add missing build step

bump prebuilt.md
fix cassette hashing
2026-08-18 13:45:44 +02:00 · 2025-02-13 23:03:58 -08:00 · 2025-02-13 22:57:15 -08:00 · 2025-02-13 22:56:16 -08:00 · 2025-02-13 21:57:45 -08:00 · 2025-02-13 21:57:44 -08:00
756 changed files with 81933 additions and 87088 deletions
@@ -0,0 +1,88 @@
+# An action for setting up poetry install with caching.
+# Using a custom action since the default action does not
+# take poetry install groups into account.
+# Action code from:
+# https://github.com/actions/setup-python/issues/505#issuecomment-1273013236
+name: poetry-install-with-caching
+description: Poetry install with support for caching of dependency groups.
+
+inputs:
+  python-version:
+    description: Python version, supporting MAJOR.MINOR only
+    required: true
+
+  poetry-version:
+    description: Poetry version
+    required: true
+
+  cache-key:
+    description: Cache key to use for manual handling of caching
+    required: true
+
+runs:
+  using: composite
+  steps:
+    - uses: actions/setup-python@v5
+      name: Setup python ${{ inputs.python-version }}
+      id: setup-python
+      with:
+        python-version: ${{ inputs.python-version }}
+
+    - uses: actions/cache@v3
+      id: cache-bin-poetry
+      name: Cache Poetry binary - Python ${{ inputs.python-version }}
+      env:
+        SEGMENT_DOWNLOAD_TIMEOUT_MIN: "1"
+      with:
+        path: |
+          /opt/pipx/venvs/poetry
+        # This step caches the poetry installation, so make sure it's keyed on the poetry version as well.
+        key: bin-poetry-${{ runner.os }}-${{ runner.arch }}-py-${{ inputs.python-version }}-${{ inputs.poetry-version }}
+
+    - name: Refresh shell hashtable and fixup softlinks
+      if: steps.cache-bin-poetry.outputs.cache-hit == 'true'
+      shell: bash
+      env:
+        POETRY_VERSION: ${{ inputs.poetry-version }}
+        PYTHON_VERSION: ${{ inputs.python-version }}
+      run: |
+        set -eux
+
+        # Refresh the shell hashtable, to ensure correct `which` output.
+        hash -r
+
+        # `actions/cache@v3` doesn't always seem able to correctly unpack softlinks.
+        # Delete and recreate the softlinks pipx expects to have.
+        rm /opt/pipx/venvs/poetry/bin/python
+        cd /opt/pipx/venvs/poetry/bin
+        ln -s "$(which "python$PYTHON_VERSION")" python
+        chmod +x python
+        cd /opt/pipx_bin/
+        ln -s /opt/pipx/venvs/poetry/bin/poetry poetry
+        chmod +x poetry
+
+        # Ensure everything got set up correctly.
+        /opt/pipx/venvs/poetry/bin/python --version
+        /opt/pipx_bin/poetry --version
+
+    - name: Install poetry
+      if: steps.cache-bin-poetry.outputs.cache-hit != 'true'
+      shell: bash
+      env:
+        POETRY_VERSION: ${{ inputs.poetry-version }}
+        PYTHON_VERSION: ${{ inputs.python-version }}
+      # Install poetry using the python version installed by setup-python step.
+      run: pipx install "poetry==$POETRY_VERSION" --python '${{ steps.setup-python.outputs.python-path }}' --verbose
+
+    - name: Restore pip and poetry cached dependencies
+      uses: actions/cache@v3
+      env:
+        SEGMENT_DOWNLOAD_TIMEOUT_MIN: "4"
+      with:
+        path: |
+          ~/.cache/pip
+          ~/.cache/pypoetry/virtualenvs
+          ~/.cache/pypoetry/cache
+          ~/.cache/pypoetry/artifacts
+          ./.venv
+        key: py-deps-${{ runner.os }}-${{ runner.arch }}-py-${{ inputs.python-version }}-poetry-${{ inputs.poetry-version }}-${{ inputs.cache-key }}-${{ hashFiles('./poetry.lock') }}
@@ -3,6 +3,9 @@ name: CLI integration test
 on:
  workflow_call:

+env:
+  POETRY_VERSION: "1.7.1"
+
 jobs:
  build:
    runs-on: ubuntu-latest
@@ -22,14 +25,13 @@ jobs:
        uses: Ana06/get-changed-files@v2.3.0
        with:
          filter: "libs/cli/**"
-      - name: Set up Python ${{ matrix.python-version }}
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
        if: steps.changed-files.outputs.all
-        uses: astral-sh/setup-uv@v6
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: ${{ matrix.python-version }}
-          enable-cache: true
-          cache-suffix: "cli-integration-test"
-          ignore-nothing-to-cache: true
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: integration-test-cli
      - name: Setup env
        if: steps.changed-files.outputs.all
        working-directory: libs/cli/examples
@@ -69,3 +71,4 @@ jobs:
        working-directory: libs/cli/js-examples
        run: |
          langgraph build -t langgraph-test-e
+  
@@ -9,6 +9,8 @@ on:
        description: "From which folder this pipeline executes"

 env:
+  POETRY_VERSION: "1.7.1"
+
  # This env var allows us to get inline annotations when ruff has complaints.
  RUFF_OUTPUT_FORMAT: github

@@ -34,18 +36,38 @@ jobs:
        uses: Ana06/get-changed-files@v2.3.0
        with:
          filter: "${{ inputs.working-directory }}/**"
-      - name: Set up Python ${{ matrix.python-version }}
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
        if: steps.changed-files.outputs.all
-        uses: astral-sh/setup-uv@v6
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: ${{ matrix.python-version }}
-          enable-cache: true
-          cache-suffix: lint-${{ inputs.working-directory }}
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: lint-${{ inputs.working-directory }}
+
+      - name: Check Poetry File
+        if: steps.changed-files.outputs.all
+        shell: bash
+        working-directory: ${{ inputs.working-directory }}
+        run: poetry check
+
+      - name: Check lock file
+        if: steps.changed-files.outputs.all
+        shell: bash
+        working-directory: ${{ inputs.working-directory }}
+        run: poetry lock --check

      - name: Install dependencies
        if: steps.changed-files.outputs.all
+        # Also installs dev/lint/test/typing dependencies, to ensure we have
+        # type hints for as many of our libraries as possible.
+        # This helps catch errors that require dependencies to be spotted, for example:
+        # https://github.com/langchain-ai/langchain/pull/10249/files#diff-935185cd488d015f026dcd9e19616ff62863e8cde8c0bee70318d3ccbca98341
+        #
+        # If you change this configuration, make sure to change the `cache-key`
+        # in the `poetry_setup` action above to stop using the old cache.
+        # It doesn't matter how you change it, any change will cause a cache-bust.
        working-directory: ${{ inputs.working-directory }}
-        run: uv sync --frozen --group dev
+        run: poetry install --with dev

      - name: Get .mypy_cache to speed up mypy
        if: steps.changed-files.outputs.all
@@ -55,7 +77,7 @@ jobs:
        with:
          path: |
            ${{ inputs.working-directory }}/.mypy_cache
-          key: mypy-lint-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/uv.lock', inputs.working-directory)) }}
+          key: mypy-lint-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}

      - name: Analysing package code with our lint
        if: steps.changed-files.outputs.all
@@ -70,8 +92,17 @@ jobs:

      - name: Install test dependencies
        if: steps.changed-files.outputs.all
+        # Also installs dev/lint/test/typing dependencies, to ensure we have
+        # type hints for as many of our libraries as possible.
+        # This helps catch errors that require dependencies to be spotted, for example:
+        # https://github.com/langchain-ai/langchain/pull/10249/files#diff-935185cd488d015f026dcd9e19616ff62863e8cde8c0bee70318d3ccbca98341
+        #
+        # If you change this configuration, make sure to change the `cache-key`
+        # in the `poetry_setup` action above to stop using the old cache.
+        # It doesn't matter how you change it, any change will cause a cache-bust.
        working-directory: ${{ inputs.working-directory }}
-        run: uv sync --group dev
+        run: |
+          poetry install --with dev

      - name: Get .mypy_cache_test to speed up mypy
        if: steps.changed-files.outputs.all
@@ -81,7 +112,7 @@ jobs:
        with:
          path: |
            ${{ inputs.working-directory }}/.mypy_cache_test
-          key: mypy-test-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/uv.lock', inputs.working-directory)) }}
+          key: mypy-test-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}

      - name: Analysing tests with our lint
        if: steps.changed-files.outputs.all
@@ -8,6 +8,9 @@ on:
        type: string
        description: "From which folder this pipeline executes"

+env:
+  POETRY_VERSION: "1.7.1"
+
 jobs:
  build:
    runs-on: ubuntu-latest
@@ -23,12 +26,12 @@ jobs:
    name: "test #${{ matrix.python-version }}"
    steps:
      - uses: actions/checkout@v4
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: ${{ matrix.python-version }}
-          enable-cache: true
-          cache-suffix: test-${{ inputs.working-directory }}
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: test-${{ inputs.working-directory }}
      - name: Login to Docker Hub
        uses: docker/login-action@v3
        if: ${{ !github.event.pull_request.head.repo.fork }}
@@ -39,12 +42,14 @@ jobs:
      - name: Install dependencies
        shell: bash
        working-directory: ${{ inputs.working-directory }}
-        run: uv sync --frozen --group dev
+        run: |
+          poetry install --with dev

      - name: Run tests
        shell: bash
        working-directory: ${{ inputs.working-directory }}
-        run: make test
+        run: |
+          make test

      - name: Ensure the tests did not create any additional files
        shell: bash
@@ -3,6 +3,9 @@ name: test
 on:
  workflow_call:

+env:
+  POETRY_VERSION: "1.7.1"
+
 jobs:
  build:
    runs-on: ubuntu-latest
@@ -21,12 +24,12 @@ jobs:
    name: "test #${{ matrix.python-version }}"
    steps:
      - uses: actions/checkout@v4
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: ${{ matrix.python-version }}
-          enable-cache: true
-          cache-suffix: "test-langgraph"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: test-langgraph
      - name: Login to Docker Hub
        uses: docker/login-action@v3
        if: ${{ !github.event.pull_request.head.repo.fork }}
@@ -36,11 +39,13 @@ jobs:

      - name: Install dependencies
        shell: bash
-        run: uv sync --frozen --group dev
+        run: |
+          poetry install --with dev

      - name: Run tests
        shell: bash
-        run: make test_parallel
+        run: |
+          make test_parallel

      - name: Ensure the tests did not create any additional files
        shell: bash
@@ -9,11 +9,12 @@ on:
        description: "From which folder this pipeline executes"

 env:
+  POETRY_VERSION: "1.7.1"
  PYTHON_VERSION: "3.10"

 jobs:
  build:
-    if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/v0'
+    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest

    outputs:
@@ -23,12 +24,12 @@ jobs:
    steps:
      - uses: actions/checkout@v4

-      - name: Set up Python $${ env.PYTHON_VERSION }}
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: ${{ env.PYTHON_VERSION }}
-          enable-cache: true
-          cache-suffix: "release"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: release

      # We want to keep this build stage *separate* from the release stage,
      # so that there's no sharing of permissions between them.
@@ -42,7 +43,7 @@ jobs:
      # > from the publish job.
      # https://github.com/pypa/gh-action-pypi-publish#non-goals
      - name: Build project for distribution
-        run: uv build
+        run: poetry build
        working-directory: ${{ inputs.working-directory }}

      - name: Upload build
@@ -56,8 +57,8 @@ jobs:
        shell: bash
        working-directory: ${{ inputs.working-directory }}
        run: |
-          echo pkg-name=$(grep -m 1 "^name = " pyproject.toml | cut -d '"' -f 2)
-          echo version=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
+          echo pkg-name="$(poetry version | cut -d ' ' -f 1)" >> $GITHUB_OUTPUT
+          echo version="$(poetry version --short)" >> $GITHUB_OUTPUT

  publish:
    needs:
@@ -3,6 +3,9 @@ name: test
 on:
  workflow_call:

+env:
+  POETRY_VERSION: "1.7.1"
+
 jobs:
  build:
    runs-on: ubuntu-latest
@@ -18,12 +21,12 @@ jobs:
    name: "test #${{ matrix.python-version }}"
    steps:
      - uses: actions/checkout@v4
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: ${{ matrix.python-version }}
-          enable-cache: true
-          cache-suffix: "test-scheduler-kafka"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: test-scheduler-kafka
      - name: Login to Docker Hub
        uses: docker/login-action@v3
        if: ${{ !github.event.pull_request.head.repo.fork }}
@@ -33,11 +36,13 @@ jobs:

      - name: Install dependencies
        shell: bash
-        run: uv sync --frozen --group dev
+        run: |
+          poetry install --with dev

      - name: Run tests
        shell: bash
-        run: make test
+        run: |
+          make test

      - name: Ensure the tests did not create any additional files
        shell: bash
@@ -7,6 +7,9 @@ on:
    paths:
      - "libs/**"

+env:
+  POETRY_VERSION: "1.7.1"
+
 jobs:
  benchmark:
    runs-on: ubuntu-latest
@@ -16,14 +19,14 @@ jobs:
    steps:
      - uses: actions/checkout@v4
      - run: SHA=$(git rev-parse HEAD) && echo "SHA=$SHA" >> $GITHUB_ENV
-      - name: Set up Python 3.11
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python 3.11 + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: "3.11"
-          enable-cache: true
-          cache-suffix: "bench"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: bench
      - name: Install dependencies
-        run: uv sync --group dev
+        run: poetry install --with dev
      - name: Run benchmarks
        run: OUTPUT=out/benchmark-baseline.json make -s benchmark
      - name: Save outputs
@@ -5,6 +5,9 @@ on:
    paths:
      - "libs/**"

+env:
+  POETRY_VERSION: "1.7.1"
+
 jobs:
  benchmark:
    runs-on: ubuntu-latest
@@ -18,14 +21,14 @@ jobs:
        uses: Ana06/get-changed-files@v2.3.0
        with:
          format: json
-      - name: Set up Python 3.11
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python 3.11 + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: "3.11"
-          enable-cache: true
-          cache-suffix: "bench"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: bench
      - name: Install dependencies
-        run: uv sync --group dev
+        run: poetry install --with dev
      - name: Download baseline
        uses: actions/cache/restore@v4
        with:
@@ -40,7 +43,7 @@ jobs:
        run: |
          {
            echo 'OUTPUT<<EOF'
-            make -s benchmark-fast
+            make -s benchmark
            echo EOF
          } >> "$GITHUB_OUTPUT"
      - name: Compare benchmarks
@@ -50,7 +53,7 @@ jobs:
            echo 'OUTPUT<<EOF'
            mv out/benchmark-baseline.json out/main.json
            mv out/benchmark.json out/changes.json
-            uv run pyperf compare_to out/main.json out/changes.json --table --group-by-speed
+            poetry run pyperf compare_to out/main.json out/changes.json --table --group-by-speed
            echo EOF
          } >> "$GITHUB_OUTPUT"
      - name: Annotation
@@ -16,32 +16,11 @@ concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true

-jobs:
-  changes:
-    runs-on: ubuntu-latest
-    outputs:
-      python: ${{ steps.filter.outputs.python }}
-      sdk-js: ${{ steps.filter.outputs.sdk-js }}
-    steps:
-      - uses: actions/checkout@v4
-      - uses: dorny/paths-filter@v3
-        id: filter
-        with:
-          filters: |
-            python:
-              - 'libs/langgraph/**'
-              - 'libs/sdk-py/**'
-              - 'libs/cli/**'
-              - 'libs/checkpoint/**'
-              - 'libs/checkpoint-sqlite/**'
-              - 'libs/checkpoint-postgres/**'
-              - 'libs/scheduler-kafka/**'
-              - 'libs/prebuilt/**'
-            sdk-js:
-              - 'libs/sdk-js/**'
+env:
+  POETRY_VERSION: "1.7.1"

+jobs:
  lint:
-    needs: changes
    name: cd ${{ matrix.working-directory }}
    strategy:
      matrix:
@@ -54,16 +33,13 @@ jobs:
            "libs/checkpoint-sqlite",
            "libs/checkpoint-postgres",
            "libs/scheduler-kafka",
-            "libs/prebuilt",
          ]
-    if: needs.changes.outputs.python == 'true'
    uses: ./.github/workflows/_lint.yml
    with:
      working-directory: ${{ matrix.working-directory }}
    secrets: inherit

  test:
-    needs: changes
    name: cd ${{ matrix.working-directory }}
    strategy:
      matrix:
@@ -73,9 +49,7 @@ jobs:
            "libs/checkpoint",
            "libs/checkpoint-sqlite",
            "libs/checkpoint-postgres",
-            "libs/prebuilt",
          ]
-    if: needs.changes.outputs.python == 'true'
    uses: ./.github/workflows/_test.yml
    with:
      working-directory: ${{ matrix.working-directory }}
@@ -83,23 +57,17 @@ jobs:

  # NOTE: we're testing langgraph separately because it requires a different matrix
  test-langgraph:
-    needs: changes
-    if: needs.changes.outputs.python == 'true'
    name: "cd libs/langgraph"
    uses: ./.github/workflows/_test_langgraph.yml
    secrets: inherit

  # NOTE: we're testing scheduler-kafka separately because it requires a different matrix
  test-scheduler-kafka:
-    needs: changes
-    if: needs.changes.outputs.python == 'true'
    name: "cd libs/scheduler-kafka"
    uses: ./.github/workflows/_test_scheduler_kafka.yml
    secrets: inherit

  check-sdk-methods:
-    needs: changes
-    if: needs.changes.outputs.python == 'true'
    name: "Check SDK methods matching"
    runs-on: ubuntu-latest
    steps:
@@ -111,52 +79,12 @@ jobs:
      - name: Run check_sdk_methods script
        run: python .github/scripts/check_sdk_methods.py

-  check-schema:
-    needs: changes
-    if: needs.changes.outputs.python == 'true'
-    name: "Check CLI schema hasn't changed #${{ matrix.python-version }}"
-    runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        python-version:
-          - "3.11"
-    steps:
-      - uses: actions/checkout@v4
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@v6
-        with:
-          python-version: "3.11"
-          enable-cache: true
-          cache-suffix: "schema-check-cli"
-      - name: Install CLI dependencies
-        run: |
-          cd libs/cli
-          uv sync
-      - name: Generate schema and check for changes
-        run: |
-          cd libs/cli
-          # Create a temporary copy of the current schema
-          cp schemas/schema.json schemas/schema.current.json
-          # Generate new schema
-          uv run python generate_schema.py
-          # Compare the new schema with the original
-          if ! diff -q schemas/schema.json schemas/schema.current.json > /dev/null; then
-            echo "Error: Langgraph.json configuration schema has changed. Please run 'uv run python generate_schema.py' in the libs/cli directory and commit the changes."
-            diff schemas/schema.json schemas/schema.current.json
-            exit 1
-          fi
-          echo "Schema check passed - no changes detected"
-
  integration-test:
-    needs: changes
-    if: needs.changes.outputs.python == 'true'
    name: CLI integration test
    uses: ./.github/workflows/_integration_test.yml
    secrets: inherit

  lint-js:
-    needs: changes
-    if: needs.changes.outputs.sdk-js == 'true'
    runs-on: ubuntu-latest
    strategy:
      matrix:
@@ -181,8 +109,6 @@ jobs:
        run: yarn build

  test-js:
-    needs: changes
-    if: needs.changes.outputs.sdk-js == 'true'
    runs-on: ubuntu-latest
    strategy:
      matrix:
@@ -213,8 +139,6 @@ jobs:
        test,
        test-langgraph,
        test-scheduler-kafka,
-        check-sdk-methods,
-        check-schema,
        integration-test,
        test-js,
      ]
@@ -4,13 +4,14 @@ on:
  push:
    branches:
      - main
-      - v0
  pull_request:
    branches:
      - main
-      - v0
  workflow_dispatch:

+env:
+  POETRY_VERSION: "1.7.1"
+
 permissions:
  contents: read
  pages: write
@@ -37,13 +38,12 @@ jobs:
        with:
          filter: "docs/docs/**"

-  # TODO: Uncomment this to run on PRs
-  # run-changed-notebooks:
-  #   needs: get-changed-files
-  #   uses: ./.github/workflows/run_notebooks.yml
-  #   secrets: inherit
-  #   with:
-  #     changed-files: ${{ needs.get-changed-files.outputs.changed-files }}
+  run-changed-notebooks:
+    needs: get-changed-files
+    uses: ./.github/workflows/run_notebooks.yml
+    secrets: inherit
+    with:
+      changed-files: ${{ needs.get-changed-files.outputs.changed-files }}

  deploy:
    # needs: run-changed-notebooks
@@ -56,23 +56,49 @@ jobs:
        with:
          fetch-depth: 0

-      - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+      - uses: actions/checkout@v4
+        with:
+          repository: langchain-ai/langchainjs
+          token: ${{ secrets.MKDOCS_GITHUB_TOKEN }}
+          path: docs/langchainjs
+
+      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: "3.12"
-          enable-cache: true
-          cache-suffix: "docs"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: docs
+
+      - name: Use Node.js
+        uses: actions/setup-node@v3
+        with:
+          node-version: "22"
+          cache: "yarn"
+          cache-dependency-path: docs/yarn.lock

      - name: Install dependencies
        run: |
+          cd langchainjs && yarn && yarn build && cd ..
          yarn
-          uv sync --all-groups
+          poetry install --with test --with docs --no-root
+          poetry run pip install -U \
+            pytest \
+            pytest-check-links \
+            GitPython \
+            "git+https://github.com/benjamincburns/markdown-exec.git@cc0d39d737e5ffd4b83d23cd8729d7ea16e363c8"
+
          # we run this installation only for internal PRs
          # as GITHUB_TOKEN is not available for PRs from outside contributors
          if [ -n "${GITHUB_TOKEN}" ]; then
-            uv run pip install "git+https://${GITHUB_TOKEN}@github.com/langchain-ai/mkdocs-material-insiders.git"
+            poetry run pip install "git+https://${GITHUB_TOKEN}@github.com/langchain-ai/mkdocs-material-insiders.git"
          fi

+          poetry run jupyter kernelspec list
+          poetry run python3 -m ipykernel install --user --name=python3
+          npm install -g tslab
+          poetry run tslab install --python=python3
+          poetry run jupyter kernelspec list
+
      - name: Run unit tests
        # Run unit tests on the docs build pipeline
        run: make tests
@@ -83,14 +109,7 @@ jobs:
      - name: Build llms-text
        run: make llms-text
      - name: Build site
-        run: |
-          # If this is v0 branch, then we want to download stats. we do this 
-          # with the env variable DOWNLOAD_STATS=true
-          if [ "${{ github.ref }}" == "refs/heads/v0" ]; then
-            DOWNLOAD_STATS=true make build-docs
-          else
-            make build-docs
-          fi
+        run: make build-docs
        env:
          MKDOCS_GIT_COMMITTERS_APIKEY: ${{ secrets.MKDOCS_GIT_COMMITTERS_APIKEY }}
          OPENAI_API_KEY: sf-proj-1234567890 # fake placeholder, shouldn't actually be used
@@ -98,15 +117,13 @@ jobs:
      - name: Check links in notebooks
        env:
          LANGCHAIN_API_KEY: test
-        if: github.event_name == 'schedule'
        run: |
-          if [ "${{ github.event_name }}" == "schedule" ]; then
+          if [ "${{ github.event_name }}" == "schedule" ] || [ "${{ github.event_name }}" == "workflow_dispatch" ] || ([ "${{ github.event_name }}" == "push" ] && [ "${{ github.ref }}" == "refs/heads/main" ]); then
            echo "Running link check on all HTML files matching notebooks in docs directory..."
-            uv run pytest -v \
+            poetry 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.*" \
@@ -116,7 +133,6 @@ jobs:
              --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
@@ -127,17 +143,15 @@ jobs:
            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 \
+              poetry 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
@@ -146,8 +160,8 @@ jobs:
          fi

      - name: Configure GitHub Pages
-        if: github.ref == 'refs/heads/v0'
-        uses: actions/configure-pages@v5
+        if: github.ref == 'refs/heads/main'
+        uses: actions/configure-pages@v4

      - name: Upload Pages Artifact
        # if: github.ref == 'refs/heads/main'
@@ -156,6 +170,6 @@ jobs:
          path: ./docs/site/

      - name: Deploy to GitHub Pages
-        if: github.ref == 'refs/heads/v0'
+        if: github.ref == 'refs/heads/main'
        id: deployment
        uses: actions/deploy-pages@v4
@@ -11,6 +11,9 @@ on:
    - cron: "0 5 * * *"
  workflow_dispatch:

+env:
+  POETRY_VERSION: "1.7.1"
+
 jobs:
  markdown-link-check:
    runs-on: ubuntu-latest
@@ -39,8 +42,8 @@ jobs:

      - name: Check README.md is in sync
        run: |
-          if ! diff -q README.md libs/langgraph/README.md >/dev/null; then
-          echo "README.md is out of sync with libs/langgraph/README.md"
-          diff -C 3 README.md libs/langgraph/README.md
-          exit 1
-          fi
+            if ! diff -q README.md libs/langgraph/README.md >/dev/null; then
+            echo "README.md is out of sync with libs/langgraph/README.md"
+            diff -C 3 README.md libs/langgraph/README.md
+            exit 1
+            fi
@@ -10,10 +10,11 @@ on:

 env:
  PYTHON_VERSION: "3.11"
+  POETRY_VERSION: "1.7.1"

 jobs:
  build:
-    if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/v0'
+    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest

    outputs:
@@ -25,12 +26,12 @@ jobs:
    steps:
      - uses: actions/checkout@v4

-      - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: ${{ env.PYTHON_VERSION }}
-          enable-cache: true
-          cache-suffix: "release"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: release

      # We want to keep this build stage *separate* from the release stage,
      # so that there's no sharing of permissions between them.
@@ -44,7 +45,7 @@ jobs:
      # > from the publish job.
      # https://github.com/pypa/gh-action-pypi-publish#non-goals
      - name: Build project for distribution
-        run: uv build
+        run: poetry build
        working-directory: ${{ inputs.working-directory }}

      - name: Upload build
@@ -58,8 +59,8 @@ jobs:
        shell: bash
        working-directory: ${{ inputs.working-directory }}
        run: |
-          PKG_NAME=$(grep -m 1 "^name = " pyproject.toml | cut -d '"' -f 2)
-          VERSION=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
+          PKG_NAME="$(poetry version | cut -d ' ' -f 1)"
+          VERSION="$(poetry version --short)"
          SHORT_PKG_NAME="$(echo "$PKG_NAME" | sed -e 's/langgraph//g' -e 's/-//g')"
          if [ -z $SHORT_PKG_NAME ]; then
            TAG="$VERSION"
@@ -162,11 +163,11 @@ jobs:
      # - The package is published, and it breaks on the missing dependency when
      #   used in the real world.

-      - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: ${{ env.PYTHON_VERSION }}
-          enable-cache: true
+          poetry-version: ${{ env.POETRY_VERSION }}

      - name: Import published package
        shell: bash
@@ -184,21 +185,17 @@ jobs:
        # - attempt install again after 5 seconds if it fails because there is
        #   sometimes a delay in availability on test pypi
        run: |
-          uv run pip install \
+          poetry run pip install \
            --extra-index-url https://test.pypi.org/simple/ \
            "$PKG_NAME==$VERSION" || \
          ( \
            sleep 5 && \
-            uv run pip install \
+            poetry run pip install \
              --extra-index-url https://test.pypi.org/simple/ \
              "$PKG_NAME==$VERSION" \
          )

-          if [[ "$PKG_NAME" == *prebuilt* ]]; then
-            uv run pip install langgraph
-          fi
-
-          if [[ "$PKG_NAME" == *checkpoint* || "$PKG_NAME" == *prebuilt* ]]; then
+          if [[ "$PKG_NAME" == *checkpoint* ]]; then
            # since checkpoint packages are namespace packages, import them with . convention
            # i.e. import langgraph.checkpoint or langgraph.checkpoint.sqlite
            IMPORT_NAME="$(echo "$PKG_NAME" | sed s/-/./g)"
@@ -208,10 +205,10 @@ jobs:
            IMPORT_NAME="$(echo "$PKG_NAME" | sed s/-/_/g)"
          fi

-          uv run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
+          poetry run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"

      - name: Import test dependencies
-        run: uv sync --group dev
+        run: poetry install --with dev
        working-directory: ${{ inputs.working-directory }}

      # Overwrite the local version of the package with the test PyPI version.
@@ -222,7 +219,7 @@ jobs:
          PKG_NAME: ${{ needs.build.outputs.pkg-name }}
          VERSION: ${{ needs.build.outputs.version }}
        run: |
-          uv run pip install \
+          poetry run pip install \
            --extra-index-url https://test.pypi.org/simple/ \
            "$PKG_NAME==$VERSION"

@@ -252,12 +249,12 @@ jobs:
    steps:
      - uses: actions/checkout@v4

-      - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: ${{ env.PYTHON_VERSION }}
-          enable-cache: true
-          cache-suffix: "release"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: release

      - uses: actions/download-artifact@v4
        with:
@@ -293,12 +290,12 @@ jobs:
    steps:
      - uses: actions/checkout@v4

-      - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
        with:
          python-version: ${{ env.PYTHON_VERSION }}
-          enable-cache: true
-          cache-suffix: "release"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: release

      - uses: actions/download-artifact@v4
        with:
@@ -9,7 +9,7 @@ on:
        type: string
        description: "JSON string of changed files"
  schedule:
-    - cron: "0 13 * * *"
+    - cron: '0 13 * * *'

 defaults:
  run:
@@ -27,43 +27,43 @@ jobs:
    steps:
      - uses: actions/checkout@v4
      - name: Set up Python + Poetry
-        uses: astral-sh/setup-uv@v6
+        uses: "./.github/actions/poetry_setup"
        with:
-          python-version: "3.11"
-          enable-cache: true
-          cache-suffix: "test-langgraph-notebooks"
+          python-version: 3.11
+          poetry-version: 1.7.1
+          cache-key: test-langgraph-notebooks

      - name: Install dependencies
        run: |
-          uv sync --group test
-          uv run pip install jupyter
+          poetry install --with test
+          poetry run pip install jupyter

      - name: Start services
        run: make start-services

      - name: Pre-download tiktoken files
        run: |
-          uv run python _scripts/download_tiktoken.py
+          poetry run python _scripts/download_tiktoken.py

      - name: Prepare notebooks
        run: |
          if [ "${{ matrix.lib-version }}" = "development" ]; then
-            uv run python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
+            poetry run python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
          else
-            uv run python _scripts/prepare_notebooks_for_ci.py
+            poetry run python _scripts/prepare_notebooks_for_ci.py
          fi

      - name: Run notebooks
        env:
          # these won't actually be used because of the VCR cassettes
          # but need to set them to avoid triggering getpass()
-          OPENAI_API_KEY: "very-secret-key"
-          ANTHROPIC_API_KEY: "very-secret-key"
-          TAVILY_API_KEY: "very-secret-key"
-          LANGSMITH_API_KEY: "very-secret-key"
-          NOMIC_API_KEY: "very-secret-key"
-          COHERE_API_KEY: "very-secret-key"
-          FIREWORKS_API_KEY: "very-secret-key"
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+          ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
+          TAVILY_API_KEY: ${{ secrets.TAVILY_API_KEY }}
+          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
+          NOMIC_API_KEY: ${{ secrets.NOMIC_API_KEY }}
+          COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
+          FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
        run: |
          if [ "${{ github.event_name }}" = "workflow_dispatch" ] || [ "${{ github.event_name }}" = "schedule" ]; then
            echo "Running all notebooks"
@@ -0,0 +1,29 @@
+name: Check File Size
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - main
+  workflow_dispatch:
+
+jobs:
+  file-size-check:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: Get changed files
+        id: changed-files
+        uses: tj-actions/changed-files@v44
+      - name: Filter by size
+        # TODO: roll back the web voyager hack
+        run: |
+          large_added_files=$(find ${{ steps.changed-files.outputs.added_files }} -maxdepth 0 -size +1M | grep -v "web_voyager" || true)
+          if [ -n "$large_added_files" ]; then
+            echo "Large files added: $large_added_files"
+            echo "# Large files added:" >> $GITHUB_STEP_SUMMARY
+            echo "$large_added_files" >> $GITHUB_STEP_SUMMARY
+            exit 1
+          fi
@@ -180,4 +180,3 @@ Chinook.db

 .vercel
 .turbo
-.editorconfig
@@ -153,7 +153,7 @@ Each category serves a distinct purpose and requires a specific approach to writ

 Here are some other guidelines you should think about when writing and organizing documentation.

-We generally do not merge new tutorials from outside contributors without an actual need.
+We generally do not merge new tutorials from outside contributors without an actue need.
 We welcome updates as well as new integration docs, how-tos, and references.

 ### Avoid duplication
@@ -227,7 +227,6 @@ see a preview of the documentation on the pull request page.

 From the **monorepo root**, run the following command to install the dependencies:

-<!-- TODO -->
 ```bash
 poetry install --with docs --no-root
 ```
@@ -1,84 +1,339 @@
-<picture class="github-only">
-  <source media="(prefers-color-scheme: light)" srcset="https://langchain-ai.github.io/langgraph/static/wordmark_dark.svg">
-  <source media="(prefers-color-scheme: dark)" srcset="https://langchain-ai.github.io/langgraph/static/wordmark_light.svg">
-  <img alt="LangGraph Logo" src="https://langchain-ai.github.io/langgraph/static/wordmark_dark.svg" width="80%">
-</picture>
+# 🦜🕸️LangGraph

-<div>
-<br>
-</div>
-
-[![Version](https://img.shields.io/pypi/v/langgraph.svg)](https://pypi.org/project/langgraph/)
+![Version](https://img.shields.io/pypi/v/langgraph)
 [![Downloads](https://static.pepy.tech/badge/langgraph/month)](https://pepy.tech/project/langgraph)
 [![Open Issues](https://img.shields.io/github/issues-raw/langchain-ai/langgraph)](https://github.com/langchain-ai/langgraph/issues)
 [![Docs](https://img.shields.io/badge/docs-latest-blue)](https://langchain-ai.github.io/langgraph/)
-[![GitMCP](https://img.shields.io/endpoint?url=https://gitmcp.io/badge/langchain-ai/langgraph)](https://gitmcp.io/langchain-ai/langgraph)

-Trusted by companies shaping the future of agents – including Klarna, Replit, Elastic, and more – LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents.
+⚡ Building language agents as graphs ⚡

-## Get started
+> [!NOTE]
+> Looking for the JS version? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://langchain-ai.github.io/langgraphjs/).

-Install LangGraph:
+## Overview

-```
+[LangGraph](https://langchain-ai.github.io/langgraph/) is a library for building
+stateful, multi-actor applications with LLMs, used to create agent and multi-agent
+workflows. Check out an introductory tutorial [here](https://langchain-ai.github.io/langgraph/tutorials/introduction/).
+
+
+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.
+
+### Why use LangGraph?
+
+LangGraph powers [production-grade agents](https://www.langchain.com/built-with-langgraph), trusted by Linkedin, Uber, Klarna, GitLab, and many more. LangGraph provides fine-grained control over both the flow and state of your agent applications. It implements a central [persistence layer](https://langchain-ai.github.io/langgraph/concepts/persistence/), enabling features that are common to most agent architectures:
+
+- **Memory**: LangGraph persists arbitrary aspects of your application's state,
+supporting memory of conversations and other updates within and across user
+interactions;
+- **Human-in-the-loop**: Because state is checkpointed, execution can be interrupted
+and resumed, allowing for decisions, validation, and corrections at key stages via
+human input.
+
+Standardizing these components allows individuals and teams to focus on the behavior
+of their agent, instead of its supporting infrastructure.
+
+Through [LangGraph Platform](#langgraph-platform), LangGraph also provides tooling for
+the development, deployment, debugging, and monitoring of your applications.
+
+LangGraph integrates seamlessly with
+[LangChain](https://python.langchain.com/docs/introduction/) and
+[LangSmith](https://docs.smith.langchain.com/) (but does not require them).
+
+To learn more about LangGraph, check out our first LangChain Academy
+course, *Introduction to LangGraph*, available for free
+[here](https://academy.langchain.com/courses/intro-to-langgraph).
+
+### LangGraph Platform
+
+[LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform) is infrastructure for deploying LangGraph agents. It is a commercial solution for deploying agentic applications to production, built on the open-source LangGraph framework. The LangGraph Platform consists of several components that work together to support the development, deployment, debugging, and monitoring of LangGraph applications: [LangGraph Server](https://langchain-ai.github.io/langgraph/concepts/langgraph_server) (APIs), [LangGraph SDKs](https://langchain-ai.github.io/langgraph/concepts/sdk) (clients for the APIs), [LangGraph CLI](https://langchain-ai.github.io/langgraph/concepts/langgraph_cli) (command line tool for building the server), and [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio) (UI/debugger).
+
+See deployment options [here](https://langchain-ai.github.io/langgraph/concepts/deployment_options/)
+(includes a free tier).
+
+Here are some common issues that arise in complex deployments, which LangGraph Platform addresses:
+
+- **Streaming support**: LangGraph Server provides [multiple streaming modes](https://langchain-ai.github.io/langgraph/concepts/streaming) optimized for various application needs
+- **Background runs**: Runs agents asynchronously in the background
+- **Support for long running agents**: Infrastructure that can handle long running processes
+- **[Double texting](https://langchain-ai.github.io/langgraph/concepts/double_texting)**: Handle the case where you get two messages from the user before the agent can respond
+- **Handle burstiness**: Task queue for ensuring requests are handled consistently without loss, even under heavy loads
+
+## Installation
+
+```shell
 pip install -U langgraph
 ```

-Then, create an agent [using prebuilt components](https://langchain-ai.github.io/langgraph/agents/agents/):
+## Example

-```python
-# pip install -qU "langchain[anthropic]" to call the model
+Let's build a tool-calling [ReAct-style](https://langchain-ai.github.io/langgraph/concepts/agentic_concepts/#react-implementation) agent that uses a search tool!

-from langgraph.prebuilt import create_react_agent
-
-def get_weather(city: str) -> str:
-    """Get weather for a given city."""
-    return f"It's always sunny in {city}!"
-
-agent = create_react_agent(
-    model="anthropic:claude-3-7-sonnet-latest",
-    tools=[get_weather],
-    prompt="You are a helpful assistant"
-)
-
-# Run the agent
-agent.invoke(
-    {"messages": [{"role": "user", "content": "what is the weather in sf"}]}
-)
+```shell
+pip install langchain-anthropic
 ```

-For more information, see the [Quickstart](https://langchain-ai.github.io/langgraph/agents/agents/). Or, to learn how to build an [agent workflow](https://langchain-ai.github.io/langgraph/concepts/low_level/) with a customizable architecture, long-term memory, and other complex task handling, see the [LangGraph basics tutorials](https://langchain-ai.github.io/langgraph/tutorials/get-started/1-build-basic-chatbot/).
+```shell
+export ANTHROPIC_API_KEY=sk-...
+```

-## Core benefits
+Optionally, we can set up [LangSmith](https://docs.smith.langchain.com/) for best-in-class observability.

-LangGraph provides low-level supporting infrastructure for *any* long-running, stateful workflow or agent. LangGraph does not abstract prompts or architecture, and provides the following central benefits:
+```shell
+export LANGSMITH_TRACING=true
+export LANGSMITH_API_KEY=lsv2_sk_...
+```

- [Durable execution](https://langchain-ai.github.io/langgraph/concepts/durable_execution/): Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off.
- [Human-in-the-loop](https://langchain-ai.github.io/langgraph/concepts/human_in_the_loop/): Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution.
- [Comprehensive memory](https://langchain-ai.github.io/langgraph/concepts/memory/): Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions.
- [Debugging with LangSmith](http://www.langchain.com/langsmith): Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics.
- [Production-ready deployment](https://langchain-ai.github.io/langgraph/concepts/deployment_options/): Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows.
+The simplest way to create a tool-calling agent in LangGraph is to use `create_react_agent`:

-## LangGraph’s ecosystem
+<details open>
+  <summary>High-level implementation</summary>

-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:
+```python
+from langgraph.prebuilt import create_react_agent
+from langgraph.checkpoint.memory import MemorySaver
+from langchain_anthropic import ChatAnthropic
+from langchain_core.tools import tool

- [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/).
- [LangChain](https://python.langchain.com/docs/introduction/) – Provides integrations and composable components to streamline LLM application development.
+# Define the tools for the agent to use
+@tool
+def search(query: str):
+    """Call to surf the web."""
+    # This is a placeholder, but don't tell the LLM that...
+    if "sf" in query.lower() or "san francisco" in query.lower():
+        return "It's 60 degrees and foggy."
+    return "It's 90 degrees and sunny."

-> [!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
+tools = [search]
+model = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)

- [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.).
- [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/tutorials/overview/): Guided examples on getting started with LangGraph.
- [LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph): Learn the basics of LangGraph in our free, structured course.
- [Templates](https://langchain-ai.github.io/langgraph/concepts/template_applications/): Pre-built reference apps for common agentic workflows (e.g. ReAct agent, memory, retrieval etc.) that can be cloned and adapted.
- [Case studies](https://www.langchain.com/built-with-langgraph): Hear how industry leaders use LangGraph to ship AI applications at scale.
+# Initialize memory to persist state between graph runs
+checkpointer = MemorySaver()

-## Acknowledgements
+app = create_react_agent(model, tools, checkpointer=checkpointer)

-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.
+# Use the agent
+final_state = app.invoke(
+    {"messages": [{"role": "user", "content": "what is the weather in sf"}]},
+    config={"configurable": {"thread_id": 42}}
+)
+final_state["messages"][-1].content
+```
+```
+"Based on the search results, I can tell you that the current weather in San Francisco is:\n\nTemperature: 60 degrees Fahrenheit\nConditions: Foggy\n\nSan Francisco is known for its microclimates and frequent fog, especially during the summer months. The temperature of 60°F (about 15.5°C) is quite typical for the city, which tends to have mild temperatures year-round. The fog, often referred to as "Karl the Fog" by locals, is a characteristic feature of San Francisco\'s weather, particularly in the mornings and evenings.\n\nIs there anything else you\'d like to know about the weather in San Francisco or any other location?"
+```
+
+Now when we pass the same <code>"thread_id"</code>, the conversation context is retained via the saved state (i.e. stored list of messages)
+
+```python
+final_state = app.invoke(
+    {"messages": [{"role": "user", "content": "what about ny"}]},
+    config={"configurable": {"thread_id": 42}}
+)
+final_state["messages"][-1].content
+```
+
+```
+"Based on the search results, I can tell you that the current weather in New York City is:\n\nTemperature: 90 degrees Fahrenheit (approximately 32.2 degrees Celsius)\nConditions: Sunny\n\nThis weather is quite different from what we just saw in San Francisco. New York is experiencing much warmer temperatures right now. Here are a few points to note:\n\n1. The temperature of 90°F is quite hot, typical of summer weather in New York City.\n2. The sunny conditions suggest clear skies, which is great for outdoor activities but also means it might feel even hotter due to direct sunlight.\n3. This kind of weather in New York often comes with high humidity, which can make it feel even warmer than the actual temperature suggests.\n\nIt's interesting to see the stark contrast between San Francisco's mild, foggy weather and New York's hot, sunny conditions. This difference illustrates how varied weather can be across different parts of the United States, even on the same day.\n\nIs there anything else you'd like to know about the weather in New York or any other location?"
+```
+</details>
+
+> [!TIP]
+> LangGraph is a **low-level** framework that allows you to implement any custom agent
+architectures. Click on the low-level implementation below to see how to implement a
+tool-calling agent from scratch.
+
+<details>
+<summary>Low-level implementation</summary>
+
+```python
+from typing import Literal
+
+from langchain_anthropic import ChatAnthropic
+from langchain_core.tools import tool
+from langgraph.checkpoint.memory import MemorySaver
+from langgraph.graph import END, START, StateGraph, MessagesState
+from langgraph.prebuilt import ToolNode
+
+
+# Define the tools for the agent to use
+@tool
+def search(query: str):
+    """Call to surf the web."""
+    # This is a placeholder, but don't tell the LLM that...
+    if "sf" in query.lower() or "san francisco" in query.lower():
+        return "It's 60 degrees and foggy."
+    return "It's 90 degrees and sunny."
+
+
+tools = [search]
+
+tool_node = ToolNode(tools)
+
+model = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0).bind_tools(tools)
+
+# Define the function that determines whether to continue or not
+def should_continue(state: MessagesState) -> Literal["tools", END]:
+    messages = state['messages']
+    last_message = messages[-1]
+    # If the LLM makes a tool call, then we route to the "tools" node
+    if last_message.tool_calls:
+        return "tools"
+    # Otherwise, we stop (reply to the user)
+    return END
+
+
+# Define the function that calls the model
+def call_model(state: MessagesState):
+    messages = state['messages']
+    response = model.invoke(messages)
+    # We return a list, because this will get added to the existing list
+    return {"messages": [response]}
+
+
+# Define a new graph
+workflow = StateGraph(MessagesState)
+
+# Define the two nodes we will cycle between
+workflow.add_node("agent", call_model)
+workflow.add_node("tools", tool_node)
+
+# Set the entrypoint as `agent`
+# This means that this node is the first one called
+workflow.add_edge(START, "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,
+)
+
+# 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("tools", 'agent')
+
+# Initialize memory to persist state between graph runs
+checkpointer = MemorySaver()
+
+# Finally, we compile it!
+# This compiles it into a LangChain Runnable,
+# meaning you can use it as you would any other runnable.
+# Note that we're (optionally) passing the memory when compiling the graph
+app = workflow.compile(checkpointer=checkpointer)
+
+# Use the agent
+final_state = app.invoke(
+    {"messages": [{"role": "user", "content": "what is the weather in sf"}]},
+    config={"configurable": {"thread_id": 42}}
+)
+final_state["messages"][-1].content
+```
+
+<b>Step-by-step Breakdown</b>:
+
+<details>
+<summary>Initialize the model and tools.</summary>
+<ul>
+  <li>
+    We use <code>ChatAnthropic</code> as our LLM. <strong>NOTE:</strong> we need to make sure the model knows that it has these tools available to call. We can do this by converting the LangChain tools into the format for OpenAI tool calling using the <code>.bind_tools()</code> method.
+  </li>
+  <li>
+    We define the tools we want to use - a search tool in our case. It is really easy to create your own tools - see documentation here on how to do that <a href="https://python.langchain.com/docs/how_to/custom_tools/">here</a>.
+  </li>
+</ul>
+</details>
+
+<details>
+<summary>Initialize graph with state.</summary>
+
+<ul>
+    <li>We initialize graph (<code>StateGraph</code>) by passing state schema (in our case <code>MessagesState</code>)</li>
+    <li><code>MessagesState</code> is a prebuilt state schema that has one attribute -- a list of LangChain <code>Message</code> objects, as well as logic for merging the updates from each node into the state.</li>
+</ul>
+</details>
+
+<details>
+<summary>Define graph nodes.</summary>
+
+There are two main nodes we need:
+
+<ul>
+    <li>The <code>agent</code> node: responsible for deciding what (if any) actions to take.</li>
+    <li>The <code>tools</code> node that invokes tools: if the agent decides to take an action, this node will then execute that action.</li>
+</ul>
+</details>
+
+<details>
+<summary>Define entry point and graph edges.</summary>
+
+First, we need to set the entry point for graph execution - <code>agent</code> node.
+
+Then we define one normal and one conditional edge. Conditional edge means that the destination depends on the contents of the graph's state (<code>MessagesState</code>). In our case, the destination is not known until the agent (LLM) decides.
+
+<ul>
+  <li>Conditional edge: after the agent is called, we should either:
+    <ul>
+      <li>a. Run tools if the agent said to take an action, OR</li>
+      <li>b. Finish (respond to the user) if the agent did not ask to run tools</li>
+    </ul>
+  </li>
+  <li>Normal edge: after the tools are invoked, the graph should always return to the agent to decide what to do next</li>
+</ul>
+</details>
+
+<details>
+<summary>Compile the graph.</summary>
+
+<ul>
+  <li>
+    When we compile the graph, we turn it into a LangChain 
+    <a href="https://python.langchain.com/docs/concepts/runnables/">Runnable</a>, 
+    which automatically enables calling <code>.invoke()</code>, <code>.stream()</code> and <code>.batch()</code> 
+    with your inputs
+  </li>
+  <li>
+    We can also optionally pass checkpointer object for persisting state between graph runs, and enabling memory, 
+    human-in-the-loop workflows, time travel and more. In our case we use <code>MemorySaver</code> - 
+    a simple in-memory checkpointer
+  </li>
+</ul>
+</details>
+
+<details>
+<summary>Execute the graph.</summary>
+
+<ol>
+  <li>LangGraph adds the input message to the internal state, then passes the state to the entrypoint node, <code>"agent"</code>.</li>
+  <li>The <code>"agent"</code> node executes, invoking the chat model.</li>
+  <li>The chat model returns an <code>AIMessage</code>. LangGraph adds this to the state.</li>
+  <li>Graph cycles the following steps until there are no more <code>tool_calls</code> on <code>AIMessage</code>:
+    <ul>
+      <li>If <code>AIMessage</code> has <code>tool_calls</code>, <code>"tools"</code> node executes</li>
+      <li>The <code>"agent"</code> node executes again and returns <code>AIMessage</code></li>
+    </ul>
+  </li>
+  <li>Execution progresses to the special <code>END</code> value and outputs the final state. And as a result, we get a list of all our chat messages as output.</li>
+</ol>
+</details>
+
+</details>
+
+## Documentation
+
+* [Tutorials](https://langchain-ai.github.io/langgraph/tutorials/): Learn to build with LangGraph through guided examples.
+* [How-to Guides](https://langchain-ai.github.io/langgraph/how-tos/): Accomplish specific things within LangGraph, from streaming, to adding memory & persistence, to common design patterns (branching, subgraphs, etc.), these are the place to go if you want to copy and run a specific code snippet.
+* [Conceptual Guides](https://langchain-ai.github.io/langgraph/concepts/high_level/): In-depth explanations of the key concepts and principles behind LangGraph, such as nodes, edges, state and more.
+* [API Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Review important classes and methods, simple examples of how to use the graph and checkpointing APIs, higher-level prebuilt components and more.
+* [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform): LangGraph Platform is a commercial solution for deploying agentic applications in production, built on the open-source LangGraph framework.
+
+## Resources
+
+* [Built with LangGraph](https://www.langchain.com/built-with-langgraph): Hear how industry leaders use LangGraph to ship powerful, production-ready AI applications.
+
+## Contributing
+
+For more information on how to contribute, see [here](https://github.com/langchain-ai/langgraph/blob/main/CONTRIBUTING.md).
@@ -0,0 +1,3 @@
+nodeLinker: node-modules
+
+yarnPath: .yarn/releases/yarn-3.5.1.cjs
@@ -10,32 +10,46 @@ build-prebuilt:
 	# Use to create an update to date prebuilt page.
 	# Looks up download stats for each of the prebuilt packages and
 	# generates the final prebuilt page.
-	@if [ "$(DOWNLOAD_STATS)" = "true" ]; then \
-		set -x; \
-		uv run python -m _scripts.third_party_page.get_download_stats stats.yml; \
-		set +x; \
-	else \
-		set -x; \
-		uv run python -m _scripts.third_party_page.get_download_stats --fake stats.yml; \
-		set +x; \
-	fi
-	uv run python -m _scripts.third_party_page.create_third_party_page stats.yml docs/agents/prebuilt.md --language python
+	poetry run python -m _scripts.third_party_page.get_download_stats stats.yml
+	poetry run python -m _scripts.third_party_page.create_third_party_page stats.yml docs/prebuilt.md --language python

-build-docs: build-typedoc build-prebuilt
-	uv run python -m mkdocs build --clean -f mkdocs.yml --strict
+grab-langgraphjs:
+	if [ -d "langgraphjs" ]; then \
+		if [ ! -d "langgraphjs/.git" ]; then \
+			rm -rf langgraphjs; \
+		fi \
+	fi
+	if [ ! -d "langgraphjs" ]; then \
+		git clone https://github.com/langchain-ai/langgraphjs.git; \
+	else \
+		cd langgraphjs && git checkout main && git pull; \
+	fi
+	cd langgraphjs && yarn
+	cd langgraphjs && yarn build
+	yarn
+
+build-docs: build-typedoc build-prebuilt grab-langgraphjs
+	poetry run python -m mkdocs build --clean -f mkdocs.yml --strict

 llms-text:
-	uv run python -m _scripts.generate_llms_text docs/llms-full.txt
+	poetry run python -m _scripts.generate_llms_text docs/llms-full.txt

 install-vercel-deps:
-	curl -sL "https://astral.sh/uv/install.sh" | bash -s
-	export PATH="${HOME}/.cargo/bin:${PATH}"
-	uv venv --python 3.11
-	uv sync --all-groups
+	dnf install -y python3.11
+	curl -sSL https://install.python-poetry.org | python3 -
+	poetry self update 1.8.5
+	# don't use vercel's python - it wasn't compiled with sqlite support, and it fails when installing ipython's kernel
+	poetry env use /usr/bin/python3.11
+	poetry install --with docs --with test --no-root
+	poetry run pip install "git+https://github.com/benjamincburns/markdown-exec.git@cc0d39d737e5ffd4b83d23cd8729d7ea16e363c8"
+	poetry run python3 -m ipykernel install --name=python3
+	npm install -g tslab
+	poetry run tslab install --python=python3
+	poetry run jupyter kernelspec list

 tests:
-	# Run unit tests
-	uv run pytest tests/unit_tests
+	# RUn unit tests
+	poetry run pytest tests/unit_tests


 vercel-build-docs: install-vercel-deps
@@ -43,10 +57,10 @@ vercel-build-docs: install-vercel-deps


 serve-clean-docs: clean-docs
-	uv run python -m mkdocs serve -c -f mkdocs.yml --strict -w ../libs/langgraph
+	poetry run python -m mkdocs serve -c -f mkdocs.yml --strict -w ../libs/langgraph

-serve-docs: build-typedoc
-	uv run python -m mkdocs serve -f mkdocs.yml -w ../libs/langgraph  -w ../libs/checkpoint -w ../libs/sdk-py --dirty
+serve-docs: build-typedoc grab-langgraphjs
+	poetry run python -m mkdocs serve -f mkdocs.yml -w ../libs/langgraph  -w ../libs/checkpoint -w ../libs/sdk-py --dirty

 clean-docs:
 	find ./docs -name "*.ipynb" -type f -delete
@@ -54,13 +68,13 @@ clean-docs:

 ## Run format against the project documentation.
 format-docs:
-	uv run ruff format docs
-	uv run ruff check --fix docs
+	poetry run ruff format docs
+	poetry run ruff check --fix docs

 # Check the docs for linting violations
 lint-docs:
-	uv run ruff format --check docs
-	uv run ruff check docs
+	poetry run ruff format --check docs
+	poetry run ruff check docs

 codespell:
 	./codespell_notebooks.sh .
@@ -3,7 +3,7 @@
 To setup requirements for building docs you can run:

 ```bash
-uv sync --group test
+poetry install --with test
 ```

 ## Serving documentation locally
@@ -14,8 +14,6 @@ To run the documentation server locally you can run:
 make serve-docs
 ```

-This will start the documentation server on [http://127.0.0.1:8000/langgraph/](http://127.0.0.1:8000/langgraph/).
-
 ## Execute notebooks

 If you would like to automatically execute all of the notebooks, to mimic the "Run notebooks" GHA, you can run:
@@ -58,4 +56,4 @@ To delete cassettes for a notebook, you can run:

 ```bash
 rm cassettes/<notebook_name>*
-```
+```
@@ -0,0 +1,77 @@
+import nock, { Definition } from "nock";
+import msgpack from "msgpack-lite";
+import zlib from "node:zlib";
+import fs from "node:fs/promises";
+import { Buffer } from "node:buffer";
+
+// deno style imports here because we're running this in the deno jupyter kernel
+
+interface NockCassetteData {
+  hash: string;
+  entries: Definition[];
+}
+
+// Utility functions for compression & serialization
+function compressData(data: NockCassetteData, compressionLevel = 9): string {
+  const packed = msgpack.encode(data);
+  const compressed = zlib.deflateSync(packed, { level: compressionLevel });
+  return compressed.toString("base64");
+}
+
+function decompressData(compressedString: string): NockCassetteData {
+  const decoded = Buffer.from(compressedString, "base64");
+  const decompressed = zlib.inflateSync(decoded);
+  return msgpack.decode(decompressed) as NockCassetteData;
+}
+
+class HashedCassette {
+  hash: string;
+  private recording = true;
+
+  constructor(
+    private readonly cassettePath: string,
+    hash: string
+  ) {
+    this.hash = hash;
+  }
+
+  async enter() {
+    try {
+      const rawCassette = await fs.readFile(this.cassettePath, "utf-8");
+      const data = decompressData(rawCassette);
+      if (data.hash === this.hash) {
+        this.recording = false;
+        nock.disableNetConnect();
+        nock.define(data.entries);
+        return;
+      }
+    } catch (error) {
+      if (error instanceof Error && error.message.includes("ENOENT")) {
+        this.recording = true;
+      } else {
+        throw error;
+      }
+    }
+
+    nock.recorder.rec({
+      dont_print: true,
+      output_objects: true,
+    });
+  }
+
+  async exit() {
+    if (this.recording) {
+      const entries = nock.recorder.play() as Definition[];
+      const data = {
+        hash: this.hash,
+        entries,
+      };
+      const compressed = compressData(data);
+      await fs.writeFile(this.cassettePath, compressed);
+    } else {
+      nock.enableNetConnect();
+      nock.restore();
+      nock.cleanAll();
+    }
+  }
+}
@@ -0,0 +1,107 @@
+import base64
+import os
+import zlib
+from types import TracebackType
+from typing import Optional, Any, Type
+
+import msgpack
+import vcr
+
+os.environ.pop("LANGCHAIN_TRACING_V2", None)
+custom_vcr = vcr.VCR()
+
+
+def compress_data(data: Any, compression_level: int = 9) -> str:
+    packed = msgpack.packb(data, use_bin_type=True)
+    compressed = zlib.compress(packed, level=compression_level)
+    return base64.b64encode(compressed).decode("utf-8")
+
+
+def decompress_data(compressed_string: str) -> Any:
+    decoded = base64.b64decode(compressed_string)
+    decompressed = zlib.decompress(decoded)
+    return msgpack.unpackb(decompressed, raw=False)
+
+
+class AdvancedCompressedSerializer:
+    def serialize(self, cassette_dict: Any) -> str:
+        return compress_data(cassette_dict)
+
+    def deserialize(self, cassette_string: str) -> Any:
+        return decompress_data(cassette_string)
+
+
+custom_vcr.register_serializer("advanced_compressed", AdvancedCompressedSerializer())
+custom_vcr.serializer = "advanced_compressed"
+
+
+class HashedCassette:
+    def __init__(self, cassette_path: str, hash_value: str) -> None:
+        """A context manager for using VCR cassettes with an embedded hash value.
+
+        Args:
+            cassette_path (str): The file path of the cassette (independent of hash).
+            hash_value (str): The expected hash value (e.g. a uuid string).
+
+        This class provides a context manager for using VCR cassettes with an embedded hash value.
+        The hash value is used to ensure that the cassette matches the expected state, and if not,
+        the cassette is removed or updated with the new hash value.
+        """
+        self.cassette_path: str = cassette_path
+        self.hash_value: str = hash_value
+        self.vcr: vcr.VCR = custom_vcr
+        self.cassette_context: Optional[Any] = None
+        self.exited: bool = False
+
+    def __enter__(self) -> Any:
+        self.exited: bool = False
+        # Get the serializer instance from the VCR instance.
+        serializer = self.vcr.serializers[self.vcr.serializer]
+        # If the cassette file exists, check its embedded hash.
+        if os.path.exists(self.cassette_path):
+            with open(self.cassette_path, "r") as f:
+                content = f.read()
+            try:
+                cassette_data = serializer.deserialize(content)
+            except Exception:
+                os.remove(self.cassette_path)
+            else:
+                existing_hash = cassette_data.get("cassette_hash")
+                if existing_hash != self.hash_value:
+                    os.remove(self.cassette_path)
+        # Now enter the VCR cassette context.
+        self.cassette_context = custom_vcr.use_cassette(
+            self.cassette_path,
+            filter_headers=["x-api-key", "authorization"],
+            record_mode="once",
+            serializer="advanced_compressed",
+        )
+        return self.cassette_context.__enter__()
+
+    def __exit__(
+        self,
+        exc_type: Optional[Type[BaseException]] = None,
+        exc_val: Optional[BaseException] = None,
+        exc_tb: Optional[TracebackType] = None,
+    ) -> Optional[bool]:
+        if self.exited:
+            return
+        self.exited = True
+        # Exit the VCR cassette context.
+        result = self.cassette_context.__exit__(exc_type, exc_val, exc_tb)
+        serializer = self.vcr.serializers[self.vcr.serializer]
+        # If a cassette was recorded (or updated), open and update its hash.
+        if os.path.exists(self.cassette_path):
+            with open(self.cassette_path, "r") as f:
+                content = f.read()
+            try:
+                cassette_data = serializer.deserialize(content)
+            except Exception:
+                return result
+            # Update the cassette data with the expected hash.
+            if cassette_data.get("cassette_hash") != self.hash_value:
+                cassette_data["cassette_hash"] = self.hash_value
+                serialized_data = serializer.serialize(cassette_data)
+                with open(self.cassette_path, "w") as f:
+                    f.write(serialized_data)
+        return result
@@ -8,7 +8,7 @@ execute_notebook() {
    file="$1"
    echo "Starting execution of $file"
    start_time=$(date +%s)
-    if ! output=$(time uv run jupyter execute "$file" 2>&1); then
+    if ! output=$(time poetry run jupyter execute "$file" 2>&1); then
        end_time=$(date +%s)
        execution_time=$((end_time - start_time))
        echo "Error in $file. Execution time: $execution_time seconds"
@@ -1,9 +1,12 @@
-import ast
 import importlib
+from importlib.machinery import ModuleSpec
+import importlib.util
+import inspect
 import logging
 import re
 from functools import lru_cache
-from typing import List, Optional
+import sys
+from typing import List, Literal, Optional

 from typing_extensions import TypedDict

@@ -22,12 +25,6 @@ MANUAL_API_REFERENCES_LANGGRAPH = [
        "create_react_agent",
        "prebuilt",
    ),
-    (
-        [],
-        "langgraph.prebuilt.chat_agent_executor",
-        "AgentState",
-        "prebuilt",
-    ),
    (["langgraph.prebuilt"], "langgraph.prebuilt.tool_node", "ToolNode", "prebuilt"),
    (
        ["langgraph.prebuilt"],
@@ -45,42 +42,26 @@ MANUAL_API_REFERENCES_LANGGRAPH = [
    (["langgraph.graph"], "langgraph.graph.message", "add_messages", "graphs"),
    (["langgraph.graph"], "langgraph.graph.state", "StateGraph", "graphs"),
    (["langgraph.graph"], "langgraph.graph.state", "CompiledStateGraph", "graphs"),
+    ([], "langgraph.types", "StreamMode", "types"),
    (["langgraph.graph"], "langgraph.constants", "START", "constants"),
    (["langgraph.graph"], "langgraph.constants", "END", "constants"),
    (["langgraph.constants"], "langgraph.types", "Send", "types"),
    (["langgraph.constants"], "langgraph.types", "Interrupt", "types"),
    (["langgraph.constants"], "langgraph.types", "interrupt", "types"),
    (["langgraph.constants"], "langgraph.types", "Command", "types"),
-    (["langgraph.config"], "langgraph.config", "get_stream_writer", "config"),
-    (["langgraph.config"], "langgraph.config", "get_store", "config"),
    (["langgraph.func"], "langgraph.func", "entrypoint", "func"),
    (["langgraph.func"], "langgraph.func", "task", "func"),
-    (["langgraph.types"], "langgraph.types", "RetryPolicy", "types"),
-    (["langgraph.types"], "langgraph.types", "StreamMode", "types"),
-    (["langgraph.types"], "langgraph.types", "StreamWriter", "types"),
+    ([], "langgraph.types", "RetryPolicy", "types"),
    ([], "langgraph.checkpoint.base", "Checkpoint", "checkpoints"),
    ([], "langgraph.checkpoint.base", "CheckpointMetadata", "checkpoints"),
    ([], "langgraph.checkpoint.base", "BaseCheckpointSaver", "checkpoints"),
    ([], "langgraph.checkpoint.base", "SerializerProtocol", "checkpoints"),
    ([], "langgraph.checkpoint.serde.jsonplus", "JsonPlusSerializer", "checkpoints"),
    ([], "langgraph.checkpoint.memory", "MemorySaver", "checkpoints"),
-    ([], "langgraph.checkpoint.memory", "InMemorySaver", "checkpoints"),
    ([], "langgraph.checkpoint.sqlite.aio", "AsyncSqliteSaver", "checkpoints"),
    ([], "langgraph.checkpoint.sqlite", "SqliteSaver", "checkpoints"),
    ([], "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.handoff", "create_forward_message_tool", "supervisor"),
-    (["langgraph_swarm"], "langgraph_swarm.swarm", "create_swarm", "swarm"),
-    (["langgraph_swarm"], "langgraph_swarm.swarm", "add_active_agent_router", "swarm"),
-    (["langgraph_swarm"], "langgraph_swarm.swarm", "SwarmState", "swarm"),
-    (["langgraph_swarm"], "langgraph_swarm.handoff", "create_handoff_tool", "swarm"),
-    ([], "langchain_mcp_adapters.client", "MultiServerMCPClient", "mcp"),
-    ([], "langchain_mcp_adapters.tools", "load_mcp_tools", "mcp"),
-    ([], "langchain_mcp_adapters.prompts", "load_mcp_prompt", "mcp"),
-    ([], "langchain_mcp_adapters.resources", "load_mcp_resources", "mcp"),
 ]

 WELL_KNOWN_LANGGRAPH_OBJECTS = {
@@ -90,154 +71,227 @@ WELL_KNOWN_LANGGRAPH_OBJECTS = {
 }


+def _make_regular_expression(pkg_prefix: str) -> re.Pattern:
+    if not pkg_prefix.isidentifier():
+        raise ValueError(f"Invalid package prefix: {pkg_prefix}")
+    return re.compile(
+        r"from\s+(" + pkg_prefix + r"(?:_\w+)?(?:\.\w+)*?)\s+import\s+\(?"
+        r"((?:\w+(?:,\s*)?)*)\s*\)?",  # Match zero or more words separated by a comma+optional ws
+        re.DOTALL,  # Match newlines as well
+    )
+
+
+# Regular expression to match langchain import lines
+_IMPORT_LANGCHAIN_RE = _make_regular_expression("langchain")
+_IMPORT_LANGGRAPH_RE = _make_regular_expression("langgraph")
+
+
@lru_cache(maxsize=10_000)
-def _get_full_module_name(module_path: str, class_name: str) -> Optional[str]:
+def _get_full_module_name(
+    module_path: str, class_name: str | None, doc_title: str
+) -> Optional[str]:
    """Get full module name using inspect, with LRU cache to memoize results."""
    try:
-        module = importlib.import_module(module_path)
-        symbol = getattr(module, class_name)
-        # First check the __module__ attribute on the symbol.
-        mod_name = getattr(symbol, "__module__", None)
-        # If __module__ is not set or comes from typing,
-        # assume the definition is in module_path.
-        if mod_name is None or mod_name.startswith("typing"):
-            return module_path
-        return mod_name
+        if module_path in sys.modules:
+            module = sys.modules[module_path]
+        else:
+            spec: ModuleSpec | None = importlib.util.find_spec(module_path)
+            if spec is not None:
+                module = importlib.util.module_from_spec(spec)
+                sys.modules[module_path] = module
+                spec.loader.exec_module(module)
+
+        if class_name is not None:
+            class_ = getattr(module, class_name)
+
+            if re.match(r"\w+\s+as\s+\w+", class_name):
+                # Handle cases like "A as B"
+                class_name, _ = class_name.split(" as ")
+
+            module = inspect.getmodule(class_)
+            if module is None:
+                # For constants, inspect.getmodule() might return None
+                # In this case, we'll return the original module_path
+                return module_path
+        return module.__name__
    except AttributeError as e:
-        logger.warning(f"API Reference: Could not find module for {class_name}, {e}")
+        if class_name is not None:
+            # the class_name might actually be a module
+            # e.g. from langchain import hub
+            # try to import it as a module, and if that doesn't work, throw
+            if class_name is not None:
+                module_name = _get_full_module_name(
+                    f"{module_path}.{class_name}", None, doc_title
+                )
+                if module_name is not None:
+                    # return the name of the parent module, rather than the name of the class as though it were a module
+                    return module.__name__
+                logger.warning(
+                    f"API Reference: Could not find module for {class_name} in {module_path}, imported in doc {doc_title}, {e}"
+                )
+            # don't log if we're trying to import the "hub" part as though it were a module
+        logger.warning(
+            f"API Reference: Could not find module for {module_path}, imported in doc {doc_title}, {e}"
+        )
        return None
    except ImportError as e:
-        logger.warning(f"API Reference: Failed to load for class {class_name}, {e}")
+        logger.warning(
+            f"API Reference: Failed to import module {module_path} {doc_title}, {e}"
+        )
        return None


+def _get_doc_title(data: str, file_name: str) -> str:
+    try:
+        return re.findall(r"^#\s*(.*)", data, re.MULTILINE)[0]
+    except IndexError:
+        pass
+    # Parse the rst-style titles
+    try:
+        return re.findall(r"^(.*)\n=+\n", data, re.MULTILINE)[0]
+    except IndexError:
+        return file_name
+
+
 class ImportInformation(TypedDict):
    imported: str  # The name of the class that was imported.
    source: str  # The full module path from which the class was imported.
    docs: str  # The URL pointing to the class's documentation.
-    path: str  # The path of the file where the markdown content originated.
+    title: str  # The title of the document where the import is used.


-def get_imports(code: str, path: str) -> List[ImportInformation]:
-    """Retrieve all import references from the given code for specified ecosystems.
+def _get_imports(
+    code: str, doc_title: str, package_ecosystem: Literal["langchain", "langgraph"]
+) -> List[ImportInformation]:
+    """Get imports from the given code block.

    Args:
-        code: The source code from which to extract import references.
-        path: The path of the file where the markdown content originated.
+        code: Python code block from which to extract imports
+        doc_title: Title of the document
+        package_ecosystem: "langchain" or "langgraph". The two live in different
+            repositories and have separate documentation sites.

    Returns:
-        A list of import information for each import found.
+        List of import information for the given code block
    """
-    # Parse the code into an AST.
-    try:
-        tree = ast.parse(code)
-    except SyntaxError:
-        return []
+    imports = []

-    found_imports = []
+    if package_ecosystem == "langchain":
+        pattern = _IMPORT_LANGCHAIN_RE
+    elif package_ecosystem == "langgraph":
+        pattern = _IMPORT_LANGGRAPH_RE
+    else:
+        raise ValueError(f"Invalid package ecosystem: {package_ecosystem}")

-    # Walk through the AST and process ImportFrom nodes.
-    for node in ast.walk(tree):
-        if isinstance(node, ast.ImportFrom):
-            # node.module is the source module.
-            if node.module is None:
+    for import_match in pattern.finditer(code):
+        module = import_match.group(1)
+        if "pydantic_v1" in module:
+            continue
+        imports_str = (
+            import_match.group(2).replace("(\n", "").replace("\n)", "")
+        )  # Handle newlines within parentheses
+        # remove any newline and spaces, then split by comma
+        imported_classes = [
+            imp.strip()
+            for imp in re.split(r",\s*", imports_str.replace("\n", ""))
+            if imp.strip()
+        ]
+        for class_name in imported_classes:
+            if module == "langchain_core.messages" and class_name == ")":
+                print("WARNING: ", file=sys.stderr)
+                print(
+                    f"WARNING: Trying to import {class_name} from {module} in doc {doc_title}",
+                    file=sys.stderr,
+                )
+                print("WARNING: ", file=sys.stderr)
+                print("WARNING:", import_match.group(0), file=sys.stderr)
+                print("WARNING: ", file=sys.stderr)
+                print(
+                    "\n".join([f"WARNING: {line}" for line in code.splitlines()]),
+                    file=sys.stderr,
+                )
+                print("WARNING: ", file=sys.stderr)
+
+            module_path = _get_full_module_name(module, class_name, doc_title)
+            if not module_path:
                continue
-            for alias in node.names:
-                if not (
-                    node.module.startswith("langchain")
-                    or node.module.startswith("langgraph")
-                ):
+            if len(module_path.split(".")) < 2:
+                continue
+
+            if package_ecosystem == "langchain":
+                pkg = module_path.split(".")[0].replace("langchain_", "")
+                top_level_mod = module_path.split(".")[1]
+
+                url = (
+                    _LANGCHAIN_API_REFERENCE
+                    + pkg
+                    + "/"
+                    + top_level_mod
+                    + "/"
+                    + module_path
+                    + "."
+                    + class_name
+                    + ".html"
+                )
+            elif package_ecosystem == "langgraph":
+                if (module, class_name) not in WELL_KNOWN_LANGGRAPH_OBJECTS:
+                    # Likely not documented yet
                    continue

-                found_imports.append(
-                    {
-                        "source": node.module,
-                        # alias.name is the original name even if an alias exists.
-                        "imported": alias.name,
-                    }
+                source_module, namespace = WELL_KNOWN_LANGGRAPH_OBJECTS[
+                    (module, class_name)
+                ]
+                url = (
+                    _LANGGRAPH_API_REFERENCE
+                    + namespace
+                    + "/#"
+                    + source_module
+                    + "."
+                    + class_name
                )
+            else:
+                raise ValueError(f"Invalid package ecosystem: {package_ecosystem}")

-    imports: list[ImportInformation] = []
-
-    for found_import in found_imports:
-        module = found_import["source"]
-
-        if module.startswith("langchain_mcp_adapters"):
-            package_ecosystem = "langgraph"
-        elif module.startswith("langchain"):
-            # Handles things like `langchain` or `langchain_anthropic`
-            package_ecosystem = "langchain"
-        elif module.startswith("langgraph"):
-            package_ecosystem = "langgraph"
-        else:
-            continue
-
-        class_name = found_import["imported"]
-        module_path = _get_full_module_name(module, class_name)
-        if not module_path:
-            continue
-        if len(module_path.split(".")) < 2:
-            continue
-
-        if package_ecosystem == "langchain":
-            pkg = module_path.split(".")[0].replace("langchain_", "")
-            top_level_mod = module_path.split(".")[1]
-
-            url = (
-                _LANGCHAIN_API_REFERENCE
-                + pkg
-                + "/"
-                + top_level_mod
-                + "/"
-                + module_path
-                + "."
-                + class_name
-                + ".html"
+            # Add the import information to our list
+            imports.append(
+                {
+                    "imported": class_name,
+                    "source": module,
+                    "docs": url,
+                    "title": doc_title,
+                }
            )
-        elif package_ecosystem == "langgraph":
-            if (module, class_name) not in WELL_KNOWN_LANGGRAPH_OBJECTS:
-                # Likely not documented yet
-                continue
-
-            source_module, namespace = WELL_KNOWN_LANGGRAPH_OBJECTS[
-                (module, class_name)
-            ]
-            url = (
-                _LANGGRAPH_API_REFERENCE
-                + namespace
-                + "/#"
-                + source_module
-                + "."
-                + class_name
-            )
-        else:
-            raise ValueError(f"Invalid package ecosystem: {package_ecosystem}")
-
-        # Add the import information to our list
-        imports.append(
-            {
-                "imported": class_name,
-                "source": module,
-                "docs": url,
-                "path": path,
-            }
-        )

    return imports


-def update_markdown_with_imports(markdown: str, path: str) -> str:
+def get_imports(code: str, doc_title: str) -> List[ImportInformation]:
+    """Retrieve all import references from the given code for specified ecosystems.
+
+    Args:
+        code: The source code from which to extract import references.
+        doc_title: The documentation title associated with the code.
+
+    Returns:
+        A list of import information for each import found.
+    """
+    ecosystems = ["langchain", "langgraph"]
+    all_imports = []
+    for package_ecosystem in ecosystems:
+        all_imports.extend(_get_imports(code, doc_title, package_ecosystem))
+    return all_imports
+
+
+def update_markdown_with_imports(markdown: str, file_name: str) -> str:
    """Update markdown to include API reference links for imports in Python code blocks.

-    This function scans the markdown content for Python code blocks, extracts any
-    imports, and appends links to their API documentation.
+    This function scans the markdown content for Python code blocks, extracts any imports, and appends links to their API documentation.

    Args:
        markdown: The markdown content to process.
-        path: The path of the file where the markdown content originated.

    Returns:
-        Updated markdown with API reference links prepended to Python code blocks.
+        Updated markdown with API reference links appended to Python code blocks.

    Example:
        Given a markdown with a Python code block:
@@ -245,8 +299,7 @@ def update_markdown_with_imports(markdown: str, path: str) -> str:
        ```python
        from langchain.nlp import TextGenerator
        ```
-        This function will append an API reference link to the `TextGenerator` class
-        from the `langchain.nlp` module if it's recognized.
+        This function will append an API reference link to the `TextGenerator` class from the `langchain.nlp` module if it's recognized.
    """
    code_block_pattern = re.compile(
        r"(?P<indent>[ \t]*)```(?P<language>python|py)\n(?P<code>.*?)\n(?P=indent)```",
@@ -260,12 +313,13 @@ def update_markdown_with_imports(markdown: str, path: str) -> str:
            match (re.Match): The regex match object containing the code block.

        Returns:
-            str: The modified code block with API reference links prepended if applicable.
+            str: The modified code block with API reference links appended if applicable.
        """
        indent = match.group("indent")
        code_block = match.group("code")
+        language = match.group("language")  # Preserve the language from the regex match
        # Retrieve import information from the code block
-        imports = get_imports(code_block, "__unused__")
+        imports = get_imports(code_block, file_name)

        original_code_block = match.group(0)
        # If no imports are found, return the original code block
@@ -276,8 +330,8 @@ def update_markdown_with_imports(markdown: str, path: str) -> str:
        api_links = " | ".join(
            f'<a href="{imp["docs"]}">{imp["imported"]}</a>' for imp in imports
        )
-        # Return the code block with prepended API reference links
-        return f"{indent}<sup><i>API Reference: {api_links}</i></sup>\n\n{original_code_block}"
+        # Return the code block with appended API reference links
+        return f"{original_code_block}\n\n{indent}API Reference: {api_links}"

    # Apply the replace_code_block function to all matches in the markdown
    updated_markdown = code_block_pattern.sub(replace_code_block, markdown)
@@ -1,19 +1,10 @@
 """Experimental script to generate consolidated llms text from the docs."""

-import asyncio
 import glob
 import os
-from typing import TypedDict, List, Optional
-import pydantic
-import re
-from pydantic import BaseModel, Field
-from langchain_core.rate_limiters import InMemoryRateLimiter

-import yaml
-from langchain.chat_models import init_chat_model
 from mkdocs.structure.files import File
 from mkdocs.structure.pages import Page
-from yaml import SafeLoader

 from _scripts.notebook_hooks import _on_page_markdown_with_config

@@ -22,59 +13,26 @@ HERE = os.path.dirname(os.path.abspath(__file__))
 SOURCE_DIR = os.path.abspath(os.path.join(os.path.dirname(HERE), "docs"))


-async def convert_ipynb_to_md(file_path: str) -> Optional[str]:
-    """Process a file (markdown or notebook) to markdown format.
-
-    Args:
-        file_path: Path to the file to process
-
-    Returns:
-        Processed markdown content if successful, None otherwise
-    """
-    rel_path = os.path.relpath(file_path, SOURCE_DIR)
-
-    # Create File and Page objects to match mkdocs structure
-    file_obj = File(
-        path=rel_path, src_dir=SOURCE_DIR, dest_dir="", use_directory_urls=True
-    )
-    page = Page(
-        title="",
-        file=file_obj,
-        config={},
-    )
-
-    try:
-        # Read raw content
-        with open(file_path, "r", encoding="utf-8") as f:
-            content = f.read()
-
-        # Convert to markdown without logic to resolve API references
-        processed_content = _on_page_markdown_with_config(
-            content, page, add_api_references=False, remove_base64_images=True
-        )
-        # Remove self-closing img tags <img ... />
-        processed_content = re.sub(r"<img[^>]*/>", "", processed_content)
-        # Remove img tags with content <img ...>...</img>
-        processed_content = re.sub(
-            r"<img[^>]*>.*?</img>", "", processed_content, flags=re.DOTALL
-        )
-        return processed_content
-    except Exception as e:
-        print(f"Error processing file {file_path}: {e}")
-        return None
-
-
-async def generate_full_llms_text(output_file: str) -> None:
+def _make_llms_text(output_file: str) -> str:
    """Generate a consolidated text file from markdown/notebook files for LLM training.

    Args:
        output_file: Path to output the consolidated text file
    """
    # Collect all markdown and notebook files
-    all_files = glob.glob(os.path.join(SOURCE_DIR, "how-tos/*.md"), recursive=True)
+    relative_paths = [
+        # Files relative to docs/docs/
+        "tutorials/introduction.ipynb",
+    ]
+    all_files = [os.path.join(SOURCE_DIR, path) for path in relative_paths]
+
+    all_files.extend(
+        glob.glob(os.path.join(SOURCE_DIR, "how-tos/*.md"), recursive=True)
+    )
    all_files.extend(
        glob.glob(os.path.join(SOURCE_DIR, "how-tos/*.ipynb"), recursive=True)
    )
+    # Add all concepts
    all_files.extend(
        glob.glob(os.path.join(SOURCE_DIR, "concepts/*.md"), recursive=True)
    )
@@ -84,14 +42,30 @@ async def generate_full_llms_text(output_file: str) -> None:

    all_content = []

-    # Process files concurrently
-    tasks = [convert_ipynb_to_md(file_path) for file_path in all_files]
-    results = await asyncio.gather(*tasks)
+    # Process each file
+    for file_path in all_files:
+        print(f"Processing {file_path}")
+        rel_path = os.path.relpath(file_path, SOURCE_DIR)

-    # Combine results with file paths
-    for file_path, processed_content in zip(all_files, results):
+        # Create File and Page objects to match mkdocs structure
+        file_obj = File(
+            path=rel_path, src_dir=SOURCE_DIR, dest_dir="", use_directory_urls=True
+        )
+        page = Page(
+            title="",
+            file=file_obj,
+            config={},
+        )
+
+        # Read raw content
+        with open(file_path, "r", encoding="utf-8") as f:
+            content = f.read()
+
+        # Convert to markdown without logic to resolve API references
+        processed_content = _on_page_markdown_with_config(
+            content, page, add_api_references=False, remove_base64_images=True
+        )
        if processed_content:
-            rel_path = os.path.relpath(file_path, SOURCE_DIR)
            # Add file name
            all_content.append(f"---\n{rel_path}\n---")
            # Add content
@@ -102,168 +76,6 @@ async def generate_full_llms_text(output_file: str) -> None:
        f.write("\n\n".join(all_content))


-def no_op_constructor(*args):
-    """No-op"""
-
-
-SafeLoader.add_multi_constructor(
-    "tag:yaml.org,2002:python/name",
-    no_op_constructor,
-)
-
-
-class NavItem(TypedDict):
-    title: str
-    url: str
-    hierarchy: tuple[str, ...]
-    description: str
-
-
-def _flatten_nav(
-    nav: list[dict[str, str | list] | str], path: tuple[str, ...] = ()
-) -> list[NavItem]:
-    flat: List[NavItem] = []
-    for item in nav:
-        if isinstance(item, dict):
-            for title, node in item.items():
-                new_path = path + (title,)
-                if isinstance(node, str):
-                    # Leaf page
-                    flat.append(
-                        {
-                            "title": title,
-                            "url": node,
-                            "hierarchy": new_path,
-                            "description": "",
-                        }
-                    )
-                elif isinstance(node, list):
-                    # Dive in, carrying along the updated path
-                    flat.extend(_flatten_nav(node, new_path))
-                else:
-                    raise TypeError(
-                        f"Unexpected node type {type(node)} under {title!r}"
-                    )
-        elif isinstance(item, str):
-            # Bare string entry → use itself as title, and as URL
-            new_path = path + (item,)
-            flat.append(
-                {"title": item, "url": item, "hierarchy": new_path, "description": ""}
-            )
-        else:
-            raise TypeError(f"Unexpected item type {type(item)} in nav")
-    return flat
-
-
-class PageInfo(BaseModel):
-    title: str = Field(description="The title of the page")
-    description: str = Field(
-        description="A short description of the page no longer than 3 sentences "
-        "explaining the kind of content that can be found in the page."
-    )
-
-
-async def process_nav_items(nav_items: list[NavItem]) -> list[NavItem]:
-    """Open the contents of each nav item and come up with a better title and description."""
-    rate_limiter = InMemoryRateLimiter(requests_per_second=10)
-    model = init_chat_model("gpt-4o-mini", temperature=0.0, rate_limiter=rate_limiter)
-    model = model.with_structured_output(PageInfo)
-
-    async def process_single_item(item: NavItem) -> NavItem:
-        path = item["url"]
-        file_path = os.path.join(SOURCE_DIR, path)
-
-        # Process the file content (handles both markdown and notebooks)
-        if path.endswith(".ipynb"):
-            content = await convert_ipynb_to_md(file_path)
-        else:
-            with open(file_path, "r", encoding="utf-8") as f:
-                content = f.read()
-
-        if not content:
-            return item
-
-        # Generate a better title and description
-        response = await model.ainvoke(
-            [
-                {
-                    "role": "system",
-                    "content": "You are a technical documentation writer. "
-                    "You are given a markdown page of documentation. "
-                    "Please come up with an appropriate title and "
-                    "description for the page. The description should "
-                    "be a short summary of the page content that is "
-                    "no longer than 3 sentences.",
-                },
-                {
-                    "role": "user",
-                    "content": "The markdown page is as follows:\n\n" + content,
-                },
-            ]
-        )
-        return {
-            "title": response.title,
-            "url": item["url"],
-            "hierarchy": item["hierarchy"],
-            "description": response.description,
-        }
-
-    # Remove any items that start with http:// or https:// looking only for
-    # local file at this stages.
-    nav_items = [
-        item for item in nav_items if not item["url"].startswith(("http://", "https://"))
-    ]
-    # Process items in parallel
-    tasks = [process_single_item(item) for item in nav_items]
-    new_nav_items = await asyncio.gather(*tasks)
-    return new_nav_items
-
-
-async def generate_nav_links_text(
-    output_file: str, *, replace_links: bool = False
-) -> None:
-    """Generate llms.txt from mkdocs.yaml."""
-    # Get path to mkdocs.yaml relative to this script
-    script_dir = os.path.dirname(os.path.abspath(__file__))
-    mkdocs_path = os.path.join(os.path.dirname(script_dir), "mkdocs.yml")
-
-    # Load and parse yaml
-    with open(mkdocs_path, "r") as f:
-        config = yaml.safe_load(f)
-
-    # Extract nav section
-    nav = config.get("nav", [])
-    flattened = _flatten_nav(nav)
-
-    processed_nav = await process_nav_items(flattened)
-
-    with open(output_file, "w") as f:
-        current_section = None
-        for item in processed_nav:
-            # Get the top-level section (first item in hierarchy)
-            section = item["hierarchy"][0]
-
-            if section not in {"Guides", "Examples", "Resources"}:
-                continue
-
-            # If we're starting a new section, add a heading
-            if section != current_section:
-                f.write(f"\n# {section}\n\n")
-                current_section = section
-
-            title = item["title"]
-            # Process URL based on replace_links flag
-            url = item["url"]
-            if replace_links:
-                # Remove .md extension and ensure single trailing slash
-                url = url.removesuffix(".md")
-                url = url.removesuffix(".ipynb")
-                url = url.rstrip("/") + "/"
-                url = f"https://langchain-ai.github.io/langgraph/{url}"
-
-            f.write(f"- [{title}]({url}): {item['description']}\n")
-
-
 if __name__ == "__main__":
    import argparse

@@ -273,23 +85,6 @@ if __name__ == "__main__":
        )
    )
    parser.add_argument("output_file", help="Path to output the consolidated text file")
-    parser.add_argument(
-        "--link-only",
-        action="store_true",
-        help="Only include link references in the output",
-    )
-    parser.add_argument(
-        "--replace-links",
-        action="store_true",
-        help="Replace markdown links with full URLs in the output",
-    )

    args = parser.parse_args()
-    if args.link_only:
-        coro = generate_nav_links_text(
-            args.output_file, replace_links=args.replace_links
-        )
-    else:
-        coro = generate_full_llms_text(args.output_file)
-
-    asyncio.run(coro)
+    _make_llms_text(args.output_file)
@@ -0,0 +1,4 @@
+hook_state = {
+    "document_filename": "__UNKNOWN__",
+    "document_content": "__UNKNOWN__",
+}
@@ -1,7 +1,10 @@
+import argparse
 import ast
+import glob
 import os
 import re
-from typing import Literal
+from pathlib import Path
+from typing import Literal, Optional

 import nbformat
 from nbconvert.exporters import MarkdownExporter
@@ -25,7 +28,7 @@ def _uses_input(source: str) -> bool:


 def _rewrite_cell_magic(code: str) -> str:
-    """Process a code block that uses cell magic.
+    """Process a code block that uses cell magic.:w

    - Lines starting with "%%capture" are ignored.
    - Lines starting with "%pip" are rewritten by removing the leading "%" character.
@@ -51,14 +54,10 @@ def _rewrite_cell_magic(code: str) -> str:
        if stripped.startswith("%%capture"):
            continue
        # Rewrite %pip lines by dropping the '%'
-        elif stripped.startswith("%") or stripped.startswith("!"):
-            # Drop the leading '%' character and then drop all leading whitespace
-            stripped = stripped.lstrip("%! \t")
-            # Check if the line starts with "pip"
-            if stripped.startswith("pip"):
-                rewritten_lines.append(stripped)
-            else:
-                raise NotImplementedError(f"Unhandled line: {line}")
+        elif stripped.startswith("%pip"):
+            # Drop the leading '%' character
+            rewritten_lines.append(stripped[1:])
+        # Anything else is not supported
        else:
            raise NotImplementedError(f"Unhandled line: {line}")

@@ -220,24 +219,6 @@ def _convert_links_in_markdown(markdown: str) -> str:
    )


-class HideCellTagPreprocessor(Preprocessor):
-    """
-    Removes cells that have '# hide-cell' at the beginning of the cell content.
-    This allows authors to include cells in the notebook that should not
-    appear in the generated markdown output.
-    """
-
-    def preprocess(self, nb, resources):
-        # Filter out cells with the '# hide-cell' comment at the beginning
-        nb.cells = [
-            cell
-            for cell in nb.cells
-            if not (cell.source.strip().startswith("# hide-cell"))
-        ]
-
-        return nb, resources
-
-
 class EscapePreprocessor(Preprocessor):
    def __init__(self, markdown_exec_migration: bool = False, **kwargs) -> None:
        super().__init__(**kwargs)
@@ -268,10 +249,13 @@ class EscapePreprocessor(Preprocessor):
            )
            cell.metadata["exec"] = is_exec

-            # For markdown exec migration we'll re-write cell magic as bash commands
-            if source.startswith("%%"):
-                cell.source = _rewrite_cell_magic(source)
-                cell.metadata["language"] = "shell"
+            if self.markdown_exec_migration:
+                # For markdown exec migration we'll re-write cell magic as bash commands
+                if source.startswith("%%"):
+                    cell.source = _rewrite_cell_magic(source)
+                    cell.metadata["language"] = "shell"
+
+                cell.metadata["has_output"] = _has_output(source)

            # Remove noqa comments
            cell.source = re.sub(r"#\s*noqa.*$", "", cell.source, flags=re.MULTILINE)
@@ -359,7 +343,6 @@ class ExtractAttachmentsPreprocessor(Preprocessor):

 exporter = MarkdownExporter(
    preprocessors=[
-        HideCellTagPreprocessor,
        EscapePreprocessor,
        ExtractAttachmentsPreprocessor,
    ],
@@ -369,14 +352,119 @@ exporter = MarkdownExporter(
    ],
 )

+md_executable = MarkdownExporter(
+    preprocessors=[
+        ExtractAttachmentsPreprocessor,
+        EscapePreprocessor(markdown_exec_migration=True),
+    ],
+    template_name="md_executable",
+    extra_template_basedirs=[
+        os.path.join(os.path.dirname(__file__), "notebook_convert_templates")
+    ],
+)
+

 def convert_notebook(
-    notebook_path: str,
+    notebook_path: Path,
    mode: Literal["markdown", "exec"] = "markdown",
 ) -> str:
    with open(notebook_path) as f:
        nb = nbformat.read(f, as_version=4)

    nb.metadata.mode = mode
-    body, _ = exporter.from_notebook_node(nb)
+    if mode == "markdown":
+        body, _ = exporter.from_notebook_node(nb)
+    else:
+        body, _ = md_executable.from_notebook_node(nb)
    return body
+
+
+HERE = Path(__file__).parent
+DOCS = HERE.parent / "docs"
+
+
+# Convert notebooks to markdown
+def _convert_notebooks(
+    *,
+    output_dir: Optional[Path] = None,
+    replace: bool = False,
+    pattern: str = "*.ipynb",
+) -> None:
+    """Converting notebooks."""
+    if not output_dir and not replace:
+        raise ValueError("Either --output_dir or --replace must be specified")
+
+    output_dir_path = DOCS if replace else Path(output_dir)
+
+    # Get the directory where the script was executed
+    base_dir = os.getcwd()
+    # Build the full search pattern using the current working directory as the base
+    full_pattern = os.path.join(base_dir, args.pattern)
+
+    # Use glob with recursive search enabled
+    matching_files = glob.glob(full_pattern, recursive=True)
+    paths = [Path(file) for file in matching_files]
+
+    file_names = [notebook.name for notebook in paths]
+
+    for notebook in paths:
+        markdown = convert_notebook(notebook, mode="exec")
+        markdown_path = output_dir_path / notebook.relative_to(DOCS).with_suffix(".md")
+        markdown_path.parent.mkdir(parents=True, exist_ok=True)
+        with open(markdown_path, "w") as f:
+            f.write(markdown)
+        if replace:
+            notebook.unlink(missing_ok=False)
+
+    if replace:
+        # The regex will match markdown links that point to *.ipynb files.
+        # It captures:
+        #   group(1): the link text (inside the square brackets)
+        #   group(2): the file path (without the trailing .ipynb)
+        link_pattern = r"(?<!!)\[([^\]]+)\]\((?![^)]*//)([^)]+)\.ipynb\)"
+
+        def replace_link(match: re.Match) -> str:
+            link_text = match.group(1)
+            link_target = match.group(2)
+            # Reconstruct the file name with the .ipynb extension.
+            # For example, if link_target is "foo/bar", then linked_file becomes "bar.ipynb".
+            linked_file = Path(link_target).name + ".ipynb"
+            # Only update if the notebook was among those converted.
+            if linked_file in file_names:
+                # Change the extension from .ipynb to .md
+                return f"[{link_text}]({link_target}.md)"
+            # Otherwise, leave the original link intact.
+            return match.group(0)
+
+        # Process all markdown files in the output directory.
+        for path in output_dir_path.rglob("**/*.md"):
+            with open(path, "r", encoding="utf-8") as f:
+                content = f.read()
+            new_content = re.sub(link_pattern, replace_link, content)
+            with open(path, "w", encoding="utf-8") as f:
+                f.write(new_content)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Convert notebooks to markdown")
+    parser.add_argument(
+        "--output_dir",
+        default=None,
+        help="Directory to output markdown files",
+    )
+    parser.add_argument(
+        "--replace",
+        action="store_true",
+        help="Replace original notebooks with markdown files",
+    )
+    parser.add_argument(
+        "--pattern",
+        default="*.ipynb",
+        help="Glob pattern to match notebooks to convert",
+    )
+    args = parser.parse_args()
+    _convert_notebooks(
+        replace=args.replace,
+        output_dir=args.output_dir,
+        pattern=args.pattern,
+    )
@@ -0,0 +1,5 @@
+{
+  "mimetypes": {
+    "text/markdown": true
+  }
+}
@@ -0,0 +1,38 @@
+{#https://github.com/rdbisme/nbconvert/blob/master/share/jupyter/nbconvert/templates/markdown/index.md.j2#}
+{% extends 'markdown/index.md.j2' %}
+
+{% block input %}
+```
+{%- if 'magics_language' in cell.metadata  -%}
+    {{ cell.metadata.magics_language}}
+{%- elif cell.metadata.get('language') == "shell" -%}
+    shell
+{%- elif 'name' in nb.metadata.get('language_info', {}) -%}
+    {{ nb.metadata.language_info.name }}{% if cell.metadata.exec|default(false) %} exec="on" source="above" session="1"{% if cell.metadata.has_output|default(false) %} result="ansi"{% endif %}{% endif %}
+{%- endif %}
+{{ cell.source}}
+```
+{% endblock input %}
+
+{%- block traceback_line -%}
+{%- endblock traceback_line -%}
+
+{%- block stream -%}
+{%- endblock stream -%}
+
+{%- block data_text scoped -%}
+{%- endblock data_text -%}
+
+{%- block data_html scoped -%}
+```html
+{{ output.data['text/html'] | safe }} 
+```
+{%- endblock data_html -%}
+
+{%- block data_jpg scoped -%}
+![](data:image/jpg;base64,{{ output.data['image/jpeg'] }})
+{%- endblock data_jpg -%}
+
+{%- block data_png scoped -%}
+![](data:image/png;base64,{{ output.data['image/png'] }})
+{%- endblock data_png -%}
@@ -1,18 +1,5 @@
 {% extends 'markdown/index.md.j2' %}

-{% block input %}{# cell.metadata.language is an addition of our docs pipeline. #}
-```{%- if 'language' in cell.metadata -%}
-{{ cell.metadata.language }}
-{%- elif 'magics_language' in cell.metadata -%}
-{{ cell.metadata.magics_language }}
-{%- elif 'name' in nb.metadata.get('language_info', {}) -%}
-{{ nb.metadata.language_info.name }}
-{%- endif %}
-{{ cell.source }}
-```
-{% endblock input %}
-
-
 {%- block traceback_line -%}
 ```output
 {{ line.rstrip() | strip_ansi }}
@@ -21,13 +8,13 @@

 {%- block stream -%}
 ```output
-{{ output.text.rstrip() | strip_ansi }}
+{{ output.text.rstrip() }}
 ```
 {%- endblock stream -%}

 {%- block data_text scoped -%}
 ```output
-{{ output.data['text/plain'].rstrip() | strip_ansi }}
+{{ output.data['text/plain'].rstrip() }}
 ```
 {%- endblock data_text -%}

@@ -38,13 +25,9 @@
 {%- endblock data_html -%}

 {%- block data_jpg scoped -%}
-<p>
-<img src="data:image/jpg;base64,{{ output.data['image/jpeg'] }}" />
-</p>
+![](data:image/jpg;base64,{{ output.data['image/jpeg'] }})
 {%- endblock data_jpg -%}

 {%- block data_png scoped -%}
-<p>
-<img src="data:image/png;base64,{{ output.data['image/png'] }}" />
-</p>
+![](data:image/png;base64,{{ output.data['image/png'] }})
 {%- endblock data_png -%}
@@ -1,21 +1,22 @@
-"""mkdocs hooks for adding custom logic to documentation pipeline.
-
-Lifecycle events: https://www.mkdocs.org/dev-guide/plugins/#events
-"""
-
 import logging
 import os
 import posixpath
 import re
-from typing import Any, Dict
+import traceback
+from typing import Any, Callable, Dict

-from bs4 import BeautifulSoup
-from mkdocs.config.defaults import MkDocsConfig
+from markdown import Markdown
 from mkdocs.structure.files import Files, File
 from mkdocs.structure.pages import Page
+from pymdownx.superfences import SuperFencesException
+
+from _scripts.hook_state import hook_state
+from markdown_exec.hooks import SessionHistoryEntry
+

 from _scripts.generate_api_reference_links import update_markdown_with_imports
 from _scripts.notebook_convert import convert_notebook
+from _scripts.setup_vcr import get_hash_for_session, load_postamble, load_preamble, _hash_string

 logger = logging.getLogger(__name__)
 logging.basicConfig()
@@ -25,90 +26,19 @@ 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-updates.ipynb": "how-tos/streaming.md#stream-graph-state",
-    "how-tos/streaming-content.ipynb": "how-tos/streaming.md",
-    "how-tos/stream-multiple.ipynb": "how-tos/streaming.md#stream-multiple-nodes",
-    "how-tos/streaming-tokens-without-langchain.ipynb": "how-tos/streaming.md#use-with-any-llm",
+    "how-tos/stream-values.ipynb": "how-tos/streaming.ipynb#values",
+    "how-tos/stream-updates.ipynb": "how-tos/streaming.ipynb#updates",
+    "how-tos/streaming-content.ipynb": "how-tos/streaming.ipynb#custom",
+    "how-tos/stream-multiple.ipynb": "how-tos/streaming.ipynb#multiple",
+    "how-tos/streaming-tokens-without-langchain.ipynb": "how-tos/streaming-tokens.ipynb#example-without-langchain",
    "how-tos/streaming-from-final-node.ipynb": "how-tos/streaming-specific-nodes.ipynb",
    "how-tos/streaming-events-from-within-tools-without-langchain.ipynb": "how-tos/streaming-events-from-within-tools.ipynb#example-without-langchain",
-    # graph-api
-    "how-tos/state-reducers.ipynb": "how-tos/graph-api#define-and-update-state",
-    "how-tos/sequence.ipynb": "how-tos/graph-api#create-a-sequence-of-steps",
-    "how-tos/branching.ipynb": "how-tos/graph-api#create-branches",
-    "how-tos/recursion-limit.ipynb": "how-tos/graph-api#create-and-control-loops",
-    "how-tos/visualization.ipynb": "how-tos/graph-api#visualize-your-graph",
-    "how-tos/input_output_schema.ipynb": "how-tos/graph-api#define-input-and-output-schemas",
-    "how-tos/pass_private_state.ipynb": "how-tos/graph-api#pass-private-state-between-nodes",
-    "how-tos/state-model.ipynb": "how-tos/graph-api#use-pydantic-models-for-graph-state",
-    "how-tos/map-reduce.ipynb": "how-tos/graph-api/#map-reduce-and-the-send-api",
-    "how-tos/command.ipynb": "how-tos/graph-api/#combine-control-flow-and-state-updates-with-command",
-    "how-tos/configuration.ipynb": "how-tos/graph-api/#add-runtime-configuration",
-    "how-tos/node-retries.ipynb": "how-tos/graph-api/#add-retry-policies",
-    "how-tos/return-when-recursion-limit-hits.ipynb": "how-tos/graph-api/#impose-a-recursion-limit",
-    "how-tos/async.ipynb": "how-tos/graph-api/#async",
-    # memory how-tos
-    "how-tos/memory/manage-conversation-history.ipynb": "how-tos/memory.ipynb",
-    "how-tos/memory/delete-messages.ipynb": "how-tos/memory.ipynb#delete-messages",
-    "how-tos/memory/add-summary-conversation-history.ipynb": "how-tos/memory.ipynb#summarize-messages",
-    # subgraph how-tos
-    "how-tos/subgraph-transform-state.ipynb": "how-tos/subgraph.ipynb#different-state-schemas",
-    "how-tos/subgraphs-manage-state.ipynb": "how-tos/subgraph.ipynb#add-persistence",
-    # persistence how-tos
-    "how-tos/persistence_postgres.ipynb": "how-tos/persistence.ipynb#use-in-production",
-    "how-tos/persistence_mongodb.ipynb": "how-tos/persistence.ipynb#use-in-production",
-    "how-tos/persistence_redis.ipynb": "how-tos/persistence.ipynb#use-in-production",
-    "how-tos/subgraph-persistence.ipynb": "how-tos/persistence.ipynb#use-with-subgraphs",
-    "how-tos/cross-thread-persistence.ipynb": "how-tos/persistence.ipynb#add-long-term-memory",
-    "cloud/how-tos/copy_threads": "cloud/how-tos/use_threads",
-    # tool calling how-tos
-    "how-tos/tool-calling-errors.ipynb": "how-tos/tool-calling.ipynb#handle-errors",
-    "how-tos/pass-config-to-tools.ipynb": "how-tos/tool-calling.ipynb#access-config",
-    "how-tos/pass-run-time-values-to-tools.ipynb": "how-tos/tool-calling.ipynb#read-state",
-    "how-tos/update-state-from-tools.ipynb": "how-tos/tool-calling.ipynb#update-state",
-    # multi-agent how-tos
-    "how-tos/agent-handoffs.ipynb": "how-tos/multi_agent.ipynb#handoffs",
-    "how-tos/multi-agent-network.ipynb": "how-tos/multi_agent.ipynb#use-in-a-multi-agent-system",
-    "how-tos/multi-agent-multi-turn-convo.ipynb": "how-tos/multi_agent.ipynb#multi-turn-conversation",
    # cloud redirects
-    "cloud/index.md": "index.md",
-    "cloud/how-tos/index.md": "concepts/langgraph_platform",
+    "cloud/index.md": "concepts/index.md#langgraph-platform",
+    "cloud/how-tos/index.md": "how-tos/index.md#langgraph-platform",
    "cloud/concepts/api.md": "concepts/langgraph_server.md",
    "cloud/concepts/cloud.md": "concepts/langgraph_cloud.md",
    "cloud/faq/studio.md": "concepts/langgraph_studio.md#studio-faqs",
-    "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_user_input.md": "cloud/how-tos/add-human-in-the-loop.md",
-    "concepts/platform_architecture.md": "concepts/langgraph_cloud#architecture",
-    # cloud streaming redirects
-    "cloud/how-tos/stream_values.md": "cloud/how-tos/streaming.md#stream-graph-state",
-    "cloud/how-tos/stream_updates.md": "cloud/how-tos/streaming.md#stream-graph-state",
-    "cloud/how-tos/stream_messages.md": "cloud/how-tos/streaming.md#messages",
-    "cloud/how-tos/stream_events.md": "cloud/how-tos/streaming.md#stream-events",
-    "cloud/how-tos/stream_debug.md": "cloud/how-tos/streaming.md#debug",
-    "cloud/how-tos/stream_multiple.md": "cloud/how-tos/streaming.md#stream-multiple-modes",
-    # prebuit redirects
-    "how-tos/create-react-agent.ipynb": "agents/agents.md#basic-configuration",
-    "how-tos/create-react-agent-memory.ipynb": "agents/memory.md",
-    "how-tos/create-react-agent-system-prompt.ipynb": "agents/context.md#prompts",
-    "how-tos/create-react-agent-hitl.ipynb": "agents/human-in-the-loop.md",
-    "how-tos/create-react-agent-structured-output.ipynb": "agents/agents.md#structured-output",
-    # Time-travel
-    "how-tos/human_in_the_loop/edit-graph-state.ipynb": "how-tos/human_in_the_loop/time-travel.ipynb",
-    # breakpoints
-    "how-tos/human_in_the_loop/dynamic_breakpoints.ipynb": "how-tos/human_in_the_loop/breakpoints.ipynb",
-    # misc
-    "prebuilt.md": "agents/prebuilt.md",
-    "reference/prebuilt.md": "reference/agents.md",
-    "concepts/high_level.md": "index.md",
-    "concepts/index.md": "index.md",
-    "concepts/v0-human-in-the-loop.md": "concepts/human-in-the-loop.md",
-    "how-tos/index.md": "index.md",
-    "tutorials/introduction.ipynb": "concepts/why-langgraph.md",
-    # deployment redirects
-    "how-tos/deploy-self-hosted.md": "cloud/deployment/self_hosted_data_plane.md",
-    "concepts/self_hosted.md": "concepts/langgraph_self_hosted_data_plane.md",
-    # assistant redirects
-    "cloud/how-tos/assistant_versioning.md": "cloud/how-tos/configuration_cloud.md",
 }


@@ -135,29 +65,6 @@ def on_files(files: Files, **kwargs: Dict[str, Any]):
    return new_files


-def _add_path_to_code_blocks(markdown: str, page: Page) -> str:
-    """Add the path to the code blocks."""
-    code_block_pattern = re.compile(
-        r"(?P<indent>[ \t]*)```(?P<language>\w+)[ ]*(?P<attributes>[^\n]*)\n"
-        r"(?P<code>((?:.*\n)*?))"  # Capture the code inside the block using named group
-        r"(?P=indent)```"  # Match closing backticks with the same indentation
-    )
-
-    def replace_code_block_header(match: re.Match) -> str:
-        indent = match.group("indent")
-        language = match.group("language")
-        attributes = match.group("attributes").rstrip()
-
-        if 'exec="on"' not in attributes:
-            # Return original code block
-            return match.group(0)
-
-        code = match.group("code")
-        return f'{indent}```{language} {attributes} path="{page.file.src_path}"\n{code}{indent}```'
-
-    return code_block_pattern.sub(replace_code_block_header, markdown)
-
-
 def _highlight_code_blocks(markdown: str) -> str:
    """Find code blocks with highlight comments and add hl_lines attribute.

@@ -235,6 +142,110 @@ def _highlight_code_blocks(markdown: str) -> str:
    markdown = code_block_pattern.sub(replace_highlight_comments, markdown)
    return markdown

+def handle_vcr_setup(
+    *,
+    formatter: Callable,
+    language: str,
+    code: str,
+    session: str,
+    id: str,
+    md: Markdown,
+    **kwargs: Dict[str, Any],
+) -> Dict[str, Any]:
+    """Handle VCR setup in markdown content if necessary."""
+    logger.info(f"handle_vcr_setup: {hook_state['document_filename']}")
+    try:
+        if hook_state['document_filename'] == '__UNKNOWN__':
+            raise SuperFencesException(
+                f"error while processing {language} block: document filename hasn't been set yet"
+            )
+        
+        if hook_state['document_content'] == '__UNKNOWN__':
+            raise SuperFencesException(
+                f"error while processing {language} block: document content hasn't been set yet"
+            )
+
+        if session is None or session == "" and id is None or id == "":
+            id = _hash_string(code)
+
+        if session is not None and session != "":
+            logger.info(f"new {language} session {session} on page {hook_state['document_filename']}")
+
+        cassette_prefix = hook_state['document_filename'].replace(".md", "").replace(os.path.sep, "_")
+
+        cassette_dir = os.path.abspath(
+            os.path.join(os.path.dirname(os.path.dirname(__file__)), "cassettes")
+        )
+        os.makedirs(cassette_dir, exist_ok=True)
+
+        # Build a unique cassette name.
+        cassette_name = os.path.join(
+            cassette_dir,
+            f"{cassette_prefix}_{session if session else id}_{language}.msgpack.zlib",
+        )
+
+        # Add context manager at start with explicit __enter__ and __exit__ calls
+
+        hash_ = get_hash_for_session(language, session, hook_state['document_content'])
+        wrapped_lines = [
+            load_preamble(language, hash_, cassette_name),
+            code,
+        ]
+
+        if session is None or session == "":
+            logger.info(
+                f"no session, adding postamble for {language} in {hook_state['document_filename']}"
+            )
+            wrapped_lines.append(load_postamble(language))
+
+        transformed_source = "\n".join(wrapped_lines)
+
+        # Propagate extras
+        keep_extras = {
+            key: value
+            for key, value in kwargs["extra"].items()
+            if key
+            in {
+                "hl_lines",
+            }
+        }
+
+        return dict(
+            transform_source=lambda code: (transformed_source, code),
+            id=id,
+            extra={ **keep_extras, "path": hook_state['document_filename'] },
+        )
+    except Exception as e:
+        raise SuperFencesException(traceback.format_exc()) from e
+
+
+def handle_vcr_teardown(
+    *,
+    formatter: Callable,
+    language: str,
+    session: str,
+    history: list[SessionHistoryEntry],
+):
+    code = load_postamble(language)
+    html = False
+    update_toc = False
+
+    logger.info(f"tearing down {language} {session} on {hook_state['document_filename']}")
+
+    kwargs = dict(
+        code=code,
+        session=session,
+        id=f"{id}_vcr_end",
+        md=None, # md is unused by the formatter, but it's a required argument
+        html=html,
+        update_toc=update_toc,
+        extra={},
+    )
+
+    # This doesn't actually render anything, we just call the formatter so it
+    # executes in the same context as the session of which we're disposing.
+    formatter(**kwargs)
+

 def _on_page_markdown_with_config(
    markdown: str,
@@ -253,23 +264,20 @@ def _on_page_markdown_with_config(

    # Append API reference links to code blocks
    if add_api_references:
-        markdown = update_markdown_with_imports(markdown, page.file.abs_src_path)
+        markdown = update_markdown_with_imports(markdown, page.file.src_path)
    # Apply highlight comments to code blocks
    markdown = _highlight_code_blocks(markdown)

-    # Add file path as an attribute to code blocks that are executable.
-    # This file path is used to associate fixtures with the executable code
-    # which can be used in CI to test the docs without making network requests.
-    markdown = _add_path_to_code_blocks(markdown, page)
-
    if remove_base64_images:
        # Remove base64 encoded images from markdown
-        markdown = re.sub(r"!\[.*?\]\(data:image/[^;]+;base64,[^)]+\)", "", markdown)
+        markdown = re.sub(r"!\[.*?\]\(data:image/+;base64,[^\)]+\)", "", markdown)

    return markdown


 def on_page_markdown(markdown: str, page: Page, **kwargs: Dict[str, Any]):
+    logger.info(f"on_page_markdown: {page.file.src_path}")
+    hook_state['document_filename'] = page.file.src_path
    return _on_page_markdown_with_config(
        markdown,
        page,
@@ -298,7 +306,7 @@ Redirecting...
 """


-def _write_html(site_dir, old_path, new_path):
+def write_html(site_dir, old_path, new_path):
    """Write an HTML file in the site_dir with a meta redirect to the new page"""
    # Determine all relevant paths
    old_path_abs = os.path.join(site_dir, old_path)
@@ -314,52 +322,6 @@ def _write_html(site_dir, old_path, new_path):
        f.write(content)


-def _inject_gtm(html: str) -> str:
-    """Inject Google Tag Manager code into the HTML.
-
-    Code to inject Google Tag Manager noscript tag immediately after <body>.
-
-    This is done via hooks rather than via a template because the MkDocs material
-    theme does not seem to allow placing the code immediately after the <body> tag
-    without modifying the template files directly.
-
-    Args:
-        html: The HTML content to modify.
-
-    Returns:
-        The modified HTML content with GTM code injected.
-    """
-    # Code was copied from Google Tag Manager setup instructions.
-    gtm_code = """
-<!-- Google Tag Manager (noscript) -->
-<noscript><iframe src="https://www.googletagmanager.com/ns.html?id=GTM-T35S4S46"
-height="0" width="0" style="display:none;visibility:hidden"></iframe></noscript>
-<!-- End Google Tag Manager (noscript) -->
-"""
-    soup = BeautifulSoup(html, "html.parser")
-    body = soup.body
-    if body:
-        # Insert the GTM code as raw HTML at the top of <body>
-        body.insert(0, BeautifulSoup(gtm_code, "html.parser"))
-        return str(soup)
-    else:
-        return html  # fallback if no <body> found
-
-
-def on_post_page(output: str, page: Page, config: MkDocsConfig) -> str:
-    """Inject Google Tag Manager noscript tag immediately after <body>.
-
-    Args:
-        output: The HTML output of the page.
-        page: The page instance.
-        config: The MkDocs configuration object.
-
-    Returns:
-        modified HTML output with GTM code injected.
-    """
-    return _inject_gtm(output)
-
-
 # Create HTML files for redirects after site dir has been built
 def on_post_build(config):
    use_directory_urls = config.get("use_directory_urls")
@@ -376,4 +338,10 @@ def on_post_build(config):
            + hash
            + suffix
        )
-        _write_html(config["site_dir"], old_html_path, new_html_path)
+        write_html(config["site_dir"], old_html_path, new_html_path)
+
+def on_pre_page(page: Page, **kwargs: Dict[str, Any]):
+    logger.info(f"on_pre_page: {page.file.src_path}")
+    hook_state['document_filename'] = page.file.src_path
+    hook_state['document_content'] = page.file.content_string
+    return page
@@ -5,7 +5,6 @@ import os
 import json
 import click
 import nbformat
-import re

 logger = logging.getLogger(__name__)
 NOTEBOOK_DIRS = ("docs/how-tos","docs/tutorials")
@@ -21,6 +20,7 @@ BLOCKLIST_COMMANDS = (

 NOTEBOOKS_NO_CASSETTES = (
    "docs/how-tos/visualization.ipynb",
+    "docs/how-tos/many-tools.ipynb"
 )

 NOTEBOOKS_NO_EXECUTION = [
@@ -49,10 +49,7 @@ NOTEBOOKS_NO_EXECUTION = [
    "docs/how-tos/map-reduce.ipynb",  # flakiness from structured output, only when running with VCR
    "docs/tutorials/tot/tot.ipynb",
    "docs/how-tos/visualization.ipynb",
-    "docs/how-tos/streaming-specific-nodes.ipynb",
-    "docs/tutorials/llm-compiler/LLMCompiler.ipynb",
-    "docs/tutorials/customer-support/customer-support.ipynb",  # relies on openai embeddings, doesn't play well w/ VCR
-    "docs/how-tos/many-tools.ipynb",  # relies on openai embeddings, doesn't play well w/ VCR
+    "docs/tutorials/llm-compiler/LLMCompiler.ipynb"
 ]


@@ -89,11 +86,6 @@ def has_blocklisted_command(code: str, metadata: dict) -> bool:
            return True
    return False

-MERMAID_PATTERN = re.compile(r'display\(Image\((\w+)\.get_graph\(\)\.draw_mermaid_png\(\)\)\)')
-
-def remove_mermaid(code: str) -> str:
-    return MERMAID_PATTERN.sub('print()', code)
-

 def add_vcr_to_notebook(
    notebook: nbformat.NotebookNode, cassette_prefix: str
@@ -107,8 +99,6 @@ def add_vcr_to_notebook(
            continue

        lines = cell.source.splitlines()
-        # remove the special tag for hidden cells
-        lines = [line for line in lines if not line.strip().startswith("# hide-cell")]
        # skip if empty cell
        if not lines:
            continue
@@ -190,20 +180,6 @@ def add_vcr_to_notebook(
    return notebook


-def remove_mermaid_from_notebook(notebook: nbformat.NotebookNode) -> nbformat.NotebookNode:
-    for cell in notebook.cells:
-        if cell.cell_type != "code":
-            continue
-
-        cell.source = remove_mermaid(cell.source)
-
-        # skip the cell entirely if it contains PYPPETEER
-        if "PYPPETEER" in cell.source:
-            cell.source = ""
-
-    return notebook
-
-
 def process_notebooks(should_comment_install_cells: bool) -> None:
    for directory in NOTEBOOK_DIRS:
        for root, _, files in os.walk(directory):
@@ -225,8 +201,6 @@ def process_notebooks(should_comment_install_cells: bool) -> None:
                            notebook, cassette_prefix=cassette_prefix
                        )

-                    notebook = remove_mermaid_from_notebook(notebook)
-
                    if notebook_path in NOTEBOOKS_NO_EXECUTION:
                        # Add a cell at the beginning to indicate that this notebook should not be executed
                        warning_cell = nbformat.v4.new_markdown_cell(
@@ -0,0 +1,140 @@
+# A list of patterns that, if found in a code block, will cause us to leave that block unchanged.
+import hashlib
+import json
+import os
+import re
+from textwrap import dedent, indent
+
+from mistune import BlockParser, BlockState, Markdown, create_markdown
+from mistune.renderers.markdown import MarkdownRenderer
+
+preambles = {
+    "python": "vcr_setup_preamble.py",
+    "typescript": "nock_setup_preamble.ts",
+}
+
+
+def _get_python_cassette_init(cassette_name: str, hash_: str) -> str:
+    return dedent(
+        f"""
+        _cassette = HashedCassette('{cassette_name}', '{hash_}')
+        _cassette.__enter__()
+        """
+    )
+
+
+def _get_typescript_cassette_init(cassette_name: str, hash_: str) -> str:
+    return dedent(
+        f"""
+        const _cassette = new HashedCassette("{cassette_name}", "{hash_}");
+        await _cassette.enter();
+        """
+    )
+
+
+def _get_python_cassette_cleanup() -> str:
+    return "_cassette.__exit__()"
+
+
+def _get_typescript_cassette_cleanup() -> str:
+    return "await _cassette.exit();"
+
+
+preamble_inits = {
+    "python": _get_python_cassette_init,
+    "py": _get_python_cassette_init,
+    "typescript": _get_typescript_cassette_init,
+    "ts": _get_typescript_cassette_init,
+}
+
+preamble_cleanups = {
+    "python": _get_python_cassette_cleanup,
+    "py": _get_python_cassette_cleanup,
+    "typescript": _get_typescript_cassette_cleanup,
+    "ts": _get_typescript_cassette_cleanup,
+}
+
+
+def load_preamble(language: str, hash_: str, cassette_name: str) -> str:
+    """Load the source code for the preamble for a given language."""
+    _assets_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "assets")
+
+    preamble_path = os.path.join(_assets_dir, preambles[language])
+    with open(preamble_path, "r") as f:
+        lines = f.readlines()
+        lines.append(preamble_inits[language](cassette_name, hash_))
+        return "\n".join(lines).strip()
+
+
+def load_postamble(language: str) -> str:
+    """Load the source code for the postamble for a given language."""
+    return preamble_cleanups[language]()
+
+
+def _hash_string(input_string: str) -> str:
+    # Encode the input string to bytes
+    encoded_string = input_string.encode("utf-8")
+    # Create a SHA-256 hash object
+    sha256_hash = hashlib.sha256(encoded_string)
+    # Get the hexadecimal digest of the hash
+    return sha256_hash.hexdigest()
+
+
+def extract_code_blocks_for_session(language: str, session: str, content: str) -> str:
+    code_blocks_for_session = []
+
+    TAB_REGEX = r"^===!? \"(?P<title>[^\"]+)\"\n(?P<content>(?:(?P<indent>    )+[^\n]*\n)+)"
+    def parse_tabs(block: BlockParser, m: re.Match, state: BlockState) -> str:
+        state.append_token(
+            {
+                "raw": m.group(0),
+                "type": "block_tab",
+                "attrs": {
+                    "title": m.group("title"),
+                    "level": len(m.group("indent")) // 4,
+                    "content": dedent(m.group("content")).strip(),
+                },
+            }
+        )
+        return m.end()
+
+    def render_tabs(self, token: dict, state: BlockState):
+        recursive_transformer = create_markdown(renderer=DocumentRenderer())
+        recursive_transformer.block.register("block_tab", TAB_REGEX, parse_tabs, before='list')
+        recursive_transformer.renderer.register("block_tab", render_tabs)
+        return (
+            f'=== "{token["attrs"]["title"]}"\n'
+            f'{indent(recursive_transformer(token["attrs"]["content"]), "    " * token["attrs"]["level"])}\n'
+        )
+
+    class DocumentRenderer(MarkdownRenderer):
+        def block_code(self, token: dict, state: BlockState):
+            if token["style"] == "fenced":
+                if token["attrs"]["info"]:
+                    attributes = {}
+                    block_language = token["attrs"]["info"].split()[0]
+                    for match in re.finditer(r'(?P<key>\w+)=(?:(?P<value>(?:[\w]+))|"(?P<value_quoted>(?:[^"\s]+))")', token["attrs"]["info"]):
+                        attributes[match.group("key")] = match.group("value") or match.group("value_quoted")
+                    if block_language == language and "session" in attributes and attributes["session"] == session:
+                        code_blocks_for_session.append(token["raw"].rstrip())
+            return super().block_code(token, state)
+
+    transformer: Markdown = create_markdown(renderer=DocumentRenderer())
+    transformer.block.register("block_tab", TAB_REGEX, parse_tabs, before='list')
+    transformer.renderer.register("block_tab", render_tabs)
+    
+    # Parses the page content, which causes the code blocks to be added to the code_blocks_for_session list.
+    # There's probably some way to do this by using the renderer as a filter, but I would've had to NO-OP
+    # all of the default behavior, and this was easier.
+    transformer(content)
+
+    return code_blocks_for_session
+
+
+def get_hash_for_session(language: str, session: str, content: str) -> str:
+    # include the preamble in the hash so we invalidate if it changes
+    preamble_hash = _hash_string(load_preamble(language, session, "test"))
+
+    code_blocks_for_session = [preamble_hash, *extract_code_blocks_for_session(language, session, content)]
+    
+    return _hash_string("\n".join(code_blocks_for_session))
@@ -9,7 +9,10 @@ import yaml

 MARKDOWN = """\
 [//]: # (This file is automatically generated using a script in docs/_scripts. Do not edit this file directly!)
-# Community Agents
+# 🚀 Prebuilt Agents
+
+LangGraph includes a prebuilt React agent. For more information on how to use it, 
+check out our [how-to guides](https://langchain-ai.github.io/langgraph/how-tos/#prebuilt-react-agent).

 If you’re looking for other prebuilt libraries, explore the community-built options 
 below. These libraries can extend LangGraph's functionality in various ways.
@@ -80,18 +83,14 @@ def generate_markdown(resolved_packages: List[ResolvedPackage], language: str) -
        resolved_packages, key=lambda p: p["weekly_downloads"] or 0, reverse=True
    )
    rows = [
-        "| Name | GitHub URL | Description | Weekly Downloads | Stars |",
-        "| --- | --- | --- | --- | --- |",
+        "| Name | GitHub URL | Description | Weekly Downloads |",
+        "| --- | --- | --- | --- |",
    ]
    for package in sorted_packages:
        name = f"**{package['name']}**"
        repo_url = f"[{package['repo']}](https://github.com/{package['repo']})"
-        stars_badge = (
-            f"https://img.shields.io/github/stars/{package['repo']}?style=social"
-        )
-        stars = f"![GitHub stars]({stars_badge})"
-        downloads = package["weekly_downloads"] or "-"
-        row = f"| {name} | {repo_url} | {package['description']} | {downloads} | {stars}"
+        downloads = package["weekly_downloads"] or 0
+        row = f"| {name} | {repo_url} | {package['description']} | {downloads} |"
        rows.append(row)
    markdown_content = MARKDOWN.format(
        library_list="\n".join(rows), langgraph_url=langgraph_url
@@ -30,63 +30,25 @@ PACKAGES_FILE = HERE / "packages.yml"
 PACKAGES = yaml.safe_load(PACKAGES_FILE.read_text())['packages']


-def _get_weekly_downloads(packages: list[Package], fake: bool) -> list[ResolvedPackage]:
+def _get_weekly_downloads(packages: list[Package]) -> list[ResolvedPackage]:
    """Retrieve the monthly download count for a list of packages from PyPIStats."""
    resolved_packages: list[ResolvedPackage] = []

-    if fake:
-        # To avoid making network requests during testing, return fake download counts
-        for package in packages:
-            resolved_packages.append(
-                {
-                    "name": package["name"],
-                    "repo": package["repo"],
-                    "weekly_downloads": -12345,
-                    "description": package["description"],
-                }
-            )
-        return resolved_packages
-
    for package in packages:
-        # First check if package exists on PyPI
-        pypi_url = f"https://pypi.org/pypi/{package['name']}/json"
-        try:
-            pypi_response = requests.get(pypi_url)
-            pypi_response.raise_for_status()
-        except requests.exceptions.HTTPError:
-            raise AssertionError(f"Package {package['name']} does not exist on PyPI")
+        url = f"https://pypistats.org/api/packages/{package['name']}/overall"

-        # Get first release date
-        pypi_data = pypi_response.json()
-        releases = pypi_data["releases"]
-        first_release_date = None
-        for version_releases in releases.values():
-            if version_releases:  # Some versions may be empty lists
-                upload_time = datetime.fromisoformat(version_releases[0]["upload_time"])
-                if first_release_date is None or upload_time < first_release_date:
-                    first_release_date = upload_time
+        response = requests.get(url)
+        response.raise_for_status()
+        data = response.json()

-        if first_release_date is None:
-            raise AssertionError(f"Package {package['name']} has no releases yet")
+        sorted_data = sorted(
+            data["data"],
+            key=lambda x: datetime.strptime(x["date"], "%Y-%m-%d"),
+            reverse=True,
+        )

-        # If package was published in last 48 hours, skip download stats
-        if (datetime.now() - first_release_date).total_seconds() >= 48 * 3600:
-            url = f"https://pypistats.org/api/packages/{package['name']}/overall"
-
-            response = requests.get(url)
-            response.raise_for_status()
-            data = response.json()
-
-            sorted_data = sorted(
-                data["data"],
-                key=lambda x: datetime.strptime(x["date"], "%Y-%m-%d"),
-                reverse=True,
-            )
-
-            # Sum the last 7 days of downloads
-            num_downloads = sum(entry["downloads"] for entry in sorted_data[:7])
-        else:
-            num_downloads = None
+        # Sum the last 7 days of downloads
+        num_downloads = sum(entry["downloads"] for entry in sorted_data[:7])

        resolved_packages.append(
            {
@@ -101,13 +63,13 @@ def _get_weekly_downloads(packages: list[Package], fake: bool) -> list[ResolvedP



-def main(output_file: str, fake: bool) -> None:
+def main(output_file: str) -> None:
    """Main function to generate package download information.

    Args:
        output_file: Path to the output YAML file.
    """
-    resolved_packages: list[ResolvedPackage] = _get_weekly_downloads(PACKAGES, fake)
+    resolved_packages: list[ResolvedPackage] = _get_weekly_downloads(PACKAGES)

    if not output_file.endswith(".yml"):
        raise ValueError("Output file must have a .yml extension")
@@ -128,15 +90,6 @@ if __name__ == "__main__":
            "downloads.yml"
        ),
    )
-    parser.add_argument(
-        "--fake",
-        default=False,
-        action="store_true",
-        help=(
-            "Generate fake download counts for testing purposes. "
-            "This option will not make any network requests."
-        ),
-    )
    args = parser.parse_args()

-    main(args.output_file, args.fake)
+    main(args.output_file)
@@ -2,40 +2,10 @@
 packages:
  - name: "trustcall"
    repo: "hinthornw/trustcall"
-    description: "Tenacious tool calling built on LangGraph."
+    description: "Tenacious tool calling built on LangGraph"
  - name: "breeze-agent"
    repo: "andrestorres123/breeze-agent"
-    description: "A streamlined research system built inspired on STORM and built on LangGraph."
+    description: "A streamlined research system built inspired on STORM and built on LangGraph"
  - name: "langgraph-supervisor"
-    repo: "langchain-ai/langgraph-supervisor-py"
-    description: "Build supervisor multi-agent systems with LangGraph."
-  - name: "langmem"
-    repo: "langchain-ai/langmem"
-    description: "Build agents that learn and adapt from interactions over time."
-  - name: "langchain-mcp-adapters"
-    repo: "langchain-ai/langchain-mcp-adapters"
-    description: "Make Anthropic Model Context Protocol (MCP) tools compatible with LangGraph agents."
-  - name: "open-deep-research"
-    repo: "langchain-ai/open_deep_research"
-    description: "Open source assistant for iterative web research and report writing."
-  - name: "langgraph-swarm"
-    repo: "langchain-ai/langgraph-swarm-py"
-    description: "Build swarm-style multi-agent systems using LangGraph."
-  - name: "delve-taxonomy-generator"
-    repo: "andrestorres123/delve"
-    description: "A taxonomy generator for unstructured data"
-  - name: "nodeology"
-    repo: "xyin-anl/Nodeology"
-    description: "Enable researcher to build scientific workflows easily with simplified interface."
-  - name: "langgraph-bigtool"
-    repo: "langchain-ai/langgraph-bigtool"
-    description: "Build LangGraph agents with large numbers of tools."
-  - name: "ai-data-science-team"
-    repo: "business-science/ai-data-science-team"
-    description: "An AI-powered data science team of agents to help you perform common data science tasks 10X faster."
-  - name: "langgraph-reflection"
-    repo: "langchain-ai/langgraph-reflection"
-    description: "LangGraph agent that runs a reflection step."
-  - name: "langgraph-codeact"
-    repo: "langchain-ai/langgraph-codeact"
-    description: "LangGraph implementation of CodeAct agent that generates and executes code instead of tool calling."
+    repo: "langchain-ai/langgraph-supervisor"
+    description: "Build supervisor multi-agent systems with LangGraph"
@@ -0,0 +1 @@
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@@ -1 +1 @@
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@@ -1 +1 @@
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@@ -1 +1 @@
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@@ -0,0 +1 @@
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--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Ben Burns	b9f26d28ea	add missing build step	2025-02-13 23:03:58 -08:00
Ben Burns	06d4ba7fa0	bump prebuilt.md	2025-02-13 22:57:15 -08:00
Ben Burns	2dbdb36743	fix cassette hashing	2025-02-13 22:56:16 -08:00
Ben Burns	2b72fbd5de	state-reducers.md WIP	2025-02-13 21:57:45 -08:00
Ben Burns	c681545c97	make CodeQL happy, fix Makefile	2025-02-13 21:57:44 -08:00
Ben Burns	5ebdefba63	ts exec works - back out half-baked TS code snippet for now	2025-02-13 21:57:44 -08:00
Ben Burns	441923282c	docs: get ts execution working in build pipeline	2025-02-13 21:57:37 -08:00
				`@@ -0,0 +1 @@`
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				`@@ -0,0 +1 @@`
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				`@@ -0,0 +1 @@`
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				`@@ -0,0 +1 @@`
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				`@@ -0,0 +1 @@`
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				`@@ -1 +0,0 @@`
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				`@@ -1 +0,0 @@`
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				`@@ -0,0 +1 @@`
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