update pydantic in lockfile

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -1,6 +1,6 @@
 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 GitHub Discussions.
-labels: [pending,bug]
+labels: ["02 Bug Report"]
 body:
   - type: markdown
     attributes:

.github/ISSUE_TEMPLATE/config.yml

@@ -1,4 +1,4 @@
-blank_issues_enabled: true
+blank_issues_enabled: false
 version: 2.1
 contact_links:
   - name: 🤔 Question or Problem

.github/ISSUE_TEMPLATE/documentation.yml

@@ -1,7 +1,7 @@
 name: Documentation
 description: Report an issue related to the LangGraph documentation.
 title: "DOC: <Please write a comprehensive title after the 'DOC: ' prefix>"
-labels: [documentation]
+labels: [03 - Documentation]
 
 body:
 - type: textarea

.github/actions/poetry_setup/action.yml

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

.github/dependabot.yml

@@ -1,11 +0,0 @@
-# Please see the documentation for all configuration options:
-# https://docs.github.com/github/administering-a-repository/configuration-options-for-dependency-updates
-# and
-# https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file
-
-version: 2
-updates:
-  - package-ecosystem: "github-actions"
-    directory: "/"
-    schedule:
-      interval: "weekly"

.github/workflows/_integration_test.yml

@@ -3,6 +3,9 @@ name: CLI integration test
 on:
   workflow_call:
 
+env:
+  POETRY_VERSION: "2.1.2"
+
 jobs:
   build:
     runs-on: ubuntu-latest
@@ -22,14 +25,13 @@ jobs:
         uses: Ana06/get-changed-files@v2.3.0
         with:
           filter: "libs/cli/**"
-      - name: Set up Python ${{ matrix.python-version }}
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
         if: steps.changed-files.outputs.all
-        uses: astral-sh/setup-uv@v6
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: ${{ matrix.python-version }}
-          enable-cache: true
-          cache-suffix: "cli-integration-test"
-          ignore-nothing-to-cache: true
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: integration-test-cli
       - name: Setup env
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples

.github/workflows/_lint.yml

@@ -9,6 +9,8 @@ on:
         description: "From which folder this pipeline executes"
 
 env:
+  POETRY_VERSION: "2.1.2"
+
   # This env var allows us to get inline annotations when ruff has complaints.
   RUFF_OUTPUT_FORMAT: github
 
@@ -34,28 +36,42 @@ jobs:
         uses: Ana06/get-changed-files@v2.3.0
         with:
           filter: "${{ inputs.working-directory }}/**"
-      - name: Set up Python ${{ matrix.python-version }}
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
         if: steps.changed-files.outputs.all
-        uses: astral-sh/setup-uv@v6
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: ${{ matrix.python-version }}
-          enable-cache: true
-          cache-suffix: lint-${{ inputs.working-directory }}
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: lint-${{ inputs.working-directory }}
+
+      - name: Check Poetry File
+        if: steps.changed-files.outputs.all
+        shell: bash
+        working-directory: ${{ inputs.working-directory }}
+        run: poetry check
 
       - name: Install dependencies
         if: steps.changed-files.outputs.all
+        # Also installs dev/lint/test/typing dependencies, to ensure we have
+        # type hints for as many of our libraries as possible.
+        # This helps catch errors that require dependencies to be spotted, for example:
+        # https://github.com/langchain-ai/langchain/pull/10249/files#diff-935185cd488d015f026dcd9e19616ff62863e8cde8c0bee70318d3ccbca98341
+        #
+        # If you change this configuration, make sure to change the `cache-key`
+        # in the `poetry_setup` action above to stop using the old cache.
+        # It doesn't matter how you change it, any change will cause a cache-bust.
         working-directory: ${{ inputs.working-directory }}
-        run: uv sync --frozen --group dev
+        run: poetry install --with dev
 
       - name: Get .mypy_cache to speed up mypy
         if: steps.changed-files.outputs.all
-        uses: actions/cache@v4
+        uses: actions/cache@v3
         env:
           SEGMENT_DOWNLOAD_TIMEOUT_MIN: "2"
         with:
           path: |
             ${{ inputs.working-directory }}/.mypy_cache
-          key: mypy-lint-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/uv.lock', inputs.working-directory)) }}
+          key: mypy-lint-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}
 
       - name: Analysing package code with our lint
         if: steps.changed-files.outputs.all
@@ -70,18 +86,27 @@ jobs:
 
       - name: Install test dependencies
         if: steps.changed-files.outputs.all
+        # Also installs dev/lint/test/typing dependencies, to ensure we have
+        # type hints for as many of our libraries as possible.
+        # This helps catch errors that require dependencies to be spotted, for example:
+        # https://github.com/langchain-ai/langchain/pull/10249/files#diff-935185cd488d015f026dcd9e19616ff62863e8cde8c0bee70318d3ccbca98341
+        #
+        # If you change this configuration, make sure to change the `cache-key`
+        # in the `poetry_setup` action above to stop using the old cache.
+        # It doesn't matter how you change it, any change will cause a cache-bust.
         working-directory: ${{ inputs.working-directory }}
-        run: uv sync --group dev
+        run: |
+          poetry install --with dev
 
       - name: Get .mypy_cache_test to speed up mypy
         if: steps.changed-files.outputs.all
-        uses: actions/cache@v4
+        uses: actions/cache@v3
         env:
           SEGMENT_DOWNLOAD_TIMEOUT_MIN: "2"
         with:
           path: |
             ${{ inputs.working-directory }}/.mypy_cache_test
-          key: mypy-test-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/uv.lock', inputs.working-directory)) }}
+          key: mypy-test-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}
 
       - name: Analysing tests with our lint
         if: steps.changed-files.outputs.all

.github/workflows/_test.yml

@@ -8,6 +8,9 @@ on:
         type: string
         description: "From which folder this pipeline executes"
 
+env:
+  POETRY_VERSION: "2.1.2"
+
 jobs:
   build:
     runs-on: ubuntu-latest
@@ -23,12 +26,12 @@ jobs:
     name: "test #${{ matrix.python-version }}"
     steps:
       - uses: actions/checkout@v4
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: ${{ matrix.python-version }}
-          enable-cache: true
-          cache-suffix: test-${{ inputs.working-directory }}
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: test-${{ inputs.working-directory }}
       - name: Login to Docker Hub
         uses: docker/login-action@v3
         if: ${{ !github.event.pull_request.head.repo.fork }}
@@ -39,12 +42,14 @@ jobs:
       - name: Install dependencies
         shell: bash
         working-directory: ${{ inputs.working-directory }}
-        run: uv sync --frozen --group dev
+        run: |
+          poetry install --with dev
 
       - name: Run tests
         shell: bash
         working-directory: ${{ inputs.working-directory }}
-        run: make test
+        run: |
+          make test
 
       - name: Ensure the tests did not create any additional files
         shell: bash

.github/workflows/_test_langgraph.yml

@@ -3,6 +3,9 @@ name: test
 on:
   workflow_call:
 
+env:
+  POETRY_VERSION: "2.1.2"
+
 jobs:
   build:
     runs-on: ubuntu-latest
@@ -21,12 +24,12 @@ jobs:
     name: "test #${{ matrix.python-version }}"
     steps:
       - uses: actions/checkout@v4
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: ${{ matrix.python-version }}
-          enable-cache: true
-          cache-suffix: "test-langgraph"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: test-langgraph
       - name: Login to Docker Hub
         uses: docker/login-action@v3
         if: ${{ !github.event.pull_request.head.repo.fork }}
@@ -36,11 +39,13 @@ jobs:
 
       - name: Install dependencies
         shell: bash
-        run: uv sync --frozen --group dev
+        run: |
+          poetry install --with dev
 
       - name: Run tests
         shell: bash
-        run: make test_parallel
+        run: |
+          make test_parallel
 
       - name: Ensure the tests did not create any additional files
         shell: bash

.github/workflows/_test_release.yml

@@ -9,6 +9,7 @@ on:
         description: "From which folder this pipeline executes"
 
 env:
+  POETRY_VERSION: "2.1.2"
   PYTHON_VERSION: "3.10"
 
 jobs:
@@ -23,12 +24,12 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python $${ env.PYTHON_VERSION }}
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          enable-cache: true
-          cache-suffix: "release"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: release
 
       # We want to keep this build stage *separate* from the release stage,
       # so that there's no sharing of permissions between them.
@@ -42,7 +43,7 @@ jobs:
       # > from the publish job.
       # https://github.com/pypa/gh-action-pypi-publish#non-goals
       - name: Build project for distribution
-        run: uv build
+        run: poetry build
         working-directory: ${{ inputs.working-directory }}
 
       - name: Upload build
@@ -56,8 +57,8 @@ jobs:
         shell: bash
         working-directory: ${{ inputs.working-directory }}
         run: |
-          echo pkg-name=$(grep -m 1 "^name = " pyproject.toml | cut -d '"' -f 2)
-          echo version=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
+          echo pkg-name="$(poetry version | cut -d ' ' -f 1)" >> $GITHUB_OUTPUT
+          echo version="$(poetry version --short)" >> $GITHUB_OUTPUT
 
   publish:
     needs:

.github/workflows/_test_scheduler_kafka.yml

@@ -0,0 +1,57 @@
+name: test
+
+on:
+  workflow_call:
+
+env:
+  POETRY_VERSION: "2.1.2"
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version:
+          - "3.11"
+          - "3.12"
+
+    defaults:
+      run:
+        working-directory: libs/scheduler-kafka
+    name: "test #${{ matrix.python-version }}"
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
+        with:
+          python-version: ${{ matrix.python-version }}
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: test-scheduler-kafka
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        if: ${{ !github.event.pull_request.head.repo.fork }}
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_RO_TOKEN }}
+
+      - name: Install dependencies
+        shell: bash
+        run: |
+          poetry install --with dev
+
+      - name: Run tests
+        shell: bash
+        run: |
+          make test
+
+      - name: Ensure the tests did not create any additional files
+        shell: bash
+        run: |
+          set -eu
+
+          STATUS="$(git status)"
+          echo "$STATUS"
+
+          # grep will exit non-zero if the target message isn't found,
+          # and `set -e` above will cause the step to fail.
+          echo "$STATUS" | grep 'nothing to commit, working tree clean'

.github/workflows/baseline.yml

@@ -7,6 +7,9 @@ on:
     paths:
       - "libs/**"
 
+env:
+  POETRY_VERSION: "2.1.2"
+
 jobs:
   benchmark:
     runs-on: ubuntu-latest
@@ -16,14 +19,14 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - run: SHA=$(git rev-parse HEAD) && echo "SHA=$SHA" >> $GITHUB_ENV
-      - name: Set up Python 3.11
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python 3.11 + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: "3.11"
-          enable-cache: true
-          cache-suffix: "bench"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: bench
       - name: Install dependencies
-        run: uv sync --group dev
+        run: poetry install --with dev
       - name: Run benchmarks
         run: OUTPUT=out/benchmark-baseline.json make -s benchmark
       - name: Save outputs

.github/workflows/bench.yml

@@ -5,6 +5,9 @@ on:
     paths:
       - "libs/**"
 
+env:
+  POETRY_VERSION: "2.1.2"
+
 jobs:
   benchmark:
     runs-on: ubuntu-latest
@@ -18,14 +21,14 @@ jobs:
         uses: Ana06/get-changed-files@v2.3.0
         with:
           format: json
-      - name: Set up Python 3.11
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python 3.11 + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: "3.11"
-          enable-cache: true
-          cache-suffix: "bench"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: bench
       - name: Install dependencies
-        run: uv sync --group dev
+        run: poetry install --with dev
       - name: Download baseline
         uses: actions/cache/restore@v4
         with:
@@ -50,7 +53,7 @@ jobs:
             echo 'OUTPUT<<EOF'
             mv out/benchmark-baseline.json out/main.json
             mv out/benchmark.json out/changes.json
-            uv run pyperf compare_to out/main.json out/changes.json --table --group-by-speed
+            poetry run pyperf compare_to out/main.json out/changes.json --table --group-by-speed
             echo EOF
           } >> "$GITHUB_OUTPUT"
       - name: Annotation

.github/workflows/ci.yml

@@ -16,6 +16,9 @@ concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}
   cancel-in-progress: true
 
+env:
+  POETRY_VERSION: "2.1.2"
+
 jobs:
   changes:
     runs-on: ubuntu-latest
@@ -35,6 +38,7 @@ jobs:
               - 'libs/checkpoint/**'
               - 'libs/checkpoint-sqlite/**'
               - 'libs/checkpoint-postgres/**'
+              - 'libs/scheduler-kafka/**'
               - 'libs/prebuilt/**'
             sdk-js:
               - 'libs/sdk-js/**'
@@ -52,7 +56,7 @@ jobs:
             "libs/checkpoint",
             "libs/checkpoint-sqlite",
             "libs/checkpoint-postgres",
-
+            "libs/scheduler-kafka",
             "libs/prebuilt",
           ]
     if: needs.changes.outputs.python == 'true'
@@ -88,6 +92,14 @@ jobs:
     uses: ./.github/workflows/_test_langgraph.yml
     secrets: inherit
 
+  # NOTE: we're testing scheduler-kafka separately because it requires a different matrix
+  test-scheduler-kafka:
+    needs: changes
+    if: needs.changes.outputs.python == 'true'
+    name: "cd libs/scheduler-kafka"
+    uses: ./.github/workflows/_test_scheduler_kafka.yml
+    secrets: inherit
+
   check-sdk-methods:
     needs: changes
     if: needs.changes.outputs.python == 'true'
@@ -113,26 +125,26 @@ jobs:
           - "3.11"
     steps:
       - uses: actions/checkout@v4
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: "3.11"
-          enable-cache: true
-          cache-suffix: "schema-check-cli"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: schema-check-cli
       - name: Install CLI dependencies
         run: |
           cd libs/cli
-          uv sync
+          poetry install
       - name: Generate schema and check for changes
         run: |
           cd libs/cli
           # Create a temporary copy of the current schema
           cp schemas/schema.json schemas/schema.current.json
           # Generate new schema
-          uv run python generate_schema.py
+          poetry run python generate_schema.py
           # Compare the new schema with the original
           if ! diff -q schemas/schema.json schemas/schema.current.json > /dev/null; then
-            echo "Error: Langgraph.json configuration schema has changed. Please run 'uv run python generate_schema.py' in the libs/cli directory and commit the changes."
+            echo "Error: Langgraph.json configuration schema has changed. Please run 'poetry run python generate_schema.py' in the libs/cli directory and commit the changes."
             diff schemas/schema.json schemas/schema.current.json
             exit 1
           fi
@@ -157,9 +169,9 @@ jobs:
       run:
         working-directory: ${{ matrix.working-directory }}
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v3
       - name: Setup Node.js (LTS)
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v3
         with:
           node-version: "20"
           cache: "yarn"
@@ -183,9 +195,9 @@ jobs:
       run:
         working-directory: ${{ matrix.working-directory }}
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v3
       - name: Setup Node.js (LTS)
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v3
         with:
           node-version: "20"
           cache: "yarn"
@@ -203,6 +215,7 @@ jobs:
         lint-js,
         test,
         test-langgraph,
+        test-scheduler-kafka,
         check-sdk-methods,
         check-schema,
         integration-test,

.github/workflows/deploy_docs.yml

@@ -4,13 +4,14 @@ on:
   push:
     branches:
       - main
-      - v0
   pull_request:
     branches:
       - main
-      - v0
   workflow_dispatch:
 
+env:
+  POETRY_VERSION: "2.1.2"
+
 permissions:
   contents: read
   pages: write
@@ -56,21 +57,21 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: "3.12"
-          enable-cache: true
-          cache-suffix: "docs"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: docs
 
       - name: Install dependencies
         run: |
           yarn
-          uv sync --all-groups
+          poetry install --with test --with docs --no-root
           # we run this installation only for internal PRs
           # as GITHUB_TOKEN is not available for PRs from outside contributors
           if [ -n "${GITHUB_TOKEN}" ]; then
-            uv run pip install "git+https://${GITHUB_TOKEN}@github.com/langchain-ai/mkdocs-material-insiders.git"
+            poetry run pip install "git+https://${GITHUB_TOKEN}@github.com/langchain-ai/mkdocs-material-insiders.git"
           fi
 
       - name: Run unit tests
@@ -84,9 +85,9 @@ jobs:
         run: make llms-text
       - name: Build site
         run: |
-          # If this is v0 branch, then we want to download stats. we do this 
+          # If this is main branch, then we want to download stats. we do this 
           # with the env variable DOWNLOAD_STATS=true
-          if [ "${{ github.ref }}" == "refs/heads/v0" ]; then
+          if [ "${{ github.ref }}" == "refs/heads/main" ]; then
             DOWNLOAD_STATS=true make build-docs
           else
             make build-docs
@@ -102,7 +103,7 @@ jobs:
         run: |
           if [ "${{ github.event_name }}" == "schedule" ]; then
             echo "Running link check on all HTML files matching notebooks in docs directory..."
-            uv run pytest -v \
+            poetry run pytest -v \
               --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
               --check-links-ignore "https://academy\.langchain\.com/.*" \
               --check-links-ignore "https://x.com/.*" \
@@ -127,7 +128,7 @@ jobs:
             echo "Changed files: ${CHANGED_FILES}"
             if [ -n "${CHANGED_FILES}" ]; then
               echo "Running link check on HTML files matching changed notebook files..."
-              uv run pytest -v \
+              poetry run pytest -v \
                 --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
                 --check-links-ignore "https://academy\.langchain\.com/.*" \
                 --check-links-ignore "http://localhost:8123/.*" \
@@ -146,8 +147,8 @@ jobs:
           fi
 
       - name: Configure GitHub Pages
-        if: github.ref == 'refs/heads/v0'
-        uses: actions/configure-pages@v5
+        if: github.ref == 'refs/heads/main'
+        uses: actions/configure-pages@v4
 
       - name: Upload Pages Artifact
         # if: github.ref == 'refs/heads/main'
@@ -156,6 +157,6 @@ jobs:
           path: ./docs/site/
 
       - name: Deploy to GitHub Pages
-        if: github.ref == 'refs/heads/v0'
+        if: github.ref == 'refs/heads/main'
         id: deployment
         uses: actions/deploy-pages@v4

.github/workflows/link_check.yml

@@ -11,6 +11,9 @@ on:
     - cron: "0 5 * * *"
   workflow_dispatch:
 
+env:
+  POETRY_VERSION: "2.1.2"
+
 jobs:
   markdown-link-check:
     runs-on: ubuntu-latest

.github/workflows/release.yml

@@ -10,6 +10,7 @@ on:
 
 env:
   PYTHON_VERSION: "3.11"
+  POETRY_VERSION: "2.1.2"
 
 jobs:
   build:
@@ -25,12 +26,12 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          enable-cache: true
-          cache-suffix: "release"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: release
 
       # We want to keep this build stage *separate* from the release stage,
       # so that there's no sharing of permissions between them.
@@ -44,7 +45,7 @@ jobs:
       # > from the publish job.
       # https://github.com/pypa/gh-action-pypi-publish#non-goals
       - name: Build project for distribution
-        run: uv build
+        run: poetry build
         working-directory: ${{ inputs.working-directory }}
 
       - name: Upload build
@@ -58,8 +59,8 @@ jobs:
         shell: bash
         working-directory: ${{ inputs.working-directory }}
         run: |
-          PKG_NAME=$(grep -m 1 "^name = " pyproject.toml | cut -d '"' -f 2)
-          VERSION=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
+          PKG_NAME="$(poetry version | cut -d ' ' -f 1)"
+          VERSION="$(poetry version --short)"
           SHORT_PKG_NAME="$(echo "$PKG_NAME" | sed -e 's/langgraph//g' -e 's/-//g')"
           if [ -z $SHORT_PKG_NAME ]; then
             TAG="$VERSION"
@@ -162,11 +163,11 @@ jobs:
       # - The package is published, and it breaks on the missing dependency when
       #   used in the real world.
 
-      - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          enable-cache: true
+          poetry-version: ${{ env.POETRY_VERSION }}
 
       - name: Import published package
         shell: bash
@@ -184,18 +185,18 @@ jobs:
         # - attempt install again after 5 seconds if it fails because there is
         #   sometimes a delay in availability on test pypi
         run: |
-          uv run pip install \
+          poetry run pip install \
             --extra-index-url https://test.pypi.org/simple/ \
             "$PKG_NAME==$VERSION" || \
           ( \
             sleep 5 && \
-            uv run pip install \
+            poetry run pip install \
               --extra-index-url https://test.pypi.org/simple/ \
               "$PKG_NAME==$VERSION" \
           )
 
           if [[ "$PKG_NAME" == *prebuilt* ]]; then
-            uv run pip install langgraph
+            poetry run pip install langgraph
           fi
 
           if [[ "$PKG_NAME" == *checkpoint* || "$PKG_NAME" == *prebuilt* ]]; then
@@ -208,10 +209,10 @@ jobs:
             IMPORT_NAME="$(echo "$PKG_NAME" | sed s/-/_/g)"
           fi
 
-          uv run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
+          poetry run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
 
       - name: Import test dependencies
-        run: uv sync --group dev
+        run: poetry install --with dev
         working-directory: ${{ inputs.working-directory }}
 
       # Overwrite the local version of the package with the test PyPI version.
@@ -222,7 +223,7 @@ jobs:
           PKG_NAME: ${{ needs.build.outputs.pkg-name }}
           VERSION: ${{ needs.build.outputs.version }}
         run: |
-          uv run pip install \
+          poetry run pip install \
             --extra-index-url https://test.pypi.org/simple/ \
             "$PKG_NAME==$VERSION"
 
@@ -252,12 +253,12 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          enable-cache: true
-          cache-suffix: "release"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: release
 
       - uses: actions/download-artifact@v4
         with:
@@ -293,12 +294,12 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python
-        uses: astral-sh/setup-uv@v6
+      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          enable-cache: true
-          cache-suffix: "release"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: release
 
       - uses: actions/download-artifact@v4
         with:

.github/workflows/release_js.yml

@@ -22,7 +22,7 @@ jobs:
       - uses: actions/checkout@v4
       # JS Build
       - name: Use Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v3
         with:
           node-version: "20"
           cache: "yarn"

.github/workflows/run_notebooks.yml

@@ -27,30 +27,30 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - name: Set up Python + Poetry
-        uses: astral-sh/setup-uv@v6
+        uses: "./.github/actions/poetry_setup"
         with:
-          python-version: "3.11"
-          enable-cache: true
-          cache-suffix: "test-langgraph-notebooks"
+          python-version: 3.11
+          poetry-version: 2.1.2
+          cache-key: test-langgraph-notebooks
 
       - name: Install dependencies
         run: |
-          uv sync --group test
-          uv run pip install jupyter
+          poetry install --with test --no-root
+          poetry run pip install jupyter
 
       - name: Start services
         run: make start-services
 
       - name: Pre-download tiktoken files
         run: |
-          uv run python _scripts/download_tiktoken.py
+          poetry run python _scripts/download_tiktoken.py
 
       - name: Prepare notebooks
         run: |
           if [ "${{ matrix.lib-version }}" = "development" ]; then
-            uv run python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
+            poetry run python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
           else
-            uv run python _scripts/prepare_notebooks_for_ci.py
+            poetry run python _scripts/prepare_notebooks_for_ci.py
           fi
 
       - name: Run notebooks

.gitignore

@@ -181,4 +181,3 @@ Chinook.db
 .vercel
 .turbo
 .editorconfig
-.scratch

AGENTS.md

@@ -1,55 +0,0 @@
-# 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 Platform 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

@@ -109,7 +109,7 @@ Here are some high-level tips on writing a good how-to guide:
 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.
+impart perspective to the user rather than to finish a practical project. These guides should cover **why** things work they way they do.
 
 
 To quote the Diataxis website:
@@ -153,7 +153,7 @@ Each category serves a distinct purpose and requires a specific approach to writ
 
 Here are some other guidelines you should think about when writing and organizing documentation.
 
-We generally do not merge new tutorials from outside contributors without an actual need.
+We generally do not merge new tutorials from outside contributors without an actue need.
 We welcome updates as well as new integration docs, how-tos, and references.
 
 ### Avoid duplication
@@ -227,7 +227,6 @@ see a preview of the documentation on the pull request page.
 
 From the **monorepo root**, run the following command to install the dependencies:
 
-<!-- TODO -->
 ```bash
 poetry install --with docs --no-root
 ```

Makefile

@@ -1,58 +0,0 @@
-# Define the directories containing projects
-LIBS_DIRS := $(wildcard libs/*)
-
-# Default target
-.PHONY: all
-all: lint format lock test
-
-# Install dependencies for all projects
-.PHONY: install
-install:
-	@echo "Creating virtual environment..."
-	@uv venv
-	@for dir in $(LIBS_DIRS); do \
-		if [ -f $$dir/pyproject.toml ]; then \
-			echo "Installing dependencies for $$dir"; \
-			uv pip install -e $$dir; \
-		fi; \
-	done
-
-# Lint all projects
-.PHONY: lint
-lint:
-	@for dir in $(LIBS_DIRS); do \
-		if [ -f $$dir/Makefile ]; then \
-			echo "Running lint in $$dir"; \
-			$(MAKE) -C $$dir lint; \
-		fi; \
-	done
-
-# Format all projects
-.PHONY: format
-format:
-	@for dir in $(LIBS_DIRS); do \
-		if [ -f $$dir/Makefile ]; then \
-			echo "Running format in $$dir"; \
-			$(MAKE) -C $$dir format; \
-		fi; \
-	done
-
-# Lock all projects
-.PHONY: lock
-lock:
-	@for dir in $(LIBS_DIRS); do \
-		if [ -f $$dir/Makefile ]; then \
-			echo "Running lock in $$dir"; \
-			(cd $$dir && uv lock); \
-		fi; \
-	done
-
-# Test all projects
-.PHONY: test
-test:
-	@for dir in $(LIBS_DIRS); do \
-		if [ -f $$dir/Makefile ]; then \
-			echo "Running test in $$dir"; \
-			$(MAKE) -C $$dir test; \
-		fi; \
-	done

README.md

@@ -13,7 +13,7 @@
 [![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/)
 
-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.
+Trusted by companies shaping the future of agents – including Klarna, Replit, Elastic, and more – LangGraph is a powerful low-level orchestration framework for building, managing, and deploying long-running, stateful agents. 
 
 ## Get started
 
@@ -73,11 +73,11 @@ While LangGraph can be used standalone, it also integrates seamlessly with any L
 
 - [Guides](https://langchain-ai.github.io/langgraph/how-tos/): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
 - [Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
-- [Examples](https://langchain-ai.github.io/langgraph/tutorials/overview/): Guided examples on getting started with LangGraph.
+- [Examples](https://langchain-ai.github.io/langgraph/tutorials/): Guided examples on getting started with LangGraph.
 - [LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph): Learn the basics of LangGraph in our free, structured course.
 - [Templates](https://langchain-ai.github.io/langgraph/concepts/template_applications/): Pre-built reference apps for common agentic workflows (e.g. ReAct agent, memory, retrieval etc.) that can be cloned and adapted.
-- [Case studies](https://www.langchain.com/built-with-langgraph): Hear how industry leaders use LangGraph to ship AI applications at scale.
+- [Case studies](https://www.langchain.com/built-with-langgraph): Hear how industry leaders use LangGraph to ship powerful, production-ready AI applications.
 
 ## 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/Makefile

@@ -12,30 +12,32 @@ build-prebuilt:
 	# 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; \
+		poetry 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; \
+		poetry run python -m _scripts.third_party_page.get_download_stats --fake stats.yml; \
 		set +x; \
 	fi
-	uv run python -m _scripts.third_party_page.create_third_party_page stats.yml docs/agents/prebuilt.md --language python
+	poetry run python -m _scripts.third_party_page.create_third_party_page stats.yml docs/agents/prebuilt.md --language python
 
 build-docs: build-typedoc build-prebuilt
-	uv run python -m mkdocs build --clean -f mkdocs.yml --strict
+	poetry run python -m mkdocs build --clean -f mkdocs.yml --strict
 
 llms-text:
-	uv run python -m _scripts.generate_llms_text docs/llms-full.txt
+	poetry run python -m _scripts.generate_llms_text docs/llms-full.txt
 
 install-vercel-deps:
-	curl -sL "https://astral.sh/uv/install.sh" | bash -s
-	export PATH="${HOME}/.cargo/bin:${PATH}"
-	uv venv --python 3.11
-	uv sync --all-groups
+	dnf install -y python3.11
+	curl -sSL https://install.python-poetry.org | python3 -
+	poetry self update 1.8.5
+	# don't use vercel's python - it wasn't compiled with sqlite support, and it fails when installing ipython's kernel
+	poetry env use /usr/bin/python3.11
+	poetry install --with docs --with test --no-root
 
 tests:
 	# Run unit tests
-	uv run pytest tests/unit_tests
+	poetry run pytest tests/unit_tests
 
 
 vercel-build-docs: install-vercel-deps
@@ -43,10 +45,10 @@ vercel-build-docs: install-vercel-deps
 
 
 serve-clean-docs: clean-docs
-	uv run python -m mkdocs serve -c -f mkdocs.yml --strict -w ../libs/langgraph
+	poetry run python -m mkdocs serve -c -f mkdocs.yml --strict -w ../libs/langgraph
 
 serve-docs: build-typedoc
-	uv run python -m mkdocs serve -f mkdocs.yml -w ../libs/langgraph  -w ../libs/checkpoint -w ../libs/sdk-py --dirty
+	poetry run python -m mkdocs serve -f mkdocs.yml -w ../libs/langgraph  -w ../libs/checkpoint -w ../libs/sdk-py --dirty
 
 clean-docs:
 	find ./docs -name "*.ipynb" -type f -delete
@@ -54,13 +56,13 @@ clean-docs:
 
 ## Run format against the project documentation.
 format-docs:
-	uv run ruff format docs
-	uv run ruff check --fix docs
+	poetry run ruff format docs
+	poetry run ruff check --fix docs
 
 # Check the docs for linting violations
 lint-docs:
-	uv run ruff format --check docs
-	uv run ruff check docs
+	poetry run ruff format --check docs
+	poetry run ruff check docs
 
 codespell:
 	./codespell_notebooks.sh .

docs/README.md

@@ -3,7 +3,7 @@
 To setup requirements for building docs you can run:
 
 ```bash
-uv sync --group test
+poetry install --with test
 ```
 
 ## Serving documentation locally

docs/_scripts/execute_notebooks.sh

@@ -8,7 +8,7 @@ execute_notebook() {
     file="$1"
     echo "Starting execution of $file"
     start_time=$(date +%s)
-    if ! output=$(time uv run jupyter execute "$file" 2>&1); then
+    if ! output=$(time poetry run jupyter execute "$file" 2>&1); then
         end_time=$(date +%s)
         execution_time=$((end_time - start_time))
         echo "Error in $file. Execution time: $execution_time seconds"

docs/_scripts/generate_llms_text.py

@@ -1,19 +1,10 @@
 """Experimental script to generate consolidated llms text from the docs."""
 
-import asyncio
 import glob
 import os
-from typing import TypedDict, List, Optional
-import pydantic
-import re
-from pydantic import BaseModel, Field
-from langchain_core.rate_limiters import InMemoryRateLimiter
 
-import yaml
-from langchain.chat_models import init_chat_model
 from mkdocs.structure.files import File
 from mkdocs.structure.pages import Page
-from yaml import SafeLoader
 
 from _scripts.notebook_hooks import _on_page_markdown_with_config
 
@@ -22,49 +13,7 @@ HERE = os.path.dirname(os.path.abspath(__file__))
 SOURCE_DIR = os.path.abspath(os.path.join(os.path.dirname(HERE), "docs"))
 
 
-async def convert_ipynb_to_md(file_path: str) -> Optional[str]:
-    """Process a file (markdown or notebook) to markdown format.
-
-    Args:
-        file_path: Path to the file to process
-
-    Returns:
-        Processed markdown content if successful, None otherwise
-    """
-    rel_path = os.path.relpath(file_path, SOURCE_DIR)
-
-    # Create File and Page objects to match mkdocs structure
-    file_obj = File(
-        path=rel_path, src_dir=SOURCE_DIR, dest_dir="", use_directory_urls=True
-    )
-    page = Page(
-        title="",
-        file=file_obj,
-        config={},
-    )
-
-    try:
-        # Read raw content
-        with open(file_path, "r", encoding="utf-8") as f:
-            content = f.read()
-
-        # Convert to markdown without logic to resolve API references
-        processed_content = _on_page_markdown_with_config(
-            content, page, add_api_references=False, remove_base64_images=True
-        )
-        # Remove self-closing img tags <img ... />
-        processed_content = re.sub(r"<img[^>]*/>", "", processed_content)
-        # Remove img tags with content <img ...>...</img>
-        processed_content = re.sub(
-            r"<img[^>]*>.*?</img>", "", processed_content, flags=re.DOTALL
-        )
-        return processed_content
-    except Exception as e:
-        print(f"Error processing file {file_path}: {e}")
-        return None
-
-
-async def generate_full_llms_text(output_file: str) -> None:
+def _make_llms_text(output_file: str) -> str:
     """Generate a consolidated text file from markdown/notebook files for LLM training.
 
     Args:
@@ -72,9 +21,11 @@ async def generate_full_llms_text(output_file: str) -> None:
     """
     # 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)
     )
+    # Add all concepts
     all_files.extend(
         glob.glob(os.path.join(SOURCE_DIR, "concepts/*.md"), recursive=True)
     )
@@ -84,14 +35,30 @@ async def generate_full_llms_text(output_file: str) -> None:
 
     all_content = []
 
-    # Process files concurrently
-    tasks = [convert_ipynb_to_md(file_path) for file_path in all_files]
-    results = await asyncio.gather(*tasks)
+    # Process each file
+    for file_path in all_files:
+        print(f"Processing {file_path}")
+        rel_path = os.path.relpath(file_path, SOURCE_DIR)
 
-    # Combine results with file paths
-    for file_path, processed_content in zip(all_files, results):
+        # Create File and Page objects to match mkdocs structure
+        file_obj = File(
+            path=rel_path, src_dir=SOURCE_DIR, dest_dir="", use_directory_urls=True
+        )
+        page = Page(
+            title="",
+            file=file_obj,
+            config={},
+        )
+
+        # Read raw content
+        with open(file_path, "r", encoding="utf-8") as f:
+            content = f.read()
+
+        # Convert to markdown without logic to resolve API references
+        processed_content = _on_page_markdown_with_config(
+            content, page, add_api_references=False, remove_base64_images=True
+        )
         if processed_content:
-            rel_path = os.path.relpath(file_path, SOURCE_DIR)
             # Add file name
             all_content.append(f"---\n{rel_path}\n---")
             # Add content
@@ -102,168 +69,6 @@ async def generate_full_llms_text(output_file: str) -> None:
         f.write("\n\n".join(all_content))
 
 
-def no_op_constructor(*args):
-    """No-op"""
-
-
-SafeLoader.add_multi_constructor(
-    "tag:yaml.org,2002:python/name",
-    no_op_constructor,
-)
-
-
-class NavItem(TypedDict):
-    title: str
-    url: str
-    hierarchy: tuple[str, ...]
-    description: str
-
-
-def _flatten_nav(
-    nav: list[dict[str, str | list] | str], path: tuple[str, ...] = ()
-) -> list[NavItem]:
-    flat: List[NavItem] = []
-    for item in nav:
-        if isinstance(item, dict):
-            for title, node in item.items():
-                new_path = path + (title,)
-                if isinstance(node, str):
-                    # Leaf page
-                    flat.append(
-                        {
-                            "title": title,
-                            "url": node,
-                            "hierarchy": new_path,
-                            "description": "",
-                        }
-                    )
-                elif isinstance(node, list):
-                    # Dive in, carrying along the updated path
-                    flat.extend(_flatten_nav(node, new_path))
-                else:
-                    raise TypeError(
-                        f"Unexpected node type {type(node)} under {title!r}"
-                    )
-        elif isinstance(item, str):
-            # Bare string entry → use itself as title, and as URL
-            new_path = path + (item,)
-            flat.append(
-                {"title": item, "url": item, "hierarchy": new_path, "description": ""}
-            )
-        else:
-            raise TypeError(f"Unexpected item type {type(item)} in nav")
-    return flat
-
-
-class PageInfo(BaseModel):
-    title: str = Field(description="The title of the page")
-    description: str = Field(
-        description="A short description of the page no longer than 3 sentences "
-        "explaining the kind of content that can be found in the page."
-    )
-
-
-async def process_nav_items(nav_items: list[NavItem]) -> list[NavItem]:
-    """Open the contents of each nav item and come up with a better title and description."""
-    rate_limiter = InMemoryRateLimiter(requests_per_second=10)
-    model = init_chat_model("gpt-4o-mini", temperature=0.0, rate_limiter=rate_limiter)
-    model = model.with_structured_output(PageInfo)
-
-    async def process_single_item(item: NavItem) -> NavItem:
-        path = item["url"]
-        file_path = os.path.join(SOURCE_DIR, path)
-
-        # Process the file content (handles both markdown and notebooks)
-        if path.endswith(".ipynb"):
-            content = await convert_ipynb_to_md(file_path)
-        else:
-            with open(file_path, "r", encoding="utf-8") as f:
-                content = f.read()
-
-        if not content:
-            return item
-
-        # Generate a better title and description
-        response = await model.ainvoke(
-            [
-                {
-                    "role": "system",
-                    "content": "You are a technical documentation writer. "
-                    "You are given a markdown page of documentation. "
-                    "Please come up with an appropriate title and "
-                    "description for the page. The description should "
-                    "be a short summary of the page content that is "
-                    "no longer than 3 sentences.",
-                },
-                {
-                    "role": "user",
-                    "content": "The markdown page is as follows:\n\n" + content,
-                },
-            ]
-        )
-        return {
-            "title": response.title,
-            "url": item["url"],
-            "hierarchy": item["hierarchy"],
-            "description": response.description,
-        }
-
-    # Remove any items that start with http:// or https:// looking only for
-    # local file at this stages.
-    nav_items = [
-        item for item in nav_items if not item["url"].startswith(("http://", "https://"))
-    ]
-    # Process items in parallel
-    tasks = [process_single_item(item) for item in nav_items]
-    new_nav_items = await asyncio.gather(*tasks)
-    return new_nav_items
-
-
-async def generate_nav_links_text(
-    output_file: str, *, replace_links: bool = False
-) -> None:
-    """Generate llms.txt from mkdocs.yaml."""
-    # Get path to mkdocs.yaml relative to this script
-    script_dir = os.path.dirname(os.path.abspath(__file__))
-    mkdocs_path = os.path.join(os.path.dirname(script_dir), "mkdocs.yml")
-
-    # Load and parse yaml
-    with open(mkdocs_path, "r") as f:
-        config = yaml.safe_load(f)
-
-    # Extract nav section
-    nav = config.get("nav", [])
-    flattened = _flatten_nav(nav)
-
-    processed_nav = await process_nav_items(flattened)
-
-    with open(output_file, "w") as f:
-        current_section = None
-        for item in processed_nav:
-            # Get the top-level section (first item in hierarchy)
-            section = item["hierarchy"][0]
-
-            if section not in {"Guides", "Examples", "Resources"}:
-                continue
-
-            # If we're starting a new section, add a heading
-            if section != current_section:
-                f.write(f"\n# {section}\n\n")
-                current_section = section
-
-            title = item["title"]
-            # Process URL based on replace_links flag
-            url = item["url"]
-            if replace_links:
-                # Remove .md extension and ensure single trailing slash
-                url = url.removesuffix(".md")
-                url = url.removesuffix(".ipynb")
-                url = url.rstrip("/") + "/"
-                url = f"https://langchain-ai.github.io/langgraph/{url}"
-
-            f.write(f"- [{title}]({url}): {item['description']}\n")
-
-
 if __name__ == "__main__":
     import argparse
 
@@ -273,23 +78,6 @@ if __name__ == "__main__":
         )
     )
     parser.add_argument("output_file", help="Path to output the consolidated text file")
-    parser.add_argument(
-        "--link-only",
-        action="store_true",
-        help="Only include link references in the output",
-    )
-    parser.add_argument(
-        "--replace-links",
-        action="store_true",
-        help="Replace markdown links with full URLs in the output",
-    )
 
     args = parser.parse_args()
-    if args.link_only:
-        coro = generate_nav_links_text(
-            args.output_file, replace_links=args.replace_links
-        )
-    else:
-        coro = generate_full_llms_text(args.output_file)
-
-    asyncio.run(coro)
+    _make_llms_text(args.output_file)

docs/_scripts/notebook_hooks.py

@@ -1,16 +1,9 @@
-"""mkdocs hooks for adding custom logic to documentation pipeline.
-
-Lifecycle events: https://www.mkdocs.org/dev-guide/plugins/#events
-"""
-
 import logging
 import os
 import posixpath
 import re
 from typing import Any, Dict
 
-from bs4 import BeautifulSoup
-from mkdocs.config.defaults import MkDocsConfig
 from mkdocs.structure.files import Files, File
 from mkdocs.structure.pages import Page
 
@@ -46,7 +39,6 @@ REDIRECT_MAP = {
     "how-tos/configuration.ipynb": "how-tos/graph-api/#add-runtime-configuration",
     "how-tos/node-retries.ipynb": "how-tos/graph-api/#add-retry-policies",
     "how-tos/return-when-recursion-limit-hits.ipynb": "how-tos/graph-api/#impose-a-recursion-limit",
-    "how-tos/async.ipynb": "how-tos/graph-api/#async",
     # memory how-tos
     "how-tos/memory/manage-conversation-history.ipynb": "how-tos/memory.ipynb",
     "how-tos/memory/delete-messages.ipynb": "how-tos/memory.ipynb#delete-messages",
@@ -60,7 +52,6 @@ REDIRECT_MAP = {
     "how-tos/persistence_redis.ipynb": "how-tos/persistence.ipynb#use-in-production",
     "how-tos/subgraph-persistence.ipynb": "how-tos/persistence.ipynb#use-with-subgraphs",
     "how-tos/cross-thread-persistence.ipynb": "how-tos/persistence.ipynb#add-long-term-memory",
-    "cloud/how-tos/copy_threads": "cloud/how-tos/use_threads",
     # tool calling how-tos
     "how-tos/tool-calling-errors.ipynb": "how-tos/tool-calling.ipynb#handle-errors",
     "how-tos/pass-config-to-tools.ipynb": "how-tos/tool-calling.ipynb#access-config",
@@ -76,9 +67,6 @@ REDIRECT_MAP = {
     "cloud/concepts/api.md": "concepts/langgraph_server.md",
     "cloud/concepts/cloud.md": "concepts/langgraph_cloud.md",
     "cloud/faq/studio.md": "concepts/langgraph_studio.md#studio-faqs",
-    "cloud/how-tos/human_in_the_loop_edit_state.md": "cloud/how-tos/add-human-in-the-loop.md",
-    "cloud/how-tos/human_in_the_loop_user_input.md": "cloud/how-tos/add-human-in-the-loop.md",
-    "concepts/platform_architecture.md": "concepts/langgraph_cloud#architecture",
     # cloud streaming redirects
     "cloud/how-tos/stream_values.md": "cloud/how-tos/streaming.md#stream-graph-state",
     "cloud/how-tos/stream_updates.md": "cloud/how-tos/streaming.md#stream-graph-state",
@@ -106,9 +94,8 @@ REDIRECT_MAP = {
     "tutorials/introduction.ipynb": "concepts/why-langgraph.md",
     # deployment redirects
     "how-tos/deploy-self-hosted.md": "cloud/deployment/self_hosted_data_plane.md",
-    "concepts/self_hosted.md": "concepts/langgraph_self_hosted_data_plane.md",
-    # assistant redirects
-    "cloud/how-tos/assistant_versioning.md": "cloud/how-tos/configuration_cloud.md",
+    "concepts/self_hosted.md": "concepts/langgraph_self_hosted_data_plane.md"
+
 }
 
 
@@ -298,7 +285,7 @@ Redirecting...
 """
 
 
-def _write_html(site_dir, old_path, new_path):
+def write_html(site_dir, old_path, new_path):
     """Write an HTML file in the site_dir with a meta redirect to the new page"""
     # Determine all relevant paths
     old_path_abs = os.path.join(site_dir, old_path)
@@ -314,52 +301,6 @@ def _write_html(site_dir, old_path, new_path):
         f.write(content)
 
 
-def _inject_gtm(html: str) -> str:
-    """Inject Google Tag Manager code into the HTML.
-
-    Code to inject Google Tag Manager noscript tag immediately after <body>.
-
-    This is done via hooks rather than via a template because the MkDocs material
-    theme does not seem to allow placing the code immediately after the <body> tag
-    without modifying the template files directly.
-
-    Args:
-        html: The HTML content to modify.
-
-    Returns:
-        The modified HTML content with GTM code injected.
-    """
-    # Code was copied from Google Tag Manager setup instructions.
-    gtm_code = """
-<!-- Google Tag Manager (noscript) -->
-<noscript><iframe src="https://www.googletagmanager.com/ns.html?id=GTM-T35S4S46"
-height="0" width="0" style="display:none;visibility:hidden"></iframe></noscript>
-<!-- End Google Tag Manager (noscript) -->
-"""
-    soup = BeautifulSoup(html, "html.parser")
-    body = soup.body
-    if body:
-        # Insert the GTM code as raw HTML at the top of <body>
-        body.insert(0, BeautifulSoup(gtm_code, "html.parser"))
-        return str(soup)
-    else:
-        return html  # fallback if no <body> found
-
-
-def on_post_page(output: str, page: Page, config: MkDocsConfig) -> str:
-    """Inject Google Tag Manager noscript tag immediately after <body>.
-
-    Args:
-        output: The HTML output of the page.
-        page: The page instance.
-        config: The MkDocs configuration object.
-
-    Returns:
-        modified HTML output with GTM code injected.
-    """
-    return _inject_gtm(output)
-
-
 # Create HTML files for redirects after site dir has been built
 def on_post_build(config):
     use_directory_urls = config.get("use_directory_urls")
@@ -376,4 +317,4 @@ def on_post_build(config):
             + hash
             + suffix
         )
-        _write_html(config["site_dir"], old_html_path, new_html_path)
+        write_html(config["site_dir"], old_html_path, new_html_path)

docs/_scripts/prepare_notebooks_for_ci.py

@@ -5,7 +5,6 @@ import os
 import json
 import click
 import nbformat
-import re
 
 logger = logging.getLogger(__name__)
 NOTEBOOK_DIRS = ("docs/how-tos","docs/tutorials")
@@ -89,10 +88,12 @@ def has_blocklisted_command(code: str, metadata: dict) -> bool:
             return True
     return False
 
-MERMAID_PATTERN = re.compile(r'display\(Image\((\w+)\.get_graph\(\)\.draw_mermaid_png\(\)\)\)')
-
 def remove_mermaid(code: str) -> str:
-    return MERMAID_PATTERN.sub('print()', code)
+    return code.replace(
+        "display(Image(graph.get_graph().draw_mermaid_png()))",
+        # replace with a dummy statement
+        "print()"
+    )
 
 
 def add_vcr_to_notebook(
@@ -107,8 +108,6 @@ def add_vcr_to_notebook(
             continue
 
         lines = cell.source.splitlines()
-        # remove the special tag for hidden cells
-        lines = [line for line in lines if not line.strip().startswith("# hide-cell")]
         # skip if empty cell
         if not lines:
             continue
@@ -196,11 +195,6 @@ def remove_mermaid_from_notebook(notebook: nbformat.NotebookNode) -> nbformat.No
             continue
 
         cell.source = remove_mermaid(cell.source)
-
-        # skip the cell entirely if it contains PYPPETEER
-        if "PYPPETEER" in cell.source:
-            cell.source = ""
-
     return notebook
 
 

docs/cassettes/graph-api_04924627-9326-438b-aa52-91cea76f4477.msgpack.zlib

@@ -1 +0,0 @@
-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

docs/cassettes/graph-api_a6033c2a-3b56-46f5-9c3f-79310e31e545.msgpack.zlib

@@ -1 +0,0 @@
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docs/cassettes/time-travel_9a92d3da-62e2-45a2-8545-e4f6a64e0ffe.msgpack.zlib

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docs/cassettes/time-travel_cfd140f0-a5a6-4697-8115-322242f197b5.msgpack.zlib

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docs/cassettes/time-travel_e986f94f-706f-4b6f-b3c4-f95483b9e9b8.msgpack.zlib

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docs/cassettes/time-travel_f0bab935-6d9b-4cfd-afe8-bfcf4638847e.msgpack.zlib

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docs/docs/agents/agents.md

@@ -15,7 +15,7 @@ This guide shows you how to set up and use LangGraph's **prebuilt**, **reusable*
 
 Before you start this tutorial, ensure you have the following:
 
-- An [Anthropic](https://console.anthropic.com/settings/keys) API key 
+- An [Anthropic](https://console.anthropic.com/settings/admin-keys) API key 
 
 ## 1. Install dependencies
 

docs/docs/agents/deployment.md

@@ -89,4 +89,4 @@ LangGraph Studio Web is a specialized UI that you can connect to LangGraph API s
 
 ## Deployment
 
-Once your LangGraph app is running locally, you can deploy it using LangGraph Platform. Refer to the [deployment options guide](../tutorials/deployment.md) for detailed instructions on all supported deployment models.
+Once your LangGraph app is running locally, you can deploy it using LangGraph Cloud or self-hosted options. Refer to the [deployment options guide](../tutorials/deployment.md) for detailed instructions on all supported deployment models.

docs/docs/agents/human-in-the-loop.md

@@ -106,7 +106,7 @@ for chunk in agent.stream(
     print("\n")
 ```
 
-1. The [`interrupt` function][langgraph.types.interrupt] is used in conjunction with the [`Command`][langgraph.types.Command] object to resume the graph with a value provided by the human.
+1. The [`interrupt` function][langgraph.types.interrupt] is used in conjunction with the [`Command`](../reference/types.md#langgraph.types.Command) object to resume the graph with a value provided by the human.
 
 ## Using with Agent Inbox
 

docs/docs/agents/mcp.md

@@ -29,7 +29,7 @@ from langchain_mcp_adapters.client import MultiServerMCPClient
 from langgraph.prebuilt import create_react_agent
 
 # highlight-next-line
-client = MultiServerMCPClient(
+async with MultiServerMCPClient(
     {
         "math": {
             "command": "python",
@@ -38,25 +38,23 @@ client = MultiServerMCPClient(
             "transport": "stdio",
         },
         "weather": {
-            # Ensure you start your weather server on port 8000
-            "url": "http://localhost:8000/mcp",
-            "transport": "streamable_http",
+            # Ensure your start your weather server on port 8000
+            "url": "http://localhost:8000/sse",
+            "transport": "sse",
         }
     }
-)
-# highlight-next-line
-tools = await client.get_tools()
-agent = create_react_agent(
-    "anthropic:claude-3-7-sonnet-latest",
-    # highlight-next-line
-    tools
-)
-math_response = await agent.ainvoke(
-    {"messages": [{"role": "user", "content": "what's (3 + 5) x 12?"}]}
-)
-weather_response = await agent.ainvoke(
-    {"messages": [{"role": "user", "content": "what is the weather in nyc?"}]}
-)
+) as client:
+    agent = create_react_agent(
+        "anthropic:claude-3-7-sonnet-latest",
+        # highlight-next-line
+        client.get_tools()
+    )
+    math_response = await agent.ainvoke(
+        {"messages": [{"role": "user", "content": "what's (3 + 5) x 12?"}]}
+    )
+    weather_response = await agent.ainvoke(
+        {"messages": [{"role": "user", "content": "what is the weather in nyc?"}]}
+    )
 ```
 
 ## Custom MCP servers
@@ -89,7 +87,7 @@ if __name__ == "__main__":
     mcp.run(transport="stdio")
 ```
 
-```python title="Example Weather Server (Streamable HTTP transport)"
+```python title="Example Weather Server (SSE transport)"
 from mcp.server.fastmcp import FastMCP
 
 mcp = FastMCP("Weather")
@@ -100,7 +98,7 @@ async def get_weather(location: str) -> str:
     return "It's always sunny in New York"
 
 if __name__ == "__main__":
-    mcp.run(transport="streamable-http")
+    mcp.run(transport="sse")
 ```
 
 ## Additional resources

docs/docs/agents/memory.md

@@ -82,13 +82,13 @@ ny_response = agent.invoke(
 ```
 
 1. The `InMemorySaver` is a checkpointer that stores the agent's state in memory. In a production setting, you would typically use a database or other persistent storage. Please review the [checkpointer documentation](../reference/checkpoints.md) for more options. If you're deploying with **LangGraph Platform**, the platform will provide a production-ready checkpointer for you.
-2. The `checkpointer` is passed to the agent. This enables the agent to persist its state across invocations.
+2. The `checkpointer` is passed to the agent. This enables the agent to persist its state across invocations. Please note that 
 3. A unique `thread_id` is provided in the config. This ID is used to identify the conversation session. The value is controlled by the user and can be any string.
 4. The agent will continue the conversation using the same `thread_id`. This will allow the agent to infer that the user is asking specifically about the **weather** in New York. 
 
 When the agent is invoked the second time with the same `thread_id`, the original message history from the first conversation is automatically included, allowing the agent to infer that the user is asking specifically about the **weather** in New York.
 
-!!! Note "LangGraph Platform provides a production-ready checkpointer"
+!!! Note "LangGraph Platform providers a production-ready checkpointer"
 
     If you're using [LangGraph Platform](./deployment.md), during deployment your checkpointer will be automatically configured to use a production-ready database.
 
@@ -294,7 +294,7 @@ agent.invoke(
 )
 ```
 
-For more details, see [how to update state from tools](../how-tos/tool-calling.ipynb#update).
+For more details, see [how to update state from tools](../how-tos/update-state-from-tools.ipynb).
 
 ## Long-term memory
 
@@ -302,7 +302,7 @@ Use long-term memory to store user-specific or application-specific data across
 
 To use long-term memory, you need to:
 
-1. [Configure a store](../how-tos/persistence.ipynb#add-long-term-memory) to persist data across invocations.
+1. [Configure a store](../how-tos/cross-thread-persistence.ipynb) to persist data across invocations.
 2. Use the [`get_store`][langgraph.config.get_store] function to access the store from within tools or prompts.
 
 ### Read { #read-long-term }

docs/docs/agents/models.md

@@ -23,182 +23,29 @@ Compatible models can be found in the [LangChain integrations directory](https:/
 
 You can configure an agent with a model name string:
 
-=== "OpenAI"
-
-    ```python
-    import os
-    from langgraph.prebuilt import create_react_agent
-
-    os.environ["OPENAI_API_KEY"] = "sk-..."
-
-    agent = create_react_agent(
-        # highlight-next-line
-        model="openai:gpt-4.1",
-        # other parameters
-    )
-    ```
-
-=== "Anthropic"
-
-    ```python
-    import os
-    from langgraph.prebuilt import create_react_agent
-
-    os.environ["ANTHROPIC_API_KEY"] = "sk-..."
-
-    agent = create_react_agent(
-        # highlight-next-line
-        model="anthropic:claude-3-7-sonnet-latest",
-        # other parameters
-    )
-    ```
-
-=== "Azure"
-
-    ```python
-    import os
-    from langgraph.prebuilt import create_react_agent
-
-    os.environ["AZURE_OPENAI_API_KEY"] = "..."
-    os.environ["AZURE_OPENAI_ENDPOINT"] = "..."
-    os.environ["OPENAI_API_VERSION"] = "2025-03-01-preview"
-
-    agent = create_react_agent(
-        # highlight-next-line
-        model="azure_openai:gpt-4.1",
-        # other parameters
-    )
-    ```
-
-=== "Google Gemini"
-
-    ```python
-    import os
-    from langgraph.prebuilt import create_react_agent
-
-    os.environ["GOOGLE_API_KEY"] = "..."
-
-    agent = create_react_agent(
-        # highlight-next-line
-        model="google_genai:gemini-2.0-flash",
-        # other parameters
-    )
-    ```
-
-=== "AWS Bedrock"
-
-    ```python
-    from langgraph.prebuilt import create_react_agent
-
-    # Follow the steps here to configure your credentials:
-    # https://docs.aws.amazon.com/bedrock/latest/userguide/getting-started.html
-
-    agent = create_react_agent(
-        # highlight-next-line
-        model="bedrock_converse:anthropic.claude-3-5-sonnet-20240620-v1:0",
-        # other parameters
-    )
-    ```
+```python
+from langgraph.prebuilt import create_react_agent
 
+agent = create_react_agent(
+    # highlight-next-line
+    model="anthropic:claude-3-7-sonnet-latest",
+    # other parameters
+)
+```
 
 ## Using `init_chat_model`
 
 The [`init_chat_model`](https://python.langchain.com/docs/how_to/chat_models_universal_init/) utility simplifies model initialization with configurable parameters:
 
-=== "OpenAI"
-
-    ```
-    pip install -U "langchain[openai]"
-    ```
-    ```python
-    import os
-    from langchain.chat_models import init_chat_model
-
-    os.environ["OPENAI_API_KEY"] = "sk-..."
-
-    model = init_chat_model(
-        "openai:gpt-4.1",
-        temperature=0,
-        # other parameters
-    )
-    ```
-
-=== "Anthropic"
-
-    ```
-    pip install -U "langchain[anthropic]"
-    ```
-    ```python
-    import os
-    from langchain.chat_models import init_chat_model
-
-    os.environ["ANTHROPIC_API_KEY"] = "sk-..."
-
-    model = init_chat_model(
-        "anthropic:claude-3-5-sonnet-latest",
-        temperature=0,
-        # other parameters
-    )
-    ```
-
-=== "Azure"
-
-    ```
-    pip install -U "langchain[openai]"
-    ```
-    ```python
-    import os
-    from langchain.chat_models import init_chat_model
-
-    os.environ["AZURE_OPENAI_API_KEY"] = "..."
-    os.environ["AZURE_OPENAI_ENDPOINT"] = "..."
-    os.environ["OPENAI_API_VERSION"] = "2025-03-01-preview"
-
-    model = init_chat_model(
-        "azure_openai:gpt-4.1",
-        azure_deployment=os.environ["AZURE_OPENAI_DEPLOYMENT_NAME"],
-        temperature=0,
-        # other parameters
-    )
-    ```
-
-=== "Google Gemini"
-
-    ```
-    pip install -U "langchain[google-genai]"
-    ```
-    ```python
-    import os
-    from langchain.chat_models import init_chat_model
-
-    os.environ["GOOGLE_API_KEY"] = "..."
-
-    model = init_chat_model(
-        "google_genai:gemini-2.0-flash",
-        temperature=0,
-        # other parameters
-    )
-    ```
-
-=== "AWS Bedrock"
-
-    ```
-    pip install -U "langchain[aws]"
-    ```
-    ```python
-    from langchain.chat_models import init_chat_model
-
-    # Follow the steps here to configure your credentials:
-    # https://docs.aws.amazon.com/bedrock/latest/userguide/getting-started.html
-
-    model = init_chat_model(
-        "anthropic.claude-3-5-sonnet-20240620-v1:0",
-        model_provider="bedrock_converse",
-        temperature=0,
-        # other parameters
-    )
-    ```
+```python
+from langchain.chat_models import init_chat_model
 
+model = init_chat_model(
+    "anthropic:claude-3-7-sonnet-latest",
+    temperature=0,
+    max_tokens=2048
+)
+```
 
 Refer to the [API reference](https://python.langchain.com/api_reference/langchain/chat_models/langchain.chat_models.base.init_chat_model.html) for advanced options.
 

docs/docs/agents/multi-agent.md

@@ -9,7 +9,7 @@ hide:
 
 # Multi-agent
 
-A single agent might struggle if it needs to specialize in multiple domains or manage many tools. To tackle this, you can break your agent into smaller, independent agents and compose them into a [multi-agent system](../concepts/multi_agent.md).
+A single agent might struggle if it needs to specialize in multiple domains or manage many tools. To tackle this, you can break your agent into smaller, independent agents and composing them into a [multi-agent system](../concepts/multi_agent.md).
 
 In multi-agent systems, agents need to communicate between each other. They do so via [handoffs](#handoffs) — a primitive that describes which agent to hand control to and the payload to send to that agent.
 

docs/docs/agents/overview.md

@@ -53,139 +53,3 @@ The high-level components are organized into several packages, each with a speci
 | `langmem`                                  | Agent memory management: [**short-term and long-term**](./memory.md)        | `pip install -U langmem`                |
 | `agentevals`                               | Utilities to [**evaluate agent performance**](./evals.md)                   | `pip install -U agentevals`             |
 
-## Visualize an agent graph
-
-Use the following tool to visualize the graph generated by
-[`create_react_agent`][langgraph.prebuilt.chat_agent_executor.create_react_agent]
-and to view an outline of the corresponding code.
-It allows you to explore the infrastructure of the agent as defined by the presence of:
-
-* [`tools`](../agents/tools.md): A list of tools (functions, APIs, or other callable objects) that the agent can use to perform tasks.
-* [`pre_model_hook`](../how-tos/create-react-agent-manage-message-history.ipynb): A function that is called before the model is invoked. It can be used to condense messages or perform other preprocessing tasks.
-* `post_model_hook`: A function that is called after the model is invoked. It can be used to implement guardrails, human-in-the-loop flows, or other postprocessing tasks.
-* [`response_format`](../agents/agents.md#6-configure-structured-output): A data structure used to constrain the type of the final output, e.g., a `pydantic` `BaseModel`.
-
-<div class="agent-layout">
-  <div class="agent-graph-features-container">
-    <div class="agent-graph-features">
-      <h3 class="agent-section-title">Features</h3>
-      <label><input type="checkbox" id="tools" checked> <code>tools</code></label>
-      <label><input type="checkbox" id="pre_model_hook"> <code>pre_model_hook</code></label>
-      <label><input type="checkbox" id="post_model_hook"> <code>post_model_hook</code></label>
-      <label><input type="checkbox" id="response_format"> <code>response_format</code></label>
-    </div>
-  </div>
-
-  <div class="agent-graph-container">
-    <h3 class="agent-section-title">Graph</h3>
-    <img id="agent-graph-img" src="../assets/react_agent_graphs/0001.svg" alt="graph image" style="max-width: 100%;"/>
-  </div>
-</div>
-
-
-The following code snippet shows how to create the above agent (and underlying graph) with
-[`create_react_agent`][langgraph.prebuilt.chat_agent_executor.create_react_agent]:
-
-<div class="language-python">
-  <pre><code id="agent-code" class="language-python"></code></pre>
-</div>
-
-
-<script>
-function getCheckedValue(id) {
-  return document.getElementById(id).checked ? "1" : "0";
-}
-
-function getKey() {
-  return [
-    getCheckedValue("response_format"),
-    getCheckedValue("post_model_hook"),
-    getCheckedValue("pre_model_hook"),
-    getCheckedValue("tools")
-  ].join("");
-}
-
-function generateCodeSnippet({ tools, pre, post, response }) {
-  const lines = [
-    "from langgraph.prebuilt import create_react_agent",
-    "from langchain_openai import ChatOpenAI"
-  ];
-
-  if (response) lines.push("from pydantic import BaseModel");
-
-  lines.push("", 'model = ChatOpenAI("o4-mini")', "");
-
-  if (tools) {
-    lines.push(
-      "def tool() -> None:",
-      '    """Testing tool."""',
-      "    ...",
-      ""
-    );
-  }
-
-  if (pre) {
-    lines.push(
-      "def pre_model_hook() -> None:",
-      '    """Pre-model hook."""',
-      "    ...",
-      ""
-    );
-  }
-
-  if (post) {
-    lines.push(
-      "def post_model_hook() -> None:",
-      '    """Post-model hook."""',
-      "    ...",
-      ""
-    );
-  }
-
-  if (response) {
-    lines.push(
-      "class ResponseFormat(BaseModel):",
-      '    """Response format for the agent."""',
-      "    result: str",
-      ""
-    );
-  }
-
-  lines.push("agent = create_react_agent(");
-  lines.push("    model,");
-
-  if (tools) lines.push("    tools=[tool],");
-  if (pre) lines.push("    pre_model_hook=pre_model_hook,");
-  if (post) lines.push("    post_model_hook=post_model_hook,");
-  if (response) lines.push("    response_format=ResponseFormat,");
-
-  lines.push(")", "", "agent.get_graph().draw_mermaid_png()");
-
-  return lines.join("\n");
-}
-
-async function render() {
-  const key = getKey();
-  document.getElementById("agent-graph-img").src = `../assets/react_agent_graphs/${key}.svg`;
-
-  const state = {
-    tools: document.getElementById("tools").checked,
-    pre: document.getElementById("pre_model_hook").checked,
-    post: document.getElementById("post_model_hook").checked,
-    response: document.getElementById("response_format").checked
-  };
-
-  document.getElementById("agent-code").textContent = generateCodeSnippet(state);
-}
-
-function initializeWidget() {
-  render(); // no need for `await` here
-  document.querySelectorAll(".agent-graph-features input").forEach((input) => {
-    input.addEventListener("change", render);
-  });
-}
-
-// Init for both full reload and SPA nav (used by MkDocs Material)
-window.addEventListener("DOMContentLoaded", initializeWidget);
-document$.subscribe(initializeWidget);
-</script>

docs/docs/agents/run_agents.md

@@ -10,7 +10,7 @@ hide:
 # Running agents
 
 
-Agents support both synchronous and asynchronous execution using either `.invoke()` / `await .ainvoke()` for full responses, or `.stream()` / `.astream()` for **incremental** [streaming](streaming.md) output. This section explains how to provide input, interpret output, enable streaming, and control execution limits.
+Agents support both synchronous and asynchronous execution using either `.invoke()` / `await .invoke()` for full responses, or `.stream()` / `.astream()` for **incremental** [streaming](streaming.md) output. This section explains how to provide input, interpret output, enable streaming, and control execution limits.
 
 
 ## Basic usage
@@ -18,7 +18,7 @@ Agents support both synchronous and asynchronous execution using either `.invoke
 Agents can be executed in two primary modes:
 
 - **Synchronous** using `.invoke()` or `.stream()`
-- **Asynchronous** using `await .ainvoke()` or `async for` with `.astream()`
+- **Asynchronous** using `await .invoke()` or `async for` with `.astream()`
 
 === "Sync invocation"
     ```python

docs/docs/agents/tools.md

@@ -280,21 +280,7 @@ LangGraph allows access to short-term and long-term memory from tools. See [Memo
 
 ## Prebuilt tools
 
-You can use prebuilt tools from model providers by passing a dictionary with tool specs to the `tools` parameter of `create_react_agent`. For example, to use the `web_search_preview` tool from OpenAI:
-
-```python
-from langgraph.prebuilt import create_react_agent
-
-agent = create_react_agent(
-    model="openai:gpt-4o-mini", 
-    tools=[{"type": "web_search_preview"}]
-)
-response = agent.invoke(
-    {"messages": ["What was a positive news story from today?"]}
-)
-```
-
-Additionally, LangChain supports a wide range of prebuilt tool integrations for interacting with APIs, databases, file systems, web data, and more. These tools extend the functionality of agents and enable rapid development.
+LangChain supports a wide range of prebuilt tool integrations for interacting with APIs, databases, file systems, web data, and more. These tools extend the functionality of agents and enable rapid development.
 
 You can browse the full list of available integrations in the [LangChain integrations directory](https://python.langchain.com/docs/integrations/tools/).
 

docs/docs/agents/ui.md

@@ -13,7 +13,7 @@ You can use a prebuilt chat UI for interacting with any LangGraph agent through
 
 ## Run agent in UI
 
-First, set up LangGraph API server [locally](./deployment.md#launch-langgraph-server-locally) or deploy your agent on [LangGraph Platform](https://langchain-ai.github.io/langgraph/cloud/quick_start/).
+First, set up LangGraph API server [locally](./deployment.md#launch-langgraph-server-locally) or deploy your agent on [LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/quick_start/).
 
 Then, navigate to [Agent Chat UI](https://agentchat.vercel.app), or clone the repository and [run the dev server locally](https://github.com/langchain-ai/agent-chat-ui?tab=readme-ov-file#setup):
 

docs/docs/assets/react-agent-graphs.json

@@ -1,19 +0,0 @@
-{
-    "0000": "graph TD;\n\t__start__ --> agent;\n\tagent --> __end__;",
-    "0001": "graph TD;\n\t__start__ --> agent;\n\tagent -.-> __end__;\n\tagent -.-> tools;\n\ttools --> agent;",
-    "0010": "graph TD;\n\t__start__ --> pre_model_hook;\n\tpre_model_hook --> agent;\n\tagent --> __end__;",
-    "0011": "graph TD;\n\t__start__ --> pre_model_hook;\n\tagent -.-> __end__;\n\tagent -.-> tools;\n\tpre_model_hook --> agent;\n\ttools --> pre_model_hook;",
-    "0100": "graph TD;\n\t__start__ --> agent;\n\tagent --> post_model_hook;\n\tpost_model_hook --> __end__;",
-    "0101": "graph TD;\n\t__start__ --> agent;\n\tagent --> post_model_hook;\n\tpost_model_hook -.-> __end__;\n\tpost_model_hook -.-> agent;\n\tpost_model_hook -.-> tools;\n\ttools --> agent;",
-    "0110": "graph TD;\n\t__start__ --> pre_model_hook;\n\tagent --> post_model_hook;\n\tpre_model_hook --> agent;\n\tpost_model_hook --> __end__;",
-    "0111": "graph TD;\n\t__start__ --> pre_model_hook;\n\tagent --> post_model_hook;\n\tpost_model_hook -.-> __end__;\n\tpost_model_hook -.-> pre_model_hook;\n\tpost_model_hook -.-> tools;\n\tpre_model_hook --> agent;\n\ttools --> pre_model_hook;",
-    "1000": "graph TD;\n\t__start__ --> agent;\n\tagent --> generate_structured_response;\n\tgenerate_structured_response --> __end__;",
-    "1001": "graph TD;\n\t__start__ --> agent;\n\tagent -.-> generate_structured_response;\n\tagent -.-> tools;\n\ttools --> agent;\n\tgenerate_structured_response --> __end__;",
-    "1010": "graph TD;\n\t__start__ --> pre_model_hook;\n\tagent --> generate_structured_response;\n\tpre_model_hook --> agent;\n\tgenerate_structured_response --> __end__;",
-    "1011": "graph TD;\n\t__start__ --> pre_model_hook;\n\tagent -.-> generate_structured_response;\n\tagent -.-> tools;\n\tpre_model_hook --> agent;\n\ttools --> pre_model_hook;\n\tgenerate_structured_response --> __end__;",
-    "1100": "graph TD;\n\t__start__ --> agent;\n\tagent --> post_model_hook;\n\tpost_model_hook --> generate_structured_response;\n\tgenerate_structured_response --> __end__;",
-    "1101": "graph TD;\n\t__start__ --> agent;\n\tagent --> post_model_hook;\n\tpost_model_hook -.-> agent;\n\tpost_model_hook -.-> generate_structured_response;\n\tpost_model_hook -.-> tools;\n\ttools --> agent;\n\tgenerate_structured_response --> __end__;",
-    "1110": "graph TD;\n\t__start__ --> pre_model_hook;\n\tagent --> post_model_hook;\n\tpost_model_hook --> generate_structured_response;\n\tpre_model_hook --> agent;\n\tgenerate_structured_response --> __end__;",
-    "1111": "graph TD;\n\t__start__ --> pre_model_hook;\n\tagent --> post_model_hook;\n\tpost_model_hook -.-> generate_structured_response;\n\tpost_model_hook -.-> pre_model_hook;\n\tpost_model_hook -.-> tools;\n\tpre_model_hook --> agent;\n\ttools --> pre_model_hook;\n\tgenerate_structured_response --> __end__;"
-}
-  

docs/docs/cloud/concepts/cron_jobs.md

@@ -5,11 +5,11 @@ There are many situations in which it is useful to run an assistant on a schedul
 For example, say that you're building an assistant that runs daily and sends an email summary
 of the day's news. You could use a cron job to run the assistant every day at 8:00 PM.
 
-LangGraph Platform supports cron jobs, which run on a user-defined schedule. The user specifies a schedule, an assistant, and some input. After that, on the specified schedule, the server will:
+LangGraph Cloud supports cron jobs, which run on a user-defined schedule. The user specifies a schedule, an assistant, and some input. After that, on the specified schedule, the server will:
 
 - Create a new thread with the specified assistant
 - Send the specified input to that thread
 
 Note that this sends the same input to the thread every time. See the [how-to guide](../../cloud/how-tos/cron_jobs.md) for creating cron jobs.
 
-The LangGraph Platform API provides several endpoints for creating and managing cron jobs. See the [API reference](../../cloud/reference/api/api_ref.html#tag/runscreate/POST/threads/{thread_id}/runs/crons) for more details.
+The LangGraph Cloud API provides several endpoints for creating and managing cron jobs. See the [API reference](../../cloud/reference/api/api_ref.html#tag/runscreate/POST/threads/{thread_id}/runs/crons) for more details.

docs/docs/cloud/concepts/runs.md

@@ -2,4 +2,4 @@
 
 A run is an invocation of an [assistant](../../concepts/assistants.md). Each run may have its own input, configuration, and metadata, which may affect execution and output of the underlying graph. A run can optionally be executed on a [thread](./threads.md).
 
-The LangGraph Platform API provides several endpoints for creating and managing runs. See the [API reference](../../cloud/reference/api/api_ref.html#tag/thread-runs/) for more details.
+The LangGraph Cloud API provides several endpoints for creating and managing runs. See the [API reference](../../cloud/reference/api/api_ref.html#tag/thread-runs/) for more details.

docs/docs/cloud/concepts/threads.md

@@ -1,12 +1,11 @@
 # Threads
 
-A thread contains the accumulated state of a sequence of [runs](./runs.md). When a run is executed, the [state](../../concepts/low_level.md#state) of the underlying graph of the assistant will be persisted to the thread.
+A thread contains the accumulated state of a sequence of [runs](./runs.md). If a run is executed on a thread, then the [state](../../concepts/low_level.md#state) of the underlying graph of the assistant will be persisted to the thread.
 
 A thread's current and historical state can be retrieved. To persist state, a thread must be created prior to executing a run.
 
-The state of a thread at a particular point in time is called a [checkpoint](../../concepts/persistence.md#checkpoints). Checkpoints are persisted and can be used to restore the state of a thread at a later time.
+The state of a thread at a particular point in time is called a [checkpoint](../../concepts/persistence.md#checkpoints). Checkpoints can be used to restore the state of a thread at a later time.
 
-## Learn more
+For more on threads and checkpoints, see this section of the [LangGraph conceptual guide](../../concepts/persistence.md).
 
-* For more on threads and checkpoints, see this section of the [LangGraph conceptual guide](../../concepts/persistence.md).
-* The LangGraph Platform API provides several endpoints for creating and managing threads and thread state. See the [API reference](../../cloud/reference/api/api_ref.html#tag/threads) for more details.
+The LangGraph Cloud API provides several endpoints for creating and managing threads and thread state. See the [API reference](../../cloud/reference/api/api_ref.html#tag/threads) for more details.

docs/docs/cloud/concepts/webhooks.md

@@ -1,7 +1,7 @@
 # Webhooks
 
-Webhooks enable event-driven communication from your LangGraph Platform application to external services. For example, you may want to issue an update to a separate service once an API call to LangGraph Platform has finished running.
+Webhooks enable event-driven communication from your LangGraph Cloud application to external services. For example, you may want to issue an update to a separate service once an API call to LangGraph Cloud has finished running.
 
-Many LangGraph Platform endpoints accept a `webhook` parameter. If this parameter is specified by an endpoint that can accept POST requests, LangGraph Platform will send a request at the completion of a run.
+Many LangGraph Cloud endpoints accept a `webhook` parameter. If this parameter is specified by a an endpoint that can accept POST requests, LangGraph Cloud will send a request at the completion of a run.
 
 See the corresponding [how-to guide](../../cloud/how-tos/webhooks.md) for more detail.

docs/docs/cloud/deployment/cloud.md

@@ -4,14 +4,14 @@ Before deploying, review the [conceptual guide for the Cloud SaaS](../../concept
 
 ## Prerequisites
 
-1. LangGraph Platform applications are deployed from GitHub repositories. Configure and upload a LangGraph Platform application to a GitHub repository in order to deploy it to LangGraph Platform.
-1. [Verify that the LangGraph API runs locally](../../tutorials/langgraph-platform/local-server.md). If the API does not run successfully (i.e. `langgraph dev`), deploying to LangGraph Platform will fail as well.
+1. LangGraph Cloud applications are deployed from GitHub repositories. Configure and upload a LangGraph Cloud application to a GitHub repository in order to deploy it to LangGraph Cloud.
+1. [Verify that the LangGraph API runs locally](../../tutorials/langgraph-platform/local-server.md). If the API does not run successfully (i.e. `langgraph dev`), deploying to LangGraph Cloud will fail as well.
 
 ## Create New Deployment
 
 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
 
-1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Platform deployments.
+1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Cloud deployments.
 1. In the top-right corner, select `+ New Deployment` to create a new deployment.
 1. In the `Create New Deployment` panel, fill out the required fields.
     1. `Deployment details`
@@ -38,7 +38,7 @@ When [creating a new deployment](#create-new-deployment), a new revision is crea
 
 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
 
-1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Platform deployments.
+1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Cloud deployments.
 1. Select an existing deployment to create a new revision for.
 1. In the `Deployment` view, in the top-right corner, select `+ New Revision`.
 1. In the `New Revision` modal, fill out the required fields.
@@ -62,15 +62,6 @@ Starting from the `LangGraph Platform` view...
 1. In the panel, select the `Server` tab to view server logs for the revision. Server logs are only available after a revision has been deployed.
 1. Within the `Server` tab, adjust the date/time range picker as needed. By default, the date/time range picker is set to the `Last 7 days`.
 
-## View Deployment Metrics
-
-Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
-
-1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Platform deployments.
-1. Select an existing deployment to monitor.
-1. Select the `Monitoring` tab to view the deployment metrics. See a list of [all available metrics](../../concepts/langgraph_control_plane.md#monitoring).
-1. Within the `Monitoring` tab, use the date/time range picker as needed. By default, the date/time range picker is set to the `Last 15 minutes`.
-
 ## Interrupt Revision
 
 Interrupting a revision will stop deployment of the revision.
@@ -88,7 +79,7 @@ Starting from the `LangGraph Platform` view...
 
 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
 
-1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Platform deployments.
+1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Cloud deployments.
 1. Select the menu icon (three dots) on the right-hand side of the row for the desired deployment and select `Delete`.
 1. A `Confirmation` modal will appear. Select `Delete`.
 

docs/docs/cloud/deployment/custom_docker.md

@@ -16,4 +16,4 @@ Users can add an array of additional lines to add to the Dockerfile following th
 }
 ```
 
-This would install the system packages required to use Pillow if we were working with `jpeg` or `png` image formats. 
+This would install the system packages required to use Pillow if we were working with `jpeq` or `png` image formats. 

docs/docs/cloud/deployment/self_hosted_control_plane.md

@@ -2,8 +2,8 @@
 
 Before deploying, review the [conceptual guide for the Self-Hosted Control Plane](../../concepts/langgraph_self_hosted_control_plane.md) deployment option.
 
-!!! info "Important"
-    The Self-Hosted Control Plane deployment option is currently in beta stage and requires an [Enterprise](../../concepts/plans.md) plan.
+!!! important "Beta"
+    The Self-Hosted Control Plane deployment option is currently in beta stage.
 
 ## Prerequisites
 
@@ -30,17 +30,18 @@ Before deploying, review the [conceptual guide for the Self-Hosted Control Plane
     1. `LangGraphPlatform CRD`: A CRD for LangGraph Platform deployments. This contains the spec for managing an instance of a LangGraph platform deployment.
     1. `operator`: This operator handles changes to your LangGraph Platform CRDs.
     1. `host-backend`: This is the [control plane](../../concepts/langgraph_control_plane.md).
-1. Two additional images will be used by the chart. Use the images that are specified in the latest release.
+1. Two additional images will be used by the chart.
 
         hostBackendImage:
           repository: "docker.io/langchain/hosted-langserve-backend"
           pullPolicy: IfNotPresent
+          tag: "0.9.80"
         operatorImage:
           repository: "docker.io/langchain/langgraph-operator"
           pullPolicy: IfNotPresent
+          tag: "aa9dff4"
 
-1. In your config file for langsmith (usually `langsmith_config.yaml`, enable the `langgraphPlatform` option. Note that you must also have a valid ingress setup:
-
+1. In your `values.yaml` file, enable the `langgraphPlatform` option. Note that you must also have a valid ingress setup:
         config:
           langgraphPlatform:
             enabled: true

docs/docs/cloud/deployment/self_hosted_data_plane.md

@@ -2,8 +2,8 @@
 
 Before deploying, review the [conceptual guide for the Self-Hosted Data Plane](../../concepts/langgraph_self_hosted_data_plane.md) deployment option.
 
-!!! info "Important"
-    The Self-Hosted Data Plane deployment option is currently in beta stage and requires an [Enterprise](../../concepts/plans.md) plan.
+!!! important "Beta"
+    The Self-Hosted Data Plane deployment option is currently in beta stage.
 
 ## Prerequisites
 
@@ -18,7 +18,7 @@ Before deploying, review the [conceptual guide for the Self-Hosted Data Plane](.
         helm repo add kedacore https://kedacore.github.io/charts 
         helm install keda kedacore/keda --namespace keda --create-namespace
 
-1. A valid `Ingress` controller is installed on your cluster.
+1. A valid `Ingress` controller is install on your cluster.
 1. You have slack space in your cluster for multiple deployments. `Cluster-Autoscaler` is recommended to automatically provision new nodes.
 
 ### Setup

docs/docs/cloud/deployment/setup.md

@@ -1,11 +1,11 @@
 # How to Set Up a LangGraph Application with requirements.txt
 
-A LangGraph application must be configured with a [LangGraph configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Platform (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph application for deployment using `requirements.txt` to specify project dependencies.
+A LangGraph application must be configured with a [LangGraph configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Cloud (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph application for deployment using `requirements.txt` to specify project dependencies.
 
 This walkthrough is based on [this repository](https://github.com/langchain-ai/langgraph-example), which you can play around with to learn more about how to setup your LangGraph application for deployment.
 
 !!! tip "Setup with pyproject.toml"
-    If you prefer using poetry for dependency management, check out [this how-to guide](./setup_pyproject.md) on using `pyproject.toml` for LangGraph Platform.
+    If you prefer using poetry for dependency management, check out [this how-to guide](./setup_pyproject.md) on using `pyproject.toml` for LangGraph Cloud.
 
 !!! tip "Setup with a Monorepo"
     If you are interested in deploying a graph located inside a monorepo, take a look at [this repository](https://github.com/langchain-ai/langgraph-example-monorepo) for an example of how to do so.
@@ -95,7 +95,7 @@ my-app/
 
 ## Define Graphs
 
-Implement your graphs! Graphs can be defined in a single file or multiple files. Make note of the variable names of each [CompiledStateGraph][langgraph.graph.state.CompiledStateGraph] to be included in the LangGraph application. The variable names will be used later when creating the [LangGraph configuration file](../reference/cli.md#configuration-file).
+Implement your graphs! Graphs can be defined in a single file or multiple files. Make note of the variable names of each [CompiledGraph][langgraph.graph.graph.CompiledGraph] to be included in the LangGraph application. The variable names will be used later when creating the [LangGraph configuration file](../reference/cli.md#configuration-file).
 
 Example `agent.py` file, which shows how to import from other modules you define (code for the modules is not shown here, please see [this repository](https://github.com/langchain-ai/langgraph-example) to see their implementation):
 
@@ -129,6 +129,9 @@ workflow.add_edge("action", "agent")
 graph = workflow.compile()
 ```
 
+!!! warning "Assign `CompiledGraph` to Variable"
+    The build process for LangGraph Cloud requires that the `CompiledGraph` object be assigned to a variable at the top-level of a Python module (alternatively, you can provide [a function that creates a graph](./graph_rebuild.md)).
+
 Example file directory:
 
 ```bash

docs/docs/cloud/deployment/setup_javascript.md

@@ -1,6 +1,6 @@
 # How to Set Up a LangGraph.js Application
 
-A [LangGraph.js](https://langchain-ai.github.io/langgraphjs/) application must be configured with a [LangGraph configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Platform (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph.js application for deployment using `package.json` to specify project dependencies.
+A [LangGraph.js](https://langchain-ai.github.io/langgraphjs/) application must be configured with a [LangGraph configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Cloud (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph.js application for deployment using `package.json` to specify project dependencies.
 
 This walkthrough is based on [this repository](https://github.com/langchain-ai/langgraphjs-studio-starter), which you can play around with to learn more about how to setup your LangGraph application for deployment.
 
@@ -155,6 +155,10 @@ const workflow = new StateGraph(MessagesAnnotation)
 export const graph = workflow.compile();
 ```
 
+!!! info "Assign `CompiledGraph` to Variable"
+
+    The build process for LangGraph Cloud requires that the `CompiledGraph` object be assigned to a variable at the top-level of a JavaScript module (alternatively, you can provide [a function that creates a graph](./graph_rebuild.md)).
+
 Example file directory:
 
 ```bash