock %}
 
 {% block announce %}
-Our new LangChain Academy Course Deep Research with LangGraph is now live! <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 %}

docs/pyproject.toml

@@ -7,14 +7,14 @@ name = "langgraph-docs"
 version = "0.0.1"
 description = "LangGraph docs"
 authors = []
-requires-python = "~=3.11"
+requires-python = ">=3.11.0,<4.0.0"
 readme = "README.md"
 license = "MIT"
 dependencies = [
     "aiohappyeyeballs==2.4.3",
-    "hub>=3.0.1,<4",
+    "hub>=3.0.1,<4.0.0",
-    "xxhash>=3.5.0,<4",
+    "xxhash>=3.5.0,<4.0.0",
-    "black>=25.1.0,<26",
+    "black>=25.1.0,<26.0.0",
 ]
 
 [dependency-groups]

docs/uv.lock

@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.11, <4"
 resolution-markers = [
     "python_full_version >= '3.13' and platform_python_implementation != 'PyPy'",
@@ -2337,7 +2337,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "0.6.2"
+version = "0.6.7"
 source = { editable = "../libs/langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -2380,6 +2380,7 @@ dev = [
     { name = "pytest-repeat" },
     { name = "pytest-watcher" },
     { name = "pytest-xdist", extras = ["psutil"] },
+    { name = "redis" },
     { name = "ruff" },
     { name = "syrupy" },
     { name = "types-requests" },
@@ -2413,6 +2414,7 @@ dev = [
     { name = "pytest-asyncio" },
     { name = "pytest-mock" },
     { name = "pytest-watcher" },
+    { name = "redis" },
     { name = "ruff" },
 ]
 
@@ -2643,7 +2645,7 @@ test = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "0.6.2"
+version = "0.6.4"
 source = { editable = "../libs/prebuilt" }
 dependencies = [
     { name = "langchain-core" },
@@ -2674,7 +2676,6 @@ dev = [
 
 [[package]]
 name = "langgraph-sdk"
-version = "0.2.0"
 source = { editable = "../libs/sdk-py" }
 dependencies = [
     { name = "httpx" },

examples/persistence_postgres.ipynb

@@ -5,7 +5,7 @@
    "id": "18526f23",
    "metadata": {},
    "source": [
-    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/persistence_postgres.ipynb"
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/memory/add-memory.md"
    ]
   }
  ],

examples/rag/langgraph_crag_local.ipynb

@@ -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",

libs/checkpoint-postgres/langgraph/checkpoint/postgres/__init__.py

@@ -7,11 +7,6 @@ from contextlib import contextmanager
 from typing import Any
 
 from langchain_core.runnables import RunnableConfig
-from psycopg import Capabilities, Connection, Cursor, Pipeline
-from psycopg.rows import DictRow, dict_row
-from psycopg.types.json import Jsonb
-from psycopg_pool import ConnectionPool
-
 from langgraph.checkpoint.base import (
     WRITES_IDX_MAP,
     ChannelVersions,
@@ -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"]),
                 },
             },

libs/checkpoint-postgres/langgraph/checkpoint/postgres/aio.py

@@ -7,11 +7,6 @@ from contextlib import asynccontextmanager
 from typing import Any
 
 from langchain_core.runnables import RunnableConfig
-from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
-from psycopg.rows import DictRow, dict_row
-from psycopg.types.json import Jsonb
-from psycopg_pool import AsyncConnectionPool
-
 from langgraph.checkpoint.base import (
     WRITES_IDX_MAP,
     ChannelVersions,
@@ -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"]),
                 },
             },

libs/checkpoint-postgres/langgraph/checkpoint/postgres/base.py

@@ -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.

libs/checkpoint-postgres/langgraph/checkpoint/postgres/shallow.py

@@ -6,6 +6,16 @@ from contextlib import asynccontextmanager, contextmanager
 from typing import Any, Optional
 
 from langchain_core.runnables import RunnableConfig
+from langgraph.checkpoint.base import (
+    WRITES_IDX_MAP,
+    ChannelVersions,
+    Checkpoint,
+    CheckpointMetadata,
+    CheckpointTuple,
+    get_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

libs/checkpoint-postgres/langgraph/store/postgres/__init__.py

@@ -1,4 +1,4 @@
 from langgraph.store.postgres.aio import AsyncPostgresStore
-from langgraph.store.postgres.base import PostgresStore
+from langgraph.store.postgres.base import PoolConfig, PostgresStore
 
-__all__ = ["AsyncPostgresStore", "PostgresStore"]
+__all__ = ["AsyncPostgresStore", "PoolConfig", "PostgresStore"]

libs/checkpoint-postgres/langgraph/store/postgres/aio.py

@@ -8,11 +8,6 @@ from types import TracebackType
 from typing import Any, Callable, cast
 
 import orjson
-from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
-from psycopg.rows import DictRow, dict_row
-from psycopg_pool import AsyncConnectionPool
-
-from langgraph.checkpoint.postgres import _ainternal
 from langgraph.store.base import (
     GetOp,
     ListNamespacesOp,
@@ -22,6 +17,11 @@ from langgraph.store.base import (
     SearchOp,
 )
 from langgraph.store.base.batch import AsyncBatchedBaseStore
+from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
+from psycopg.rows import DictRow, dict_row
+from psycopg_pool import AsyncConnectionPool
+
+from langgraph.checkpoint.postgres import _ainternal
 from langgraph.store.postgres.base import (
     PLACEHOLDER,
     BasePostgresStore,

libs/checkpoint-postgres/langgraph/store/postgres/base.py

@@ -22,14 +22,6 @@ from typing import (
 )
 
 import orjson
-from psycopg import Capabilities, Connection, Cursor, Pipeline
-from psycopg.rows import DictRow, dict_row
-from psycopg.types.json import Jsonb
-from psycopg_pool import ConnectionPool
-from typing_extensions import TypedDict
-
-from langgraph.checkpoint.postgres import _ainternal as _ainternal
-from langgraph.checkpoint.postgres import _internal as _pg_internal
 from langgraph.store.base import (
     BaseStore,
     GetOp,
@@ -46,6 +38,14 @@ from langgraph.store.base import (
     get_text_at_path,
     tokenize_path,
 )
+from psycopg import Capabilities, Connection, Cursor, Pipeline
+from psycopg.rows import DictRow, dict_row
+from psycopg.types.json import Jsonb
+from psycopg_pool import ConnectionPool
+from typing_extensions import TypedDict
+
+from langgraph.checkpoint.postgres import _ainternal as _ainternal
+from langgraph.checkpoint.postgres import _internal as _pg_internal
 
 if TYPE_CHECKING:
     from langchain_core.embeddings import Embeddings

libs/checkpoint-postgres/pyproject.toml

@@ -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",

libs/checkpoint-postgres/tests/test_async.py

@@ -6,10 +6,6 @@ from uuid import uuid4
 
 import pytest
 from langchain_core.runnables import RunnableConfig
-from psycopg import AsyncConnection
-from psycopg.rows import dict_row
-from psycopg_pool import AsyncConnectionPool
-
 from langgraph.checkpoint.base import (
     EXCLUDED_METADATA_KEYS,
     Checkpoint,
@@ -17,11 +13,15 @@ from langgraph.checkpoint.base import (
     create_checkpoint,
     empty_checkpoint,
 )
+from langgraph.checkpoint.serde.types import TASKS
+from psycopg import AsyncConnection
+from psycopg.rows import dict_row
+from psycopg_pool import AsyncConnectionPool
+
 from langgraph.checkpoint.postgres.aio import (
     AsyncPostgresSaver,
     AsyncShallowPostgresSaver,
 )
-from langgraph.checkpoint.serde.types import TASKS
 from tests.conftest import DEFAULT_POSTGRES_URI
 
 
@@ -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"] == {}

libs/checkpoint-postgres/tests/test_async_store.py

@@ -12,8 +12,6 @@ from typing import Any
 
 import pytest
 from langchain_core.embeddings import Embeddings
-from psycopg import AsyncConnection
-
 from langgraph.store.base import (
     GetOp,
     Item,
@@ -21,6 +19,8 @@ from langgraph.store.base import (
     PutOp,
     SearchOp,
 )
+from psycopg import AsyncConnection
+
 from langgraph.store.postgres import AsyncPostgresStore
 from tests.conftest import (
     DEFAULT_URI,

libs/checkpoint-postgres/tests/test_store.py

@@ -9,8 +9,6 @@ from uuid import uuid4
 
 import pytest
 from langchain_core.embeddings import Embeddings
-from psycopg import Connection
-
 from langgraph.store.base import (
     GetOp,
     Item,
@@ -19,6 +17,8 @@ from langgraph.store.base import (
     PutOp,
     SearchOp,
 )
+from psycopg import Connection
+
 from langgraph.store.postgres import PostgresStore
 from tests.conftest import (
     DEFAULT_URI,
@@ -861,3 +861,41 @@ def test_store_ttl(store):
     # Now has been (TTL_SECONDS-2)*2 > TTL_SECONDS + TTL_SECONDS/2
     res = store.search(ns, query="bar", refresh_ttl=False)
     assert len(res) == 0
+
+
+@pytest.mark.parametrize(
+    "vector_type,distance_type",
+    [
+        ("vector", "cosine"),
+        ("vector", "inner_product"),
+        ("halfvec", "cosine"),
+        ("halfvec", "inner_product"),
+    ],
+)
+def test_non_ascii(
+    request: Any,
+    fake_embeddings: CharacterEmbeddings,
+    vector_type: str,
+    distance_type: str,
+) -> None:
+    """Test support for non-ascii characters"""
+    with _create_vector_store(vector_type, distance_type, fake_embeddings) as store:
+        store.put(("user_123", "memories"), "1", {"text": "这是中文"})  # Chinese
+        store.put(
+            ("user_123", "memories"), "2", {"text": "これは日本語です"}
+        )  # Japanese
+        store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"})  # Korean
+        store.put(("user_123", "memories"), "4", {"text": "Это русский"})  # Russian
+        store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"})  # Hindi
+
+        result1 = store.search(("user_123", "memories"), query="这是中文")
+        result2 = store.search(("user_123", "memories"), query="これは日本語です")
+        result3 = store.search(("user_123", "memories"), query="이건 한국어야")
+        result4 = store.search(("user_123", "memories"), query="Это русский")
+        result5 = store.search(("user_123", "memories"), query="यह रूसी है")
+
+        assert result1[0].key == "1"
+        assert result2[0].key == "2"
+        assert result3[0].key == "3"
+        assert result4[0].key == "4"
+        assert result5[0].key == "5"

libs/checkpoint-postgres/tests/test_sync.py

@@ -7,10 +7,6 @@ from uuid import uuid4
 
 import pytest
 from langchain_core.runnables import RunnableConfig
-from psycopg import Connection
-from psycopg.rows import dict_row
-from psycopg_pool import ConnectionPool
-
 from langgraph.checkpoint.base import (
     EXCLUDED_METADATA_KEYS,
     Checkpoint,
@@ -18,8 +14,12 @@ from langgraph.checkpoint.base import (
     create_checkpoint,
     empty_checkpoint,
 )
-from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver
 from langgraph.checkpoint.serde.types import TASKS
+from psycopg import Connection
+from psycopg.rows import dict_row
+from psycopg_pool import ConnectionPool
+
+from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver
 from tests.conftest import DEFAULT_POSTGRES_URI
 
 
@@ -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"] == {}

libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/__init__.py

@@ -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 = (

libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/aio.py

@@ -8,7 +8,6 @@ from typing import Any, Callable, TypeVar, cast
 
 import aiosqlite
 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import (
     WRITES_IDX_MAP,
     BaseCheckpointSaver,
@@ -21,6 +20,7 @@ from langgraph.checkpoint.base import (
     get_checkpoint_metadata,
 )
 from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
+
 from langgraph.checkpoint.sqlite.utils import search_where
 
 T = TypeVar("T", bound=Callable)

libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/utils.py

@@ -5,7 +5,6 @@ from collections.abc import Sequence
 from typing import Any
 
 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import get_checkpoint_id
 
 

libs/checkpoint-sqlite/langgraph/store/sqlite/aio.py

@@ -11,7 +11,6 @@ from typing import Any, Callable, cast
 import aiosqlite
 import orjson
 import sqlite_vec  # type: ignore[import-untyped]
-
 from langgraph.store.base import (
     GetOp,
     ListNamespacesOp,
@@ -22,6 +21,7 @@ from langgraph.store.base import (
     TTLConfig,
 )
 from langgraph.store.base.batch import AsyncBatchedBaseStore
+
 from langgraph.store.sqlite.base import (
     _PLACEHOLDER,
     BaseSqliteStore,
@@ -507,7 +507,9 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
             results: List to store results in.
             cur: Database cursor.
         """
-        queries, embedding_requests = self._prepare_batch_search_queries(search_ops)
+        prepared_queries, embedding_requests = self._prepare_batch_search_queries(
+            search_ops
+        )
 
         # Setup dot_product function if it doesn't exist
         if embedding_requests and self.embeddings:
@@ -515,23 +517,60 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
                 [query for _, query in embedding_requests]
             )
 
-            for (idx, _), embedding in zip(embedding_requests, vectors):
+            for (embed_req_idx, _), embedding in zip(embedding_requests, vectors):
-                _params_list: list = queries[idx][1]
+                # Find the corresponding query in prepared_queries
-                for i, param in enumerate(_params_list):
+                # The embed_req_idx is the original index in search_ops, which should map to prepared_queries
-                    if param is _PLACEHOLDER:
+                if embed_req_idx < len(prepared_queries):
-                        _params_list[i] = sqlite_vec.serialize_float32(embedding)
+                    _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],
+                            "key": row[1],  # key
-                            "value": row[2],
+                            "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],
+                            "key": row[1],  # key
-                            "value": row[2],
+                            "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,

libs/checkpoint-sqlite/langgraph/store/sqlite/base.py

@@ -13,7 +13,6 @@ from typing import Any, Callable, Literal, NamedTuple, cast
 
 import orjson
 import sqlite_vec  # type: ignore[import-untyped]
-
 from langgraph.store.base import (
     BaseStore,
     GetOp,
@@ -372,13 +371,15 @@ class BaseSqliteStore:
     def _prepare_batch_search_queries(
         self, search_ops: Sequence[tuple[int, SearchOp]]
     ) -> tuple[
-        list[tuple[str, list[None | str | list[float]]]],  # queries, params
+        list[
+            tuple[str, list[None | str | list[float]], bool]
+        ],  # queries, params, needs_refresh
         list[tuple[int, str]],  # idx, query_text pairs to embed
     ]:
         """
-        Build per-SearchOp SQL queries (with optional TTL refresh) plus embedding requests.
+        Build per-SearchOp SQL queries (with optional TTL refresh flag) plus embedding requests.
         Returns:
-        - queries: list of (SQL, param_list)
+        - queries: list of (SQL, param_list, needs_ttl_refresh_flag)
         - embedding_requests: list of (original_index_in_search_ops, text_query)
         """
         queries = []
@@ -519,30 +520,18 @@ class BaseSqliteStore:
                 logger.debug(f"Search query: {base_query}")
                 logger.debug(f"Search params: {params}")
 
-            # Handle TTL refresh if requested
+            # Determine if TTL refresh is needed
-            if (
+            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):
+            for (embed_req_idx, _), embedding in zip(embedding_requests, embeddings):
-                _params_list: list = queries[idx][1]
+                if embed_req_idx < len(prepared_queries):
-                for i, param in enumerate(_params_list):
+                    _params_list: list = prepared_queries[embed_req_idx][1]
-                    if param is _PLACEHOLDER:
+                    for i, param in enumerate(_params_list):
-                        _params_list[i] = sqlite_vec.serialize_float32(embedding)
+                        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,

libs/checkpoint-sqlite/tests/test_aiosqlite.py

@@ -2,13 +2,13 @@ from typing import Any
 
 import pytest
 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import (
     Checkpoint,
     CheckpointMetadata,
     create_checkpoint,
     empty_checkpoint,
 )
+
 from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
 
 

libs/checkpoint-sqlite/tests/test_async_store.py

@@ -8,7 +8,6 @@ from contextlib import asynccontextmanager
 from typing import Optional, Union, cast
 
 import pytest
-
 from langgraph.store.base import (
     GetOp,
     Item,
@@ -16,6 +15,7 @@ from langgraph.store.base import (
     PutOp,
     SearchOp,
 )
+
 from langgraph.store.sqlite import AsyncSqliteStore
 from langgraph.store.sqlite.base import SqliteIndexConfig
 from tests.test_store import CharacterEmbeddings

libs/checkpoint-sqlite/tests/test_sqlite.py

@@ -2,13 +2,13 @@ from typing import Any, cast
 
 import pytest
 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import (
     Checkpoint,
     CheckpointMetadata,
     create_checkpoint,
     empty_checkpoint,
 )
+
 from langgraph.checkpoint.sqlite import SqliteSaver
 from langgraph.checkpoint.sqlite.utils import _metadata_predicate, search_where
 
@@ -116,7 +116,17 @@ class TestSqliteSaver:
                 search_results_5[1].config["configurable"]["checkpoint_ns"],
             } == {"", "inner"}
 
-            # TODO: test before and limit params
+            # search with before param
+            search_results_6 = list(saver.list(None, before=search_results_5[1].config))
+            assert len(search_results_6) == 1
+            assert search_results_6[0].config["configurable"]["thread_id"] == "thread-1"
+
+            # search with limit param
+            search_results_7 = list(
+                saver.list({"configurable": {"thread_id": "thread-2"}}, limit=1)
+            )
+            assert len(search_results_7) == 1
+            assert search_results_7[0].config["configurable"]["thread_id"] == "thread-2"
 
     def test_search_where(self) -> None:
         # call method / assertions

libs/checkpoint-sqlite/tests/test_store.py

@@ -9,7 +9,6 @@ from typing import Any, Literal, Optional, Union, cast
 
 import pytest
 from langchain_core.embeddings import Embeddings
-
 from langgraph.store.base import (
     GetOp,
     Item,
@@ -18,6 +17,7 @@ from langgraph.store.base import (
     PutOp,
     SearchOp,
 )
+
 from langgraph.store.sqlite import SqliteStore
 from langgraph.store.sqlite.base import SqliteIndexConfig
 
@@ -1067,3 +1067,31 @@ def test_sql_injection_vulnerability(store: SqliteStore) -> None:
 
     with pytest.raises(ValueError, match="Invalid filter key"):
         store.search(("docs",), filter={malicious_key: "dummy"})
+
+
+@pytest.mark.parametrize("distance_type", VECTOR_TYPES)
+def test_non_ascii(
+    fake_embeddings: CharacterEmbeddings,
+    distance_type: str,
+) -> None:
+    """Test support for non-ascii characters"""
+    with create_vector_store(fake_embeddings, distance_type=distance_type) as store:
+        store.put(("user_123", "memories"), "1", {"text": "这是中文"})  # Chinese
+        store.put(
+            ("user_123", "memories"), "2", {"text": "これは日本語です"}
+        )  # Japanese
+        store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"})  # Korean
+        store.put(("user_123", "memories"), "4", {"text": "Это русский"})  # Russian
+        store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"})  # Hindi
+
+        result1 = store.search(("user_123", "memories"), query="这是中文")
+        result2 = store.search(("user_123", "memories"), query="これは日本語です")
+        result3 = store.search(("user_123", "memories"), query="이건 한국어야")
+        result4 = store.search(("user_123", "memories"), query="Это русский")
+        result5 = store.search(("user_123", "memories"), query="यह रूसी है")
+
+        assert result1[0].key == "1"
+        assert result2[0].key == "2"
+        assert result3[0].key == "3"
+        assert result4[0].key == "4"
+        assert result5[0].key == "5"

libs/checkpoint-sqlite/tests/test_ttl.py

@@ -7,6 +7,7 @@ import time
 from collections.abc import Generator
 
 import pytest
+from langgraph.store.base import TTLConfig
 
 from langgraph.store.sqlite import SqliteStore
 from langgraph.store.sqlite.aio import AsyncSqliteStore
@@ -93,9 +94,13 @@ def test_ttl_sweeper(temp_db_file: str) -> None:
     ttl_seconds = 2
     ttl_minutes = ttl_seconds / 60
 
+    ttl_config: TTLConfig = {
+        "default_ttl": ttl_minutes,
+        "sweep_interval_minutes": ttl_minutes / 2,
+    }
     with SqliteStore.from_conn_string(
         temp_db_file,
-        ttl={"default_ttl": ttl_minutes, "sweep_interval_minutes": ttl_minutes / 2},
+        ttl=ttl_config,
     ) as store:
         store.setup()
 
@@ -298,9 +303,14 @@ async def test_async_ttl_sweeper(temp_db_file: str) -> None:
     ttl_seconds = 2
     ttl_minutes = ttl_seconds / 60
 
+    ttl_config: TTLConfig = {
+        "default_ttl": ttl_minutes,
+        "sweep_interval_minutes": ttl_minutes / 2,
+    }
+
     async with AsyncSqliteStore.from_conn_string(
         temp_db_file,
-        ttl={"default_ttl": ttl_minutes, "sweep_interval_minutes": ttl_minutes / 2},
+        ttl=ttl_config,
     ) as store:
         await store.setup()
 
@@ -353,3 +363,67 @@ async def test_async_search_with_ttl(temp_db_file: str) -> None:
         # Search after expiration
         results = await store.asearch(("test",), filter={"value": "apple"})
         assert len(results) == 0
+
+
+@pytest.mark.asyncio
+@pytest.mark.flaky(retries=3)
+async def test_async_asearch_refresh_ttl(temp_db_file: str) -> None:
+    """Test TTL refresh on asearch with async API."""
+    ttl_seconds = 4.0  # Increased TTL for less sensitivity to timing
+    ttl_minutes = ttl_seconds / 60.0
+
+    async with AsyncSqliteStore.from_conn_string(
+        temp_db_file, ttl={"default_ttl": ttl_minutes, "refresh_on_read": True}
+    ) as store:
+        await store.setup()
+
+        namespace = ("docs", "user1")
+        # t=0: items put, expire at t=4.0s
+        await store.aput(namespace, "item1", {"text": "content1", "id": 1})
+        await store.aput(namespace, "item2", {"text": "content2", "id": 2})
+
+        # t=3.0s: (after sleep ttl_seconds * 0.75 = 3s)
+        await asyncio.sleep(ttl_seconds * 0.75)
+
+        # Perform asearch with refresh_ttl=True for item1.
+        # item1's TTL should be refreshed. New expiry: t=3.0s + 4.0s = t=7.0s.
+        # item2's TTL is not affected. Expires at t=4.0s.
+        searched_items = await store.asearch(
+            namespace, filter={"id": 1}, refresh_ttl=True
+        )
+        assert len(searched_items) == 1
+        assert searched_items[0].key == "item1"
+
+        # t=5.0s: (after sleep ttl_seconds * 0.5 = 2s more. Total elapsed: 3s + 2s = 5s)
+        await asyncio.sleep(ttl_seconds * 0.5)
+        # At this point:
+        # - item1 (refreshed by asearch) should expire at t=7.0s. Should be ALIVE.
+        # - item2 (original TTL) should have expired at t=4.0s. Should be GONE after sweep.
+
+        await store.sweep_ttl()
+
+        # Check item1 (should exist due to asearch refresh)
+        item1_check1 = await store.aget(namespace, "item1", refresh_ttl=False)
+        assert item1_check1 is not None, (
+            "Item1 should exist after asearch refresh and first sweep"
+        )
+        assert item1_check1.value["text"] == "content1"
+
+        # Check item2 (should be gone)
+        item2_check1 = await store.aget(namespace, "item2", refresh_ttl=False)
+        assert item2_check1 is None, (
+            "Item2 should be gone after its original TTL expired"
+        )
+
+        # t=7.5s: (after sleep ttl_seconds * 0.625 = 2.5s more. 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"
+        )

libs/checkpoint/langgraph/checkpoint/base/__init__.py

@@ -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.

libs/checkpoint/langgraph/checkpoint/memory/__init__.py

@@ -39,7 +39,7 @@ class InMemorySaver(
         Only use `InMemorySaver` for debugging or testing purposes.
         For production use cases we recommend installing [langgraph-checkpoint-postgres](https://pypi.org/project/langgraph-checkpoint-postgres/) and using `PostgresSaver` / `AsyncPostgresSaver`.
 
-        If you are using the LangGraph Platform, no checkpointer needs to be specified. The correct managed checkpointer will be used automatically.
+        If you are using LangSmith Deployment, no checkpointer needs to be specified. The correct managed checkpointer will be used automatically.
 
     Args:
         serde: The serializer to use for serializing and deserializing checkpoints. Defaults to None.

libs/checkpoint/langgraph/store/base/embed.py

@@ -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 == "*":

libs/checkpoint/pyproject.toml

@@ -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"

libs/checkpoint/tests/test_redis_cache.py

@@ -5,12 +5,13 @@ import time
 import pytest
 import redis
 
+from langgraph.cache.base import FullKey
 from langgraph.cache.redis import RedisCache
 
 
 class TestRedisCache:
     @pytest.fixture(autouse=True)
-    def setup(self):
+    def setup(self) -> None:
         """Set up test Redis client and cache."""
         self.client = redis.Redis(
             host="localhost", port=6379, db=0, decode_responses=False
@@ -20,21 +21,21 @@ class TestRedisCache:
         except redis.ConnectionError:
             pytest.skip("Redis server not available")
 
-        self.cache = RedisCache(self.client, prefix="test:cache:")
+        self.cache: RedisCache = RedisCache(self.client, prefix="test:cache:")
 
         # Clean up before each test
         self.client.flushdb()
 
-    def teardown_method(self):
+    def teardown_method(self) -> None:
         """Clean up after each test."""
         try:
             self.client.flushdb()
         except Exception:
             pass
 
-    def test_basic_set_and_get(self):
+    def test_basic_set_and_get(self) -> None:
         """Test basic set and get operations."""
-        keys = [(("graph", "node"), "key1")]
+        keys: list[FullKey] = [(("graph", "node"), "key1")]
         values = {keys[0]: ({"result": 42}, None)}
 
         # Set value
@@ -45,9 +46,9 @@ class TestRedisCache:
         assert len(result) == 1
         assert result[keys[0]] == {"result": 42}
 
-    def test_batch_operations(self):
+    def test_batch_operations(self) -> None:
         """Test batch set and get operations."""
-        keys = [
+        keys: list[FullKey] = [
             (("graph", "node1"), "key1"),
             (("graph", "node2"), "key2"),
             (("other", "node"), "key3"),
@@ -68,9 +69,9 @@ class TestRedisCache:
         assert result[keys[1]] == {"result": 2}
         assert result[keys[2]] == {"result": 3}
 
-    def test_ttl_behavior(self):
+    def test_ttl_behavior(self) -> None:
         """Test TTL (time-to-live) functionality."""
-        key = (("graph", "node"), "ttl_key")
+        key: FullKey = (("graph", "node"), "ttl_key")
         values = {key: ({"data": "expires_soon"}, 1)}  # 1 second TTL
 
         # Set with TTL
@@ -88,10 +89,10 @@ class TestRedisCache:
         result = self.cache.get([key])
         assert len(result) == 0
 
-    def test_namespace_isolation(self):
+    def test_namespace_isolation(self) -> None:
         """Test that different namespaces are isolated."""
-        key1 = (("graph1", "node"), "same_key")
+        key1: FullKey = (("graph1", "node"), "same_key")
-        key2 = (("graph2", "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)

libs/checkpoint/tests/test_store.py

@@ -950,8 +950,8 @@ async def test_embed_with_path(fake_embeddings: CharacterEmbeddings) -> None:
     assert results[0].key != results[1].key
     ascore = results[0].score
     bscore = results[1].score
-    assert ascore == bscore
     assert ascore is not None and bscore is not None
+    assert ascore == pytest.approx(bscore, abs=1e-5)
 
     results = await store.asearch(("test",), query="uuu")
     assert len(results) == 2
@@ -1021,3 +1021,27 @@ async def test_embed_with_path(fake_embeddings: CharacterEmbeddings) -> None:
     assert len(results) == 3
     doc5_result = next(r for r in results if r.key == "doc5")
     assert doc5_result.score is None
+
+
+def test_non_ascii(fake_embeddings: CharacterEmbeddings) -> None:
+    """Test support for non-ascii characters"""
+    store = InMemoryStore(
+        index={"dims": fake_embeddings.dims, "embed": fake_embeddings}
+    )
+    store.put(("user_123", "memories"), "1", {"text": "这是中文"})  # Chinese
+    store.put(("user_123", "memories"), "2", {"text": "これは日本語です"})  # Japanese
+    store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"})  # Korean
+    store.put(("user_123", "memories"), "4", {"text": "Это русский"})  # Russian
+    store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"})  # Hindi
+
+    result1 = store.search(("user_123", "memories"), query="这是中文")
+    result2 = store.search(("user_123", "memories"), query="これは日本語です")
+    result3 = store.search(("user_123", "memories"), query="이건 한국어야")
+    result4 = store.search(("user_123", "memories"), query="Это русский")
+    result5 = store.search(("user_123", "memories"), query="यह रूसी है")
+
+    assert result1[0].key == "1"
+    assert result2[0].key == "2"
+    assert result3[0].key == "3"
+    assert result4[0].key == "4"
+    assert result5[0].key == "5"

libs/cli/examples/graph_prerelease_reqs/agent.py

@@ -0,0 +1,89 @@
+from collections.abc import Sequence
+from typing import Annotated, Literal, TypedDict
+
+from langchain_community.tools.tavily_search import TavilySearchResults
+from langchain_core.messages import BaseMessage
+from langchain_openai import ChatOpenAI
+from langgraph.graph import END, StateGraph, add_messages
+from langgraph.prebuilt import ToolNode
+
+tools = [TavilySearchResults(max_results=1)]
+
+model_oai = ChatOpenAI(temperature=0)
+
+model_oai = model_oai.bind_tools(tools)
+
+
+class AgentState(TypedDict):
+    messages: Annotated[Sequence[BaseMessage], add_messages]
+
+
+# Define the function that determines whether to continue or not
+def should_continue(state):
+    messages = state["messages"]
+    last_message = messages[-1]
+    # If there are no tool calls, then we finish
+    if not last_message.tool_calls:
+        return "end"
+    # Otherwise if there is, we continue
+    else:
+        return "continue"
+
+
+# Define the function that calls the model
+def call_model(state, config):
+    model = model_oai
+    messages = state["messages"]
+    response = model.invoke(messages)
+    # We return a list, because this will get added to the existing list
+    return {"messages": [response]}
+
+
+# Define the function to execute tools
+tool_node = ToolNode(tools)
+
+
+class ContextSchema(TypedDict):
+    model: Literal["anthropic", "openai"]
+
+
+# Define a new graph
+workflow = StateGraph(AgentState, context_schema=ContextSchema)
+
+# Define the two nodes we will cycle between
+workflow.add_node("agent", call_model)
+workflow.add_node("action", tool_node)
+
+# Set the entrypoint as `agent`
+# This means that this node is the first one called
+workflow.set_entry_point("agent")
+
+# We now add a conditional edge
+workflow.add_conditional_edges(
+    # First, we define the start node. We use `agent`.
+    # This means these are the edges taken after the `agent` node is called.
+    "agent",
+    # Next, we pass in the function that will determine which node is called next.
+    should_continue,
+    # Finally we pass in a mapping.
+    # The keys are strings, and the values are other nodes.
+    # END is a special node marking that the graph should finish.
+    # What will happen is we will call `should_continue`, and then the output of that
+    # will be matched against the keys in this mapping.
+    # Based on which one it matches, that node will then be called.
+    {
+        # If `tools`, then we call the tool node.
+        "continue": "action",
+        # Otherwise we finish.
+        "end": END,
+    },
+)
+
+# We now add a normal edge from `tools` to `agent`.
+# This means that after `tools` is called, `agent` node is called next.
+workflow.add_edge("action", "agent")
+
+# Finally, we compile it!
+# This compiles it into a LangChain Runnable,
+# meaning you can use it as you would any other runnable
+graph = workflow.compile()

libs/cli/examples/graph_prerelease_reqs/deps/additional_deps/pyproject.toml

@@ -0,0 +1,9 @@
+[project]
+name = "graph-prerelease-reqs-additional-deps"
+version = "0.1.0"
+description = "Test for prerelease stuff"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+  "langgraph==0.6.0"
+]

libs/cli/examples/graph_prerelease_reqs/deps/zuper_deps/pyproject.toml

@@ -0,0 +1,9 @@
+[project]
+name = "graph-prerelease-reqs-zuper-deps"
+version = "0.1.0"
+description = "Test for prerelease stuff"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+  "langchain-openai==0.3.0"
+]

libs/cli/examples/graph_prerelease_reqs/langgraph.json

@@ -0,0 +1,13 @@
+{
+    "python_version": "3.12",
+    "dependencies": [
+      ".",
+      "./deps/additional_deps",
+      "./deps/zuper_deps"
+    ],
+    "graphs": {
+      "agent": "./agent.py:graph"
+    },
+    "env": "../.env"
+  }
+  

libs/cli/examples/graph_prerelease_reqs/pyproject.toml

@@ -0,0 +1,14 @@
+[project]
+name = "graph-prerelease-reqs"
+version = "0.1.0"
+description = "Test for prerelease stuff"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+  "langchain-openai==1.0.0a2",
+  "langgraph==1.0.0a2",
+  "langchain_community>=0.3.0",
+]
+
+[tool.uv]
+prerelease = "allow"

libs/cli/examples/graph_prerelease_reqs_fail/agent.py

@@ -0,0 +1,89 @@
+from collections.abc import Sequence
+from typing import Annotated, Literal, TypedDict
+
+from langchain_community.tools.tavily_search import TavilySearchResults
+from langchain_core.messages import BaseMessage
+from langchain_openai import ChatOpenAI
+from langgraph.graph import END, StateGraph, add_messages
+from langgraph.prebuilt import ToolNode
+
+tools = [TavilySearchResults(max_results=1)]
+
+model_oai = ChatOpenAI(temperature=0)
+
+model_oai = model_oai.bind_tools(tools)
+
+
+class AgentState(TypedDict):
+    messages: Annotated[Sequence[BaseMessage], add_messages]
+
+
+# Define the function that determines whether to continue or not
+def should_continue(state):
+    messages = state["messages"]
+    last_message = messages[-1]
+    # If there are no tool calls, then we finish
+    if not last_message.tool_calls:
+        return "end"
+    # Otherwise if there is, we continue
+    else:
+        return "continue"
+
+
+# Define the function that calls the model
+def call_model(state, config):
+    model = model_oai
+    messages = state["messages"]
+    response = model.invoke(messages)
+    # We return a list, because this will get added to the existing list
+    return {"messages": [response]}
+
+
+# Define the function to execute tools
+tool_node = ToolNode(tools)
+
+
+class ContextSchema(TypedDict):
+    model: Literal["anthropic", "openai"]
+
+
+# Define a new graph
+workflow = StateGraph(AgentState, context_schema=ContextSchema)
+
+# Define the two nodes we will cycle between
+workflow.add_node("agent", call_model)
+workflow.add_node("action", tool_node)
+
+# Set the entrypoint as `agent`
+# This means that this node is the first one called
+workflow.set_entry_point("agent")
+
+# We now add a conditional edge
+workflow.add_conditional_edges(
+    # First, we define the start node. We use `agent`.
+    # This means these are the edges taken after the `agent` node is called.
+    "agent",
+    # Next, we pass in the function that will determine which node is called next.
+    should_continue,
+    # Finally we pass in a mapping.
+    # The keys are strings, and the values are other nodes.
+    # END is a special node marking that the graph should finish.
+    # What will happen is we will call `should_continue`, and then the output of that
+    # will be matched against the keys in this mapping.
+    # Based on which one it matches, that node will then be called.
+    {
+        # If `tools`, then we call the tool node.
+        "continue": "action",
+        # Otherwise we finish.
+        "end": END,
+    },
+)
+
+# We now add a normal edge from `tools` to `agent`.
+# This means that after `tools` is called, `agent` node is called next.
+workflow.add_edge("action", "agent")
+
+# Finally, we compile it!
+# This compiles it into a LangChain Runnable,
+# meaning you can use it as you would any other runnable
+graph = workflow.compile()

libs/cli/examples/graph_prerelease_reqs_fail/langgraph.json

@@ -0,0 +1,11 @@
+{
+    "python_version": "3.12",
+    "dependencies": [
+      "."
+    ],
+    "graphs": {
+      "agent": "./agent.py:graph"
+    },
+    "env": "../.env"
+  }
+  

libs/cli/examples/graph_prerelease_reqs_fail/pyproject.toml

@@ -0,0 +1,11 @@
+[project]
+name = "graph-prerelease-reqs"
+version = "0.1.0"
+description = "Test for prerelease stuff"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+  "langchain-openai==1.0.0a2",
+  "langgraph==1.0.0a2",
+  "langchain_community>=0.3.0",
+]

libs/cli/examples/graphs/agent.py

@@ -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):
+def call_model(state, runtime: Runtime[AgentContext]):
-    if config["configurable"].get("model", "anthropic") == "anthropic":
+    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)

libs/cli/examples/graphs/langgraph.json

@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
   "python_version": "3.12",
   "dependencies": [
     "langchain_community",

libs/cli/examples/graphs_reqs_a/graphs_submod/agent.py

@@ -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):
+def call_model(state, runtime: Runtime[AgentContext]):
-    if config["configurable"].get("model", "anthropic") == "anthropic":
+    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)

libs/cli/examples/graphs_reqs_a/langgraph.json

@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
   "dependencies": [
     "."
   ],

libs/cli/examples/graphs_reqs_b/graphs_submod/agent.py

@@ -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):
+def call_model(state, runtime: Runtime[AgentContext]):
-    if config["configurable"].get("model", "anthropic") == "anthropic":
+    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)

libs/cli/examples/graphs_reqs_b/langgraph.json

@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
   "dependencies": [
     "."
   ],

libs/cli/js-examples/langgraph.json

@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
   "node_version": "20",
   "graphs": {
     "agent": "./src/agent/graph.ts:graph"

libs/cli/js-monorepo-example/.eslintrc.cjs

@@ -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 }],
+  },
+};

libs/cli/js-monorepo-example/apps/agent/langgraph.json

@@ -0,0 +1,7 @@
+{
+  "node_version": "20",
+  "graphs": {
+    "agent": "./src/graph.ts:graph"
+  },
+  "env": "../../.env"
+}

libs/cli/js-monorepo-example/apps/agent/package.json

@@ -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"
+  }
+}

libs/cli/js-monorepo-example/apps/agent/src/graph.ts

@@ -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();

libs/cli/js-monorepo-example/apps/agent/src/state.ts

@@ -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: () => [],
+  }),
+});

libs/cli/js-monorepo-example/apps/agent/tsconfig.json

@@ -0,0 +1,9 @@
+{
+  "extends": "../../tsconfig.json",
+  "compilerOptions": {
+    "outDir": "./dist",
+    "rootDir": "./src"
+  },
+  "include": ["src/**/*"],
+  "exclude": ["node_modules", "dist"]
+}

libs/cli/js-monorepo-example/libs/shared/package.json

@@ -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"
+  }
+}

libs/cli/js-monorepo-example/libs/shared/src/index.ts

@@ -0,0 +1,6 @@
+/**
+ * Simple utility functions for monorepo testing
+ */
+export function getGreeting(): string {
+  return "Hello from shared library!";
+}

libs/cli/js-monorepo-example/libs/shared/tsconfig.json

@@ -0,0 +1,9 @@
+{
+  "extends": "../../tsconfig.json",
+  "compilerOptions": {
+    "outDir": "./dist",
+    "rootDir": "./src"
+  },
+  "include": ["src/**/*"],
+  "exclude": ["node_modules", "dist"]
+}

libs/cli/js-monorepo-example/package.json

@@ -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"
+  }
+}

libs/cli/js-monorepo-example/tsconfig.json

@@ -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"]
+}