check

Update check for prerelease installs
update test deps
2026-08-20 06:35:46 +02:00 · 2025-10-31 18:10:17 -07:00 · 2025-10-31 17:19:03 -07:00 · 2025-10-31 13:59:09 -07:00 · 2025-10-31 13:17:11 -07:00 · 2025-10-31 14:12:59 -04:00
241 changed files with 16474 additions and 9032 deletions
@@ -1,21 +1,21 @@
 name: "\U0001F41B Bug Report"
 description: Report a bug in LangGraph. To report a security issue, please instead use the security option below. For questions, please use the LangChain Forum at forum.langchain.com.
-labels: [pending,bug]
+labels: [pending, bug]
 body:
  - type: markdown
    attributes:
      value: |
        Thank you for taking the time to file a bug report. 
-        
+
        Use this to report BUGS in LangGraph. For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
-        
+
        Relevant links to check before filing a bug report to see if your issue has already been reported, fixed or
        if there's another way to solve your problem:
-        
+
        * [LangChain Forum](https://forum.langchain.com/),
        * [LangGraph Github Issues](https://github.com/langchain-ai/langgraph/issues),
        * [LangGraph how-to guides](https://langchain-ai.github.io/langgraph/how-tos/).
-        * [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
+        * [LangChain documentation with the integrated search](https://docs.langchain.com/),
        * [GitHub search](https://github.com/langchain-ai/langgraph),
  - type: checkboxes
    id: checks
@@ -1,6 +1,9 @@
 blank_issues_enabled: false
 version: 2.1
 contact_links:
  - name: Documentation
    url: https://github.com/langchain-ai/docs/issues/new?template=langgraph.yml
    about: Report an issue related to the LangGraph documentation
  - name: LangChain Forum
    url:  https://forum.langchain.com/
-    about: General community discussions, support, and feature requests
+    about: General community discussions and support
@@ -1,19 +0,0 @@
 name: Documentation
 description: Report an issue related to the LangGraph documentation.
 title: "DOC: <Please write a comprehensive title after the 'DOC: ' prefix>"
 labels: [documentation]
 body:
 - type: textarea
  attributes: 
    label: "Issue with current documentation:"
    description: >
      Please make sure to leave a reference to the document/code you're
      referring to.
 - type: textarea
  attributes:
    label: "Idea or request for content:"
    description: >
      Please describe as clearly as possible what topics you think are missing
      from the current documentation.
@@ -1,7 +1,8 @@
 import logging
 import pathlib
 import sys
 import time
-from urllib import request, error
+from urllib import error, request
 import langgraph_cli
 import langgraph_cli.config
@@ -11,9 +12,13 @@ from langgraph_cli.constants import DEFAULT_PORT
 from langgraph_cli.exec import Runner, subp_exec
 from langgraph_cli.progress import Progress
 logger = logging.getLogger(__name__)
 logging.basicConfig(level=logging.INFO)
 def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
    """Spin up API with Postgres/Redis via docker compose and wait until ready."""
    logger.info("Starting test...")
    with Runner() as runner, Progress(message="Pulling...") as set:
        # Detect docker/compose capabilities
        capabilities = langgraph_cli.docker.check_capabilities(runner)
@@ -57,7 +62,9 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
            sys.stderr.write(f"docker compose up failed: {e}\n")
            try:
                sys.stderr.write("\n== docker compose ps ==\n")
-                runner.run(subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=False))
+                runner.run(
                    subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=False)
                )
            except Exception:
                pass
            try:
@@ -93,7 +100,7 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
        set("")
        base_url = f"http://localhost:{port}"
        ok_url = f"{base_url}/ok"
-        print(f"Waiting for {ok_url} to respond with 200...")
+        logger.info(f"Waiting for {ok_url} to respond with 200...")
        deadline = time.time() + 30
        last_err: Exception | None = None
        while time.time() < deadline:
@@ -107,13 +114,16 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
                        break
                    else:
                        last_err = RuntimeError(f"Unexpected status: {resp.status}")
-                        print(f"Unexpected status: {resp.status}")
+                        logger.error(f"Unexpected status: {resp.status}")
            except error.URLError as e:
                logger.error(f"URLError: {e}")
                last_err = e
            except Exception as e:  # noqa: BLE001
                logger.error(f"Exception: {e}")
                last_err = e
            time.sleep(0.5)
        else:
            logger.error("Timeout waiting for /ok to return 200")
            # Bring stack down before raising
            args_down = [*args, "down", "-v", "--remove-orphans"]
            try:
@@ -131,15 +141,23 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
                )
        # Clean up: bring compose stack down to free ports for next test
-        args_down = [*args, "down", "-v", "--remove-orphans"]
+        logger.info("Test succeeded. Bringing down compose stack...")
-        runner.run(
+        try:
-            subp_exec(
+            args_down = [*args, "down", "-v", "--remove-orphans"]
-                *compose_cmd,
+            runner.run(
-                *args_down,
+                subp_exec(
-                input=stdin,
+                    *compose_cmd,
-                verbose=verbose,
+                    *args_down,
                    input=stdin,
                    verbose=verbose,
                )
            )
-        )
+            logger.info("Compose stack down. Finishing...")
        except Exception:
            logger.exception("Failed to bring down compose stack")
            pass
    logger.info("Test finished")
 if __name__ == "__main__":
@@ -150,4 +168,10 @@ if __name__ == "__main__":
    parser.add_argument("-c", "--config", type=str, default="./langgraph.json")
    parser.add_argument("-p", "--port", type=int, default=DEFAULT_PORT)
    args = parser.parse_args()
-    test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
+    try:
        test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
    except BaseException:
        logger.exception("Test failed")
        raise
    logger.info("Test execution finished")
@@ -13,13 +13,26 @@ jobs:
      matrix:
        python-version:
          - "3.10"
-          - "3.11"
+          - "3.14"
        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
@@ -27,75 +40,45 @@ 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
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
        working-directory: libs/cli/js-examples
        run: |
          langgraph build -t langgraph-test-e
      - name: Build JS monorepo service
-        if: steps.changed-files.outputs.all
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
        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
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
        working-directory: libs/cli/python-monorepo-example
        run: |
          langgraph build -t langgraph-test-g -c apps/agent/langgraph.json
@@ -104,10 +87,32 @@ jobs:
          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
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
        working-directory: libs/cli/examples/graph_prerelease_reqs
        run: |
          langgraph build -t langgraph-test-h
          cp ../.env.example .env
          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-h
          echo "Finished starting up langgraph-test-h"
          LANGGRAPH_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langgraph'); print(v);")
          if [ "$LANGGRAPH_VERSION" != "1.0.2" ]; then
            echo "LANGGRAPH_VERSION != 1.0.2; $LANGGRAPH_VERSION"
            exit 1
          fi
          LANGCHAIN_OPENAI_VERSION=$(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" != "1.0.1" ]; then
            echo "LANGCHAIN_OPENAI_VERSION != 1.0.1; $LANGCHAIN_OPENAI_VERSION"
            exit 1
          fi
          LANGCHAIN_ANTHROPIC_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-anthropic'); print(v);")
          if [ "$LANGCHAIN_ANTHROPIC_VERSION" != "1.0.0a5" ]; then
            echo "LANGCHAIN_ANTHROPIC_VERSION != 1.0.0a5; $LANGCHAIN_ANTHROPIC_VERSION"
            exit 1
          fi
      - name: Build and test prerelease reqs fail service
        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
        working-directory: libs/cli/examples/graph_prerelease_reqs_fail
        run: |
          langgraph build -t langgraph-test-i || [ $? -eq 1 ]
@@ -31,7 +31,7 @@ jobs:
          - "3.12"
    name: "lint #${{ matrix.python-version }}"
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - name: Get changed files
        id: changed-files
        uses: Ana06/get-changed-files@v2.3.0
@@ -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
@@ -48,7 +48,7 @@ jobs:
      - name: Install dependencies
        if: steps.changed-files.outputs.all
        working-directory: ${{ inputs.working-directory }}
-        run: uv sync --frozen --group dev
+        run: uv sync --frozen --group lint
      - name: Get .mypy_cache to speed up mypy
        if: steps.changed-files.outputs.all
@@ -74,7 +74,7 @@ jobs:
      - name: Install test dependencies
        if: steps.changed-files.outputs.all
        working-directory: ${{ inputs.working-directory }}
-        run: uv sync --group dev
+        run: uv sync --group lint
      - name: Get .mypy_cache_test to speed up mypy
        if: steps.changed-files.outputs.all
@@ -17,17 +17,17 @@ jobs:
    strategy:
      matrix:
        python-version:
          - "3.9"
          - "3.10"
          - "3.11"
          - "3.12"
          - "3.13"
          - "3.14"
    name: "test #${{ 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
@@ -42,7 +42,7 @@ jobs:
      - name: Install dependencies
        shell: bash
        working-directory: ${{ inputs.working-directory }}
-        run: uv sync --frozen --group dev
+        run: uv sync --frozen --group test --no-dev
      - name: Run tests
        shell: bash
@@ -12,20 +12,20 @@ jobs:
    strategy:
      matrix:
        python-version:
          - "3.9"
          - "3.10"
          - "3.11"
          - "3.12"
          - "3.13"
          - "3.14"
    defaults:
      run:
        working-directory: libs/langgraph
    name: "test #${{ 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
@@ -39,7 +39,7 @@ jobs:
      - name: Install dependencies
        shell: bash
-        run: uv sync --frozen --group dev
+        run: uv sync --frozen --group test --no-dev
      - name: Run tests
        shell: bash
@@ -16,7 +16,6 @@ permissions:
 jobs:
  build:
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    outputs:
@@ -24,10 +23,10 @@ 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
@@ -49,7 +48,7 @@ jobs:
        working-directory: ${{ inputs.working-directory }}
      - name: Upload build
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v5
        with:
          name: test-dist
          path: ${{ inputs.working-directory }}/dist/
@@ -75,9 +74,9 @@ jobs:
      id-token: write
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
-      - uses: actions/download-artifact@v4
+      - uses: actions/download-artifact@v6
        with:
          name: test-dist
          path: ${{ inputs.working-directory }}/dist/
@@ -17,16 +17,16 @@ jobs:
      run:
        working-directory: libs/langgraph
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - run: SHA=$(git rev-parse HEAD) && echo "SHA=$SHA" >> $GITHUB_ENV
      - name: Set up Python 3.11
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
        with:
          python-version: "3.11"
          enable-cache: true
          cache-suffix: "bench"
      - name: Install dependencies
-        run: uv sync --group dev
+        run: uv sync --group test
      - name: Run benchmarks
        run: OUTPUT=out/benchmark-baseline.json make -s benchmark
      - name: Save outputs
@@ -15,20 +15,20 @@ jobs:
      run:
        working-directory: libs/langgraph
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - id: files
        name: Get changed files
        uses: Ana06/get-changed-files@v2.3.0
        with:
          format: json
      - name: Set up Python 3.11
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
        with:
          python-version: "3.11"
          enable-cache: true
          cache-suffix: "bench"
      - name: Install dependencies
-        run: uv sync --group dev
+        run: uv sync --group test
      - name: Download baseline
        uses: actions/cache/restore@v4
        with:
@@ -57,7 +57,7 @@ jobs:
            echo EOF
          } >> "$GITHUB_OUTPUT"
      - name: Annotation
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
        with:
          script: |
            const file = JSON.parse(`${{ steps.files.outputs.added_modified_renamed }}`)[0]
@@ -27,7 +27,7 @@ jobs:
      python: ${{ steps.filter.outputs.python }}
      deps: ${{ steps.filter.outputs.deps }}
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - uses: dorny/paths-filter@v3
        id: filter
        with:
@@ -100,9 +100,9 @@ jobs:
    name: "Check SDK methods matching"
    runs-on: ubuntu-latest
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
      - name: Set up Python
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v6
        with:
          python-version: "3.11"
      - name: Run check_sdk_methods script
@@ -118,9 +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
@@ -21,7 +21,7 @@
        steps:
          - name: Checkout
-            uses: actions/checkout@v4
+            uses: actions/checkout@v5
          - name: Install Dependencies
            run: |
@@ -1,12 +1,9 @@
-name: Deploy Docs
+name: Deploy Docs Redirects
 on:
  push:
    branches:
      - main
  pull_request:
    branches:
      - main
  workflow_dispatch:
 permissions:
@@ -23,30 +20,18 @@ defaults:
    working-directory: docs
 jobs:
  get-changed-files:
    runs-on: ubuntu-latest
    outputs:
      changed-files: ${{ steps.changed-files.outputs.added_modified }}
    steps:
      - uses: actions/checkout@v4
      - name: Get changed files
        id: changed-files
        uses: Ana06/get-changed-files@v2.3.0
        with:
          filter: "docs/docs/**"
  deploy:
    runs-on: ubuntu-latest
    timeout-minutes: 10 # Job will be cancelled if it runs for more than 10 minutes
    env:
      GITHUB_TOKEN: ${{ secrets.MKDOCS_GITHUB_TOKEN }}
    steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
        with:
          fetch-depth: 0
      - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
        with:
          python-version: "3.12"
          enable-cache: true
@@ -62,85 +47,22 @@ jobs:
            uv run pip install "git+https://${GITHUB_TOKEN}@github.com/langchain-ai/mkdocs-material-insiders.git"
          fi
      - name: Run unit tests
        # Run unit tests on the docs build pipeline
        run: make tests
      - name: Lint Docs
        # This step lints the docs using the existing linting set up.
        # It should be very fast and should not require any external services.
        run: make lint-docs
      - name: Build llms-text
        run: make llms-text
-      - name: Build site
+
-        run: |
+      - name: Build site (redirects only)
-          # If this is main branch, then we want to download stats. we do this 
+        run: make build-docs
          # with the env variable DOWNLOAD_STATS=true
          if [ "${{ github.ref }}" == "refs/heads/main" ]; then
            DOWNLOAD_STATS=true make build-docs
          else
            make build-docs
          fi
        env:
          MKDOCS_GIT_COMMITTERS_APIKEY: ${{ secrets.MKDOCS_GIT_COMMITTERS_APIKEY }}
          OPENAI_API_KEY: sf-proj-1234567890 # fake placeholder, shouldn't actually be used
          ANTHROPIC_API_KEY: sk-ant-api03-1234567890 # fake placeholder, shouldn't actually be used
      - name: Check links in notebooks
        env:
          LANGCHAIN_API_KEY: test
        if: github.event_name == 'schedule'
        run: |
          if [ "${{ github.event_name }}" == "schedule" ]; then
            echo "Running link check on all HTML files matching notebooks in docs directory..."
            uv run pytest -v \
              --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
              --check-links-ignore "https://academy\.langchain\.com/.*" \
              --check-links-ignore "https://x.com/.*" \
              --check-links-ignore "https://twitter.com/.*" \
              --check-links-ignore "https://github\.com/.*" \
              --check-links-ignore "http://localhost:8123/.*" \
              --check-links-ignore "http://localhost:2024.*" \
              --check-links-ignore "http://127.0.0.1:.*" \
              --check-links-ignore "/.*\.(ipynb|html)$" \
              --check-links-ignore "https://python\.langchain\.com/.*" \
              --check-links-ignore "https://openai\.com/.*" \
              --check-links-ignore "https://www\.uber\.com/.*" \
              --check-links-ignore "https://pepy\.tech/.*" \
              --check-links-ignore "docs/docs/static/wordmark_*" \
              --check-links $(find site -name "index.html" | grep -v 'storm/index.html')
          else
            echo "Fetching changes from origin/main..."
            git fetch origin main
            echo "Checking for changed notebook files..."
            CHANGED_FILES=$(git diff --name-only --diff-filter=d origin/main | grep 'docs/docs/.*\.ipynb$' | grep -v 'storm.ipynb' | sed -E 's|^docs/docs/|site/|; s/\.ipynb$/\/index.html/' || true)
            echo "Changed files: ${CHANGED_FILES}"
            if [ -n "${CHANGED_FILES}" ]; then
              echo "Running link check on HTML files matching changed notebook files..."
              uv run pytest -v \
                --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
                --check-links-ignore "https://academy\.langchain\.com/.*" \
                --check-links-ignore "http://localhost:8123/.*" \
                --check-links-ignore "http://localhost:2024.*" \
                --check-links-ignore "http://127.0.0.1:.*" \
                --check-links-ignore "https://x.com/.*" \
                --check-links-ignore "https://twitter.com/.*" \
                --check-links-ignore "https://github\.com/.*" \
                --check-links-ignore "/.*\.(ipynb|html)$" \
                --check-links-ignore "docs/docs/static/wordmark_*" \
                --check-links ${CHANGED_FILES} \
                || ([ $? = 5 ] && exit 0 || exit $?)
            else
              echo "No notebook files changed."
            fi
          fi
      - name: Configure GitHub Pages
        if: github.ref == 'refs/heads/main'
        uses: actions/configure-pages@v5
      - name: Upload Pages Artifact
-        # if: github.ref == 'refs/heads/main'
+        if: github.ref == 'refs/heads/main'
-        uses: actions/upload-pages-artifact@v3
+        uses: actions/upload-pages-artifact@v4
        with:
          path: ./docs/site/
@@ -19,7 +19,7 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
        with:
          fetch-depth: 0
@@ -36,7 +36,7 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
        with:
          fetch-depth: 1
@@ -12,7 +12,7 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Validate PR Title
-        uses: amannn/action-semantic-pull-request@v5
+        uses: amannn/action-semantic-pull-request@v6
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
        with:
@@ -40,6 +40,7 @@ jobs:
            sdk-py
            docs
            ci
            deps
          requireScope: false
          ignoreLabels: |
            ignore-lint-pr-title
@@ -16,7 +16,6 @@ env:
 jobs:
  build:
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    outputs:
@@ -26,10 +25,10 @@ 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
@@ -51,7 +50,7 @@ jobs:
        working-directory: ${{ inputs.working-directory }}
      - name: Upload build
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v5
        with:
          name: dist
          path: ${{ inputs.working-directory }}/dist/
@@ -87,7 +86,7 @@ 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 +157,7 @@ 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 +173,7 @@ 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
@@ -222,7 +221,7 @@ jobs:
          uv run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
      - name: Import test dependencies
-        run: uv sync --group dev
+        run: uv sync --group test
        working-directory: ${{ inputs.working-directory }}
      # Overwrite the local version of the package with the test PyPI version.
@@ -261,16 +260,16 @@ 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@v6
        with:
          name: dist
          path: ${{ inputs.working-directory }}/dist/
@@ -302,16 +301,16 @@ 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@v6
        with:
          name: dist
          path: ${{ inputs.working-directory }}/dist/
@@ -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
@@ -16,13 +16,13 @@ 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"
+          python-version: "3.10"
          enable-cache: true
          cache-suffix: "uv-lock-upgrade"
@@ -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`.
@@ -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
@@ -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
@@ -63,15 +63,15 @@ 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.
+- [LangChain](https://docs.langchain.com/oss/python/langchain/overview) – Provides integrations and composable components to streamline LLM application development.
 > [!NOTE]
 > Looking for the JS version of LangGraph? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://langchain-ai.github.io/langgraphjs/).
 ## 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.
@@ -81,4 +81,4 @@ While LangGraph can be used standalone, it also integrates seamlessly with any L
 ## Acknowledgements
-LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
+LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
@@ -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
@@ -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"),
@@ -29,7 +29,11 @@ logger = logging.getLogger(__name__)
 def _transform_link(
-    link_name: str, scope: str, file_path: str, line_number: int, custom_title: Optional[str] = None
+    link_name: str,
    scope: str,
    file_path: str,
    line_number: int,
    custom_title: Optional[str] = None,
 ) -> Optional[str]:
    """Transform a cross-reference link based on the current scope.
@@ -38,7 +42,7 @@ def _transform_link(
        scope: The current scope context ("global", "python", "js", etc.).
        file_path: The file path for error reporting.
        line_number: The line number for error reporting.
-        custom_title: Optional custom title for the link. If None, uses link_name.
+        custom_title: Optional custom title for the link. If `None`, uses link_name.
    Returns:
        A formatted markdown link if the link is found in the scope mapping,
@@ -117,7 +121,9 @@ CROSS_REFERENCE_PATTERN = re.compile(
 )
-def _replace_autolinks(markdown: str, file_path: str, *, default_scope: str = "python") -> str:
+def _replace_autolinks(
    markdown: str, file_path: str, *, default_scope: str = "python"
 ) -> str:
    """Preprocess markdown lines to handle @[links] with conditional fence scopes.
    This function processes markdown content to transform @[link_name] references
@@ -169,7 +175,7 @@ def _replace_autolinks(markdown: str, file_path: str, *, default_scope: str = "p
                # This is @[ref] format
                link_name = match.group("link_name")
                custom_title = None
-            
+
            transformed = _transform_link(
                link_name, current_scope, file_path, line_number, custom_title
            )
@@ -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
@@ -1,3 +1,5 @@
 """Convert Jupyter notebooks to markdown with custom processing."""
 import ast
 import os
 import re
@@ -27,185 +27,413 @@ DISABLED = os.getenv("DISABLE_NOTEBOOK_CONVERT") in ("1", "true", "True")
 REDIRECT_MAP = {
    # lib redirects
-    "how-tos/stream-values.ipynb": "how-tos/streaming.md#stream-graph-state",
+    "how-tos/stream-values.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
-    "how-tos/stream-updates.ipynb": "how-tos/streaming.md#stream-graph-state",
+    "how-tos/stream-updates.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
-    "how-tos/streaming-content.ipynb": "how-tos/streaming.md",
+    "how-tos/streaming-content.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
-    "how-tos/stream-multiple.ipynb": "how-tos/streaming.md#stream-multiple-nodes",
+    "how-tos/stream-multiple.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
-    "how-tos/streaming-tokens-without-langchain.ipynb": "how-tos/streaming.md#use-with-any-llm",
+    "how-tos/streaming-tokens-without-langchain.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
-    "how-tos/streaming-from-final-node.ipynb": "how-tos/streaming-specific-nodes.ipynb",
+    "how-tos/streaming-from-final-node.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
-    "how-tos/streaming-events-from-within-tools-without-langchain.ipynb": "how-tos/streaming-events-from-within-tools.ipynb#example-without-langchain",
+    "how-tos/streaming-events-from-within-tools-without-langchain.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
    # graph-api
-    "how-tos/state-reducers.ipynb": "how-tos/graph-api.md#define-and-update-state",
+    "how-tos/state-reducers.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#define-and-update-state",
-    "how-tos/sequence.ipynb": "how-tos/graph-api.md#create-a-sequence-of-steps",
+    "how-tos/sequence.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#create-a-sequence-of-steps",
-    "how-tos/branching.ipynb": "how-tos/graph-api.md#create-branches",
+    "how-tos/branching.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#create-branches",
-    "how-tos/recursion-limit.ipynb": "how-tos/graph-api.md#create-and-control-loops",
+    "how-tos/recursion-limit.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#create-and-control-loops",
-    "how-tos/visualization.ipynb": "how-tos/graph-api.md#visualize-your-graph",
+    "how-tos/visualization.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#visualize-your-graph",
-    "how-tos/input_output_schema.ipynb": "how-tos/graph-api.md#define-input-and-output-schemas",
+    "how-tos/input_output_schema.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#define-input-and-output-schemas",
-    "how-tos/pass_private_state.ipynb": "how-tos/graph-api.md#pass-private-state-between-nodes",
+    "how-tos/pass_private_state.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#pass-private-state-between-nodes",
-    "how-tos/state-model.ipynb": "how-tos/graph-api.md#use-pydantic-models-for-graph-state",
+    "how-tos/state-model.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#use-pydantic-models-for-graph-state",
-    "how-tos/map-reduce.ipynb": "how-tos/graph-api.md#map-reduce-and-the-send-api",
+    "how-tos/map-reduce.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#map-reduce-and-the-send-api",
-    "how-tos/command.ipynb": "how-tos/graph-api.md#combine-control-flow-and-state-updates-with-command",
+    "how-tos/command.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#combine-control-flow-and-state-updates-with-command",
-    "how-tos/configuration.ipynb": "how-tos/graph-api.md#add-runtime-configuration",
+    "how-tos/configuration.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#add-runtime-configuration",
-    "how-tos/node-retries.ipynb": "how-tos/graph-api.md#add-retry-policies",
+    "how-tos/node-retries.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#add-retry-policies",
-    "how-tos/return-when-recursion-limit-hits.ipynb": "how-tos/graph-api.md#impose-a-recursion-limit",
+    "how-tos/return-when-recursion-limit-hits.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#impose-a-recursion-limit",
-    "how-tos/async.ipynb": "how-tos/graph-api.md#async",
+    "how-tos/async.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#async",
    # memory how-tos
-    "how-tos/memory/manage-conversation-history.ipynb": "how-tos/memory/add-memory.md",
+    "how-tos/memory/manage-conversation-history.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
-    "how-tos/memory/delete-messages.ipynb": "how-tos/memory/add-memory.md#delete-messages",
+    "how-tos/memory/delete-messages.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#delete-messages",
-    "how-tos/memory/add-summary-conversation-history.ipynb": "how-tos/memory/add-memory.md#summarize-messages",
+    "how-tos/memory/add-summary-conversation-history.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#summarize-messages",
-    "how-tos/memory.ipynb": "how-tos/memory/add-memory.md",
+    "how-tos/memory.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
-    "agents/memory.ipynb": "how-tos/memory/add-memory.md",
+    "agents/memory.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
    # subgraph how-tos
-    "how-tos/subgraph-transform-state.ipynb": "how-tos/subgraph.md#different-state-schemas",
+    "how-tos/subgraph-transform-state.ipynb": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs#different-state-schemas",
-    "how-tos/subgraphs-manage-state.ipynb": "how-tos/subgraph.md#add-persistence",
+    "how-tos/subgraphs-manage-state.ipynb": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs#add-persistence",
    # persistence how-tos
-    "how-tos/persistence_postgres.ipynb": "how-tos/memory/add-memory.md#use-in-production",
+    "how-tos/persistence_postgres.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-in-production",
-    "how-tos/persistence_mongodb.ipynb": "how-tos/memory/add-memory.md#use-in-production",
+    "how-tos/persistence_mongodb.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-in-production",
-    "how-tos/persistence_redis.ipynb": "how-tos/memory/add-memory.md#use-in-production",
+    "how-tos/persistence_redis.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-in-production",
-    "how-tos/subgraph-persistence.ipynb": "how-tos/memory/add-memory.md#use-with-subgraphs",
+    "how-tos/subgraph-persistence.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-with-subgraphs",
-    "how-tos/cross-thread-persistence.ipynb": "how-tos/memory/add-memory.md#add-long-term-memory",
+    "how-tos/cross-thread-persistence.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#add-long-term-memory",
-    "cloud/how-tos/copy_threads": "cloud/how-tos/use_threads",
+    "cloud/how-tos/copy_threads": "https://docs.langchain.com/langsmith/use-threads",
-    "cloud/how-tos/check-thread-status": "cloud/how-tos/use_threads",
+    "cloud/how-tos/check-thread-status": "https://docs.langchain.com/langsmith/use-threads",
-    "cloud/concepts/threads.md": "concepts/persistence.md#threads",
+    "cloud/concepts/threads.md": "https://docs.langchain.com/oss/python/langgraph/persistence#threads",
-    "how-tos/persistence.ipynb": "how-tos/memory/add-memory.md",
+    "how-tos/persistence.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
    # tool calling how-tos
-    "how-tos/tool-calling-errors.ipynb": "how-tos/tool-calling.ipynb#handle-errors",
+    "how-tos/tool-calling-errors.ipynb": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
-    "how-tos/pass-config-to-tools.ipynb": "how-tos/tool-calling.ipynb#access-config",
+    "how-tos/pass-config-to-tools.ipynb": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
-    "how-tos/pass-run-time-values-to-tools.ipynb": "how-tos/tool-calling.ipynb#read-state",
+    "how-tos/pass-run-time-values-to-tools.ipynb": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
-    "how-tos/update-state-from-tools.ipynb": "how-tos/tool-calling.ipynb#update-state",
+    "how-tos/update-state-from-tools.ipynb": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
-    "agents/tools.md": "how-tos/tool-calling.md",
+    "agents/tools.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    # multi-agent how-tos
-    "how-tos/agent-handoffs.ipynb": "how-tos/multi_agent.md#handoffs",
+    "how-tos/agent-handoffs.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api",
-    "how-tos/multi-agent-network.ipynb": "how-tos/multi_agent.md#use-in-a-multi-agent-system",
+    "how-tos/multi-agent-network.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api",
-    "how-tos/multi-agent-multi-turn-convo.ipynb": "how-tos/multi_agent.md#multi-turn-conversation",
+    "how-tos/multi-agent-multi-turn-convo.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api",
    # cloud redirects
-    "cloud/index.md": "index.md",
+    "cloud/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
-    "cloud/how-tos/index.md": "concepts/langgraph_platform",
+    "cloud/how-tos/index.md": "https://docs.langchain.com/langsmith/home",
-    "cloud/concepts/api.md": "concepts/langgraph_server.md",
+    "cloud/concepts/api.md": "https://docs.langchain.com/langsmith/langgraph-server",
-    "cloud/concepts/cloud.md": "concepts/langgraph_cloud.md",
+    "cloud/concepts/cloud.md": "https://docs.langchain.com/langsmith/cloud",
-    "cloud/faq/studio.md": "concepts/langgraph_studio.md#studio-faqs",
+    "cloud/faq/studio.md": "https://docs.langchain.com/langsmith/studio",
-    "cloud/how-tos/human_in_the_loop_edit_state.md": "cloud/how-tos/add-human-in-the-loop.md",
+    "cloud/how-tos/human_in_the_loop_edit_state.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
-    "cloud/how-tos/human_in_the_loop_user_input.md": "cloud/how-tos/add-human-in-the-loop.md",
+    "cloud/how-tos/human_in_the_loop_user_input.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
-    "concepts/platform_architecture.md": "concepts/langgraph_cloud#architecture",
+    "concepts/platform_architecture.md": "https://docs.langchain.com/langsmith/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",
+    "cloud/concepts/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
-    "agents/streaming.md": "how-tos/streaming.md",
+    "agents/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
    # prebuilt redirects
-    "how-tos/create-react-agent.ipynb": "agents/agents.md#basic-configuration",
+    "how-tos/create-react-agent.ipynb": "https://docs.langchain.com/oss/python/langchain/agents#basic-configuration",
-    "how-tos/create-react-agent-memory.ipynb": "agents/memory.md",
+    "how-tos/create-react-agent-memory.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
-    "how-tos/create-react-agent-system-prompt.ipynb": "agents/context.md#prompts",
+    "how-tos/create-react-agent-system-prompt.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
-    "how-tos/create-react-agent-structured-output.ipynb": "agents/agents.md#structured-output",
+    "how-tos/create-react-agent-structured-output.ipynb": "https://docs.langchain.com/oss/python/langchain/agents#structured-output",
    # misc
-    "prebuilt.md": "agents/prebuilt.md",
+    "prebuilt.md": "https://docs.langchain.com/oss/python/langchain/agents",
-    "reference/prebuilt.md": "reference/agents.md",
+    "reference/prebuilt.md": "https://reference.langchain.com/python/langgraph/agents/",
-    "concepts/high_level.md": "index.md",
+    "concepts/high_level.md": "https://docs.langchain.com/oss/python/langgraph/overview",
-    "concepts/index.md": "index.md",
+    "concepts/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
-    "concepts/v0-human-in-the-loop.md": "concepts/human-in-the-loop.md",
+    "concepts/v0-human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
-    "how-tos/index.md": "index.md",
+    "how-tos/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
-    "tutorials/introduction.ipynb": "concepts/why-langgraph.md",
+    "tutorials/introduction.ipynb": "https://docs.langchain.com/oss/python/langgraph/overview",
-    "agents/deployment.md": "tutorials/langgraph-platform/local-server.md",
+    "agents/deployment.md": "https://docs.langchain.com/oss/python/langgraph/local-server",
    # deployment redirects
-    "how-tos/deploy-self-hosted.md": "cloud/deployment/self_hosted_data_plane.md",
+    "how-tos/deploy-self-hosted.md": "https://docs.langchain.com/langsmith/hosting",
-    "concepts/self_hosted.md": "concepts/langgraph_self_hosted_data_plane.md",
+    "concepts/self_hosted.md": "https://docs.langchain.com/langsmith/hosting",
-    "tutorials/deployment.md": "concepts/deployment_options.md",
+    "tutorials/deployment.md": "https://docs.langchain.com/langsmith/deployments",
    # assistant redirects
-    "cloud/how-tos/assistant_versioning.md": "cloud/how-tos/configuration_cloud.md",
+    "cloud/how-tos/assistant_versioning.md": "https://docs.langchain.com/langsmith/configuration-cloud",
-    "cloud/concepts/runs.md": "concepts/assistants.md#execution",
+    "cloud/concepts/runs.md": "https://docs.langchain.com/langsmith/assistants#execution",
    # hitl redirects
-    "how-tos/wait-user-input-functional.ipynb": "how-tos/use-functional-api.md",
+    "how-tos/wait-user-input-functional.ipynb": "https://docs.langchain.com/oss/python/langgraph/functional-api",
-    "how-tos/review-tool-calls-functional.ipynb": "how-tos/use-functional-api.md",
+    "how-tos/review-tool-calls-functional.ipynb": "https://docs.langchain.com/oss/python/langgraph/functional-api",
-    "how-tos/create-react-agent-hitl.ipynb": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
+    "how-tos/create-react-agent-hitl.ipynb": "https://docs.langchain.com/oss/python/langgraph/interrupts",
-    "agents/human-in-the-loop.md": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
+    "agents/human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
-    "how-tos/human_in_the_loop/dynamic_breakpoints.ipynb": "how-tos/human_in_the_loop/breakpoints.md",
+    "how-tos/human_in_the_loop/dynamic_breakpoints.ipynb": "https://docs.langchain.com/oss/python/langgraph/interrupts",
-    "concepts/breakpoints.md": "concepts/human_in_the_loop.md",
+    "concepts/breakpoints.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
-    "how-tos/human_in_the_loop/breakpoints.md": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
+    "how-tos/human_in_the_loop/breakpoints.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
-    "cloud/how-tos/human_in_the_loop_breakpoint.md": "cloud/how-tos/add-human-in-the-loop.md",
+    "cloud/how-tos/human_in_the_loop_breakpoint.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
-    "how-tos/human_in_the_loop/edit-graph-state.ipynb": "how-tos/human_in_the_loop/time-travel.md",
+    "how-tos/human_in_the_loop/edit-graph-state.ipynb": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",
    # 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/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/platform-setup",
-    "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",
    # LangGraph mintlify migration redirects
    "index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "agents/agents.md": "https://docs.langchain.com/oss/python/langchain/agents",
    "concepts/why-langgraph.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "tutorials/get-started/1-build-basic-chatbot.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
    "tutorials/get-started/2-add-tools.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
    "tutorials/get-started/3-add-memory.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
    "tutorials/get-started/4-human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
    "tutorials/get-started/5-customize-state.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
    "tutorials/get-started/6-time-travel.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
    "tutorials/langsmith/local-server.md": "https://docs.langchain.com/oss/python/langgraph/local-server",
    "tutorials/workflows.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    "concepts/agentic_concepts.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    "guides/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
    "agents/overview.md": "https://docs.langchain.com/oss/python/langchain/agents",
    "agents/run_agents.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
    "concepts/low_level.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
    "how-tos/graph-api.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
    "concepts/functional_api.md": "https://docs.langchain.com/oss/python/langgraph/functional-api",
    "how-tos/use-functional-api.md": "https://docs.langchain.com/oss/python/langgraph/functional-api",
    "concepts/pregel.md": "https://docs.langchain.com/oss/python/langgraph/pregel",
    "concepts/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
    "how-tos/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
    "concepts/persistence.md": "https://docs.langchain.com/oss/python/langgraph/persistence",
    "concepts/durable_execution.md": "https://docs.langchain.com/oss/python/langgraph/durable-execution",
    "concepts/memory.md": "https://docs.langchain.com/oss/python/langgraph/memory",
    "how-tos/memory/add-memory.md": "https://docs.langchain.com/oss/python/langgraph/add-memory",
    "agents/context.md": "https://docs.langchain.com/oss/python/langgraph/add-memory",
    "agents/models.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "concepts/tools.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    "how-tos/tool-calling.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    "concepts/human_in_the_loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
    "how-tos/human_in_the_loop/add-human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
    "concepts/time-travel.md": "https://docs.langchain.com/oss/python/langgraph/persistence",
    "how-tos/human_in_the_loop/time-travel.md": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",
    "concepts/subgraphs.md": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
    "how-tos/subgraph.md": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
    "concepts/multi_agent.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
    "agents/multi-agent.md": "https://docs.langchain.com/oss/python/langchain/multi-agent",
    "how-tos/multi_agent.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
    "concepts/mcp.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "agents/mcp.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "concepts/tracing.md": "https://docs.langchain.com/oss/python/langgraph/observability",
    "how-tos/enable-tracing.md": "https://docs.langchain.com/oss/python/langgraph/observability",
    "agents/evals.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "examples/index.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
    "concepts/template_applications.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "tutorials/rag/langgraph_agentic_rag.md": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
    "tutorials/multi_agent/agent_supervisor.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    "tutorials/sql/sql-agent.md": "https://docs.langchain.com/oss/python/langgraph/sql-agent",
    "agents/ui.md": "https://docs.langchain.com/oss/python/langgraph/ui",
    "how-tos/run-id-langsmith.md": "https://docs.langchain.com/oss/python/langgraph/observability",
    "troubleshooting/errors/index.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
    "troubleshooting/errors/INVALID_CHAT_HISTORY.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CHAT_HISTORY",
    "troubleshooting/errors/INVALID_LICENSE.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
    "adopters.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
    "concepts/faq.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "agents/prebuilt.md": "https://docs.langchain.com/oss/python/langchain/agents",
    "reference/index.md": "https://reference.langchain.com/python/langgraph/",
    "reference/graphs.md": "https://reference.langchain.com/python/langgraph/graphs/",
    "reference/func.md": "https://reference.langchain.com/python/langgraph/func/",
    "reference/pregel.md": "https://reference.langchain.com/python/langgraph/pregel/",
    "reference/checkpoints.md": "https://reference.langchain.com/python/langgraph/checkpoints/",
    "reference/store.md": "https://reference.langchain.com/python/langgraph/store/",
    "reference/cache.md": "https://reference.langchain.com/python/langgraph/cache/",
    "reference/types.md": "https://reference.langchain.com/python/langgraph/types/",
    "reference/runtime.md": "https://reference.langchain.com/python/langgraph/runtime/",
    "reference/config.md": "https://reference.langchain.com/python/langgraph/config/",
    "reference/errors.md": "https://reference.langchain.com/python/langgraph/errors/",
    "reference/constants.md": "https://reference.langchain.com/python/langgraph/constants/",
    "reference/channels.md": "https://reference.langchain.com/python/langgraph/channels/",
    "reference/agents.md": "https://reference.langchain.com/python/langgraph/agents/",
    "reference/supervisor.md": "https://reference.langchain.com/python/langgraph/supervisor/",
    "reference/swarm.md": "https://reference.langchain.com/python/langgraph/swarm/",
    "reference/mcp.md": "https://reference.langchain.com/python/langgraph/mcp/",
    "cloud/reference/sdk/python_sdk_ref.md": "https://reference.langchain.com/python/platform/python_sdk/",
    "reference/remote_graph.md": "https://reference.langchain.com/python/platform/remote_graph/",
    # additional exclude-search entries from mkdocs.yml
    "additional-resources/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
    "cloud/concepts/cron_jobs.md": "https://docs.langchain.com/langsmith/cron-jobs",
    "cloud/concepts/data_storage_and_privacy.md": "https://docs.langchain.com/langsmith/data-storage-and-privacy",
    "cloud/concepts/webhooks.md": "https://docs.langchain.com/langsmith/use-webhooks",
    "cloud/deployment/cloud.md": "https://docs.langchain.com/langsmith/cloud",
    "cloud/deployment/custom_docker.md": "https://docs.langchain.com/langsmith/custom-docker",
    "cloud/deployment/egress.md": "https://docs.langchain.com/langsmith/env-var",
    "cloud/deployment/graph_rebuild.md": "https://docs.langchain.com/langsmith/graph-rebuild",
    "cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/hosting",
    "cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/hosting",
    "cloud/deployment/semantic_search.md": "https://docs.langchain.com/langsmith/semantic-search",
    "cloud/deployment/setup_javascript.md": "https://docs.langchain.com/langsmith/setup-javascript",
    "cloud/deployment/setup_pyproject.md": "https://docs.langchain.com/langsmith/setup-pyproject",
    "cloud/deployment/setup.md": "https://docs.langchain.com/langsmith/setup-app-requirements-txt",
    "cloud/deployment/standalone_container.md": "https://docs.langchain.com/langsmith/docker",
    "cloud/how-tos/add-human-in-the-loop.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
    "cloud/how-tos/background_run.md": "https://docs.langchain.com/langsmith/background-run",
    "cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langsmith/observability",
    "cloud/how-tos/configurable_headers.md": "https://docs.langchain.com/langsmith/configurable-headers",
    "cloud/how-tos/configuration_cloud.md": "https://docs.langchain.com/langsmith/configuration-cloud",
    "cloud/how-tos/cron_jobs.md": "https://docs.langchain.com/langsmith/cron-jobs",
    "cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langsmith/use-studio",
    "cloud/how-tos/enqueue_concurrent.md": "https://docs.langchain.com/langsmith/enqueue-concurrent",
    "cloud/how-tos/generative_ui_react.md": "https://docs.langchain.com/langsmith/generative-ui-react",
    "cloud/how-tos/human_in_the_loop_time_travel.md": "https://docs.langchain.com/langsmith/human-in-the-loop-time-travel",
    "cloud/how-tos/interrupt_concurrent.md": "https://docs.langchain.com/langsmith/interrupt-concurrent",
    "cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langsmith/use-studio",
    "cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langsmith/use-studio",
    "cloud/how-tos/reject_concurrent.md": "https://docs.langchain.com/langsmith/reject-concurrent",
    "cloud/how-tos/rollback_concurrent.md": "https://docs.langchain.com/langsmith/rollback-concurrent",
    "cloud/how-tos/same-thread.md": "https://docs.langchain.com/langsmith/same-thread",
    "cloud/how-tos/stateless_runs.md": "https://docs.langchain.com/langsmith/stateless-runs",
    "cloud/how-tos/streaming.md": "https://docs.langchain.com/langsmith/streaming",
    "cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langsmith/use-studio",
    "cloud/how-tos/studio/quick_start.md": "https://docs.langchain.com/langsmith/quick-start-studio",
    "cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langsmith/observability",
    "cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langsmith/use-threads",
    "cloud/how-tos/use_stream_react.md": "https://docs.langchain.com/langsmith/use-stream-react",
    "cloud/how-tos/use_threads.md": "https://docs.langchain.com/langsmith/use-threads",
    "cloud/how-tos/webhooks.md": "https://docs.langchain.com/langsmith/use-webhooks",
    "cloud/quick_start.md": "https://docs.langchain.com/langsmith/deployment-quickstart",
    "cloud/reference/api/api_ref_control_plane.md": "https://docs.langchain.com/langsmith/api-ref-control-plane",
    "cloud/reference/api/api_ref.md": "https://docs.langchain.com/langsmith/server-api-ref",
    "cloud/reference/cli.md": "https://docs.langchain.com/langsmith/cli",
    "cloud/reference/env_var.md": "https://docs.langchain.com/langsmith/env-var",
    "cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langsmith/langgraph-server-changelog",
    "cloud/reference/sdk/js_ts_sdk_ref.md": "https://reference.langchain.com/javascript/modules/langsmith.html",
    "concepts/application_structure.md": "https://docs.langchain.com/langsmith/application-structure",
    "concepts/assistants.md": "https://docs.langchain.com/langsmith/assistants",
    "concepts/auth.md": "https://docs.langchain.com/langsmith/auth",
    "concepts/deployment_options.md": "https://docs.langchain.com/langsmith/deployments",
    "concepts/double_texting.md": "https://docs.langchain.com/langsmith/double-texting",
    "concepts/faq.md": "https://docs.langchain.com/langsmith/faq",
    "concepts/langgraph_cli.md": "https://docs.langchain.com/langsmith/cli",
    "concepts/langgraph_cloud.md": "https://docs.langchain.com/langsmith/cloud",
    "concepts/langgraph_components.md": "https://docs.langchain.com/langsmith/components",
    "concepts/langgraph_control_plane.md": "https://docs.langchain.com/langsmith/control-plane",
    "concepts/langgraph_data_plane.md": "https://docs.langchain.com/langsmith/data-plane",
    "concepts/langgraph_platform.md": "https://docs.langchain.com/langsmith/home",
    "concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/hosting",
    "concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/hosting",
    "concepts/langgraph_server.md": "https://docs.langchain.com/langsmith/langgraph-server",
    "concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langsmith/docker",
    "concepts/langgraph_studio.md": "https://docs.langchain.com/langsmith/studio",
    "concepts/plans.md": "https://docs.langchain.com/langsmith/home",
    "concepts/scalability_and_resilience.md": "https://docs.langchain.com/langsmith/scalability-and-resilience",
    "concepts/sdk.md": "https://docs.langchain.com/langsmith/sdk",
    "concepts/server-mcp.md": "https://docs.langchain.com/langsmith/server-mcp",
    "concepts/template_applications.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "concepts/why-langgraph.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "examples/index.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
    "guides/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
    "how-tos/auth/custom_auth.md": "https://docs.langchain.com/langsmith/custom-auth",
    "how-tos/auth/openapi_security.md": "https://docs.langchain.com/langsmith/openapi-security",
    "how-tos/autogen-integration.md": "https://docs.langchain.com/langsmith/autogen-integration",
    "how-tos/http/custom_lifespan.md": "https://docs.langchain.com/langsmith/custom-lifespan",
    "how-tos/http/custom_middleware.md": "https://docs.langchain.com/langsmith/custom-middleware",
    "how-tos/http/custom_routes.md": "https://docs.langchain.com/langsmith/custom-routes",
    "how-tos/ttl/configure_ttl.md": "https://docs.langchain.com/langsmith/configure-ttl",
    "how-tos/use-remote-graph.md": "https://docs.langchain.com/langsmith/use-remote-graph",
    "index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "snippets/chat_model_tabs.md": "https://docs.langchain.com/oss/python/langchain/overview",
    "troubleshooting/errors/GRAPH_RECURSION_LIMIT.md": "https://docs.langchain.com/oss/python/langgraph/GRAPH_RECURSION_LIMIT",
    "troubleshooting/errors/index.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
    "troubleshooting/errors/INVALID_CHAT_HISTORY.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CHAT_HISTORY",
    "troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CONCURRENT_GRAPH_UPDATE",
    "troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_GRAPH_NODE_RETURN_VALUE",
    "troubleshooting/errors/INVALID_LICENSE.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
    "troubleshooting/errors/MULTIPLE_SUBGRAPHS.md": "https://docs.langchain.com/oss/python/langgraph/MULTIPLE_SUBGRAPHS",
    "troubleshooting/studio.md": "https://docs.langchain.com/langsmith/troubleshooting-studio",
    "tutorials/auth/add_auth_server.md": "https://docs.langchain.com/langsmith/add-auth-server",
    "tutorials/auth/getting_started.md": "https://docs.langchain.com/langsmith/auth",
    "tutorials/auth/resource_auth.md": "https://docs.langchain.com/langsmith/resource-auth",
    "agents/agents.md": "https://docs.langchain.com/oss/python/langchain/agents",
    "concepts/why-langgraph.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "tutorials/langsmith/local-server.md": "https://docs.langchain.com/oss/python/langgraph/local-server",
    "tutorials/workflows.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    "concepts/agentic_concepts.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    "guides/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
    "agents/overview.md": "https://docs.langchain.com/oss/python/langchain/agents",
    "concepts/agentic_concepts.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    "agents/run_agents.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
    "concepts/low_level.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
    "how-tos/graph-api.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
    "concepts/functional_api.md": "https://docs.langchain.com/oss/python/langgraph/functional-api",
    "how-tos/use-functional-api.md": "https://docs.langchain.com/oss/python/langgraph/functional-api",
    "concepts/pregel.md": "https://docs.langchain.com/oss/python/langgraph/pregel",
    "concepts/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
    "how-tos/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
    "concepts/persistence.md": "https://docs.langchain.com/oss/python/langgraph/persistence",
    "concepts/durable_execution.md": "https://docs.langchain.com/oss/python/langgraph/durable-execution",
    "concepts/memory.md": "https://docs.langchain.com/oss/python/langgraph/memory",
    "how-tos/memory/add-memory.md": "https://docs.langchain.com/oss/python/langgraph/add-memory",
    "agents/context.md": "https://docs.langchain.com/oss/python/langgraph/add-memory",
    "agents/models.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "concepts/tools.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    "how-tos/tool-calling.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    "concepts/human_in_the_loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
    "how-tos/human_in_the_loop/add-human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
    "concepts/time-travel.md": "https://docs.langchain.com/oss/python/langgraph/persistence",
    "how-tos/human_in_the_loop/time-travel.md": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",
    "concepts/subgraphs.md": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
    "how-tos/subgraph.md": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
    "concepts/multi_agent.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
    "agents/multi-agent.md": "https://docs.langchain.com/oss/python/langchain/multi-agent",
    "how-tos/multi_agent.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
    "concepts/mcp.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "agents/mcp.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "concepts/tracing.md": "https://docs.langchain.com/oss/python/langgraph/observability",
    "how-tos/enable-tracing.md": "https://docs.langchain.com/oss/python/langgraph/observability",
    "agents/evals.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "examples/index.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
    "concepts/template_applications.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "tutorials/rag/langgraph_agentic_rag.md": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
    "tutorials/multi_agent/agent_supervisor.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    "tutorials/sql/sql-agent.md": "https://docs.langchain.com/oss/python/langgraph/sql-agent",
    "agents/ui.md": "https://docs.langchain.com/oss/python/langgraph/ui",
    "how-tos/run-id-langsmith.md": "https://docs.langchain.com/oss/python/langgraph/observability",
    "troubleshooting/errors/index.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
    "troubleshooting/errors/GRAPH_RECURSION_LIMIT.md": "https://docs.langchain.com/oss/python/langgraph/GRAPH_RECURSION_LIMIT",
    "troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CONCURRENT_GRAPH_UPDATE",
    "troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_GRAPH_NODE_RETURN_VALUE",
    "troubleshooting/errors/MULTIPLE_SUBGRAPHS.md": "https://docs.langchain.com/oss/python/langgraph/MULTIPLE_SUBGRAPHS",
    "troubleshooting/errors/INVALID_CHAT_HISTORY.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CHAT_HISTORY",
    "troubleshooting/errors/INVALID_LICENSE.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
    "adopters.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
    "concepts/faq.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "agents/prebuilt.md": "https://docs.langchain.com/oss/python/langchain/agents",
 }
@@ -560,10 +788,16 @@ def on_post_page(html: str, page: Page, config: MkDocsConfig) -> str:
 # Create HTML files for redirects after site dir has been built
 def on_post_build(config):
    use_directory_urls = config.get("use_directory_urls")
    site_dir = config["site_dir"]
    # Track which paths have explicit redirects
    redirected_paths = set()
    # Process explicit redirects from REDIRECT_MAP
    for page_old, page_new in REDIRECT_MAP.items():
        # Convert .ipynb to .md for path calculation
        page_old = page_old.replace(".ipynb", ".md")
-        
+
        # Calculate the HTML path for the old page (whether it exists or not)
        if use_directory_urls:
            # With directory URLs: /path/to/page/ becomes /path/to/page/index.html
@@ -577,15 +811,18 @@ def on_post_build(config):
                old_html_path = page_old[:-3] + ".html"
            else:
                old_html_path = page_old + ".html"
-        
+
        # Track this path as redirected
        redirected_paths.add(old_html_path)
        if isinstance(page_new, str) and page_new.startswith("http"):
            # Handle external redirects
-            _write_html(config["site_dir"], old_html_path, page_new)
+            _write_html(site_dir, old_html_path, page_new)
        else:
            # Handle internal redirects
            page_new = page_new.replace(".ipynb", ".md")
            page_new_before_hash, hash, suffix = page_new.partition("#")
-            
+
            # Try to get the new path using File class, but fallback to manual calculation
            try:
                new_html_path = File(page_new_before_hash, "", "", True).url
@@ -607,5 +844,46 @@ def on_post_build(config):
                    else:
                        new_html_path = page_new_before_hash + ".html"
                new_html_path += hash + suffix
-            
+
-            _write_html(config["site_dir"], old_html_path, new_html_path)
+            _write_html(site_dir, old_html_path, new_html_path)
    # Create root index.html redirect
    root_redirect_html = """<!doctype html>
 <html lang="en">
 <head>
    <meta charset="utf-8">
    <title>Redirecting to LangGraph Documentation</title>
    <link rel="canonical" href="https://docs.langchain.com/oss/python/langgraph/overview">
    <meta name="robots" content="noindex">
    <script>var anchor=window.location.hash.substr(1);location.href="https://docs.langchain.com/oss/python/langgraph/overview"+(anchor?"#"+anchor:"")</script>
    <meta http-equiv="refresh" content="0; url=https://docs.langchain.com/oss/python/langgraph/overview">
 </head>
 <body>
 <h1>Documentation has moved</h1>
 <p>The LangGraph documentation has moved to <a href="https://docs.langchain.com/oss/python/langgraph/overview">docs.langchain.com</a>.</p>
 <p>Redirecting you now...</p>
 </body>
 </html>
 """
    root_index_path = os.path.join(site_dir, "index.html")
    with open(root_index_path, "w", encoding="utf-8") as f:
        f.write(root_redirect_html)
    # Create server-side catch-all redirect file for Netlify/Cloudflare Pages
    # This handles any pages not explicitly mapped in REDIRECT_MAP
    # Note: This won't work on GitHub Pages, but kept for potential future use
    redirects_content = """# Netlify/Cloudflare Pages redirect rules
 # Specific redirects are handled by individual HTML redirect pages
 # This is the catch-all for any unmapped pages
 # Exclude reference docs from catch-all
 /reference/*  200
 # Catch-all: redirect any page not explicitly mapped
 /*  https://docs.langchain.com/oss/python/langgraph/overview  301
 """
    redirects_path = os.path.join(site_dir, "_redirects")
    with open(redirects_path, "w", encoding="utf-8") as f:
        f.write(redirects_content)
@@ -20,16 +20,19 @@ class Package(TypedDict):
    description: str
    """A brief description of what the package does."""
 class ResolvedPackage(Package):
    weekly_downloads: int | None
    """The weekly download count of the package."""
    language: str
    """The language of the package. (either 'python' or 'js')"""
 HERE = pathlib.Path(__file__).parent
 PACKAGES_FILE = HERE / "packages.yml"
 PACKAGES = yaml.safe_load(PACKAGES_FILE.read_text())["packages"]
 def _get_pypi_downloads(package: Package) -> int:
    """Retrieve the weekly download count for a package from PyPIStats."""
@@ -72,7 +75,8 @@ def _get_pypi_downloads(package: Package) -> int:
        return sum(entry["downloads"] for entry in sorted_data[:7])
    else:
        return None
-    
+
 def _get_npm_downloads(package: Package) -> int:
    """Retrieve the weekly download count for a package on the npm registry."""
@@ -82,14 +86,18 @@ def _get_npm_downloads(package: Package) -> int:
        npm_response = requests.get(npm_url)
        npm_response.raise_for_status()
    except requests.exceptions.HTTPError:
-        raise AssertionError(f"Package {package['name']} does not exist on npm registry")
+        raise AssertionError(
            f"Package {package['name']} does not exist on npm registry"
        )
    npm_data = npm_response.json()
    # Retrieve the first publish date using the 'created' timestamp from the 'time' field.
    created_str = npm_data.get("time", {}).get("created")
    if created_str is None:
-        raise AssertionError(f"Package {package['name']} has no creation time in registry data")
+        raise AssertionError(
            f"Package {package['name']} has no creation time in registry data"
        )
    # Remove the trailing 'Z' if present and parse the ISO format timestamp
    first_publish_date = datetime.fromisoformat(created_str.rstrip("Z"))
@@ -103,7 +111,10 @@ def _get_npm_downloads(package: Package) -> int:
    else:
        return None
-def _get_weekly_downloads(packages: dict[str, list[Package]], fake: bool) -> list[ResolvedPackage]:
+
 def _get_weekly_downloads(
    packages: dict[str, list[Package]], fake: bool
 ) -> list[ResolvedPackage]:
    """Retrieve the weekly download count for a dictionary of python or js packages."""
    resolved_packages: list[ResolvedPackage] = []
@@ -131,7 +142,7 @@ def _get_weekly_downloads(packages: dict[str, list[Package]], fake: bool) -> lis
                num_downloads = _get_npm_downloads(package)
            else:
                num_downloads = None
-            
+
            resolved_packages.append(
                {
                    "name": package["name"],
@@ -145,12 +156,13 @@ def _get_weekly_downloads(packages: dict[str, list[Package]], fake: bool) -> lis
    return resolved_packages
 def main(output_file: str, fake: bool) -> None:
    """Main function to generate package download information.
    Args:
        output_file: Path to the output YAML file.
-        fake: If True, use fake download counts for testing purposes.
+        fake: If `True`, use fake download counts for testing purposes.
    """
    resolved_packages: list[ResolvedPackage] = _get_weekly_downloads(PACKAGES, fake)
@@ -33,7 +33,7 @@ LangGraph provides three ways to manage context, which combines the mutability a
 **Static runtime context** represents immutable data like user metadata, tools, and database connections that are passed to an application at the start of a run via the `context` argument to `invoke`/`stream`. This data does not change during execution.
-!!! version-added "New in LangGraph v0.6: `context` replaces `config['configurable']`"
+!!! version-added "Added in version 0.6.0: `context` replaces `config['configurable']`"
    Runtime context is now passed to the `context` argument of `invoke`/`stream`,
    which replaces the previous pattern of passing application configuration to `config['configurable']`.
@@ -90,7 +90,7 @@ graph.invoke( # (1)!
    from langgraph.runtime import Runtime
    # highlight-next-line
-    def node(state: State, config: Runtime[ContextSchema]):
+    def node(state: State, runtime: Runtime[ContextSchema]):
        user_name = runtime.context.user_name
        ...
    ```
@@ -211,7 +211,7 @@ output = agent.invoke(
 print(output["messages"][-1].text())
 ```
-!!! version-added "New in LangGraph v0.6"
+!!! version-added "Added in version 0.6.0"
 :::
@@ -351,11 +351,13 @@ If your desired LLM isn't officially supported by LangChain, consider these opti
 :::python
 1. **Implement a custom LangChain chat model**: Create a model conforming to the [LangChain chat model interface](https://python.langchain.com/docs/how_to/custom_chat_model/). This enables full compatibility with LangGraph's agents and workflows but requires understanding of the LangChain framework.
   :::
 :::js
 1. **Implement a custom LangChain chat model**: Create a model conforming to the [LangChain chat model interface](https://js.langchain.com/docs/how_to/custom_chat/). This enables full compatibility with LangGraph's agents and workflows but requires understanding of the LangChain framework.
   :::
 2. **Direct invocation with custom streaming**: Use your model directly by [adding custom streaming logic](../how-tos/streaming.md#use-with-any-llm) with `StreamWriter`.
@@ -371,6 +373,7 @@ If your desired LLM isn't officially supported by LangChain, consider these opti
 - [Force model to call a specific tool](https://python.langchain.com/docs/how_to/tool_choice/)
 - [All chat model how-to guides](https://python.langchain.com/docs/how_to/#chat-models)
 - [Chat model integrations](https://python.langchain.com/docs/integrations/chat/)
  :::
 :::js
@@ -381,4 +384,5 @@ If your desired LLM isn't officially supported by LangChain, consider these opti
 - [Force model to call a specific tool](https://js.langchain.com/docs/how_to/tool_choice/)
 - [All chat model how-to guides](https://js.langchain.com/docs/how_to/#chat-models)
 - [Chat model integrations](https://js.langchain.com/docs/integrations/chat/)
  :::
@@ -1,7 +1,7 @@
 {
  "openapi": "3.1.0",
  "info": {
-    "title": "LangGraph Platform",
+    "title": "LangSmith Deployment",
    "version": "0.1.0"
  },
  "tags": [
@@ -21,12 +21,16 @@ To leverage durable execution in LangGraph, you need to:
 1. Enable [persistence](./persistence.md) in your workflow by specifying a [checkpointer](./persistence.md#checkpointer-libraries) that will save workflow progress.
 2. Specify a [thread identifier](./persistence.md#threads) when executing a workflow. This will track the execution history for a particular instance of the workflow.
-:::python 
+:::python
 3. Wrap any non-deterministic operations (e.g., random number generation) or operations with side effects (e.g., file writes, API calls) inside @[tasks][task] to ensure that when a workflow is resumed, these operations are not repeated for the particular run, and instead their results are retrieved from the persistence layer. For more information, see [Determinism and Consistent Replay](#determinism-and-consistent-replay).
 :::
-:::js 
+:::js
 3. Wrap any non-deterministic operations (e.g., random number generation) or operations with side effects (e.g., file writes, API calls) inside @[tasks][task] to ensure that when a workflow is resumed, these operations are not repeated for the particular run, and instead their results are retrieved from the persistence layer. For more information, see [Determinism and Consistent Replay](#determinism-and-consistent-replay).
 :::
 ## Determinism and Consistent Replay
@@ -61,7 +65,7 @@ LangGraph supports three durability modes that allow you to balance performance
 A higher durability mode add more overhead to the workflow execution.
-!!! version-added "Added in v0.6.0"
+!!! version-added "Added in version 0.6.0"
    Use the `durability` parameter instead of `checkpoint_during` (deprecated in v0.6.0) for persistence policy management:
@@ -73,14 +77,16 @@ A higher durability mode add more overhead to the workflow execution.
    * `checkpoint_during=True` -> `durability="async"`
    * `checkpoint_during=False` -> `durability="exit"`
 ### `"exit"`
 Changes are persisted only when graph execution completes (either successfully or with an error). This provides the best performance for long-running graphs but means intermediate state is not saved, so you cannot recover from mid-execution failures or interrupt the graph execution.
 ### `"async"`
 Changes are persisted asynchronously while the next step executes. This provides good performance and durability, but there's a small risk that checkpoints might not be written if the process crashes during execution.
 ### `"sync"`
 Changes are persisted synchronously before the next step starts. This ensures that every checkpoint is written before continuing execution, providing high durability at the cost of some performance overhead.
 You can specify the durability mode when calling any graph execution method:
@@ -310,12 +316,14 @@ Once you have enabled durable execution in your workflow, you can resume executi
 - **Pausing and Resuming Workflows:** Use the @[interrupt][interrupt] function to pause a workflow at specific points and the @[Command] primitive to resume it with updated state. See [**Human-in-the-Loop**](./human_in_the_loop.md) for more details.
 - **Recovering from Failures:** Automatically resume workflows from the last successful checkpoint after an exception (e.g., LLM provider outage). This involves executing the workflow with the same thread identifier by providing it with a `None` as the input value (see this [example](../how-tos/use-functional-api.md#resuming-after-an-error) with the functional API).
  :::
 :::js
 - **Pausing and Resuming Workflows:** Use the @[interrupt][interrupt] function to pause a workflow at specific points and the @[Command] primitive to resume it with updated state. See [**Human-in-the-Loop**](./human_in_the_loop.md) for more details.
 - **Recovering from Failures:** Automatically resume workflows from the last successful checkpoint after an exception (e.g., LLM provider outage). This involves executing the workflow with the same thread identifier by providing it with a `null` as the input value (see this [example](../how-tos/use-functional-api.md#resuming-after-an-error) with the functional API).
  :::
 ## Starting Points for Resuming Workflows
@@ -326,6 +334,7 @@ Once you have enabled durable execution in your workflow, you can resume executi
 - If you're making a subgraph call inside a node, the starting point will be the **parent** node that called the subgraph that was halted.
  Inside the subgraph, the starting point will be the specific [**node**](./low_level.md#nodes) where execution stopped.
 - If you're using the Functional API, the starting point is the beginning of the [**entrypoint**](./functional_api.md#entrypoint) where execution stopped.
  :::
 :::js
@@ -334,4 +343,5 @@ Once you have enabled durable execution in your workflow, you can resume executi
 - If you're making a subgraph call inside a node, the starting point will be the **parent** node that called the subgraph that was halted.
  Inside the subgraph, the starting point will be the specific [**node**](./low_level.md#nodes) where execution stopped.
 - If you're using the Functional API, the starting point is the beginning of the [**entrypoint**](./functional_api.md#entrypoint) where execution stopped.
  :::
@@ -134,7 +134,7 @@ def update_instructions(state: State, store: BaseStore):
    namespace = ("instructions",)
    current_instructions = store.search(namespace)[0]
    # Memory logic
-    prompt = prompt_template.format(instructions=instructions.value["instructions"], conversation=state["messages"])
+    prompt = prompt_template.format(instructions=current_instructions.value["instructions"], conversation=state["messages"])
    output = llm.invoke(prompt)
    new_instructions = output['new_instructions']
    store.put(("agent_instructions",), "agent_a", {"instructions": new_instructions})
@@ -278,4 +278,4 @@ const items = await store.search(
 ```
 :::
-For more information about the memory store, see the [Persistence](persistence.md#memory-store) guide.
+For more information about the memory store, see the [Persistence](persistence.md#memory-store) guide.
@@ -897,5 +897,5 @@ There are two high-level approaches to achieve that:
 An agent might need to have a different state schema from the rest of the agents. For example, a search agent might only need to keep track of queries and retrieved documents. There are two ways to achieve this in LangGraph:
- Define [subgraph](./subgraphs.md) agents with a separate state schema. If there are no shared state keys (channels) between the subgraph and the parent graph, it's important to [add input / output transformations](../how-tos/subgraph.ipynb#different-state-schemas) so that the parent graph knows how to communicate with the subgraphs.
+- Define [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.
@@ -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);
 ```
-:::
+:::
@@ -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'}
@@ -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"
 :::
@@ -2,4 +2,4 @@
 ::: langgraph.cache.base
 ::: langgraph.cache.memory
-::: langgraph.cache.sqlite
+::: langgraph.cache.sqlite
@@ -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!
@@ -294,9 +294,9 @@ Now that you have a LangGraph app running locally, take your journey further by
 :::python
 - [Python SDK Reference](../../cloud/reference/sdk/python_sdk_ref.md): Explore the Python SDK API Reference.
-  :::
+:::
 :::js
 - [JS/TS SDK Reference](../../cloud/reference/sdk/js_ts_sdk_ref.md): Explore the JS/TS SDK API Reference.
-  :::
+:::
@@ -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"]
@@ -149,6 +149,67 @@ plugins:
        - tutorials/auth/add_auth_server.md
        - tutorials/auth/getting_started.md
        - tutorials/auth/resource_auth.md
        - agents/agents.md
        - concepts/why-langgraph.md
        - tutorials/get-started/1-build-basic-chatbot.md
        - tutorials/get-started/2-add-tools.md
        - tutorials/get-started/3-add-memory.md
        - tutorials/get-started/4-human-in-the-loop.md
        - tutorials/get-started/5-customize-state.md
        - tutorials/get-started/6-time-travel.md
        - tutorials/langgraph-platform/local-server.md
        - tutorials/workflows.md
        - concepts/agentic_concepts.md
        - guides/index.md
        - agents/overview.md
        - agents/run_agents.md
        - concepts/low_level.md
        - how-tos/graph-api.md
        - concepts/functional_api.md
        - how-tos/use-functional-api.md
        - concepts/pregel.md
        - concepts/streaming.md
        - how-tos/streaming.md
        - concepts/persistence.md
        - concepts/durable_execution.md
        - concepts/memory.md
        - how-tos/memory/add-memory.md
        - agents/context.md
        - agents/models.md
        - concepts/tools.md
        - how-tos/tool-calling.md
        - concepts/human_in_the_loop.md
        - how-tos/human_in_the_loop/add-human-in-the-loop.md
        - concepts/time-travel.md
        - how-tos/human_in_the_loop/time-travel.md
        - concepts/subgraphs.md
        - how-tos/subgraph.md
        - concepts/multi_agent.md
        - agents/multi-agent.md
        - how-tos/multi_agent.md
        - concepts/mcp.md
        - agents/mcp.md
        - concepts/tracing.md
        - how-tos/enable-tracing.md
        - agents/evals.md
        - examples/index.md
        - concepts/template_applications.md  # TODO: make tutorial
        - tutorials/rag/langgraph_agentic_rag.md
        - tutorials/multi_agent/agent_supervisor.md
        - tutorials/sql/sql-agent.md
        - agents/ui.md
        - how-tos/run-id-langsmith.md
        - troubleshooting/errors/index.md
        - troubleshooting/errors/GRAPH_RECURSION_LIMIT.md
        - troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE.md
        - troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE.md
        - troubleshooting/errors/MULTIPLE_SUBGRAPHS.md
        - troubleshooting/errors/INVALID_CHAT_HISTORY.md
        - troubleshooting/errors/INVALID_LICENSE.md
        - adopters.md
        - concepts/faq.md
        - agents/prebuilt.md # NOTE: prebuilt.md is auto-generated by `make build-prebuilt`
  - tags
  - include-markdown
  - mkdocstrings:
@@ -186,75 +247,6 @@ plugins:
                - "!^_"
 nav:
  - Get started:
    - index.md
    - Quickstarts:
      - Start with a prebuilt agent: agents/agents.md
      - Build a custom workflow:
          -  concepts/why-langgraph.md
          -  1. Build a basic chatbot: tutorials/get-started/1-build-basic-chatbot.md
          -  2. Add tools: tutorials/get-started/2-add-tools.md
          -  3. Add memory: tutorials/get-started/3-add-memory.md
          -  4. Add human-in-the-loop: tutorials/get-started/4-human-in-the-loop.md
          -  5. Customize state: tutorials/get-started/5-customize-state.md
          -  6. Time travel: tutorials/get-started/6-time-travel.md
      - Run a local server: tutorials/langgraph-platform/local-server.md
    - General concepts:
      - Workflows & agents: tutorials/workflows.md
      - Agent architectures: concepts/agentic_concepts.md
  - Guides:
    - guides/index.md
    - Agent development:
      - Overview: agents/overview.md
      - Run an agent: agents/run_agents.md
    - LangGraph APIs:
      - Graph API:
          - Overview: concepts/low_level.md
          - Use the Graph API: how-tos/graph-api.md
      - Functional API:
          - Overview: concepts/functional_api.md
          - Use the Functional API: how-tos/use-functional-api.md
      - Runtime: concepts/pregel.md
    - Core capabilities:
      - Streaming:
          - Overview: concepts/streaming.md
          - Stream outputs: how-tos/streaming.md
      - Persistence:
          - Overview: concepts/persistence.md
      - Durable execution:
          - Overview: concepts/durable_execution.md
      - Memory:
          - Overview: concepts/memory.md
          - Add memory: how-tos/memory/add-memory.md
      - Context:
          - Add context: agents/context.md
      - Models:
          - Configure model: agents/models.md
      - Tools:
          - Overview: concepts/tools.md
          - Call tools: how-tos/tool-calling.md
      - Human-in-the-loop:
          - Overview: concepts/human_in_the_loop.md
          - Add human intervention: how-tos/human_in_the_loop/add-human-in-the-loop.md
      - Time travel:
          - Overview: concepts/time-travel.md
          - Use time travel: how-tos/human_in_the_loop/time-travel.md
      - Subgraphs:
          - Overview: concepts/subgraphs.md
          - Use subgraphs: how-tos/subgraph.md
      - Multi-agent:
          - Overview: concepts/multi_agent.md
          - Prebuilt implementation: agents/multi-agent.md
          - Custom implementation: how-tos/multi_agent.md
      - MCP:
          - Overview: concepts/mcp.md
          - Use MCP: agents/mcp.md
      - Tracing:
          - Overview: concepts/tracing.md
          - Enable tracing: how-tos/enable-tracing.md
          - Evaluate performance: agents/evals.md
  - Reference:
    - reference/index.md
    - LangGraph:
@@ -278,35 +270,7 @@ nav:
    - LangGraph Platform:
      - SDK (Python): cloud/reference/sdk/python_sdk_ref.md
      - SDK (JS/TS): https://langchain-ai.github.io/langgraphjs/reference/modules/sdk.html
-      - RemoteGraph: reference/remote_graph.md
+      - RemoteGraph: reference/remote_graph.md 
  - Examples:
    - examples/index.md
    - Template applications: concepts/template_applications.md  # TODO: make tutorial
    - Agentic RAG: tutorials/rag/langgraph_agentic_rag.md
    - Agent Supervisor: tutorials/multi_agent/agent_supervisor.md
    - SQL agent: tutorials/sql/sql-agent.md
    - Prebuilt chat UI: agents/ui.md
    - Graph runs in LangSmith: how-tos/run-id-langsmith.md
  - Additional resources:
    - additional-resources/index.md
    - agents/prebuilt.md # NOTE: prebuilt.md is auto-generated by `make build-prebuilt`
    - LangGraph Academy course: https://academy.langchain.com/courses/intro-to-langgraph
    - Case studies: adopters.md
    - concepts/faq.md
    - llms.txt: llms-txt-overview.md
    - LangChain Forum: https://forum.langchain.com/
    - Troubleshooting:
        - Errors:
          - troubleshooting/errors/index.md
          - troubleshooting/errors/GRAPH_RECURSION_LIMIT.md
          - troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE.md
          - troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE.md
          - troubleshooting/errors/MULTIPLE_SUBGRAPHS.md
          - troubleshooting/errors/INVALID_CHAT_HISTORY.md
          - troubleshooting/errors/INVALID_LICENSE.md
 markdown_extensions:
  - abbr
@@ -291,7 +291,7 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
    }
    .md-banner {
-      background-color: #CFC9FA;
+      background-color: #FFAE42;
      color: #000000;
    }
@@ -360,5 +360,5 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
 {% endblock %}
 {% block announce %}
-Our new LangChain Academy Course Deep Research with LangGraph is now live! <a href="https://academy.langchain.com/courses/deep-research-with-langgraph/?utm_medium=internal&utm_source=docs&utm_campaign=q3-2025_deep-research-course_co" target="_blank">Enroll for free</a>.
+These docs will be deprecated and removed with the release of LangGraph v1.0 in October 2025. <a href="https://docs.langchain.com/oss/python/langgraph/overview" target="_blank">Visit the v1.0 alpha docs</a>
 {% endblock %}
@@ -7,14 +7,14 @@ name = "langgraph-docs"
 version = "0.0.1"
 description = "LangGraph docs"
 authors = []
-requires-python = "~=3.11"
+requires-python = ">=3.11.0,<4.0.0"
 readme = "README.md"
 license = "MIT"
 dependencies = [
    "aiohappyeyeballs==2.4.3",
-    "hub>=3.0.1,<4",
+    "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]
@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.11, <4"
 resolution-markers = [
    "python_full_version >= '3.13' and platform_python_implementation != 'PyPy'",
@@ -2337,7 +2337,7 @@ wheels = [
 [[package]]
 name = "langgraph"
-version = "0.6.2"
+version = "0.6.7"
 source = { editable = "../libs/langgraph" }
 dependencies = [
    { name = "langchain-core" },
@@ -2380,6 +2380,7 @@ dev = [
    { name = "pytest-repeat" },
    { name = "pytest-watcher" },
    { name = "pytest-xdist", extras = ["psutil"] },
    { name = "redis" },
    { name = "ruff" },
    { name = "syrupy" },
    { name = "types-requests" },
@@ -2413,6 +2414,7 @@ dev = [
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
    { name = "pytest-watcher" },
    { name = "redis" },
    { name = "ruff" },
 ]
@@ -2643,7 +2645,7 @@ test = [
 [[package]]
 name = "langgraph-prebuilt"
-version = "0.6.2"
+version = "0.6.4"
 source = { editable = "../libs/prebuilt" }
 dependencies = [
    { name = "langchain-core" },
@@ -2674,7 +2676,6 @@ dev = [
 [[package]]
 name = "langgraph-sdk"
 version = "0.2.0"
 source = { editable = "../libs/sdk-py" }
 dependencies = [
    { name = "httpx" },
@@ -5,7 +5,7 @@
   "id": "18526f23",
   "metadata": {},
   "source": [
-    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/persistence_postgres.ipynb"
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/memory/add-memory.md"
   ]
  }
 ],
@@ -707,7 +707,9 @@
    "    \"\"\"\n",
    "    Find all tool calls in the messages returned\n",
    "    \"\"\"\n",
-    "    tool_calls = [tc['name'] for m in messages['messages'] for tc in getattr(m, 'tool_calls', [])]\n",
+    "    tool_calls = [\n",
    "        tc[\"name\"] for m in messages[\"messages\"] for tc in getattr(m, \"tool_calls\", [])\n",
    "    ]\n",
    "    return tool_calls\n",
    "\n",
    "\n",
@@ -7,11 +7,6 @@ from contextlib import contextmanager
 from typing import Any
 from langchain_core.runnables import RunnableConfig
 from psycopg import Capabilities, Connection, Cursor, Pipeline
 from psycopg.rows import DictRow, dict_row
 from psycopg.types.json import Jsonb
 from psycopg_pool import ConnectionPool
 from langgraph.checkpoint.base import (
    WRITES_IDX_MAP,
    ChannelVersions,
@@ -19,12 +14,17 @@ from langgraph.checkpoint.base import (
    CheckpointMetadata,
    CheckpointTuple,
    get_checkpoint_id,
-    get_checkpoint_metadata,
+    get_serializable_checkpoint_metadata,
 )
 from langgraph.checkpoint.serde.base import SerializerProtocol
 from psycopg import Capabilities, Connection, Cursor, Pipeline
 from psycopg.rows import DictRow, dict_row
 from psycopg.types.json import Jsonb
 from psycopg_pool import ConnectionPool
 from langgraph.checkpoint.postgres import _internal
 from langgraph.checkpoint.postgres.base import BasePostgresSaver
 from langgraph.checkpoint.postgres.shallow import ShallowPostgresSaver
 from langgraph.checkpoint.serde.base import SerializerProtocol
 Conn = _internal.Conn  # For backward compatibility
@@ -94,6 +94,7 @@ class PostgresSaver(BasePostgresSaver):
            for v, migration in zip(
                range(version + 1, len(self.MIGRATIONS)),
                self.MIGRATIONS[version + 1 :],
                strict=False,
            ):
                cur.execute(migration)
                cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
@@ -115,12 +116,12 @@ class PostgresSaver(BasePostgresSaver):
        Args:
            config: The config to use for listing the checkpoints.
-            filter: Additional filtering criteria for metadata. Defaults to None.
+            filter: Additional filtering criteria for metadata.
-            before: If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None.
+            before: If provided, only checkpoints before the specified checkpoint ID are returned.
-            limit: The maximum number of checkpoints to return. Defaults to None.
+            limit: The maximum number of checkpoints to return.
        Yields:
-            Iterator[CheckpointTuple]: An iterator of checkpoint tuples.
+            An iterator of checkpoint tuples.
        Examples:
            >>> from langgraph.checkpoint.postgres import PostgresSaver
@@ -182,7 +183,7 @@ class PostgresSaver(BasePostgresSaver):
        """Get a checkpoint tuple from the database.
        This method retrieves a checkpoint tuple from the Postgres database based on the
-        provided config. If the config contains a "checkpoint_id" key, the checkpoint with
+        provided config. If the config contains a `checkpoint_id` key, the checkpoint with
        the matching thread ID and timestamp is retrieved. Otherwise, the latest checkpoint
        for the given thread ID is retrieved.
@@ -190,7 +191,7 @@ class PostgresSaver(BasePostgresSaver):
            config: The config to use for retrieving the checkpoint.
        Returns:
-            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+            The retrieved checkpoint tuple, or None if no matching checkpoint was found.
        Examples:
@@ -325,7 +326,7 @@ 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 +451,7 @@ class PostgresSaver(BasePostgresSaver):
            {
                **value["checkpoint"],
                "channel_values": {
-                    **value["checkpoint"].get("channel_values"),
+                    **(value["checkpoint"].get("channel_values") or {}),
                    **self._load_blobs(value["channel_values"]),
                },
            },
@@ -2,13 +2,12 @@
 from collections.abc import AsyncIterator
 from contextlib import asynccontextmanager
 from typing import Union
 from psycopg import AsyncConnection
 from psycopg.rows import DictRow
 from psycopg_pool import AsyncConnectionPool
-Conn = Union[AsyncConnection[DictRow], AsyncConnectionPool[AsyncConnection[DictRow]]]
+Conn = AsyncConnection[DictRow] | AsyncConnectionPool[AsyncConnection[DictRow]]
@asynccontextmanager
@@ -2,13 +2,12 @@
 from collections.abc import Iterator
 from contextlib import contextmanager
 from typing import Union
 from psycopg import Connection
 from psycopg.rows import DictRow
 from psycopg_pool import ConnectionPool
-Conn = Union[Connection[DictRow], ConnectionPool[Connection[DictRow]]]
+Conn = Connection[DictRow] | ConnectionPool[Connection[DictRow]]
@contextmanager
@@ -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
@@ -99,6 +99,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
            for v, migration in zip(
                range(version + 1, len(self.MIGRATIONS)),
                self.MIGRATIONS[version + 1 :],
                strict=False,
            ):
                await cur.execute(migration)
                await cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
@@ -121,11 +122,11 @@ class AsyncPostgresSaver(BasePostgresSaver):
        Args:
            config: Base configuration for filtering checkpoints.
            filter: Additional filtering criteria for metadata.
-            before: If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None.
+            before: If provided, only checkpoints before the specified checkpoint ID are returned.
            limit: Maximum number of checkpoints to return.
        Yields:
-            AsyncIterator[CheckpointTuple]: An asynchronous iterator of matching checkpoint tuples.
+            An asynchronous iterator of matching checkpoint tuples.
        """
        where, args = self._search_where(config, filter, before)
        query = self.SELECT_SQL + where + " ORDER BY checkpoint_id DESC"
@@ -169,7 +170,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
        """Get a checkpoint tuple from the database asynchronously.
        This method retrieves a checkpoint tuple from the Postgres database based on the
-        provided config. If the config contains a "checkpoint_id" key, the checkpoint with
+        provided config. If the config contains a `checkpoint_id` key, the checkpoint with
        the matching thread ID and "checkpoint_id" is retrieved. Otherwise, the latest checkpoint
        for the given thread ID is retrieved.
@@ -177,7 +178,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
            config: The config to use for retrieving the checkpoint.
        Returns:
-            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+            The retrieved checkpoint tuple, or None if no matching checkpoint was found.
        """
        thread_id = config["configurable"]["thread_id"]
        checkpoint_id = get_checkpoint_id(config)
@@ -283,7 +284,7 @@ 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 +410,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
            {
                **value["checkpoint"],
                "channel_values": {
-                    **value["checkpoint"].get("channel_values"),
+                    **(value["checkpoint"].get("channel_values") or {}),
                    **self._load_blobs(value["channel_values"]),
                },
            },
@@ -444,11 +445,11 @@ class AsyncPostgresSaver(BasePostgresSaver):
        Args:
            config: Base configuration for filtering checkpoints.
            filter: Additional filtering criteria for metadata.
-            before: If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None.
+            before: If provided, only checkpoints before the specified checkpoint ID are returned.
            limit: Maximum number of checkpoints to return.
        Yields:
-            Iterator[CheckpointTuple]: An iterator of matching checkpoint tuples.
+            An iterator of matching checkpoint tuples.
        """
        try:
            # check if we are in the main thread, only bg threads can block
@@ -476,7 +477,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
        """Get a checkpoint tuple from the database.
        This method retrieves a checkpoint tuple from the Postgres database based on the
-        provided config. If the config contains a "checkpoint_id" key, the checkpoint with
+        provided config. If the config contains a `checkpoint_id` key, the checkpoint with
        the matching thread ID and "checkpoint_id" is retrieved. Otherwise, the latest checkpoint
        for the given thread ID is retrieved.
@@ -484,7 +485,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
            config: The config to use for retrieving the checkpoint.
        Returns:
-            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+            The retrieved checkpoint tuple, or None if no matching checkpoint was found.
        """
        try:
            # check if we are in the main thread, only bg threads can block
@@ -1,12 +1,12 @@
 from __future__ import annotations
 import random
 import warnings
 from collections.abc import Sequence
-from typing import Any, Optional, cast
+from importlib.metadata import version as get_version
 from typing import Any, cast
 from langchain_core.runnables import RunnableConfig
 from psycopg.types.json import Jsonb
 from langgraph.checkpoint.base import (
    WRITES_IDX_MAP,
    BaseCheckpointSaver,
@@ -14,8 +14,21 @@ 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]]
+MetadataInput = dict[str, Any] | None
 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.
@@ -3,9 +3,19 @@ import threading
 import warnings
 from collections.abc import AsyncIterator, Iterator, Sequence
 from contextlib import asynccontextmanager, contextmanager
-from typing import Any, Optional
+from typing import Any
 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.
@@ -151,7 +151,7 @@ def _dump_blobs(
    checkpoint_ns: str,
    values: dict[str, Any],
    versions: ChannelVersions,
-) -> list[tuple[str, str, str, str, Optional[bytes]]]:
+) -> list[tuple[str, str, str, str, bytes | None]]:
    if not versions:
        return []
@@ -186,8 +186,8 @@ class ShallowPostgresSaver(BasePostgresSaver):
    def __init__(
        self,
        conn: _internal.Conn,
-        pipe: Optional[Pipeline] = None,
+        pipe: Pipeline | None = None,
-        serde: Optional[SerializerProtocol] = None,
+        serde: SerializerProtocol | None = None,
    ) -> None:
        warnings.warn(
            "ShallowPostgresSaver is deprecated as of version 2.0.20 and will be removed in 3.0.0. "
@@ -249,6 +249,7 @@ class ShallowPostgresSaver(BasePostgresSaver):
            for v, migration in zip(
                range(version + 1, len(self.MIGRATIONS)),
                self.MIGRATIONS[version + 1 :],
                strict=False,
            ):
                cur.execute(migration)
                cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
@@ -257,11 +258,11 @@ class ShallowPostgresSaver(BasePostgresSaver):
    def list(
        self,
-        config: Optional[RunnableConfig],
+        config: RunnableConfig | None,
        *,
-        filter: Optional[dict[str, Any]] = None,
+        filter: dict[str, Any] | None = None,
-        before: Optional[RunnableConfig] = None,
+        before: RunnableConfig | None = None,
-        limit: Optional[int] = None,
+        limit: int | None = None,
    ) -> Iterator[CheckpointTuple]:
        """List checkpoints from the database.
@@ -299,7 +300,7 @@ class ShallowPostgresSaver(BasePostgresSaver):
                    pending_writes=self._load_writes(value["pending_writes"]),
                )
-    def get_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
+    def get_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
        """Get a checkpoint tuple from the database.
        This method retrieves a checkpoint tuple from the Postgres database based on the
@@ -309,7 +310,7 @@ class ShallowPostgresSaver(BasePostgresSaver):
            config: The config to use for retrieving the checkpoint.
        Returns:
-            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+            The retrieved checkpoint tuple, or None if no matching checkpoint was found.
        Examples:
@@ -441,7 +442,7 @@ 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
@@ -542,8 +543,8 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
    def __init__(
        self,
        conn: _ainternal.Conn,
-        pipe: Optional[AsyncPipeline] = None,
+        pipe: AsyncPipeline | None = None,
-        serde: Optional[SerializerProtocol] = None,
+        serde: SerializerProtocol | None = None,
    ) -> None:
        warnings.warn(
            "AsyncShallowPostgresSaver is deprecated as of version 2.0.20 and will be removed in 3.0.0. "
@@ -570,7 +571,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
        conn_string: str,
        *,
        pipeline: bool = False,
-        serde: Optional[SerializerProtocol] = None,
+        serde: SerializerProtocol | None = None,
    ) -> AsyncIterator["AsyncShallowPostgresSaver"]:
        """Create a new AsyncShallowPostgresSaver instance from a connection string.
@@ -610,6 +611,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
            for v, migration in zip(
                range(version + 1, len(self.MIGRATIONS)),
                self.MIGRATIONS[version + 1 :],
                strict=False,
            ):
                await cur.execute(migration)
                await cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
@@ -618,11 +620,11 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
    async def alist(
        self,
-        config: Optional[RunnableConfig],
+        config: RunnableConfig | None,
        *,
-        filter: Optional[dict[str, Any]] = None,
+        filter: dict[str, Any] | None = None,
-        before: Optional[RunnableConfig] = None,
+        before: RunnableConfig | None = None,
-        limit: Optional[int] = None,
+        limit: int | None = None,
    ) -> AsyncIterator[CheckpointTuple]:
        """List checkpoints from the database asynchronously.
@@ -662,7 +664,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
                    ),
                )
-    async def aget_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
+    async def aget_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
        """Get a checkpoint tuple from the database asynchronously.
        This method retrieves a checkpoint tuple from the Postgres database based on the
@@ -672,7 +674,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
            config: The config to use for retrieving the checkpoint.
        Returns:
-            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+            The retrieved checkpoint tuple, or None if no matching checkpoint was found.
        """
        thread_id = config["configurable"]["thread_id"]
        checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
@@ -774,7 +776,7 @@ 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
@@ -861,11 +863,11 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
    def list(
        self,
-        config: Optional[RunnableConfig],
+        config: RunnableConfig | None,
        *,
-        filter: Optional[dict[str, Any]] = None,
+        filter: dict[str, Any] | None = None,
-        before: Optional[RunnableConfig] = None,
+        before: RunnableConfig | None = None,
-        limit: Optional[int] = None,
+        limit: int | None = None,
    ) -> Iterator[CheckpointTuple]:
        """List checkpoints from the database.
@@ -883,7 +885,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
            except StopAsyncIteration:
                break
-    def get_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
+    def get_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
        """Get a checkpoint tuple from the database.
        This method retrieves a checkpoint tuple from the Postgres database based on the
@@ -893,7 +895,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
            config: The config to use for retrieving the checkpoint.
        Returns:
-            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+            The retrieved checkpoint tuple, or None if no matching checkpoint was found.
        """
        try:
            # check if we are in the main thread, only bg threads can block
@@ -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"]
@@ -2,17 +2,12 @@ from __future__ import annotations
 import asyncio
 import logging
-from collections.abc import AsyncIterator, Iterable, Sequence
+from collections.abc import AsyncIterator, Callable, Iterable, Sequence
 from contextlib import asynccontextmanager
 from types import TracebackType
-from typing import Any, Callable, cast
+from typing import Any, 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,
@@ -339,7 +339,7 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
        Args:
            timeout: Maximum time to wait for the task to stop, in seconds.
-                If None, wait indefinitely.
+                If `None`, wait indefinitely.
        Returns:
            bool: True if the task was successfully stopped or wasn't running,
@@ -465,7 +465,9 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
                    query,
                    [
                        p
-                        for (ns, k, pathname, _), vector in zip(txt_params, vectors)
+                        for (ns, k, pathname, _), vector in zip(
                            txt_params, vectors, strict=False
                        )
                        for p in (ns, k, pathname, vector)
                    ],
                )
@@ -486,13 +488,13 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
            vectors = await self.embeddings.aembed_documents(
                [query for _, query in embedding_requests]
            )
-            for (idx, _), vector in zip(embedding_requests, vectors):
+            for (idx, _), vector in zip(embedding_requests, vectors, strict=False):
                _paramslist = queries[idx][1]
                for i in range(len(_paramslist)):
                    if _paramslist[i] is PLACEHOLDER:
                        _paramslist[i] = vector
-        for (idx, _), (query, params) in zip(search_ops, queries):
+        for (idx, _), (query, params) in zip(search_ops, queries, strict=False):
            await cur.execute(query, params)
            rows = cast(list[Row], await cur.fetchall())
            items = [
@@ -510,7 +512,7 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
        cur: AsyncCursor[DictRow],
    ) -> None:
        queries = self._get_batch_list_namespaces_queries(list_ops)
-        for (query, params), (idx, _) in zip(queries, list_ops):
+        for (query, params), (idx, _) in zip(queries, list_ops, strict=False):
            await cur.execute(query, params)
            rows = cast(list[dict], await cur.fetchall())
            namespaces = [_decode_ns_bytes(row["truncated_prefix"]) for row in rows]
@@ -6,30 +6,20 @@ import json
 import logging
 import threading
 from collections import defaultdict
-from collections.abc import Iterable, Iterator, Sequence
+from collections.abc import Callable, Iterable, Iterator, Sequence
 from contextlib import contextmanager
 from datetime import datetime
 from typing import (
    TYPE_CHECKING,
    Any,
    Callable,
    Generic,
    Literal,
    NamedTuple,
    TypeVar,
    Union,
    cast,
 )
 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 +36,14 @@ 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
@@ -141,7 +139,7 @@ CREATE INDEX CONCURRENTLY IF NOT EXISTS store_vectors_embedding_idx ON store_vec
 ]
-C = TypeVar("C", bound=Union[_pg_internal.Conn, _ainternal.Conn])
+C = TypeVar("C", bound=_pg_internal.Conn | _ainternal.Conn)
 class PoolConfig(TypedDict, total=False):
@@ -255,7 +253,7 @@ class BasePostgresStore(Generic[C]):
        results = []
        for namespace, items in namespace_groups.items():
-            _, keys = zip(*items)
+            _, keys = zip(*items, strict=False)
            this_refresh_ttls = refresh_ttls[namespace]
            query = """
@@ -868,7 +866,7 @@ class PostgresStore(BaseStore, BasePostgresStore[_pg_internal.Conn]):
        Args:
            timeout: Maximum time to wait for the thread to stop, in seconds.
-                If None, wait indefinitely.
+                If `None`, wait indefinitely.
        Returns:
            bool: True if the thread was successfully stopped or wasn't running,
@@ -1014,7 +1012,9 @@ class PostgresStore(BaseStore, BasePostgresStore[_pg_internal.Conn]):
                    query,
                    [
                        p
-                        for (ns, k, pathname, _), vector in zip(txt_params, vectors)
+                        for (ns, k, pathname, _), vector in zip(
                            txt_params, vectors, strict=False
                        )
                        for p in (ns, k, pathname, vector)
                    ],
                )
@@ -1035,13 +1035,15 @@ class PostgresStore(BaseStore, BasePostgresStore[_pg_internal.Conn]):
            embeddings = self.embeddings.embed_documents(
                [query for _, query in embedding_requests]
            )
-            for (idx, _), embedding in zip(embedding_requests, embeddings):
+            for (idx, _), embedding in zip(
                embedding_requests, embeddings, strict=False
            ):
                _paramslist = queries[idx][1]
                for i in range(len(_paramslist)):
                    if _paramslist[i] is PLACEHOLDER:
                        _paramslist[i] = embedding
-        for (idx, _), (query, params) in zip(search_ops, queries):
+        for (idx, _), (query, params) in zip(search_ops, queries, strict=False):
            cur.execute(query, params)
            rows = cast(list[Row], cur.fetchall())
            results[idx] = [
@@ -1058,7 +1060,7 @@ class PostgresStore(BaseStore, BasePostgresStore[_pg_internal.Conn]):
        cur: Cursor[DictRow],
    ) -> None:
        for (query, params), (idx, _) in zip(
-            self._get_batch_list_namespaces_queries(list_ops), list_ops
+            self._get_batch_list_namespaces_queries(list_ops), list_ops, strict=False
        ):
            cur.execute(query, params)
            results[idx] = [_decode_ns_bytes(row["truncated_prefix"]) for row in cur]
@@ -4,15 +4,15 @@ build-backend = "hatchling.build"
 [project]
 name = "langgraph-checkpoint-postgres"
-version = "2.0.23"
+version = "3.0.0"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 authors = []
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
 dependencies = [
-  "langgraph-checkpoint>=2.0.21,<3.0.0",
+  "langgraph-checkpoint>=2.1.2,<4.0.0",
  "orjson>=3.10.1",
  "psycopg>=3.2.0",
  "psycopg-pool>=3.2.0",
@@ -22,18 +22,24 @@ dependencies = [
 Repository = "https://www.github.com/langchain-ai/langgraph"
 [dependency-groups]
-dev = [
+test = [
  "ruff",
  "codespell",
  "pytest",
  "anyio",
  "pytest-asyncio",
  "pytest-mock",
  "mypy",
  "psycopg[binary]",
  "langgraph-checkpoint",
  "pytest-watcher",
 ]
 lint = [
  "ruff",
  "codespell",
  "mypy",
 ]
 dev = [
  {include-group = "test"},
  {include-group = "lint"},
 ]
 [tool.uv]
 default-groups = ['dev']
@@ -55,8 +61,10 @@ lint.select = [
  "UP", # pyupgrade
  "B",  # flake8-bugbear
  "I",  # isort
  "UP", # pyupgrade
 ]
 lint.ignore = ["E501", "B008"]
 target-version = "py310"
 [tool.mypy]
 # https://mypy.readthedocs.io/en/stable/config_file.html
@@ -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"] == {}
@@ -3,7 +3,6 @@ from __future__ import annotations
 import asyncio
 import itertools
 import sys
 import uuid
 from collections.abc import AsyncIterator
 from concurrent.futures import ThreadPoolExecutor
@@ -12,8 +11,6 @@ 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 +18,8 @@ from langgraph.store.base import (
    PutOp,
    SearchOp,
 )
 from psycopg import AsyncConnection
 from langgraph.store.postgres import AsyncPostgresStore
 from tests.conftest import (
    DEFAULT_URI,
@@ -34,9 +33,6 @@ TTL_MINUTES = TTL_SECONDS / 60
@pytest.fixture(scope="function", params=["default", "pipe", "pool"])
 async def store(request) -> AsyncIterator[AsyncPostgresStore]:
    if sys.version_info < (3, 10):
        pytest.skip("Async Postgres tests require Python 3.10+")
    database = f"test_{uuid.uuid4().hex[:16]}"
    uri_parts = DEFAULT_URI.split("/")
    uri_base = "/".join(uri_parts[:-1])
@@ -358,8 +354,6 @@ async def _create_vector_store(
    text_fields: list[str] | None = None,
 ) -> AsyncIterator[AsyncPostgresStore]:
    """Create a store with vector search enabled."""
    if sys.version_info < (3, 10):
        pytest.skip("Async Postgres tests require Python 3.10+")
    database = f"test_{uuid.uuid4().hex[:16]}"
    uri_parts = DEFAULT_URI.split("/")
@@ -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,
@@ -754,7 +754,7 @@ def _cosine_similarity(X: list[float], Y: list[list[float]]) -> list[float]:
    similarities = []
    for y in Y:
-        dot_product = sum(a * b for a, b in zip(X, y))
+        dot_product = sum(a * b for a, b in zip(X, y, strict=False))
        norm1 = sum(a * a for a in X) ** 0.5
        norm2 = sum(a * a for a in y) ** 0.5
        similarity = dot_product / (norm1 * norm2) if norm1 > 0 and norm2 > 0 else 0.0
@@ -771,7 +771,7 @@ def _inner_product(X: list[float], Y: list[list[float]]) -> list[float]:
    similarities = []
    for y in Y:
-        similarity = sum(a * b for a, b in zip(X, y))
+        similarity = sum(a * b for a, b in zip(X, y, strict=False))
        similarities.append(similarity)
    return similarities
@@ -785,7 +785,7 @@ def _neg_l2_distance(X: list[float], Y: list[list[float]]) -> list[float]:
    similarities = []
    for y in Y:
-        similarity = sum((a - b) ** 2 for a, b in zip(X, y)) ** 0.5
+        similarity = sum((a - b) ** 2 for a, b in zip(X, y, strict=False)) ** 0.5
        similarities.append(-similarity)
    return similarities
@@ -861,3 +861,41 @@ def test_store_ttl(store):
    # Now has been (TTL_SECONDS-2)*2 > TTL_SECONDS + TTL_SECONDS/2
    res = store.search(ns, query="bar", refresh_ttl=False)
    assert len(res) == 0
@pytest.mark.parametrize(
    "vector_type,distance_type",
    [
        ("vector", "cosine"),
        ("vector", "inner_product"),
        ("halfvec", "cosine"),
        ("halfvec", "inner_product"),
    ],
 )
 def test_non_ascii(
    request: Any,
    fake_embeddings: CharacterEmbeddings,
    vector_type: str,
    distance_type: str,
 ) -> None:
    """Test support for non-ascii characters"""
    with _create_vector_store(vector_type, distance_type, fake_embeddings) as store:
        store.put(("user_123", "memories"), "1", {"text": "这是中文"})  # Chinese
        store.put(
            ("user_123", "memories"), "2", {"text": "これは日本語です"}
        )  # Japanese
        store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"})  # Korean
        store.put(("user_123", "memories"), "4", {"text": "Это русский"})  # Russian
        store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"})  # Hindi
        result1 = store.search(("user_123", "memories"), query="这是中文")
        result2 = store.search(("user_123", "memories"), query="これは日本語です")
        result3 = store.search(("user_123", "memories"), query="이건 한국어야")
        result4 = store.search(("user_123", "memories"), query="Это русский")
        result5 = store.search(("user_123", "memories"), query="यह रूसी है")
        assert result1[0].key == "1"
        assert result2[0].key == "2"
        assert result3[0].key == "3"
        assert result4[0].key == "4"
        assert result5[0].key == "5"
@@ -7,10 +7,6 @@ from uuid import uuid4
 import pytest
 from langchain_core.runnables import RunnableConfig
 from psycopg import Connection
 from psycopg.rows import dict_row
 from psycopg_pool import ConnectionPool
 from langgraph.checkpoint.base import (
    EXCLUDED_METADATA_KEYS,
    Checkpoint,
@@ -18,8 +14,12 @@ from langgraph.checkpoint.base import (
    create_checkpoint,
    empty_checkpoint,
 )
 from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver
 from langgraph.checkpoint.serde.types import TASKS
 from psycopg import Connection
 from psycopg.rows import dict_row
 from psycopg_pool import ConnectionPool
 from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver
 from tests.conftest import DEFAULT_POSTGRES_URI
@@ -169,13 +169,11 @@ def test_data():
    metadata_1: CheckpointMetadata = {
        "source": "input",
        "step": 2,
        "writes": {},
        "score": 1,
    }
    metadata_2: CheckpointMetadata = {
        "source": "loop",
        "step": 1,
        "writes": {"foo": "bar"},
        "score": None,
    }
    metadata_3: CheckpointMetadata = {}
@@ -202,7 +200,6 @@ def test_combined_metadata(saver_name: str, test_data) -> None:
        metadata: CheckpointMetadata = {
            "source": "loop",
            "step": 1,
            "writes": {"foo": "bar"},
            "score": None,
        }
        saver.put(config, chkpnt, metadata, {})
@@ -228,7 +225,6 @@ def test_search(saver_name: str, test_data) -> None:
        query_1 = {"source": "input"}  # search by 1 key
        query_2 = {
            "step": 1,
            "writes": {"foo": "bar"},
        }  # search by multiple keys
        query_3: dict[str, Any] = {}  # search by no keys, return all checkpoints
        query_4 = {"source": "update", "step": 1}  # no match
@@ -332,3 +328,33 @@ def test_pending_sends_migration(saver_name: str) -> None:
            TASKS: ["send-1", "send-2", "send-3"]
        }
        assert TASKS in search_results[0].checkpoint["channel_versions"]
@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
 def test_get_checkpoint_no_channel_values(
    monkeypatch, saver_name: str, test_data
 ) -> None:
    """Backwards compatibility test that verifies a checkpoint with no channel_values key can be retrieved without throwing an error."""
    with _saver(saver_name) as saver:
        config = {
            "configurable": {
                "thread_id": "thread-2",
                "checkpoint_ns": "",
                "__super_private_key": "super_private_value",
            },
        }
        chkpnt: Checkpoint = create_checkpoint(empty_checkpoint(), {}, 1)
        saver.put(config, chkpnt, {}, {})
        load_checkpoint_tuple = saver._load_checkpoint_tuple
        def patched_load_checkpoint_tuple(value):
            value["checkpoint"].pop("channel_values", None)
            return load_checkpoint_tuple(value)
        monkeypatch.setattr(
            saver, "_load_checkpoint_tuple", patched_load_checkpoint_tuple
        )
        checkpoint = saver.get_tuple(config)
        assert checkpoint.checkpoint["channel_values"] == {}
@@ -1,5 +1,6 @@
 from __future__ import annotations
 import json
 import random
 import sqlite3
 import threading
@@ -8,7 +9,6 @@ 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 +21,7 @@ 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 = (
@@ -184,7 +185,7 @@ class SqliteSaver(BaseCheckpointSaver[str]):
        """Get a checkpoint tuple from the database.
        This method retrieves a checkpoint tuple from the SQLite database based on the
-        provided config. If the config contains a "checkpoint_id" key, the checkpoint with
+        provided config. If the config contains a `checkpoint_id` key, the checkpoint with
        the matching thread ID and checkpoint ID is retrieved. Otherwise, the latest checkpoint
        for the given thread ID is retrieved.
@@ -192,7 +193,7 @@ class SqliteSaver(BaseCheckpointSaver[str]):
            config: The config to use for retrieving the checkpoint.
        Returns:
-            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+            The retrieved checkpoint tuple, or None if no matching checkpoint was found.
        Examples:
@@ -265,9 +266,7 @@ class SqliteSaver(BaseCheckpointSaver[str]):
                    self.serde.loads_typed((type, checkpoint)),
                    cast(
                        CheckpointMetadata,
-                        self.jsonplus_serde.loads(metadata)
+                        json.loads(metadata) if metadata is not None else {},
                        if metadata is not None
                        else {},
                    ),
                    (
                        {
@@ -301,12 +300,12 @@ class SqliteSaver(BaseCheckpointSaver[str]):
        Args:
            config: The config to use for listing the checkpoints.
-            filter: Additional filtering criteria for metadata. Defaults to None.
+            filter: Additional filtering criteria for metadata.
-            before: If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None.
+            before: If provided, only checkpoints before the specified checkpoint ID are returned.
-            limit: The maximum number of checkpoints to return. Defaults to None.
+            limit: The maximum number of checkpoints to return.
        Yields:
-            Iterator[CheckpointTuple]: An iterator of checkpoint tuples.
+            An iterator of checkpoint tuples.
        Examples:
            >>> from langgraph.checkpoint.sqlite import SqliteSaver
@@ -358,9 +357,7 @@ class SqliteSaver(BaseCheckpointSaver[str]):
                    self.serde.loads_typed((type, checkpoint)),
                    cast(
                        CheckpointMetadata,
-                        self.jsonplus_serde.loads(metadata)
+                        json.loads(metadata) if metadata is not None else {},
                        if metadata is not None
                        else {},
                    ),
                    (
                        {
@@ -413,9 +410,9 @@ class SqliteSaver(BaseCheckpointSaver[str]):
        thread_id = config["configurable"]["thread_id"]
        checkpoint_ns = config["configurable"]["checkpoint_ns"]
        type_, serialized_checkpoint = self.serde.dumps_typed(checkpoint)
-        serialized_metadata = self.jsonplus_serde.dumps(
+        serialized_metadata = json.dumps(
-            get_checkpoint_metadata(config, metadata)
+            get_checkpoint_metadata(config, metadata), ensure_ascii=False
-        )
+        ).encode("utf-8", "ignore")
        with self.cursor() as cur:
            cur.execute(
                "INSERT OR REPLACE INTO checkpoints (thread_id, checkpoint_ns, checkpoint_id, parent_checkpoint_id, type, checkpoint, metadata) VALUES (?, ?, ?, ?, ?, ?, ?)",
@@ -1,14 +1,14 @@
 from __future__ import annotations
 import asyncio
 import json
 import random
-from collections.abc import AsyncIterator, Iterator, Sequence
+from collections.abc import AsyncIterator, Callable, Iterator, Sequence
 from contextlib import asynccontextmanager
-from typing import Any, Callable, TypeVar, cast
+from typing import Any, TypeVar, cast
 import aiosqlite
 from langchain_core.runnables import RunnableConfig
 from langgraph.checkpoint.base import (
    WRITES_IDX_MAP,
    BaseCheckpointSaver,
@@ -21,6 +21,7 @@ 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)
@@ -139,7 +140,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
        """Get a checkpoint tuple from the database.
        This method retrieves a checkpoint tuple from the SQLite database based on the
-        provided config. If the config contains a "checkpoint_id" key, the checkpoint with
+        provided config. If the config contains a `checkpoint_id` key, the checkpoint with
        the matching thread ID and checkpoint ID is retrieved. Otherwise, the latest checkpoint
        for the given thread ID is retrieved.
@@ -147,7 +148,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
            config: The config to use for retrieving the checkpoint.
        Returns:
-            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+            The retrieved checkpoint tuple, or None if no matching checkpoint was found.
        """
        try:
            # check if we are in the main thread, only bg threads can block
@@ -181,11 +182,11 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
        Args:
            config: Base configuration for filtering checkpoints.
            filter: Additional filtering criteria for metadata.
-            before: If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None.
+            before: If provided, only checkpoints before the specified checkpoint ID are returned.
            limit: Maximum number of checkpoints to return.
        Yields:
-            Iterator[CheckpointTuple]: An iterator of matching checkpoint tuples.
+            An iterator of matching checkpoint tuples.
        """
        try:
            # check if we are in the main thread, only bg threads can block
@@ -316,7 +317,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
        """Get a checkpoint tuple from the database asynchronously.
        This method retrieves a checkpoint tuple from the SQLite database based on the
-        provided config. If the config contains a "checkpoint_id" key, the checkpoint with
+        provided config. If the config contains a `checkpoint_id` key, the checkpoint with
        the matching thread ID and checkpoint ID is retrieved. Otherwise, the latest checkpoint
        for the given thread ID is retrieved.
@@ -324,7 +325,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
            config: The config to use for retrieving the checkpoint.
        Returns:
-            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+            The retrieved checkpoint tuple, or None if no matching checkpoint was found.
        """
        await self.setup()
        checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
@@ -377,9 +378,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
                    self.serde.loads_typed((type, checkpoint)),
                    cast(
                        CheckpointMetadata,
-                        self.jsonplus_serde.loads(metadata)
+                        (json.loads(metadata) if metadata is not None else {}),
                        if metadata is not None
                        else {},
                    ),
                    (
                        {
@@ -414,11 +413,11 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
        Args:
            config: Base configuration for filtering checkpoints.
            filter: Additional filtering criteria for metadata.
-            before: If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None.
+            before: If provided, only checkpoints before the specified checkpoint ID are returned.
            limit: Maximum number of checkpoints to return.
        Yields:
-            AsyncIterator[CheckpointTuple]: An asynchronous iterator of matching checkpoint tuples.
+            An asynchronous iterator of matching checkpoint tuples.
        """
        await self.setup()
        where, params = search_where(config, filter, before)
@@ -457,9 +456,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
                    self.serde.loads_typed((type, checkpoint)),
                    cast(
                        CheckpointMetadata,
-                        self.jsonplus_serde.loads(metadata)
+                        (json.loads(metadata) if metadata is not None else {}),
                        if metadata is not None
                        else {},
                    ),
                    (
                        {
@@ -503,9 +500,9 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
        thread_id = config["configurable"]["thread_id"]
        checkpoint_ns = config["configurable"]["checkpoint_ns"]
        type_, serialized_checkpoint = self.serde.dumps_typed(checkpoint)
-        serialized_metadata = self.jsonplus_serde.dumps(
+        serialized_metadata = json.dumps(
-            get_checkpoint_metadata(config, metadata)
+            get_checkpoint_metadata(config, metadata), ensure_ascii=False
-        )
+        ).encode("utf-8", "ignore")
        async with (
            self.lock,
            self.conn.execute(
@@ -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
@@ -3,15 +3,14 @@ from __future__ import annotations
 import asyncio
 import logging
 from collections import defaultdict
-from collections.abc import AsyncIterator, Iterable, Sequence
+from collections.abc import AsyncIterator, Callable, Iterable, Sequence
 from contextlib import asynccontextmanager
 from types import TracebackType
-from typing import Any, Callable, cast
+from typing import Any, 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,
@@ -303,7 +303,7 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
        Args:
            timeout: Maximum time to wait for the task to stop, in seconds.
-                If None, wait indefinitely.
+                If `None`, wait indefinitely.
        Returns:
            bool: True if the task was successfully stopped or wasn't running,
@@ -484,7 +484,7 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
            # Convert vectors to SQLite-friendly format
            vector_params = []
-            for (ns, k, pathname, _), vector in zip(txt_params, vectors):
+            for (ns, k, pathname, _), vector in zip(txt_params, vectors, strict=False):
                vector_params.extend(
                    [ns, k, pathname, sqlite_vec.serialize_float32(vector)]
                )
@@ -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 +517,62 @@ 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(
-                _params_list: list = queries[idx][1]
+                embedding_requests, vectors, strict=False
-                for i, param in enumerate(_params_list):
+            ):
-                    if param is _PLACEHOLDER:
+                # Find the corresponding query in prepared_queries
-                        _params_list[i] = sqlite_vec.serialize_float32(embedding)
+                # The embed_req_idx is the original index in search_ops, which should map to prepared_queries
                if embed_req_idx < len(prepared_queries):
                    _params_list: list = prepared_queries[embed_req_idx][1]
                    for i, param in enumerate(_params_list):
                        if param is _PLACEHOLDER:
                            _params_list[i] = sqlite_vec.serialize_float32(embedding)
                else:
                    logger.warning(
                        f"Embedding request index {embed_req_idx} out of bounds for prepared_queries."
                    )
-        for (idx, _), (query, params) in zip(search_ops, queries):
+        for (original_op_idx, _), (query, params, needs_refresh) in zip(
            search_ops, prepared_queries, strict=False
        ):
            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 +586,10 @@ 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 +600,7 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
                    for row in rows
                ]
-            results[idx] = items
+            results[original_op_idx] = items
    async def _batch_list_namespaces_ops(
        self,
@@ -575,7 +616,7 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
            cur: Database cursor.
        """
        queries = self._get_batch_list_namespaces_queries(list_ops)
-        for (query, params), (idx, _) in zip(queries, list_ops):
+        for (query, params), (idx, _) in zip(queries, list_ops, strict=False):
            await cur.execute(query, params)
            rows = await cur.fetchall()
@@ -7,13 +7,12 @@ import re
 import sqlite3
 import threading
 from collections import defaultdict
-from collections.abc import Iterable, Iterator, Sequence
+from collections.abc import Callable, Iterable, Iterator, Sequence
 from contextlib import contextmanager
-from typing import Any, Callable, Literal, NamedTuple, cast
+from typing import Any, Literal, NamedTuple, cast
 import orjson
 import sqlite_vec  # type: ignore[import-untyped]
 from langgraph.store.base import (
    BaseStore,
    GetOp,
@@ -233,7 +232,7 @@ class BaseSqliteStore:
        results = []
        for namespace, items in namespace_groups.items():
-            _, keys = zip(*items)
+            _, keys = zip(*items, strict=False)
            this_refresh_ttls = refresh_ttls[namespace]
            refresh_ttl_any = any(this_refresh_ttls)
@@ -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
@@ -840,7 +829,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
        results = []
        for namespace, items in namespace_groups.items():
-            _, keys = zip(*items)
+            _, keys = zip(*items, strict=False)
            this_refresh_ttls = refresh_ttls[namespace]
            refresh_ttl_any = any(this_refresh_ttls)
@@ -1167,7 +1156,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
        Args:
            timeout: Maximum time to wait for the thread to stop, in seconds.
-                If None, wait indefinitely.
+                If `None`, wait indefinitely.
        Returns:
            bool: True if the thread was successfully stopped or wasn't running,
@@ -1315,7 +1304,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
            # Convert vectors to SQLite-friendly format
            vector_params = []
-            for (ns, k, pathname, _), vector in zip(txt_params, vectors):
+            for (ns, k, pathname, _), vector in zip(txt_params, vectors, strict=False):
                vector_params.extend(
                    [ns, k, pathname, sqlite_vec.serialize_float32(vector)]
                )
@@ -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 +1332,50 @@ class SqliteStore(BaseSqliteStore, BaseStore):
            )
            # Replace placeholders with actual embeddings
-            for (idx, _), embedding in zip(embedding_requests, embeddings):
+            for (embed_req_idx, _), embedding in zip(
-                _params_list: list = queries[idx][1]
+                embedding_requests, embeddings, strict=False
-                for i, param in enumerate(_params_list):
+            ):
-                    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, strict=False
        ):
            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 +1410,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
                    for row in rows
                ]
-            results[idx] = items
+            results[original_op_idx] = items
    def _batch_list_namespaces_ops(
        self,
@@ -1394,7 +1419,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
        cur: sqlite3.Cursor,
    ) -> None:
        queries = self._get_batch_list_namespaces_queries(list_ops)
-        for (query, params), (idx, _) in zip(queries, list_ops):
+        for (query, params), (idx, _) in zip(queries, list_ops, strict=False):
            cur.execute(query, params)
            results[idx] = [_decode_ns_text(row[0]) for row in cur.fetchall()]
@@ -4,15 +4,15 @@ build-backend = "hatchling.build"
 [project]
 name = "langgraph-checkpoint-sqlite"
-version = "2.0.11"
+version = "3.0.0"
 description = "Library with a SQLite implementation of LangGraph checkpoint saver."
 authors = []
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
 dependencies = [
-    "langgraph-checkpoint>=2.0.21,<3.0.0",
+    "langgraph-checkpoint>=3,<4.0.0",
    "aiosqlite>=0.20",
    "sqlite-vec>=0.1.6",
 ]
@@ -21,17 +21,23 @@ dependencies = [
 Repository = "https://www.github.com/langchain-ai/langgraph"
 [dependency-groups]
-dev = [
+test = [
  "ruff",
  "codespell",
  "pytest",
  "pytest-asyncio",
  "pytest-mock",
  "pytest-watcher",
  "mypy",
  "langgraph-checkpoint",
  "pytest-retry>=1.7.0",
 ]
 lint = [
  "ruff",
  "codespell",
  "mypy",
 ]
 dev = [
  {include-group = "test"},
  {include-group = "lint"},
 ]
 [tool.uv]
 default-groups = ['dev']
@@ -53,8 +59,10 @@ lint.select = [
  "UP", # pyupgrade
  "B",  # flake8-bugbear
  "I",  # isort
  "UP", # pyupgrade
 ]
 lint.ignore = ["E501", "B008"]
 target-version = "py310"
 [tool.pytest-watcher]
 now = true
@@ -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
@@ -5,10 +5,9 @@ import tempfile
 import uuid
 from collections.abc import AsyncIterator, Generator, Iterable
 from contextlib import asynccontextmanager
-from typing import Optional, Union, cast
+from typing import 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
@@ -51,7 +51,7 @@ def fake_embeddings() -> CharacterEmbeddings:
 async def create_vector_store(
    fake_embeddings: CharacterEmbeddings,
    conn_string: str = ":memory:",
-    text_fields: Optional[list[str]] = None,
+    text_fields: list[str] | None = None,
 ) -> AsyncIterator[AsyncSqliteStore]:
    """Create an AsyncSqliteStore with vector search capabilities."""
    index_config: SqliteIndexConfig = {
@@ -168,7 +168,7 @@ async def test_abatch_order(store: AsyncSqliteStore) -> None:
    ]
    results = await store.abatch(
-        cast(Iterable[Union[GetOp, PutOp, SearchOp, ListNamespacesOp]], ops)
+        cast(Iterable[GetOp | PutOp | SearchOp | ListNamespacesOp], ops)
    )
    assert len(results) == 5
    assert isinstance(results[0], Item)
@@ -193,7 +193,7 @@ async def test_abatch_order(store: AsyncSqliteStore) -> None:
    ]
    results_reordered = await store.abatch(
-        cast(Iterable[Union[GetOp, PutOp, SearchOp, ListNamespacesOp]], ops_reordered)
+        cast(Iterable[GetOp | PutOp | SearchOp | ListNamespacesOp], ops_reordered)
    )
    assert len(results_reordered) == 5
    assert isinstance(results_reordered[0], list)
@@ -681,7 +681,7 @@ async def test_search_items(
        fake_embeddings, text_fields=["key0", "key1", "key3"]
    ) as store:
        # Insert test data
-        for ns, item in zip(test_namespaces, test_items):
+        for ns, item in zip(test_namespaces, test_items, strict=False):
            key = f"item_{ns[-1]}"
            await store.aput(ns, key, item)
@@ -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
@@ -5,11 +5,10 @@ import tempfile
 import uuid
 from collections.abc import Generator, Iterable
 from contextlib import contextmanager
-from typing import Any, Literal, Optional, Union, cast
+from typing import Any, Literal, 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
@@ -110,7 +110,7 @@ VECTOR_TYPES = ["cosine"]  # SQLite only supports cosine similarity
@contextmanager
 def create_vector_store(
    fake_embeddings: CharacterEmbeddings,
-    text_fields: Optional[list[str]] = None,
+    text_fields: list[str] | None = None,
    distance_type: str = "cosine",
    conn_type: Literal["memory", "file"] = "memory",
 ) -> Generator[SqliteStore, None, None]:
@@ -153,7 +153,7 @@ def test_batch_order(store: SqliteStore) -> None:
    ]
    results = store.batch(
-        cast(Iterable[Union[GetOp, PutOp, SearchOp, ListNamespacesOp]], ops)
+        cast(Iterable[GetOp | PutOp | SearchOp | ListNamespacesOp], ops)
    )
    assert len(results) == 5
    assert isinstance(results[0], Item)
@@ -182,7 +182,7 @@ def test_batch_order(store: SqliteStore) -> None:
    ]
    results_reordered = store.batch(
-        cast(Iterable[Union[GetOp, PutOp, SearchOp, ListNamespacesOp]], ops_reordered)
+        cast(Iterable[GetOp | PutOp | SearchOp | ListNamespacesOp], ops_reordered)
    )
    assert len(results_reordered) == 5
    assert isinstance(results_reordered[0], list)
@@ -301,7 +301,7 @@ def test_batch_list_namespaces_ops(store: SqliteStore) -> None:
    ]
    results = store.batch(
-        cast(Iterable[Union[GetOp, PutOp, SearchOp, ListNamespacesOp]], ops)
+        cast(Iterable[GetOp | PutOp | SearchOp | ListNamespacesOp], ops)
    )
    assert len(results) == 3
@@ -778,7 +778,7 @@ def _cosine_similarity(X: list[float], Y: list[list[float]]) -> list[float]:
    similarities = []
    for y in Y:
-        dot_product = sum(a * b for a, b in zip(X, y))
+        dot_product = sum(a * b for a, b in zip(X, y, strict=False))
        norm1 = sum(a * a for a in X) ** 0.5
        norm2 = sum(a * a for a in y) ** 0.5
        similarity = dot_product / (norm1 * norm2) if norm1 > 0 and norm2 > 0 else 0.0
@@ -1011,7 +1011,7 @@ def test_search_items(
        fake_embeddings, text_fields=["key0", "key1", "key3"]
    ) as store:
        # Insert test data
-        for ns, item in zip(test_namespaces, test_items):
+        for ns, item in zip(test_namespaces, test_items, strict=False):
            key = f"item_{ns[-1]}"
            store.put(ns, key, item)
@@ -1067,3 +1067,31 @@ def test_sql_injection_vulnerability(store: SqliteStore) -> None:
    with pytest.raises(ValueError, match="Invalid filter key"):
        store.search(("docs",), filter={malicious_key: "dummy"})
@pytest.mark.parametrize("distance_type", VECTOR_TYPES)
 def test_non_ascii(
    fake_embeddings: CharacterEmbeddings,
    distance_type: str,
 ) -> None:
    """Test support for non-ascii characters"""
    with create_vector_store(fake_embeddings, distance_type=distance_type) as store:
        store.put(("user_123", "memories"), "1", {"text": "这是中文"})  # Chinese
        store.put(
            ("user_123", "memories"), "2", {"text": "これは日本語です"}
        )  # Japanese
        store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"})  # Korean
        store.put(("user_123", "memories"), "4", {"text": "Это русский"})  # Russian
        store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"})  # Hindi
        result1 = store.search(("user_123", "memories"), query="这是中文")
        result2 = store.search(("user_123", "memories"), query="これは日本語です")
        result3 = store.search(("user_123", "memories"), query="이건 한국어야")
        result4 = store.search(("user_123", "memories"), query="Это русский")
        result5 = store.search(("user_123", "memories"), query="यह रूसी है")
        assert result1[0].key == "1"
        assert result2[0].key == "2"
        assert result3[0].key == "3"
        assert result4[0].key == "4"
        assert result5[0].key == "5"
@@ -7,6 +7,7 @@ import time
 from collections.abc import Generator
 import pytest
 from langgraph.store.base import TTLConfig
 from langgraph.store.sqlite import SqliteStore
 from langgraph.store.sqlite.aio import AsyncSqliteStore
@@ -93,9 +94,13 @@ def test_ttl_sweeper(temp_db_file: str) -> None:
    ttl_seconds = 2
    ttl_minutes = ttl_seconds / 60
    ttl_config: TTLConfig = {
        "default_ttl": ttl_minutes,
        "sweep_interval_minutes": ttl_minutes / 2,
    }
    with SqliteStore.from_conn_string(
        temp_db_file,
-        ttl={"default_ttl": ttl_minutes, "sweep_interval_minutes": ttl_minutes / 2},
+        ttl=ttl_config,
    ) as store:
        store.setup()
@@ -298,9 +303,14 @@ async def test_async_ttl_sweeper(temp_db_file: str) -> None:
    ttl_seconds = 2
    ttl_minutes = ttl_seconds / 60
    ttl_config: TTLConfig = {
        "default_ttl": ttl_minutes,
        "sweep_interval_minutes": ttl_minutes / 2,
    }
    async with AsyncSqliteStore.from_conn_string(
        temp_db_file,
-        ttl={"default_ttl": ttl_minutes, "sweep_interval_minutes": ttl_minutes / 2},
+        ttl=ttl_config,
    ) as store:
        await store.setup()
@@ -353,3 +363,67 @@ async def test_async_search_with_ttl(temp_db_file: str) -> None:
        # Search after expiration
        results = await store.asearch(("test",), filter={"value": "apple"})
        assert len(results) == 0
@pytest.mark.asyncio
@pytest.mark.flaky(retries=3)
 async def test_async_asearch_refresh_ttl(temp_db_file: str) -> None:
    """Test TTL refresh on asearch with async API."""
    ttl_seconds = 4.0  # Increased TTL for less sensitivity to timing
    ttl_minutes = ttl_seconds / 60.0
    async with AsyncSqliteStore.from_conn_string(
        temp_db_file, ttl={"default_ttl": ttl_minutes, "refresh_on_read": True}
    ) as store:
        await store.setup()
        namespace = ("docs", "user1")
        # t=0: items put, expire at t=4.0s
        await store.aput(namespace, "item1", {"text": "content1", "id": 1})
        await store.aput(namespace, "item2", {"text": "content2", "id": 2})
        # t=3.0s: (after sleep ttl_seconds * 0.75 = 3s)
        await asyncio.sleep(ttl_seconds * 0.75)
        # Perform asearch with refresh_ttl=True for item1.
        # item1's TTL should be refreshed. New expiry: t=3.0s + 4.0s = t=7.0s.
        # item2's TTL is not affected. Expires at t=4.0s.
        searched_items = await store.asearch(
            namespace, filter={"id": 1}, refresh_ttl=True
        )
        assert len(searched_items) == 1
        assert searched_items[0].key == "item1"
        # t=5.0s: (after sleep ttl_seconds * 0.5 = 2s more. Total elapsed: 3s + 2s = 5s)
        await asyncio.sleep(ttl_seconds * 0.5)
        # At this point:
        # - item1 (refreshed by asearch) should expire at t=7.0s. Should be ALIVE.
        # - item2 (original TTL) should have expired at t=4.0s. Should be GONE after sweep.
        await store.sweep_ttl()
        # Check item1 (should exist due to asearch refresh)
        item1_check1 = await store.aget(namespace, "item1", refresh_ttl=False)
        assert item1_check1 is not None, (
            "Item1 should exist after asearch refresh and first sweep"
        )
        assert item1_check1.value["text"] == "content1"
        # Check item2 (should be gone)
        item2_check1 = await store.aget(namespace, "item2", refresh_ttl=False)
        assert item2_check1 is None, (
            "Item2 should be gone after its original TTL expired"
        )
        # t=7.5s: (after sleep ttl_seconds * 0.625 = 2.5s more. Total elapsed: 5s + 2.5s = 7.5s)
        await asyncio.sleep(ttl_seconds * 0.625)
        # At this point:
        # - item1 (refreshed by asearch, expired at t=7.0s) should be GONE after sweep.
        await store.sweep_ttl()
        # Check item1 again (should be gone now)
        item1_final_check = await store.aget(namespace, "item1", refresh_ttl=False)
        assert item1_final_check is None, (
            "Item1 should be gone after its refreshed TTL expired"
        )
@@ -8,7 +8,6 @@ from typing import (  # noqa: UP035
    NamedTuple,
    TypedDict,
    TypeVar,
    Union,
 )
 from langchain_core.runnables import RunnableConfig
@@ -35,17 +34,17 @@ class CheckpointMetadata(TypedDict, total=False):
    source: Literal["input", "loop", "update", "fork"]
    """The source of the checkpoint.
-    - "input": The checkpoint was created from an input to invoke/stream/batch.
+    - `"input"`: The checkpoint was created from an input to invoke/stream/batch.
-    - "loop": The checkpoint was created from inside the pregel loop.
+    - `"loop"`: The checkpoint was created from inside the pregel loop.
-    - "update": The checkpoint was created from a manual state update.
+    - `"update"`: The checkpoint was created from a manual state update.
-    - "fork": The checkpoint was created as a copy of another checkpoint.
+    - `"fork"`: The checkpoint was created as a copy of another checkpoint.
    """
    step: int
    """The step number of the checkpoint.
-    -1 for the first "input" checkpoint.
+    `-1` for the first `"input"` checkpoint.
-    0 for the first "loop" checkpoint.
+    `0` for the first `"loop"` checkpoint.
-    ... for the nth checkpoint afterwards.
+    `...` for the `nth` checkpoint afterwards.
    """
    parents: dict[str, str]
    """The IDs of the parent checkpoints.
@@ -54,7 +53,7 @@ class CheckpointMetadata(TypedDict, total=False):
    """
-ChannelVersions = dict[str, Union[str, int, float]]
+ChannelVersions = dict[str, str | int | float]
 class Checkpoint(TypedDict):
@@ -148,7 +147,7 @@ class BaseCheckpointSaver(Generic[V]):
            config: Configuration specifying which checkpoint to retrieve.
        Returns:
-            Optional[Checkpoint]: The requested checkpoint, or None if not found.
+            The requested checkpoint, or `None` if not found.
        """
        if value := self.get_tuple(config):
            return value.checkpoint
@@ -160,7 +159,7 @@ class BaseCheckpointSaver(Generic[V]):
            config: Configuration specifying which checkpoint to retrieve.
        Returns:
-            Optional[CheckpointTuple]: The requested checkpoint tuple, or None if not found.
+            The requested checkpoint tuple, or `None` if not found.
        Raises:
            NotImplementedError: Implement this method in your custom checkpoint saver.
@@ -184,7 +183,7 @@ class BaseCheckpointSaver(Generic[V]):
            limit: Maximum number of checkpoints to return.
        Returns:
-            Iterator[CheckpointTuple]: Iterator of matching checkpoint tuples.
+            Iterator of matching checkpoint tuples.
        Raises:
            NotImplementedError: Implement this method in your custom checkpoint saver.
@@ -252,7 +251,7 @@ class BaseCheckpointSaver(Generic[V]):
            config: Configuration specifying which checkpoint to retrieve.
        Returns:
-            Optional[Checkpoint]: The requested checkpoint, or None if not found.
+            The requested checkpoint, or `None` if not found.
        """
        if value := await self.aget_tuple(config):
            return value.checkpoint
@@ -264,7 +263,7 @@ class BaseCheckpointSaver(Generic[V]):
            config: Configuration specifying which checkpoint to retrieve.
        Returns:
-            Optional[CheckpointTuple]: The requested checkpoint tuple, or None if not found.
+            The requested checkpoint tuple, or `None` if not found.
        Raises:
            NotImplementedError: Implement this method in your custom checkpoint saver.
@@ -288,7 +287,7 @@ class BaseCheckpointSaver(Generic[V]):
            limit: Maximum number of checkpoints to return.
        Returns:
-            AsyncIterator[CheckpointTuple]: Async iterator of matching checkpoint tuples.
+            Async iterator of matching checkpoint tuples.
        Raises:
            NotImplementedError: Implement this method in your custom checkpoint saver.
@@ -353,11 +352,11 @@ class BaseCheckpointSaver(Generic[V]):
    def get_next_version(self, current: V | None, channel: None) -> V:
        """Generate the next version ID for a channel.
-        Default is to use integer versions, incrementing by 1. If you override, you can use str/int/float versions,
+        Default is to use integer versions, incrementing by `1`. If you override, you can use `str`/`int`/`float`
-        as long as they are monotonically increasing.
+        versions, as long as they are monotonically increasing.
        Args:
-            current: The current version identifier (int, float, or str).
+            current: The current version identifier (`int`, `float`, or `str`).
            channel: Deprecated argument, kept for backwards compatibility.
        Returns:
@@ -404,6 +403,16 @@ 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.
@@ -39,10 +39,10 @@ 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.
+        serde: The serializer to use for serializing and deserializing checkpoints.
    Examples:
@@ -133,7 +133,7 @@ class InMemorySaver(
        """Get a checkpoint tuple from the in-memory storage.
        This method retrieves a checkpoint tuple from the in-memory storage based on the
-        provided config. If the config contains a "checkpoint_id" key, the checkpoint with
+        provided config. If the config contains a `checkpoint_id` key, the checkpoint with
        the matching thread ID and timestamp is retrieved. Otherwise, the latest checkpoint
        for the given thread ID is retrieved.
@@ -141,7 +141,7 @@ class InMemorySaver(
            config: The config to use for retrieving the checkpoint.
        Returns:
-            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+            The retrieved checkpoint tuple, or None if no matching checkpoint was found.
        """
        thread_id: str = config["configurable"]["thread_id"]
        checkpoint_ns: str = config["configurable"].get("checkpoint_ns", "")
@@ -231,7 +231,7 @@ class InMemorySaver(
            limit: Maximum number of checkpoints to return.
        Yields:
-            Iterator[CheckpointTuple]: An iterator of matching checkpoint tuples.
+            An iterator of matching checkpoint tuples.
        """
        thread_ids = (config["configurable"]["thread_id"],) if config else self.storage
        config_checkpoint_ns = (
@@ -423,16 +423,16 @@ class InMemorySaver(
                del self.blobs[k]
    async def aget_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
-        """Asynchronous version of get_tuple.
+        """Asynchronous version of `get_tuple`.
-        This method is an asynchronous wrapper around get_tuple that runs the synchronous
+        This method is an asynchronous wrapper around `get_tuple` that runs the synchronous
        method in a separate thread using asyncio.
        Args:
            config: The config to use for retrieving the checkpoint.
        Returns:
-            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+            The retrieved checkpoint tuple, or None if no matching checkpoint was found.
        """
        return self.get_tuple(config)
@@ -444,16 +444,16 @@ class InMemorySaver(
        before: RunnableConfig | None = None,
        limit: int | None = None,
    ) -> AsyncIterator[CheckpointTuple]:
-        """Asynchronous version of list.
+        """Asynchronous version of `list`.
-        This method is an asynchronous wrapper around list that runs the synchronous
+        This method is an asynchronous wrapper around `list` that runs the synchronous
        method in a separate thread using asyncio.
        Args:
            config: The config to use for listing the checkpoints.
        Yields:
-            AsyncIterator[CheckpointTuple]: An asynchronous iterator of checkpoint tuples.
+            An asynchronous iterator of checkpoint tuples.
        """
        for item in self.list(config, filter=filter, before=before, limit=limit):
            yield item
@@ -465,7 +465,7 @@ class InMemorySaver(
        metadata: CheckpointMetadata,
        new_versions: ChannelVersions,
    ) -> RunnableConfig:
-        """Asynchronous version of put.
+        """Asynchronous version of `put`.
        Args:
            config: The config to associate with the checkpoint.
@@ -485,9 +485,9 @@ class InMemorySaver(
        task_id: str,
        task_path: str = "",
    ) -> None:
-        """Asynchronous version of put_writes.
+        """Asynchronous version of `put_writes`.
-        This method is an asynchronous wrapper around put_writes that runs the synchronous
+        This method is an asynchronous wrapper around `put_writes` that runs the synchronous
        method in a separate thread using asyncio.
        Args:
@@ -1,6 +1,6 @@
 from __future__ import annotations
-from typing import Any, Protocol
+from typing import Any, Protocol, runtime_checkable
 class UntypedSerializerProtocol(Protocol):
@@ -11,13 +11,14 @@ class UntypedSerializerProtocol(Protocol):
    def loads(self, data: bytes) -> Any: ...
-class SerializerProtocol(UntypedSerializerProtocol, Protocol):
+@runtime_checkable
 class SerializerProtocol(Protocol):
    """Protocol for serialization and deserialization of objects.
    - `dumps`: Serialize an object to bytes.
-    - `dumps_typed`: Serialize an object to a tuple (type, bytes).
+    - `dumps_typed`: Serialize an object to a tuple `(type, bytes)`.
    - `loads`: Deserialize an object from bytes.
-    - `loads_typed`: Deserialize an object from a tuple (type, bytes).
+    - `loads_typed`: Deserialize an object from a tuple `(type, bytes)`.
    Valid implementations include the `pickle`, `json` and `orjson` modules.
    """
@@ -31,12 +32,6 @@ class SerializerCompat(SerializerProtocol):
    def __init__(self, serde: UntypedSerializerProtocol) -> None:
        self.serde = serde
    def dumps(self, obj: Any) -> bytes:
        return self.serde.dumps(obj)
    def loads(self, data: bytes) -> Any:
        return self.serde.loads(data)
    def dumps_typed(self, obj: Any) -> tuple[str, bytes]:
        return type(obj).__name__, self.serde.dumps(obj)
@@ -49,7 +44,7 @@ def maybe_add_typed_methods(
 ) -> SerializerProtocol:
    """Wrap serde old serde implementations in a class with loads_typed and dumps_typed for backwards compatibility."""
-    if not hasattr(serde, "loads_typed") or not hasattr(serde, "dumps_typed"):
+    if not isinstance(serde, SerializerProtocol):
        return SerializerCompat(serde)
    return serde
@@ -14,14 +14,8 @@ class EncryptedSerializer(SerializerProtocol):
        self.cipher = cipher
        self.serde = serde
    def dumps(self, obj: Any) -> bytes:
        return self.serde.dumps(obj)
    def loads(self, data: bytes) -> Any:
        return self.serde.loads(data)
    def dumps_typed(self, obj: Any) -> tuple[str, bytes]:
-        """Serialize an object to a tuple (type, bytes) and encrypt the bytes."""
+        """Serialize an object to a tuple `(type, bytes)` and encrypt the bytes."""
        # serialize data
        typ, data = self.serde.dumps_typed(obj)
        # encrypt data
@@ -45,7 +39,7 @@ class EncryptedSerializer(SerializerProtocol):
    def from_pycryptodome_aes(
        cls, serde: SerializerProtocol = JsonPlusSerializer(), **kwargs: Any
    ) -> "EncryptedSerializer":
-        """Create an EncryptedSerializer using AES encryption."""
+        """Create an `EncryptedSerializer` using AES encryption."""
        try:
            from Crypto.Cipher import AES  # type: ignore
        except ImportError:
@@ -4,12 +4,13 @@ import dataclasses
 import decimal
 import importlib
 import json
 import logging
 import pathlib
 import pickle
 import re
 import sys
 from collections import deque
-from collections.abc import Sequence
+from collections.abc import Callable, Sequence
 from datetime import date, datetime, time, timedelta, timezone
 from enum import Enum
 from inspect import isclass
@@ -21,13 +22,12 @@ from ipaddress import (
    IPv6Interface,
    IPv6Network,
 )
-from typing import Any, Callable, cast
+from typing import Any, Literal
 from uuid import UUID
 from zoneinfo import ZoneInfo
 import ormsgpack
 from langchain_core.load.load import Reviver
 from langchain_core.load.serializable import Serializable
 from langgraph.checkpoint.serde.base import SerializerProtocol
 from langgraph.checkpoint.serde.types import SendProtocol
@@ -35,18 +35,31 @@ from langgraph.store.base import Item
 LC_REVIVER = Reviver()
 EMPTY_BYTES = b""
 logger = logging.getLogger(__name__)
 class JsonPlusSerializer(SerializerProtocol):
-    """Serializer that uses ormsgpack, with a fallback to extended JSON serializer."""
+    """Serializer that uses ormsgpack, with optional fallbacks.
    Security note: this serializer is intended for use within the BaseCheckpointSaver
    class and called within the Pregel loop. It should not be used on untrusted
    python objects. If an attacker can write directly to your checkpoint database,
    they may be able to trigger code execution when data is deserialized.
    """
    def __init__(
        self,
        *,
        pickle_fallback: bool = False,
        allowed_json_modules: Sequence[tuple[str, ...]] | Literal[True] | None = None,
        __unpack_ext_hook__: Callable[[int, bytes], Any] | None = None,
    ) -> None:
        self.pickle_fallback = pickle_fallback
        self._allowed_modules = (
            {mod_and_name for mod_and_name in allowed_json_modules}
            if allowed_json_modules and allowed_json_modules is not True
            else (allowed_json_modules if allowed_json_modules is True else None)
        )
        self._unpack_ext_hook = (
            __unpack_ext_hook__
            if __unpack_ext_hook__ is not None
@@ -74,134 +87,90 @@ class JsonPlusSerializer(SerializerProtocol):
            out["kwargs"] = kwargs
        return out
    def _default(self, obj: Any) -> str | dict[str, Any]:
        if isinstance(obj, Serializable):
            return cast(dict[str, Any], obj.to_json())
        elif hasattr(obj, "model_dump") and callable(obj.model_dump):
            return self._encode_constructor_args(
                obj.__class__, method=(None, "model_construct"), kwargs=obj.model_dump()
            )
        elif hasattr(obj, "dict") and callable(obj.dict):
            return self._encode_constructor_args(
                obj.__class__, method=(None, "construct"), kwargs=obj.dict()
            )
        elif hasattr(obj, "_asdict") and callable(obj._asdict):
            return self._encode_constructor_args(obj.__class__, kwargs=obj._asdict())
        elif isinstance(obj, pathlib.Path):
            return self._encode_constructor_args(pathlib.Path, args=obj.parts)
        elif isinstance(obj, re.Pattern):
            return self._encode_constructor_args(
                re.compile, args=(obj.pattern, obj.flags)
            )
        elif isinstance(obj, UUID):
            return self._encode_constructor_args(UUID, args=(obj.hex,))
        elif isinstance(obj, decimal.Decimal):
            return self._encode_constructor_args(decimal.Decimal, args=(str(obj),))
        elif isinstance(obj, (set, frozenset, deque)):
            return self._encode_constructor_args(type(obj), args=(tuple(obj),))
        elif isinstance(obj, (IPv4Address, IPv4Interface, IPv4Network)):
            return self._encode_constructor_args(obj.__class__, args=(str(obj),))
        elif isinstance(obj, (IPv6Address, IPv6Interface, IPv6Network)):
            return self._encode_constructor_args(obj.__class__, args=(str(obj),))
        elif isinstance(obj, datetime):
            return self._encode_constructor_args(
                datetime, method="fromisoformat", args=(obj.isoformat(),)
            )
        elif isinstance(obj, timezone):
            return self._encode_constructor_args(
                timezone,
                args=obj.__getinitargs__(),  # type: ignore[attr-defined]
            )
        elif isinstance(obj, ZoneInfo):
            return self._encode_constructor_args(ZoneInfo, args=(obj.key,))
        elif isinstance(obj, timedelta):
            return self._encode_constructor_args(
                timedelta, args=(obj.days, obj.seconds, obj.microseconds)
            )
        elif isinstance(obj, date):
            return self._encode_constructor_args(
                date, args=(obj.year, obj.month, obj.day)
            )
        elif isinstance(obj, time):
            return self._encode_constructor_args(
                time,
                args=(obj.hour, obj.minute, obj.second, obj.microsecond, obj.tzinfo),
                kwargs={"fold": obj.fold},
            )
        elif dataclasses.is_dataclass(obj):
            return self._encode_constructor_args(
                obj.__class__,
                kwargs={
                    field.name: getattr(obj, field.name)
                    for field in dataclasses.fields(obj)
                },
            )
        elif isinstance(obj, Enum):
            return self._encode_constructor_args(obj.__class__, args=(obj.value,))
        elif isinstance(obj, SendProtocol):
            return self._encode_constructor_args(
                obj.__class__, kwargs={"node": obj.node, "arg": obj.arg}
            )
        elif isinstance(obj, (bytes, bytearray)):
            return self._encode_constructor_args(
                obj.__class__, method="fromhex", args=(obj.hex(),)
            )
        elif isinstance(obj, BaseException):
            return repr(obj)
        else:
            raise TypeError(
                f"Object of type {obj.__class__.__name__} is not JSON serializable"
            )
    def _reviver(self, value: dict[str, Any]) -> Any:
-        if (
+        if self._allowed_modules and (
            value.get("lc", None) == 2
            and value.get("type", None) == "constructor"
            and value.get("id", None) is not None
        ):
            try:
-                # Get module and class name
+                return self._revive_lc2(value)
-                [*module, name] = value["id"]
+            except InvalidModuleError as e:
-                # Import module
+                logger.warning(
-                mod = importlib.import_module(".".join(module))
+                    "Object %s is not in the deserialization allowlist.\n%s",
-                # Import class
+                    value["id"],
-                cls = getattr(mod, name)
+                    e.message,
-                # Instantiate class
+                )
                method = value.get("method")
                if isinstance(method, str):
                    methods = [getattr(cls, method)]
                elif isinstance(method, list):
                    methods = [
                        cls if method is None else getattr(cls, method)
                        for method in method
                    ]
                else:
                    methods = [cls]
                args = value.get("args")
                kwargs = value.get("kwargs")
                for method in methods:
                    try:
                        if isclass(method) and issubclass(method, BaseException):
                            return None
                        if args and kwargs:
                            return method(*args, **kwargs)
                        elif args:
                            return method(*args)
                        elif kwargs:
                            return method(**kwargs)
                        else:
                            return method()
                    except Exception:
                        continue
            except Exception:
                return None
        return LC_REVIVER(value)
-    def dumps(self, obj: Any) -> bytes:
+    def _revive_lc2(self, value: dict[str, Any]) -> Any:
-        return json.dumps(obj, default=self._default, ensure_ascii=False).encode(
+        self._check_allowed_modules(value)
-            "utf-8", "ignore"
+
        [*module, name] = value["id"]
        try:
            mod = importlib.import_module(".".join(module))
            cls = getattr(mod, name)
            method = value.get("method")
            if isinstance(method, str):
                methods = [getattr(cls, method)]
            elif isinstance(method, list):
                methods = [cls if m is None else getattr(cls, m) for m in method]
            else:
                methods = [cls]
            args = value.get("args")
            kwargs = value.get("kwargs")
            for method in methods:
                try:
                    if isclass(method) and issubclass(method, BaseException):
                        return None
                    if args and kwargs:
                        return method(*args, **kwargs)
                    elif args:
                        return method(*args)
                    elif kwargs:
                        return method(**kwargs)
                    else:
                        return method()
                except Exception:
                    continue
        except Exception:
            return None
    def _check_allowed_modules(self, value: dict[str, Any]) -> None:
        needed = tuple(value["id"])
        method = value.get("method")
        if isinstance(method, list):
            method_display = ",".join(m or "<init>" for m in method)
        elif isinstance(method, str):
            method_display = method
        else:
            method_display = "<init>"
        dotted = ".".join(needed)
        if not self._allowed_modules:
            raise InvalidModuleError(
                f"Refused to deserialize JSON constructor: {dotted} (method: {method_display}). "
                "No allowed_json_modules configured.\n\n"
                "Unblock with ONE of:\n"
                f"  • JsonPlusSerializer(allowed_json_modules=[{needed!r}, ...])\n"
                "  • (DANGEROUS) JsonPlusSerializer(allowed_json_modules=True)\n\n"
                "Note: Prefix allowlists are intentionally unsupported; prefer exact symbols "
                "or plain-JSON representations revived without import-time side effects."
            )
        if self._allowed_modules is True:
            return
        if needed in self._allowed_modules:
            return
        raise InvalidModuleError(
            f"Refused to deserialize JSON constructor: {dotted} (method: {method_display}). "
            "Symbol is not in the deserialization allowlist.\n\n"
            "Add exactly this symbol to unblock:\n"
            f"  JsonPlusSerializer(allowed_json_modules=[{needed!r}, ...])\n"
            "Or, as a last resort (DANGEROUS):\n"
            "  JsonPlusSerializer(allowed_json_modules=True)"
        )
    def dumps_typed(self, obj: Any) -> tuple[str, bytes]:
@@ -215,15 +184,10 @@ class JsonPlusSerializer(SerializerProtocol):
            try:
                return "msgpack", _msgpack_enc(obj)
            except ormsgpack.MsgpackEncodeError as exc:
-                if "valid UTF-8" in str(exc):
+                if self.pickle_fallback:
                    return "json", self.dumps(obj)
                elif self.pickle_fallback:
                    return "pickle", pickle.dumps(obj)
                raise exc
    def loads(self, data: bytes) -> Any:
        return json.loads(data, object_hook=self._reviver)
    def loads_typed(self, data: tuple[str, bytes]) -> Any:
        type_, data_ = data
        if type_ == "null":
@@ -233,7 +197,7 @@ class JsonPlusSerializer(SerializerProtocol):
        elif type_ == "bytearray":
            return bytearray(data_)
        elif type_ == "json":
-            return self.loads(data_)
+            return json.loads(data_, object_hook=self._reviver)
        elif type_ == "msgpack":
            return ormsgpack.unpackb(
                data_, ext_hook=self._unpack_ext_hook, option=ormsgpack.OPT_NON_STR_KEYS
@@ -663,6 +627,13 @@ def _msgpack_ext_hook_to_json(code: int, data: bytes) -> Any:
            return
 class InvalidModuleError(Exception):
    """Exception raised when a module is not in the allowlist."""
    def __init__(self, message: str):
        self.message = message
 _option = (
    ormsgpack.OPT_NON_STR_KEYS
    | ormsgpack.OPT_PASSTHROUGH_DATACLASS
@@ -1,7 +1,6 @@
 from collections.abc import Sequence
 from typing import (
    Any,
    Optional,
    Protocol,
    TypeVar,
    runtime_checkable,
@@ -28,9 +27,9 @@ class ChannelProtocol(Protocol[Value, Update, C]):
    @property
    def UpdateType(self) -> Any: ...
-    def checkpoint(self) -> Optional[C]: ...
+    def checkpoint(self) -> C | None: ...
-    def from_checkpoint(self, checkpoint: Optional[C]) -> Self: ...
+    def from_checkpoint(self, checkpoint: C | None) -> Self: ...
    def update(self, values: Sequence[Update]) -> bool: ...
@@ -4,9 +4,9 @@ Stores provide long-term memory that persists across threads and conversations.
 Supports hierarchical namespaces, key-value storage, and optional vector search.
 Core types:
-    - BaseStore: Store interface with sync/async operations
+    - `BaseStore`: Store interface with sync/async operations
-    - Item: Stored key-value pairs with metadata
+    - `Item`: Stored key-value pairs with metadata
-    - Op: Get/Put/Search/List operations
+    - `Op`: Get/Put/Search/List operations
 """
 from __future__ import annotations
@@ -19,7 +19,6 @@ from typing import (
    Literal,
    NamedTuple,
    TypedDict,
    Union,
    cast,
 )
@@ -57,7 +56,7 @@ class Item:
        key: Unique identifier within the namespace.
        namespace: Hierarchical path defining the collection in which this document resides.
            Represented as a tuple of strings, allowing for nested categorization.
-            For example: ("documents", 'user123')
+            For example: `("documents", 'user123')`
        created_at: Timestamp of item creation.
        updated_at: Timestamp of last update.
    """
@@ -164,6 +163,7 @@ class GetOp(NamedTuple):
    ???+ example "Examples"
        Basic item retrieval:
        ```python
        GetOp(namespace=("users", "profiles"), key="user123")
        GetOp(namespace=("cache", "embeddings"), key="doc456")
@@ -207,11 +207,14 @@ class SearchOp(NamedTuple):
    within a given namespace prefix. It provides pagination through limit and offset
    parameters.
-    Note:
+    !!! note
        Natural language search support depends on your store implementation.
    ???+ example "Examples"
        Search with filters and pagination:
        ```python
        SearchOp(
            namespace_prefix=("documents",),
@@ -222,6 +225,7 @@ class SearchOp(NamedTuple):
        ```
        Natural language search:
        ```python
        SearchOp(
            namespace_prefix=("users", "content"),
@@ -249,14 +253,15 @@ class SearchOp(NamedTuple):
    The filter supports both exact matches and operator-based comparisons.
    Supported Operators:
-        - $eq: Equal to (same as direct value comparison)
+        - `$eq`: Equal to (same as direct value comparison)
-        - $ne: Not equal to
+        - `$ne`: Not equal to
-        - $gt: Greater than
+        - `$gt`: Greater than
-        - $gte: Greater than or equal to
+        - `$gte`: Greater than or equal to
-        - $lt: Less than
+        - `$lt`: Less than
-        - $lte: Less than or equal to
+        - `$lte`: Less than or equal to
    ???+ example "Examples"
        Simple exact match:
        ```python
@@ -289,6 +294,7 @@ class SearchOp(NamedTuple):
    """Natural language search query for semantic search capabilities.
    ???+ example "Examples"
        - "technical documentation about REST APIs"
        - "machine learning papers from 2023"
    """
@@ -302,10 +308,11 @@ class SearchOp(NamedTuple):
 # Type representing a namespace path that can include wildcards
-NamespacePath = tuple[Union[str, Literal["*"]], ...]
+NamespacePath = tuple[str | Literal["*"], ...]
 """A tuple representing a namespace path that can include wildcards.
 ???+ example "Examples"
    ```python
    ("users",)  # Exact users namespace
    ("documents", "*")  # Any sub-namespace under documents
@@ -331,17 +338,21 @@ class MatchCondition(NamedTuple):
    hierarchies.
    ???+ example "Examples"
        Prefix matching:
        ```python
        MatchCondition(match_type="prefix", path=("users", "profiles"))
        ```
        Suffix matching with wildcard:
        ```python
        MatchCondition(match_type="suffix", path=("cache", "*"))
        ```
        Simple suffix matching:
        ```python
        MatchCondition(match_type="suffix", path=("v1",))
        ```
@@ -362,7 +373,8 @@ class ListNamespacesOp(NamedTuple):
    ???+ example "Examples"
-        List all namespaces under the "documents" path:
+        List all namespaces under the `"documents"` path:
        ```python
        ListNamespacesOp(
            match_conditions=(MatchCondition(match_type="prefix", path=("documents",)),),
@@ -370,7 +382,8 @@ class ListNamespacesOp(NamedTuple):
        )
        ```
-        List all namespaces that end with "v1":
+        List all namespaces that end with `"v1"`:
        ```python
        ListNamespacesOp(
            match_conditions=(MatchCondition(match_type="suffix", path=("v1",)),),
@@ -384,12 +397,15 @@ class ListNamespacesOp(NamedTuple):
    """Optional conditions for filtering namespaces.
    ???+ example "Examples"
        All user namespaces:
        ```python
        (MatchCondition(match_type="prefix", path=("users",)),)
        ```
-        All namespaces that start with "docs" and end with "draft":
+        All namespaces that start with `"docs"` and end with `"draft"`:
        ```python
        (
            MatchCondition(match_type="prefix", path=("docs",)),
@@ -426,17 +442,21 @@ class PutOp(NamedTuple):
    Each element in the tuple represents one level in the hierarchy.
    ???+ example "Examples"
-        Root level documents
+
        Root level documents:
        ```python
        ("documents",)
        ```
-        User-specific documents
+        User-specific documents:
        ```python
        ("documents", "user123")
        ```
-        Nested cache structure
+        Nested cache structure:
        ```python
        ("cache", "embeddings", "v1")
        ```
@@ -449,15 +469,15 @@ class PutOp(NamedTuple):
    Together with the namespace, it forms a complete path to the item.
    Example:
-        If namespace is ("documents", "user123") and key is "report1",
+        If namespace is `("documents", "user123")` and key is `"report1"`,
-        the full path would effectively be "documents/user123/report1"
+        the full path would effectively be `"documents/user123/report1"`
    """
    value: dict[str, Any] | None
-    """The data to store, or None to mark the item for deletion.
+    """The data to store, or `None` to mark the item for deletion.
    The value must be a dictionary with string keys and JSON-serializable values.
-    Setting this to None signals that the item should be deleted.
+    Setting this to `None` signals that the item should be deleted.
    Example:
        {
@@ -471,25 +491,26 @@ class PutOp(NamedTuple):
    """Controls how the item's fields are indexed for search operations.
    Indexing configuration determines how the item can be found through search:
-        - None (default): Uses the store's default indexing configuration (if provided)
+        - `None` (default): Uses the store's default indexing configuration (if provided)
-        - False: Disables indexing for this item
+        - `False`: Disables indexing for this item
-        - list[str]: Specifies which json path fields to index for search
+        - `list[str]`: Specifies which json path fields to index for search
    The item remains accessible through direct get() operations regardless of indexing.
    When indexed, fields can be searched using natural language queries through
    vector similarity search (if supported by the store implementation).
    Path Syntax:
-        - Simple field access: "field"
+        - Simple field access: `"field"`
-        - Nested fields: "parent.child.grandchild"
+        - Nested fields: `"parent.child.grandchild"`
        - Array indexing:
-          - Specific index: "array[0]"
+            - Specific index: `"array[0]"`
-          - Last element: "array[-1]"
+            - Last element: `"array[-1]"`
-          - All elements (each individually): "array[*]"
+            - All elements (each individually): `"array[*]"`
    ???+ example "Examples"
-        - None - Use store defaults (whole item)
+
-        - list[str] - List of fields to index
+        - `None` - Use store defaults (whole item)
        - `list[str]` - List of fields to index
        ```python
        [
@@ -509,12 +530,12 @@ class PutOp(NamedTuple):
    will expire this many minutes after it was last accessed. The expiration timer
    refreshes on both read operations (get/search) and write operations (put/update).
    When the TTL expires, the item will be scheduled for deletion on a best-effort basis.
-    Defaults to None (no expiration).
+    Defaults to `None` (no expiration).
    """
-Op = Union[GetOp, SearchOp, PutOp, ListNamespacesOp]
+Op = GetOp | SearchOp | PutOp | ListNamespacesOp
-Result = Union[Item, list[Item], list[SearchItem], list[tuple[str, ...]], None]
+Result = Item | list[Item] | list[SearchItem] | list[tuple[str, ...]] | None
 class InvalidNamespaceError(ValueError):
@@ -525,18 +546,18 @@ class TTLConfig(TypedDict, total=False):
    """Configuration for TTL (time-to-live) behavior in the store."""
    refresh_on_read: bool
-    """Default behavior for refreshing TTLs on read operations (GET and SEARCH).
+    """Default behavior for refreshing TTLs on read operations (`GET` and `SEARCH`).
-    If True, TTLs will be refreshed on read operations (get/search) by default.
+    If `True`, TTLs will be refreshed on read operations (get/search) by default.
-    This can be overridden per-operation by explicitly setting refresh_ttl.
+    This can be overridden per-operation by explicitly setting `refresh_ttl`.
-    Defaults to True if not configured.
+    Defaults to `True` if not configured.
    """
    default_ttl: float | None
    """Default TTL (time-to-live) in minutes for new items.
    If provided, new items will expire after this many minutes after their last access.
    The expiration timer refreshes on both read and write operations.
-    Defaults to None (no expiration).
+    Defaults to `None` (no expiration).
    """
    sweep_interval_minutes: int | None
    """Interval in minutes between TTL sweep operations.
@@ -550,33 +571,35 @@ class IndexConfig(TypedDict, total=False):
    """Configuration for indexing documents for semantic search in the store.
    If not provided to the store, the store will not support vector search.
-    In that case, all `index` arguments to put() and `aput()` operations will be ignored.
+    In that case, all `index` arguments to `put()` and `aput()` operations will be ignored.
    """
    dims: int
    """Number of dimensions in the embedding vectors.
    Common embedding models have the following dimensions:
-        - openai:text-embedding-3-large: 3072
+        - `openai:text-embedding-3-large`: `3072`
-        - openai:text-embedding-3-small: 1536
+        - `openai:text-embedding-3-small`: `1536`
-        - openai:text-embedding-ada-002: 1536
+        - `openai:text-embedding-ada-002`: `1536`
-        - cohere:embed-english-v3.0: 1024
+        - `cohere:embed-english-v3.0`: `1024`
-        - cohere:embed-english-light-v3.0: 384
+        - `cohere:embed-english-light-v3.0`: `384`
-        - cohere:embed-multilingual-v3.0: 1024
+        - `cohere:embed-multilingual-v3.0`: `1024`
-        - cohere:embed-multilingual-light-v3.0: 384
+        - `cohere:embed-multilingual-light-v3.0`: `384`
    """
    embed: Embeddings | EmbeddingsFunc | AEmbeddingsFunc | str
    """Optional function to generate embeddings from text.
    Can be specified in three ways:
-        1. A LangChain Embeddings instance
+        1. A LangChain `Embeddings` instance
-        2. A synchronous embedding function (EmbeddingsFunc)
+        2. A synchronous embedding function (`EmbeddingsFunc`)
-        3. An asynchronous embedding function (AEmbeddingsFunc)
+        3. An asynchronous embedding function (`AEmbeddingsFunc`)
-        4. A provider string (e.g., "openai:text-embedding-3-small")
+        4. A provider string (e.g., `"openai:text-embedding-3-small"`)
    ???+ example "Examples"
-        Using LangChain's initialization with InMemoryStore:
+
        Using LangChain's initialization with `InMemoryStore`:
        ```python
        from langchain.embeddings import init_embeddings
        from langgraph.store.memory import InMemoryStore
@@ -589,7 +612,8 @@ class IndexConfig(TypedDict, total=False):
        )
        ```
-        Using a custom embedding function with InMemoryStore:
+        Using a custom embedding function with `InMemoryStore`:
        ```python
        from openai import OpenAI
        from langgraph.store.memory import InMemoryStore
@@ -611,7 +635,8 @@ class IndexConfig(TypedDict, total=False):
        )
        ```
-        Using an asynchronous embedding function with InMemoryStore:
+        Using an asynchronous embedding function with `InMemoryStore`:
        ```python
        from openai import AsyncOpenAI
        from langgraph.store.memory import InMemoryStore
@@ -639,16 +664,17 @@ class IndexConfig(TypedDict, total=False):
    Controls which parts of stored items are embedded for semantic search. Follows JSON path syntax:
-        - ["$"]: Embeds the entire JSON object as one vector  (default)
+    - `["$"]`: Embeds the entire JSON object as one vector  (default)
-        - ["field1", "field2"]: Embeds specific top-level fields
+    - `["field1", "field2"]`: Embeds specific top-level fields
-        - ["parent.child"]: Embeds nested fields using dot notation
+    - `["parent.child"]`: Embeds nested fields using dot notation
-        - ["array[*].field"]: Embeds field from each array element separately
+    - `["array[*].field"]`: Embeds field from each array element separately
    Note:
        You can always override this behavior when storing an item using the
        `index` parameter in the `put` or `aput` operations.
    ???+ example "Examples"
        ```python
        # Embed entire document (default)
        fields=["$"]
@@ -667,7 +693,7 @@ class IndexConfig(TypedDict, total=False):
    Note:
        - Fields missing from a document are skipped
        - Array notation creates separate embeddings for each element
-        - Complex nested paths are supported (e.g., "a.b[*].c.d")
+        - Complex nested paths are supported (e.g., `"a.b[*].c.d"`)
    """
@@ -732,11 +758,11 @@ class BaseStore(ABC):
            namespace: Hierarchical path for the item.
            key: Unique identifier within the namespace.
            refresh_ttl: Whether to refresh TTLs for the returned item.
-                If None (default), uses the store's default refresh_ttl setting.
+                If `None`, uses the store's default `refresh_ttl` setting.
                If no TTL is specified, this argument is ignored.
        Returns:
-            The retrieved item or None if not found.
+            The retrieved item or `None` if not found.
        """
        return self.batch(
            [GetOp(namespace, str(key), _ensure_refresh(self.ttl_config, refresh_ttl))]
@@ -768,7 +794,9 @@ class BaseStore(ABC):
            List of items matching the search criteria.
        ???+ example "Examples"
            Basic filtering:
            ```python
            # Search for documents with specific metadata
            results = store.search(
@@ -778,6 +806,7 @@ class BaseStore(ABC):
            ```
            Natural language search (requires vector store implementation):
            ```python
            # Initialize store with embedding configuration
            store = YourStore( # e.g., InMemoryStore, AsyncPostgresStore
@@ -789,6 +818,7 @@ class BaseStore(ABC):
            )
            # Search for semantically similar documents
            results = store.search(
                ("docs",),
                query="machine learning applications in healthcare",
@@ -797,8 +827,10 @@ class BaseStore(ABC):
            )
            ```
-            Note: Natural language search support depends on your store implementation
+            !!! note
-            and requires proper embedding configuration.
+
                Natural language search support depends on your store implementation
                and requires proper embedding configuration.
        """
        return self.batch(
            [
@@ -826,7 +858,7 @@ class BaseStore(ABC):
        Args:
            namespace: Hierarchical path for the item, represented as a tuple of strings.
-                Example: ("documents", "user123")
+                Example: `("documents", "user123")`
            key: Unique identifier within the namespace. Together with namespace forms
                the complete path to the item.
            value: Dictionary containing the item's data. Must contain string keys
@@ -837,10 +869,10 @@ class BaseStore(ABC):
                    If you do not initialize the store with indexing capabilities,
                    the `index` parameter will be ignored
                - False: Disable indexing for this item
-                - list[str]: List of field paths to index, supporting:
+                - `list[str]`: List of field paths to index, supporting:
-                    - Nested fields: "metadata.title"
+                    - Nested fields: `"metadata.title"`
-                    - Array access: "chapters[*].content" (each indexed separately)
+                    - Array access: `"chapters[*].content"` (each indexed separately)
-                    - Specific indices: "authors[0].name"
+                    - Specific indices: `"authors[0].name"`
            ttl: Time to live in minutes. Support for this argument depends on your store adapter.
                If specified, the item will expire after this many minutes from when it was last accessed.
                None means no expiration. Expired runs will be deleted opportunistically.
@@ -856,18 +888,22 @@ class BaseStore(ABC):
            Some implementations may not support expiration of items.
        ???+ example "Examples"
-            Store item. Indexing depends on how you configure the store.
+
            Store item. Indexing depends on how you configure the store:
            ```python
            store.put(("docs",), "report", {"memory": "Will likes ai"})
            ```
-            Do not index item for semantic search. Still accessible through get()
+            Do not index item for semantic search. Still accessible through `get()`
-            and search() operations but won't have a vector representation.
+            and `search()` operations but won't have a vector representation.
            ```python
            store.put(("docs",), "report", {"memory": "Will likes ai"}, index=False)
            ```
-            Index specific fields for search.
+            Index specific fields for search:
            ```python
            store.put(("docs",), "report", {"memory": "Will likes ai"}, index=["memory"])
            ```
@@ -918,15 +954,17 @@ class BaseStore(ABC):
            suffix: Filter namespaces that end with this path.
            max_depth: Return namespaces up to this depth in the hierarchy.
                Namespaces deeper than this level will be truncated.
-            limit: Maximum number of namespaces to return (default 100).
+            limit: Maximum number of namespaces to return.
-            offset: Number of namespaces to skip for pagination (default 0).
+            offset: Number of namespaces to skip for pagination.
        Returns:
-            List[Tuple[str, ...]]: A list of namespace tuples that match the criteria.
+            A list of namespace tuples that match the criteria. Each tuple represents a
-            Each tuple represents a full namespace path up to `max_depth`.
+                full namespace path up to `max_depth`.
        ???+ example "Examples":
-            Setting max_depth=3. Given the namespaces:
+
            Setting `max_depth=3`. Given the namespaces:
            ```python
            # Example if you have the following namespaces:
            # ("a", "b", "c")
@@ -966,7 +1004,7 @@ class BaseStore(ABC):
            key: Unique identifier within the namespace.
        Returns:
-            The retrieved item or None if not found.
+            The retrieved item or `None` if not found.
        """
        return (
            await self.abatch(
@@ -1000,14 +1038,16 @@ class BaseStore(ABC):
            limit: Maximum number of items to return.
            offset: Number of items to skip before returning results.
            refresh_ttl: Whether to refresh TTLs for the returned items.
-                If None (default), uses the store's TTLConfig.refresh_default setting.
+                If `None`, uses the store's `TTLConfig.refresh_default` setting.
-                If TTLConfig is not provided or no TTL is specified, this argument is ignored.
+                If `TTLConfig` is not provided or no TTL is specified, this argument is ignored.
        Returns:
            List of items matching the search criteria.
        ???+ example "Examples"
            Basic filtering:
            ```python
            # Search for documents with specific metadata
            results = await store.asearch(
@@ -1017,6 +1057,7 @@ class BaseStore(ABC):
            ```
            Natural language search (requires vector store implementation):
            ```python
            # Initialize store with embedding configuration
            store = YourStore( # e.g., InMemoryStore, AsyncPostgresStore
@@ -1028,6 +1069,7 @@ class BaseStore(ABC):
            )
            # Search for semantically similar documents
            results = await store.asearch(
                ("docs",),
                query="machine learning applications in healthcare",
@@ -1036,8 +1078,10 @@ class BaseStore(ABC):
            )
            ```
-            Note: Natural language search support depends on your store implementation
+            !!! note
-            and requires proper embedding configuration.
+
                Natural language search support depends on your store implementation
                and requires proper embedding configuration.
        """
        return (
            await self.abatch(
@@ -1067,7 +1111,7 @@ class BaseStore(ABC):
        Args:
            namespace: Hierarchical path for the item, represented as a tuple of strings.
-                Example: ("documents", "user123")
+                Example: `("documents", "user123")`
            key: Unique identifier within the namespace. Together with namespace forms
                the complete path to the item.
            value: Dictionary containing the item's data. Must contain string keys
@@ -1078,10 +1122,10 @@ class BaseStore(ABC):
                    If you do not initialize the store with indexing capabilities,
                    the `index` parameter will be ignored
                - False: Disable indexing for this item
-                - list[str]: List of field paths to index, supporting:
+                - `list[str]`: List of field paths to index, supporting:
-                    - Nested fields: "metadata.title"
+                    - Nested fields: `"metadata.title"`
-                    - Array access: "chapters[*].content" (each indexed separately)
+                    - Array access: `"chapters[*].content"` (each indexed separately)
-                    - Specific indices: "authors[0].name"
+                    - Specific indices: `"authors[0].name"`
            ttl: Time to live in minutes. Support for this argument depends on your store adapter.
                If specified, the item will expire after this many minutes from when it was last accessed.
                None means no expiration. Expired runs will be deleted opportunistically.
@@ -1097,18 +1141,22 @@ class BaseStore(ABC):
            Some implementations may not support expiration of items.
        ???+ example "Examples"
-            Store item. Indexing depends on how you configure the store.
+
            Store item. Indexing depends on how you configure the store:
            ```python
            await store.aput(("docs",), "report", {"memory": "Will likes ai"})
            ```
-            Do not index item for semantic search. Still accessible through get()
+            Do not index item for semantic search. Still accessible through `get()`
-            and search() operations but won't have a vector representation.
+            and `search()` operations but won't have a vector representation.
            ```python
            await store.aput(("docs",), "report", {"memory": "Will likes ai"}, index=False)
            ```
            Index specific fields for search (if store configured to index items):
            ```python
            await store.aput(
                ("docs",),
@@ -1167,15 +1215,16 @@ class BaseStore(ABC):
            suffix: Filter namespaces that end with this path.
            max_depth: Return namespaces up to this depth in the hierarchy.
                Namespaces deeper than this level will be truncated to this depth.
-            limit: Maximum number of namespaces to return (default 100).
+            limit: Maximum number of namespaces to return.
-            offset: Number of namespaces to skip for pagination (default 0).
+            offset: Number of namespaces to skip for pagination.
        Returns:
-            List[Tuple[str, ...]]: A list of namespace tuples that match the criteria.
+            A list of namespace tuples that match the criteria. Each tuple represents a
-            Each tuple represents a full namespace path up to `max_depth`.
+                full namespace path up to `max_depth`.
        ???+ example "Examples"
-            Setting max_depth=3 with existing namespaces:
+
            Setting `max_depth=3` with existing namespaces:
            ```python
            # Given the following namespaces:
            # ("a", "b", "c")
@@ -5,8 +5,8 @@ from __future__ import annotations
 import asyncio
 import functools
 import weakref
-from collections.abc import Iterable
+from collections.abc import Callable, Iterable
-from typing import Any, Callable, Literal, TypeVar
+from typing import Any, Literal, TypeVar
 from langgraph.store.base import (
    NOT_PROVIDED,
@@ -349,7 +349,7 @@ async def _run(
                        results = [results[ix] for ix in listen]
                    # set the results of each operation
-                    for fut, result in zip(futs, results):
+                    for fut, result in zip(futs, results, strict=False):
                        # guard against future being done (e.g. cancelled)
                        if not fut.done():
                            fut.set_result(result)
@@ -11,8 +11,8 @@ from __future__ import annotations
 import asyncio
 import functools
 import json
-from collections.abc import Awaitable, Sequence
+from collections.abc import Awaitable, Callable, Sequence
-from typing import Any, Callable
+from typing import Any
 from langchain_core.embeddings import Embeddings
@@ -49,7 +49,9 @@ def ensure_embeddings(
        An Embeddings instance that wraps the provided function(s).
    ??? example "Examples"
        Wrap a synchronous embedding function:
        ```python
        def my_embed_fn(texts):
            return [[0.1, 0.2] for _ in texts]
@@ -59,6 +61,7 @@ def ensure_embeddings(
        ```
        Wrap an asynchronous embedding function:
        ```python
        async def my_async_fn(texts):
            return [[0.1, 0.2] for _ in texts]
@@ -68,6 +71,7 @@ def ensure_embeddings(
        ```
        Initialize embeddings using a provider string:
        ```python
        # Requires langchain>=0.3.9 and langgraph-checkpoint>=2.0.11
        embeddings = ensure_embeddings("openai:text-embedding-3-small")
@@ -119,7 +123,9 @@ class EmbeddingsLambda(Embeddings):
            will raise an error. If sync, it will be used for both sync and async operations.
    ??? example "Examples"
        With a sync function:
        ```python
        def my_embed_fn(texts):
            # Return 2D embeddings for each text
@@ -131,6 +137,7 @@ class EmbeddingsLambda(Embeddings):
        ```
        With an async function:
        ```python
        async def my_async_fn(texts):
            return [[0.1, 0.2] for _ in texts]
@@ -238,7 +245,7 @@ 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 +256,7 @@ 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 +302,11 @@ 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 == "*":
@@ -295,7 +295,7 @@ class InMemoryStore(BaseStore):
            if queries:
                coros = [self.embeddings.aembed_query(q) for q in list(queries)]
                results = await asyncio.gather(*coros)
-                queryinmem_store = dict(zip(queries, results))
+                queryinmem_store = dict(zip(queries, results, strict=False))
        return queryinmem_store
@@ -323,7 +323,9 @@ class InMemoryStore(BaseStore):
                scores = _cosine_similarity(query_embedding, flat_vectors)
                sorted_results = sorted(
-                    zip(scores, flat_items), key=lambda x: x[0], reverse=True
+                    zip(scores, flat_items, strict=False),
                    key=lambda x: x[0],
                    reverse=True,
                )
                # max pooling
                seen: set[tuple[tuple[str, ...], str]] = set()
@@ -452,7 +454,7 @@ class InMemoryStore(BaseStore):
                f"Number of embeddings ({len(embeddings)}) does not"
                f" match number of indices ({len(indices)})"
            )
-        for embedding, (ns, key, path) in zip(embeddings, indices):
+        for embedding, (ns, key, path) in zip(embeddings, indices, strict=False):
            self._vectors[ns][key][path] = embedding
    def _handle_list_namespaces(self, op: ListNamespacesOp) -> list[tuple[str, ...]]:
@@ -511,7 +513,7 @@ def _cosine_similarity(X: list[float], Y: list[list[float]]) -> list[float]:
    similarities = []
    for y in Y:
-        dot_product = sum(a * b for a, b in zip(X, y))
+        dot_product = sum(a * b for a, b in zip(X, y, strict=False))
        norm1 = sum(a * a for a in X) ** 0.5
        norm2 = sum(a * a for a in y) ** 0.5
        similarity = dot_product / (norm1 * norm2) if norm1 > 0 and norm2 > 0 else 0.0
@@ -529,14 +531,14 @@ def _does_match(match_condition: MatchCondition, key: tuple[str, ...]) -> bool:
        return False
    if match_type == "prefix":
-        for k_elem, p_elem in zip(key, path):
+        for k_elem, p_elem in zip(key, path, strict=False):
            if p_elem == "*":
                continue  # Wildcard matches any element
            if k_elem != p_elem:
                return False
        return True
    elif match_type == "suffix":
-        for k_elem, p_elem in zip(reversed(key), reversed(path)):
+        for k_elem, p_elem in zip(reversed(key), reversed(path), strict=False):
            if p_elem == "*":
                continue  # Wildcard matches any element
            if k_elem != p_elem:
@@ -563,7 +565,10 @@ def _compare_values(item_value: Any, filter_value: Any) -> bool:
        return (
            isinstance(item_value, (list, tuple))
            and len(item_value) == len(filter_value)
-            and all(_compare_values(iv, fv) for iv, fv in zip(item_value, filter_value))
+            and all(
                _compare_values(iv, fv)
                for iv, fv in zip(item_value, filter_value, strict=False)
            )
        )
    else:
        return item_value == filter_value
@@ -4,10 +4,10 @@ build-backend = "hatchling.build"
 [project]
 name = "langgraph-checkpoint"
-version = "2.1.1"
+version = "3.0.0"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 authors = []
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
@@ -20,20 +20,26 @@ dependencies = [
 Repository = "https://www.github.com/langchain-ai/langgraph"
 [dependency-groups]
-dev = [
+test = [
  "ruff",
  "codespell",
  "pytest",
  "pytest-asyncio",
  "pytest-mock",
  "pytest-watcher",
  "mypy",
  "dataclasses-json",
  "numpy",
  "pandas",
  "pandas-stubs>=2.2.2.240807",
  "redis",
 ]
 lint = [
  "ruff",
  "codespell",
  "mypy",
 ]
 dev = [
  {include-group = "test"},
  {include-group = "lint"},
 ]
 [tool.hatch.build.targets.wheel]
 include = ["langgraph"]
@@ -49,8 +55,10 @@ lint.select = [
  "UP", # pyupgrade
  "B",  # flake8-bugbear
  "I",  # isort
  "UP", # pyupgrade
 ]
 lint.ignore = ["E501", "B008"]
 target-version = "py310"
 [tool.pytest-watcher]
 now = true
@@ -1,4 +1,5 @@
 import dataclasses
 import json
 import pathlib
 import re
 import sys
@@ -19,6 +20,7 @@ from pydantic.v1 import BaseModel as BaseModelV1
 from pydantic.v1 import SecretStr as SecretStrV1
 from langgraph.checkpoint.serde.jsonplus import (
    InvalidModuleError,
    JsonPlusSerializer,
    _msgpack_ext_hook_to_json,
 )
@@ -60,22 +62,15 @@ class MyDataclass:
        pass
-if sys.version_info < (3, 10):
+@dataclasses.dataclass(slots=True)
 class MyDataclassWSlots:
    foo: str
    bar: int
    inner: InnerDataclass
-    class MyDataclassWSlots(MyDataclass):
+    def something(self) -> None:
        pass
 else:
    @dataclasses.dataclass(slots=True)
    class MyDataclassWSlots:
        foo: str
        bar: int
        inner: InnerDataclass
        def something(self) -> None:
            pass
 class MyEnum(Enum):
    FOO = "foo"
@@ -115,11 +110,7 @@ def test_serde_jsonplus() -> None:
        "my_dataclass": MyDataclass("foo", 1, InnerDataclass("hello")),
        "my_enum": MyEnum.FOO,
        "my_pydantic": MyPydantic(foo="foo", bar=1, inner=InnerPydantic(hello="hello")),
        "my_pydantic_v1": MyPydanticV1(
            foo="foo", bar=1, inner=InnerPydanticV1(hello="hello")
        ),
        "my_secret_str": SecretStr("meow"),
        "my_secret_str_v1": SecretStrV1("meow"),
        "person": Person(name="foo"),
        "a_bool": True,
        "a_none": None,
@@ -141,6 +132,12 @@ def test_serde_jsonplus() -> None:
        ),
    }
    if sys.version_info < (3, 14):
        to_serialize["my_pydantic_v1"] = MyPydanticV1(
            foo="foo", bar=1, inner=InnerPydanticV1(hello="hello")
        )
        to_serialize["my_secret_str_v1"] = SecretStrV1("meow")
    serde = JsonPlusSerializer()
    dumped = serde.dumps_typed(to_serialize)
@@ -165,10 +162,9 @@ def test_serde_jsonplus() -> None:
        "Text\ud83d\udcac",
        "收花🙄·到",
    ]
    serde = JsonPlusSerializer(pickle_fallback=True)
-    assert serde.loads_typed(serde.dumps_typed(surrogates)) == [
+    assert serde.loads_typed(serde.dumps_typed(surrogates)) == surrogates
        v.encode("utf-8", "ignore").decode() for v in surrogates
    ]
 def test_serde_jsonplus_json_mode() -> None:
@@ -197,11 +193,7 @@ def test_serde_jsonplus_json_mode() -> None:
        "my_dataclass": MyDataclass("foo", 1, InnerDataclass("hello")),
        "my_enum": MyEnum.FOO,
        "my_pydantic": MyPydantic(foo="foo", bar=1, inner=InnerPydantic(hello="hello")),
        "my_pydantic_v1": MyPydanticV1(
            foo="foo", bar=1, inner=InnerPydanticV1(hello="hello")
        ),
        "my_secret_str": SecretStr("meow"),
        "my_secret_str_v1": SecretStrV1("meow"),
        "person": Person(name="foo"),
        "a_bool": True,
        "a_none": None,
@@ -223,13 +215,20 @@ def test_serde_jsonplus_json_mode() -> None:
        ),
    }
    if sys.version_info < (3, 14):
        to_serialize["my_pydantic_v1"] = MyPydanticV1(
            foo="foo", bar=1, inner=InnerPydanticV1(hello="hello")
        )
        to_serialize["my_secret_str_v1"] = SecretStrV1("meow")
    serde = JsonPlusSerializer(__unpack_ext_hook__=_msgpack_ext_hook_to_json)
    dumped = serde.dumps_typed(to_serialize)
    assert dumped[0] == "msgpack"
    result = serde.loads_typed(dumped)
-    assert result == {
+
    expected_result = {
        "path": ["foo", "bar"],
        "re": ["foo", 48],
        "decimal": "1.10101",
@@ -253,9 +252,7 @@ def test_serde_jsonplus_json_mode() -> None:
        "my_dataclass": {"foo": "foo", "bar": 1, "inner": {"hello": "hello"}},
        "my_enum": "foo",
        "my_pydantic": {"foo": "foo", "bar": 1, "inner": {"hello": "hello"}},
        "my_pydantic_v1": {"foo": "foo", "bar": 1, "inner": {"hello": "hello"}},
        "my_secret_str": "meow",
        "my_secret_str_v1": "meow",
        "person": {"name": "foo"},
        "a_bool": True,
        "a_none": None,
@@ -277,6 +274,16 @@ def test_serde_jsonplus_json_mode() -> None:
        },
    }
    if sys.version_info < (3, 14):
        expected_result["my_pydantic_v1"] = {
            "foo": "foo",
            "bar": 1,
            "inner": {"hello": "hello"},
        }
        expected_result["my_secret_str_v1"] = "meow"
    assert result == expected_result
 def test_serde_jsonplus_bytes() -> None:
    serde = JsonPlusSerializer()
@@ -288,6 +295,20 @@ def test_serde_jsonplus_bytes() -> None:
    assert serde.loads_typed(dumped) == some_bytes
 def test_deserde_invalid_module() -> None:
    serde = JsonPlusSerializer()
    load = {
        "lc": 2,
        "type": "constructor",
        "id": ["pprint", "pprint"],
        "kwargs": {"object": "HELLO"},
    }
    with pytest.raises(InvalidModuleError):
        serde._revive_lc2(load)
    serde = JsonPlusSerializer(allowed_json_modules=[("pprint", "pprint")])
    serde.loads_typed(("json", json.dumps(load).encode("utf-8")))
 def test_serde_jsonplus_bytearray() -> None:
    serde = JsonPlusSerializer()
@@ -364,7 +385,12 @@ def test_serde_jsonplus_numpy_array_json_hook(arr: np.ndarray) -> None:
                "str_col": ["a", None, "c"],
            }
        ),
-        pd.DataFrame({"cat_col": pd.Categorical(["a", "b", "a", "c"])}),
+        pytest.param(
            pd.DataFrame({"cat_col": pd.Categorical(["a", "b", "a", "c"])}),
            marks=pytest.mark.skipif(
                sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
            ),
        ),
        pd.DataFrame(
            {
                "int8": pd.array([1, 2, 3], dtype="int8"),
@@ -392,11 +418,25 @@ def test_serde_jsonplus_numpy_array_json_hook(arr: np.ndarray) -> None:
                "col3": np.random.rand(1000),
            }
        ),
-        pd.DataFrame(
+        pytest.param(
-            {"tz_datetime": pd.date_range("2024-01-01", periods=3, freq="D", tz="UTC")}
+            pd.DataFrame(
                {
                    "tz_datetime": pd.date_range(
                        "2024-01-01", periods=3, freq="D", tz="UTC"
                    )
                }
            ),
            marks=pytest.mark.skipif(
                sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
            ),
        ),
        pd.DataFrame({"timedelta": pd.to_timedelta([1, 2, 3], unit="D")}),
-        pd.DataFrame({"period": pd.period_range("2024-01", periods=3, freq="M")}),
+        pytest.param(
            pd.DataFrame({"period": pd.period_range("2024-01", periods=3, freq="M")}),
            marks=pytest.mark.skipif(
                sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
            ),
        ),
        pd.DataFrame({"interval": pd.interval_range(start=0, end=3, periods=3)}),
        pd.DataFrame({"unicode": ["Hello 🌍", "Python 🐍", "Data 📊"]}),
        pd.DataFrame({"mixed": [1, "string", [1, 2, 3], {"key": "value"}]}),
@@ -433,7 +473,12 @@ def test_serde_jsonplus_pandas_dataframe(df: pd.DataFrame) -> None:
        pd.Series([1, 2, None]),
        pd.Series([1.1, None, 3.3]),
        pd.Series(["a", None, "c"]),
-        pd.Series(pd.Categorical(["a", "b", "a", "c"])),
+        pytest.param(
            pd.Series(pd.Categorical(["a", "b", "a", "c"])),
            marks=pytest.mark.skipif(
                sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
            ),
        ),
        pd.Series([1, 2, 3], dtype="int8"),
        pd.Series([10, 20, 30], dtype="int16"),
        pd.Series([100, 200, 300], dtype="int32"),
@@ -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)
@@ -845,7 +845,7 @@ async def test_async_batched_vector_search_concurrent(
        ]
    )
-    for results, (query, filter_) in zip(all_results, search_queries):
+    for results, (query, filter_) in zip(all_results, search_queries, strict=False):
        assert len(results) > 0, f"No results for query '{query}' with filter {filter_}"
        for result in results:
@@ -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"
@@ -1,19 +1,15 @@
 from collections.abc import Sequence
 from typing import Annotated, Literal, TypedDict
 from langchain.chat_models import init_chat_model
 from langchain_community.tools.tavily_search import TavilySearchResults
 from langchain_core.messages import BaseMessage
 from langchain_openai import ChatOpenAI
 from langgraph.graph import END, StateGraph, add_messages
 from langgraph.prebuilt import ToolNode
-tools = [TavilySearchResults(max_results=1)]
+tools = []
 model_anth = init_chat_model("claude-3-7-sonnet-20250219", model_provider="anthropic")
 model_oai = ChatOpenAI(temperature=0)
 model_anth = model_anth.bind_tools(tools)
 model_oai = model_oai.bind_tools(tools)
@@ -35,10 +31,7 @@ def should_continue(state):
 # Define the function that calls the model
 def call_model(state, config):
-    if config["configurable"].get("model", "anthropic") == "anthropic":
+    model = model_oai
        model = model_anth
    else:
        model = model_oai
    messages = state["messages"]
    response = model.invoke(messages)
    # We return a list, because this will get added to the existing list
@@ -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==1.0.2"
 ]
@@ -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==1.0.1"
 ]
@@ -1,7 +1,9 @@
 {
    "python_version": "3.12",
    "dependencies": [
-      "."
+      ".",
      "./deps/additional_deps",
      "./deps/zuper_deps"
    ],
    "graphs": {
      "agent": "./agent.py:graph"
@@ -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",
  "langchain-anthropic==1.0.0a5",
  "langgraph==1.0.2"
 ]
 [tool.uv]
 prerelease = "allow"
@@ -1,6 +0,0 @@
 requests
 langchain_anthropic
 langchain_openai
 langchain_community
 langchain
 langgraph==1.0.0a2
@@ -0,0 +1,89 @@
 from collections.abc import Sequence
 from typing import Annotated, Literal, TypedDict
 from langchain_community.tools.tavily_search import TavilySearchResults
 from langchain_core.messages import BaseMessage
 from langchain_openai import ChatOpenAI
 from langgraph.graph import END, StateGraph, add_messages
 from langgraph.prebuilt import ToolNode
 tools = [TavilySearchResults(max_results=1)]
 model_oai = ChatOpenAI(temperature=0)
 model_oai = model_oai.bind_tools(tools)
 class AgentState(TypedDict):
    messages: Annotated[Sequence[BaseMessage], add_messages]
 # Define the function that determines whether to continue or not
 def should_continue(state):
    messages = state["messages"]
    last_message = messages[-1]
    # If there are no tool calls, then we finish
    if not last_message.tool_calls:
        return "end"
    # Otherwise if there is, we continue
    else:
        return "continue"
 # Define the function that calls the model
 def call_model(state, config):
    model = model_oai
    messages = state["messages"]
    response = model.invoke(messages)
    # We return a list, because this will get added to the existing list
    return {"messages": [response]}
 # Define the function to execute tools
 tool_node = ToolNode(tools)
 class ContextSchema(TypedDict):
    model: Literal["anthropic", "openai"]
 # Define a new graph
 workflow = StateGraph(AgentState, context_schema=ContextSchema)
 # Define the two nodes we will cycle between
 workflow.add_node("agent", call_model)
 workflow.add_node("action", tool_node)
 # Set the entrypoint as `agent`
 # This means that this node is the first one called
 workflow.set_entry_point("agent")
 # We now add a conditional edge
 workflow.add_conditional_edges(
    # First, we define the start node. We use `agent`.
    # This means these are the edges taken after the `agent` node is called.
    "agent",
    # Next, we pass in the function that will determine which node is called next.
    should_continue,
    # Finally we pass in a mapping.
    # The keys are strings, and the values are other nodes.
    # END is a special node marking that the graph should finish.
    # What will happen is we will call `should_continue`, and then the output of that
    # will be matched against the keys in this mapping.
    # Based on which one it matches, that node will then be called.
    {
        # If `tools`, then we call the tool node.
        "continue": "action",
        # Otherwise we finish.
        "end": END,
    },
 )
 # We now add a normal edge from `tools` to `agent`.
 # This means that after `tools` is called, `agent` node is called next.
 workflow.add_edge("action", "agent")
 # Finally, we compile it!
 # This compiles it into a LangChain Runnable,
 # meaning you can use it as you would any other runnable
 graph = workflow.compile()
@@ -0,0 +1,11 @@
 {
    "python_version": "3.12",
    "dependencies": [
      "."
    ],
    "graphs": {
      "agent": "./agent.py:graph"
    },
    "env": "../.env"
  }
@@ -0,0 +1,11 @@
 [project]
 name = "graph-prerelease-reqs"
 version = "0.1.0"
 description = "Test for prerelease stuff"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
  "langchain-openai==1.0.0a2",
  "langgraph==1.0.0a2",
  "langchain_community>=0.3.0",
 ]
--- a/Show More
+++ b/Show More