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William Fu-Hinthorn 38fac0099c update
Signed-off-by: William Fu-Hinthorn <13333726+hinthornw@users.noreply.github.com>
2025-04-03 10:00:46 -07:00
William Fu-Hinthorn 3ac3fb414e Show lifespan 2025-04-03 09:23:23 -07:00
675 changed files with 73673 additions and 66242 deletions
+88
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@@ -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') }}
+8 -5
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@@ -3,6 +3,9 @@ name: CLI integration test
on:
workflow_call:
env:
POETRY_VERSION: "1.7.1"
jobs:
build:
runs-on: ubuntu-latest
@@ -22,14 +25,13 @@ jobs:
uses: Ana06/get-changed-files@v2.3.0
with:
filter: "libs/cli/**"
- name: Set up Python ${{ matrix.python-version }}
- name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
if: steps.changed-files.outputs.all
uses: astral-sh/setup-uv@v6
uses: "./.github/actions/poetry_setup"
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
cache-suffix: "cli-integration-test"
ignore-nothing-to-cache: true
poetry-version: ${{ env.POETRY_VERSION }}
cache-key: integration-test-cli
- name: Setup env
if: steps.changed-files.outputs.all
working-directory: libs/cli/examples
@@ -69,3 +71,4 @@ jobs:
working-directory: libs/cli/js-examples
run: |
langgraph build -t langgraph-test-e
+39 -8
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@@ -9,6 +9,8 @@ on:
description: "From which folder this pipeline executes"
env:
POETRY_VERSION: "1.7.1"
# This env var allows us to get inline annotations when ruff has complaints.
RUFF_OUTPUT_FORMAT: github
@@ -34,18 +36,38 @@ jobs:
uses: Ana06/get-changed-files@v2.3.0
with:
filter: "${{ inputs.working-directory }}/**"
- name: Set up Python ${{ matrix.python-version }}
- name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
if: steps.changed-files.outputs.all
uses: astral-sh/setup-uv@v6
uses: "./.github/actions/poetry_setup"
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
cache-suffix: lint-${{ inputs.working-directory }}
poetry-version: ${{ env.POETRY_VERSION }}
cache-key: lint-${{ inputs.working-directory }}
- name: Check Poetry File
if: steps.changed-files.outputs.all
shell: bash
working-directory: ${{ inputs.working-directory }}
run: poetry check
- name: Check lock file
if: steps.changed-files.outputs.all
shell: bash
working-directory: ${{ inputs.working-directory }}
run: poetry check --lock
- name: Install dependencies
if: steps.changed-files.outputs.all
# Also installs dev/lint/test/typing dependencies, to ensure we have
# type hints for as many of our libraries as possible.
# This helps catch errors that require dependencies to be spotted, for example:
# https://github.com/langchain-ai/langchain/pull/10249/files#diff-935185cd488d015f026dcd9e19616ff62863e8cde8c0bee70318d3ccbca98341
#
# If you change this configuration, make sure to change the `cache-key`
# in the `poetry_setup` action above to stop using the old cache.
# It doesn't matter how you change it, any change will cause a cache-bust.
working-directory: ${{ inputs.working-directory }}
run: uv sync --frozen --group dev
run: poetry install --with dev
- name: Get .mypy_cache to speed up mypy
if: steps.changed-files.outputs.all
@@ -55,7 +77,7 @@ jobs:
with:
path: |
${{ inputs.working-directory }}/.mypy_cache
key: mypy-lint-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/uv.lock', inputs.working-directory)) }}
key: mypy-lint-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}
- name: Analysing package code with our lint
if: steps.changed-files.outputs.all
@@ -70,8 +92,17 @@ jobs:
- name: Install test dependencies
if: steps.changed-files.outputs.all
# Also installs dev/lint/test/typing dependencies, to ensure we have
# type hints for as many of our libraries as possible.
# This helps catch errors that require dependencies to be spotted, for example:
# https://github.com/langchain-ai/langchain/pull/10249/files#diff-935185cd488d015f026dcd9e19616ff62863e8cde8c0bee70318d3ccbca98341
#
# If you change this configuration, make sure to change the `cache-key`
# in the `poetry_setup` action above to stop using the old cache.
# It doesn't matter how you change it, any change will cause a cache-bust.
working-directory: ${{ inputs.working-directory }}
run: uv sync --group dev
run: |
poetry install --with dev
- name: Get .mypy_cache_test to speed up mypy
if: steps.changed-files.outputs.all
@@ -81,7 +112,7 @@ jobs:
with:
path: |
${{ inputs.working-directory }}/.mypy_cache_test
key: mypy-test-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/uv.lock', inputs.working-directory)) }}
key: mypy-test-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}
- name: Analysing tests with our lint
if: steps.changed-files.outputs.all
+17 -6
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@@ -8,6 +8,9 @@ on:
type: string
description: "From which folder this pipeline executes"
env:
POETRY_VERSION: "1.7.1"
jobs:
build:
runs-on: ubuntu-latest
@@ -23,12 +26,12 @@ jobs:
name: "test #${{ matrix.python-version }}"
steps:
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: astral-sh/setup-uv@v6
- name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
uses: "./.github/actions/poetry_setup"
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
cache-suffix: test-${{ inputs.working-directory }}
poetry-version: ${{ env.POETRY_VERSION }}
cache-key: test-${{ inputs.working-directory }}
- name: Login to Docker Hub
uses: docker/login-action@v3
if: ${{ !github.event.pull_request.head.repo.fork }}
@@ -36,15 +39,23 @@ jobs:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_RO_TOKEN }}
- name: Check Lock
shell: bash
working-directory: ${{ inputs.working-directory }}
run: |
poetry check --lock
- 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: ${{ inputs.working-directory }}
run: make test
run: |
make test
- name: Ensure the tests did not create any additional files
shell: bash
+11 -6
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@@ -3,6 +3,9 @@ name: test
on:
workflow_call:
env:
POETRY_VERSION: "1.7.1"
jobs:
build:
runs-on: ubuntu-latest
@@ -21,12 +24,12 @@ jobs:
name: "test #${{ matrix.python-version }}"
steps:
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: astral-sh/setup-uv@v6
- name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
uses: "./.github/actions/poetry_setup"
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
cache-suffix: "test-langgraph"
poetry-version: ${{ env.POETRY_VERSION }}
cache-key: test-langgraph
- name: Login to Docker Hub
uses: docker/login-action@v3
if: ${{ !github.event.pull_request.head.repo.fork }}
@@ -36,11 +39,13 @@ jobs:
- name: Install dependencies
shell: bash
run: uv sync --frozen --group dev
run: |
poetry install --with dev
- name: Run tests
shell: bash
run: make test_parallel
run: |
make test_parallel
- name: Ensure the tests did not create any additional files
shell: bash
+9 -8
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@@ -9,11 +9,12 @@ on:
description: "From which folder this pipeline executes"
env:
POETRY_VERSION: "1.7.1"
PYTHON_VERSION: "3.10"
jobs:
build:
if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/v0'
if: github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
outputs:
@@ -23,12 +24,12 @@ jobs:
steps:
- uses: actions/checkout@v4
- name: Set up Python $${ env.PYTHON_VERSION }}
uses: astral-sh/setup-uv@v6
- name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
uses: "./.github/actions/poetry_setup"
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: true
cache-suffix: "release"
poetry-version: ${{ env.POETRY_VERSION }}
cache-key: release
# We want to keep this build stage *separate* from the release stage,
# so that there's no sharing of permissions between them.
@@ -42,7 +43,7 @@ jobs:
# > from the publish job.
# https://github.com/pypa/gh-action-pypi-publish#non-goals
- name: Build project for distribution
run: uv build
run: poetry build
working-directory: ${{ inputs.working-directory }}
- name: Upload build
@@ -56,8 +57,8 @@ jobs:
shell: bash
working-directory: ${{ inputs.working-directory }}
run: |
echo pkg-name=$(grep -m 1 "^name = " pyproject.toml | cut -d '"' -f 2)
echo version=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
echo pkg-name="$(poetry version | cut -d ' ' -f 1)" >> $GITHUB_OUTPUT
echo version="$(poetry version --short)" >> $GITHUB_OUTPUT
publish:
needs:
+11 -6
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@@ -3,6 +3,9 @@ name: test
on:
workflow_call:
env:
POETRY_VERSION: "1.7.1"
jobs:
build:
runs-on: ubuntu-latest
@@ -18,12 +21,12 @@ jobs:
name: "test #${{ matrix.python-version }}"
steps:
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: astral-sh/setup-uv@v6
- name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
uses: "./.github/actions/poetry_setup"
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
cache-suffix: "test-scheduler-kafka"
poetry-version: ${{ env.POETRY_VERSION }}
cache-key: test-scheduler-kafka
- name: Login to Docker Hub
uses: docker/login-action@v3
if: ${{ !github.event.pull_request.head.repo.fork }}
@@ -33,11 +36,13 @@ jobs:
- name: Install dependencies
shell: bash
run: uv sync --frozen --group dev
run: |
poetry install --with dev
- name: Run tests
shell: bash
run: make test
run: |
make test
- name: Ensure the tests did not create any additional files
shell: bash
+8 -5
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@@ -7,6 +7,9 @@ on:
paths:
- "libs/**"
env:
POETRY_VERSION: "1.7.1"
jobs:
benchmark:
runs-on: ubuntu-latest
@@ -16,14 +19,14 @@ jobs:
steps:
- uses: actions/checkout@v4
- run: SHA=$(git rev-parse HEAD) && echo "SHA=$SHA" >> $GITHUB_ENV
- name: Set up Python 3.11
uses: astral-sh/setup-uv@v6
- name: Set up Python 3.11 + Poetry ${{ env.POETRY_VERSION }}
uses: "./.github/actions/poetry_setup"
with:
python-version: "3.11"
enable-cache: true
cache-suffix: "bench"
poetry-version: ${{ env.POETRY_VERSION }}
cache-key: bench
- name: Install dependencies
run: uv sync --group dev
run: poetry install --with dev
- name: Run benchmarks
run: OUTPUT=out/benchmark-baseline.json make -s benchmark
- name: Save outputs
+9 -6
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@@ -5,6 +5,9 @@ on:
paths:
- "libs/**"
env:
POETRY_VERSION: "1.7.1"
jobs:
benchmark:
runs-on: ubuntu-latest
@@ -18,14 +21,14 @@ jobs:
uses: Ana06/get-changed-files@v2.3.0
with:
format: json
- name: Set up Python 3.11
uses: astral-sh/setup-uv@v6
- name: Set up Python 3.11 + Poetry ${{ env.POETRY_VERSION }}
uses: "./.github/actions/poetry_setup"
with:
python-version: "3.11"
enable-cache: true
cache-suffix: "bench"
poetry-version: ${{ env.POETRY_VERSION }}
cache-key: bench
- name: Install dependencies
run: uv sync --group dev
run: poetry install --with dev
- name: Download baseline
uses: actions/cache/restore@v4
with:
@@ -50,7 +53,7 @@ jobs:
echo 'OUTPUT<<EOF'
mv out/benchmark-baseline.json out/main.json
mv out/benchmark.json out/changes.json
uv run pyperf compare_to out/main.json out/changes.json --table --group-by-speed
poetry run pyperf compare_to out/main.json out/changes.json --table --group-by-speed
echo EOF
} >> "$GITHUB_OUTPUT"
- name: Annotation
+10 -7
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@@ -16,6 +16,9 @@ concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
env:
POETRY_VERSION: "1.7.1"
jobs:
changes:
runs-on: ubuntu-latest
@@ -122,26 +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
+22 -23
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@@ -4,13 +4,14 @@ on:
push:
branches:
- main
- v0
pull_request:
branches:
- main
- v0
workflow_dispatch:
env:
POETRY_VERSION: "1.7.1"
permissions:
contents: read
pages: write
@@ -37,13 +38,12 @@ jobs:
with:
filter: "docs/docs/**"
# TODO: Uncomment this to run on PRs
# run-changed-notebooks:
# needs: get-changed-files
# uses: ./.github/workflows/run_notebooks.yml
# secrets: inherit
# with:
# changed-files: ${{ needs.get-changed-files.outputs.changed-files }}
run-changed-notebooks:
needs: get-changed-files
uses: ./.github/workflows/run_notebooks.yml
secrets: inherit
with:
changed-files: ${{ needs.get-changed-files.outputs.changed-files }}
deploy:
# needs: run-changed-notebooks
@@ -56,21 +56,21 @@ 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 +84,9 @@ 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
@@ -98,11 +98,10 @@ jobs:
- name: Check links in notebooks
env:
LANGCHAIN_API_KEY: test
if: github.event_name == 'schedule'
run: |
if [ "${{ github.event_name }}" == "schedule" ]; then
echo "Running link check on all HTML files matching notebooks in docs directory..."
uv run pytest -v \
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 +126,7 @@ 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 +145,8 @@ 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 +155,6 @@ 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
+8 -5
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@@ -11,6 +11,9 @@ on:
- cron: "0 5 * * *"
workflow_dispatch:
env:
POETRY_VERSION: "1.7.1"
jobs:
markdown-link-check:
runs-on: ubuntu-latest
@@ -39,8 +42,8 @@ jobs:
- name: Check README.md is in sync
run: |
if ! diff -q README.md libs/langgraph/README.md >/dev/null; then
echo "README.md is out of sync with libs/langgraph/README.md"
diff -C 3 README.md libs/langgraph/README.md
exit 1
fi
if ! diff -q README.md libs/langgraph/README.md >/dev/null; then
echo "README.md is out of sync with libs/langgraph/README.md"
diff -C 3 README.md libs/langgraph/README.md
exit 1
fi
+26 -25
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@@ -10,10 +10,11 @@ on:
env:
PYTHON_VERSION: "3.11"
POETRY_VERSION: "1.7.1"
jobs:
build:
if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/v0'
if: github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
outputs:
@@ -25,12 +26,12 @@ jobs:
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: astral-sh/setup-uv@v6
- name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
uses: "./.github/actions/poetry_setup"
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: true
cache-suffix: "release"
poetry-version: ${{ env.POETRY_VERSION }}
cache-key: release
# We want to keep this build stage *separate* from the release stage,
# so that there's no sharing of permissions between them.
@@ -44,7 +45,7 @@ jobs:
# > from the publish job.
# https://github.com/pypa/gh-action-pypi-publish#non-goals
- name: Build project for distribution
run: uv build
run: poetry build
working-directory: ${{ inputs.working-directory }}
- name: Upload build
@@ -58,8 +59,8 @@ jobs:
shell: bash
working-directory: ${{ inputs.working-directory }}
run: |
PKG_NAME=$(grep -m 1 "^name = " pyproject.toml | cut -d '"' -f 2)
VERSION=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
PKG_NAME="$(poetry version | cut -d ' ' -f 1)"
VERSION="$(poetry version --short)"
SHORT_PKG_NAME="$(echo "$PKG_NAME" | sed -e 's/langgraph//g' -e 's/-//g')"
if [ -z $SHORT_PKG_NAME ]; then
TAG="$VERSION"
@@ -162,11 +163,11 @@ jobs:
# - The package is published, and it breaks on the missing dependency when
# used in the real world.
- name: Set up Python
uses: astral-sh/setup-uv@v6
- name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
uses: "./.github/actions/poetry_setup"
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: true
poetry-version: ${{ env.POETRY_VERSION }}
- name: Import published package
shell: bash
@@ -184,18 +185,18 @@ jobs:
# - attempt install again after 5 seconds if it fails because there is
# sometimes a delay in availability on test pypi
run: |
uv run pip install \
poetry run pip install \
--extra-index-url https://test.pypi.org/simple/ \
"$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: ${{ env.POETRY_VERSION }}
cache-key: release
- uses: actions/download-artifact@v4
with:
+10 -10
View File
@@ -9,7 +9,7 @@ on:
type: string
description: "JSON string of changed files"
schedule:
- cron: "0 13 * * *"
- cron: '0 13 * * *'
defaults:
run:
@@ -27,30 +27,30 @@ jobs:
steps:
- uses: actions/checkout@v4
- name: Set up Python + Poetry
uses: astral-sh/setup-uv@v6
uses: "./.github/actions/poetry_setup"
with:
python-version: "3.11"
enable-cache: true
cache-suffix: "test-langgraph-notebooks"
python-version: 3.11
poetry-version: 1.7.1
cache-key: test-langgraph-notebooks
- name: Install dependencies
run: |
uv sync --group test
uv run pip install jupyter
poetry install --with test
poetry run pip install jupyter
- name: Start services
run: make start-services
- name: Pre-download tiktoken files
run: |
uv run python _scripts/download_tiktoken.py
poetry run python _scripts/download_tiktoken.py
- name: Prepare notebooks
run: |
if [ "${{ matrix.lib-version }}" = "development" ]; then
uv run python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
poetry run python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
else
uv run python _scripts/prepare_notebooks_for_ci.py
poetry run python _scripts/prepare_notebooks_for_ci.py
fi
- name: Run notebooks
-1
View File
@@ -180,4 +180,3 @@ Chinook.db
.vercel
.turbo
.editorconfig
+1 -2
View File
@@ -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
```
+38 -35
View File
@@ -12,52 +12,49 @@
[![Downloads](https://static.pepy.tech/badge/langgraph/month)](https://pepy.tech/project/langgraph)
[![Open Issues](https://img.shields.io/github/issues-raw/langchain-ai/langgraph)](https://github.com/langchain-ai/langgraph/issues)
[![Docs](https://img.shields.io/badge/docs-latest-blue)](https://langchain-ai.github.io/langgraph/)
[![GitMCP](https://img.shields.io/endpoint?url=https://gitmcp.io/badge/langchain-ai/langgraph)](https://gitmcp.io/langchain-ai/langgraph)
Trusted by companies shaping the future of agents including Klarna, Replit, Elastic, and more LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents.
> [!NOTE]
> Looking for the JS version? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://langchain-ai.github.io/langgraphjs/).
## Get started
LangGraph — used by Replit, Uber, LinkedIn, GitLab and more — is a low-level orchestration framework for building controllable agents. While langchain provides integrations and composable components to streamline LLM application development, the LangGraph library enables agent orchestration — offering customizable architectures, long-term memory, and human-in-the-loop to reliably handle complex tasks.
Install LangGraph:
```
```bash
pip install -U langgraph
```
Then, create an agent [using prebuilt components](https://langchain-ai.github.io/langgraph/agents/agents/):
To learn more about how to use LangGraph, check out [the docs](https://langchain-ai.github.io/langgraph/). We show a simple example below of how to create a ReAct agent.
```python
# pip install -qU "langchain[anthropic]" to call the model
# This code depends on pip install langchain[anthropic]
from langgraph.prebuilt import create_react_agent
def get_weather(city: str) -> str:
"""Get weather for a given city."""
return f"It's always sunny in {city}!"
def search(query: str):
"""Call to surf the web."""
if "sf" in query.lower() or "san francisco" in query.lower():
return "It's 60 degrees and foggy."
return "It's 90 degrees and sunny."
agent = create_react_agent(
model="anthropic:claude-3-7-sonnet-latest",
tools=[get_weather],
prompt="You are a helpful assistant"
)
# Run the agent
agent = create_react_agent("anthropic:claude-3-7-sonnet-latest", tools=[search])
agent.invoke(
{"messages": [{"role": "user", "content": "what is the weather in sf"}]}
)
```
For more information, see the [Quickstart](https://langchain-ai.github.io/langgraph/agents/agents/). Or, to learn how to build an [agent workflow](https://langchain-ai.github.io/langgraph/concepts/low_level/) with a customizable architecture, long-term memory, and other complex task handling, see the [LangGraph basics tutorials](https://langchain-ai.github.io/langgraph/tutorials/get-started/1-build-basic-chatbot/).
## Why use LangGraph?
## Core benefits
LangGraph is built for developers who want to build powerful, adaptable AI agents. Developers choose LangGraph for:
LangGraph provides low-level supporting infrastructure for *any* long-running, stateful workflow or agent. LangGraph does not abstract prompts or architecture, and provides the following central benefits:
- **Reliability and controllability.** Steer agent actions with moderation checks and human-in-the-loop approvals. LangGraph persists context for long-running workflows, keeping your agents on course.
- **Low-level and extensible.** Build custom agents with fully descriptive, low-level primitives free from rigid abstractions that limit customization. Design scalable multi-agent systems, with each agent serving a specific role tailored to your use case.
- **First-class streaming support.** With token-by-token streaming and streaming of intermediate steps, LangGraph gives users clear visibility into agent reasoning and actions as they unfold in real time.
- [Durable execution](https://langchain-ai.github.io/langgraph/concepts/durable_execution/): Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off.
- [Human-in-the-loop](https://langchain-ai.github.io/langgraph/concepts/human_in_the_loop/): Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution.
- [Comprehensive memory](https://langchain-ai.github.io/langgraph/concepts/memory/): Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions.
- [Debugging with LangSmith](http://www.langchain.com/langsmith): Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics.
- [Production-ready deployment](https://langchain-ai.github.io/langgraph/concepts/deployment_options/): Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows.
LangGraph is trusted in production and powering agents for companies like:
- [Klarna](https://blog.langchain.dev/customers-klarna/): Customer support bot for 85 million active users
- [Elastic](https://www.elastic.co/blog/elastic-security-generative-ai-features): Security AI assistant for threat detection
- [Uber](https://dpe.org/sessions/ty-smith-adam-huda/this-year-in-ubers-ai-driven-developer-productivity-revolution/): Automated unit test generation
- [Replit](https://www.langchain.com/breakoutagents/replit): Code generation
- And many more ([see list here](https://www.langchain.com/built-with-langgraph))
## LangGraphs ecosystem
@@ -65,20 +62,26 @@ While LangGraph can be used standalone, it also integrates seamlessly with any L
- [LangSmith](http://www.langchain.com/langsmith) — Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
- [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
- [LangChain](https://python.langchain.com/docs/introduction/) Provides integrations and composable components to streamline LLM application development.
> [!NOTE]
> Looking for the JS version of LangGraph? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://langchain-ai.github.io/langgraphjs/).
## Pairing with LangGraph Platform
While LangGraph is our open-source agent orchestration framework, enterprises that need scalable agent deployment can benefit from [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/).
LangGraph Platform can help engineering teams:
- **Accelerate agent development**: Quickly create agent UXs with configurable templates and [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/) for visualizing and debugging agent interactions.
- **Deploy seamlessly**: We handle the complexity of deploying your agent. LangGraph Platform includes robust APIs for memory, threads, and cron jobs plus auto-scaling task queues & servers.
- **Centralize agent management & reusability**: Discover, reuse, and manage agents across the organization. Business users can also modify agents without coding.
## Additional resources
- [Guides](https://langchain-ai.github.io/langgraph/how-tos/): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
- [Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
- [Examples](https://langchain-ai.github.io/langgraph/tutorials/overview/): Guided examples on getting started with LangGraph.
- [LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph): Learn the basics of LangGraph in our free, structured course.
- [Tutorials](https://langchain-ai.github.io/langgraph/tutorials/): Simple walkthroughs with guided examples on getting started with LangGraph.
- [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.
- [How-to 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.).
- [API 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.
- [Built with LangGraph](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.
+18 -16
View File
@@ -12,30 +12,32 @@ build-prebuilt:
# generates the final prebuilt page.
@if [ "$(DOWNLOAD_STATS)" = "true" ]; then \
set -x; \
uv run python -m _scripts.third_party_page.get_download_stats stats.yml; \
poetry run python -m _scripts.third_party_page.get_download_stats stats.yml; \
set +x; \
else \
set -x; \
uv run python -m _scripts.third_party_page.get_download_stats --fake stats.yml; \
poetry run python -m _scripts.third_party_page.get_download_stats --fake stats.yml; \
set +x; \
fi
uv run python -m _scripts.third_party_page.create_third_party_page stats.yml docs/agents/prebuilt.md --language python
poetry run python -m _scripts.third_party_page.create_third_party_page stats.yml docs/prebuilt.md --language python
build-docs: build-typedoc build-prebuilt
uv run python -m mkdocs build --clean -f mkdocs.yml --strict
poetry run python -m mkdocs build --clean -f mkdocs.yml --strict
llms-text:
uv run python -m _scripts.generate_llms_text docs/llms-full.txt
poetry run python -m _scripts.generate_llms_text docs/llms-full.txt
install-vercel-deps:
curl -sL "https://astral.sh/uv/install.sh" | bash -s
export PATH="${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 .
+2 -2
View File
@@ -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
@@ -58,4 +58,4 @@ To delete cassettes for a notebook, you can run:
```bash
rm cassettes/<notebook_name>*
```
```
+1 -1
View File
@@ -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"
+5 -28
View File
@@ -22,12 +22,6 @@ MANUAL_API_REFERENCES_LANGGRAPH = [
"create_react_agent",
"prebuilt",
),
(
[],
"langgraph.prebuilt.chat_agent_executor",
"AgentState",
"prebuilt",
),
(["langgraph.prebuilt"], "langgraph.prebuilt.tool_node", "ToolNode", "prebuilt"),
(
["langgraph.prebuilt"],
@@ -51,8 +45,6 @@ MANUAL_API_REFERENCES_LANGGRAPH = [
(["langgraph.constants"], "langgraph.types", "Interrupt", "types"),
(["langgraph.constants"], "langgraph.types", "interrupt", "types"),
(["langgraph.constants"], "langgraph.types", "Command", "types"),
(["langgraph.config"], "langgraph.config", "get_stream_writer", "config"),
(["langgraph.config"], "langgraph.config", "get_store", "config"),
(["langgraph.func"], "langgraph.func", "entrypoint", "func"),
(["langgraph.func"], "langgraph.func", "task", "func"),
(["langgraph.types"], "langgraph.types", "RetryPolicy", "types"),
@@ -64,23 +56,10 @@ MANUAL_API_REFERENCES_LANGGRAPH = [
([], "langgraph.checkpoint.base", "SerializerProtocol", "checkpoints"),
([], "langgraph.checkpoint.serde.jsonplus", "JsonPlusSerializer", "checkpoints"),
([], "langgraph.checkpoint.memory", "MemorySaver", "checkpoints"),
([], "langgraph.checkpoint.memory", "InMemorySaver", "checkpoints"),
([], "langgraph.checkpoint.sqlite.aio", "AsyncSqliteSaver", "checkpoints"),
([], "langgraph.checkpoint.sqlite", "SqliteSaver", "checkpoints"),
([], "langgraph.checkpoint.postgres.aio", "AsyncPostgresSaver", "checkpoints"),
([], "langgraph.checkpoint.postgres", "PostgresSaver", "checkpoints"),
# other prebuilts
(["langgraph_supervisor"], "langgraph_supervisor.supervisor", "create_supervisor", "supervisor"),
(["langgraph_supervisor"], "langgraph_supervisor.handoff", "create_handoff_tool", "supervisor"),
([], "langgraph_supervisor.handoff", "create_forward_message_tool", "supervisor"),
(["langgraph_swarm"], "langgraph_swarm.swarm", "create_swarm", "swarm"),
(["langgraph_swarm"], "langgraph_swarm.swarm", "add_active_agent_router", "swarm"),
(["langgraph_swarm"], "langgraph_swarm.swarm", "SwarmState", "swarm"),
(["langgraph_swarm"], "langgraph_swarm.handoff", "create_handoff_tool", "swarm"),
([], "langchain_mcp_adapters.client", "MultiServerMCPClient", "mcp"),
([], "langchain_mcp_adapters.tools", "load_mcp_tools", "mcp"),
([], "langchain_mcp_adapters.prompts", "load_mcp_prompt", "mcp"),
([], "langchain_mcp_adapters.resources", "load_mcp_resources", "mcp"),
]
WELL_KNOWN_LANGGRAPH_OBJECTS = {
@@ -162,9 +141,7 @@ def get_imports(code: str, path: str) -> List[ImportInformation]:
for found_import in found_imports:
module = found_import["source"]
if module.startswith("langchain_mcp_adapters"):
package_ecosystem = "langgraph"
elif module.startswith("langchain"):
if module.startswith("langchain"):
# Handles things like `langchain` or `langchain_anthropic`
package_ecosystem = "langchain"
elif module.startswith("langgraph"):
@@ -237,7 +214,7 @@ def update_markdown_with_imports(markdown: str, path: str) -> str:
path: The path of the file where the markdown content originated.
Returns:
Updated markdown with API reference links prepended to Python code blocks.
Updated markdown with API reference links appended to Python code blocks.
Example:
Given a markdown with a Python code block:
@@ -260,7 +237,7 @@ def update_markdown_with_imports(markdown: str, path: str) -> str:
match (re.Match): The regex match object containing the code block.
Returns:
str: The modified code block with API reference links prepended if applicable.
str: The modified code block with API reference links appended if applicable.
"""
indent = match.group("indent")
code_block = match.group("code")
@@ -276,8 +253,8 @@ def update_markdown_with_imports(markdown: str, path: str) -> str:
api_links = " | ".join(
f'<a href="{imp["docs"]}">{imp["imported"]}</a>' for imp in imports
)
# Return the code block with prepended API reference links
return f"{indent}<sup><i>API Reference: {api_links}</i></sup>\n\n{original_code_block}"
# Return the code block with appended API reference links
return f"{original_code_block}\n\n{indent}API Reference: {api_links}"
# Apply the replace_code_block function to all matches in the markdown
updated_markdown = code_block_pattern.sub(replace_code_block, markdown)
+34 -239
View File
@@ -1,19 +1,10 @@
"""Experimental script to generate consolidated llms text from the docs."""
import asyncio
import glob
import os
from typing import TypedDict, List, Optional
import pydantic
import re
from pydantic import BaseModel, Field
from langchain_core.rate_limiters import InMemoryRateLimiter
import yaml
from langchain.chat_models import init_chat_model
from mkdocs.structure.files import File
from mkdocs.structure.pages import Page
from yaml import SafeLoader
from _scripts.notebook_hooks import _on_page_markdown_with_config
@@ -22,59 +13,26 @@ HERE = os.path.dirname(os.path.abspath(__file__))
SOURCE_DIR = os.path.abspath(os.path.join(os.path.dirname(HERE), "docs"))
async def convert_ipynb_to_md(file_path: str) -> Optional[str]:
"""Process a file (markdown or notebook) to markdown format.
Args:
file_path: Path to the file to process
Returns:
Processed markdown content if successful, None otherwise
"""
rel_path = os.path.relpath(file_path, SOURCE_DIR)
# Create File and Page objects to match mkdocs structure
file_obj = File(
path=rel_path, src_dir=SOURCE_DIR, dest_dir="", use_directory_urls=True
)
page = Page(
title="",
file=file_obj,
config={},
)
try:
# Read raw content
with open(file_path, "r", encoding="utf-8") as f:
content = f.read()
# Convert to markdown without logic to resolve API references
processed_content = _on_page_markdown_with_config(
content, page, add_api_references=False, remove_base64_images=True
)
# Remove self-closing img tags <img ... />
processed_content = re.sub(r"<img[^>]*/>", "", processed_content)
# Remove img tags with content <img ...>...</img>
processed_content = re.sub(
r"<img[^>]*>.*?</img>", "", processed_content, flags=re.DOTALL
)
return processed_content
except Exception as e:
print(f"Error processing file {file_path}: {e}")
return None
async def generate_full_llms_text(output_file: str) -> None:
def _make_llms_text(output_file: str) -> str:
"""Generate a consolidated text file from markdown/notebook files for LLM training.
Args:
output_file: Path to output the consolidated text file
"""
# Collect all markdown and notebook files
all_files = glob.glob(os.path.join(SOURCE_DIR, "how-tos/*.md"), recursive=True)
relative_paths = [
# Files relative to docs/docs/
"tutorials/introduction.ipynb",
]
all_files = [os.path.join(SOURCE_DIR, path) for path in relative_paths]
all_files.extend(
glob.glob(os.path.join(SOURCE_DIR, "how-tos/*.md"), recursive=True)
)
all_files.extend(
glob.glob(os.path.join(SOURCE_DIR, "how-tos/*.ipynb"), recursive=True)
)
# Add all concepts
all_files.extend(
glob.glob(os.path.join(SOURCE_DIR, "concepts/*.md"), recursive=True)
)
@@ -84,14 +42,30 @@ async def generate_full_llms_text(output_file: str) -> None:
all_content = []
# Process files concurrently
tasks = [convert_ipynb_to_md(file_path) for file_path in all_files]
results = await asyncio.gather(*tasks)
# Process each file
for file_path in all_files:
print(f"Processing {file_path}")
rel_path = os.path.relpath(file_path, SOURCE_DIR)
# Combine results with file paths
for file_path, processed_content in zip(all_files, results):
# Create File and Page objects to match mkdocs structure
file_obj = File(
path=rel_path, src_dir=SOURCE_DIR, dest_dir="", use_directory_urls=True
)
page = Page(
title="",
file=file_obj,
config={},
)
# Read raw content
with open(file_path, "r", encoding="utf-8") as f:
content = f.read()
# Convert to markdown without logic to resolve API references
processed_content = _on_page_markdown_with_config(
content, page, add_api_references=False, remove_base64_images=True
)
if processed_content:
rel_path = os.path.relpath(file_path, SOURCE_DIR)
# Add file name
all_content.append(f"---\n{rel_path}\n---")
# Add content
@@ -102,168 +76,6 @@ async def generate_full_llms_text(output_file: str) -> None:
f.write("\n\n".join(all_content))
def no_op_constructor(*args):
"""No-op"""
SafeLoader.add_multi_constructor(
"tag:yaml.org,2002:python/name",
no_op_constructor,
)
class NavItem(TypedDict):
title: str
url: str
hierarchy: tuple[str, ...]
description: str
def _flatten_nav(
nav: list[dict[str, str | list] | str], path: tuple[str, ...] = ()
) -> list[NavItem]:
flat: List[NavItem] = []
for item in nav:
if isinstance(item, dict):
for title, node in item.items():
new_path = path + (title,)
if isinstance(node, str):
# Leaf page
flat.append(
{
"title": title,
"url": node,
"hierarchy": new_path,
"description": "",
}
)
elif isinstance(node, list):
# Dive in, carrying along the updated path
flat.extend(_flatten_nav(node, new_path))
else:
raise TypeError(
f"Unexpected node type {type(node)} under {title!r}"
)
elif isinstance(item, str):
# Bare string entry → use itself as title, and as URL
new_path = path + (item,)
flat.append(
{"title": item, "url": item, "hierarchy": new_path, "description": ""}
)
else:
raise TypeError(f"Unexpected item type {type(item)} in nav")
return flat
class PageInfo(BaseModel):
title: str = Field(description="The title of the page")
description: str = Field(
description="A short description of the page no longer than 3 sentences "
"explaining the kind of content that can be found in the page."
)
async def process_nav_items(nav_items: list[NavItem]) -> list[NavItem]:
"""Open the contents of each nav item and come up with a better title and description."""
rate_limiter = InMemoryRateLimiter(requests_per_second=10)
model = init_chat_model("gpt-4o-mini", temperature=0.0, rate_limiter=rate_limiter)
model = model.with_structured_output(PageInfo)
async def process_single_item(item: NavItem) -> NavItem:
path = item["url"]
file_path = os.path.join(SOURCE_DIR, path)
# Process the file content (handles both markdown and notebooks)
if path.endswith(".ipynb"):
content = await convert_ipynb_to_md(file_path)
else:
with open(file_path, "r", encoding="utf-8") as f:
content = f.read()
if not content:
return item
# Generate a better title and description
response = await model.ainvoke(
[
{
"role": "system",
"content": "You are a technical documentation writer. "
"You are given a markdown page of documentation. "
"Please come up with an appropriate title and "
"description for the page. The description should "
"be a short summary of the page content that is "
"no longer than 3 sentences.",
},
{
"role": "user",
"content": "The markdown page is as follows:\n\n" + content,
},
]
)
return {
"title": response.title,
"url": item["url"],
"hierarchy": item["hierarchy"],
"description": response.description,
}
# Remove any items that start with http:// or https:// looking only for
# local file at this stages.
nav_items = [
item for item in nav_items if not item["url"].startswith(("http://", "https://"))
]
# Process items in parallel
tasks = [process_single_item(item) for item in nav_items]
new_nav_items = await asyncio.gather(*tasks)
return new_nav_items
async def generate_nav_links_text(
output_file: str, *, replace_links: bool = False
) -> None:
"""Generate llms.txt from mkdocs.yaml."""
# Get path to mkdocs.yaml relative to this script
script_dir = os.path.dirname(os.path.abspath(__file__))
mkdocs_path = os.path.join(os.path.dirname(script_dir), "mkdocs.yml")
# Load and parse yaml
with open(mkdocs_path, "r") as f:
config = yaml.safe_load(f)
# Extract nav section
nav = config.get("nav", [])
flattened = _flatten_nav(nav)
processed_nav = await process_nav_items(flattened)
with open(output_file, "w") as f:
current_section = None
for item in processed_nav:
# Get the top-level section (first item in hierarchy)
section = item["hierarchy"][0]
if section not in {"Guides", "Examples", "Resources"}:
continue
# If we're starting a new section, add a heading
if section != current_section:
f.write(f"\n# {section}\n\n")
current_section = section
title = item["title"]
# Process URL based on replace_links flag
url = item["url"]
if replace_links:
# Remove .md extension and ensure single trailing slash
url = url.removesuffix(".md")
url = url.removesuffix(".ipynb")
url = url.rstrip("/") + "/"
url = f"https://langchain-ai.github.io/langgraph/{url}"
f.write(f"- [{title}]({url}): {item['description']}\n")
if __name__ == "__main__":
import argparse
@@ -273,23 +85,6 @@ if __name__ == "__main__":
)
)
parser.add_argument("output_file", help="Path to output the consolidated text file")
parser.add_argument(
"--link-only",
action="store_true",
help="Only include link references in the output",
)
parser.add_argument(
"--replace-links",
action="store_true",
help="Replace markdown links with full URLs in the output",
)
args = parser.parse_args()
if args.link_only:
coro = generate_nav_links_text(
args.output_file, replace_links=args.replace_links
)
else:
coro = generate_full_llms_text(args.output_file)
asyncio.run(coro)
_make_llms_text(args.output_file)
+14 -33
View File
@@ -1,6 +1,7 @@
import ast
import os
import re
from pathlib import Path
from typing import Literal
import nbformat
@@ -25,7 +26,7 @@ def _uses_input(source: str) -> bool:
def _rewrite_cell_magic(code: str) -> str:
"""Process a code block that uses cell magic.
"""Process a code block that uses cell magic.:w
- Lines starting with "%%capture" are ignored.
- Lines starting with "%pip" are rewritten by removing the leading "%" character.
@@ -51,14 +52,10 @@ def _rewrite_cell_magic(code: str) -> str:
if stripped.startswith("%%capture"):
continue
# Rewrite %pip lines by dropping the '%'
elif stripped.startswith("%") or stripped.startswith("!"):
# Drop the leading '%' character and then drop all leading whitespace
stripped = stripped.lstrip("%! \t")
# Check if the line starts with "pip"
if stripped.startswith("pip"):
rewritten_lines.append(stripped)
else:
raise NotImplementedError(f"Unhandled line: {line}")
elif stripped.startswith("%pip"):
# Drop the leading '%' character
rewritten_lines.append(stripped[1:])
# Anything else is not supported
else:
raise NotImplementedError(f"Unhandled line: {line}")
@@ -220,24 +217,6 @@ def _convert_links_in_markdown(markdown: str) -> str:
)
class HideCellTagPreprocessor(Preprocessor):
"""
Removes cells that have '# hide-cell' at the beginning of the cell content.
This allows authors to include cells in the notebook that should not
appear in the generated markdown output.
"""
def preprocess(self, nb, resources):
# Filter out cells with the '# hide-cell' comment at the beginning
nb.cells = [
cell
for cell in nb.cells
if not (cell.source.strip().startswith("# hide-cell"))
]
return nb, resources
class EscapePreprocessor(Preprocessor):
def __init__(self, markdown_exec_migration: bool = False, **kwargs) -> None:
super().__init__(**kwargs)
@@ -268,10 +247,13 @@ class EscapePreprocessor(Preprocessor):
)
cell.metadata["exec"] = is_exec
# For markdown exec migration we'll re-write cell magic as bash commands
if source.startswith("%%"):
cell.source = _rewrite_cell_magic(source)
cell.metadata["language"] = "shell"
if self.markdown_exec_migration:
# For markdown exec migration we'll re-write cell magic as bash commands
if source.startswith("%%"):
cell.source = _rewrite_cell_magic(source)
cell.metadata["language"] = "shell"
cell.metadata["has_output"] = _has_output(source)
# Remove noqa comments
cell.source = re.sub(r"#\s*noqa.*$", "", cell.source, flags=re.MULTILINE)
@@ -359,7 +341,6 @@ class ExtractAttachmentsPreprocessor(Preprocessor):
exporter = MarkdownExporter(
preprocessors=[
HideCellTagPreprocessor,
EscapePreprocessor,
ExtractAttachmentsPreprocessor,
],
@@ -371,7 +352,7 @@ exporter = MarkdownExporter(
def convert_notebook(
notebook_path: str,
notebook_path: Path,
mode: Literal["markdown", "exec"] = "markdown",
) -> str:
with open(notebook_path) as f:
@@ -1,18 +1,5 @@
{% extends 'markdown/index.md.j2' %}
{% block input %}{# cell.metadata.language is an addition of our docs pipeline. #}
```{%- if 'language' in cell.metadata -%}
{{ cell.metadata.language }}
{%- elif 'magics_language' in cell.metadata -%}
{{ cell.metadata.magics_language }}
{%- elif 'name' in nb.metadata.get('language_info', {}) -%}
{{ nb.metadata.language_info.name }}
{%- endif %}
{{ cell.source }}
```
{% endblock input %}
{%- block traceback_line -%}
```output
{{ line.rstrip() | strip_ansi }}
@@ -21,13 +8,13 @@
{%- block stream -%}
```output
{{ output.text.rstrip() | strip_ansi }}
{{ output.text.rstrip() }}
```
{%- endblock stream -%}
{%- block data_text scoped -%}
```output
{{ output.data['text/plain'].rstrip() | strip_ansi }}
{{ output.data['text/plain'].rstrip() }}
```
{%- endblock data_text -%}
@@ -38,13 +25,9 @@
{%- endblock data_html -%}
{%- block data_jpg scoped -%}
<p>
<img src="data:image/jpg;base64,{{ output.data['image/jpeg'] }}" />
</p>
![](data:image/jpg;base64,{{ output.data['image/jpeg'] }})
{%- endblock data_jpg -%}
{%- block data_png scoped -%}
<p>
<img src="data:image/png;base64,{{ output.data['image/png'] }}" />
</p>
![](data:image/png;base64,{{ output.data['image/png'] }})
{%- endblock data_png -%}
+9 -133
View File
@@ -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
@@ -25,90 +18,19 @@ DISABLED = os.getenv("DISABLE_NOTEBOOK_CONVERT") in ("1", "true", "True")
REDIRECT_MAP = {
# lib redirects
"how-tos/stream-values.ipynb": "how-tos/streaming.md#stream-graph-state",
"how-tos/stream-updates.ipynb": "how-tos/streaming.md#stream-graph-state",
"how-tos/streaming-content.ipynb": "how-tos/streaming.md",
"how-tos/stream-multiple.ipynb": "how-tos/streaming.md#stream-multiple-nodes",
"how-tos/streaming-tokens-without-langchain.ipynb": "how-tos/streaming.md#use-with-any-llm",
"how-tos/stream-values.ipynb": "how-tos/streaming.ipynb#values",
"how-tos/stream-updates.ipynb": "how-tos/streaming.ipynb#updates",
"how-tos/streaming-content.ipynb": "how-tos/streaming.ipynb#custom",
"how-tos/stream-multiple.ipynb": "how-tos/streaming.ipynb#multiple",
"how-tos/streaming-tokens-without-langchain.ipynb": "how-tos/streaming-tokens.ipynb#example-without-langchain",
"how-tos/streaming-from-final-node.ipynb": "how-tos/streaming-specific-nodes.ipynb",
"how-tos/streaming-events-from-within-tools-without-langchain.ipynb": "how-tos/streaming-events-from-within-tools.ipynb#example-without-langchain",
# graph-api
"how-tos/state-reducers.ipynb": "how-tos/graph-api#define-and-update-state",
"how-tos/sequence.ipynb": "how-tos/graph-api#create-a-sequence-of-steps",
"how-tos/branching.ipynb": "how-tos/graph-api#create-branches",
"how-tos/recursion-limit.ipynb": "how-tos/graph-api#create-and-control-loops",
"how-tos/visualization.ipynb": "how-tos/graph-api#visualize-your-graph",
"how-tos/input_output_schema.ipynb": "how-tos/graph-api#define-input-and-output-schemas",
"how-tos/pass_private_state.ipynb": "how-tos/graph-api#pass-private-state-between-nodes",
"how-tos/state-model.ipynb": "how-tos/graph-api#use-pydantic-models-for-graph-state",
"how-tos/map-reduce.ipynb": "how-tos/graph-api/#map-reduce-and-the-send-api",
"how-tos/command.ipynb": "how-tos/graph-api/#combine-control-flow-and-state-updates-with-command",
"how-tos/configuration.ipynb": "how-tos/graph-api/#add-runtime-configuration",
"how-tos/node-retries.ipynb": "how-tos/graph-api/#add-retry-policies",
"how-tos/return-when-recursion-limit-hits.ipynb": "how-tos/graph-api/#impose-a-recursion-limit",
"how-tos/async.ipynb": "how-tos/graph-api/#async",
# memory how-tos
"how-tos/memory/manage-conversation-history.ipynb": "how-tos/memory.ipynb",
"how-tos/memory/delete-messages.ipynb": "how-tos/memory.ipynb#delete-messages",
"how-tos/memory/add-summary-conversation-history.ipynb": "how-tos/memory.ipynb#summarize-messages",
# subgraph how-tos
"how-tos/subgraph-transform-state.ipynb": "how-tos/subgraph.ipynb#different-state-schemas",
"how-tos/subgraphs-manage-state.ipynb": "how-tos/subgraph.ipynb#add-persistence",
# persistence how-tos
"how-tos/persistence_postgres.ipynb": "how-tos/persistence.ipynb#use-in-production",
"how-tos/persistence_mongodb.ipynb": "how-tos/persistence.ipynb#use-in-production",
"how-tos/persistence_redis.ipynb": "how-tos/persistence.ipynb#use-in-production",
"how-tos/subgraph-persistence.ipynb": "how-tos/persistence.ipynb#use-with-subgraphs",
"how-tos/cross-thread-persistence.ipynb": "how-tos/persistence.ipynb#add-long-term-memory",
"cloud/how-tos/copy_threads": "cloud/how-tos/use_threads",
# tool calling how-tos
"how-tos/tool-calling-errors.ipynb": "how-tos/tool-calling.ipynb#handle-errors",
"how-tos/pass-config-to-tools.ipynb": "how-tos/tool-calling.ipynb#access-config",
"how-tos/pass-run-time-values-to-tools.ipynb": "how-tos/tool-calling.ipynb#read-state",
"how-tos/update-state-from-tools.ipynb": "how-tos/tool-calling.ipynb#update-state",
# multi-agent how-tos
"how-tos/agent-handoffs.ipynb": "how-tos/multi_agent.ipynb#handoffs",
"how-tos/multi-agent-network.ipynb": "how-tos/multi_agent.ipynb#use-in-a-multi-agent-system",
"how-tos/multi-agent-multi-turn-convo.ipynb": "how-tos/multi_agent.ipynb#multi-turn-conversation",
# cloud redirects
"cloud/index.md": "index.md",
"cloud/how-tos/index.md": "concepts/langgraph_platform",
"cloud/index.md": "concepts/index.md#langgraph-platform",
"cloud/how-tos/index.md": "how-tos/index.md#langgraph-platform",
"cloud/concepts/api.md": "concepts/langgraph_server.md",
"cloud/concepts/cloud.md": "concepts/langgraph_cloud.md",
"cloud/faq/studio.md": "concepts/langgraph_studio.md#studio-faqs",
"cloud/how-tos/human_in_the_loop_edit_state.md": "cloud/how-tos/add-human-in-the-loop.md",
"cloud/how-tos/human_in_the_loop_user_input.md": "cloud/how-tos/add-human-in-the-loop.md",
"concepts/platform_architecture.md": "concepts/langgraph_cloud#architecture",
# cloud streaming redirects
"cloud/how-tos/stream_values.md": "cloud/how-tos/streaming.md#stream-graph-state",
"cloud/how-tos/stream_updates.md": "cloud/how-tos/streaming.md#stream-graph-state",
"cloud/how-tos/stream_messages.md": "cloud/how-tos/streaming.md#messages",
"cloud/how-tos/stream_events.md": "cloud/how-tos/streaming.md#stream-events",
"cloud/how-tos/stream_debug.md": "cloud/how-tos/streaming.md#debug",
"cloud/how-tos/stream_multiple.md": "cloud/how-tos/streaming.md#stream-multiple-modes",
# prebuit redirects
"how-tos/create-react-agent.ipynb": "agents/agents.md#basic-configuration",
"how-tos/create-react-agent-memory.ipynb": "agents/memory.md",
"how-tos/create-react-agent-system-prompt.ipynb": "agents/context.md#prompts",
"how-tos/create-react-agent-hitl.ipynb": "agents/human-in-the-loop.md",
"how-tos/create-react-agent-structured-output.ipynb": "agents/agents.md#structured-output",
# Time-travel
"how-tos/human_in_the_loop/edit-graph-state.ipynb": "how-tos/human_in_the_loop/time-travel.ipynb",
# breakpoints
"how-tos/human_in_the_loop/dynamic_breakpoints.ipynb": "how-tos/human_in_the_loop/breakpoints.ipynb",
# misc
"prebuilt.md": "agents/prebuilt.md",
"reference/prebuilt.md": "reference/agents.md",
"concepts/high_level.md": "index.md",
"concepts/index.md": "index.md",
"concepts/v0-human-in-the-loop.md": "concepts/human-in-the-loop.md",
"how-tos/index.md": "index.md",
"tutorials/introduction.ipynb": "concepts/why-langgraph.md",
# deployment redirects
"how-tos/deploy-self-hosted.md": "cloud/deployment/self_hosted_data_plane.md",
"concepts/self_hosted.md": "concepts/langgraph_self_hosted_data_plane.md",
# assistant redirects
"cloud/how-tos/assistant_versioning.md": "cloud/how-tos/configuration_cloud.md",
}
@@ -298,7 +220,7 @@ 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 +236,6 @@ 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 +252,4 @@ 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)
+2 -28
View File
@@ -5,7 +5,6 @@ import os
import json
import click
import nbformat
import re
logger = logging.getLogger(__name__)
NOTEBOOK_DIRS = ("docs/how-tos","docs/tutorials")
@@ -21,6 +20,7 @@ BLOCKLIST_COMMANDS = (
NOTEBOOKS_NO_CASSETTES = (
"docs/how-tos/visualization.ipynb",
"docs/how-tos/many-tools.ipynb"
)
NOTEBOOKS_NO_EXECUTION = [
@@ -49,10 +49,7 @@ NOTEBOOKS_NO_EXECUTION = [
"docs/how-tos/map-reduce.ipynb", # flakiness from structured output, only when running with VCR
"docs/tutorials/tot/tot.ipynb",
"docs/how-tos/visualization.ipynb",
"docs/how-tos/streaming-specific-nodes.ipynb",
"docs/tutorials/llm-compiler/LLMCompiler.ipynb",
"docs/tutorials/customer-support/customer-support.ipynb", # relies on openai embeddings, doesn't play well w/ VCR
"docs/how-tos/many-tools.ipynb", # relies on openai embeddings, doesn't play well w/ VCR
"docs/tutorials/llm-compiler/LLMCompiler.ipynb"
]
@@ -89,11 +86,6 @@ def has_blocklisted_command(code: str, metadata: dict) -> bool:
return True
return False
MERMAID_PATTERN = re.compile(r'display\(Image\((\w+)\.get_graph\(\)\.draw_mermaid_png\(\)\)\)')
def remove_mermaid(code: str) -> str:
return MERMAID_PATTERN.sub('print()', code)
def add_vcr_to_notebook(
notebook: nbformat.NotebookNode, cassette_prefix: str
@@ -107,8 +99,6 @@ def add_vcr_to_notebook(
continue
lines = cell.source.splitlines()
# remove the special tag for hidden cells
lines = [line for line in lines if not line.strip().startswith("# hide-cell")]
# skip if empty cell
if not lines:
continue
@@ -190,20 +180,6 @@ def add_vcr_to_notebook(
return notebook
def remove_mermaid_from_notebook(notebook: nbformat.NotebookNode) -> nbformat.NotebookNode:
for cell in notebook.cells:
if cell.cell_type != "code":
continue
cell.source = remove_mermaid(cell.source)
# skip the cell entirely if it contains PYPPETEER
if "PYPPETEER" in cell.source:
cell.source = ""
return notebook
def process_notebooks(should_comment_install_cells: bool) -> None:
for directory in NOTEBOOK_DIRS:
for root, _, files in os.walk(directory):
@@ -225,8 +201,6 @@ def process_notebooks(should_comment_install_cells: bool) -> None:
notebook, cassette_prefix=cassette_prefix
)
notebook = remove_mermaid_from_notebook(notebook)
if notebook_path in NOTEBOOKS_NO_EXECUTION:
# Add a cell at the beginning to indicate that this notebook should not be executed
warning_cell = nbformat.v4.new_markdown_cell(
@@ -9,7 +9,10 @@ import yaml
MARKDOWN = """\
[//]: # (This file is automatically generated using a script in docs/_scripts. Do not edit this file directly!)
# Community Agents
# 🚀 Prebuilt Agents
LangGraph includes a prebuilt React agent. For more information on how to use it,
check out our [how-to guides](https://langchain-ai.github.io/langgraph/how-tos/#prebuilt-react-agent).
If youre looking for other prebuilt libraries, explore the community-built options
below. These libraries can extend LangGraph's functionality in various ways.
@@ -0,0 +1 @@
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@@ -1 +1 @@
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@@ -1 +1 @@
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