fix: flip default on base cache (#6677)

rebasing https://github.com/langchain-ai/langgraph/pull/6562 w/ current
main

.github/CONTRIBUTING.md

@@ -0,0 +1,6 @@
+# Contributing to LangGraph
+
+Hi there! Thank you for even being interested in contributing to LangGraph.
+As an open-source project in a rapidly developing field, we are extremely open to contributions, whether they involve new features, improved infrastructure, better documentation, or bug fixes.
+
+To learn how to contribute to LangGraph, please follow the [contribution guide here](https://docs.langchain.com/oss/python/contributing).

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -1,21 +1,20 @@
 name: "\U0001F41B Bug Report"
 description: Report a bug in LangGraph. To report a security issue, please instead use the security option below. For questions, please use the LangChain Forum at forum.langchain.com.
-labels: [pending,bug]
+labels: [pending, bug]
 body:
   - type: markdown
     attributes:
       value: |
         Thank you for taking the time to file a bug report. 
-        
+
         Use this to report BUGS in LangGraph. For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
-        
+
         Relevant links to check before filing a bug report to see if your issue has already been reported, fixed or
         if there's another way to solve your problem:
-        
+
         * [LangChain Forum](https://forum.langchain.com/),
         * [LangGraph Github Issues](https://github.com/langchain-ai/langgraph/issues),
-        * [LangGraph how-to guides](https://langchain-ai.github.io/langgraph/how-tos/).
-        * [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
+        * [LangChain documentation with the integrated search](https://docs.langchain.com/),
         * [GitHub search](https://github.com/langchain-ai/langgraph),
   - type: checkboxes
     id: checks

.github/scripts/check_sdk_methods.py

@@ -38,7 +38,7 @@ def main():
         tree = ast.parse(file.read())
 
     classes = find_classes(tree)
-  
+
     def is_sync(class_spec: Tuple[str, List[str]]) -> bool:
         return class_spec[0].startswith("Sync")
 

.github/scripts/run_langgraph_cli_test.py

@@ -1,7 +1,8 @@
+import logging
 import pathlib
 import sys
 import time
-from urllib import request, error
+from urllib import error, request
 
 import langgraph_cli
 import langgraph_cli.config
@@ -11,9 +12,13 @@ from langgraph_cli.constants import DEFAULT_PORT
 from langgraph_cli.exec import Runner, subp_exec
 from langgraph_cli.progress import Progress
 
+logger = logging.getLogger(__name__)
+logging.basicConfig(level=logging.INFO)
+
 
 def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
     """Spin up API with Postgres/Redis via docker compose and wait until ready."""
+    logger.info("Starting test...")
     with Runner() as runner, Progress(message="Pulling...") as set:
         # Detect docker/compose capabilities
         capabilities = langgraph_cli.docker.check_capabilities(runner)
@@ -57,7 +62,9 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
             sys.stderr.write(f"docker compose up failed: {e}\n")
             try:
                 sys.stderr.write("\n== docker compose ps ==\n")
-                runner.run(subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=False))
+                runner.run(
+                    subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=False)
+                )
             except Exception:
                 pass
             try:
@@ -93,7 +100,7 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
         set("")
         base_url = f"http://localhost:{port}"
         ok_url = f"{base_url}/ok"
-        print(f"Waiting for {ok_url} to respond with 200...")
+        logger.info(f"Waiting for {ok_url} to respond with 200...")
         deadline = time.time() + 30
         last_err: Exception | None = None
         while time.time() < deadline:
@@ -107,13 +114,16 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
                         break
                     else:
                         last_err = RuntimeError(f"Unexpected status: {resp.status}")
-                        print(f"Unexpected status: {resp.status}")
+                        logger.error(f"Unexpected status: {resp.status}")
             except error.URLError as e:
+                logger.error(f"URLError: {e}")
                 last_err = e
             except Exception as e:  # noqa: BLE001
+                logger.error(f"Exception: {e}")
                 last_err = e
             time.sleep(0.5)
         else:
+            logger.error("Timeout waiting for /ok to return 200")
             # Bring stack down before raising
             args_down = [*args, "down", "-v", "--remove-orphans"]
             try:
@@ -131,15 +141,23 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
                 )
 
         # Clean up: bring compose stack down to free ports for next test
-        args_down = [*args, "down", "-v", "--remove-orphans"]
-        runner.run(
-            subp_exec(
-                *compose_cmd,
-                *args_down,
-                input=stdin,
-                verbose=verbose,
+        logger.info("Test succeeded. Bringing down compose stack...")
+        try:
+            args_down = [*args, "down", "-v", "--remove-orphans"]
+            runner.run(
+                subp_exec(
+                    *compose_cmd,
+                    *args_down,
+                    input=stdin,
+                    verbose=verbose,
+                )
             )
-        )
+            logger.info("Compose stack down. Finishing...")
+        except Exception:
+            logger.exception("Failed to bring down compose stack")
+            pass
+
+    logger.info("Test finished")
 
 
 if __name__ == "__main__":
@@ -150,4 +168,10 @@ if __name__ == "__main__":
     parser.add_argument("-c", "--config", type=str, default="./langgraph.json")
     parser.add_argument("-p", "--port", type=int, default=DEFAULT_PORT)
     args = parser.parse_args()
-    test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
+    try:
+        test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
+    except BaseException:
+        logger.exception("Test failed")
+        raise
+    
+    logger.info("Test execution finished")

.github/workflows/_integration_test.yml

@@ -13,7 +13,7 @@ jobs:
       matrix:
         python-version:
           - "3.10"
-          - "3.11"
+          - "3.14"
         example:
           - name: A
             workdir: libs/cli/examples
@@ -32,7 +32,7 @@ jobs:
       run:
         working-directory: libs/cli
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
       - name: Get changed files
         id: changed-files
         uses: Ana06/get-changed-files@v2.3.0
@@ -40,7 +40,7 @@ jobs:
           filter: "libs/cli/**"
       - name: Set up Python ${{ matrix.python-version }}
         if: steps.changed-files.outputs.all
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ matrix.python-version }}
           enable-cache: true
@@ -66,19 +66,19 @@ jobs:
           timeout 60 python "$REPO_ROOT/.github/scripts/run_langgraph_cli_test.py" -t ${{ matrix.example.tag }}
 
       - name: Build JS service
-        if: steps.changed-files.outputs.all
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
         working-directory: libs/cli/js-examples
         run: |
           langgraph build -t langgraph-test-e
 
       - name: Build JS monorepo service
-        if: steps.changed-files.outputs.all
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
         working-directory: libs/cli/js-monorepo-example
         run: |
           langgraph build -t langgraph-test-f -c apps/agent/langgraph.json --build-command "yarn run turbo build" --install-command "yarn install"
 
       - name: Build Python monorepo service
-        if: steps.changed-files.outputs.all
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
         working-directory: libs/cli/python-monorepo-example
         run: |
           langgraph build -t langgraph-test-g -c apps/agent/langgraph.json
@@ -87,24 +87,32 @@ jobs:
           timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-g -c apps/agent/langgraph.json
 
       - name: Build and test prerelease reqs service
-        if: steps.changed-files.outputs.all
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
         working-directory: libs/cli/examples/graph_prerelease_reqs
         run: |
           langgraph build -t langgraph-test-h
           cp ../.env.example .env
           if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
           timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-h
+          echo "Finished starting up langgraph-test-h"
           LANGGRAPH_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langgraph'); print(v);")
-          if [ "$LANGGRAPH_VERSION" != "1.0.0a2" ]; then
+          if [ "$LANGGRAPH_VERSION" != "1.0.2" ]; then
+            echo "LANGGRAPH_VERSION != 1.0.2; $LANGGRAPH_VERSION"
             exit 1
           fi
           LANGCHAIN_OPENAI_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-openai'); print(v);")
-          if [ "$LANGCHAIN_OPENAI_VERSION" != "0.3.0" ]; then
+          if [ "$LANGCHAIN_OPENAI_VERSION" != "1.0.1" ]; then
+            echo "LANGCHAIN_OPENAI_VERSION != 1.0.1; $LANGCHAIN_OPENAI_VERSION"
+            exit 1
+          fi
+          LANGCHAIN_ANTHROPIC_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-anthropic'); print(v);")
+          if [ "$LANGCHAIN_ANTHROPIC_VERSION" != "1.0.0a5" ]; then
+            echo "LANGCHAIN_ANTHROPIC_VERSION != 1.0.0a5; $LANGCHAIN_ANTHROPIC_VERSION"
             exit 1
           fi
 
       - name: Build and test prerelease reqs fail service
-        if: steps.changed-files.outputs.all
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
         working-directory: libs/cli/examples/graph_prerelease_reqs_fail
         run: |
           langgraph build -t langgraph-test-i || [ $? -eq 1 ]

.github/workflows/_lint.yml

@@ -31,7 +31,7 @@ jobs:
           - "3.12"
     name: "lint #${{ matrix.python-version }}"
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
       - name: Get changed files
         id: changed-files
         uses: Ana06/get-changed-files@v2.3.0
@@ -39,7 +39,7 @@ jobs:
           filter: "${{ inputs.working-directory }}/**"
       - name: Set up Python ${{ matrix.python-version }}
         if: steps.changed-files.outputs.all
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ matrix.python-version }}
           enable-cache: true
@@ -48,11 +48,11 @@ jobs:
       - name: Install dependencies
         if: steps.changed-files.outputs.all
         working-directory: ${{ inputs.working-directory }}
-        run: uv sync --frozen --group dev
+        run: uv sync --frozen --group lint
 
       - name: Get .mypy_cache to speed up mypy
         if: steps.changed-files.outputs.all
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         env:
           SEGMENT_DOWNLOAD_TIMEOUT_MIN: "2"
         with:
@@ -74,11 +74,11 @@ jobs:
       - name: Install test dependencies
         if: steps.changed-files.outputs.all
         working-directory: ${{ inputs.working-directory }}
-        run: uv sync --group dev
+        run: uv sync --group lint
 
       - name: Get .mypy_cache_test to speed up mypy
         if: steps.changed-files.outputs.all
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         env:
           SEGMENT_DOWNLOAD_TIMEOUT_MIN: "2"
         with:

.github/workflows/_test.yml

@@ -17,17 +17,17 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.9"
           - "3.10"
           - "3.11"
           - "3.12"
           - "3.13"
+          - "3.14"
 
     name: "test #${{ matrix.python-version }}"
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
       - name: Set up Python ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ matrix.python-version }}
           enable-cache: true
@@ -42,7 +42,7 @@ jobs:
       - name: Install dependencies
         shell: bash
         working-directory: ${{ inputs.working-directory }}
-        run: uv sync --frozen --group dev
+        run: uv sync --frozen --group test --no-dev
 
       - name: Run tests
         shell: bash

.github/workflows/_test_langgraph.yml

@@ -12,20 +12,20 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.9"
           - "3.10"
           - "3.11"
           - "3.12"
           - "3.13"
+          - "3.14"
 
     defaults:
       run:
         working-directory: libs/langgraph
     name: "test #${{ matrix.python-version }}"
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
       - name: Set up Python ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ matrix.python-version }}
           enable-cache: true
@@ -39,7 +39,7 @@ jobs:
 
       - name: Install dependencies
         shell: bash
-        run: uv sync --frozen --group dev
+        run: uv sync --frozen --group test --no-dev
 
       - name: Run tests
         shell: bash

.github/workflows/_test_release.yml

@@ -16,7 +16,6 @@ permissions:
 
 jobs:
   build:
-    if: github.ref == 'refs/heads/main'
     runs-on: ubuntu-latest
 
     outputs:
@@ -24,10 +23,10 @@ jobs:
       version: ${{ steps.check-version.outputs.version }}
 
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
 
       - name: Set up Python $${ env.PYTHON_VERSION }}
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           enable-cache: true
@@ -49,7 +48,7 @@ jobs:
         working-directory: ${{ inputs.working-directory }}
 
       - name: Upload build
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v6
         with:
           name: test-dist
           path: ${{ inputs.working-directory }}/dist/
@@ -75,9 +74,9 @@ jobs:
       id-token: write
 
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
 
-      - uses: actions/download-artifact@v5
+      - uses: actions/download-artifact@v7
         with:
           name: test-dist
           path: ${{ inputs.working-directory }}/dist/

.github/workflows/baseline.yml

@@ -17,20 +17,20 @@ jobs:
       run:
         working-directory: libs/langgraph
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
       - run: SHA=$(git rev-parse HEAD) && echo "SHA=$SHA" >> $GITHUB_ENV
       - name: Set up Python 3.11
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: "3.11"
           enable-cache: true
           cache-suffix: "bench"
       - name: Install dependencies
-        run: uv sync --group dev
+        run: uv sync --group test
       - name: Run benchmarks
         run: OUTPUT=out/benchmark-baseline.json make -s benchmark
       - name: Save outputs
-        uses: actions/cache/save@v4
+        uses: actions/cache/save@v5
         with:
           key: ${{ runner.os }}-benchmark-baseline-${{ env.SHA }}
           path: |

.github/workflows/bench.yml

@@ -15,22 +15,22 @@ jobs:
       run:
         working-directory: libs/langgraph
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
       - id: files
         name: Get changed files
         uses: Ana06/get-changed-files@v2.3.0
         with:
           format: json
       - name: Set up Python 3.11
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: "3.11"
           enable-cache: true
           cache-suffix: "bench"
       - name: Install dependencies
-        run: uv sync --group dev
+        run: uv sync --group test
       - name: Download baseline
-        uses: actions/cache/restore@v4
+        uses: actions/cache/restore@v5
         with:
           key: ${{ runner.os }}-benchmark-baseline
           restore-keys: |

.github/workflows/ci.yml

@@ -27,7 +27,7 @@ jobs:
       python: ${{ steps.filter.outputs.python }}
       deps: ${{ steps.filter.outputs.deps }}
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
       - uses: dorny/paths-filter@v3
         id: filter
         with:
@@ -100,7 +100,7 @@ jobs:
     name: "Check SDK methods matching"
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
       - name: Set up Python
         uses: actions/setup-python@v6
         with:
@@ -116,13 +116,13 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.11"
+          - "3.13"
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
       - name: Set up Python ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
-          python-version: "3.11"
+          python-version: "3.13"
           enable-cache: true
           cache-suffix: "schema-check-cli"
       - name: Install CLI dependencies

.github/workflows/codespell-ignore-words.txt

@@ -1,11 +0,0 @@
-LangChain
-LangGraph
-LangSmith
-thead
-stdio
-nd
-jupyter
-lets
-lite
-uis
-deque

.github/workflows/codespell.yml

@@ -1,49 +0,0 @@
----
-    name: CI / cd . / make spell_check
-    
-    on:
-      push:
-        branches: [main]
-      pull_request:
-        branches: [main]
-    
-    permissions:
-      contents: read
-
-    defaults:
-      run:
-        working-directory: docs
-
-    jobs:
-      codespell:
-        name: (Check for spelling errors)
-        runs-on: ubuntu-latest
-    
-        steps:
-          - name: Checkout
-            uses: actions/checkout@v5
-    
-          - name: Install Dependencies
-            run: |
-              pip install toml codespell==2.3.0 jupytext
-    
-          - name: Extract Ignore Words List
-            run: |
-              # Use a Python script to extract the ignore words list from pyproject.toml
-              python ../.github/workflows/extract_ignored_words_list.py
-            id: extract_ignore_words
-    
-          - name: Codespell
-            uses: codespell-project/actions-codespell@v2.1
-            with:
-              skip: '*.ambr,*.lock,*.ipynb,*.yaml,*.zlib,*.css.map,*.js.map'
-              ignore_words_list: ${{ steps.extract_ignore_words.outputs.ignore_words_list }}
-          # We do this to avoid spellchecking cell outputs
-          - name: Codespell Notebooks
-            run: make codespell
-          
-          - name: Codespell LangGraph Library
-            run: |
-              # Change to root directory to check the main LangGraph library
-              cd ..
-              codespell --skip="*.ambr,*.lock,*.ipynb,*.yaml,*.zlib,*.css.map,*.js.map,*.pyc,__pycache__/*" --ignore-words-list="${{ steps.extract_ignore_words.outputs.ignore_words_list }}" libs/langgraph/langgraph/

.github/workflows/deploy_docs.yml

@@ -1,150 +0,0 @@
-name: Deploy Docs
-
-on:
-  push:
-    branches:
-      - main
-  pull_request:
-    branches:
-      - main
-  workflow_dispatch:
-
-permissions:
-  contents: read
-  pages: write
-  id-token: write
-
-concurrency:
-  group: "pages"
-  cancel-in-progress: false
-
-defaults:
-  run:
-    working-directory: docs
-
-jobs:
-  get-changed-files:
-    runs-on: ubuntu-latest
-    outputs:
-      changed-files: ${{ steps.changed-files.outputs.added_modified }}
-    steps:
-      - uses: actions/checkout@v5
-      - name: Get changed files
-        id: changed-files
-        uses: Ana06/get-changed-files@v2.3.0
-        with:
-          filter: "docs/docs/**"
-
-  deploy:
-    runs-on: ubuntu-latest
-    timeout-minutes: 10 # Job will be cancelled if it runs for more than 10 minutes
-    env:
-      GITHUB_TOKEN: ${{ secrets.MKDOCS_GITHUB_TOKEN }}
-    steps:
-      - uses: actions/checkout@v5
-        with:
-          fetch-depth: 0
-
-      - name: Set up Python
-        uses: astral-sh/setup-uv@v6
-        with:
-          python-version: "3.12"
-          enable-cache: true
-          cache-suffix: "docs"
-
-      - name: Install dependencies
-        run: |
-          yarn
-          uv sync --all-groups
-          # we run this installation only for internal PRs
-          # as GITHUB_TOKEN is not available for PRs from outside contributors
-          if [ -n "${GITHUB_TOKEN}" ]; then
-            uv run pip install "git+https://${GITHUB_TOKEN}@github.com/langchain-ai/mkdocs-material-insiders.git"
-          fi
-
-      - name: Run unit tests
-        # Run unit tests on the docs build pipeline
-        run: make tests
-      - name: Lint Docs
-        # This step lints the docs using the existing linting set up.
-        # It should be very fast and should not require any external services.
-        run: make lint-docs
-      - name: Build llms-text
-        run: make llms-text
-      - name: Build site
-        run: |
-          # If this is main branch, then we want to download stats. we do this 
-          # with the env variable DOWNLOAD_STATS=true
-          if [ "${{ github.ref }}" == "refs/heads/main" ]; then
-            DOWNLOAD_STATS=true make build-docs
-          else
-            make build-docs
-          fi
-        env:
-          MKDOCS_GIT_COMMITTERS_APIKEY: ${{ secrets.MKDOCS_GIT_COMMITTERS_APIKEY }}
-          OPENAI_API_KEY: sf-proj-1234567890 # fake placeholder, shouldn't actually be used
-          ANTHROPIC_API_KEY: sk-ant-api03-1234567890 # fake placeholder, shouldn't actually be used
-      - name: Check links in notebooks
-        env:
-          LANGCHAIN_API_KEY: test
-        if: github.event_name == 'schedule'
-        run: |
-          if [ "${{ github.event_name }}" == "schedule" ]; then
-            echo "Running link check on all HTML files matching notebooks in docs directory..."
-            uv run pytest -v \
-              --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
-              --check-links-ignore "https://academy\.langchain\.com/.*" \
-              --check-links-ignore "https://x.com/.*" \
-              --check-links-ignore "https://twitter.com/.*" \
-              --check-links-ignore "https://github\.com/.*" \
-              --check-links-ignore "http://localhost:8123/.*" \
-              --check-links-ignore "http://localhost:2024.*" \
-              --check-links-ignore "http://127.0.0.1:.*" \
-              --check-links-ignore "/.*\.(ipynb|html)$" \
-              --check-links-ignore "https://python\.langchain\.com/.*" \
-              --check-links-ignore "https://openai\.com/.*" \
-              --check-links-ignore "https://www\.uber\.com/.*" \
-              --check-links-ignore "https://pepy\.tech/.*" \
-              --check-links-ignore "docs/docs/static/wordmark_*" \
-              --check-links $(find site -name "index.html" | grep -v 'storm/index.html')
-              
-          else
-            echo "Fetching changes from origin/main..."
-            git fetch origin main
-            echo "Checking for changed notebook files..."
-            CHANGED_FILES=$(git diff --name-only --diff-filter=d origin/main | grep 'docs/docs/.*\.ipynb$' | grep -v 'storm.ipynb' | sed -E 's|^docs/docs/|site/|; s/\.ipynb$/\/index.html/' || true)
-            echo "Changed files: ${CHANGED_FILES}"
-            if [ -n "${CHANGED_FILES}" ]; then
-              echo "Running link check on HTML files matching changed notebook files..."
-              uv run pytest -v \
-                --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
-                --check-links-ignore "https://academy\.langchain\.com/.*" \
-                --check-links-ignore "http://localhost:8123/.*" \
-                --check-links-ignore "http://localhost:2024.*" \
-                --check-links-ignore "http://127.0.0.1:.*" \
-                --check-links-ignore "https://x.com/.*" \
-                --check-links-ignore "https://twitter.com/.*" \
-                --check-links-ignore "https://github\.com/.*" \
-                --check-links-ignore "/.*\.(ipynb|html)$" \
-                --check-links-ignore "docs/docs/static/wordmark_*" \
-                --check-links ${CHANGED_FILES} \
-                || ([ $? = 5 ] && exit 0 || exit $?)
-            else
-              echo "No notebook files changed."
-            fi
-          fi
-
-      - name: Configure GitHub Pages
-        if: github.ref == 'refs/heads/main'
-        uses: actions/configure-pages@v5
-
-      - name: Upload Pages Artifact
-        # if: github.ref == 'refs/heads/main'
-        uses: actions/upload-pages-artifact@v4
-        with:
-          path: ./docs/site/
-
-      - name: Deploy to GitHub Pages
-        if: github.ref == 'refs/heads/main'
-        id: deployment
-        uses: actions/deploy-pages@v4

.github/workflows/extract_ignored_words_list.py

@@ -1,10 +0,0 @@
-import toml
-
-pyproject_toml = toml.load("pyproject.toml")
-
-# Extract the ignore words list (adjust the key as per your TOML structure)
-ignore_words_list = (
-    pyproject_toml.get("tool", {}).get("codespell", {}).get("ignore-words-list")
-)
-
-print(f"::set-output name=ignore_words_list::{ignore_words_list}")  # noqa: T201

.github/workflows/link_check.yml

@@ -1,49 +0,0 @@
-name: Check Docs & Links
-
-on:
-  pull_request:
-    branches:
-      - main
-  push:
-    branches:
-      - main
-  schedule:
-    - cron: "0 5 * * *"
-  workflow_dispatch:
-
-permissions:
-  contents: read
-
-jobs:
-  markdown-link-check:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v5
-        with:
-          fetch-depth: 0
-
-      - name: Check links in Markdown files
-        uses: gaurav-nelson/github-action-markdown-link-check@v1
-        with:
-          folder-path: "docs/"
-          check-modified-files-only: ${{ github.event_name != 'schedule' }}
-          file-path: "./README.md"
-          config-file: "./.markdown-link-check.config.json"
-
-  check-readmes-synced:
-    # This checks that the repo README.md is identical to the libs/langgraph/README.md
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v5
-        with:
-          fetch-depth: 1
-
-      - 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

.github/workflows/release.yml

@@ -16,7 +16,6 @@ env:
 
 jobs:
   build:
-    if: github.ref == 'refs/heads/main'
     runs-on: ubuntu-latest
 
     outputs:
@@ -26,10 +25,10 @@ jobs:
       tag: ${{ steps.check-version.outputs.tag }}
 
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
 
       - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           enable-cache: true
@@ -51,7 +50,7 @@ jobs:
         working-directory: ${{ inputs.working-directory }}
 
       - name: Upload build
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v6
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/
@@ -87,7 +86,7 @@ jobs:
     outputs:
       release-body: ${{ steps.generate-release-body.outputs.release-body }}
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
         with:
           repository: langchain-ai/langgraph
           path: langgraph
@@ -158,7 +157,7 @@ jobs:
       - test-pypi-publish
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
 
       # We explicitly *don't* set up caching here. This ensures our tests are
       # maximally sensitive to catching breakage.
@@ -174,7 +173,7 @@ jobs:
       #   used in the real world.
 
       - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           enable-cache: true
@@ -222,7 +221,7 @@ jobs:
           uv run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
 
       - name: Import test dependencies
-        run: uv sync --group dev
+        run: uv sync --group test
         working-directory: ${{ inputs.working-directory }}
 
       # Overwrite the local version of the package with the test PyPI version.
@@ -261,16 +260,16 @@ jobs:
         working-directory: ${{ inputs.working-directory }}
 
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
 
       - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           enable-cache: true
           cache-suffix: "release"
 
-      - uses: actions/download-artifact@v5
+      - uses: actions/download-artifact@v7
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/
@@ -302,16 +301,16 @@ jobs:
         working-directory: ${{ inputs.working-directory }}
 
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
 
       - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           enable-cache: true
           cache-suffix: "release"
 
-      - uses: actions/download-artifact@v5
+      - uses: actions/download-artifact@v7
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/
@@ -323,5 +322,6 @@ jobs:
           token: ${{ secrets.GITHUB_TOKEN }}
           generateReleaseNotes: false
           tag: ${{needs.build.outputs.tag}}
+          name: ${{ needs.build.outputs.pkg-name }}==${{ needs.build.outputs.version }}
           body: ${{ needs.release-notes.outputs.release-body }}
           commit: ${{ github.sha }}

.github/workflows/run_notebooks.yml

@@ -1,85 +0,0 @@
-name: Run notebooks
-
-on:
-  workflow_dispatch:
-  workflow_call:
-    inputs:
-      changed-files:
-        required: false
-        type: string
-        description: "JSON string of changed files"
-  schedule:
-    - cron: "0 13 * * *"
-
-permissions:
-  contents: read
-
-defaults:
-  run:
-    working-directory: docs
-
-jobs:
-  build:
-    runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        lib-version:
-          - "development"
-          - "latest"
-
-    steps:
-      - uses: actions/checkout@v5
-      - name: Set up Python + Poetry
-        uses: astral-sh/setup-uv@v6
-        with:
-          python-version: "3.11"
-          enable-cache: true
-          cache-suffix: "test-langgraph-notebooks"
-
-      - name: Install dependencies
-        run: |
-          uv sync --group test
-          uv run pip install jupyter
-
-      - name: Start services
-        run: make start-services
-
-      - name: Pre-download tiktoken files
-        run: |
-          uv run python _scripts/download_tiktoken.py
-
-      - name: Prepare notebooks
-        run: |
-          if [ "${{ matrix.lib-version }}" = "development" ]; then
-            uv run python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
-          else
-            uv run python _scripts/prepare_notebooks_for_ci.py
-          fi
-
-      - name: Run notebooks
-        env:
-          # these won't actually be used because of the VCR cassettes
-          # but need to set them to avoid triggering getpass()
-          OPENAI_API_KEY: "very-secret-key"
-          ANTHROPIC_API_KEY: "very-secret-key"
-          TAVILY_API_KEY: "very-secret-key"
-          LANGSMITH_API_KEY: "very-secret-key"
-          NOMIC_API_KEY: "very-secret-key"
-          COHERE_API_KEY: "very-secret-key"
-          FIREWORKS_API_KEY: "very-secret-key"
-        run: |
-          if [ "${{ github.event_name }}" = "workflow_dispatch" ] || [ "${{ github.event_name }}" = "schedule" ]; then
-            echo "Running all notebooks"
-            ./_scripts/execute_notebooks.sh
-          else
-            CHANGED_FILES=$(echo '${{ inputs.changed-files }}' | tr ' ' '\n' | sed 's|^docs/docs/|docs/|' | grep '\.ipynb$' || true)
-            if [ -n "$CHANGED_FILES" ]; then
-              echo "Running changed notebooks: $CHANGED_FILES"
-              ./_scripts/execute_notebooks.sh $CHANGED_FILES
-            else
-              echo "No notebook files changed, skipping execution"
-            fi
-          fi
-
-      - name: Stop services
-        run: make stop-services

.github/workflows/uv_lock_ugprade.yml

@@ -16,13 +16,13 @@ jobs:
     runs-on: ubuntu-latest
     
     steps:
-      - uses: actions/checkout@v5
+      - uses: actions/checkout@v6
       
       - name: Set up uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
         with:
           # use minimum supported Python version
-          python-version: "3.9"
+          python-version: "3.10"
           enable-cache: true
           cache-suffix: "uv-lock-upgrade"
           
@@ -30,7 +30,7 @@ jobs:
         run: make lock-upgrade
           
       - name: Create Pull Request
-        uses: peter-evans/create-pull-request@v7
+        uses: peter-evans/create-pull-request@v8
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           commit-message: "chore(deps): upgrade dependencies with `uv lock --upgrade`"

.gitignore

@@ -6,9 +6,6 @@ __pycache__/
 *.py[cod]
 *$py.class
 
-# C extensions
-*.so
-
 # Distribution / packaging
 .Python
 build/
@@ -54,27 +51,12 @@ coverage.xml
 .hypothesis/
 .pytest_cache/
 
-# Translations
-*.mo
-*.pot
-
 # Django stuff:
 *.log
 local_settings.py
 db.sqlite3
 db.sqlite3-journal
 
-# Flask stuff:
-instance/
-.webassets-cache
-
-# Scrapy stuff:
-.scrapy
-
-# Sphinx documentation
-docs/_build/
-docs/docs/_build/
-
 # PyBuilder
 target/
 
@@ -89,23 +71,9 @@ ipython_config.py
 # pyenv
 .python-version
 
-# pipenv
-#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
-#   However, in case of collaboration, if having platform-specific dependencies or dependencies
-#   having no cross-platform support, pipenv may install dependencies that don't work, or not
-#   install all needed dependencies.
-#Pipfile.lock
-
 # PEP 582; used by e.g. github.com/David-OConnor/pyflow
 __pypackages__/
 
-# Celery stuff
-celerybeat-schedule
-celerybeat.pid
-
-# SageMath parsed files
-*.sage.py
-
 # Environments
 .env
 .envrc
@@ -117,16 +85,6 @@ ENV/
 env.bak/
 venv.bak/
 
-# Spyder project settings
-.spyderproject
-.spyproject
-
-# Rope project settings
-.ropeproject
-
-# mkdocs documentation
-/site
-
 # mypy
 .mypy_cache/
 .dmypy.json
@@ -138,46 +96,6 @@ dmypy.json
 # macOS display setting files
 .DS_Store
 
-# Wandb directory
-wandb/
-
-# asdf tool versions
-.tool-versions
-/.ruff_cache/
-
-*.pkl
-*.bin
-
-# integration test artifacts
-data_map*
-\[('_type', 'fake'), ('stop', None)]
-
-# Replit files
-*replit*
-
-node_modules
-docs/.yarn/
-docs/node_modules/
-docs/.docusaurus/
-docs/.cache-loader/
-docs/_dist
-docs/api_reference/api_reference.rst
-docs/api_reference/experimental_api_reference.rst
-docs/api_reference/_build
-docs/api_reference/*/
-!docs/api_reference/_static/
-!docs/api_reference/templates/
-!docs/api_reference/themes/
-docs/docs_skeleton/build
-docs/docs_skeleton/node_modules
-docs/docs_skeleton/yarn.lock
-
-# Any new jupyter notebooks
-# not intended for the repo
-Untitled*.ipynb
-
-Chinook.db
-
 .vercel
 .turbo
 .editorconfig

.markdown-link-check.config.json

@@ -1,4 +0,0 @@
-{
-  "aliveStatusCodes": [200, 206, 402],
-  "ignorePatterns": ["*dcbadge.vercel.app*"]
-}

AGENTS.md

@@ -10,7 +10,7 @@ When you modify code in any library, run the following commands in that library'
 
 To run a particular test file or to pass additional pytest options you can specify the `TEST` variable:
 
-```
+```txt
 TEST=path/to/test.py make test
 ```
 
@@ -28,7 +28,7 @@ Below is a high-level overview:
 - **langgraph** – core framework for building stateful, multi-actor agents.
 - **prebuilt** – high-level APIs for creating and running agents and tools.
 - **sdk-js** – JS/TS SDK for interacting with the LangGraph REST API.
-- **sdk-py** – Python SDK for the LangGraph Platform API.
+- **sdk-py** – Python SDK for the LangGraph Server API.
 
 ### Dependency map
 

CLAUDE.md

@@ -0,0 +1,55 @@
+# AGENTS Instructions
+
+This repository is a monorepo. Each library lives in a subdirectory under `libs/`.
+
+When you modify code in any library, run the following commands in that library's directory before creating a pull request:
+
+- `make format` – run code formatters
+- `make lint` – run the linter
+- `make test` – execute the test suite
+
+To run a particular test file or to pass additional pytest options you can specify the `TEST` variable:
+
+```
+TEST=path/to/test.py make test
+```
+
+Other pytest arguments can also be supplied inside the `TEST` variable.
+
+## Libraries
+
+The repository contains several Python and JavaScript/TypeScript libraries.
+Below is a high-level overview:
+
+- **checkpoint** – base interfaces for LangGraph checkpointers.
+- **checkpoint-postgres** – Postgres implementation of the checkpoint saver.
+- **checkpoint-sqlite** – SQLite implementation of the checkpoint saver.
+- **cli** – official command-line interface for LangGraph.
+- **langgraph** – core framework for building stateful, multi-actor agents.
+- **prebuilt** – high-level APIs for creating and running agents and tools.
+- **sdk-js** – JS/TS SDK for interacting with the LangGraph REST API.
+- **sdk-py** – Python SDK for the LangGraph Server API.
+
+### Dependency map
+
+The diagram below lists downstream libraries for each production dependency as
+declared in that library's `pyproject.toml` (or `package.json`).
+
+```text
+checkpoint
+├── checkpoint-postgres
+├── checkpoint-sqlite
+├── prebuilt
+└── langgraph
+
+prebuilt
+└── langgraph
+
+sdk-py
+├── langgraph
+└── cli
+
+sdk-js (standalone)
+```
+
+Changes to a library may impact all of its dependents shown above.

CONTRIBUTING.md

@@ -1,293 +0,0 @@
-# Contributing to LangGraph
-
-Thank you for being interested in contributing to LangGraph!
-
-## General guidelines
-
-Here are some things to keep in mind for all types of contributions:
-
-- Follow the ["fork and pull request"](https://docs.github.com/en/get-started/exploring-projects-on-github/contributing-to-a-project) workflow.
-- Fill out the checked-in pull request template when opening pull requests. Note related issues and tag relevant maintainers.
-- Ensure your PR passes formatting, linting, and testing checks before requesting a review.
-  - If you would like comments or feedback, please tag a maintainer.
-- Backwards compatibility is key. Your changes must not be breaking, except in case of critical bug and security fixes.
-- Look for duplicate PRs or issues that have already been opened before opening a new one.
-- Keep scope as isolated as possible. As a general rule, your changes should not affect more than one package at a time.
-
-### Bugfixes
-
-For bug fixes, please open up an issue before proposing a fix to ensure the proposal properly addresses the underlying problem. In general, bug fixes should all have an accompanying unit test that fails before the fix.
-
-### New features
-
-For new features, please start a new [discussion](https://forum.langchain.com/), where the maintainers will help with scoping out the necessary changes.
-
-## Contribute Documentation
-
-Documentation is a vital part of LangGraph. We welcome both new documentation for new features and
-community improvements to our current documentation. Please read the resources below before getting started:
-
-- [Documentation style guide](#documentation-style-guide)
-- [Documentation setup](#setup)
-
-## Documentation Style Guide
-
-As LangGraph continues to grow, the surface area of documentation required to cover it continues to grow too.
-This page provides guidelines for anyone writing documentation for LangGraph, as well as some of our philosophies around organization and structure.
-
-## Philosophy
-
-LangGraph's documentation follows the [Diataxis framework](https://diataxis.fr).
-Under this framework, all documentation falls under one of four categories: [Tutorials](#tutorials),
-[How-to guides](#how-to-guides),
-[References](#references), and [Explanations (aka conceptual guides)](#conceptual-guide).
-
-### Tutorials
-
-Tutorials are lessons that take the reader through a practical activity. Their purpose is to help the user
-gain understanding of concepts and how they interact by showing one way to achieve some goal in a hands-on way.
-
-They should **avoid** giving
-multiple permutations of ways to achieve that goal in-depth. Choice is burdensome. Instead, they should guide a new user through a recommended path to accomplishing a concrete goal. While the end result of a tutorial does not necessarily need to
-be completely production-ready, it should be useful and practically satisfy the goal that you clearly stated in the tutorial's introduction.
-
-To quote the Diataxis website:
-
-> A tutorial serves the user’s *acquisition* of skills and knowledge - their study. Its purpose is not to help the user get something done, but to help them learn.
-
-In LangGraph, these are often higher level guides that show off end-to-end use cases.
-
-Some examples include:
-
-- [Build a Customer Support Bot](https://langchain-ai.github.io/langgraph/tutorials/customer-support/customer-support/)
-- [Build a SQL Agent](https://langchain-ai.github.io/langgraph/tutorials/sql/sql-agent/)
-
-Here are some high-level tips on writing a good tutorial:
-
-- Focus on guiding the user to get something done, but keep in mind the end-goal is more to impart principles than to create a perfect production system.
-- Be specific, not abstract and follow one path.
-  - No need to go deeply into alternative approaches, but it’s ok to reference them, ideally with a link to an appropriate how-to guide.
-- Get "a point on the board" as soon as possible - something the user can run that outputs something.
-  - You can iterate and expand afterwards.
-  - Try to frequently checkpoint at given steps where the user can run code and see progress.
-- Focus on results, not technical explanation.
-  - Crosslink heavily to appropriate conceptual/reference pages
-- The first time you mention a LangGraph concept, use its full name (e.g. "human-in-the-loop"), and link to its conceptual/other documentation page.
-  - It's also helpful to add a prerequisite callout that links to any pages with necessary background information.
-- End with a recap/next steps section summarizing what the tutorial covered and future reading, such as related how-to guides.
-- Use phrases like "Next we can run X & Y. We will expect Z.". Then afterwards, use language like "Notice Z" that recalls our expectations and directs the reader's attention to the topic we are trying to teach.
-- Do not shy away from repetition.
-
-### How-to guides
-
-A how-to guide, as the name implies, demonstrates how to do something discrete and specific.
-It should assume that the user is already familiar with underlying concepts, and is trying to solve an immediate problem, but
-should still give some background or list the scenarios where the information contained within can be relevant.
-They can and should discuss alternatives if one approach may be better than another in certain cases.
-
-To quote the Diataxis website:
-
-> A how-to guide serves the work of the already-competent user, whom you can assume to know what they want to do, and to be able to follow your instructions correctly.
-
-Some examples include:
-
-- [How to add persistence to your graph](https://langchain-ai.github.io/langgraph/how-tos/persistence/)
-- [How to view and update past graph state](https://langchain-ai.github.io/langgraph/how-tos/human_in_the_loop/time-travel/)
-
-Here are some high-level tips on writing a good how-to guide:
-
-- Clearly explain what you are guiding the user through at the start
-- Assume higher intent than a tutorial and show what the user needs to do to get that task done
-- Assume familiarity of concepts, but explain why suggested actions are helpful
-  - Crosslink heavily to conceptual/reference pages
-- Discuss alternatives and responses to real-world tradeoffs that may arise when solving a problem
-- Use lots of example code, ideally within complete code blocks that the reader can copy and run.
-- End with a recap/next steps section summarizing what the tutorial covered and future reading, such as other related how-to guides
-
-### Conceptual guides
-
-LangGraph's conceptual guides fall under the **Explanation** quadrant of Diataxis. They should cover LangChain terms and concepts
-in a more abstract way than how-to guides or tutorials, and should be geared towards curious users interested in
-gaining a deeper understanding of the framework. Try to avoid excessively large code examples. The goal here is to
-impart perspective to the user rather than to finish a practical project. These guides should cover **why** things work the way they do.
-
-To quote the Diataxis website:
-
-> The perspective of explanation is higher and wider than that of the other types. It does not take the user’s eye-level view, as in a how-to guide, or a close-up view of the machinery, like reference material. Its scope in each case is a topic - “an area of knowledge”, that somehow has to be bounded in a reasonable, meaningful way.
-
-Some examples include:
-
-- [What does it mean to be agentic?](https://langchain-ai.github.io/langgraph/concepts/high_level/)
-- [Tool calling](https://langchain-ai.github.io/langgraph/concepts/agentic_concepts/#tool-calling)
-
-Here are some high-level tips on writing a good conceptual guide:
-
-- Explain design decisions. Why does concept X exist and why was it designed this way?
-- Use analogies and reference other concepts and alternatives
-- Avoid blending in too much reference content
-- You can and should reference content covered in other guides, but make sure to link to them
-
-### References
-
-References contain detailed, low-level information that describes exactly what functionality exists and how to use it.
-In LangGraph, this is mainly our API reference pages, which are populated from docstrings within code.
-References pages are generally not read end-to-end, but are consulted as necessary when a user needs to know
-how to use something specific.
-
-To quote the Diataxis website:
-
-> The only purpose of a reference guide is to describe, as succinctly as possible, and in an orderly way. Whereas the content of tutorials and how-to guides are led by needs of the user, reference material is led by the product it describes.
-
-Many of the reference pages in LangChain are automatically generated from code,
-but here are some high-level tips on writing a good docstring:
-
-- Be concise
-- Discuss special cases and deviations from a user's expectations
-- Go into detail on required inputs and outputs
-- Light details on when one might use the feature are fine, but in-depth details belong in other sections.
-
-Each category serves a distinct purpose and requires a specific approach to writing and structuring the content.
-
-## General guidelines
-
-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 welcome updates as well as new integration docs, how-tos, and references.
-
-### Avoid duplication
-
-Multiple pages that cover the same material in depth are difficult to maintain and cause confusion. There should
-be only one (very rarely two), canonical pages for a given concept or feature. Instead, you should link to other guides.
-
-### Link to other sections
-
-Because sections of the docs do not exist in a vacuum, it is important to link to other sections as often as possible
-to allow a developer to learn more about an unfamiliar topic inline.
-
-This includes linking to the API references as well as conceptual sections!
-
-### Be concise
-
-In general, take a less-is-more approach. If a section with a good explanation of a concept already exists, you should link to it rather than
-re-explain it, unless the concept you are documenting presents some new wrinkle.
-
-Be concise, including in code samples.
-
-### General style
-
-- Use active voice and present tense whenever possible
-- Use examples and code snippets to illustrate concepts and usage
-- Use appropriate header levels (`#`, `##`, `###`, etc.) to organize the content hierarchically
-- Use fewer cells with more code to make copy/paste easier
-- Use bullet points and numbered lists to break down information into easily digestible chunks
-- Use tables (especially for **Reference** sections) and diagrams often to present information visually
-- Include the table of contents for longer documentation pages to help readers navigate the content, but hide it for shorter pages
-
-## Setup
-
-LangGraph documentation consists of two components:
-
-1. Main Documentation: Hosted at [https://langchain-ai.github.io/langgraph/](https://langchain-ai.github.io/langgraph/),
-this comprehensive resource serves as the primary user-facing documentation.
-It covers a wide array of topics, including tutorials, use cases, integrations,
-and more, offering extensive guidance on building with LangGraph.
-The content for this documentation lives in the `/docs` directory of the monorepo.
-2. In-code Documentation: This is documentation of the codebase itself, which is also
-used to generate the externally facing [API Reference](https://langchain-ai.github.io/langgraph/reference/graphs/).
-The content for the API reference is autogenerated by scanning the docstrings in the codebase. For this reason we ask that developers document their code well.
-
-We appreciate all contributions to the documentation, whether it be fixing a typo,
-adding a new tutorial or example and whether it be in the main documentation or the API Reference.
-
-### 📜 Main Documentation
-
-The content for the main documentation is located in the `/docs` directory of the monorepo.
-
-The documentation is written using a combination of ipython notebooks (`.ipynb` files)
-and markdown (`.md` files). The notebooks are converted to markdown
-and then built using [MkDocs](https://www.mkdocs.org/).
-
-Feel free to make contributions to the main documentation! 🥰
-
-After modifying the documentation:
-
-1. Run the linting and formatting commands (see below) to ensure that the documentation is well-formatted and free of errors.
-2. Optionally build the documentation locally to verify that the changes look good.
-3. Make a pull request with the changes.
-
-### ⚒️ Linting and Building Documentation Locally
-
-After writing up the documentation, you may want to lint and build the documentation
-locally to ensure that it looks good and is free of errors.
-
-If you're unable to build it locally that's okay as well, as you will be able to
-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
-```
-
-#### Building
-
-The code that builds the documentation is located in the `/docs` directory of the monorepo.
-
-Before building the documentation, it is always a good idea to clean the build directory:
-
-```bash
-make clean-docs
-```
-
-You can build and preview the documentation as outlined below:
-
-```bash
-make serve-docs
-```
-
-#### Linting
-
-To spell check the docs, run the following from the `docs` directory:
-
-```bash
-codespell --skip="*.ambr,*.lock,*.ipynb,*.yaml,*.zlib,*.css.map,*.js.map" --ignore-words-list="infor,thead,stdio,nd,jupyter,lets,lite,uis,deque" .
-```
-
-### ️In-code Documentation
-
-The in-code documentation is autogenerated from docstrings.
-
-For the API reference to be useful, the codebase must be well-documented. This means that all functions, classes, and methods should have a docstring that explains what they do, what the arguments are, and what the return value is. This is a good practice in general, but it is especially important for LangGraph because the API reference is the primary resource for developers to understand how to use the codebase.
-
-We generally follow the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html#38-comments-and-docstrings) for docstrings.
-
-Here is an example of a well-documented function:
-
-```python
-
-def my_function(arg1: int, arg2: str) -> float:
-    """This is a short description of the function. (It should be a single sentence.)
-
-    This is a longer description of the function. It should explain what
-    the function does, what the arguments are, and what the return value is.
-    It should wrap at 88 characters.
-
-    Examples:
-        This is a section for examples of how to use the function.
-
-        ```python
-        my_function(1, "hello")
-        \```
-
-    Args:
-        arg1: This is a description of arg1. We do not need to specify the type since
-            it is already specified in the function signature.
-        arg2: This is a description of arg2.
-
-    Returns:
-        This is a description of the return value.
-    """
-    return 3.14
-```

README.md

@@ -11,7 +11,7 @@
 [![Version](https://img.shields.io/pypi/v/langgraph.svg)](https://pypi.org/project/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/)
+[![Docs](https://img.shields.io/badge/docs-latest-blue)](https://docs.langchain.com/oss/python/langgraph/overview)
 
 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.
 
@@ -23,62 +23,69 @@ Install LangGraph:
 pip install -U langgraph
 ```
 
-Then, create an agent [using prebuilt components](https://langchain-ai.github.io/langgraph/agents/agents/):
+Create a simple workflow:
 
 ```python
-# pip install -qU "langchain[anthropic]" to call the model
+from langgraph.graph import START, StateGraph
+from typing_extensions import TypedDict
 
-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}!"
+class State(TypedDict):
+    text: str
 
-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"}]}
-)
+def node_a(state: State) -> dict:
+    return {"text": state["text"] + "a"}
+
+
+def node_b(state: State) -> dict:
+    return {"text": state["text"] + "b"}
+
+
+graph = StateGraph(State)
+graph.add_node("node_a", node_a)
+graph.add_node("node_b", node_b)
+graph.add_edge(START, "node_a")
+graph.add_edge("node_a", "node_b")
+
+print(graph.compile().invoke({"text": ""}))
+# {'text': 'ab'}
 ```
 
-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/).
+Get started with the [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart).
+
+To quickly build agents with LangChain's `create_agent` (built on LangGraph), see the [LangChain Agents documentation](https://docs.langchain.com/oss/python/langchain/agents).
 
 ## Core benefits
 
 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:
 
-- [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.
+- [Durable execution](https://docs.langchain.com/oss/python/langgraph/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://docs.langchain.com/oss/python/langgraph/interrupts): Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution.
+- [Comprehensive memory](https://docs.langchain.com/oss/python/langgraph/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.
+- [Production-ready deployment](https://docs.langchain.com/langsmith/app-development): Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows.
 
 ## LangGraph’s ecosystem
 
 While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents. To improve your LLM application development, pair LangGraph with:
 
 - [LangSmith](http://www.langchain.com/langsmith) — Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
-- [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
-- [LangChain](https://python.langchain.com/docs/introduction/) – Provides integrations and composable components to streamline LLM application development.
+- [LangSmith Deployment](https://docs.langchain.com/langsmith/deployments) — 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://docs.langchain.com/oss/python/langgraph/studio).
+- [LangChain](https://docs.langchain.com/oss/python/langchain/overview) – Provides integrations and composable components to streamline LLM application development.
 
 > [!NOTE]
-> Looking for the JS version of LangGraph? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://langchain-ai.github.io/langgraphjs/).
+> Looking for the JS version of LangGraph? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://docs.langchain.com/oss/javascript/langgraph/overview).
 
 ## Additional resources
 
-- [Guides](https://langchain-ai.github.io/langgraph/guides/): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
-- [Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
-- [Examples](https://langchain-ai.github.io/langgraph/examples/): Guided examples on getting started with LangGraph.
+- [Guides](https://docs.langchain.com/oss/python/langgraph/guides): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
+- [Reference](https://reference.langchain.com/python/langgraph/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
+- [Examples](https://docs.langchain.com/oss/python/langgraph/agentic-rag): Guided examples on getting started with LangGraph.
 - [LangChain Forum](https://forum.langchain.com/): Connect with the community and share all of your technical questions, ideas, and feedback.
 - [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.
 
 ## Acknowledgements
 
-LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
+LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.

docs/.gitignore

@@ -1,3 +0,0 @@
-site/
-
-.vercel

docs/Makefile

@@ -1,69 +0,0 @@
-.PHONY: lint-docs format-docs build-docs serve-docs serve-clean-docs clean-docs codespell llms-text build-prebuilt tests
-
-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 [ "$(DOWNLOAD_STATS)" = "true" ]; then \
-		set -x; \
-		uv run python -m _scripts.third_party_page.get_download_stats stats.yml; \
-		set +x; \
-	else \
-		set -x; \
-		uv run python -m _scripts.third_party_page.get_download_stats --fake stats.yml; \
-		set +x; \
-	fi
-	uv run python -m _scripts.third_party_page.create_third_party_page stats.yml docs/agents/prebuilt.md
-
-build-docs: build-prebuilt
-	TARGET_LANGUAGE=python uv run python -m mkdocs build --clean -f mkdocs.yml --strict
-
-build-docs-js: build-prebuilt
-	TARGET_LANGUAGE=js uv run python -m mkdocs build --clean -f mkdocs.yml --strict
-
-llms-text:
-	uv run python -m _scripts.generate_llms_text docs/llms-full.txt
-
-install-vercel-deps:
-	curl -sL "https://astral.sh/uv/install.sh" | bash -s
-	export PATH="${HOME}/.cargo/bin:${PATH}"
-	uv venv --python 3.11
-	uv sync --all-groups
-
-tests:
-	# Run unit tests
-	uv run pytest tests/unit_tests
-
-
-vercel-build-docs: install-vercel-deps
-	make build-docs
-
-
-serve-clean-docs: clean-docs
-	uv run python -m mkdocs serve -c -f mkdocs.yml --strict -w ../libs/langgraph
-
-serve-docs:
-	uv 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
-	rm -rf site
-
-## Run format against the project documentation.
-format-docs:
-	uv run ruff format docs
-	uv run ruff check --fix docs
-
-# Check the docs for linting violations
-lint-docs:
-	uv run ruff format --check docs
-	uv run ruff check docs
-
-codespell:
-	./codespell_notebooks.sh .
-
-start-services:
-	docker compose -f test-compose.yml up -V --force-recreate --wait --remove-orphans
-
-stop-services:
-	docker compose -f test-compose.yml down

docs/README.md

@@ -1,164 +0,0 @@
-# LangGraph Documentation
-
-For more information on contributing to our documentation, see the [Contributing Guide](../CONTRIBUTING.md).
-
-## Structure
-
-The primary documentation is located in the `docs/` directory. This directory contains both the source files for the main documentation as well as the API reference doc build process.
-
-### Main Documentation
-
-Main documentation files are located in `docs/docs/` and are written in Markdown format. The site uses [**MkDocs**](https://www.mkdocs.org/) with the [Material theme](https://squidfunk.github.io/mkdocs-material/) and includes:
-
-- **Concepts**: Core LangGraph concepts and explanations
-- **Tutorials**: Step-by-step learning guides
-- **How-tos**: Task-focused guides for specific use cases
-- **Examples**: Real-world applications and use cases
-- **Jupyter Notebooks**: Interactive tutorials that are automatically converted to markdown
-
-### API Reference
-
-API reference documentation is defined in `docs/docs/reference/`. Each `.md` file outlines the "template" that each page is built from. Reference content is automatically generated from docstrings in the codebase using the **mkdocstrings** plugin. Once generated, the content is plugged into the corresponding markdown file where it is referenced by using manual directives to specify which classes and/or functions are documented:
-
-```markdown
-::: langgraph.graph.state.StateGraph
-    options:
-      show_if_no_docstring: true
-      show_root_heading: true
-      show_root_full_path: false
-      members:
-        - add_node
-        - add_edge
-        - add_conditional_edges
-        - add_sequence
-        - compile
-```
-
-## Build Process
-
-Docs are built following these steps:
-
-1. **Content Processing:**
-   - `_scripts/notebook_hooks.py` - Main processing pipeline that:
-     - Converts how-tos/tutorial Jupyter notebooks to markdown using `notebook_convert.py`
-     - Adds automatic API reference links to code blocks using `generate_api_reference_links.py`
-     - Handles conditional rendering for Python/JS versions
-     - Processes highlight comments and custom syntax
-
-2. **API Reference Generation:**
-   - **mkdocstrings** plugin extracts docstrings from Python source code
-   - Manual `::: module.Class` directives in reference pages (`/docs/docs/*`) specify what to document
-   - Cross-references are automatically generated between docs and API
-
-3. **Site Generation:**
-   - **MkDocs** processes all markdown files and generates static HTML
-   - Custom hooks handle redirects and inject additional functionality
-
-4. **Deployment:**
-   - Site is deployed with Vercel
-   - `make build-docs` generates production build (also usable for local testing)
-   - Automatic redirects handle URL changes between versions
-
-### Local Development
-
-For local development, use the Makefile targets:
-
-```bash
-# Serve docs locally with hot reloading
-make serve-docs
-
-# Clean build for production testing
-make build-docs
-
-# Serve with clean build
-make serve-clean-docs
-```
-
-The `serve-docs` command:
-
-- Watches source files for changes
-- Includes dirty builds for faster iteration
-- Serves on [http://127.0.0.1:8000/langgraph/](http://127.0.0.1:8000/langgraph/)
-
-## Standards
-
-**Docstring Format:**
-The API reference uses **Google-style docstrings** with Markdown markup. The `mkdocstrings` plugin processes these to generate documentation.
-
-**Required format:**
-
-```python
-def example_function(param1: str, param2: int = 5) -> bool:
-    """Brief description of the function.
-
-    Longer description can go here. Use Markdown syntax for
-    rich formatting like **bold** and *italic*.
-
-    Args:
-        param1: Description of the first parameter.
-        param2: Description of the second parameter with default value.
-
-    Returns:
-        Description of the return value.
-
-    Raises:
-        ValueError: When param1 is empty.
-        TypeError: When param2 is not an integer.
-
-    !!! warning
-        This function is experimental and may change.
-
-    !!! version-added "Added in version 0.2.0"
-    """
-```
-
-**Special Markers:**
-
-- **MkDocs admonitions**: `!!! warning`, `!!! note`, `!!! version-added`
-- **Code blocks**: Standard markdown ``` syntax
-- **Cross-references**: Automatic linking via `generate_api_reference_links.py`
-
-## Execute notebooks
-
-If you would like to automatically execute all of the notebooks, to mimic the "Run notebooks" GitHub action, you can run:
-
-```bash
-python _scripts/prepare_notebooks_for_ci.py
-./_scripts/execute_notebooks.sh
-```
-
-**Note**: if you want to run the notebooks without `%pip install` cells, you can run:
-
-```bash
-python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
-./_scripts/execute_notebooks.sh
-```
-
-`prepare_notebooks_for_ci.py` script will add VCR cassette context manager for each cell in the notebook, so that:
-
-- when the notebook is run for the first time, cells with network requests will be recorded to a VCR cassette file
-- when the notebook is run subsequently, the cells with network requests will be replayed from the cassettes
-
-## Adding new notebooks
-
-If you are adding a notebook with API requests, it's **recommended** to record network requests so that they can be subsequently replayed. If this is not done, the notebook runner will make API requests every time the notebook is run, which can be costly and slow.
-
-To record network requests, please make sure to first run `prepare_notebooks_for_ci.py` script.
-
-Then, run
-
-```bash
-jupyter execute <path_to_notebook>
-```
-
-Once the notebook is executed, you should see the new VCR cassettes recorded in `cassettes` directory and discard the updated notebook.
-
-## Updating existing notebooks
-
-If you are updating an existing notebook, please make sure to remove any existing cassettes for the notebook in `cassettes` directory (each cassette is prefixed with the notebook name), and then run the steps from the "Adding new notebooks" section above.
-
-To delete cassettes for a notebook, you can run:
-
-```bash
-rm cassettes/<notebook_name>*
-```

docs/_scripts/_patch.py

@@ -1,93 +0,0 @@
-import functools
-
-from urllib3 import __version__ as urllib3version  # type: ignore[import-untyped]
-from urllib3 import connection  # type: ignore[import-untyped]
-
-
-def _ensure_str(s, encoding="utf-8", errors="strict") -> str:
-    if isinstance(s, str):
-        return s
-
-    if isinstance(s, bytes):
-        return s.decode(encoding, errors)
-    return str(s)
-
-
-# Copied from https://github.com/urllib3/urllib3/blob/1c994dfc8c5d5ecaee8ed3eb585d4785f5febf6e/src/urllib3/connection.py#L231
-def request(self, method, url, body=None, headers=None):
-    """Make the request.
-
-    This function is based on the urllib3 request method, with modifications
-    to handle potential issues when using vcrpy in concurrent workloads.
-
-    Args:
-        self: The HTTPConnection instance.
-        method (str): The HTTP method (e.g., 'GET', 'POST').
-        url (str): The URL for the request.
-        body (Optional[Any]): The body of the request.
-        headers (Optional[dict]): Headers to send with the request.
-
-    Returns:
-        The result of calling the parent request method.
-    """
-    # Update the inner socket's timeout value to send the request.
-    # This only triggers if the connection is reused.
-    if getattr(self, "sock", None) is not None:
-        self.sock.settimeout(self.timeout)
-
-    if headers is None:
-        headers = {}
-    else:
-        # Avoid modifying the headers passed into .request()
-        headers = headers.copy()
-    if "user-agent" not in (_ensure_str(k.lower()) for k in headers):
-        headers["User-Agent"] = connection._get_default_user_agent()
-    # The above is all the same ^^^
-    # The following is different:
-    return self._parent_request(method, url, body=body, headers=headers)
-
-
-_PATCHED = False
-
-
-def patch_urllib3():
-    """Patch the request method of urllib3 to avoid type errors when using vcrpy.
-
-    In concurrent workloads (such as the tracing background queue), the
-    connection pool can get in a state where an HTTPConnection is created
-    before vcrpy patches the HTTPConnection class. In urllib3 >= 2.0 this isn't
-    a problem since they use the proper super().request(...) syntax, but in older
-    versions, super(HTTPConnection, self).request is used, resulting in a TypeError
-    since self is no longer a subclass of "HTTPConnection" (which at this point
-    is vcr.stubs.VCRConnection).
-
-    This method patches the class to fix the super() syntax to avoid mixed inheritance.
-    In the case of the LangSmith tracing logic, it doesn't really matter since we always
-    exclude cache checks for calls to LangSmith.
-
-    The patch is only applied for urllib3 versions older than 2.0.
-    """
-    global _PATCHED
-    if _PATCHED:
-        return
-    from packaging import version
-
-    if version.parse(urllib3version) >= version.parse("2.0"):
-        _PATCHED = True
-        return
-
-    # Lookup the parent class and its request method
-    parent_class = connection.HTTPConnection.__bases__[0]
-    parent_request = parent_class.request
-
-    def new_request(self, *args, **kwargs):
-        """Handle parent request.
-
-        This method binds the parent's request method to self and then
-        calls our modified request function.
-        """
-        self._parent_request = functools.partial(parent_request, self)
-        return request(self, *args, **kwargs)
-
-    connection.HTTPConnection.request = new_request
-    _PATCHED = True

docs/_scripts/download_tiktoken.py

@@ -1,5 +0,0 @@
-import tiktoken
-
-# This will trigger the download and caching of the necessary files
-for encoding in ("gpt2", "gpt-3.5"):
-    tiktoken.encoding_for_model(encoding)

docs/_scripts/execute_notebooks.sh

@@ -1,36 +0,0 @@
-#!/bin/bash
-
-# Read the list of notebooks to skip from the JSON file
-SKIP_NOTEBOOKS=$(python -c "import json; print('\n'.join(json.load(open('notebooks_no_execution.json'))))")
-
-# Function to execute a single notebook
-execute_notebook() {
-    file="$1"
-    echo "Starting execution of $file"
-    start_time=$(date +%s)
-    if ! output=$(time uv run jupyter execute "$file" 2>&1); then
-        end_time=$(date +%s)
-        execution_time=$((end_time - start_time))
-        echo "Error in $file. Execution time: $execution_time seconds"
-        echo "Error details: $output"
-        exit 1
-    fi
-    end_time=$(date +%s)
-    execution_time=$((end_time - start_time))
-    echo "Finished $file. Execution time: $execution_time seconds"
-}
-
-export -f execute_notebook
-
-# Check if custom notebook paths are provided
-if [ $# -gt 0 ]; then
-    notebooks=$(echo "$@" | tr ' ' '\n' | grep -vFf <(echo "$SKIP_NOTEBOOKS"))
-else
-    # Find all notebooks and filter out those in the skip list
-    notebooks=$(find docs/tutorials docs/how-tos -name "*.ipynb" | grep -v ".ipynb_checkpoints" | grep -vFf <(echo "$SKIP_NOTEBOOKS"))
-fi
-
-# Execute notebooks sequentially
-for file in $notebooks; do
-    execute_notebook "$file"
-done

docs/_scripts/generate_api_reference_links.py

@@ -1,296 +0,0 @@
-"""Generate API reference links for imports in Python code blocks within markdown files."""
-
-import ast
-import importlib
-import logging
-import re
-from functools import lru_cache
-from typing import List, Optional
-
-from typing_extensions import TypedDict
-
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-# Base URL for all class documentation
-_LANGCHAIN_API_REFERENCE = "https://python.langchain.com/api_reference/"
-_LANGGRAPH_API_REFERENCE = "https://langchain-ai.github.io/langgraph/reference/"
-
-
-# (alias/re-exported modules, source module, class, docs namespace)
-MANUAL_API_REFERENCES_LANGGRAPH = [
-    (
-        ["langgraph.prebuilt"],
-        "langgraph.prebuilt.chat_agent_executor",
-        "create_react_agent",
-        "prebuilt",
-    ),
-    (
-        [],
-        "langgraph.prebuilt.chat_agent_executor",
-        "AgentState",
-        "prebuilt",
-    ),
-    (["langgraph.prebuilt"], "langgraph.prebuilt.tool_node", "ToolNode", "prebuilt"),
-    (
-        ["langgraph.prebuilt"],
-        "langgraph.prebuilt.tool_node",
-        "tools_condition",
-        "prebuilt",
-    ),
-    (
-        ["langgraph.prebuilt"],
-        "langgraph.prebuilt.tool_node",
-        "InjectedState",
-        "prebuilt",
-    ),
-    # Graph
-    (["langgraph.graph"], "langgraph.graph.message", "add_messages", "graphs"),
-    (["langgraph.graph"], "langgraph.graph.state", "StateGraph", "graphs"),
-    (["langgraph.graph"], "langgraph.graph.state", "CompiledStateGraph", "graphs"),
-    (["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.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 = {
-    (module_, class_): (source_module, namespace)
-    for (modules, source_module, class_, namespace) in MANUAL_API_REFERENCES_LANGGRAPH
-    for module_ in modules + [source_module]
-}
-
-
-@lru_cache(maxsize=10_000)
-def _get_full_module_name(module_path: str, class_name: 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
-    except AttributeError as e:
-        logger.warning(f"API Reference: Could not find module for {class_name}, {e}")
-        return None
-    except ImportError as e:
-        logger.warning(f"API Reference: Failed to load for class {class_name}, {e}")
-        return None
-
-
-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.
-
-
-def get_imports(code: str, path: 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.
-        path: The path of the file where the markdown content originated.
-
-    Returns:
-        A list of import information for each import found.
-    """
-    # Parse the code into an AST.
-    try:
-        tree = ast.parse(code)
-    except SyntaxError:
-        return []
-
-    found_imports = []
-
-    # 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:
-                continue
-            for alias in node.names:
-                if not (
-                    node.module.startswith("langchain")
-                    or node.module.startswith("langgraph")
-                ):
-                    continue
-
-                found_imports.append(
-                    {
-                        "source": node.module,
-                        # alias.name is the original name even if an alias exists.
-                        "imported": alias.name,
-                    }
-                )
-
-    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"
-            )
-        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:
-    """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.
-
-    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.
-
-    Example:
-        Given a markdown with a Python code block:
-
-        ```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.
-    """
-    code_block_pattern = re.compile(
-        r"(?P<indent>[ \t]*)```(?P<language>python|py)\n(?P<code>.*?)\n(?P=indent)```",
-        re.DOTALL,
-    )
-
-    def replace_code_block(match: re.Match) -> str:
-        """Replace the matched code block with additional API reference links if imports are found.
-
-        Args:
-            match (re.Match): The regex match object containing the code block.
-
-        Returns:
-            str: The modified code block with API reference links prepended if applicable.
-        """
-        indent = match.group("indent")
-        code_block = match.group("code")
-        # Retrieve import information from the code block
-        imports = get_imports(code_block, "__unused__")
-
-        original_code_block = match.group(0)
-        # If no imports are found, return the original code block
-        if not imports:
-            return original_code_block
-
-        # Generate API reference links for each import
-        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}"
-
-    # Apply the replace_code_block function to all matches in the markdown
-    updated_markdown = code_block_pattern.sub(replace_code_block, markdown)
-    return updated_markdown

docs/_scripts/generate_llms_text.py

@@ -1,296 +0,0 @@
-"""Experimental script to generate consolidated llms text from the docs."""
-
-import asyncio
-import glob
-import os
-import re
-from typing import TypedDict, List, Optional
-
-import yaml
-from langchain.chat_models import init_chat_model
-from langchain_core.rate_limiters import InMemoryRateLimiter
-from mkdocs.structure.files import File
-from mkdocs.structure.pages import Page
-from pydantic import BaseModel, Field
-from yaml import SafeLoader
-
-from _scripts.notebook_hooks import _on_page_markdown_with_config
-
-HERE = os.path.dirname(os.path.abspath(__file__))
-# Get source directory (parent of HERE / docs)
-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:
-    """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)
-    all_files.extend(
-        glob.glob(os.path.join(SOURCE_DIR, "how-tos/*.ipynb"), recursive=True)
-    )
-    all_files.extend(
-        glob.glob(os.path.join(SOURCE_DIR, "concepts/*.md"), recursive=True)
-    )
-    all_files.extend(
-        glob.glob(os.path.join(SOURCE_DIR, "concepts/*.ipynb"), recursive=True)
-    )
-
-    all_content = []
-
-    # Process files concurrently
-    tasks = [convert_ipynb_to_md(file_path) for file_path in all_files]
-    results = await asyncio.gather(*tasks)
-
-    # Combine results with file paths
-    for file_path, processed_content in zip(all_files, results):
-        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
-            all_content.append(processed_content)
-
-    # Write consolidated output
-    with open(output_file, "w", encoding="utf-8") as f:
-        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
-
-    parser = argparse.ArgumentParser(
-        description=(
-            "Generate consolidated text file from markdown/notebook files for LLMs."
-        )
-    )
-    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)

docs/_scripts/handle_auto_links.py

@@ -1,181 +0,0 @@
-"""Logic to identify and transform cross-reference links in markdown files.
-
-This module allows supporting custom markdown syntax for "autolinks". These are links
-that will be transformed based on the current scope context, such as "global", "python",
-or "js" into an appropriate markdown link format.
-
-For example,
-
-```markdown
-@[StateGraph]
-```
-
-May be transformed into:
-
-```markdown
-[StateGraph](some_path/api-reference/state-graph.md)
-```
-
-The transformation value depends on the scope in which the link is used.
-"""
-
-import logging
-import re
-from typing import Optional
-
-from _scripts.link_map import SCOPE_LINK_MAPS
-
-logger = logging.getLogger(__name__)
-
-
-def _transform_link(
-    link_name: str, scope: str, file_path: str, line_number: int, custom_title: Optional[str] = None
-) -> Optional[str]:
-    """Transform a cross-reference link based on the current scope.
-
-    Args:
-        link_name: The name of the link to transform (e.g., "StateGraph").
-        scope: The current scope context ("global", "python", "js", etc.).
-        file_path: The file path for error reporting.
-        line_number: The line number for error reporting.
-        custom_title: Optional custom title for the link. If None, uses link_name.
-
-    Returns:
-        A formatted markdown link if the link is found in the scope mapping,
-        None otherwise.
-
-    Example:
-        >>> _transform_link("StateGraph", "python", "file.md", 5)
-        "[StateGraph](https://langchain-ai.github.io/langgraph/reference/graphs/#langgraph.graph.StateGraph)"
-
-        >>> _transform_link("StateGraph", "python", "file.md", 5, "Custom Title")
-        "[Custom Title](https://langchain-ai.github.io/langgraph/reference/graphs/#langgraph.graph.StateGraph)"
-
-        >>> _transform_link("unknown-link", "python", "file.md", 5)
-        None
-    """
-    if scope == "global":
-        # Special scope that is composed of both Python and JS links
-        # For now, we will substitute in the python scope!
-        # But we need to add support for handling both scopes.
-        scope = "python"
-        logger.error(
-            "Encountered unhandled 'global' scope. Defaulting to 'python'."
-            "In file: %s, line %d, link_name: %s",
-            file_path,
-            line_number,
-            link_name,
-        )
-    link_map = SCOPE_LINK_MAPS.get(scope, {})
-    url = link_map.get(link_name)
-
-    if url:
-        title = custom_title if custom_title is not None else link_name
-        return f"[{title}]({url})"
-    else:
-        # Log error with file location information
-        logger.info(
-            # Using %s
-            "Link '%s' not found in scope '%s'. "
-            "In file: %s, line %d. Available links in scope: %s",
-            link_name,
-            scope,
-            file_path,
-            line_number,
-            list(link_map.keys() if link_map else []),
-        )
-        return None
-
-
-CONDITIONAL_FENCE_PATTERN = re.compile(
-    r"""
-    ^                       # Start of line
-    (?P<indent>[ \t]*)      # Optional indentation (spaces or tabs)
-    :::                     # Literal fence marker
-    (?P<language>\w+)?      # Optional language identifier (named group: language)
-    \s*                     # Optional trailing whitespace
-    $                       # End of line
-    """,
-    re.VERBOSE,
-)
-CROSS_REFERENCE_PATTERN = re.compile(
-    r"""
-    (?:                     # Non-capturing group for two possible formats:
-        @\[                 # @ symbol followed by opening bracket for title
-        (?P<title>[^\]]+)   # Custom title - one or more non-bracket characters
-        \]                  # Closing bracket for title
-        \[                  # Opening bracket for link name
-        (?P<link_name_with_title>[^\]]+)  # Link name - one or more non-bracket characters
-        \]                  # Closing bracket for link name
-        |                   # OR
-        @\[                 # @ symbol followed by opening bracket
-        (?P<link_name>[^\]]+)   # Link name - one or more non-bracket characters
-        \]                  # Closing bracket
-    )
-    """,
-    re.VERBOSE,
-)
-
-
-def _replace_autolinks(markdown: str, file_path: str, *, default_scope: str = "python") -> str:
-    """Preprocess markdown lines to handle @[links] with conditional fence scopes.
-
-    This function processes markdown content to transform @[link_name] references
-    based on the current conditional fence scope. Conditional fences use the
-    syntax :::language to define scope boundaries.
-
-    Args:
-        markdown: The markdown content to process.
-        file_path: The file path for error reporting.
-        default_scope: The default scope to use if no scope is matched.
-
-    Returns:
-        Processed markdown content with @[references] transformed to proper
-        markdown links or left unchanged if not found.
-
-    Example:
-        Input:
-            "@[StateGraph]\\n:::python\\n@[Command]\\n:::\\n"
-        Output:
-            "[StateGraph](url)\\n:::python\\n[Command](url)\\n:::\\n"
-    """
-    # Track the current scope context
-    current_scope = default_scope
-    lines = markdown.splitlines(keepends=True)
-    processed_lines = []
-
-    for line_number, line in enumerate(lines, 1):
-        line_stripped = line.strip()
-
-        # Check if this line defines a new conditional fence scope
-        fence_match = CONDITIONAL_FENCE_PATTERN.match(line_stripped)
-        if fence_match:
-            language = fence_match.group("language")
-            # Set scope to the specified language, or reset to global if no language
-            current_scope = language.lower() if language else default_scope
-            processed_lines.append(line)
-            continue
-
-        # Transform all @[link_name] references in this line based on current scope
-        def replace_cross_reference(match: re.Match[str]) -> str:
-            """Replace a single @[link_name] with the scoped equivalent."""
-            # Check if this is the @[title][ref] format or @[ref] format
-            title = match.group("title")
-            if title is not None:
-                # This is @[title][ref] format
-                link_name = match.group("link_name_with_title")
-                custom_title = title
-            else:
-                # This is @[ref] format
-                link_name = match.group("link_name")
-                custom_title = None
-            
-            transformed = _transform_link(
-                link_name, current_scope, file_path, line_number, custom_title
-            )
-            return transformed if transformed is not None else match.group(0)
-
-        transformed_line = CROSS_REFERENCE_PATTERN.sub(replace_cross_reference, line)
-        processed_lines.append(transformed_line)
-
-    return "".join(processed_lines)

docs/_scripts/js_translation/add_translation.py

@@ -1,236 +0,0 @@
-"""Translate Python markdown to TypeScript and/or consolidate Python-JS markdown into a single document."""
-
-import argparse
-
-import requests
-from langchain_anthropic import ChatAnthropic
-from textwrap import dedent
-
-
-# Load reference TypeScript snippets
-URL = "https://gist.githubusercontent.com/dqbd/b35d49e2ceec80e654fe1c5ab61ec477/raw/f4768aeedb67628190a4e06d063a938afc8e7672/snippets.md"
-response = requests.get(URL)
-response.raise_for_status()
-reference_snippets = response.text
-
-# Initialize model
-model = ChatAnthropic(model="claude-sonnet-4-0", max_tokens=64_000)
-
-
-FLUENT_INTERFACE_PROMPT = (
-    "CRITICAL: Always use method chaining (fluent interface) for StateGraph operations in TypeScript. "
-    "Never create separate variables for the graph builder or call methods individually. "
-    "The fluent interface provides better type safety and is the preferred pattern.\n\n"
-    "CORRECT examples with fluent interface:\n"
-    + dedent(
-        """
-        ```typescript
-        const graph = new StateGraph(MyState)
-          .addNode('node1', node1)
-          .addNode('node2', node2)
-          .addEdge(START, 'node1')
-          .addEdge('node1', 'node2')
-          .addEdge('node2', END)
-          .compile()
-        ```
-        
-        ```typescript
-        const graph = new StateGraph(MyState)
-          .addNode('chatbot', chatbot)
-          .addEdge(START, 'chatbot')
-          .addEdge('chatbot', END)
-          .compile()
-        ```
-        
-        ```typescript
-        const graph = new StateGraph(MyState)
-          .addNode('chatbot', chatbot)
-          .addEdge(START, 'chatbot')
-          .addEdge('chatbot', END)
-          .compile()
-        ```
-        """
-    )
-    + "\n"
-    + "INCORRECT examples to avoid:\n"
-    + dedent(
-        """
-        ```typescript
-        // WRONG: Creating separate builder variable
-        const graphBuilder = new StateGraph(MyState)
-        graphBuilder.addNode('node1', node1)
-        graphBuilder.addEdge(START, 'node1')
-        const graph = graphBuilder.compile()
-        ```
-        
-        ```typescript
-        // WRONG: Using Python-style method names
-        const workflow = new StateGraph(MyState)
-        workflow.add_node('node1', node1)
-        workflow.add_edge(START, 'node1')
-        const graph = workflow.compile()
-        ```
-        
-        ```typescript
-        // WRONG: Calling methods individually
-        const graphBuilder = new StateGraph(MyState)
-        graphBuilder.addNode('chatbot', chatbot)
-        graphBuilder.addEdge(START, 'chatbot')
-        graphBuilder.addEdge('chatbot', END)
-        const graph = graphBuilder.compile()
-        ```
-        """
-    )
-    + "\n"
-    + "Key rules:\n"
-    + "- Always chain methods directly on the StateGraph constructor\n"
-    + "- Use camelCase method names (addNode, addEdge, not add_node, add_edge)\n"
-    + "- Always end with .compile()\n"
-    + "- Never store the builder in a separate variable\n"
-)
-
-
-TRANSLATION_PROMPT = (
-    "You are a helpful assistant that translates Python-based technical "
-    "documentation written in Markdown to equivalent TypeScript-based documentation. "
-    "The input is a Markdown file written in mkdocs format. It contains "
-    "Python code snippets embedded in prose. "
-    "Your task is to rewrite the content by translating the Python code to "
-    "idiomatic TypeScript, using the provided TypeScript reference snippets "
-    "to ensure accurate and consistent usage (e.g., correct imports, function "
-    "names, and patterns). "
-    "Remove the original Python code and replace it with the corresponding "
-    "TypeScript version. "
-    "Do not alter the surrounding prose unless a change is necessary to "
-    "reflect differences between Python and TypeScript. "
-    "Preserve the structure and formatting of the original Markdown document. "
-    "Do not make stylistic or structural changes unless they directly support "
-    "the translation. "
-    "Use the reference TypeScript snippets as guidance whenever possible to "
-    "maintain alignment with existing conventions.\n\n"
-    "IMPORTANT REQUIREMENTS:\n"
-    "- Use Zod for state definition for StateGraph. Avoid using Annotation since it will be deprecated in the future.\n"
-    "- ALWAYS use fluent interface (method chaining) for StateGraph operations - this is CRITICAL\n"
-    "- Never create separate variables for graph builders\n"
-    "- Always chain methods directly on the StateGraph constructor and end with .compile()\n\n"
-    f"{FLUENT_INTERFACE_PROMPT}\n\n"
-    f"Here are the reference TypeScript snippets:\n\n{reference_snippets}\n\n"
-)
-
-CONSOLIDATION_PROMPT = (
-    "You are a helpful assistant that consolidates parallel Python and JavaScript (TypeScript) technical documentation "
-    "written in Markdown into a single unified Markdown document. "
-    "The input consists of two documents: the first is for Python users, and the second is for JavaScript/TypeScript users. "
-    "Your task is to merge these into one Markdown file using language-specific fenced blocks to separate the content where needed. "
-    "Use the following syntax to distinguish content for each language:\n\n"
-    ":::python\n"
-    "# Python-specific content\n"
-    ":::\n\n"
-    ":::js\n"
-    "# JavaScript/TypeScript-specific content\n"
-    ":::\n\n"
-    "Follow these consolidation rules:\n"
-    "- When content (prose or code) is the same or nearly identical in both versions, include it only once—outside of any fenced block.\n"
-    "- When content differs between the Python and JS versions, wrap each version in its corresponding fenced block.\n"
-    "- Prefer **paragraph-level separation** of language-specific content. Do not combine Python and JS snippets or terminology in the same sentence or paragraph using conditional phrases.\n"
-    "  For example, avoid inline constructs like:\n"
-    "  `The :::python add_messages ::: :::js reducer ::: function...`\n"
-    "  Instead, write two distinct paragraphs:\n\n"
-    "  :::python\n"
-    "  The `add_messages` function in our `State` will append the LLM's response messages to whatever messages are already in the state.\n"
-    "  ::: \n\n"
-    "  :::js\n"
-    "  The `reducer` function in our `StateAnnotation` will append the LLM's response messages to whatever messages are already in the state.\n"
-    "  :::\n\n"
-    "- Preserve the overall structure, ordering, and formatting of the original Markdown documents.\n"
-    "- Do not rephrase or unify content unless it is logically and semantically identical.\n"
-    "- Use the fenced blocks for both prose and code as needed, and ensure output is clean, readable Markdown suitable for tools that parse these directives.\n"
-    "Your goal is to produce a cleanly merged documentation file that serves both Python and JavaScript users without redundancy, while maximizing clarity and separation of language-specific details."
-)
-
-
-def translate_python_to_ts(markdown_content: str) -> str:
-    response = model.invoke(
-        [
-            {
-                "role": "system",
-                "content": TRANSLATION_PROMPT,
-                "cache_control": {"type": "ephemeral"},
-            },
-            {"role": "user", "content": markdown_content},
-        ]
-    )
-    return response.content
-
-
-def consolidate_python_and_ts(combined_content: str) -> str:
-    response = model.invoke(
-        [
-            {
-                "role": "system",
-                "content": CONSOLIDATION_PROMPT,
-                "cache_control": {"type": "ephemeral"},
-            },
-            {"role": "user", "content": combined_content},
-        ]
-    )
-    return response.content
-
-
-def main(file_path: str, translate_only: bool, consolidate_only: bool) -> None:
-    with open(file_path, "r", encoding="utf-8") as f:
-        markdown_content = f.read()
-
-    if translate_only:
-        translated = translate_python_to_ts(markdown_content)
-        output_path = file_path.replace(".md", ".translated.md")
-        with open(output_path, "w", encoding="utf-8") as f:
-            f.write(translated)
-        print(f"Translated JS/TS version written to: {output_path}")
-
-    elif consolidate_only:
-        consolidated = consolidate_python_and_ts(markdown_content)
-        with open(file_path, "w", encoding="utf-8") as f:
-            f.write(consolidated)
-        print(f"Consolidated content written to: {file_path}")
-
-    else:
-        # Default behavior: translate first, then consolidate both
-        translated = translate_python_to_ts(markdown_content)
-        combined = f"{markdown_content.strip()}\n\n\n{translated.strip()}"
-        consolidated = consolidate_python_and_ts(combined)
-        with open(file_path, "w", encoding="utf-8") as f:
-            f.write(consolidated)
-        print(f"Translated and consolidated content written to: {file_path}")
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
-        description=(
-            "Translate Python markdown to TypeScript and/or consolidate "
-            "Python-JS markdown into one file."
-        )
-    )
-    parser.add_argument("file_path", type=str, help="Path to the markdown file.")
-    parser.add_argument(
-        "--translate-only",
-        action="store_true",
-        help="Only generate the JS translation.",
-    )
-    parser.add_argument(
-        "--consolidate-only",
-        action="store_true",
-        help="Only consolidate pre-paired Python and JS content.",
-    )
-    args = parser.parse_args()
-
-    if args.translate_only and args.consolidate_only:
-        raise ValueError(
-            "Cannot use both --translate-only and --consolidate-only at the same time."
-        )
-
-    main(
-        args.file_path,
-        translate_only=args.translate_only,
-        consolidate_only=args.consolidate_only,
-    )

docs/_scripts/js_translation/codeblocks/.gitkeep

@@ -1,6 +0,0 @@
-.prettierrc
-.eslint.config.mjs
-package.json
-README.md
-tsconfig.json
-yarn.lock

docs/_scripts/js_translation/codeblocks/.prettierrc

@@ -1,19 +0,0 @@
-{
-  "$schema": "https://json.schemastore.org/prettierrc",
-  "printWidth": 80,
-  "tabWidth": 2,
-  "useTabs": false,
-  "semi": true,
-  "singleQuote": false,
-  "quoteProps": "as-needed",
-  "jsxSingleQuote": false,
-  "trailingComma": "es5",
-  "bracketSpacing": true,
-  "arrowParens": "always",
-  "requirePragma": false,
-  "insertPragma": false,
-  "proseWrap": "preserve",
-  "htmlWhitespaceSensitivity": "css",
-  "vueIndentScriptAndStyle": false,
-  "endOfLine": "lf"
-}

docs/_scripts/js_translation/codeblocks/README.md

@@ -1 +0,0 @@
-# \_codeblocks

docs/_scripts/js_translation/codeblocks/eslint.config.mjs

@@ -1,14 +0,0 @@
-import js from "@eslint/js";
-import globals from "globals";
-import tseslint from "typescript-eslint";
-import { defineConfig } from "eslint/config";
-
-export default defineConfig([
-  {
-    files: ["**/*.{js,mjs,cjs,ts,mts,cts}"],
-    plugins: { js },
-    extends: ["js/recommended"],
-    languageOptions: { globals: globals.browser },
-  },
-  tseslint.configs.recommended,
-]);

docs/_scripts/js_translation/codeblocks/package.json

@@ -1,27 +0,0 @@
-{
-  "name": "_codeblocks",
-  "packageManager": "yarn@4.6.0",
-  "scripts": {
-    "lint": "eslint .",
-    "lint:fix": "eslint . --fix",
-    "format": "prettier --write .",
-    "format:fix": "prettier --write . --fix"
-  },
-  "dependencies": {
-    "@langchain/anthropic": "^0.3.24",
-    "@langchain/core": "^0.3.66",
-    "@langchain/langgraph": "^0.3.11",
-    "@langchain/langgraph-api": "^0.0.52",
-    "@langchain/langgraph-sdk": "^0.0.102",
-    "@langchain/openai": "^0.6.3",
-    "zod": "^4.0.10"
-  },
-  "devDependencies": {
-    "@eslint/js": "^9.32.0",
-    "eslint": "^9.32.0",
-    "globals": "^16.3.0",
-    "jiti": "^2.5.1",
-    "typescript": "^5.8.3",
-    "typescript-eslint": "^8.38.0"
-  }
-}

docs/_scripts/js_translation/codeblocks/tsconfig.json

@@ -1,114 +0,0 @@
-{
-  "compilerOptions": {
-    /* Visit https://aka.ms/tsconfig to read more about this file */
-
-    /* Projects */
-    // "incremental": true,                              /* Save .tsbuildinfo files to allow for incremental compilation of projects. */
-    // "composite": true,                                /* Enable constraints that allow a TypeScript project to be used with project references. */
-    // "tsBuildInfoFile": "./.tsbuildinfo",              /* Specify the path to .tsbuildinfo incremental compilation file. */
-    // "disableSourceOfProjectReferenceRedirect": true,  /* Disable preferring source files instead of declaration files when referencing composite projects. */
-    // "disableSolutionSearching": true,                 /* Opt a project out of multi-project reference checking when editing. */
-    // "disableReferencedProjectLoad": true,             /* Reduce the number of projects loaded automatically by TypeScript. */
-
-    /* Language and Environment */
-    "target": "esnext",                                  /* Set the JavaScript language version for emitted JavaScript and include compatible library declarations. */
-    // "lib": [],                                        /* Specify a set of bundled library declaration files that describe the target runtime environment. */
-    // "jsx": "preserve",                                /* Specify what JSX code is generated. */
-    // "libReplacement": true,                           /* Enable lib replacement. */
-    // "experimentalDecorators": true,                   /* Enable experimental support for legacy experimental decorators. */
-    // "emitDecoratorMetadata": true,                    /* Emit design-type metadata for decorated declarations in source files. */
-    // "jsxFactory": "",                                 /* Specify the JSX factory function used when targeting React JSX emit, e.g. 'React.createElement' or 'h'. */
-    // "jsxFragmentFactory": "",                         /* Specify the JSX Fragment reference used for fragments when targeting React JSX emit e.g. 'React.Fragment' or 'Fragment'. */
-    // "jsxImportSource": "",                            /* Specify module specifier used to import the JSX factory functions when using 'jsx: react-jsx*'. */
-    // "reactNamespace": "",                             /* Specify the object invoked for 'createElement'. This only applies when targeting 'react' JSX emit. */
-    // "noLib": true,                                    /* Disable including any library files, including the default lib.d.ts. */
-    // "useDefineForClassFields": true,                  /* Emit ECMAScript-standard-compliant class fields. */
-    // "moduleDetection": "auto",                        /* Control what method is used to detect module-format JS files. */
-
-    /* Modules */
-    "module": "nodenext",                                /* Specify what module code is generated. */
-    // "rootDir": "./",                                  /* Specify the root folder within your source files. */
-    "moduleResolution": "nodenext",                     /* Specify how TypeScript looks up a file from a given module specifier. */
-    // "baseUrl": "./",                                  /* Specify the base directory to resolve non-relative module names. */
-    // "paths": {},                                      /* Specify a set of entries that re-map imports to additional lookup locations. */
-    // "rootDirs": [],                                   /* Allow multiple folders to be treated as one when resolving modules. */
-    // "typeRoots": [],                                  /* Specify multiple folders that act like './node_modules/@types'. */
-    // "types": [],                                      /* Specify type package names to be included without being referenced in a source file. */
-    // "allowUmdGlobalAccess": true,                     /* Allow accessing UMD globals from modules. */
-    // "moduleSuffixes": [],                             /* List of file name suffixes to search when resolving a module. */
-    // "allowImportingTsExtensions": true,               /* Allow imports to include TypeScript file extensions. Requires '--moduleResolution bundler' and either '--noEmit' or '--emitDeclarationOnly' to be set. */
-    // "rewriteRelativeImportExtensions": true,          /* Rewrite '.ts', '.tsx', '.mts', and '.cts' file extensions in relative import paths to their JavaScript equivalent in output files. */
-    // "resolvePackageJsonExports": true,                /* Use the package.json 'exports' field when resolving package imports. */
-    // "resolvePackageJsonImports": true,                /* Use the package.json 'imports' field when resolving imports. */
-    // "customConditions": [],                           /* Conditions to set in addition to the resolver-specific defaults when resolving imports. */
-    // "noUncheckedSideEffectImports": true,             /* Check side effect imports. */
-    // "resolveJsonModule": true,                        /* Enable importing .json files. */
-    // "allowArbitraryExtensions": true,                 /* Enable importing files with any extension, provided a declaration file is present. */
-    // "noResolve": true,                                /* Disallow 'import's, 'require's or '<reference>'s from expanding the number of files TypeScript should add to a project. */
-
-    /* JavaScript Support */
-    // "allowJs": true,                                  /* Allow JavaScript files to be a part of your program. Use the 'checkJS' option to get errors from these files. */
-    // "checkJs": true,                                  /* Enable error reporting in type-checked JavaScript files. */
-    // "maxNodeModuleJsDepth": 1,                        /* Specify the maximum folder depth used for checking JavaScript files from 'node_modules'. Only applicable with 'allowJs'. */
-
-    /* Emit */
-    // "declaration": true,                              /* Generate .d.ts files from TypeScript and JavaScript files in your project. */
-    // "declarationMap": true,                           /* Create sourcemaps for d.ts files. */
-    // "emitDeclarationOnly": true,                      /* Only output d.ts files and not JavaScript files. */
-    // "sourceMap": true,                                /* Create source map files for emitted JavaScript files. */
-    // "inlineSourceMap": true,                          /* Include sourcemap files inside the emitted JavaScript. */
-    // "noEmit": true,                                   /* Disable emitting files from a compilation. */
-    // "outFile": "./",                                  /* Specify a file that bundles all outputs into one JavaScript file. If 'declaration' is true, also designates a file that bundles all .d.ts output. */
-    // "outDir": "./",                                   /* Specify an output folder for all emitted files. */
-    // "removeComments": true,                           /* Disable emitting comments. */
-    // "importHelpers": true,                            /* Allow importing helper functions from tslib once per project, instead of including them per-file. */
-    // "downlevelIteration": true,                       /* Emit more compliant, but verbose and less performant JavaScript for iteration. */
-    // "sourceRoot": "",                                 /* Specify the root path for debuggers to find the reference source code. */
-    // "mapRoot": "",                                    /* Specify the location where debugger should locate map files instead of generated locations. */
-    // "inlineSources": true,                            /* Include source code in the sourcemaps inside the emitted JavaScript. */
-    // "emitBOM": true,                                  /* Emit a UTF-8 Byte Order Mark (BOM) in the beginning of output files. */
-    // "newLine": "crlf",                                /* Set the newline character for emitting files. */
-    // "stripInternal": true,                            /* Disable emitting declarations that have '@internal' in their JSDoc comments. */
-    // "noEmitHelpers": true,                            /* Disable generating custom helper functions like '__extends' in compiled output. */
-    // "noEmitOnError": true,                            /* Disable emitting files if any type checking errors are reported. */
-    // "preserveConstEnums": true,                       /* Disable erasing 'const enum' declarations in generated code. */
-    // "declarationDir": "./",                           /* Specify the output directory for generated declaration files. */
-
-    /* Interop Constraints */
-    // "isolatedModules": true,                          /* Ensure that each file can be safely transpiled without relying on other imports. */
-    // "verbatimModuleSyntax": true,                     /* Do not transform or elide any imports or exports not marked as type-only, ensuring they are written in the output file's format based on the 'module' setting. */
-    // "isolatedDeclarations": true,                     /* Require sufficient annotation on exports so other tools can trivially generate declaration files. */
-    // "erasableSyntaxOnly": true,                       /* Do not allow runtime constructs that are not part of ECMAScript. */
-    // "allowSyntheticDefaultImports": true,             /* Allow 'import x from y' when a module doesn't have a default export. */
-    "esModuleInterop": true,                             /* Emit additional JavaScript to ease support for importing CommonJS modules. This enables 'allowSyntheticDefaultImports' for type compatibility. */
-    // "preserveSymlinks": true,                         /* Disable resolving symlinks to their realpath. This correlates to the same flag in node. */
-    "forceConsistentCasingInFileNames": true,            /* Ensure that casing is correct in imports. */
-
-    /* Type Checking */
-    "strict": false,                                      /* Enable all strict type-checking options. */
-    // "noImplicitAny": true,                            /* Enable error reporting for expressions and declarations with an implied 'any' type. */
-    // "strictNullChecks": true,                         /* When type checking, take into account 'null' and 'undefined'. */
-    // "strictFunctionTypes": true,                      /* When assigning functions, check to ensure parameters and the return values are subtype-compatible. */
-    // "strictBindCallApply": true,                      /* Check that the arguments for 'bind', 'call', and 'apply' methods match the original function. */
-    // "strictPropertyInitialization": true,             /* Check for class properties that are declared but not set in the constructor. */
-    // "strictBuiltinIteratorReturn": true,              /* Built-in iterators are instantiated with a 'TReturn' type of 'undefined' instead of 'any'. */
-    // "noImplicitThis": true,                           /* Enable error reporting when 'this' is given the type 'any'. */
-    // "useUnknownInCatchVariables": true,               /* Default catch clause variables as 'unknown' instead of 'any'. */
-    // "alwaysStrict": true,                             /* Ensure 'use strict' is always emitted. */
-    // "noUnusedLocals": true,                           /* Enable error reporting when local variables aren't read. */
-    // "noUnusedParameters": true,                       /* Raise an error when a function parameter isn't read. */
-    // "exactOptionalPropertyTypes": true,               /* Interpret optional property types as written, rather than adding 'undefined'. */
-    // "noImplicitReturns": true,                        /* Enable error reporting for codepaths that do not explicitly return in a function. */
-    // "noFallthroughCasesInSwitch": true,               /* Enable error reporting for fallthrough cases in switch statements. */
-    // "noUncheckedIndexedAccess": true,                 /* Add 'undefined' to a type when accessed using an index. */
-    // "noImplicitOverride": true,                       /* Ensure overriding members in derived classes are marked with an override modifier. */
-    // "noPropertyAccessFromIndexSignature": true,       /* Enforces using indexed accessors for keys declared using an indexed type. */
-    // "allowUnusedLabels": true,                        /* Disable error reporting for unused labels. */
-    // "allowUnreachableCode": true,                     /* Disable error reporting for unreachable code. */
-
-    /* Completeness */
-    // "skipDefaultLibCheck": true,                      /* Skip type checking .d.ts files that are included with TypeScript. */
-    "skipLibCheck": true                                 /* Skip type checking all .d.ts files. */
-    ""
-  }
-}

docs/_scripts/js_translation/extract_codeblocks.py

@@ -1,150 +0,0 @@
-#!/usr/bin/env python
-"""Extracts typescript code blocks from a markdown file."""
-
-import argparse
-import json
-import re
-import os
-from typing import List, TypedDict, Literal
-
-
-class CodeBlock(TypedDict):
-    """A code block extracted from a markdown file."""
-    starting_line: int
-    """The line number where the code block starts in the source file"""
-    ending_line: int
-    """The line number where the code block ends in the source file"""
-    indentation: int
-    """Number of spaces/tabs used for indentation of the code block"""
-    source_file: str
-    """Path to the markdown file containing this code block"""
-    frontmatter: str
-    """Any metadata or frontmatter specified after the opening code fence"""
-    code: str
-    """The actual code content within the code block"""
-    language: str
-    """The language of the code block (e.g. typescript, javascript)"""
-
-
-def extract_code_blocks(markdown_content: str, source_file: str) -> List[CodeBlock]:
-    """Extracts code blocks from a markdown file.
-
-    Args:
-        markdown_content: The content of the markdown file.
-        source_file: The path to the markdown file.
-
-    Returns:
-        A list of TypedDicts, where each dict represents a code block.
-    """
-    # Regex to find code blocks with specified languages, capturing indentation
-    # and frontmatter.
-    pattern = re.compile(
-        r"^(?P<indentation>\s*)```(?P<language>typescript|javascript|ts|js)(?P<frontmatter>[^\n]*)\n(?P<code>.*?)\n^(?P=indentation)```\s*$",
-        re.DOTALL | re.MULTILINE,
-    )
-
-    code_blocks: List[CodeBlock] = []
-    for match in pattern.finditer(markdown_content):
-        start_pos = match.start()
-
-        # Calculate line numbers
-        starting_line = markdown_content.count("\n", 0, start_pos) + 1
-        ending_line = starting_line + match.group(0).count("\n")
-
-        indentation_str = match.group("indentation")
-
-        code_block: CodeBlock = {
-            "starting_line": starting_line,
-            "ending_line": ending_line,
-            "indentation": len(indentation_str),
-            "source_file": source_file,
-            "frontmatter": match.group("frontmatter").strip(),
-            "code": match.group("code"),
-            "language": match.group("language"),
-        }
-        code_blocks.append(code_block)
-
-    return code_blocks
-
-def dump_code_blocks(input_file: str, output_file: str, format: Literal["json", "inline"]) -> None:
-    """Function to extract and save code blocks from a markdown file.
-
-    Args:
-        input_file: Path to the input markdown file.
-        output_file: Path to the output JSON file for the extracted code blocks.
-        format: Output format - either "json" or "inline"
-    """
-    with open(input_file, "r", encoding="utf-8") as f:
-        markdown_content = f.read()
-
-    extracted_code = extract_code_blocks(markdown_content, input_file)
-
-    if len(extracted_code) == 0:
-        print(f"No code blocks found in {input_file}")
-        return
-    
-    if format == "json":
-        with open(output_file, "w", encoding="utf-8") as f:
-            json.dump(extracted_code, f, indent=2)
-    elif format == "inline":
-        with open(output_file, "w", encoding="utf-8") as f:
-            for code_block in extracted_code:
-                f.write(f"// {json.dumps({k:v for k,v in code_block.items() if k != 'code'})}\n")
-                f.write("\n")
-                f.write(code_block["code"])
-                f.write("\n")
-    print(f"Extracted {len(extracted_code)} code blocks from {input_file} to {output_file}")
-
-def main(input_path: str, output_path: str, format: Literal["json", "inline"]) -> None:
-    """Main function to extract code blocks from a markdown file.
-
-    Args:
-        input_file: Path to the input markdown file.
-        output_file: Path to the output JSON file for the extracted code blocks.
-        format: Output format - either "json" or "inline"
-    """
-    # Check if input path is a directory
-    if os.path.isdir(input_path):
-        if os.path.isfile(output_path):
-            raise ValueError("If input_path is a directory, output_path must also be a directory")
-        if not os.path.isdir(output_path):
-            os.makedirs(output_path, exist_ok=True)
-        
-        # Process each markdown file in the directory recursively
-        for root, _, files in os.walk(input_path):
-            for filename in files:
-                if filename.endswith(".md"):
-                    # Get relative path to maintain directory structure
-                    rel_path = os.path.relpath(root, input_path)
-                    input_file = os.path.join(root, filename)
-                    # Create output directory if it doesn't exist
-                    output_dir = os.path.join(output_path, rel_path)
-                    os.makedirs(output_dir, exist_ok=True)
-                    output_file = os.path.join(output_dir, filename.replace(".md", ".ts"))
-                    dump_code_blocks(input_file, output_file, format)
-    else:
-        # Process single file
-        dump_code_blocks(input_path, output_path, format)
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
-        description="Extract typescript code blocks from a markdown file."
-    )
-    parser.add_argument(
-        "input_file",
-        help="Path to the input markdown file.",
-    )
-    parser.add_argument(
-        "output_file",
-        help="Path to the output JSON file for the extracted code blocks.",
-    )
-    parser.add_argument(
-        "--format",
-        choices=["json", "inline"],
-        default="json",
-        help="Output format - either 'json' or 'inline'",
-    )
-    args = parser.parse_args()
-
-    main(args.input_file, args.output_file, args.format)

docs/_scripts/link_map.py

@@ -1,127 +0,0 @@
-"""Link mapping for cross-reference resolution across different scopes.
-
-This module provides link mappings for different language/framework scopes
-to resolve @[link_name] references to actual URLs.
-"""
-
-# Python-specific link mappings
-PYTHON_LINK_MAP = {
-    "StateGraph": "reference/graphs/#langgraph.graph.StateGraph",
-    "add_conditional_edges": "reference/graphs/#langgraph.graph.state.StateGraph.add_conditional_edges",
-    "add_edge": "reference/graphs/#langgraph.graph.state.StateGraph.add_edge",
-    "add_node": "reference/graphs/#langgraph.graph.state.StateGraph.add_node",
-    "add_messages": "reference/graphs/#langgraph.graph.message.add_messages",
-    "ToolNode": "reference/agents/#langgraph.prebuilt.tool_node.ToolNode",
-    "CompiledStateGraph.astream": "reference/graphs/#langgraph.graph.state.CompiledStateGraph.astream",
-    "Pregel.astream": "reference/pregel/#langgraph.pregel.Pregel.astream",
-    "AsyncPostgresSaver": "reference/checkpoints/#langgraph.checkpoint.postgres.aio.AsyncPostgresSaver",
-    "AsyncSqliteSaver": "reference/checkpoints/#langgraph.checkpoint.sqlite.aio.AsyncSqliteSaver",
-    "BaseCheckpointSaver": "reference/checkpoints/#langgraph.checkpoint.base.BaseCheckpointSaver",
-    "BaseStore": "reference/store/#langgraph.store.base.BaseStore",
-    "BaseStore.put": "reference/store/#langgraph.store.base.BaseStore.put",
-    "BinaryOperatorAggregate": "reference/pregel/#langgraph.pregel.Pregel--advanced-channels-context-and-binaryoperatoraggregate",
-    "CipherProtocol": "reference/checkpoints/#langgraph.checkpoint.serde.base.CipherProtocol",
-    "client.runs.stream": "cloud/reference/sdk/python_sdk_ref/#langgraph_sdk.client.RunsClient.stream",
-    "client.runs.wait": "cloud/reference/sdk/python_sdk_ref/#langgraph_sdk.client.RunsClient.wait",
-    "client.threads.get_history": "cloud/reference/sdk/python_sdk_ref/#langgraph_sdk.client.ThreadsClient.get_history",
-    "client.threads.update_state": "cloud/reference/sdk/python_sdk_ref/#langgraph_sdk.client.ThreadsClient.update_state",
-    "Command": "reference/types/#langgraph.types.Command",
-    "CompiledStateGraph": "reference/graphs/#langgraph.graph.state.CompiledStateGraph",
-    "create_react_agent": "reference/prebuilt/#langgraph.prebuilt.chat_agent_executor.create_react_agent",
-    "create_supervisor": "reference/supervisor/#langgraph_supervisor.supervisor.create_supervisor",
-    "EncryptedSerializer": "reference/checkpoints/#langgraph.checkpoint.serde.encrypted.EncryptedSerializer",
-    "entrypoint.final": "reference/func/#langgraph.func.entrypoint.final",
-    "entrypoint": "reference/func/#langgraph.func.entrypoint",
-    "from_pycryptodome_aes": "reference/checkpoints/#langgraph.checkpoint.serde.encrypted.EncryptedSerializer.from_pycryptodome_aes",
-    "get_state_history": "reference/graphs/#langgraph.graph.state.CompiledStateGraph.get_state_history",
-    "get_stream_writer": "reference/config/#langgraph.config.get_stream_writer",
-    "HumanInterrupt": "reference/prebuilt/#langgraph.prebuilt.interrupt.HumanInterrupt",
-    "InjectedState": "reference/agents/#langgraph.prebuilt.tool_node.InjectedState",
-    "InMemorySaver": "reference/checkpoints/#langgraph.checkpoint.memory.InMemorySaver",
-    "interrupt": "reference/types/#langgraph.types.Interrupt",
-    "CompiledStateGraph.invoke": "reference/graphs/#langgraph.graph.state.CompiledStateGraph.invoke",
-    "JsonPlusSerializer": "reference/checkpoints/#langgraph.checkpoint.serde.jsonplus.JsonPlusSerializer",
-    "langgraph.json": "cloud/reference/cli/#configuration-file",
-    "LastValue": "reference/channels/#langgraph.channels.LastValue",
-    "PostgresSaver": "reference/checkpoints/#langgraph.checkpoint.postgres.PostgresSaver",
-    "Pregel": "reference/pregel/",
-    "Pregel.stream": "reference/pregel/#langgraph.pregel.Pregel.stream",
-    "pre_model_hook": "reference/prebuilt/#langgraph.prebuilt.chat_agent_executor.create_react_agent",
-    "protocol": "reference/checkpoints/#langgraph.checkpoint.serde.base.SerializerProtocol",
-    "Send": "reference/types/#langgraph.types.Send",
-    "SerializerProtocol": "reference/checkpoints/#langgraph.checkpoint.serde.base.SerializerProtocol",
-    "SqliteSaver": "reference/checkpoints/#langgraph.checkpoint.sqlite.SqliteSaver",
-    "START": "reference/constants/#langgraph.constants.START",
-    "CompiledStateGraph.stream": "reference/graphs/#langgraph.graph.state.CompiledStateGraph.stream",
-    "task": "reference/func/#langgraph.func.task",
-    "Topic": "reference/channels/#langgraph.channels.Topic",
-    "update_state": "reference/graphs/#langgraph.graph.state.CompiledStateGraph.update_state",
-}
-
-# JavaScript-specific link mappings
-JS_LINK_MAP = {
-    "Auth": "reference/classes/sdk_auth.Auth.html",
-    "StateGraph": "reference/classes/langgraph.StateGraph.html",
-    "add_conditional_edges": "/reference/classes/langgraph.StateGraph.html#addConditionalEdges",
-    "add_edge": "reference/classes/langgraph.StateGraph.html#addEdge",
-    "add_node": "reference/classes/langgraph.StateGraph.html#addNode",
-    "add_messages": "reference/modules/langgraph.html#addMessages",
-    "ToolNode": "reference/classes/langgraph_prebuilt.ToolNode.html",
-    "BaseCheckpointSaver": "reference/classes/checkpoint.BaseCheckpointSaver.html",
-    "BaseStore": "reference/classes/checkpoint.BaseStore.html",
-    "BaseStore.put": "reference/classes/checkpoint.BaseStore.html#put",
-    "BinaryOperatorAggregate": "reference/classes/langgraph.BinaryOperatorAggregate.html",
-    "client.runs.stream": "reference/classes/sdk_client.RunsClient.html#stream",
-    "client.runs.wait": "reference/classes/sdk_client.RunsClient.html#wait",
-    "client.threads.get_history": "reference/classes/sdk_client.ThreadsClient.html#getHistory",
-    "client.threads.update_state": "reference/classes/sdk_client.ThreadsClient.html#updateState",
-    "Command": "reference/classes/langgraph.Command.html",
-    "CompiledStateGraph": "reference/classes/langgraph.CompiledStateGraph.html",
-    "create_react_agent": "reference/functions/langgraph_prebuilt.createReactAgent.html",
-    "create_supervisor": "reference/functions/langgraph_supervisor.createSupervisor.html",
-    "entrypoint.final": "reference/functions/langgraph.entrypoint.html#final",
-    "entrypoint": "reference/functions/langgraph.entrypoint.html",
-    "getContextVariable": "https://v03.api.js.langchain.com/functions/_langchain_core.context.getContextVariable.html",
-    "get_state_history": "reference/classes/langgraph.CompiledStateGraph.html#getStateHistory",
-    "HumanInterrupt": "reference/interfaces/langgraph_prebuilt.HumanInterrupt.html",
-    "interrupt": "reference/functions/langgraph.interrupt-2.html",
-    "CompiledStateGraph.invoke": "reference/classes/langgraph.CompiledStateGraph.html#invoke",
-    "langgraph.json": "cloud/reference/cli/#configuration-file",
-    "MemorySaver": "reference/classes/checkpoint.MemorySaver.html",
-    "messagesStateReducer": "reference/functions/langgraph.messagesStateReducer.html",
-    "PostgresSaver": "reference/classes/checkpoint_postgres.PostgresSaver.html",
-    "Pregel": "reference/classes/langgraph.Pregel.html",
-    "Pregel.stream": "reference/classes/langgraph.Pregel.html#stream",
-    "pre_model_hook": "reference/functions/langgraph_prebuilt.createReactAgent.html",
-    "protocol": "reference/interfaces/checkpoint.SerializerProtocol.html",
-    "Send": "reference/classes/langgraph.Send.html",
-    "SerializerProtocol": "reference/interfaces/checkpoint.SerializerProtocol.html",
-    "SqliteSaver": "reference/classes/checkpoint_sqlite.SqliteSaver.html",
-    "START": "reference/variables/langgraph.START.html",
-    "CompiledStateGraph.stream": "reference/classes/langgraph.CompiledStateGraph.html#stream",
-    "task": "reference/functions/langgraph.task.html",
-    ## TODO (hntrl): export Topic from langgraphjs
-    # "Topic": "reference/classes/langgraph_channels.Topic.html",
-    "update_state": "reference/classes/langgraph.CompiledStateGraph.html#updateState",
-}
-
-# TODO: Allow updating these to localhost for local development
-PY_REFERENCE_HOST = "https://langchain-ai.github.io/langgraph/"
-JS_REFERENCE_HOST = "https://langchain-ai.github.io/langgraphjs/"
-
-for key, value in PYTHON_LINK_MAP.items():
-    # Ensure the link is absolute
-    if not value.startswith("http"):
-        PYTHON_LINK_MAP[key] = f"{PY_REFERENCE_HOST}{value}"
-
-for key, value in JS_LINK_MAP.items():
-    # Ensure the link is absolute
-    if not value.startswith("http"):
-        JS_LINK_MAP[key] = f"{JS_REFERENCE_HOST}{value}"
-
-# Global scope is assembled from the Python and JS mappings
-# Combined mapping by scope
-SCOPE_LINK_MAPS = {
-    "python": PYTHON_LINK_MAP,
-    "js": JS_LINK_MAP,
-}

docs/_scripts/notebook_convert.py

@@ -1,384 +0,0 @@
-"""Convert Jupyter notebooks to markdown with custom processing."""
-
-import ast
-import os
-import re
-from typing import Literal
-
-import nbformat
-from nbconvert.exporters import MarkdownExporter
-from nbconvert.preprocessors import Preprocessor
-
-
-def _uses_input(source: str) -> bool:
-    """Parse the source code to determine if it uses the input() function."""
-    try:
-        tree = ast.parse(source)
-    except SyntaxError:
-        # If there's a syntax error, assume input() might be present to be safe.
-        return False
-
-    for node in ast.walk(tree):
-        if isinstance(node, ast.Call):
-            # Check if the function called is named 'input'
-            if isinstance(node.func, ast.Name) and node.func.id == "input":
-                return True
-    return False
-
-
-def _rewrite_cell_magic(code: str) -> str:
-    """Process a code block that uses cell magic.
-
-    - Lines starting with "%%capture" are ignored.
-    - Lines starting with "%pip" are rewritten by removing the leading "%" character.
-    - Any other non-empty line causes a NotImplementedError.
-
-    Args:
-        code (str): The original code block.
-
-    Returns:
-        str: The transformed code block.
-
-    Raises:
-        NotImplementedError: If a line doesn't start with either "%%capture" or "%pip".
-    """
-    rewritten_lines = []
-
-    for line in code.splitlines():
-        stripped = line.strip()
-        # Skip empty lines
-        if not stripped:
-            continue
-        # Ignore %%capture lines
-        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}")
-        else:
-            raise NotImplementedError(f"Unhandled line: {line}")
-
-    return "\n".join(rewritten_lines)
-
-
-class PrintCallVisitor(ast.NodeVisitor):
-    """
-    This visitor sets self.has_print to True if it encounters a call
-    to a print within the global scope.
-
-    This should catch calls to print(), print_stream(), etc. (Prefixed with "print").
-
-    May have some false positives, but it's not meant to be perfect.
-
-    Temporary code for notebook conversion.
-    """
-
-    def __init__(self):
-        self.has_print = False
-        self.scope_level = 0  # counter to track whether we're inside a def/lambda
-
-    def visit_FunctionDef(self, node):
-        self.scope_level += 1
-        self.generic_visit(node)
-        self.scope_level -= 1
-
-    def visit_AsyncFunctionDef(self, node):
-        self.scope_level += 1
-        self.generic_visit(node)
-        self.scope_level -= 1
-
-    def visit_Lambda(self, node):
-        self.scope_level += 1
-        self.generic_visit(node)
-        self.scope_level -= 1
-
-    def visit_ClassDef(self, node):
-        self.scope_level += 1
-        self.generic_visit(node)
-        self.scope_level -= 1
-
-    def visit_Call(self, node):
-        # Only consider calls when not inside a function definition.
-        if self.scope_level == 0:
-            if isinstance(node.func, ast.Name) and node.func.id.startswith("print"):
-                self.has_print = True
-        self.generic_visit(node)
-
-
-def _has_output(source: str) -> bool:
-    """Determine if the code block is expected to produce output.
-
-    Args:
-        source (str): The source code of the code block.
-
-    Returns:
-        True if the code block is expected to produce output, False otherwise.
-
-        Must meet the following conditions:
-
-        1. There is a call to a printing function (name starts with "print")
-           that is not inside a function definition.
-        2. The last top-level statement is an expression that is valid if:
-         - It is any expression (including calls) AND
-         - It is NOT a call to `display(...)`.
-
-        `display` isn't handled currently by markdown-exec
-    """
-    try:
-        tree = ast.parse(source)
-    except SyntaxError:
-        return False
-
-    # Condition (1): Check for a global print-like call.
-    visitor = PrintCallVisitor()
-    visitor.visit(tree)
-    condition_a = visitor.has_print
-
-    # Condition (2): Check the last top-level statement.
-    condition_b = False
-    if tree.body:
-        last_stmt = tree.body[-1]
-        if isinstance(last_stmt, ast.Expr):
-            # If the expression is a call, ensure it's not a call to "display"
-            if isinstance(last_stmt.value, ast.Call):
-                if (
-                    isinstance(last_stmt.value.func, ast.Name)
-                    and last_stmt.value.func.id == "display"
-                ):
-                    condition_b = False  # exclude display-wrapped expressions
-                else:
-                    condition_b = True
-            else:
-                # Any other expression qualifies.
-                condition_b = True
-
-    return condition_a or condition_b
-
-
-def _convert_links_in_markdown(markdown: str) -> str:
-    """Convert links present in notebook markdown cells to standardized format.
-
-    We want to update markdown links code cells by linking to markdown
-    files rather than assuming that the link is to the finalized HTML.
-
-    This code is needed temporarily since the markdown links that are present
-    in ipython notebooks do not follow the same conventions as regular markdown
-    files in mkdocs (which should link to a .md file).
-    """
-
-    # Define the regex pattern in parts for clarity:
-    pattern = (
-        r"(?<!!)"  # Negative lookbehind: ensure the link is not an image (i.e., doesn't start with "!")
-        r"\["  # Literal '[' indicating the start of the link text.
-        r"(?P<text>[^\]]*)"  # Named group 'text': match any characters except ']', representing the link text.
-        r"\]"  # Literal ']' indicating the end of the link text.
-        r"\("  # Literal '(' indicating the start of the URL.
-        r"(?![^\)]*//)"  # Negative lookahead: ensure that the URL does not contain '//' (skip absolute URLs).
-        r"(?P<url>[^)]*)"  # Named group 'url': match any characters except ')', representing the URL.
-        r"\)"  # Literal ')' indicating the end of the URL.
-    )
-
-    def custom_replacement(match):
-        """logic will correct the link format used in ipython notebooks
-
-        Ipython notebooks were being converted directly into HTML links
-        instead of markdown links that retain the markdown extension.
-
-        It needs to handle the following cases:
-        - optional fragments (e.g., `#section`)
-            e.g., `[text](url/#section)` -> `[text](url.md#section)`
-            e.g., `[text](url#section)` -> `[text](url.md#section)`
-        - relative paths (e.g., `../path/to/file`) need to be denested by 1 level
-        """
-        text = match.group("text")
-        url = match.group("url")
-
-        if url.startswith("../"):
-            # we strip the "../" from the start of the URL
-            # We only need to denest one level.
-            url = url[3:]
-
-        url = url.rstrip("/")  # Strip `/` from the end of the URL
-
-        # if url has a fragment
-        if "#" in url:
-            url, fragment = url.split("#")
-            url = url.rstrip("/")
-            # Strip `/` from the end of the URL
-            return f"[{text}]({url}.md#{fragment})"
-        # Otherwise add the .md extension
-        return f"[{text}]({url}.md)"
-
-    return re.sub(
-        pattern,
-        custom_replacement,
-        markdown,
-    )
-
-
-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)
-        self.markdown_exec_migration = markdown_exec_migration
-
-    def preprocess_cell(self, cell, resources, cell_index):
-        if cell.cell_type == "markdown":
-            if not self.markdown_exec_migration:
-                # Old logic is to convert ipynb links to HTML links
-                cell.source = re.sub(
-                    r"(?<!!)\[([^\]]*)\]\((?![^\)]*//)([^)]*)(?:\.ipynb)?\)",
-                    r'<a href="\2">\1</a>',
-                    cell.source,
-                )
-            else:
-                cell.source = _convert_links_in_markdown(cell.source)
-
-            # Fix image paths in <img> tags
-            cell.source = re.sub(
-                r'<img\s+src="\.?/img/([^"]+)"', r'<img src="../img/\1"', cell.source
-            )
-
-        elif cell.cell_type == "code":
-            # Determine if the cell has bash or cell magic
-            source = cell.source
-            is_exec = not (
-                source.startswith("%") or source.startswith("!") or _uses_input(source)
-            )
-            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"
-
-            # Remove noqa comments
-            cell.source = re.sub(r"#\s*noqa.*$", "", cell.source, flags=re.MULTILINE)
-            # escape ``` in code
-            # This is needed because the markdown exporter will wrap code blocks in
-            # triple backticks, which will break the markdown output if the code block
-            # contains triple backticks.
-            cell.source = cell.source.replace("```", r"\`\`\`")
-            # escape ``` in output
-            if "outputs" in cell:
-                filter_out = set()
-                for i, output in enumerate(cell["outputs"]):
-                    if "text" in output:
-                        if not output["text"].strip():
-                            filter_out.add(i)
-                            continue
-
-                        value = output["text"].replace("```", r"\`\`\`")
-                        # handle a funky case w/ references in text
-                        value = re.sub(r"\[(\d+)\](?=\[(\d+)\])", r"[\1]\\", value)
-                        output["text"] = value
-                    elif "data" in output:
-                        for key, value in output["data"].items():
-                            if isinstance(value, str):
-                                value = value.replace("```", r"\`\`\`")
-                                # handle a funky case w/ references in text
-                                output["data"][key] = re.sub(
-                                    r"\[(\d+)\](?=\[(\d+)\])", r"[\1]\\", value
-                                )
-                cell["outputs"] = [
-                    output
-                    for i, output in enumerate(cell["outputs"])
-                    if i not in filter_out
-                ]
-
-        return cell, resources
-
-
-class ExtractAttachmentsPreprocessor(Preprocessor):
-    """
-    Extracts all of the outputs from the notebook file.  The extracted
-    outputs are returned in the 'resources' dictionary.
-    """
-
-    def preprocess_cell(self, cell, resources, cell_index):
-        """
-        Apply a transformation on each cell,
-        Parameters
-        ----------
-        cell : NotebookNode cell
-            Notebook cell being processed
-        resources : dictionary
-            Additional resources used in the conversion process.  Allows
-            preprocessors to pass variables into the Jinja engine.
-        cell_index : int
-            Index of the cell being processed (see base.py)
-        """
-
-        # Get files directory if it has been specified
-
-        # Make sure outputs key exists
-        if not isinstance(resources["outputs"], dict):
-            resources["outputs"] = {}
-
-        # Loop through all of the attachments in the cell
-        for name, attach in cell.get("attachments", {}).items():
-            for mime, data in attach.items():
-                if mime not in {
-                    "image/png",
-                    "image/jpeg",
-                    "image/svg+xml",
-                    "application/pdf",
-                }:
-                    continue
-
-                # attachments are pre-rendered. Only replace markdown-formatted
-                # images with the following logic
-                attach_str = f"({name})"
-                if attach_str in cell.source:
-                    data = f"(data:{mime};base64,{data})"
-                    cell.source = cell.source.replace(attach_str, data)
-
-        return cell, resources
-
-
-exporter = MarkdownExporter(
-    preprocessors=[
-        HideCellTagPreprocessor,
-        EscapePreprocessor,
-        ExtractAttachmentsPreprocessor,
-    ],
-    template_name="mdoutput",
-    extra_template_basedirs=[
-        os.path.join(os.path.dirname(__file__), "notebook_convert_templates")
-    ],
-)
-
-
-def convert_notebook(
-    notebook_path: str,
-    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)
-    return body

docs/_scripts/notebook_convert_templates/mdoutput/conf.json

@@ -1,5 +0,0 @@
-{
-  "mimetypes": {
-    "text/markdown": true
-  }
-}

docs/_scripts/notebook_convert_templates/mdoutput/index.md.j2

@@ -1,50 +0,0 @@
-{% 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 }}
-```
-{%- endblock traceback_line -%}
-
-{%- block stream -%}
-```output
-{{ output.text.rstrip() | strip_ansi }}
-```
-{%- endblock stream -%}
-
-{%- block data_text scoped -%}
-```output
-{{ output.data['text/plain'].rstrip() | strip_ansi }}
-```
-{%- endblock data_text -%}
-
-{%- block data_html scoped -%}
-```html
-{{ output.data['text/html'] | safe }} 
-```
-{%- endblock data_html -%}
-
-{%- block data_jpg scoped -%}
-<p>
-<img src="data:image/jpg;base64,{{ output.data['image/jpeg'] }}" />
-</p>
-{%- endblock data_jpg -%}
-
-{%- block data_png scoped -%}
-<p>
-<img src="data:image/png;base64,{{ output.data['image/png'] }}" />
-</p>
-{%- endblock data_png -%}

docs/_scripts/notebook_hooks.py

@@ -1,611 +0,0 @@
-"""mkdocs hooks for adding custom logic to documentation pipeline.
-
-Lifecycle events: https://www.mkdocs.org/dev-guide/plugins/#events
-"""
-
-import json
-import logging
-import os
-import posixpath
-import re
-from typing import Any, Dict
-
-from bs4 import BeautifulSoup
-from mkdocs.config.defaults import MkDocsConfig
-from mkdocs.structure.files import Files, File
-from mkdocs.structure.pages import Page
-
-from _scripts.generate_api_reference_links import update_markdown_with_imports
-from _scripts.handle_auto_links import _replace_autolinks
-from _scripts.notebook_convert import convert_notebook
-
-logger = logging.getLogger(__name__)
-logging.basicConfig()
-logger.setLevel(logging.INFO)
-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/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.md#define-and-update-state",
-    "how-tos/sequence.ipynb": "how-tos/graph-api.md#create-a-sequence-of-steps",
-    "how-tos/branching.ipynb": "how-tos/graph-api.md#create-branches",
-    "how-tos/recursion-limit.ipynb": "how-tos/graph-api.md#create-and-control-loops",
-    "how-tos/visualization.ipynb": "how-tos/graph-api.md#visualize-your-graph",
-    "how-tos/input_output_schema.ipynb": "how-tos/graph-api.md#define-input-and-output-schemas",
-    "how-tos/pass_private_state.ipynb": "how-tos/graph-api.md#pass-private-state-between-nodes",
-    "how-tos/state-model.ipynb": "how-tos/graph-api.md#use-pydantic-models-for-graph-state",
-    "how-tos/map-reduce.ipynb": "how-tos/graph-api.md#map-reduce-and-the-send-api",
-    "how-tos/command.ipynb": "how-tos/graph-api.md#combine-control-flow-and-state-updates-with-command",
-    "how-tos/configuration.ipynb": "how-tos/graph-api.md#add-runtime-configuration",
-    "how-tos/node-retries.ipynb": "how-tos/graph-api.md#add-retry-policies",
-    "how-tos/return-when-recursion-limit-hits.ipynb": "how-tos/graph-api.md#impose-a-recursion-limit",
-    "how-tos/async.ipynb": "how-tos/graph-api.md#async",
-    # memory how-tos
-    "how-tos/memory/manage-conversation-history.ipynb": "how-tos/memory/add-memory.md",
-    "how-tos/memory/delete-messages.ipynb": "how-tos/memory/add-memory.md#delete-messages",
-    "how-tos/memory/add-summary-conversation-history.ipynb": "how-tos/memory/add-memory.md#summarize-messages",
-    "how-tos/memory.ipynb": "how-tos/memory/add-memory.md",
-    "agents/memory.ipynb": "how-tos/memory/add-memory.md",
-    # subgraph how-tos
-    "how-tos/subgraph-transform-state.ipynb": "how-tos/subgraph.md#different-state-schemas",
-    "how-tos/subgraphs-manage-state.ipynb": "how-tos/subgraph.md#add-persistence",
-    # persistence how-tos
-    "how-tos/persistence_postgres.ipynb": "how-tos/memory/add-memory.md#use-in-production",
-    "how-tos/persistence_mongodb.ipynb": "how-tos/memory/add-memory.md#use-in-production",
-    "how-tos/persistence_redis.ipynb": "how-tos/memory/add-memory.md#use-in-production",
-    "how-tos/subgraph-persistence.ipynb": "how-tos/memory/add-memory.md#use-with-subgraphs",
-    "how-tos/cross-thread-persistence.ipynb": "how-tos/memory/add-memory.md#add-long-term-memory",
-    "cloud/how-tos/copy_threads": "cloud/how-tos/use_threads",
-    "cloud/how-tos/check-thread-status": "cloud/how-tos/use_threads",
-    "cloud/concepts/threads.md": "concepts/persistence.md#threads",
-    "how-tos/persistence.ipynb": "how-tos/memory/add-memory.md",
-    # 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",
-    "agents/tools.md": "how-tos/tool-calling.md",
-    # multi-agent how-tos
-    "how-tos/agent-handoffs.ipynb": "how-tos/multi_agent.md#handoffs",
-    "how-tos/multi-agent-network.ipynb": "how-tos/multi_agent.md#use-in-a-multi-agent-system",
-    "how-tos/multi-agent-multi-turn-convo.ipynb": "how-tos/multi_agent.md#multi-turn-conversation",
-    # cloud redirects
-    "cloud/index.md": "index.md",
-    "cloud/how-tos/index.md": "concepts/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": "https://docs.langchain.com/langgraph-platform/streaming",
-    "cloud/how-tos/stream_updates.md": "https://docs.langchain.com/langgraph-platform/streaming",
-    "cloud/how-tos/stream_messages.md": "https://docs.langchain.com/langgraph-platform/streaming",
-    "cloud/how-tos/stream_events.md": "https://docs.langchain.com/langgraph-platform/streaming",
-    "cloud/how-tos/stream_debug.md": "https://docs.langchain.com/langgraph-platform/streaming",
-    "cloud/how-tos/stream_multiple.md": "https://docs.langchain.com/langgraph-platform/streaming",
-    "cloud/concepts/streaming.md": "concepts/streaming.md",
-    "agents/streaming.md": "how-tos/streaming.md",
-    # prebuilt 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-structured-output.ipynb": "agents/agents.md#structured-output",
-    # 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",
-    "agents/deployment.md": "tutorials/langgraph-platform/local-server.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",
-    "tutorials/deployment.md": "concepts/deployment_options.md",
-    # assistant redirects
-    "cloud/how-tos/assistant_versioning.md": "cloud/how-tos/configuration_cloud.md",
-    "cloud/concepts/runs.md": "concepts/assistants.md#execution",
-    # hitl redirects
-    "how-tos/wait-user-input-functional.ipynb": "how-tos/use-functional-api.md",
-    "how-tos/review-tool-calls-functional.ipynb": "how-tos/use-functional-api.md",
-    "how-tos/create-react-agent-hitl.ipynb": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
-    "agents/human-in-the-loop.md": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
-    "how-tos/human_in_the_loop/dynamic_breakpoints.ipynb": "how-tos/human_in_the_loop/breakpoints.md",
-    "concepts/breakpoints.md": "concepts/human_in_the_loop.md",
-    "how-tos/human_in_the_loop/breakpoints.md": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
-    "cloud/how-tos/human_in_the_loop_breakpoint.md": "cloud/how-tos/add-human-in-the-loop.md",
-    "how-tos/human_in_the_loop/edit-graph-state.ipynb": "how-tos/human_in_the_loop/time-travel.md",
-
-    # LGP mintlify migration redirects
-    "tutorials/auth/getting_started.md": "https://docs.langchain.com/langgraph-platform/auth",
-    "tutorials/auth/resource_auth.md": "https://docs.langchain.com/langgraph-platform/resource-auth",
-    "tutorials/auth/add_auth_server.md": "https://docs.langchain.com/langgraph-platform/add-auth-server",
-    "how-tos/use-remote-graph.md": "https://docs.langchain.com/langgraph-platform/use-remote-graph",
-    "how-tos/autogen-integration.md": "https://docs.langchain.com/langgraph-platform/autogen-integration",
-    "cloud/how-tos/use_stream_react.md": "https://docs.langchain.com/langgraph-platform/use-stream-react",
-    "cloud/how-tos/generative_ui_react.md": "https://docs.langchain.com/langgraph-platform/generative-ui-react",
-    "concepts/langgraph_platform.md": "https://docs.langchain.com/langgraph-platform/index",
-    "concepts/langgraph_components.md": "https://docs.langchain.com/langgraph-platform/components",
-    "concepts/langgraph_server.md": "https://docs.langchain.com/langgraph-platform/langgraph-server",
-    "concepts/langgraph_data_plane.md": "https://docs.langchain.com/langgraph-platform/data-plane",
-    "concepts/langgraph_control_plane.md": "https://docs.langchain.com/langgraph-platform/control-plane",
-    "concepts/langgraph_cli.md": "https://docs.langchain.com/langgraph-platform/langgraph-cli",
-    "concepts/langgraph_studio.md": "https://docs.langchain.com/langgraph-platform/langgraph-studio",
-    "cloud/how-tos/studio/quick_start.md": "https://docs.langchain.com/langgraph-platform/quick-start-studio",
-    "cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langgraph-platform/use-studio#run-application",
-    "cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langgraph-platform/use-studio#manage-assistants",
-    "cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langgraph-platform/use-studio#manage-threads",
-    "cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langgraph-platform/observability-studio#iterate-on-prompts",
-    "cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langgraph-platform/observability-studio#run-experiments-over-a-dataset",
-    "cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langgraph-platform/observability-studio#debug-langsmith-traces",
-    "cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langgraph-platform/observability-studio#add-node-to-dataset",
-    "concepts/sdk.md": "https://docs.langchain.com/langgraph-platform/sdk",
-    "concepts/plans.md": "https://docs.langchain.com/langgraph-platform/plans",
-    "concepts/application_structure.md": "https://docs.langchain.com/langgraph-platform/application-structure",
-    "concepts/scalability_and_resilience.md": "https://docs.langchain.com/langgraph-platform/scalability-and-resilience",
-    "concepts/auth.md": "https://docs.langchain.com/langgraph-platform/auth",
-    "how-tos/auth/custom_auth.md": "https://docs.langchain.com/langgraph-platform/custom-auth",
-    "how-tos/auth/openapi_security.md": "https://docs.langchain.com/langgraph-platform/openapi-security",
-    "concepts/assistants.md": "https://docs.langchain.com/langgraph-platform/assistants",
-    "cloud/how-tos/configuration_cloud.md": "https://docs.langchain.com/langgraph-platform/configuration-cloud",
-    "cloud/how-tos/use_threads.md": "https://docs.langchain.com/langgraph-platform/use-threads",
-    "cloud/how-tos/background_run.md": "https://docs.langchain.com/langgraph-platform/background-run",
-    "cloud/how-tos/same-thread.md": "https://docs.langchain.com/langgraph-platform/same-thread",
-    "cloud/how-tos/stateless_runs.md": "https://docs.langchain.com/langgraph-platform/stateless-runs",
-    "cloud/how-tos/configurable_headers.md": "https://docs.langchain.com/langgraph-platform/configurable-headers",
-    "concepts/double_texting.md": "https://docs.langchain.com/langgraph-platform/double-texting",
-    "cloud/how-tos/interrupt_concurrent.md": "https://docs.langchain.com/langgraph-platform/interrupt-concurrent",
-    "cloud/how-tos/rollback_concurrent.md": "https://docs.langchain.com/langgraph-platform/rollback-concurrent",
-    "cloud/how-tos/reject_concurrent.md": "https://docs.langchain.com/langgraph-platform/reject-concurrent",
-    "cloud/how-tos/enqueue_concurrent.md": "https://docs.langchain.com/langgraph-platform/enqueue-concurrent",
-    "cloud/concepts/webhooks.md": "https://docs.langchain.com/langgraph-platform/use-webhooks",
-    "cloud/how-tos/webhooks.md": "https://docs.langchain.com/langgraph-platform/use-webhooks",
-    "cloud/concepts/cron_jobs.md": "https://docs.langchain.com/langgraph-platform/cron-jobs",
-    "cloud/how-tos/cron_jobs.md": "https://docs.langchain.com/langgraph-platform/cron-jobs",
-    "how-tos/http/custom_lifespan.md": "https://docs.langchain.com/langgraph-platform/custom-lifespan",
-    "how-tos/http/custom_middleware.md": "https://docs.langchain.com/langgraph-platform/custom-middleware",
-    "how-tos/http/custom_routes.md": "https://docs.langchain.com/langgraph-platform/custom-routes",
-    "cloud/concepts/data_storage_and_privacy.md": "https://docs.langchain.com/langgraph-platform/data-storage-and-privacy",
-    "cloud/deployment/semantic_search.md": "https://docs.langchain.com/langgraph-platform/semantic-search",
-    "how-tos/ttl/configure_ttl.md": "https://docs.langchain.com/langgraph-platform/configure-ttl",
-    "concepts/deployment_options.md": "https://docs.langchain.com/langgraph-platform/deployment-options",
-    "cloud/quick_start.md": "https://docs.langchain.com/langgraph-platform/deployment-quickstart",
-    "cloud/deployment/setup.md": "https://docs.langchain.com/langgraph-platform/setup-app-requirements-txt",
-    "cloud/deployment/setup_pyproject.md": "https://docs.langchain.com/langgraph-platform/setup-pyproject",
-    "cloud/deployment/setup_javascript.md": "https://docs.langchain.com/langgraph-platform/setup-javascript",
-    "cloud/deployment/custom_docker.md": "https://docs.langchain.com/langgraph-platform/custom-docker",
-    "cloud/deployment/graph_rebuild.md": "https://docs.langchain.com/langgraph-platform/graph-rebuild",
-    "concepts/langgraph_cloud.md": "https://docs.langchain.com/langgraph-platform/cloud",
-    "concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/hybrid",
-    "concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/self-hosted",
-    "concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langgraph-platform/self-hosted#standalone-server",
-    "cloud/deployment/cloud.md": "https://docs.langchain.com/langgraph-platform/cloud",
-    "cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-hybrid",
-    "cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-self-hosted-full-platform",
-    "cloud/deployment/standalone_container.md": "https://docs.langchain.com/langgraph-platform/deploy-standalone-server",
-    "concepts/server-mcp.md": "https://docs.langchain.com/langgraph-platform/server-mcp",
-    "cloud/how-tos/human_in_the_loop_time_travel.md": "https://docs.langchain.com/langgraph-platform/human-in-the-loop-time-travel",
-    "cloud/how-tos/add-human-in-the-loop.md": "https://docs.langchain.com/langgraph-platform/add-human-in-the-loop",
-    "cloud/deployment/egress.md": "https://docs.langchain.com/langgraph-platform/env-var",
-    "cloud/how-tos/streaming.md": "https://docs.langchain.com/langgraph-platform/streaming",
-    "cloud/reference/api/api_ref.md": "https://docs.langchain.com/langgraph-platform/server-api-ref",
-    "cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langgraph-platform/langgraph-server-changelog",
-    "cloud/reference/api/api_ref_control_plane.md": "https://docs.langchain.com/langgraph-platform/api-ref-control-plane",
-    "cloud/reference/cli.md": "https://docs.langchain.com/langgraph-platform/cli",
-    "cloud/reference/env_var.md": "https://docs.langchain.com/langgraph-platform/env-var",
-    "troubleshooting/studio.md": "https://docs.langchain.com/langgraph-platform/troubleshooting-studio",
-}
-
-
-class NotebookFile(File):
-    def is_documentation_page(self):
-        return True
-
-
-def on_files(files: Files, **kwargs: Dict[str, Any]):
-    if DISABLED:
-        return files
-    new_files = Files([])
-    for file in files:
-        if file.src_path.endswith(".ipynb"):
-            new_file = NotebookFile(
-                path=file.src_path,
-                src_dir=file.src_dir,
-                dest_dir=file.dest_dir,
-                use_directory_urls=file.use_directory_urls,
-            )
-            new_files.append(new_file)
-        else:
-            new_files.append(file)
-    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)
-
-
-# Compiled regex patterns for better performance and readability
-
-
-def _apply_conditional_rendering(md_text: str, target_language: str) -> str:
-    if target_language not in {"python", "js"}:
-        raise ValueError("target_language must be 'python' or 'js'")
-
-    pattern = re.compile(
-        r"(?P<indent>[ \t]*):::(?P<language>\w+)\s*\n"
-        r"(?P<content>((?:.*\n)*?))"  # Capture the content inside the block
-        r"(?P=indent)[ \t]*:::"  # Match closing with the same indentation + any additional whitespace
-    )
-
-    def replace_conditional_blocks(match: re.Match) -> str:
-        """Keep active conditionals."""
-        language = match.group("language")
-        content = match.group("content")
-
-        if language not in {"python", "js"}:
-            # If the language is not supported, return the original block
-            return match.group(0)
-
-        if language == target_language:
-            return content
-
-        # If the language does not match, return an empty string
-        return ""
-
-    processed = pattern.sub(replace_conditional_blocks, md_text)
-    return processed
-
-
-def _highlight_code_blocks(markdown: str) -> str:
-    """Find code blocks with highlight comments and add hl_lines attribute.
-
-    Args:
-        markdown: The markdown content to process.
-
-    Returns:
-        updated Markdown code with code blocks containing highlight comments
-        updated to use the hl_lines attribute.
-    """
-    # Pattern to find code blocks with highlight comments and without
-    # existing hl_lines for Python and JavaScript
-    # Pattern to find code blocks with highlight comments, handling optional indentation
-    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_highlight_comments(match: re.Match) -> str:
-        indent = match.group("indent")
-        language = match.group("language")
-        code_block = match.group("code")
-        attributes = match.group("attributes").rstrip()
-
-        # Account for a case where hl_lines is manually specified
-        if "hl_lines" in attributes:
-            # Return original code block
-            return match.group(0)
-
-        lines = code_block.split("\n")
-        highlighted_lines = []
-
-        # Skip initial empty lines
-        while lines and not lines[0].strip():
-            lines.pop(0)
-
-        lines_to_keep = []
-
-        comment_syntax = (
-            "# highlight-next-line"
-            if language in ["py", "python"]
-            else "// highlight-next-line"
-        )
-
-        for line in lines:
-            if comment_syntax in line:
-                count = len(lines_to_keep) + 1
-                highlighted_lines.append(str(count))
-            else:
-                lines_to_keep.append(line)
-
-        # Reconstruct the new code block
-        new_code_block = "\n".join(lines_to_keep)
-
-        # Construct the full code block that also includes
-        # the fenced code block syntax.
-        opening_fence = f"```{language}"
-
-        if attributes:
-            opening_fence += f" {attributes}"
-
-        if highlighted_lines:
-            opening_fence += f' hl_lines="{" ".join(highlighted_lines)}"'
-
-        return (
-            # The indent and opening fence
-            f"{indent}{opening_fence}\n"
-            # The indent and terminating \n is already included in the code block
-            f"{new_code_block}"
-            f"{indent}```"
-        )
-
-    # Replace all code blocks in the markdown
-    markdown = code_block_pattern.sub(replace_highlight_comments, markdown)
-    return markdown
-
-
-def _save_page_output(markdown: str, output_path: str):
-    """Save markdown content to a file, creating parent directories if needed.
-
-    Args:
-        markdown: The markdown content to save
-        output_path: The file path to save to
-    """
-    # Create parent directories recursively if they don't exist
-    os.makedirs(os.path.dirname(output_path), exist_ok=True)
-    
-    # Write the markdown content to the file
-    with open(output_path, "w", encoding="utf-8") as f:
-        f.write(markdown)
-
-
-def _on_page_markdown_with_config(
-    markdown: str,
-    page: Page,
-    *,
-    add_api_references: bool = True,
-    remove_base64_images: bool = False,
-    **kwargs: Any,
-) -> str:
-    if DISABLED:
-        return markdown
-
-    if page.file.src_path.endswith(".ipynb"):
-        # logger.info("Processing Jupyter notebook: %s", page.file.src_path)
-        markdown = convert_notebook(page.file.abs_src_path)
-
-    target_language = kwargs.get(
-        "target_language",
-        os.environ.get("TARGET_LANGUAGE", "python")
-    )
-
-    # Apply cross-reference preprocessing to all markdown content
-    markdown = _replace_autolinks(markdown, page.file.src_path, default_scope=target_language)
-
-    # Append API reference links to code blocks
-    if add_api_references:
-        markdown = update_markdown_with_imports(markdown, page.file.abs_src_path)
-    # Apply highlight comments to code blocks
-    markdown = _highlight_code_blocks(markdown)
-
-    # Apply conditional rendering for code blocks
-    markdown = _apply_conditional_rendering(markdown, target_language)
-
-    # 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)
-
-    return markdown
-
-
-def on_page_markdown(markdown: str, page: Page, **kwargs: Dict[str, Any]):
-    finalized_markdown = _on_page_markdown_with_config(
-        markdown,
-        page,
-        add_api_references=True,
-        **kwargs,
-    )
-    page.meta["original_markdown"] = finalized_markdown
-
-    output_path = os.environ.get("MD_OUTPUT_PATH")
-    if output_path:
-        file_path = os.path.join(output_path, page.file.src_path)
-        _save_page_output(finalized_markdown, file_path)
-
-    return finalized_markdown
-
-
-# redirects
-
-HTML_TEMPLATE = """
-<!doctype html>
-<html lang="en">
-<head>
-    <meta charset="utf-8">
-    <title>Redirecting...</title>
-    <link rel="canonical" href="{url}">
-    <meta name="robots" content="noindex">
-    <script>var anchor=window.location.hash.substr(1);location.href="{url}"+(anchor?"#"+anchor:"")</script>
-    <meta http-equiv="refresh" content="0; url={url}">
-</head>
-<body>
-Redirecting...
-</body>
-</html>
-"""
-
-
-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)
-    old_dir_abs = os.path.dirname(old_path_abs)
-
-    # Create parent directories if they don't exist
-    if not os.path.exists(old_dir_abs):
-        os.makedirs(old_dir_abs)
-
-    # Write the HTML redirect file in place of the old file
-    content = HTML_TEMPLATE.format(url=new_path)
-    with open(old_path_abs, "w", encoding="utf-8") as f:
-        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 _inject_markdown_into_html(html: str, page: Page) -> str:
-    """Inject the original markdown content into the HTML page as JSON."""
-    original_markdown = page.meta.get("original_markdown", "")
-    if not original_markdown:
-        return html
-    markdown_data = {
-        "markdown": original_markdown,
-        "title": page.title or "Page Content",
-        "url": page.url or "",
-    }
-
-    # Properly escape the JSON for HTML
-    json_content = json.dumps(markdown_data, ensure_ascii=False)
-
-    json_content = (
-        json_content.replace("</", "\\u003c/")
-        .replace("<script", "\\u003cscript")
-        .replace("</script", "\\u003c/script")
-    )
-
-    script_content = (
-        f'<script id="page-markdown-content" '
-        f'type="application/json">{json_content}</script>'
-    )
-
-    # Insert before </head> if it exists, otherwise before </body>
-    if "</head>" not in html:
-        raise ValueError(
-            "HTML does not contain </head> tag. Cannot inject markdown content."
-        )
-    return html.replace("</head>", f"{script_content}</head>")
-
-
-def on_post_page(html: str, page: Page, config: MkDocsConfig) -> str:
-    """Inject Google Tag Manager noscript tag immediately after <body>.
-
-    Args:
-        html: The HTML output of the page.
-        page: The page instance.
-        config: The MkDocs configuration object.
-
-    Returns:
-        modified HTML output with GTM code injected.
-    """
-    html = _inject_markdown_into_html(html, page)
-    return _inject_gtm(html)
-
-
-# Create HTML files for redirects after site dir has been built
-def on_post_build(config):
-    use_directory_urls = config.get("use_directory_urls")
-    for page_old, page_new in REDIRECT_MAP.items():
-        # Convert .ipynb to .md for path calculation
-        page_old = page_old.replace(".ipynb", ".md")
-        
-        # Calculate the HTML path for the old page (whether it exists or not)
-        if use_directory_urls:
-            # With directory URLs: /path/to/page/ becomes /path/to/page/index.html
-            if page_old.endswith(".md"):
-                old_html_path = page_old[:-3] + "/index.html"
-            else:
-                old_html_path = page_old + "/index.html"
-        else:
-            # Without directory URLs: /path/to/page.md becomes /path/to/page.html
-            if page_old.endswith(".md"):
-                old_html_path = page_old[:-3] + ".html"
-            else:
-                old_html_path = page_old + ".html"
-        
-        if isinstance(page_new, str) and page_new.startswith("http"):
-            # Handle external redirects
-            _write_html(config["site_dir"], old_html_path, page_new)
-        else:
-            # Handle internal redirects
-            page_new = page_new.replace(".ipynb", ".md")
-            page_new_before_hash, hash, suffix = page_new.partition("#")
-            
-            # Try to get the new path using File class, but fallback to manual calculation
-            try:
-                new_html_path = File(page_new_before_hash, "", "", True).url
-                new_html_path = (
-                    posixpath.relpath(new_html_path, start=posixpath.dirname(old_html_path))
-                    + hash
-                    + suffix
-                )
-            except:
-                # Fallback: calculate relative path manually
-                if use_directory_urls:
-                    if page_new_before_hash.endswith(".md"):
-                        new_html_path = page_new_before_hash[:-3] + "/"
-                    else:
-                        new_html_path = page_new_before_hash + "/"
-                else:
-                    if page_new_before_hash.endswith(".md"):
-                        new_html_path = page_new_before_hash[:-3] + ".html"
-                    else:
-                        new_html_path = page_new_before_hash + ".html"
-                new_html_path += hash + suffix
-            
-            _write_html(config["site_dir"], old_html_path, new_html_path)

docs/_scripts/prepare_notebooks_for_ci.py

@@ -1,263 +0,0 @@
-"""Preprocess notebooks for CI. Currently adds VCR cassettes and optionally removes pip install cells."""
-
-import logging
-import os
-import json
-import click
-import nbformat
-import re
-
-logger = logging.getLogger(__name__)
-NOTEBOOK_DIRS = ("docs/how-tos","docs/tutorials")
-DOCS_PATH = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-CASSETTES_PATH = os.path.join(DOCS_PATH, "cassettes")
-
-BLOCKLIST_COMMANDS = (
-    # skip if has WebBaseLoader to avoid caching web pages
-    "WebBaseLoader",
-    # skip if has draw_mermaid_png to avoid generating mermaid images via API
-    "draw_mermaid_png",
-)
-
-NOTEBOOKS_NO_CASSETTES = (
-    "docs/how-tos/visualization.ipynb",
-)
-
-NOTEBOOKS_NO_EXECUTION = [
-    # this uses a user provided project name for langsmith
-    "docs/tutorials/tnt-llm/tnt-llm.ipynb",
-    # this uses langsmith datasets
-    "docs/tutorials/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb",
-    # this uses browser APIs
-    "docs/tutorials/web-navigation/web_voyager.ipynb",
-    # these RAG guides use an ollama model
-    "docs/tutorials/rag/langgraph_adaptive_rag_local.ipynb",
-    "docs/tutorials/rag/langgraph_crag_local.ipynb",
-    "docs/tutorials/rag/langgraph_self_rag_local.ipynb",
-    # this loads a massive dataset from gcp
-    "docs/tutorials/usaco/usaco.ipynb",
-    # TODO: figure out why autogen notebook is not runnable (they are just hanging. possible due to code execution?)
-    "docs/how-tos/autogen-integration.ipynb",
-    "docs/how-tos/autogen-integration-functional.ipynb",
-    # TODO: need to update these notebooks to make sure they are runnable in CI
-    "docs/tutorials/storm/storm.ipynb",  # issues only when running with VCR
-    "docs/tutorials/lats/lats.ipynb",  # issues only when running with VCR
-    "docs/tutorials/rag/langgraph_crag.ipynb",  # flakiness from tavily
-    "docs/tutorials/rag/langgraph_adaptive_rag.ipynb",  # flakiness only when running in GHA 
-    "docs/tutorials/rag/langgraph_self_rag.ipynb",  # flakiness only when running in GHA
-    "docs/tutorials/rag/langgraph_agentic_rag.ipynb",  # flakiness only when running in GHA
-    "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
-]
-
-
-def comment_install_cells(notebook: nbformat.NotebookNode) -> nbformat.NotebookNode:
-    for cell in notebook.cells:
-        if cell.cell_type != "code":
-            continue
-
-        if "pip install" in cell.source:
-            # Comment out the lines in cells containing "pip install"
-            cell.source = "\n".join(
-                f"# {line}" if line.strip() else line
-                for line in cell.source.splitlines()
-            )
-
-    return notebook
-
-
-def is_magic_command(code: str) -> bool:
-    return code.strip().startswith("%") or code.strip().startswith("!")
-
-
-def is_comment(code: str) -> bool:
-    return code.strip().startswith("#")
-
-
-def has_blocklisted_command(code: str, metadata: dict) -> bool:
-    if 'hide_from_vcr' in metadata:
-        return True
-    
-    code = code.strip()
-    for blocklisted_pattern in BLOCKLIST_COMMANDS:
-        if blocklisted_pattern in code:
-            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
-) -> nbformat.NotebookNode:
-    """Inject `with vcr.cassette` into each code cell of the notebook."""
-
-    uses_langsmith = False
-    # Inject VCR context manager into each code cell
-    for idx, cell in enumerate(notebook.cells):
-        if cell.cell_type != "code":
-            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
-
-        are_magic_lines = [is_magic_command(line) for line in lines]
-
-        # skip if all magic
-        if all(are_magic_lines):
-            continue
-
-        if any(are_magic_lines):
-            raise ValueError(
-                "Cannot process code cells with mixed magic and non-magic code."
-            )
-
-        # skip if just comments
-        if all(is_comment(line) or not line.strip() for line in lines):
-            continue
-
-        if has_blocklisted_command(cell.source, cell.metadata):
-            continue
-
-        cell_id = cell.get("id", idx)
-        cassette_name = f"{cassette_prefix}_{cell_id}.msgpack.zlib"
-        cell.source = f"with custom_vcr.use_cassette('{cassette_name}', filter_headers=['x-api-key', 'authorization'], record_mode='once', serializer='advanced_compressed'):\n" + "\n".join(
-            f"    {line}" for line in lines
-        )
-
-        if any("hub.pull" in line or "from langsmith import" in line for line in lines):
-            uses_langsmith = True
-
-    # Add import statement
-    vcr_import_lines = []
-    if uses_langsmith:
-        vcr_import_lines.extend([
-            # patch urllib3 to handle vcr errors, see more here:
-            # https://github.com/langchain-ai/langsmith-sdk/blob/main/python/langsmith/_internal/_patch.py
-            "import sys",
-            f"sys.path.insert(0, '{os.path.join(DOCS_PATH, '_scripts')}')",
-            "import _patch as patch_urllib3",
-            "patch_urllib3.patch_urllib3()",
-        ])
-
-    vcr_import_lines.extend([
-        "import nest_asyncio",
-        "nest_asyncio.apply()",
-        "import vcr",
-        "import msgpack",
-        "import base64",
-        "import zlib",
-        "import os",
-        "os.environ.pop(\"LANGCHAIN_TRACING_V2\", None)",
-        "custom_vcr = vcr.VCR()",
-        "",
-        "def compress_data(data, compression_level=9):",
-        "    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):",
-        "    decoded = base64.b64decode(compressed_string)",
-        "    decompressed = zlib.decompress(decoded)",
-        "    return msgpack.unpackb(decompressed, raw=False)",
-        "",
-        "class AdvancedCompressedSerializer:",
-        "    def serialize(self, cassette_dict):",
-        "        return compress_data(cassette_dict)",
-        "",
-        "    def deserialize(self, cassette_string):",
-        "        return decompress_data(cassette_string)",
-        "",
-        "custom_vcr.register_serializer('advanced_compressed', AdvancedCompressedSerializer())",
-        "custom_vcr.serializer = 'advanced_compressed'",
-    ])
-
-    import_cell = nbformat.v4.new_code_cell(source="\n".join(vcr_import_lines))
-    import_cell.pop("id", None)
-    notebook.cells.insert(0, import_cell)
-    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):
-            for file in files:
-                if not file.endswith(".ipynb") or "ipynb_checkpoints" in root:
-                    continue
-
-                notebook_path = os.path.join(root, file)
-                try:
-                    notebook = nbformat.read(notebook_path, as_version=4)
-
-                    if should_comment_install_cells:
-                        notebook = comment_install_cells(notebook)
-
-                    base_filename = os.path.splitext(os.path.basename(file))[0]
-                    cassette_prefix = os.path.join(CASSETTES_PATH, base_filename)
-                    if notebook_path not in NOTEBOOKS_NO_CASSETTES:
-                        notebook = add_vcr_to_notebook(
-                            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(
-                            source="**Warning:** This notebook is not meant to be executed automatically."
-                        )
-                        notebook.cells.insert(0, warning_cell)
-
-                        # Add a special tag to the first code cell
-                        if notebook.cells and notebook.cells[1].cell_type == "code":
-                            notebook.cells[1].metadata["tags"] = notebook.cells[1].metadata.get("tags", []) + ["no_execution"]
-
-                    nbformat.write(notebook, notebook_path)
-                    logger.info(f"Processed: {notebook_path}")
-                except Exception as e:
-                    logger.error(f"Error processing {notebook_path}: {e}")
-    
-    with open("notebooks_no_execution.json", "w") as f:
-        json.dump(NOTEBOOKS_NO_EXECUTION, f)
-
-
-@click.command()
-@click.option(
-    "--comment-install-cells",
-    is_flag=True,
-    default=False,
-    help="Whether to comment out install cells",
-)
-def main(comment_install_cells):
-    process_notebooks(should_comment_install_cells=comment_install_cells)
-    logger.info("All notebooks processed successfully.")
-
-
-if __name__ == "__main__":
-    main()

docs/_scripts/third_party_page/create_third_party_page.py

@@ -1,172 +0,0 @@
-#!/usr/bin/env python
-"""Create the third party page for the documentation."""
-
-import argparse
-from typing import List
-from typing import TypedDict
-
-import yaml
-
-MARKDOWN = """\
-[//]: # (This file is automatically generated using a script in docs/_scripts. Do not edit this file directly!)
-# Community Agents
-
-If you’re looking for other prebuilt libraries, explore the community-built options 
-below. These libraries can extend LangGraph's functionality in various ways.
-
-## 📚 Available Libraries
-[//]: # (This file is automatically generated using a script in docs/_scripts. Do not edit this file directly!)
-
-:::python
-{python_library_list}
-
-## ✨ Contributing Your Library
-
-Have you built an awesome open-source library using LangGraph? We'd love to feature 
-your project on the official LangGraph documentation pages! 🏆
-
-To share your project, simply open a Pull Request adding an entry for your package in our [packages.yml]({langgraph_url}) file.
-
-**Guidelines**
-
-- Your repo must be distributed as an installable package on PyPI 📦
-- The repo should either use the Graph API (exposing a `StateGraph` instance) or 
-  the Functional API (exposing an `entrypoint`).
-- The package must include documentation (e.g., a `README.md` or docs site) 
-  explaining how to use it.
-
-We'll review your contribution and merge it in!
-
-Thanks for contributing! 🚀
-:::
-
-:::js
-{js_library_list}
-
-## ✨ Contributing Your Library
-
-Have you built an awesome open-source library using LangGraph? We'd love to feature 
-your project on the official LangGraph documentation pages! 🏆
-
-To share your project, simply open a Pull Request adding an entry for your package in our [packages.yml]({langgraph_url}) file.
-
-**Guidelines**
-
-- Your repo must be distributed as an installable package on npm 📦
-- The repo should either use the Graph API (exposing a `StateGraph` instance) or 
-  the Functional API (exposing an `entrypoint`).
-- The package must include documentation (e.g., a `README.md` or docs site) 
-  explaining how to use it.
-
-We'll review your contribution and merge it in!
-
-Thanks for contributing! 🚀
-:::
-"""
-
-
-class ResolvedPackage(TypedDict):
-    name: str
-    """The name of the package."""
-    repo: str
-    """Repository ID within github. Format is: [orgname]/[repo_name]."""
-    monorepo_path: str | None
-    """Optional: The path to the package in the monorepo. Must be relative to the root of the monorepo."""
-    language: str
-    """The language of the package. (either 'python' or 'js')"""
-    weekly_downloads: int | None
-    """The weekly download count of the package."""
-    description: str
-    """A brief description of what the package does."""
-
-def generate_package_table(resolved_packages: List[ResolvedPackage]) -> str:
-    """Generate the package table for the third party page.
-    """
-    sorted_packages = sorted(
-        resolved_packages, key=lambda p: p["weekly_downloads"] or 0, reverse=True
-    )
-    rows = [
-        "| Name | GitHub URL | Description | Weekly Downloads | Stars |",
-        "| --- | --- | --- | --- | --- |",
-    ]
-    for package in sorted_packages:
-        name = f"**{package['name']}**"
-        
-        monorepo_path = package.get("monorepo_path", "")
-        if monorepo_path:
-            monorepo_path = monorepo_path[1:] if monorepo_path.startswith('/') else monorepo_path
-            repo_url_suffix = f"/tree/main/{monorepo_path}"
-        else:
-            repo_url_suffix = ""
-        repo_url = f"https://github.com/{package['repo']}{repo_url_suffix}"
-
-        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}"
-        rows.append(row)
-    return "\n".join(rows)
-
-def generate_markdown(resolved_packages: List[ResolvedPackage]) -> str:
-    """Generate the markdown content for the third party page.
-
-    Args:
-        resolved_packages: A list of resolved package information.
-
-    Returns:
-        The markdown content as a string.
-    """
-    # Update the URL to the actual file once the initial version is merged
-    langgraph_url = (
-        "https://github.com/langchain-ai/langgraph/blob/main/docs"
-        "/_scripts/third_party_page/packages.yml"
-    )
-
-    python_library_list = generate_package_table(
-        [p for p in resolved_packages if p["language"] == "python"]
-    )
-    js_library_list = generate_package_table(
-        [p for p in resolved_packages if p["language"] == "js"]
-    )
-    
-    markdown_content = MARKDOWN.format(
-        python_library_list=python_library_list,
-        js_library_list=js_library_list,
-        langgraph_url=langgraph_url,
-    )
-    return markdown_content
-
-
-def main(input_file: str, output_file: str) -> None:
-    """Main function to create the third party page.
-
-    Args:
-        input_file: Path to the input YAML file containing resolved package information.
-        output_file: Path to the output file for the third party page.
-        language: The language for which to generate the third party page.
-    """
-    # Parse the input YAML file
-    with open(input_file, "r") as f:
-        resolved_packages: List[ResolvedPackage] = yaml.safe_load(f)
-
-    markdown_content = generate_markdown(resolved_packages)
-
-    # Write the markdown content to the output file
-    with open(output_file, "w", encoding="utf-8") as f:
-        f.write(markdown_content)
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Create the third party page.")
-    parser.add_argument(
-        "input_file",
-        help="Path to the input YAML file containing resolved package information.",
-    )
-    parser.add_argument(
-        "output_file", help="Path to the output file for the third party page."
-    )
-    args = parser.parse_args()
-
-    main(args.input_file, args.output_file)

docs/_scripts/third_party_page/get_download_stats.py

@@ -1,187 +0,0 @@
-#!/usr/bin/env python
-"""Retrieve download count for a list of Python packages from PyPI."""
-
-import argparse
-from datetime import datetime
-from typing import TypedDict
-import pathlib
-
-import requests
-import yaml
-
-
-class Package(TypedDict):
-    name: str
-    """The name of the package."""
-    repo: str
-    """Repository ID within github. Format is: [orgname]/[repo_name]."""
-    monorepo_path: str | None
-    """The path to the package in the monorepo. Only used for JS packages."""
-    description: str
-    """A brief description of what the package does."""
-
-class ResolvedPackage(Package):
-    weekly_downloads: int | None
-    """The weekly download count of the package."""
-    language: str
-    """The language of the package. (either 'python' or 'js')"""
-
-HERE = pathlib.Path(__file__).parent
-PACKAGES_FILE = HERE / "packages.yml"
-PACKAGES = yaml.safe_load(PACKAGES_FILE.read_text())["packages"]
-
-def _get_pypi_downloads(package: Package) -> int:
-    """Retrieve the weekly download count for a package from PyPIStats."""
-
-    # 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")
-
-    # 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
-
-    if first_release_date is None:
-        raise AssertionError(f"Package {package['name']} has no releases yet")
-
-    # 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
-        return sum(entry["downloads"] for entry in sorted_data[:7])
-    else:
-        return None
-    
-def _get_npm_downloads(package: Package) -> int:
-    """Retrieve the weekly download count for a package on the npm registry."""
-
-    # Check if package exists on the npm registry
-    npm_url = f"https://registry.npmjs.org/{package['name']}"
-    try:
-        npm_response = requests.get(npm_url)
-        npm_response.raise_for_status()
-    except requests.exceptions.HTTPError:
-        raise AssertionError(f"Package {package['name']} does not exist on npm registry")
-
-    npm_data = npm_response.json()
-
-    # Retrieve the first publish date using the 'created' timestamp from the 'time' field.
-    created_str = npm_data.get("time", {}).get("created")
-    if created_str is None:
-        raise AssertionError(f"Package {package['name']} has no creation time in registry data")
-    # Remove the trailing 'Z' if present and parse the ISO format timestamp
-    first_publish_date = datetime.fromisoformat(created_str.rstrip("Z"))
-
-    # If package was published more than 48 hours ago, fetch download stats.
-    if (datetime.now() - first_publish_date).total_seconds() >= 48 * 3600:
-        stats_url = f"https://api.npmjs.org/downloads/point/last-week/{package['name']}"
-        stats_response = requests.get(stats_url)
-        stats_response.raise_for_status()
-        stats_data = stats_response.json()
-        return stats_data.get("downloads", None)
-    else:
-        return None
-
-def _get_weekly_downloads(packages: dict[str, list[Package]], fake: bool) -> list[ResolvedPackage]:
-    """Retrieve the weekly download count for a dictionary of python or js packages."""
-    resolved_packages: list[ResolvedPackage] = []
-
-    if fake:
-        # To avoid making network requests during testing, return fake download counts
-        for language, package_list in packages.items():
-            for package in package_list:
-                resolved_packages.append(
-                    {
-                        "name": package["name"],
-                        "repo": package["repo"],
-                        "monorepo_path": package.get("monorepo_path", None),
-                        "language": language,
-                        "description": package["description"],
-                        "weekly_downloads": -12345,
-                    }
-                )
-        return resolved_packages
-
-    for language, package_list in packages.items():
-        for package in package_list:
-            if language == "python":
-                num_downloads = _get_pypi_downloads(package)
-            elif language == "js":
-                num_downloads = _get_npm_downloads(package)
-            else:
-                num_downloads = None
-            
-            resolved_packages.append(
-                {
-                    "name": package["name"],
-                    "repo": package["repo"],
-                    "monorepo_path": package.get("monorepo_path", None),
-                    "language": language,
-                    "description": package["description"],
-                    "weekly_downloads": num_downloads,
-                }
-            )
-
-    return resolved_packages
-
-def main(output_file: str, fake: bool) -> None:
-    """Main function to generate package download information.
-
-    Args:
-        output_file: Path to the output YAML file.
-        fake: If True, use fake download counts for testing purposes.
-    """
-    resolved_packages: list[ResolvedPackage] = _get_weekly_downloads(PACKAGES, fake)
-
-    if not output_file.endswith(".yml"):
-        raise ValueError("Output file must have a .yml extension")
-
-    with open(output_file, "w") as f:
-        f.write("# This file is auto-generated. Do not edit.\n")
-        yaml.dump(resolved_packages, f)
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
-        description="Generate package download information."
-    )
-    parser.add_argument(
-        "output_file",
-        help=(
-            "Path to the output YAML file. Example: python generate_downloads.py "
-            "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)

docs/_scripts/third_party_page/packages.yml

@@ -1,58 +0,0 @@
-#A list of third-party packages to surface on the third-party page.
-packages:
-  python:
-    - name: "trustcall"
-      repo: "hinthornw/trustcall"
-      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."
-    - 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."
-  js:
-    - name: "@langchain/mcp-adapters"
-      repo: "langchain-ai/langchainjs"
-      description: "Make Anthropic Model Context Protocol (MCP) tools compatible with LangGraph agents."
-    - name: "@langchain/langgraph-supervisor"
-      repo: "langchain-ai/langgraphjs"
-      monorepo_path: "libs/langgraph-supervisor"
-      description: "Build supervisor multi-agent systems with LangGraph"
-    - name: "@langchain/langgraph-swarm"
-      repo: "langchain-ai/langgraphjs"
-      monorepo_path: "libs/langgraph-swarm"
-      description: "Build multi-agent swarms with LangGraph"
-    - name: "@langchain/langgraph-cua"
-      repo: "langchain-ai/langgraphjs"
-      monorepo_path: "libs/langgraph-cua"
-      description: "Build computer use agents with LangGraph"

docs/cassettes/agent-simulation-evaluation_6f80669e-aa78-4666-b67c-a539366d5aab.msgpack.zlib

@@ -1 +0,0 @@
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docs/cassettes/agent_supervisor_f803943c-6dd2-4b42-93ba-0210ec276132.msgpack.zlib

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docs/cassettes/async_8edb04b9-40b6-46f1-a7a8-4b2d8aba7752.msgpack.zlib

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docs/cassettes/async_cfd140f0-a5a6-4697-8115-322242f197b5.msgpack.zlib

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docs/cassettes/async_f544977e-31f7-41f0-88c4-ec9c27b8cecb.msgpack.zlib

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docs/cassettes/configuration_718685f7-4cdd-4181-9fc8-e7762d584727.msgpack.zlib

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docs/cassettes/configuration_e043a719-f197-46ef-9d45-84740a39aeb0.msgpack.zlib

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docs/cassettes/configuration_ef50f048-fc43-40c0-b713-346408fcf052.msgpack.zlib

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docs/cassettes/configuration_f2f7c74b-9fb0-41c6-9728-dcf9d8a3c397.msgpack.zlib

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docs/cassettes/create-react-agent-manage-message-history_26c53429-90ba-4d0b-abb9-423d9120ad26.msgpack.zlib

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docs/cassettes/disable-streaming_4.msgpack.zlib

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docs/cassettes/disable-streaming_8.msgpack.zlib

@@ -1 +0,0 @@
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