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Author SHA1 Message Date
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
904 changed files with 116393 additions and 115337 deletions
+12 -12
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@@ -1,29 +1,29 @@
name: "\U0001F41B Bug Report"
description: Report a bug in LangGraph. To report a security issue, please instead use the security option below. For questions, please use the LangChain Forum at forum.langchain.com.
labels: [pending,bug]
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: ["02 Bug Report"]
body:
- type: markdown
attributes:
value: |
value: >
Thank you for taking the time to file a bug report.
Use this to report BUGS in LangGraph. For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
Use this to report BUGS in LangGraph. For usage questions, feature requests and general design questions, please use [GitHub Discussions](https://github.com/langchain-ai/langgraph/discussions).
Relevant links to check before filing a bug report to see if your issue has already been reported, fixed or
if there's another way to solve your problem:
* [LangChain Forum](https://forum.langchain.com/),
* [LangGraph Github Issues](https://github.com/langchain-ai/langgraph/issues),
* [LangGraph how-to guides](https://langchain-ai.github.io/langgraph/how-tos/).
* [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
* [GitHub search](https://github.com/langchain-ai/langgraph),
[LangGraph Github Discussions](https://github.com/langchain-ai/langgraph/discussions),
[LangGraph Github Issues](https://github.com/langchain-ai/langgraph/issues),
[LangGraph how-to guides](https://langchain-ai.github.io/langgraph/how-tos/).
[LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
[GitHub search](https://github.com/langchain-ai/langgraph),
- type: checkboxes
id: checks
attributes:
label: Checked other resources
description: Before submitting this issue, please confirm that you have completed all the steps below by checking each option. These steps help ensure your issue is well-defined, relevant, and actionable.
options:
- label: This is a bug, not a usage question. For questions, please use the LangChain Forum (https://forum.langchain.com/).
- label: This is a bug, not a usage question. For questions, please use GitHub Discussions.
required: true
- label: I added a clear and detailed title that summarizes the issue.
required: true
@@ -38,7 +38,7 @@ body:
attributes:
label: Example Code
description: |
Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case. Replace this code with your own!
Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case.
placeholder: |
from langgraph.graph import StateGraph
@@ -78,7 +78,7 @@ body:
attributes:
label: System Info
description: |
Run on your machine: `python -m langchain_core.sys_info`
python -m langchain_core.sys_info
placeholder: |
python -m langchain_core.sys_info
validations:
+12 -3
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@@ -1,6 +1,15 @@
blank_issues_enabled: false
version: 2.1
contact_links:
- name: LangChain Forum
url: https://forum.langchain.com/
about: General community discussions, support, and feature requests
- name: 🤔 Question or Problem
about: Ask a question or ask about a problem in GitHub Discussions.
url: https://github.com/langchain-ai/langgraph/discussions/categories/q-a
- name: Feature Request
url: https://github.com/langchain-ai/langgraph/discussions/categories/ideas
about: Suggest a feature or an idea
- name: Show and tell
about: Show what you built with LangChain
url: https://github.com/langchain-ai/langgraph/discussions/categories/show-and-tell
- name: Slack
url: https://www.langchain.com/join-community
about: General community discussions
+1 -1
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@@ -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
+8 -12
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@@ -1,29 +1,25 @@
name: 🔒 Privileged
description: You are a LangGraph maintainer, or was asked directly by a maintainer to create an issue here. If not, check the other options.
description: You are a LangChain maintainer, or was asked directly by a maintainer to create an issue here. If not, check the other options.
body:
- type: markdown
attributes:
value: |
Thanks for your interest in LangGraph! 🚀
If you are not a LangGraph maintainer or were not asked directly by a maintainer to create an issue, then please start the conversation on the [LangChain Forum](https://forum.langchain.com/) instead.
You are a LangGraph maintainer if you maintain any of the packages inside of the LangGraph repository
or are a regular contributor to LangGraph with previous merged merged pull requests.
Thanks for your interest in LangChain! 🚀
If you are not a LangChain maintainer or were not asked directly by a maintainer to create an issue, then please start the conversation in a [Question in GitHub Discussions](https://github.com/langchain-ai/langchain/discussions/categories/q-a) instead.
You are a LangChain maintainer if you maintain any of the packages inside of the LangChain repository
or are a regular contributor to LangChain with previous merged merged pull requests.
- type: checkboxes
id: privileged
attributes:
label: Privileged issue
description: Confirm that you are allowed to create an issue here.
options:
- label: I am a LangGraph maintainer, or was asked directly by a LangGraph maintainer to create an issue here.
- label: I am a LangChain maintainer, or was asked directly by a LangChain maintainer to create an issue here.
required: true
- type: textarea
id: content
attributes:
label: Issue Content
description: Add the content of the issue here.
- type: markdown
attributes:
value: |
Community members should **NOT** work on Privileged issues unless these issues have been explicitly marked with a "help-wanted" tag.
-31
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@@ -1,31 +0,0 @@
Thank you for contributing to LangGraph! Follow these steps to mark your pull request as ready for review. **If any of these steps are not completed, your PR will not be considered for review.**
- [ ] **PR title**: Follows the format: {TYPE}({SCOPE}): {DESCRIPTION}
- Examples:
- feat(core): add multi-tenant support
- fix(cli): resolve flag parsing error
- docs(openai): update API usage examples
- Allowed `{TYPE}` values:
- feat, fix, docs, style, refactor, perf, test, build, ci, chore, revert, release
- Allowed `{SCOPE}` values (optional):
- langgraph, docs, cli, checkpoint, checkpoint-postgres, checkpoint-sqlite, prebuilt, scheduler-kafka, sdk-py
- Once you've written the title, please delete this checklist item; do not include it in the PR.
- [ ] **PR message**: ***Delete this entire checklist*** and replace with
- **Description:** a description of the change. Include a [closing keyword](https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword) if applicable.
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: If you're adding a new integration, you must include:
1. A test for the integration, preferably unit tests that do not rely on network access,
2. An example notebook showing its use. It lives in `docs/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. We will not consider a PR unless these three are passing in CI. See [contribution guidelines](https://github.com/langchain-ai/langgraph/blob/main/CONTRIBUTING.md) for more.
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to `pyproject.toml` files (even optional ones) unless they are **required** for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
+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') }}
-18
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@@ -1,18 +0,0 @@
version: 2
updates:
- package-ecosystem: "github-actions"
directory: "/"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directories:
- "libs/checkpoint"
- "libs/checkpoint-postgres"
- "libs/checkpoint-sqlite"
- "libs/cli"
- "libs/langgraph"
- "libs/prebuilt"
- "libs/sdk-py"
schedule:
interval: "weekly"
+2 -7
View File
@@ -1,15 +1,10 @@
import ast
import os
from itertools import filterfalse
from typing import Dict, List, Tuple
from typing import List, Tuple
ROOT_PATH = os.path.abspath(os.path.join(__file__, "..", "..", ".."))
CLIENT_PATH = os.path.join(ROOT_PATH, "libs", "sdk-py", "langgraph_sdk", "client.py")
ASYNC_TO_SYNC_METHOD_MAP: Dict[str, str] = {
"aclose": "close",
"__aenter__": "__enter__",
"__aexit__": "__exit__",
}
def get_class_methods(node: ast.ClassDef) -> List[str]:
@@ -27,7 +22,7 @@ def find_classes(tree: ast.AST) -> List[Tuple[str, List[str]]]:
def compare_sync_async_methods(sync_methods: List[str], async_methods: List[str]) -> List[str]:
sync_set = set(sync_methods)
async_set = {ASYNC_TO_SYNC_METHOD_MAP.get(async_method, async_method) for async_method in async_methods}
async_set = set(async_methods)
missing_in_sync = list(async_set - sync_set)
missing_in_async = list(sync_set - async_set)
return missing_in_sync + missing_in_async
+86 -124
View File
@@ -1,145 +1,107 @@
import asyncio
import json
import os
import pathlib
import sys
import time
from urllib import request, error
import langgraph_cli
import langgraph_cli.config
import langgraph_cli.docker
from langgraph_cli.cli import prepare_args_and_stdin
from langgraph_cli.constants import DEFAULT_PORT
import langgraph_cli.config
from langgraph_cli.exec import Runner, subp_exec
from langgraph_cli.progress import Progress
from langgraph_cli.constants import DEFAULT_PORT
def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
"""Spin up API with Postgres/Redis via docker compose and wait until ready."""
def test(
config: pathlib.Path,
port: int,
tag: str,
verbose: bool,
):
with Runner() as runner, Progress(message="Pulling...") as set:
# Detect docker/compose capabilities
# check docker available
capabilities = langgraph_cli.docker.check_capabilities(runner)
# Validate config and prepare compose stdin/args using built image
# open config
config_json = langgraph_cli.config.validate_config_file(config)
args, stdin = prepare_args_and_stdin(
capabilities=capabilities,
config_path=config,
config=config_json,
docker_compose=None,
port=port,
watch=False,
debugger_port=None,
debugger_base_url=f"http://127.0.0.1:{port}",
postgres_uri=None,
api_version=None,
image=tag,
base_image=None,
)
# Compose up with wait (implies detach), similar to `langgraph up --wait`
args_up = [*args, "up", "--remove-orphans", "--wait"]
set("Running...")
args = [
"run",
"--rm",
"-p",
f"{port}:8000",
]
if isinstance(config_json["env"], str):
args.extend(
[
"--env-file",
str(config.parent / config_json["env"]),
]
)
else:
for k, v in config_json["env"].items():
args.extend(
[
"-e",
f"{k}={v}",
]
)
if capabilities.healthcheck_start_interval:
args.extend(
[
"--health-interval",
"5s",
"--health-retries",
"1",
"--health-start-period",
"10s",
"--health-start-interval",
"1s",
]
)
else:
args.extend(
[
"--health-interval",
"5s",
"--health-retries",
"2",
]
)
compose_cmd = ["docker", "compose"]
if capabilities.compose_type == "standalone":
compose_cmd = ["docker-compose"]
_task = None
def on_stdout(line: str):
nonlocal _task
if "GET /ok" in line or "Uvicorn running on" in line:
set("")
sys.stdout.write(
f"""Ready!
- API: http://localhost:{port}
"""
)
sys.stdout.flush()
_task.cancel()
return True
return False
async def subp_exec_task(*args, **kwargs):
nonlocal _task
_task = asyncio.create_task(subp_exec(*args, **kwargs))
await _task
set("Starting...")
try:
runner.run(
subp_exec(
*compose_cmd,
*args_up,
input=stdin,
subp_exec_task(
"docker",
*args,
tag,
verbose=verbose,
on_stdout=on_stdout,
)
)
except Exception as e: # noqa: BLE001
# On failure, show diagnostics then ensure clean teardown
sys.stderr.write(f"docker compose up failed: {e}\n")
try:
sys.stderr.write("\n== docker compose ps ==\n")
runner.run(subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=False))
except Exception:
pass
try:
sys.stderr.write("\n== docker compose logs (api) ==\n")
runner.run(
subp_exec(
*compose_cmd,
*args,
"logs",
"langgraph-api",
input=stdin,
verbose=False,
)
)
except Exception:
pass
finally:
try:
runner.run(
subp_exec(
*compose_cmd,
*args,
"down",
"-v",
"--remove-orphans",
input=stdin,
verbose=False,
)
)
finally:
raise
set("")
base_url = f"http://localhost:{port}"
ok_url = f"{base_url}/ok"
print(f"Waiting for {ok_url} to respond with 200...")
deadline = time.time() + 30
last_err: Exception | None = None
while time.time() < deadline:
try:
with request.urlopen(ok_url, timeout=2) as resp:
if resp.status == 200:
sys.stdout.write(
f"""Ready!\n- API: {base_url}\n- /ok: 200 OK\n"""
)
sys.stdout.flush()
break
else:
last_err = RuntimeError(f"Unexpected status: {resp.status}")
print(f"Unexpected status: {resp.status}")
except error.URLError as e:
last_err = e
except Exception as e: # noqa: BLE001
last_err = e
time.sleep(0.5)
else:
# Bring stack down before raising
args_down = [*args, "down", "-v", "--remove-orphans"]
try:
runner.run(
subp_exec(
*compose_cmd,
*args_down,
input=stdin,
verbose=verbose,
)
)
finally:
raise SystemExit(
f"/ok did not return 202 within timeout. Last error: {last_err}"
)
# Clean up: bring compose stack down to free ports for next test
args_down = [*args, "down", "-v", "--remove-orphans"]
runner.run(
subp_exec(
*compose_cmd,
*args_down,
input=stdin,
verbose=verbose,
)
)
except asyncio.CancelledError:
pass
if __name__ == "__main__":
@@ -148,6 +110,6 @@ if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("-t", "--tag", type=str)
parser.add_argument("-c", "--config", type=str, default="./langgraph.json")
parser.add_argument("-p", "--port", type=int, default=DEFAULT_PORT)
parser.add_argument("-p", "--port", default=DEFAULT_PORT)
args = parser.parse_args()
test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
+12 -51
View File
@@ -3,8 +3,8 @@ name: CLI integration test
on:
workflow_call:
permissions:
contents: read
env:
POETRY_VERSION: "1.7.1"
jobs:
build:
@@ -25,14 +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
@@ -43,43 +42,28 @@ jobs:
- name: Build and test service A
if: steps.changed-files.outputs.all
working-directory: libs/cli/examples
env:
LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
run: |
# The build-arg isn't used; just testing that we accept other args
langgraph build -t langgraph-test-a
cp .env.example .env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
langgraph build -t langgraph-test-a --base-image "langchain/langgraph-trial"
cp .env.example .envg
timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -c langgraph.json -t langgraph-test-a
- name: Build and test service B
if: steps.changed-files.outputs.all
working-directory: libs/cli/examples/graphs
env:
LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
run: |
langgraph build -t langgraph-test-b
cp ../.env.example .env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
langgraph build -t langgraph-test-b --base-image "langchain/langgraph-trial"
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-b
- name: Build and test service C
if: steps.changed-files.outputs.all
working-directory: libs/cli/examples/graphs_reqs_a
env:
LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
run: |
langgraph build -t langgraph-test-c
cp ../.env.example .env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
langgraph build -t langgraph-test-c --base-image "langchain/langgraph-trial"
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-c
- name: Build and test service D
if: steps.changed-files.outputs.all
working-directory: libs/cli/examples/graphs_reqs_b
env:
LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
run: |
langgraph build -t langgraph-test-d
cp ../.env.example .env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
langgraph build -t langgraph-test-d --base-image "langchain/langgraph-trial"
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-d
- name: Build JS service
@@ -87,27 +71,4 @@ jobs:
working-directory: libs/cli/js-examples
run: |
langgraph build -t langgraph-test-e
- name: Build JS monorepo service
if: steps.changed-files.outputs.all
working-directory: libs/cli/js-monorepo-example
run: |
langgraph build -t langgraph-test-f -c apps/agent/langgraph.json --build-command "yarn run turbo build" --install-command "yarn install"
- name: Build Python monorepo service
if: steps.changed-files.outputs.all
working-directory: libs/cli/python-monorepo-example
run: |
langgraph build -t langgraph-test-g -c apps/agent/langgraph.json
cp apps/agent/.env.example apps/agent/.env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> apps/agent/.env; fi
timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-g -c apps/agent/langgraph.json
- name: Build and test prerelease reqs service
if: steps.changed-files.outputs.all
working-directory: libs/cli/examples/graph_prerelease_reqs
run: |
langgraph build -t langgraph-test-h
cp ../.env.example .env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-h
+41 -13
View File
@@ -8,10 +8,9 @@ on:
type: string
description: "From which folder this pipeline executes"
permissions:
contents: read
env:
POETRY_VERSION: "1.7.1"
# This env var allows us to get inline annotations when ruff has complaints.
RUFF_OUTPUT_FORMAT: github
@@ -37,28 +36,48 @@ jobs:
uses: Ana06/get-changed-files@v2.3.0
with:
filter: "${{ 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
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
@@ -73,18 +92,27 @@ 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 }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}
- name: Analysing tests with our lint
if: steps.changed-files.outputs.all
+16 -8
View File
@@ -8,8 +8,8 @@ on:
type: string
description: "From which folder this pipeline executes"
permissions:
contents: read
env:
POETRY_VERSION: "1.7.1"
jobs:
build:
@@ -26,12 +26,12 @@ jobs:
name: "test #${{ 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 }}
@@ -39,15 +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: ${{ inputs.working-directory }}
run: make test
run: |
make test
- name: Ensure the tests did not create any additional files
shell: bash
+10 -8
View File
@@ -3,8 +3,8 @@ name: test
on:
workflow_call:
permissions:
contents: read
env:
POETRY_VERSION: "1.7.1"
jobs:
build:
@@ -24,12 +24,12 @@ jobs:
name: "test #${{ 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 }}
@@ -39,11 +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
+8 -10
View File
@@ -9,11 +9,9 @@ on:
description: "From which folder this pipeline executes"
env:
POETRY_VERSION: "1.7.1"
PYTHON_VERSION: "3.10"
permissions:
contents: read
jobs:
build:
if: github.ref == 'refs/heads/main'
@@ -26,12 +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.
@@ -45,7 +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
@@ -59,8 +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)" >> $GITHUB_OUTPUT
publish:
needs:
@@ -0,0 +1,57 @@
name: test
on:
workflow_call:
env:
POETRY_VERSION: "1.7.1"
jobs:
build:
runs-on: ubuntu-latest
strategy:
matrix:
python-version:
- "3.11"
- "3.12"
defaults:
run:
working-directory: libs/scheduler-kafka
name: "test #${{ 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'
+7 -7
View File
@@ -7,8 +7,8 @@ on:
paths:
- "libs/**"
permissions:
contents: read
env:
POETRY_VERSION: "1.7.1"
jobs:
benchmark:
@@ -19,14 +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
+8 -8
View File
@@ -5,8 +5,8 @@ on:
paths:
- "libs/**"
permissions:
contents: read
env:
POETRY_VERSION: "1.7.1"
jobs:
benchmark:
@@ -21,14 +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: ${{ env.POETRY_VERSION }}
cache-key: bench
- name: Install dependencies
run: uv sync --group dev
run: poetry install --with dev
- name: Download baseline
uses: actions/cache/restore@v4
with:
@@ -53,7 +53,7 @@ jobs:
echo 'OUTPUT<<EOF'
mv out/benchmark-baseline.json out/main.json
mv out/benchmark.json out/changes.json
uv run pyperf compare_to out/main.json out/changes.json --table --group-by-speed
poetry run pyperf compare_to out/main.json out/changes.json --table --group-by-speed
echo EOF
} >> "$GITHUB_OUTPUT"
- name: Annotation
+81 -22
View File
@@ -3,13 +3,9 @@ name: CI
on:
push:
branches:
- main
branches: [main]
pull_request:
permissions:
contents: read
# If another push to the same PR or branch happens while this workflow is still running,
# cancel the earlier run in favor of the next run.
#
@@ -20,12 +16,15 @@ concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
env:
POETRY_VERSION: "1.7.1"
jobs:
changes:
runs-on: ubuntu-latest
outputs:
python: ${{ steps.filter.outputs.python }}
deps: ${{ steps.filter.outputs.deps }}
sdk-js: ${{ steps.filter.outputs.sdk-js }}
steps:
- uses: actions/checkout@v4
- uses: dorny/paths-filter@v3
@@ -39,10 +38,10 @@ jobs:
- 'libs/checkpoint/**'
- 'libs/checkpoint-sqlite/**'
- 'libs/checkpoint-postgres/**'
- 'libs/scheduler-kafka/**'
- 'libs/prebuilt/**'
deps:
- '**/pyproject.toml'
- '**/uv.lock'
sdk-js:
- 'libs/sdk-js/**'
lint:
needs: changes
@@ -57,10 +56,10 @@ jobs:
"libs/checkpoint",
"libs/checkpoint-sqlite",
"libs/checkpoint-postgres",
"libs/scheduler-kafka",
"libs/prebuilt",
]
if: needs.changes.outputs.python == 'true' || needs.changes.outputs.deps == 'true'
if: needs.changes.outputs.python == 'true'
uses: ./.github/workflows/_lint.yml
with:
working-directory: ${{ matrix.working-directory }}
@@ -78,9 +77,8 @@ jobs:
"libs/checkpoint-sqlite",
"libs/checkpoint-postgres",
"libs/prebuilt",
"libs/sdk-py",
]
if: needs.changes.outputs.python == 'true' || needs.changes.outputs.deps == 'true'
if: needs.changes.outputs.python == 'true'
uses: ./.github/workflows/_test.yml
with:
working-directory: ${{ matrix.working-directory }}
@@ -89,11 +87,19 @@ jobs:
# NOTE: we're testing langgraph separately because it requires a different matrix
test-langgraph:
needs: changes
if: needs.changes.outputs.python == 'true' || needs.changes.outputs.deps == 'true'
if: needs.changes.outputs.python == 'true'
name: "cd libs/langgraph"
uses: ./.github/workflows/_test_langgraph.yml
secrets: inherit
# NOTE: we're testing scheduler-kafka separately because it requires a different matrix
test-scheduler-kafka:
needs: changes
if: needs.changes.outputs.python == 'true'
name: "cd libs/scheduler-kafka"
uses: ./.github/workflows/_test_scheduler_kafka.yml
secrets: inherit
check-sdk-methods:
needs: changes
if: needs.changes.outputs.python == 'true'
@@ -119,26 +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
@@ -146,21 +152,74 @@ jobs:
integration-test:
needs: changes
if: needs.changes.outputs.python == 'true' || needs.changes.outputs.deps == 'true'
if: needs.changes.outputs.python == 'true'
name: CLI integration test
uses: ./.github/workflows/_integration_test.yml
secrets: inherit
lint-js:
needs: changes
if: needs.changes.outputs.sdk-js == 'true'
runs-on: ubuntu-latest
strategy:
matrix:
working-directory:
- "libs/sdk-js"
defaults:
run:
working-directory: ${{ matrix.working-directory }}
steps:
- uses: actions/checkout@v3
- name: Setup Node.js (LTS)
uses: actions/setup-node@v3
with:
node-version: "20"
cache: "yarn"
cache-dependency-path: ${{ matrix.working-directory }}/yarn.lock
- name: Install dependencies
run: yarn install
- name: Run lint
run: yarn lint
- name: Build
run: yarn build
test-js:
needs: changes
if: needs.changes.outputs.sdk-js == 'true'
runs-on: ubuntu-latest
strategy:
matrix:
working-directory:
- "libs/sdk-js"
defaults:
run:
working-directory: ${{ matrix.working-directory }}
steps:
- uses: actions/checkout@v3
- name: Setup Node.js (LTS)
uses: actions/setup-node@v3
with:
node-version: "20"
cache: "yarn"
cache-dependency-path: ${{ matrix.working-directory }}/yarn.lock
- name: Install dependencies
run: yarn install
- name: Run tests
run: yarn test
ci_success:
name: "CI Success"
needs:
[
lint,
lint-js,
test,
test-langgraph,
test-scheduler-kafka,
check-sdk-methods,
check-schema,
integration-test,
test-js,
]
if: |
always()
@@ -1,11 +0,0 @@
LangChain
LangGraph
LangSmith
thead
stdio
nd
jupyter
lets
lite
uis
deque
+3 -9
View File
@@ -34,16 +34,10 @@
id: extract_ignore_words
- name: Codespell
uses: codespell-project/actions-codespell@v2.1
uses: codespell-project/actions-codespell@v2
with:
skip: '*.ambr,*.lock,*.ipynb,*.yaml,*.zlib,*.css.map,*.js.map'
skip: '*.ambr,*.lock,*.ipynb,*.yaml,*.zlib,*.md'
ignore_words_list: ${{ steps.extract_ignore_words.outputs.ignore_words_list }}
# We do this to avoid spellchecking cell outputs
- name: Codespell Notebooks
run: make codespell
- name: Codespell LangGraph Library
run: |
# Change to root directory to check the main LangGraph library
cd ..
codespell --skip="*.ambr,*.lock,*.ipynb,*.yaml,*.zlib,*.css.map,*.js.map,*.pyc,__pycache__/*" --ignore-words-list="${{ steps.extract_ignore_words.outputs.ignore_words_list }}" libs/langgraph/langgraph/
run: make codespell
+20 -10
View File
@@ -9,6 +9,9 @@ on:
- main
workflow_dispatch:
env:
POETRY_VERSION: "1.7.1"
permissions:
contents: read
pages: write
@@ -35,7 +38,15 @@ jobs:
with:
filter: "docs/docs/**"
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
runs-on: ubuntu-latest
timeout-minutes: 10 # Job will be cancelled if it runs for more than 10 minutes
env:
@@ -45,21 +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
@@ -87,11 +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/.*" \
@@ -116,7 +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/.*" \
@@ -136,7 +146,7 @@ jobs:
- name: Configure GitHub Pages
if: github.ref == 'refs/heads/main'
uses: actions/configure-pages@v5
uses: actions/configure-pages@v4
- name: Upload Pages Artifact
# if: github.ref == 'refs/heads/main'
+7 -7
View File
@@ -11,8 +11,8 @@ on:
- cron: "0 5 * * *"
workflow_dispatch:
permissions:
contents: read
env:
POETRY_VERSION: "1.7.1"
jobs:
markdown-link-check:
@@ -42,8 +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
-45
View File
@@ -1,45 +0,0 @@
name: PR Title Lint
permissions:
pull-requests: read
on:
pull_request:
types: [opened, edited, synchronize]
jobs:
lint-pr-title:
runs-on: ubuntu-latest
steps:
- name: Validate PR Title
uses: amannn/action-semantic-pull-request@v5
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
types: |
feat
fix
docs
style
refactor
perf
test
build
ci
chore
revert
release
scopes: |
checkpoint
checkpoint-postgres
checkpoint-sqlite
cli
langgraph
prebuilt
scheduler-kafka
sdk-py
docs
ci
requireScope: false
ignoreLabels: |
ignore-lint-pr-title
+26 -36
View File
@@ -8,11 +8,9 @@ on:
type: string
default: "libs/langgraph"
permissions:
contents: read
env:
PYTHON_VERSION: "3.11"
POETRY_VERSION: "1.7.1"
jobs:
build:
@@ -28,12 +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.
@@ -47,7 +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
@@ -61,14 +59,8 @@ jobs:
shell: bash
working-directory: ${{ inputs.working-directory }}
run: |
PKG_NAME=$(grep -m 1 "^name = " pyproject.toml | cut -d '"' -f 2)
if grep -q 'dynamic.*=.*\[.*"version".*\]' pyproject.toml; then
# handle dynamic versioning
DIR_NAME=$(echo "$PKG_NAME" | tr '-' '_')
VERSION=$(grep -m 1 '^__version__' "${DIR_NAME}/__init__.py" | cut -d '"' -f 2)
else
VERSION=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
fi
PKG_NAME="$(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"
@@ -143,9 +135,7 @@ jobs:
needs:
- build
- release-notes
permissions:
contents: read
id-token: write
permissions: write-all
uses: ./.github/workflows/_test_release.yml
with:
working-directory: ${{ inputs.working-directory }}
@@ -173,11 +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: ${{ env.POETRY_VERSION }}
- name: Import published package
shell: bash
@@ -195,18 +185,18 @@ jobs:
# - attempt install again after 5 seconds if it fails because there is
# sometimes a delay in availability on test pypi
run: |
uv run pip install \
poetry run pip install \
--extra-index-url https://test.pypi.org/simple/ \
"$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
@@ -219,10 +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.
@@ -233,7 +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"
@@ -263,12 +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:
@@ -304,12 +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:
+38
View File
@@ -0,0 +1,38 @@
name: JS Release
on:
workflow_dispatch:
jobs:
publish:
# Disallow publishing from branches that aren't `main`.
if: github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
strategy:
matrix:
working-directory:
- "libs/sdk-js"
defaults:
run:
working-directory: ${{ matrix.working-directory }}
steps:
- uses: actions/checkout@v4
# JS Build
- name: Use Node.js
uses: actions/setup-node@v3
with:
node-version: "20"
cache: "yarn"
cache-dependency-path: ${{ matrix.working-directory }}/yarn.lock
- name: Install dependencies
run: yarn install
- name: Build
run: yarn build
- name: Publish package to NPM
run: |
echo "//registry.npmjs.org/:_authToken=${{ secrets.NPM_TOKEN }}" > .npmrc
npm publish
+10 -13
View File
@@ -9,10 +9,7 @@ on:
type: string
description: "JSON string of changed files"
schedule:
- cron: "0 13 * * *"
permissions:
contents: read
- cron: '0 13 * * *'
defaults:
run:
@@ -30,30 +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
-45
View File
@@ -1,45 +0,0 @@
name: UV Lock Upgrade
on:
schedule:
# run at midnight every Sunday
- cron: '0 0 * * 0'
# allow manual triggering
workflow_dispatch:
permissions:
contents: write
pull-requests: write
jobs:
upgrade-dependencies:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Set up uv
uses: astral-sh/setup-uv@v6
with:
# use minimum supported Python version
python-version: "3.9"
enable-cache: true
cache-suffix: "uv-lock-upgrade"
- name: Run uv lock --upgrade in all Python packages
run: make lock-upgrade
- name: Create Pull Request
uses: peter-evans/create-pull-request@v7
with:
token: ${{ secrets.GITHUB_TOKEN }}
commit-message: "chore[deps]: upgrade dependencies with `uv lock --upgrade`"
title: "chore[deps]: upgrade dependencies with `uv lock --upgrade`"
body: |
This PR updates the dependencies in all Python packages using `uv lock --upgrade`.
This is an automated PR created by the UV Lock Upgrade workflow.
branch: deps/uv-lock-upgrade
delete-branch: true
labels: |
dependencies
-2
View File
@@ -180,5 +180,3 @@ Chinook.db
.vercel
.turbo
.editorconfig
.scratch
-55
View File
@@ -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.
+12 -12
View File
@@ -9,7 +9,7 @@ Here are some things to keep in mind for all types of contributions:
- Follow the ["fork and pull request"](https://docs.github.com/en/get-started/exploring-projects-on-github/contributing-to-a-project) workflow.
- Fill out the checked-in pull request template when opening pull requests. Note related issues and tag relevant maintainers.
- Ensure your PR passes formatting, linting, and testing checks before requesting a review.
- If you would like comments or feedback, please tag a maintainer.
- If you would like comments or feedback, please open an issue or discussion and tag a maintainer.
- Backwards compatibility is key. Your changes must not be breaking, except in case of critical bug and security fixes.
- Look for duplicate PRs or issues that have already been opened before opening a new one.
- Keep scope as isolated as possible. As a general rule, your changes should not affect more than one package at a time.
@@ -20,7 +20,7 @@ For bug fixes, please open up an issue before proposing a fix to ensure the prop
### New features
For new features, please start a new [discussion](https://forum.langchain.com/), where the maintainers will help with scoping out the necessary changes.
For new features, please start a new [discussion](https://github.com/langchain-ai/langgraph/discussions), where the maintainers will help with scoping out the necessary changes.
## Contribute Documentation
@@ -60,7 +60,7 @@ In LangGraph, these are often higher level guides that show off end-to-end use c
Some examples include:
- [Build a Customer Support Bot](https://langchain-ai.github.io/langgraph/tutorials/customer-support/customer-support/)
- [Build a SQL Agent](https://langchain-ai.github.io/langgraph/tutorials/sql/sql-agent/)
- [Build a SQL Agent](https://langchain-ai.github.io/langgraph/tutorials/sql-agent/)
Here are some high-level tips on writing a good tutorial:
@@ -109,7 +109,8 @@ 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:
@@ -152,7 +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
@@ -186,9 +187,9 @@ Be concise, including in code samples.
## Setup
LangGraph documentation consists of two components:
LangChain documentation consists of two components:
1. Main Documentation: Hosted at [https://langchain-ai.github.io/langgraph/](https://langchain-ai.github.io/langgraph/),
1. Main Documentation: Hosted at [https://langchain-ai.github.io](https://langchain-ai.github.io/langgraph/),
this comprehensive resource serves as the primary user-facing documentation.
It covers a wide array of topics, including tutorials, use cases, integrations,
and more, offering extensive guidance on building with LangGraph.
@@ -226,7 +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
```
@@ -249,17 +249,17 @@ make serve-docs
#### Linting
To spell check the docs, run the following from the `docs` directory:
The documentation is linted from the **monorepo root**. To lint it, run the following from there:
```bash
codespell --skip="*.ambr,*.lock,*.ipynb,*.yaml,*.zlib,*.css.map,*.js.map" --ignore-words-list="infor,thead,stdio,nd,jupyter,lets,lite,uis,deque" .
make spellcheck
```
### In-code Documentation
The in-code documentation is autogenerated from docstrings.
For the API reference to be useful, the codebase must be well-documented. This means that all functions, classes, and methods should have a docstring that explains what they do, what the arguments are, and what the return value is. This is a good practice in general, but it is especially important for LangGraph because the API reference is the primary resource for developers to understand how to use the codebase.
For the API reference to be useful, the codebase must be well-documented. This means that all functions, classes, and methods should have a docstring that explains what they do, what the arguments are, and what the return value is. This is a good practice in general, but it is especially important for LangChain because the API reference is the primary resource for developers to understand how to use the codebase.
We generally follow the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html#38-comments-and-docstrings) for docstrings.
@@ -290,4 +290,4 @@ def my_function(arg1: int, arg2: str) -> float:
This is a description of the return value.
"""
return 3.14
```
```
-68
View File
@@ -1,68 +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
# Lock all projects and upgrade dependencies
.PHONY: lock-upgrade
lock-upgrade:
@for dir in $(LIBS_DIRS); do \
if [ -f $$dir/Makefile ]; then \
echo "Running lock-upgrade in $$dir"; \
(cd $$dir && uv lock --upgrade); \
fi; \
done
# Test all projects
.PHONY: test
test:
@for dir in $(LIBS_DIRS); do \
if [ -f $$dir/Makefile ]; then \
echo "Running test in $$dir"; \
$(MAKE) -C $$dir test; \
fi; \
done
+38 -35
View File
@@ -13,71 +13,74 @@
[![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.
> [!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
While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents. To improve your LLM application development, pair LangGraph with:
- [LangSmith](http://www.langchain.com/langsmith) — Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
- [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
- [LangChain](https://python.langchain.com/docs/introduction/) Provides integrations and composable components to streamline LLM application development.
- [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/).
> [!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/examples/): Guided examples on getting started with LangGraph.
- [LangChain Forum](https://forum.langchain.com/): Connect with the community and share all of your technical questions, ideas, and feedback.
- [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
+1
View File
@@ -1,3 +1,4 @@
site/
docs/cloud/reference/sdk/js_ts_sdk_ref.md
.vercel
+27 -22
View File
@@ -1,4 +1,10 @@
.PHONY: lint-docs format-docs build-docs serve-docs serve-clean-docs clean-docs codespell llms-text build-prebuilt tests
.PHONY: lint-docs format-docs build-docs serve-docs serve-clean-docs clean-docs codespell build-typedoc llms-text build-prebuilt tests
build-typedoc:
cd ../libs/sdk-js && yarn install --include-dev && yarn typedoc
cd ../libs/sdk-js && yarn --silent concat-md --decrease-title-levels --ignore=js_ts_sdk_ref.md --start-title-level-at 2 docs > ../../docs/docs/cloud/reference/sdk/js_ts_sdk_ref.md 2>/dev/null
# Add links to the monorepo
sed -e '1,10s|@langchain/langgraph-sdk|[@langchain/langgraph-sdk](https://github.com/langchain-ai/langgraph/tree/main/libs/sdk-js)|g' docs/cloud/reference/sdk/js_ts_sdk_ref.md > temp_file && mv temp_file docs/cloud/reference/sdk/js_ts_sdk_ref.md
build-prebuilt:
# Use to create an update to date prebuilt page.
@@ -6,33 +12,32 @@ build-prebuilt:
# generates the final prebuilt page.
@if [ "$(DOWNLOAD_STATS)" = "true" ]; then \
set -x; \
uv run python -m _scripts.third_party_page.get_download_stats stats.yml; \
poetry run python -m _scripts.third_party_page.get_download_stats stats.yml; \
set +x; \
else \
set -x; \
uv run python -m _scripts.third_party_page.get_download_stats --fake stats.yml; \
poetry run python -m _scripts.third_party_page.get_download_stats --fake stats.yml; \
set +x; \
fi
uv run python -m _scripts.third_party_page.create_third_party_page stats.yml docs/agents/prebuilt.md
poetry run python -m _scripts.third_party_page.create_third_party_page stats.yml docs/prebuilt.md --language python
build-docs: build-prebuilt
TARGET_LANGUAGE=python uv run python -m mkdocs build --clean -f mkdocs.yml --strict
build-docs-js: build-prebuilt
TARGET_LANGUAGE=js uv run python -m mkdocs build --clean -f mkdocs.yml --strict
build-docs: build-typedoc build-prebuilt
poetry run python -m mkdocs build --clean -f mkdocs.yml --strict
llms-text:
uv run python -m _scripts.generate_llms_text docs/llms-full.txt
poetry run python -m _scripts.generate_llms_text docs/llms-full.txt
install-vercel-deps:
curl -sL "https://astral.sh/uv/install.sh" | bash -s
export PATH="${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
@@ -40,10 +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:
uv run python -m mkdocs serve -f mkdocs.yml -w ../libs/langgraph -w ../libs/checkpoint -w ../libs/sdk-py --dirty
serve-docs: build-typedoc
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
@@ -51,13 +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>*
```
```
+157
View File
@@ -0,0 +1,157 @@
"""Add typescript translation to a given markdown file."""
import argparse
import re
import requests
from langchain_anthropic import ChatAnthropic
URL = "https://gist.githubusercontent.com/eyurtsev/e7486731415463a9bc5b4682358859c8/raw/b5a5fda9c7e3387cfcb781f25082814d43675d50/gistfile1.txt"
response = requests.get(URL)
response.raise_for_status()
reference_snippets = response.text
model = ChatAnthropic(model="claude-3-5-sonnet-latest")
def _get_tqdm():
try:
from tqdm import tqdm
except ImportError:
# If not available return a simple identity function
def tqdm(iterable, *args, **kwargs):
return iterable
return tqdm
_tqdm = _get_tqdm()
opening_pattern = re.compile(r"^\s*```python(?:\s+.*)?\s*$")
closing_pattern = re.compile(r"^\s*```\s*$")
def extract_python_snippets(markdown: str) -> list[str]:
"""
Extract all python code blocks (including their fence lines) from the markdown content.
A python block is defined as any block that starts with a line containing an opening fence
with '```python' (optionally with extra parameters) and ends with a closing fence '```'.
"""
snippets = []
inside_block = False
current_snippet = []
for line in markdown.splitlines(keepends=True):
if not inside_block:
if opening_pattern.match(line):
inside_block = True
current_snippet = [line]
else:
current_snippet.append(line)
if closing_pattern.match(line):
inside_block = False
snippets.append("".join(current_snippet))
current_snippet = []
return snippets
def translate_snippet(python_snippet: str) -> str:
"""Translate a python code block into a TypeScript code block using Langchain.
The response is expected to be a properly fenced TypeScript code block (i.e.
starting with ```typescript and ending with ```).
"""
ai_message = model.invoke(
[
{
"role": "system",
"content": (
f"You have access to the following up-to-date example TypeScript code "
f"snippets that show examples of building with langgraph "
f"and langchain:\n\n{reference_snippets}\n\n"
"Use this context to translate the following Python code to equivalent "
"TypeScript. Ensure that your output is a valid fenced TypeScript "
"code block (i.e. starts with ```typescript and ends with ```)."
),
},
{
"role": "user",
"content": f"Translate this Python snippet to TypeScript:\n\n{python_snippet}",
},
]
)
# Use a regular expression to search for a TypeScript code block in the response.
pattern = r"```typescript\s*(.*?)\s*```"
match = re.search(pattern, ai_message.content, re.DOTALL)
if match:
# Reconstruct the code block with proper fences.
typescript_code = match.group(1).strip()
return f"```typescript\n{typescript_code}\n```"
else:
raise ValueError("No TypeScript code block found in the model's response.")
def insert_translations_into_markdown(
markdown: str, typescript_snippets: list[str]
) -> str:
"""Walks through the original markdown content and, after each
Python snippet block, inserts the corresponding translated TypeScript snippet.
It assumes that the ordering of the Python snippets
(from extract_python_snippets) matches the order they appear in the markdown.
"""
output_lines = []
lines = markdown.splitlines(keepends=True)
inside_block = False
snippet_index = 0
for line in lines:
output_lines.append(line)
if not inside_block and opening_pattern.match(line):
# We've encountered the start of a python code block.
inside_block = True
elif inside_block:
if closing_pattern.match(line):
# End of a python snippet block.
inside_block = False
if snippet_index < len(typescript_snippets):
# Insert an extra newline for clarity, then the translated TypeScript snippet.
output_lines.append("\n")
output_lines.append(typescript_snippets[snippet_index])
output_lines.append("\n")
snippet_index += 1
return "".join(output_lines)
def main(file_path: str) -> None:
# Read the markdown file.
with open(file_path, "r") as f:
markdown_content = f.read()
# 1. Extract all Python snippets.
python_snippets = extract_python_snippets(markdown_content)[:1]
# 2. Translate each Python snippet to TypeScript.
typescript_snippets = []
# Replace with .batch() for faster translation
for python_snippet in _tqdm(python_snippets):
ts_snippet = translate_snippet(python_snippet)
typescript_snippets.append(ts_snippet)
# 3. Insert the TypeScript translations after their respective Python snippets.
updated_markdown = insert_translations_into_markdown(
markdown_content, typescript_snippets
)
# Overwrite the original markdown file with the updated content.
with open(file_path, "w") as f:
f.write(updated_markdown)
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Translate Python snippets in a markdown file to TypeScript and insert them after each Python snippet."
)
parser.add_argument("file_path", type=str, help="Path to the markdown file.")
args = parser.parse_args()
main(args.file_path)
+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 -240
View File
@@ -1,18 +1,10 @@
"""Experimental script to generate consolidated llms text from the docs."""
import asyncio
import glob
import os
import re
from typing import TypedDict, List, Optional
import yaml
from langchain.chat_models import init_chat_model
from langchain_core.rate_limiters import InMemoryRateLimiter
from mkdocs.structure.files import File
from mkdocs.structure.pages import Page
from pydantic import BaseModel, Field
from yaml import SafeLoader
from _scripts.notebook_hooks import _on_page_markdown_with_config
@@ -21,59 +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)
)
@@ -83,14 +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
@@ -101,170 +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
@@ -274,23 +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)
-181
View File
@@ -1,181 +0,0 @@
"""Logic to identify and transform cross-reference links in markdown files.
This module allows supporting custom markdown syntax for "autolinks". These are links
that will be transformed based on the current scope context, such as "global", "python",
or "js" into an appropriate markdown link format.
For example,
```markdown
@[StateGraph]
```
May be transformed into:
```markdown
[StateGraph](some_path/api-reference/state-graph.md)
```
The transformation value depends on the scope in which the link is used.
"""
import logging
import re
from typing import Optional
from _scripts.link_map import SCOPE_LINK_MAPS
logger = logging.getLogger(__name__)
def _transform_link(
link_name: str, scope: str, file_path: str, line_number: int, custom_title: Optional[str] = None
) -> Optional[str]:
"""Transform a cross-reference link based on the current scope.
Args:
link_name: The name of the link to transform (e.g., "StateGraph").
scope: The current scope context ("global", "python", "js", etc.).
file_path: The file path for error reporting.
line_number: The line number for error reporting.
custom_title: Optional custom title for the link. If None, uses link_name.
Returns:
A formatted markdown link if the link is found in the scope mapping,
None otherwise.
Example:
>>> _transform_link("StateGraph", "python", "file.md", 5)
"[StateGraph](https://langchain-ai.github.io/langgraph/reference/graphs/#langgraph.graph.StateGraph)"
>>> _transform_link("StateGraph", "python", "file.md", 5, "Custom Title")
"[Custom Title](https://langchain-ai.github.io/langgraph/reference/graphs/#langgraph.graph.StateGraph)"
>>> _transform_link("unknown-link", "python", "file.md", 5)
None
"""
if scope == "global":
# Special scope that is composed of both Python and JS links
# For now, we will substitute in the python scope!
# But we need to add support for handling both scopes.
scope = "python"
logger.error(
"Encountered unhandled 'global' scope. Defaulting to 'python'."
"In file: %s, line %d, link_name: %s",
file_path,
line_number,
link_name,
)
link_map = SCOPE_LINK_MAPS.get(scope, {})
url = link_map.get(link_name)
if url:
title = custom_title if custom_title is not None else link_name
return f"[{title}]({url})"
else:
# Log error with file location information
logger.info(
# Using %s
"Link '%s' not found in scope '%s'. "
"In file: %s, line %d. Available links in scope: %s",
link_name,
scope,
file_path,
line_number,
list(link_map.keys() if link_map else []),
)
return None
CONDITIONAL_FENCE_PATTERN = re.compile(
r"""
^ # Start of line
(?P<indent>[ \t]*) # Optional indentation (spaces or tabs)
::: # Literal fence marker
(?P<language>\w+)? # Optional language identifier (named group: language)
\s* # Optional trailing whitespace
$ # End of line
""",
re.VERBOSE,
)
CROSS_REFERENCE_PATTERN = re.compile(
r"""
(?: # Non-capturing group for two possible formats:
@\[ # @ symbol followed by opening bracket for title
(?P<title>[^\]]+) # Custom title - one or more non-bracket characters
\] # Closing bracket for title
\[ # Opening bracket for link name
(?P<link_name_with_title>[^\]]+) # Link name - one or more non-bracket characters
\] # Closing bracket for link name
| # OR
@\[ # @ symbol followed by opening bracket
(?P<link_name>[^\]]+) # Link name - one or more non-bracket characters
\] # Closing bracket
)
""",
re.VERBOSE,
)
def _replace_autolinks(markdown: str, file_path: str, *, default_scope: str = "python") -> str:
"""Preprocess markdown lines to handle @[links] with conditional fence scopes.
This function processes markdown content to transform @[link_name] references
based on the current conditional fence scope. Conditional fences use the
syntax :::language to define scope boundaries.
Args:
markdown: The markdown content to process.
file_path: The file path for error reporting.
default_scope: The default scope to use if no scope is matched.
Returns:
Processed markdown content with @[references] transformed to proper
markdown links or left unchanged if not found.
Example:
Input:
"@[StateGraph]\\n:::python\\n@[Command]\\n:::\\n"
Output:
"[StateGraph](url)\\n:::python\\n[Command](url)\\n:::\\n"
"""
# Track the current scope context
current_scope = default_scope
lines = markdown.splitlines(keepends=True)
processed_lines = []
for line_number, line in enumerate(lines, 1):
line_stripped = line.strip()
# Check if this line defines a new conditional fence scope
fence_match = CONDITIONAL_FENCE_PATTERN.match(line_stripped)
if fence_match:
language = fence_match.group("language")
# Set scope to the specified language, or reset to global if no language
current_scope = language.lower() if language else default_scope
processed_lines.append(line)
continue
# Transform all @[link_name] references in this line based on current scope
def replace_cross_reference(match: re.Match[str]) -> str:
"""Replace a single @[link_name] with the scoped equivalent."""
# Check if this is the @[title][ref] format or @[ref] format
title = match.group("title")
if title is not None:
# This is @[title][ref] format
link_name = match.group("link_name_with_title")
custom_title = title
else:
# This is @[ref] format
link_name = match.group("link_name")
custom_title = None
transformed = _transform_link(
link_name, current_scope, file_path, line_number, custom_title
)
return transformed if transformed is not None else match.group(0)
transformed_line = CROSS_REFERENCE_PATTERN.sub(replace_cross_reference, line)
processed_lines.append(transformed_line)
return "".join(processed_lines)
@@ -1,236 +0,0 @@
"""Translate Python markdown to TypeScript and/or consolidate Python-JS markdown into a single document."""
import argparse
import requests
from langchain_anthropic import ChatAnthropic
from textwrap import dedent
# Load reference TypeScript snippets
URL = "https://gist.githubusercontent.com/dqbd/b35d49e2ceec80e654fe1c5ab61ec477/raw/f4768aeedb67628190a4e06d063a938afc8e7672/snippets.md"
response = requests.get(URL)
response.raise_for_status()
reference_snippets = response.text
# Initialize model
model = ChatAnthropic(model="claude-sonnet-4-0", max_tokens=64_000)
FLUENT_INTERFACE_PROMPT = (
"CRITICAL: Always use method chaining (fluent interface) for StateGraph operations in TypeScript. "
"Never create separate variables for the graph builder or call methods individually. "
"The fluent interface provides better type safety and is the preferred pattern.\n\n"
"CORRECT examples with fluent interface:\n"
+ dedent(
"""
```typescript
const graph = new StateGraph(MyState)
.addNode('node1', node1)
.addNode('node2', node2)
.addEdge(START, 'node1')
.addEdge('node1', 'node2')
.addEdge('node2', END)
.compile()
```
```typescript
const graph = new StateGraph(MyState)
.addNode('chatbot', chatbot)
.addEdge(START, 'chatbot')
.addEdge('chatbot', END)
.compile()
```
```typescript
const graph = new StateGraph(MyState)
.addNode('chatbot', chatbot)
.addEdge(START, 'chatbot')
.addEdge('chatbot', END)
.compile()
```
"""
)
+ "\n"
+ "INCORRECT examples to avoid:\n"
+ dedent(
"""
```typescript
// WRONG: Creating separate builder variable
const graphBuilder = new StateGraph(MyState)
graphBuilder.addNode('node1', node1)
graphBuilder.addEdge(START, 'node1')
const graph = graphBuilder.compile()
```
```typescript
// WRONG: Using Python-style method names
const workflow = new StateGraph(MyState)
workflow.add_node('node1', node1)
workflow.add_edge(START, 'node1')
const graph = workflow.compile()
```
```typescript
// WRONG: Calling methods individually
const graphBuilder = new StateGraph(MyState)
graphBuilder.addNode('chatbot', chatbot)
graphBuilder.addEdge(START, 'chatbot')
graphBuilder.addEdge('chatbot', END)
const graph = graphBuilder.compile()
```
"""
)
+ "\n"
+ "Key rules:\n"
+ "- Always chain methods directly on the StateGraph constructor\n"
+ "- Use camelCase method names (addNode, addEdge, not add_node, add_edge)\n"
+ "- Always end with .compile()\n"
+ "- Never store the builder in a separate variable\n"
)
TRANSLATION_PROMPT = (
"You are a helpful assistant that translates Python-based technical "
"documentation written in Markdown to equivalent TypeScript-based documentation. "
"The input is a Markdown file written in mkdocs format. It contains "
"Python code snippets embedded in prose. "
"Your task is to rewrite the content by translating the Python code to "
"idiomatic TypeScript, using the provided TypeScript reference snippets "
"to ensure accurate and consistent usage (e.g., correct imports, function "
"names, and patterns). "
"Remove the original Python code and replace it with the corresponding "
"TypeScript version. "
"Do not alter the surrounding prose unless a change is necessary to "
"reflect differences between Python and TypeScript. "
"Preserve the structure and formatting of the original Markdown document. "
"Do not make stylistic or structural changes unless they directly support "
"the translation. "
"Use the reference TypeScript snippets as guidance whenever possible to "
"maintain alignment with existing conventions.\n\n"
"IMPORTANT REQUIREMENTS:\n"
"- Use Zod for state definition for StateGraph. Avoid using Annotation since it will be deprecated in the future.\n"
"- ALWAYS use fluent interface (method chaining) for StateGraph operations - this is CRITICAL\n"
"- Never create separate variables for graph builders\n"
"- Always chain methods directly on the StateGraph constructor and end with .compile()\n\n"
f"{FLUENT_INTERFACE_PROMPT}\n\n"
f"Here are the reference TypeScript snippets:\n\n{reference_snippets}\n\n"
)
CONSOLIDATION_PROMPT = (
"You are a helpful assistant that consolidates parallel Python and JavaScript (TypeScript) technical documentation "
"written in Markdown into a single unified Markdown document. "
"The input consists of two documents: the first is for Python users, and the second is for JavaScript/TypeScript users. "
"Your task is to merge these into one Markdown file using language-specific fenced blocks to separate the content where needed. "
"Use the following syntax to distinguish content for each language:\n\n"
":::python\n"
"# Python-specific content\n"
":::\n\n"
":::js\n"
"# JavaScript/TypeScript-specific content\n"
":::\n\n"
"Follow these consolidation rules:\n"
"- When content (prose or code) is the same or nearly identical in both versions, include it only once—outside of any fenced block.\n"
"- When content differs between the Python and JS versions, wrap each version in its corresponding fenced block.\n"
"- Prefer **paragraph-level separation** of language-specific content. Do not combine Python and JS snippets or terminology in the same sentence or paragraph using conditional phrases.\n"
" For example, avoid inline constructs like:\n"
" `The :::python add_messages ::: :::js reducer ::: function...`\n"
" Instead, write two distinct paragraphs:\n\n"
" :::python\n"
" The `add_messages` function in our `State` will append the LLM's response messages to whatever messages are already in the state.\n"
" ::: \n\n"
" :::js\n"
" The `reducer` function in our `StateAnnotation` will append the LLM's response messages to whatever messages are already in the state.\n"
" :::\n\n"
"- Preserve the overall structure, ordering, and formatting of the original Markdown documents.\n"
"- Do not rephrase or unify content unless it is logically and semantically identical.\n"
"- Use the fenced blocks for both prose and code as needed, and ensure output is clean, readable Markdown suitable for tools that parse these directives.\n"
"Your goal is to produce a cleanly merged documentation file that serves both Python and JavaScript users without redundancy, while maximizing clarity and separation of language-specific details."
)
def translate_python_to_ts(markdown_content: str) -> str:
response = model.invoke(
[
{
"role": "system",
"content": TRANSLATION_PROMPT,
"cache_control": {"type": "ephemeral"},
},
{"role": "user", "content": markdown_content},
]
)
return response.content
def consolidate_python_and_ts(combined_content: str) -> str:
response = model.invoke(
[
{
"role": "system",
"content": CONSOLIDATION_PROMPT,
"cache_control": {"type": "ephemeral"},
},
{"role": "user", "content": combined_content},
]
)
return response.content
def main(file_path: str, translate_only: bool, consolidate_only: bool) -> None:
with open(file_path, "r", encoding="utf-8") as f:
markdown_content = f.read()
if translate_only:
translated = translate_python_to_ts(markdown_content)
output_path = file_path.replace(".md", ".translated.md")
with open(output_path, "w", encoding="utf-8") as f:
f.write(translated)
print(f"Translated JS/TS version written to: {output_path}")
elif consolidate_only:
consolidated = consolidate_python_and_ts(markdown_content)
with open(file_path, "w", encoding="utf-8") as f:
f.write(consolidated)
print(f"Consolidated content written to: {file_path}")
else:
# Default behavior: translate first, then consolidate both
translated = translate_python_to_ts(markdown_content)
combined = f"{markdown_content.strip()}\n\n\n{translated.strip()}"
consolidated = consolidate_python_and_ts(combined)
with open(file_path, "w", encoding="utf-8") as f:
f.write(consolidated)
print(f"Translated and consolidated content written to: {file_path}")
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description=(
"Translate Python markdown to TypeScript and/or consolidate "
"Python-JS markdown into one file."
)
)
parser.add_argument("file_path", type=str, help="Path to the markdown file.")
parser.add_argument(
"--translate-only",
action="store_true",
help="Only generate the JS translation.",
)
parser.add_argument(
"--consolidate-only",
action="store_true",
help="Only consolidate pre-paired Python and JS content.",
)
args = parser.parse_args()
if args.translate_only and args.consolidate_only:
raise ValueError(
"Cannot use both --translate-only and --consolidate-only at the same time."
)
main(
args.file_path,
translate_only=args.translate_only,
consolidate_only=args.consolidate_only,
)
@@ -1,6 +0,0 @@
.prettierrc
.eslint.config.mjs
package.json
README.md
tsconfig.json
yarn.lock
@@ -1,19 +0,0 @@
{
"$schema": "https://json.schemastore.org/prettierrc",
"printWidth": 80,
"tabWidth": 2,
"useTabs": false,
"semi": true,
"singleQuote": false,
"quoteProps": "as-needed",
"jsxSingleQuote": false,
"trailingComma": "es5",
"bracketSpacing": true,
"arrowParens": "always",
"requirePragma": false,
"insertPragma": false,
"proseWrap": "preserve",
"htmlWhitespaceSensitivity": "css",
"vueIndentScriptAndStyle": false,
"endOfLine": "lf"
}
@@ -1 +0,0 @@
# \_codeblocks
@@ -1,14 +0,0 @@
import js from "@eslint/js";
import globals from "globals";
import tseslint from "typescript-eslint";
import { defineConfig } from "eslint/config";
export default defineConfig([
{
files: ["**/*.{js,mjs,cjs,ts,mts,cts}"],
plugins: { js },
extends: ["js/recommended"],
languageOptions: { globals: globals.browser },
},
tseslint.configs.recommended,
]);
@@ -1,27 +0,0 @@
{
"name": "_codeblocks",
"packageManager": "yarn@4.6.0",
"scripts": {
"lint": "eslint .",
"lint:fix": "eslint . --fix",
"format": "prettier --write .",
"format:fix": "prettier --write . --fix"
},
"dependencies": {
"@langchain/anthropic": "^0.3.24",
"@langchain/core": "^0.3.66",
"@langchain/langgraph": "^0.3.11",
"@langchain/langgraph-api": "^0.0.52",
"@langchain/langgraph-sdk": "^0.0.102",
"@langchain/openai": "^0.6.3",
"zod": "^4.0.10"
},
"devDependencies": {
"@eslint/js": "^9.32.0",
"eslint": "^9.32.0",
"globals": "^16.3.0",
"jiti": "^2.5.1",
"typescript": "^5.8.3",
"typescript-eslint": "^8.38.0"
}
}
@@ -1,114 +0,0 @@
{
"compilerOptions": {
/* Visit https://aka.ms/tsconfig to read more about this file */
/* Projects */
// "incremental": true, /* Save .tsbuildinfo files to allow for incremental compilation of projects. */
// "composite": true, /* Enable constraints that allow a TypeScript project to be used with project references. */
// "tsBuildInfoFile": "./.tsbuildinfo", /* Specify the path to .tsbuildinfo incremental compilation file. */
// "disableSourceOfProjectReferenceRedirect": true, /* Disable preferring source files instead of declaration files when referencing composite projects. */
// "disableSolutionSearching": true, /* Opt a project out of multi-project reference checking when editing. */
// "disableReferencedProjectLoad": true, /* Reduce the number of projects loaded automatically by TypeScript. */
/* Language and Environment */
"target": "esnext", /* Set the JavaScript language version for emitted JavaScript and include compatible library declarations. */
// "lib": [], /* Specify a set of bundled library declaration files that describe the target runtime environment. */
// "jsx": "preserve", /* Specify what JSX code is generated. */
// "libReplacement": true, /* Enable lib replacement. */
// "experimentalDecorators": true, /* Enable experimental support for legacy experimental decorators. */
// "emitDecoratorMetadata": true, /* Emit design-type metadata for decorated declarations in source files. */
// "jsxFactory": "", /* Specify the JSX factory function used when targeting React JSX emit, e.g. 'React.createElement' or 'h'. */
// "jsxFragmentFactory": "", /* Specify the JSX Fragment reference used for fragments when targeting React JSX emit e.g. 'React.Fragment' or 'Fragment'. */
// "jsxImportSource": "", /* Specify module specifier used to import the JSX factory functions when using 'jsx: react-jsx*'. */
// "reactNamespace": "", /* Specify the object invoked for 'createElement'. This only applies when targeting 'react' JSX emit. */
// "noLib": true, /* Disable including any library files, including the default lib.d.ts. */
// "useDefineForClassFields": true, /* Emit ECMAScript-standard-compliant class fields. */
// "moduleDetection": "auto", /* Control what method is used to detect module-format JS files. */
/* Modules */
"module": "nodenext", /* Specify what module code is generated. */
// "rootDir": "./", /* Specify the root folder within your source files. */
"moduleResolution": "nodenext", /* Specify how TypeScript looks up a file from a given module specifier. */
// "baseUrl": "./", /* Specify the base directory to resolve non-relative module names. */
// "paths": {}, /* Specify a set of entries that re-map imports to additional lookup locations. */
// "rootDirs": [], /* Allow multiple folders to be treated as one when resolving modules. */
// "typeRoots": [], /* Specify multiple folders that act like './node_modules/@types'. */
// "types": [], /* Specify type package names to be included without being referenced in a source file. */
// "allowUmdGlobalAccess": true, /* Allow accessing UMD globals from modules. */
// "moduleSuffixes": [], /* List of file name suffixes to search when resolving a module. */
// "allowImportingTsExtensions": true, /* Allow imports to include TypeScript file extensions. Requires '--moduleResolution bundler' and either '--noEmit' or '--emitDeclarationOnly' to be set. */
// "rewriteRelativeImportExtensions": true, /* Rewrite '.ts', '.tsx', '.mts', and '.cts' file extensions in relative import paths to their JavaScript equivalent in output files. */
// "resolvePackageJsonExports": true, /* Use the package.json 'exports' field when resolving package imports. */
// "resolvePackageJsonImports": true, /* Use the package.json 'imports' field when resolving imports. */
// "customConditions": [], /* Conditions to set in addition to the resolver-specific defaults when resolving imports. */
// "noUncheckedSideEffectImports": true, /* Check side effect imports. */
// "resolveJsonModule": true, /* Enable importing .json files. */
// "allowArbitraryExtensions": true, /* Enable importing files with any extension, provided a declaration file is present. */
// "noResolve": true, /* Disallow 'import's, 'require's or '<reference>'s from expanding the number of files TypeScript should add to a project. */
/* JavaScript Support */
// "allowJs": true, /* Allow JavaScript files to be a part of your program. Use the 'checkJS' option to get errors from these files. */
// "checkJs": true, /* Enable error reporting in type-checked JavaScript files. */
// "maxNodeModuleJsDepth": 1, /* Specify the maximum folder depth used for checking JavaScript files from 'node_modules'. Only applicable with 'allowJs'. */
/* Emit */
// "declaration": true, /* Generate .d.ts files from TypeScript and JavaScript files in your project. */
// "declarationMap": true, /* Create sourcemaps for d.ts files. */
// "emitDeclarationOnly": true, /* Only output d.ts files and not JavaScript files. */
// "sourceMap": true, /* Create source map files for emitted JavaScript files. */
// "inlineSourceMap": true, /* Include sourcemap files inside the emitted JavaScript. */
// "noEmit": true, /* Disable emitting files from a compilation. */
// "outFile": "./", /* Specify a file that bundles all outputs into one JavaScript file. If 'declaration' is true, also designates a file that bundles all .d.ts output. */
// "outDir": "./", /* Specify an output folder for all emitted files. */
// "removeComments": true, /* Disable emitting comments. */
// "importHelpers": true, /* Allow importing helper functions from tslib once per project, instead of including them per-file. */
// "downlevelIteration": true, /* Emit more compliant, but verbose and less performant JavaScript for iteration. */
// "sourceRoot": "", /* Specify the root path for debuggers to find the reference source code. */
// "mapRoot": "", /* Specify the location where debugger should locate map files instead of generated locations. */
// "inlineSources": true, /* Include source code in the sourcemaps inside the emitted JavaScript. */
// "emitBOM": true, /* Emit a UTF-8 Byte Order Mark (BOM) in the beginning of output files. */
// "newLine": "crlf", /* Set the newline character for emitting files. */
// "stripInternal": true, /* Disable emitting declarations that have '@internal' in their JSDoc comments. */
// "noEmitHelpers": true, /* Disable generating custom helper functions like '__extends' in compiled output. */
// "noEmitOnError": true, /* Disable emitting files if any type checking errors are reported. */
// "preserveConstEnums": true, /* Disable erasing 'const enum' declarations in generated code. */
// "declarationDir": "./", /* Specify the output directory for generated declaration files. */
/* Interop Constraints */
// "isolatedModules": true, /* Ensure that each file can be safely transpiled without relying on other imports. */
// "verbatimModuleSyntax": true, /* Do not transform or elide any imports or exports not marked as type-only, ensuring they are written in the output file's format based on the 'module' setting. */
// "isolatedDeclarations": true, /* Require sufficient annotation on exports so other tools can trivially generate declaration files. */
// "erasableSyntaxOnly": true, /* Do not allow runtime constructs that are not part of ECMAScript. */
// "allowSyntheticDefaultImports": true, /* Allow 'import x from y' when a module doesn't have a default export. */
"esModuleInterop": true, /* Emit additional JavaScript to ease support for importing CommonJS modules. This enables 'allowSyntheticDefaultImports' for type compatibility. */
// "preserveSymlinks": true, /* Disable resolving symlinks to their realpath. This correlates to the same flag in node. */
"forceConsistentCasingInFileNames": true, /* Ensure that casing is correct in imports. */
/* Type Checking */
"strict": false, /* Enable all strict type-checking options. */
// "noImplicitAny": true, /* Enable error reporting for expressions and declarations with an implied 'any' type. */
// "strictNullChecks": true, /* When type checking, take into account 'null' and 'undefined'. */
// "strictFunctionTypes": true, /* When assigning functions, check to ensure parameters and the return values are subtype-compatible. */
// "strictBindCallApply": true, /* Check that the arguments for 'bind', 'call', and 'apply' methods match the original function. */
// "strictPropertyInitialization": true, /* Check for class properties that are declared but not set in the constructor. */
// "strictBuiltinIteratorReturn": true, /* Built-in iterators are instantiated with a 'TReturn' type of 'undefined' instead of 'any'. */
// "noImplicitThis": true, /* Enable error reporting when 'this' is given the type 'any'. */
// "useUnknownInCatchVariables": true, /* Default catch clause variables as 'unknown' instead of 'any'. */
// "alwaysStrict": true, /* Ensure 'use strict' is always emitted. */
// "noUnusedLocals": true, /* Enable error reporting when local variables aren't read. */
// "noUnusedParameters": true, /* Raise an error when a function parameter isn't read. */
// "exactOptionalPropertyTypes": true, /* Interpret optional property types as written, rather than adding 'undefined'. */
// "noImplicitReturns": true, /* Enable error reporting for codepaths that do not explicitly return in a function. */
// "noFallthroughCasesInSwitch": true, /* Enable error reporting for fallthrough cases in switch statements. */
// "noUncheckedIndexedAccess": true, /* Add 'undefined' to a type when accessed using an index. */
// "noImplicitOverride": true, /* Ensure overriding members in derived classes are marked with an override modifier. */
// "noPropertyAccessFromIndexSignature": true, /* Enforces using indexed accessors for keys declared using an indexed type. */
// "allowUnusedLabels": true, /* Disable error reporting for unused labels. */
// "allowUnreachableCode": true, /* Disable error reporting for unreachable code. */
/* Completeness */
// "skipDefaultLibCheck": true, /* Skip type checking .d.ts files that are included with TypeScript. */
"skipLibCheck": true /* Skip type checking all .d.ts files. */
""
}
}
File diff suppressed because it is too large Load Diff
@@ -1,150 +0,0 @@
#!/usr/bin/env python
"""Extracts typescript code blocks from a markdown file."""
import argparse
import json
import re
import os
from typing import List, TypedDict, Literal
class CodeBlock(TypedDict):
"""A code block extracted from a markdown file."""
starting_line: int
"""The line number where the code block starts in the source file"""
ending_line: int
"""The line number where the code block ends in the source file"""
indentation: int
"""Number of spaces/tabs used for indentation of the code block"""
source_file: str
"""Path to the markdown file containing this code block"""
frontmatter: str
"""Any metadata or frontmatter specified after the opening code fence"""
code: str
"""The actual code content within the code block"""
language: str
"""The language of the code block (e.g. typescript, javascript)"""
def extract_code_blocks(markdown_content: str, source_file: str) -> List[CodeBlock]:
"""Extracts code blocks from a markdown file.
Args:
markdown_content: The content of the markdown file.
source_file: The path to the markdown file.
Returns:
A list of TypedDicts, where each dict represents a code block.
"""
# Regex to find code blocks with specified languages, capturing indentation
# and frontmatter.
pattern = re.compile(
r"^(?P<indentation>\s*)```(?P<language>typescript|javascript|ts|js)(?P<frontmatter>[^\n]*)\n(?P<code>.*?)\n^(?P=indentation)```\s*$",
re.DOTALL | re.MULTILINE,
)
code_blocks: List[CodeBlock] = []
for match in pattern.finditer(markdown_content):
start_pos = match.start()
# Calculate line numbers
starting_line = markdown_content.count("\n", 0, start_pos) + 1
ending_line = starting_line + match.group(0).count("\n")
indentation_str = match.group("indentation")
code_block: CodeBlock = {
"starting_line": starting_line,
"ending_line": ending_line,
"indentation": len(indentation_str),
"source_file": source_file,
"frontmatter": match.group("frontmatter").strip(),
"code": match.group("code"),
"language": match.group("language"),
}
code_blocks.append(code_block)
return code_blocks
def dump_code_blocks(input_file: str, output_file: str, format: Literal["json", "inline"]) -> None:
"""Function to extract and save code blocks from a markdown file.
Args:
input_file: Path to the input markdown file.
output_file: Path to the output JSON file for the extracted code blocks.
format: Output format - either "json" or "inline"
"""
with open(input_file, "r", encoding="utf-8") as f:
markdown_content = f.read()
extracted_code = extract_code_blocks(markdown_content, input_file)
if len(extracted_code) == 0:
print(f"No code blocks found in {input_file}")
return
if format == "json":
with open(output_file, "w", encoding="utf-8") as f:
json.dump(extracted_code, f, indent=2)
elif format == "inline":
with open(output_file, "w", encoding="utf-8") as f:
for code_block in extracted_code:
f.write(f"// {json.dumps({k:v for k,v in code_block.items() if k != 'code'})}\n")
f.write("\n")
f.write(code_block["code"])
f.write("\n")
print(f"Extracted {len(extracted_code)} code blocks from {input_file} to {output_file}")
def main(input_path: str, output_path: str, format: Literal["json", "inline"]) -> None:
"""Main function to extract code blocks from a markdown file.
Args:
input_file: Path to the input markdown file.
output_file: Path to the output JSON file for the extracted code blocks.
format: Output format - either "json" or "inline"
"""
# Check if input path is a directory
if os.path.isdir(input_path):
if os.path.isfile(output_path):
raise ValueError("If input_path is a directory, output_path must also be a directory")
if not os.path.isdir(output_path):
os.makedirs(output_path, exist_ok=True)
# Process each markdown file in the directory recursively
for root, _, files in os.walk(input_path):
for filename in files:
if filename.endswith(".md"):
# Get relative path to maintain directory structure
rel_path = os.path.relpath(root, input_path)
input_file = os.path.join(root, filename)
# Create output directory if it doesn't exist
output_dir = os.path.join(output_path, rel_path)
os.makedirs(output_dir, exist_ok=True)
output_file = os.path.join(output_dir, filename.replace(".md", ".ts"))
dump_code_blocks(input_file, output_file, format)
else:
# Process single file
dump_code_blocks(input_path, output_path, format)
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Extract typescript code blocks from a markdown file."
)
parser.add_argument(
"input_file",
help="Path to the input markdown file.",
)
parser.add_argument(
"output_file",
help="Path to the output JSON file for the extracted code blocks.",
)
parser.add_argument(
"--format",
choices=["json", "inline"],
default="json",
help="Output format - either 'json' or 'inline'",
)
args = parser.parse_args()
main(args.input_file, args.output_file, args.format)
-127
View File
@@ -1,127 +0,0 @@
"""Link mapping for cross-reference resolution across different scopes.
This module provides link mappings for different language/framework scopes
to resolve @[link_name] references to actual URLs.
"""
# Python-specific link mappings
PYTHON_LINK_MAP = {
"StateGraph": "reference/graphs/#langgraph.graph.StateGraph",
"add_conditional_edges": "reference/graphs/#langgraph.graph.state.StateGraph.add_conditional_edges",
"add_edge": "reference/graphs/#langgraph.graph.state.StateGraph.add_edge",
"add_node": "reference/graphs/#langgraph.graph.state.StateGraph.add_node",
"add_messages": "reference/graphs/#langgraph.graph.message.add_messages",
"ToolNode": "reference/agents/#langgraph.prebuilt.tool_node.ToolNode",
"CompiledStateGraph.astream": "reference/graphs/#langgraph.graph.state.CompiledStateGraph.astream",
"Pregel.astream": "reference/pregel/#langgraph.pregel.Pregel.astream",
"AsyncPostgresSaver": "reference/checkpoints/#langgraph.checkpoint.postgres.aio.AsyncPostgresSaver",
"AsyncSqliteSaver": "reference/checkpoints/#langgraph.checkpoint.sqlite.aio.AsyncSqliteSaver",
"BaseCheckpointSaver": "reference/checkpoints/#langgraph.checkpoint.base.BaseCheckpointSaver",
"BaseStore": "reference/store/#langgraph.store.base.BaseStore",
"BaseStore.put": "reference/store/#langgraph.store.base.BaseStore.put",
"BinaryOperatorAggregate": "reference/pregel/#langgraph.pregel.Pregel--advanced-channels-context-and-binaryoperatoraggregate",
"CipherProtocol": "reference/checkpoints/#langgraph.checkpoint.serde.base.CipherProtocol",
"client.runs.stream": "cloud/reference/sdk/python_sdk_ref/#langgraph_sdk.client.RunsClient.stream",
"client.runs.wait": "cloud/reference/sdk/python_sdk_ref/#langgraph_sdk.client.RunsClient.wait",
"client.threads.get_history": "cloud/reference/sdk/python_sdk_ref/#langgraph_sdk.client.ThreadsClient.get_history",
"client.threads.update_state": "cloud/reference/sdk/python_sdk_ref/#langgraph_sdk.client.ThreadsClient.update_state",
"Command": "reference/types/#langgraph.types.Command",
"CompiledStateGraph": "reference/graphs/#langgraph.graph.state.CompiledStateGraph",
"create_react_agent": "reference/prebuilt/#langgraph.prebuilt.chat_agent_executor.create_react_agent",
"create_supervisor": "reference/supervisor/#langgraph_supervisor.supervisor.create_supervisor",
"EncryptedSerializer": "reference/checkpoints/#langgraph.checkpoint.serde.encrypted.EncryptedSerializer",
"entrypoint.final": "reference/func/#langgraph.func.entrypoint.final",
"entrypoint": "reference/func/#langgraph.func.entrypoint",
"from_pycryptodome_aes": "reference/checkpoints/#langgraph.checkpoint.serde.encrypted.EncryptedSerializer.from_pycryptodome_aes",
"get_state_history": "reference/graphs/#langgraph.graph.state.CompiledStateGraph.get_state_history",
"get_stream_writer": "reference/config/#langgraph.config.get_stream_writer",
"HumanInterrupt": "reference/prebuilt/#langgraph.prebuilt.interrupt.HumanInterrupt",
"InjectedState": "reference/agents/#langgraph.prebuilt.tool_node.InjectedState",
"InMemorySaver": "reference/checkpoints/#langgraph.checkpoint.memory.InMemorySaver",
"interrupt": "reference/types/#langgraph.types.Interrupt",
"CompiledStateGraph.invoke": "reference/graphs/#langgraph.graph.state.CompiledStateGraph.invoke",
"JsonPlusSerializer": "reference/checkpoints/#langgraph.checkpoint.serde.jsonplus.JsonPlusSerializer",
"langgraph.json": "cloud/reference/cli/#configuration-file",
"LastValue": "reference/channels/#langgraph.channels.LastValue",
"PostgresSaver": "reference/checkpoints/#langgraph.checkpoint.postgres.PostgresSaver",
"Pregel": "reference/pregel/",
"Pregel.stream": "reference/pregel/#langgraph.pregel.Pregel.stream",
"pre_model_hook": "reference/prebuilt/#langgraph.prebuilt.chat_agent_executor.create_react_agent",
"protocol": "reference/checkpoints/#langgraph.checkpoint.serde.base.SerializerProtocol",
"Send": "reference/types/#langgraph.types.Send",
"SerializerProtocol": "reference/checkpoints/#langgraph.checkpoint.serde.base.SerializerProtocol",
"SqliteSaver": "reference/checkpoints/#langgraph.checkpoint.sqlite.SqliteSaver",
"START": "reference/constants/#langgraph.constants.START",
"CompiledStateGraph.stream": "reference/graphs/#langgraph.graph.state.CompiledStateGraph.stream",
"task": "reference/func/#langgraph.func.task",
"Topic": "reference/channels/#langgraph.channels.Topic",
"update_state": "reference/graphs/#langgraph.graph.state.CompiledStateGraph.update_state",
}
# JavaScript-specific link mappings
JS_LINK_MAP = {
"Auth": "reference/classes/sdk_auth.Auth.html",
"StateGraph": "reference/classes/langgraph.StateGraph.html",
"add_conditional_edges": "/reference/classes/langgraph.StateGraph.html#addConditionalEdges",
"add_edge": "reference/classes/langgraph.StateGraph.html#addEdge",
"add_node": "reference/classes/langgraph.StateGraph.html#addNode",
"add_messages": "reference/modules/langgraph.html#addMessages",
"ToolNode": "reference/classes/langgraph_prebuilt.ToolNode.html",
"BaseCheckpointSaver": "reference/classes/checkpoint.BaseCheckpointSaver.html",
"BaseStore": "reference/classes/checkpoint.BaseStore.html",
"BaseStore.put": "reference/classes/checkpoint.BaseStore.html#put",
"BinaryOperatorAggregate": "reference/classes/langgraph.BinaryOperatorAggregate.html",
"client.runs.stream": "reference/classes/sdk_client.RunsClient.html#stream",
"client.runs.wait": "reference/classes/sdk_client.RunsClient.html#wait",
"client.threads.get_history": "reference/classes/sdk_client.ThreadsClient.html#getHistory",
"client.threads.update_state": "reference/classes/sdk_client.ThreadsClient.html#updateState",
"Command": "reference/classes/langgraph.Command.html",
"CompiledStateGraph": "reference/classes/langgraph.CompiledStateGraph.html",
"create_react_agent": "reference/functions/langgraph_prebuilt.createReactAgent.html",
"create_supervisor": "reference/functions/langgraph_supervisor.createSupervisor.html",
"entrypoint.final": "reference/functions/langgraph.entrypoint.html#final",
"entrypoint": "reference/functions/langgraph.entrypoint.html",
"getContextVariable": "https://v03.api.js.langchain.com/functions/_langchain_core.context.getContextVariable.html",
"get_state_history": "reference/classes/langgraph.CompiledStateGraph.html#getStateHistory",
"HumanInterrupt": "reference/interfaces/langgraph_prebuilt.HumanInterrupt.html",
"interrupt": "reference/functions/langgraph.interrupt-2.html",
"CompiledStateGraph.invoke": "reference/classes/langgraph.CompiledStateGraph.html#invoke",
"langgraph.json": "cloud/reference/cli/#configuration-file",
"MemorySaver": "reference/classes/checkpoint.MemorySaver.html",
"messagesStateReducer": "reference/functions/langgraph.messagesStateReducer.html",
"PostgresSaver": "reference/classes/checkpoint_postgres.PostgresSaver.html",
"Pregel": "reference/classes/langgraph.Pregel.html",
"Pregel.stream": "reference/classes/langgraph.Pregel.html#stream",
"pre_model_hook": "reference/functions/langgraph_prebuilt.createReactAgent.html",
"protocol": "reference/interfaces/checkpoint.SerializerProtocol.html",
"Send": "reference/classes/langgraph.Send.html",
"SerializerProtocol": "reference/interfaces/checkpoint.SerializerProtocol.html",
"SqliteSaver": "reference/classes/checkpoint_sqlite.SqliteSaver.html",
"START": "reference/variables/langgraph.START.html",
"CompiledStateGraph.stream": "reference/classes/langgraph.CompiledStateGraph.html#stream",
"task": "reference/functions/langgraph.task.html",
## TODO (hntrl): export Topic from langgraphjs
# "Topic": "reference/classes/langgraph_channels.Topic.html",
"update_state": "reference/classes/langgraph.CompiledStateGraph.html#updateState",
}
# TODO: Allow updating these to localhost for local development
PY_REFERENCE_HOST = "https://langchain-ai.github.io/langgraph/"
JS_REFERENCE_HOST = "https://langchain-ai.github.io/langgraphjs/"
for key, value in PYTHON_LINK_MAP.items():
# Ensure the link is absolute
if not value.startswith("http"):
PYTHON_LINK_MAP[key] = f"{PY_REFERENCE_HOST}{value}"
for key, value in JS_LINK_MAP.items():
# Ensure the link is absolute
if not value.startswith("http"):
JS_LINK_MAP[key] = f"{JS_REFERENCE_HOST}{value}"
# Global scope is assembled from the Python and JS mappings
# Combined mapping by scope
SCOPE_LINK_MAPS = {
"python": PYTHON_LINK_MAP,
"js": JS_LINK_MAP,
}
+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 -%}
+22 -378
View File
@@ -1,22 +1,13 @@
"""mkdocs hooks for adding custom logic to documentation pipeline.
Lifecycle events: https://www.mkdocs.org/dev-guide/plugins/#events
"""
import json
import logging
import os
import posixpath
import re
from typing import Any, Dict
from bs4 import BeautifulSoup
from mkdocs.config.defaults import MkDocsConfig
from mkdocs.structure.files import Files, File
from mkdocs.structure.pages import Page
from _scripts.generate_api_reference_links import update_markdown_with_imports
from _scripts.handle_auto_links import _replace_autolinks
from _scripts.notebook_convert import convert_notebook
logger = logging.getLogger(__name__)
@@ -27,185 +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.md#define-and-update-state",
"how-tos/sequence.ipynb": "how-tos/graph-api.md#create-a-sequence-of-steps",
"how-tos/branching.ipynb": "how-tos/graph-api.md#create-branches",
"how-tos/recursion-limit.ipynb": "how-tos/graph-api.md#create-and-control-loops",
"how-tos/visualization.ipynb": "how-tos/graph-api.md#visualize-your-graph",
"how-tos/input_output_schema.ipynb": "how-tos/graph-api.md#define-input-and-output-schemas",
"how-tos/pass_private_state.ipynb": "how-tos/graph-api.md#pass-private-state-between-nodes",
"how-tos/state-model.ipynb": "how-tos/graph-api.md#use-pydantic-models-for-graph-state",
"how-tos/map-reduce.ipynb": "how-tos/graph-api.md#map-reduce-and-the-send-api",
"how-tos/command.ipynb": "how-tos/graph-api.md#combine-control-flow-and-state-updates-with-command",
"how-tos/configuration.ipynb": "how-tos/graph-api.md#add-runtime-configuration",
"how-tos/node-retries.ipynb": "how-tos/graph-api.md#add-retry-policies",
"how-tos/return-when-recursion-limit-hits.ipynb": "how-tos/graph-api.md#impose-a-recursion-limit",
"how-tos/async.ipynb": "how-tos/graph-api.md#async",
# memory how-tos
"how-tos/memory/manage-conversation-history.ipynb": "how-tos/memory/add-memory.md",
"how-tos/memory/delete-messages.ipynb": "how-tos/memory/add-memory.md#delete-messages",
"how-tos/memory/add-summary-conversation-history.ipynb": "how-tos/memory/add-memory.md#summarize-messages",
"how-tos/memory.ipynb": "how-tos/memory/add-memory.md",
"agents/memory.ipynb": "how-tos/memory/add-memory.md",
# subgraph how-tos
"how-tos/subgraph-transform-state.ipynb": "how-tos/subgraph.md#different-state-schemas",
"how-tos/subgraphs-manage-state.ipynb": "how-tos/subgraph.md#add-persistence",
# persistence how-tos
"how-tos/persistence_postgres.ipynb": "how-tos/memory/add-memory.md#use-in-production",
"how-tos/persistence_mongodb.ipynb": "how-tos/memory/add-memory.md#use-in-production",
"how-tos/persistence_redis.ipynb": "how-tos/memory/add-memory.md#use-in-production",
"how-tos/subgraph-persistence.ipynb": "how-tos/memory/add-memory.md#use-with-subgraphs",
"how-tos/cross-thread-persistence.ipynb": "how-tos/memory/add-memory.md#add-long-term-memory",
"cloud/how-tos/copy_threads": "cloud/how-tos/use_threads",
"cloud/how-tos/check-thread-status": "cloud/how-tos/use_threads",
"cloud/concepts/threads.md": "concepts/persistence.md#threads",
"how-tos/persistence.ipynb": "how-tos/memory/add-memory.md",
# tool calling how-tos
"how-tos/tool-calling-errors.ipynb": "how-tos/tool-calling.ipynb#handle-errors",
"how-tos/pass-config-to-tools.ipynb": "how-tos/tool-calling.ipynb#access-config",
"how-tos/pass-run-time-values-to-tools.ipynb": "how-tos/tool-calling.ipynb#read-state",
"how-tos/update-state-from-tools.ipynb": "how-tos/tool-calling.ipynb#update-state",
"agents/tools.md": "how-tos/tool-calling.md",
# multi-agent how-tos
"how-tos/agent-handoffs.ipynb": "how-tos/multi_agent.md#handoffs",
"how-tos/multi-agent-network.ipynb": "how-tos/multi_agent.md#use-in-a-multi-agent-system",
"how-tos/multi-agent-multi-turn-convo.ipynb": "how-tos/multi_agent.md#multi-turn-conversation",
# cloud redirects
"cloud/index.md": "index.md",
"cloud/how-tos/index.md": "concepts/langgraph_platform",
"cloud/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": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/how-tos/stream_updates.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/how-tos/stream_messages.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/how-tos/stream_events.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/how-tos/stream_debug.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/how-tos/stream_multiple.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/concepts/streaming.md": "concepts/streaming.md",
"agents/streaming.md": "how-tos/streaming.md",
# prebuilt redirects
"how-tos/create-react-agent.ipynb": "agents/agents.md#basic-configuration",
"how-tos/create-react-agent-memory.ipynb": "agents/memory.md",
"how-tos/create-react-agent-system-prompt.ipynb": "agents/context.md#prompts",
"how-tos/create-react-agent-structured-output.ipynb": "agents/agents.md#structured-output",
# misc
"prebuilt.md": "agents/prebuilt.md",
"reference/prebuilt.md": "reference/agents.md",
"concepts/high_level.md": "index.md",
"concepts/index.md": "index.md",
"concepts/v0-human-in-the-loop.md": "concepts/human-in-the-loop.md",
"how-tos/index.md": "index.md",
"tutorials/introduction.ipynb": "concepts/why-langgraph.md",
"agents/deployment.md": "tutorials/langgraph-platform/local-server.md",
# deployment redirects
"how-tos/deploy-self-hosted.md": "cloud/deployment/self_hosted_data_plane.md",
"concepts/self_hosted.md": "concepts/langgraph_self_hosted_data_plane.md",
"tutorials/deployment.md": "concepts/deployment_options.md",
# assistant redirects
"cloud/how-tos/assistant_versioning.md": "cloud/how-tos/configuration_cloud.md",
"cloud/concepts/runs.md": "concepts/assistants.md#execution",
# hitl redirects
"how-tos/wait-user-input-functional.ipynb": "how-tos/use-functional-api.md",
"how-tos/review-tool-calls-functional.ipynb": "how-tos/use-functional-api.md",
"how-tos/create-react-agent-hitl.ipynb": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
"agents/human-in-the-loop.md": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
"how-tos/human_in_the_loop/dynamic_breakpoints.ipynb": "how-tos/human_in_the_loop/breakpoints.md",
"concepts/breakpoints.md": "concepts/human_in_the_loop.md",
"how-tos/human_in_the_loop/breakpoints.md": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
"cloud/how-tos/human_in_the_loop_breakpoint.md": "cloud/how-tos/add-human-in-the-loop.md",
"how-tos/human_in_the_loop/edit-graph-state.ipynb": "how-tos/human_in_the_loop/time-travel.md",
# LGP mintlify migration redirects
"tutorials/auth/getting_started.md": "https://docs.langchain.com/langgraph-platform/auth",
"tutorials/auth/resource_auth.md": "https://docs.langchain.com/langgraph-platform/resource-auth",
"tutorials/auth/add_auth_server.md": "https://docs.langchain.com/langgraph-platform/add-auth-server",
"how-tos/use-remote-graph.md": "https://docs.langchain.com/langgraph-platform/use-remote-graph",
"how-tos/autogen-integration.md": "https://docs.langchain.com/langgraph-platform/autogen-integration",
"cloud/how-tos/use_stream_react.md": "https://docs.langchain.com/langgraph-platform/use-stream-react",
"cloud/how-tos/generative_ui_react.md": "https://docs.langchain.com/langgraph-platform/generative-ui-react",
"concepts/langgraph_platform.md": "https://docs.langchain.com/langgraph-platform/index",
"concepts/langgraph_components.md": "https://docs.langchain.com/langgraph-platform/components",
"concepts/langgraph_server.md": "https://docs.langchain.com/langgraph-platform/langgraph-server",
"concepts/langgraph_data_plane.md": "https://docs.langchain.com/langgraph-platform/data-plane",
"concepts/langgraph_control_plane.md": "https://docs.langchain.com/langgraph-platform/control-plane",
"concepts/langgraph_cli.md": "https://docs.langchain.com/langgraph-platform/langgraph-cli",
"concepts/langgraph_studio.md": "https://docs.langchain.com/langgraph-platform/langgraph-studio",
"cloud/how-tos/studio/quick_start.md": "https://docs.langchain.com/langgraph-platform/quick-start-studio",
"cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langgraph-platform/invoke-studio",
"cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langgraph-platform/manage-assistants-studio",
"cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langgraph-platform/threads-studio",
"cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langgraph-platform/iterate-graph-studio",
"cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langgraph-platform/run-evals-studio",
"cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langgraph-platform/clone-traces-studio",
"cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langgraph-platform/datasets-studio",
"concepts/sdk.md": "https://docs.langchain.com/langgraph-platform/sdk",
"concepts/plans.md": "https://docs.langchain.com/langgraph-platform/plans",
"concepts/application_structure.md": "https://docs.langchain.com/langgraph-platform/application-structure",
"concepts/scalability_and_resilience.md": "https://docs.langchain.com/langgraph-platform/scalability-and-resilience",
"concepts/auth.md": "https://docs.langchain.com/langgraph-platform/auth",
"how-tos/auth/custom_auth.md": "https://docs.langchain.com/langgraph-platform/custom-auth",
"how-tos/auth/openapi_security.md": "https://docs.langchain.com/langgraph-platform/openapi-security",
"concepts/assistants.md": "https://docs.langchain.com/langgraph-platform/assistants",
"cloud/how-tos/configuration_cloud.md": "https://docs.langchain.com/langgraph-platform/configuration-cloud",
"cloud/how-tos/use_threads.md": "https://docs.langchain.com/langgraph-platform/use-threads",
"cloud/how-tos/background_run.md": "https://docs.langchain.com/langgraph-platform/background-run",
"cloud/how-tos/same-thread.md": "https://docs.langchain.com/langgraph-platform/same-thread",
"cloud/how-tos/stateless_runs.md": "https://docs.langchain.com/langgraph-platform/stateless-runs",
"cloud/how-tos/configurable_headers.md": "https://docs.langchain.com/langgraph-platform/configurable-headers",
"concepts/double_texting.md": "https://docs.langchain.com/langgraph-platform/double-texting",
"cloud/how-tos/interrupt_concurrent.md": "https://docs.langchain.com/langgraph-platform/interrupt-concurrent",
"cloud/how-tos/rollback_concurrent.md": "https://docs.langchain.com/langgraph-platform/rollback-concurrent",
"cloud/how-tos/reject_concurrent.md": "https://docs.langchain.com/langgraph-platform/reject-concurrent",
"cloud/how-tos/enqueue_concurrent.md": "https://docs.langchain.com/langgraph-platform/enqueue-concurrent",
"cloud/concepts/webhooks.md": "https://docs.langchain.com/langgraph-platform/use-webhooks",
"cloud/how-tos/webhooks.md": "https://docs.langchain.com/langgraph-platform/use-webhooks",
"cloud/concepts/cron_jobs.md": "https://docs.langchain.com/langgraph-platform/cron-jobs",
"cloud/how-tos/cron_jobs.md": "https://docs.langchain.com/langgraph-platform/cron-jobs",
"how-tos/http/custom_lifespan.md": "https://docs.langchain.com/langgraph-platform/custom-lifespan",
"how-tos/http/custom_middleware.md": "https://docs.langchain.com/langgraph-platform/custom-middleware",
"how-tos/http/custom_routes.md": "https://docs.langchain.com/langgraph-platform/custom-routes",
"cloud/concepts/data_storage_and_privacy.md": "https://docs.langchain.com/langgraph-platform/data-storage-and-privacy",
"cloud/deployment/semantic_search.md": "https://docs.langchain.com/langgraph-platform/semantic-search",
"how-tos/ttl/configure_ttl.md": "https://docs.langchain.com/langgraph-platform/configure-ttl",
"concepts/deployment_options.md": "https://docs.langchain.com/langgraph-platform/deployment-options",
"cloud/quick_start.md": "https://docs.langchain.com/langgraph-platform/deployment-quickstart",
"cloud/deployment/setup.md": "https://docs.langchain.com/langgraph-platform/setup-app-requirements-txt",
"cloud/deployment/setup_pyproject.md": "https://docs.langchain.com/langgraph-platform/setup-pyproject",
"cloud/deployment/setup_javascript.md": "https://docs.langchain.com/langgraph-platform/setup-javascript",
"cloud/deployment/custom_docker.md": "https://docs.langchain.com/langgraph-platform/custom-docker",
"cloud/deployment/graph_rebuild.md": "https://docs.langchain.com/langgraph-platform/graph-rebuild",
"concepts/langgraph_cloud.md": "https://docs.langchain.com/langgraph-platform/cloud",
"concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/hybrid",
"concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/self-hosted",
"concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langgraph-platform/self-hosted#standalone-server",
"cloud/deployment/cloud.md": "https://docs.langchain.com/langgraph-platform/cloud",
"cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-hybrid",
"cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-self-hosted-full-platform",
"cloud/deployment/standalone_container.md": "https://docs.langchain.com/langgraph-platform/deploy-standalone-server",
"concepts/server-mcp.md": "https://docs.langchain.com/langgraph-platform/server-mcp",
"cloud/how-tos/human_in_the_loop_time_travel.md": "https://docs.langchain.com/langgraph-platform/human-in-the-loop-time-travel",
"cloud/how-tos/add-human-in-the-loop.md": "https://docs.langchain.com/langgraph-platform/add-human-in-the-loop",
"cloud/deployment/egress.md": "https://docs.langchain.com/langgraph-platform/env-var",
"cloud/how-tos/streaming.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/reference/api/api_ref.md": "https://docs.langchain.com/langgraph-platform/server-api-ref",
"cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langgraph-platform/langgraph-server-changelog",
"cloud/reference/api/api_ref_control_plane.md": "https://docs.langchain.com/langgraph-platform/api-ref-control-plane",
"cloud/reference/cli.md": "https://docs.langchain.com/langgraph-platform/cli",
"cloud/reference/env_var.md": "https://docs.langchain.com/langgraph-platform/env-var",
"troubleshooting/studio.md": "https://docs.langchain.com/langgraph-platform/troubleshooting-studio",
}
@@ -255,38 +80,6 @@ def _add_path_to_code_blocks(markdown: str, page: Page) -> str:
return code_block_pattern.sub(replace_code_block_header, markdown)
# Compiled regex patterns for better performance and readability
def _apply_conditional_rendering(md_text: str, target_language: str) -> str:
if target_language not in {"python", "js"}:
raise ValueError("target_language must be 'python' or 'js'")
pattern = re.compile(
r"(?P<indent>[ \t]*):::(?P<language>\w+)\s*\n"
r"(?P<content>((?:.*\n)*?))" # Capture the content inside the block
r"(?P=indent)[ \t]*:::" # Match closing with the same indentation + any additional whitespace
)
def replace_conditional_blocks(match: re.Match) -> str:
"""Keep active conditionals."""
language = match.group("language")
content = match.group("content")
if language not in {"python", "js"}:
# If the language is not supported, return the original block
return match.group(0)
if language == target_language:
return content
# If the language does not match, return an empty string
return ""
processed = pattern.sub(replace_conditional_blocks, md_text)
return processed
def _highlight_code_blocks(markdown: str) -> str:
"""Find code blocks with highlight comments and add hl_lines attribute.
@@ -350,7 +143,7 @@ def _highlight_code_blocks(markdown: str) -> str:
opening_fence += f" {attributes}"
if highlighted_lines:
opening_fence += f' hl_lines="{" ".join(highlighted_lines)}"'
opening_fence += f" hl_lines=\"{' '.join(highlighted_lines)}\""
return (
# The indent and opening fence
@@ -365,21 +158,6 @@ def _highlight_code_blocks(markdown: str) -> str:
return markdown
def _save_page_output(markdown: str, output_path: str):
"""Save markdown content to a file, creating parent directories if needed.
Args:
markdown: The markdown content to save
output_path: The file path to save to
"""
# Create parent directories recursively if they don't exist
os.makedirs(os.path.dirname(output_path), exist_ok=True)
# Write the markdown content to the file
with open(output_path, "w", encoding="utf-8") as f:
f.write(markdown)
def _on_page_markdown_with_config(
markdown: str,
page: Page,
@@ -395,23 +173,12 @@ def _on_page_markdown_with_config(
# logger.info("Processing Jupyter notebook: %s", page.file.src_path)
markdown = convert_notebook(page.file.abs_src_path)
target_language = kwargs.get(
"target_language",
os.environ.get("TARGET_LANGUAGE", "python")
)
# Apply cross-reference preprocessing to all markdown content
markdown = _replace_autolinks(markdown, page.file.src_path, default_scope=target_language)
# Append API reference links to code blocks
if add_api_references:
markdown = update_markdown_with_imports(markdown, page.file.abs_src_path)
# Apply highlight comments to code blocks
markdown = _highlight_code_blocks(markdown)
# Apply conditional rendering for code blocks
markdown = _apply_conditional_rendering(markdown, target_language)
# Add file path as an attribute to code blocks that are executable.
# This file path is used to associate fixtures with the executable code
# which can be used in CI to test the docs without making network requests.
@@ -425,20 +192,12 @@ def _on_page_markdown_with_config(
def on_page_markdown(markdown: str, page: Page, **kwargs: Dict[str, Any]):
finalized_markdown = _on_page_markdown_with_config(
return _on_page_markdown_with_config(
markdown,
page,
add_api_references=True,
**kwargs,
)
page.meta["original_markdown"] = finalized_markdown
output_path = os.environ.get("MD_OUTPUT_PATH")
if output_path:
file_path = os.path.join(output_path, page.file.src_path)
_save_page_output(finalized_markdown, file_path)
return finalized_markdown
# redirects
@@ -461,7 +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)
@@ -477,135 +236,20 @@ 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 _inject_markdown_into_html(html: str, page: Page) -> str:
"""Inject the original markdown content into the HTML page as JSON."""
original_markdown = page.meta.get("original_markdown", "")
if not original_markdown:
return html
markdown_data = {
"markdown": original_markdown,
"title": page.title or "Page Content",
"url": page.url or "",
}
# Properly escape the JSON for HTML
json_content = json.dumps(markdown_data, ensure_ascii=False)
json_content = (
json_content.replace("</", "\\u003c/")
.replace("<script", "\\u003cscript")
.replace("</script", "\\u003c/script")
)
script_content = (
f'<script id="page-markdown-content" '
f'type="application/json">{json_content}</script>'
)
# Insert before </head> if it exists, otherwise before </body>
if "</head>" not in html:
raise ValueError(
"HTML does not contain </head> tag. Cannot inject markdown content."
)
return html.replace("</head>", f"{script_content}</head>")
def on_post_page(html: str, page: Page, config: MkDocsConfig) -> str:
"""Inject Google Tag Manager noscript tag immediately after <body>.
Args:
html: The HTML output of the page.
page: The page instance.
config: The MkDocs configuration object.
Returns:
modified HTML output with GTM code injected.
"""
html = _inject_markdown_into_html(html, page)
return _inject_gtm(html)
# Create HTML files for redirects after site dir has been built
def on_post_build(config):
use_directory_urls = config.get("use_directory_urls")
for page_old, page_new in REDIRECT_MAP.items():
# Convert .ipynb to .md for path calculation
page_old = page_old.replace(".ipynb", ".md")
# Calculate the HTML path for the old page (whether it exists or not)
if use_directory_urls:
# With directory URLs: /path/to/page/ becomes /path/to/page/index.html
if page_old.endswith(".md"):
old_html_path = page_old[:-3] + "/index.html"
else:
old_html_path = page_old + "/index.html"
else:
# Without directory URLs: /path/to/page.md becomes /path/to/page.html
if page_old.endswith(".md"):
old_html_path = page_old[:-3] + ".html"
else:
old_html_path = page_old + ".html"
if isinstance(page_new, str) and page_new.startswith("http"):
# Handle external redirects
_write_html(config["site_dir"], old_html_path, page_new)
else:
# Handle internal redirects
page_new = page_new.replace(".ipynb", ".md")
page_new_before_hash, hash, suffix = page_new.partition("#")
# Try to get the new path using File class, but fallback to manual calculation
try:
new_html_path = File(page_new_before_hash, "", "", True).url
new_html_path = (
posixpath.relpath(new_html_path, start=posixpath.dirname(old_html_path))
+ hash
+ suffix
)
except:
# Fallback: calculate relative path manually
if use_directory_urls:
if page_new_before_hash.endswith(".md"):
new_html_path = page_new_before_hash[:-3] + "/"
else:
new_html_path = page_new_before_hash + "/"
else:
if page_new_before_hash.endswith(".md"):
new_html_path = page_new_before_hash[:-3] + ".html"
else:
new_html_path = page_new_before_hash + ".html"
new_html_path += hash + suffix
_write_html(config["site_dir"], old_html_path, new_html_path)
page_new = page_new.replace(".ipynb", ".md")
page_new_before_hash, hash, suffix = page_new.partition("#")
old_html_path = File(page_old, "", "", use_directory_urls).dest_path.replace(
os.sep, "/"
)
new_html_path = File(page_new_before_hash, "", "", True).url
new_html_path = (
posixpath.relpath(new_html_path, start=posixpath.dirname(old_html_path))
+ hash
+ suffix
)
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(
@@ -9,16 +9,18 @@ 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.
## 📚 Available Libraries
[//]: # (This file is automatically generated using a script in docs/_scripts. Do not edit this file directly!)
:::python
{python_library_list}
{library_list}
## ✨ Contributing Your Library
@@ -29,39 +31,16 @@ To share your project, simply open a Pull Request adding an entry for your packa
**Guidelines**
- Your repo must be distributed as an installable package on PyPI 📦
- Your repo must be distributed as an installable package (e.g., PyPI for Python, npm
for JavaScript/TypeScript, etc.) 📦
- The repo should either use the Graph API (exposing a `StateGraph` instance) or
the Functional API (exposing an `entrypoint`).
- The package must include documentation (e.g., a `README.md` or docs site)
explaining how to use it.
We'll review your contribution and merge it in!
Thanks for contributing! 🚀
:::
:::js
{js_library_list}
## ✨ Contributing Your Library
Have you built an awesome open-source library using LangGraph? We'd love to feature
your project on the official LangGraph documentation pages! 🏆
To share your project, simply open a Pull Request adding an entry for your package in our [packages.yml]({langgraph_url}) file.
**Guidelines**
- Your repo must be distributed as an installable package on npm 📦
- The repo should either use the Graph API (exposing a `StateGraph` instance) or
the Functional API (exposing an `entrypoint`).
- The package must include documentation (e.g., a `README.md` or docs site)
explaining how to use it.
We'll review your contribution and merge it in!
Thanks for contributing! 🚀
:::
"""
@@ -70,18 +49,36 @@ class ResolvedPackage(TypedDict):
"""The name of the package."""
repo: str
"""Repository ID within github. Format is: [orgname]/[repo_name]."""
monorepo_path: str | None
"""Optional: The path to the package in the monorepo. Must be relative to the root of the monorepo."""
language: str
"""The language of the package. (either 'python' or 'js')"""
weekly_downloads: int | None
"""The weekly download count of the package."""
description: str
"""A brief description of what the package does."""
def generate_package_table(resolved_packages: List[ResolvedPackage]) -> str:
"""Generate the package table for the third party page.
def generate_markdown(resolved_packages: List[ResolvedPackage], language: str) -> str:
"""Generate the markdown content for the third party page.
Args:
resolved_packages: A list of resolved package information.
language: str
Returns:
The markdown content as a string.
"""
# Update the URL to the actual file once the initial version is merged
if language == "python":
langgraph_url = (
"https://github.com/langchain-ai/langgraph/blob/main/docs"
"/_scripts/third_party_page/packages.yml"
)
elif language == "js":
langgraph_url = (
"https://github.com/langchain-ai/langgraphjs/blob/main/docs"
"/_scripts/third_party/packages.yml"
)
else:
raise ValueError(f"Invalid language '{language}'. Expected 'python' or 'js'.")
sorted_packages = sorted(
resolved_packages, key=lambda p: p["weekly_downloads"] or 0, reverse=True
)
@@ -91,15 +88,7 @@ def generate_package_table(resolved_packages: List[ResolvedPackage]) -> str:
]
for package in sorted_packages:
name = f"**{package['name']}**"
monorepo_path = package.get("monorepo_path", "")
if monorepo_path:
monorepo_path = monorepo_path[1:] if monorepo_path.startswith('/') else monorepo_path
repo_url_suffix = f"/tree/main/{monorepo_path}"
else:
repo_url_suffix = ""
repo_url = f"https://github.com/{package['repo']}{repo_url_suffix}"
repo_url = f"[{package['repo']}](https://github.com/{package['repo']})"
stars_badge = (
f"https://img.shields.io/github/stars/{package['repo']}?style=social"
)
@@ -107,39 +96,13 @@ def generate_package_table(resolved_packages: List[ResolvedPackage]) -> str:
downloads = package["weekly_downloads"] or "-"
row = f"| {name} | {repo_url} | {package['description']} | {downloads} | {stars}"
rows.append(row)
return "\n".join(rows)
def generate_markdown(resolved_packages: List[ResolvedPackage]) -> str:
"""Generate the markdown content for the third party page.
Args:
resolved_packages: A list of resolved package information.
Returns:
The markdown content as a string.
"""
# Update the URL to the actual file once the initial version is merged
langgraph_url = (
"https://github.com/langchain-ai/langgraph/blob/main/docs"
"/_scripts/third_party_page/packages.yml"
)
python_library_list = generate_package_table(
[p for p in resolved_packages if p["language"] == "python"]
)
js_library_list = generate_package_table(
[p for p in resolved_packages if p["language"] == "js"]
)
markdown_content = MARKDOWN.format(
python_library_list=python_library_list,
js_library_list=js_library_list,
langgraph_url=langgraph_url,
library_list="\n".join(rows), langgraph_url=langgraph_url
)
return markdown_content
def main(input_file: str, output_file: str) -> None:
def main(input_file: str, output_file: str, language: str) -> None:
"""Main function to create the third party page.
Args:
@@ -151,7 +114,7 @@ def main(input_file: str, output_file: str) -> None:
with open(input_file, "r") as f:
resolved_packages: List[ResolvedPackage] = yaml.safe_load(f)
markdown_content = generate_markdown(resolved_packages)
markdown_content = generate_markdown(resolved_packages, language)
# Write the markdown content to the output file
with open(output_file, "w", encoding="utf-8") as f:
@@ -167,6 +130,12 @@ if __name__ == "__main__":
parser.add_argument(
"output_file", help="Path to the output file for the third party page."
)
parser.add_argument(
"--language",
choices=["python", "js"],
default="python",
help="The language for which to generate the third party page. Defaults to 'python'.",
)
args = parser.parse_args()
main(args.input_file, args.output_file)
main(args.input_file, args.output_file, args.language)
@@ -11,146 +11,101 @@ import yaml
class Package(TypedDict):
"""A TypedDict representing a package"""
name: str
"""The name of the package."""
repo: str
"""Repository ID within github. Format is: [orgname]/[repo_name]."""
monorepo_path: str | None
"""The path to the package in the monorepo. Only used for JS packages."""
description: str
"""A brief description of what the package does."""
class ResolvedPackage(Package):
weekly_downloads: int | None
"""The weekly download count of the package."""
language: str
"""The language of the package. (either 'python' or 'js')"""
HERE = pathlib.Path(__file__).parent
PACKAGES_FILE = HERE / "packages.yml"
PACKAGES = yaml.safe_load(PACKAGES_FILE.read_text())["packages"]
PACKAGES = yaml.safe_load(PACKAGES_FILE.read_text())['packages']
def _get_pypi_downloads(package: Package) -> int:
"""Retrieve the weekly download count for a package from PyPIStats."""
# First check if package exists on PyPI
pypi_url = f"https://pypi.org/pypi/{package['name']}/json"
try:
pypi_response = requests.get(pypi_url)
pypi_response.raise_for_status()
except requests.exceptions.HTTPError:
raise AssertionError(f"Package {package['name']} does not exist on PyPI")
# Get first release date
pypi_data = pypi_response.json()
releases = pypi_data["releases"]
first_release_date = None
for version_releases in releases.values():
if version_releases: # Some versions may be empty lists
upload_time = datetime.fromisoformat(version_releases[0]["upload_time"])
if first_release_date is None or upload_time < first_release_date:
first_release_date = upload_time
if first_release_date is None:
raise AssertionError(f"Package {package['name']} has no releases yet")
# If package was published in last 48 hours, skip download stats
if (datetime.now() - first_release_date).total_seconds() >= 48 * 3600:
url = f"https://pypistats.org/api/packages/{package['name']}/overall"
response = requests.get(url)
response.raise_for_status()
data = response.json()
sorted_data = sorted(
data["data"],
key=lambda x: datetime.strptime(x["date"], "%Y-%m-%d"),
reverse=True,
)
# Sum the last 7 days of downloads
return sum(entry["downloads"] for entry in sorted_data[:7])
else:
return None
def _get_npm_downloads(package: Package) -> int:
"""Retrieve the weekly download count for a package on the npm registry."""
# Check if package exists on the npm registry
npm_url = f"https://registry.npmjs.org/{package['name']}"
try:
npm_response = requests.get(npm_url)
npm_response.raise_for_status()
except requests.exceptions.HTTPError:
raise AssertionError(f"Package {package['name']} does not exist on npm registry")
npm_data = npm_response.json()
# Retrieve the first publish date using the 'created' timestamp from the 'time' field.
created_str = npm_data.get("time", {}).get("created")
if created_str is None:
raise AssertionError(f"Package {package['name']} has no creation time in registry data")
# Remove the trailing 'Z' if present and parse the ISO format timestamp
first_publish_date = datetime.fromisoformat(created_str.rstrip("Z"))
# If package was published more than 48 hours ago, fetch download stats.
if (datetime.now() - first_publish_date).total_seconds() >= 48 * 3600:
stats_url = f"https://api.npmjs.org/downloads/point/last-week/{package['name']}"
stats_response = requests.get(stats_url)
stats_response.raise_for_status()
stats_data = stats_response.json()
return stats_data.get("downloads", None)
else:
return None
def _get_weekly_downloads(packages: dict[str, list[Package]], fake: bool) -> list[ResolvedPackage]:
"""Retrieve the weekly download count for a dictionary of python or js packages."""
def _get_weekly_downloads(packages: list[Package], fake: bool) -> list[ResolvedPackage]:
"""Retrieve the monthly download count for a list of packages from PyPIStats."""
resolved_packages: list[ResolvedPackage] = []
if fake:
# To avoid making network requests during testing, return fake download counts
for language, package_list in packages.items():
for package in package_list:
resolved_packages.append(
{
"name": package["name"],
"repo": package["repo"],
"monorepo_path": package.get("monorepo_path", None),
"language": language,
"description": package["description"],
"weekly_downloads": -12345,
}
)
return resolved_packages
for language, package_list in packages.items():
for package in package_list:
if language == "python":
num_downloads = _get_pypi_downloads(package)
elif language == "js":
num_downloads = _get_npm_downloads(package)
else:
num_downloads = None
for package in packages:
resolved_packages.append(
{
"name": package["name"],
"repo": package["repo"],
"monorepo_path": package.get("monorepo_path", None),
"language": language,
"weekly_downloads": -12345,
"description": package["description"],
"weekly_downloads": num_downloads,
}
)
return resolved_packages
for package in packages:
# First check if package exists on PyPI
pypi_url = f"https://pypi.org/pypi/{package['name']}/json"
try:
pypi_response = requests.get(pypi_url)
pypi_response.raise_for_status()
except requests.exceptions.HTTPError:
raise AssertionError(f"Package {package['name']} does not exist on PyPI")
# Get first release date
pypi_data = pypi_response.json()
releases = pypi_data["releases"]
first_release_date = None
for version_releases in releases.values():
if version_releases: # Some versions may be empty lists
upload_time = datetime.fromisoformat(version_releases[0]["upload_time"])
if first_release_date is None or upload_time < first_release_date:
first_release_date = upload_time
if first_release_date is None:
raise AssertionError(f"Package {package['name']} has no releases yet")
# If package was published in last 48 hours, skip download stats
if (datetime.now() - first_release_date).total_seconds() >= 48 * 3600:
url = f"https://pypistats.org/api/packages/{package['name']}/overall"
response = requests.get(url)
response.raise_for_status()
data = response.json()
sorted_data = sorted(
data["data"],
key=lambda x: datetime.strptime(x["date"], "%Y-%m-%d"),
reverse=True,
)
# Sum the last 7 days of downloads
num_downloads = sum(entry["downloads"] for entry in sorted_data[:7])
else:
num_downloads = None
resolved_packages.append(
{
"name": package["name"],
"repo": package["repo"],
"weekly_downloads": num_downloads,
"description": package["description"],
}
)
return resolved_packages
def main(output_file: str, fake: bool) -> None:
"""Main function to generate package download information.
Args:
output_file: Path to the output YAML file.
fake: If True, use fake download counts for testing purposes.
"""
resolved_packages: list[ResolvedPackage] = _get_weekly_downloads(PACKAGES, fake)
+39 -56
View File
@@ -1,58 +1,41 @@
#A list of third-party packages to surface on the third-party page.
packages:
python:
- name: "trustcall"
repo: "hinthornw/trustcall"
description: "Tenacious tool calling built on LangGraph."
- name: "breeze-agent"
repo: "andrestorres123/breeze-agent"
description: "A streamlined research system built inspired on STORM and built on LangGraph."
- name: "langgraph-supervisor"
repo: "langchain-ai/langgraph-supervisor-py"
description: "Build supervisor multi-agent systems with LangGraph."
- name: "langmem"
repo: "langchain-ai/langmem"
description: "Build agents that learn and adapt from interactions over time."
- name: "langchain-mcp-adapters"
repo: "langchain-ai/langchain-mcp-adapters"
description: "Make Anthropic Model Context Protocol (MCP) tools compatible with LangGraph agents."
- name: "open-deep-research"
repo: "langchain-ai/open_deep_research"
description: "Open source assistant for iterative web research and report writing."
- name: "langgraph-swarm"
repo: "langchain-ai/langgraph-swarm-py"
description: "Build swarm-style multi-agent systems using LangGraph."
- name: "delve-taxonomy-generator"
repo: "andrestorres123/delve"
description: "A taxonomy generator for unstructured data"
- name: "nodeology"
repo: "xyin-anl/Nodeology"
description: "Enable researcher to build scientific workflows easily with simplified interface."
- name: "langgraph-bigtool"
repo: "langchain-ai/langgraph-bigtool"
description: "Build LangGraph agents with large numbers of tools."
- name: "ai-data-science-team"
repo: "business-science/ai-data-science-team"
description: "An AI-powered data science team of agents to help you perform common data science tasks 10X faster."
- name: "langgraph-reflection"
repo: "langchain-ai/langgraph-reflection"
description: "LangGraph agent that runs a reflection step."
- name: "langgraph-codeact"
repo: "langchain-ai/langgraph-codeact"
description: "LangGraph implementation of CodeAct agent that generates and executes code instead of tool calling."
js:
- name: "@langchain/mcp-adapters"
repo: "langchain-ai/langchainjs"
description: "Make Anthropic Model Context Protocol (MCP) tools compatible with LangGraph agents."
- name: "@langchain/langgraph-supervisor"
repo: "langchain-ai/langgraphjs"
monorepo_path: "libs/langgraph-supervisor"
description: "Build supervisor multi-agent systems with LangGraph"
- name: "@langchain/langgraph-swarm"
repo: "langchain-ai/langgraphjs"
monorepo_path: "libs/langgraph-swarm"
description: "Build multi-agent swarms with LangGraph"
- name: "@langchain/langgraph-cua"
repo: "langchain-ai/langgraphjs"
monorepo_path: "libs/langgraph-cua"
description: "Build computer use agents with LangGraph"
- name: "trustcall"
repo: "hinthornw/trustcall"
description: "Tenacious tool calling built on LangGraph."
- name: "breeze-agent"
repo: "andrestorres123/breeze-agent"
description: "A streamlined research system built inspired on STORM and built on LangGraph."
- name: "langgraph-supervisor"
repo: "langchain-ai/langgraph-supervisor-py"
description: "Build supervisor multi-agent systems with LangGraph."
- name: "langmem"
repo: "langchain-ai/langmem"
description: "Build agents that learn and adapt from interactions over time."
- name: "langchain-mcp-adapters"
repo: "langchain-ai/langchain-mcp-adapters"
description: "Make Anthropic Model Context Protocol (MCP) tools compatible with LangGraph agents."
- name: "open-deep-research"
repo: "langchain-ai/open_deep_research"
description: "Open source assistant for iterative web research and report writing."
- name: "langgraph-swarm"
repo: "langchain-ai/langgraph-swarm-py"
description: "Build swarm-style multi-agent systems using LangGraph."
- name: "delve-taxonomy-generator"
repo: "andrestorres123/delve"
description: "A taxonomy generator for unstructured data"
- name: "nodeology"
repo: "xyin-anl/Nodeology"
description: "Enable researcher to build scientific workflows easily with simplified interface."
- name: "langgraph-bigtool"
repo: "langchain-ai/langgraph-bigtool"
description: "Build LangGraph agents with large numbers of tools."
- name: "ai-data-science-team"
repo: "business-science/ai-data-science-team"
description: "An AI-powered data science team of agents to help you perform common data science tasks 10X faster."
- name: "langgraph-reflection"
repo: "langchain-ai/langgraph-reflection"
description: "LangGraph agent that runs a reflection step."
- name: "langgraph-codeact"
repo: "langchain-ai/langgraph-codeact"
description: "LangGraph implementation of CodeAct agent that generates and executes code instead of tool calling."
@@ -0,0 +1 @@
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@@ -1 +1 @@
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@@ -1 +0,0 @@
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