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9b6100bc4f | ||
|
|
238b562e78 | ||
|
|
7fcc0da4e3 | ||
|
|
d7eff6ab85 | ||
|
|
330c91f622 | ||
|
|
3dbf6f144e | ||
|
|
8c2fefcb28 | ||
|
|
86c047eb31 | ||
|
|
a161a9ca97 | ||
|
|
422ed92aef | ||
|
|
eee91d2129 |
@@ -7,35 +7,29 @@ body:
|
||||
value: >
|
||||
Thank you for taking the time to file a bug report.
|
||||
|
||||
Use this to report bugs in LangChain.
|
||||
|
||||
If you're not certain that your issue is due to a bug in LangChain, please use [GitHub Discussions](https://github.com/langchain-ai/langchain/discussions)
|
||||
to ask for help with your issue.
|
||||
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:
|
||||
|
||||
[LangGraph documentation](https://langchain-ai.github.io/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),
|
||||
[LangChain Github Discussions](https://github.com/langchain-ai/langgraph/discussions),
|
||||
[LangChain Github Issues](https://github.com/langchain-ai/langgraph/issues),
|
||||
[LangChain ChatBot](https://chat.langchain.com/)
|
||||
- type: checkboxes
|
||||
id: checks
|
||||
attributes:
|
||||
label: Checked other resources
|
||||
description: Please confirm and check all the following options.
|
||||
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: I added a very descriptive title to this issue.
|
||||
- label: This is a bug, not a usage question. For questions, please use GitHub Discussions.
|
||||
required: true
|
||||
- label: I searched the [LangGraph](https://langchain-ai.github.io/langgraph/)/LangChain documentation with the integrated search.
|
||||
- label: I added a clear and detailed title that summarizes the issue.
|
||||
required: true
|
||||
- label: I used the GitHub search to find a similar question and didn't find it.
|
||||
- label: I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
|
||||
required: true
|
||||
- label: I am sure that this is a bug in LangGraph/LangChain rather than my code.
|
||||
required: true
|
||||
- label: I am sure this is better as an issue [rather than a GitHub discussion](https://github.com/langchain-ai/langgraph/discussions/new/choose), since this is a LangGraph bug and not a design question.
|
||||
- label: I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
|
||||
required: true
|
||||
- type: textarea
|
||||
id: reproduction
|
||||
@@ -45,14 +39,6 @@ body:
|
||||
label: Example Code
|
||||
description: |
|
||||
Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case.
|
||||
|
||||
If a maintainer can copy it, run it, and see it right away, there's a much higher chance that you'll be able to get help.
|
||||
|
||||
**Important!**
|
||||
|
||||
* Reduce your code to the minimum required to reproduce the issue if possible. This makes it much easier for others to help you.
|
||||
* Avoid screenshots when possible, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
|
||||
|
||||
placeholder: |
|
||||
from langgraph.graph import StateGraph
|
||||
|
||||
@@ -92,25 +78,8 @@ body:
|
||||
attributes:
|
||||
label: System Info
|
||||
description: |
|
||||
Please share your system info with us.
|
||||
|
||||
"pip freeze | grep langchain"
|
||||
platform (windows / linux / mac)
|
||||
python version
|
||||
|
||||
OR if you're on a recent version of langchain-core you can paste the output of:
|
||||
|
||||
python -m langchain_core.sys_info
|
||||
placeholder: |
|
||||
"pip freeze | grep langgraph"
|
||||
platform
|
||||
python version
|
||||
|
||||
Alternatively, if you're on a recent version of langchain-core you can paste the output of:
|
||||
|
||||
python -m langchain_core.sys_info
|
||||
|
||||
These will only surface LangChain packages, don't forget to include any other relevant
|
||||
packages you're using (if you're not sure what's relevant, you can paste the entire output of `pip freeze`).
|
||||
validations:
|
||||
required: true
|
||||
|
||||
@@ -1,88 +0,0 @@
|
||||
# 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') }}
|
||||
@@ -0,0 +1,64 @@
|
||||
import ast
|
||||
import os
|
||||
from itertools import filterfalse
|
||||
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")
|
||||
|
||||
|
||||
def get_class_methods(node: ast.ClassDef) -> List[str]:
|
||||
return [n.name for n in node.body if isinstance(n, (ast.FunctionDef, ast.AsyncFunctionDef))]
|
||||
|
||||
|
||||
def find_classes(tree: ast.AST) -> List[Tuple[str, List[str]]]:
|
||||
classes = []
|
||||
for node in ast.walk(tree):
|
||||
if isinstance(node, ast.ClassDef):
|
||||
methods = get_class_methods(node)
|
||||
classes.append((node.name, methods))
|
||||
return classes
|
||||
|
||||
|
||||
def compare_sync_async_methods(sync_methods: List[str], async_methods: List[str]) -> List[str]:
|
||||
sync_set = set(sync_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
|
||||
|
||||
|
||||
def main():
|
||||
with open(CLIENT_PATH, "r") as file:
|
||||
tree = ast.parse(file.read())
|
||||
|
||||
classes = find_classes(tree)
|
||||
|
||||
def is_sync(class_spec: Tuple[str, List[str]]) -> bool:
|
||||
return class_spec[0].startswith("Sync")
|
||||
|
||||
sync_class_name_to_methods = {class_name: class_methods for class_name, class_methods in filter(is_sync, classes)}
|
||||
async_class_name_to_methods = {class_name: class_methods for class_name, class_methods in filterfalse(is_sync, classes)}
|
||||
|
||||
mismatches = []
|
||||
|
||||
for async_class_name, async_class_methods in async_class_name_to_methods.items():
|
||||
sync_class_name = "Sync" + async_class_name
|
||||
sync_class_methods = sync_class_name_to_methods.get(sync_class_name, [])
|
||||
diff = compare_sync_async_methods(sync_class_methods, async_class_methods)
|
||||
if diff:
|
||||
mismatches.append((sync_class_name, async_class_name, diff))
|
||||
|
||||
if mismatches:
|
||||
error_message = "Mismatches found between sync and async client methods:\n"
|
||||
for sync_class_name, async_class_name, diff in mismatches:
|
||||
error_message += f"{sync_class_name} vs {async_class_name}:\n"
|
||||
for method in diff:
|
||||
error_message += f" - {method}\n"
|
||||
raise ValueError(error_message)
|
||||
|
||||
print("All sync and async client methods match.")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,115 @@
|
||||
import asyncio
|
||||
import json
|
||||
import os
|
||||
import pathlib
|
||||
import sys
|
||||
import langgraph_cli
|
||||
import langgraph_cli.docker
|
||||
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,
|
||||
):
|
||||
with Runner() as runner, Progress(message="Pulling...") as set:
|
||||
# check docker available
|
||||
capabilities = langgraph_cli.docker.check_capabilities(runner)
|
||||
# open config
|
||||
config_json = langgraph_cli.config.validate_config_file(config)
|
||||
|
||||
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",
|
||||
]
|
||||
)
|
||||
|
||||
_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
|
||||
|
||||
try:
|
||||
runner.run(
|
||||
subp_exec_task(
|
||||
"docker",
|
||||
*args,
|
||||
tag,
|
||||
verbose=verbose,
|
||||
on_stdout=on_stdout,
|
||||
)
|
||||
)
|
||||
except asyncio.CancelledError:
|
||||
pass
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import argparse
|
||||
|
||||
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", default=DEFAULT_PORT)
|
||||
args = parser.parse_args()
|
||||
test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
|
||||
@@ -3,9 +3,6 @@ name: CLI integration test
|
||||
on:
|
||||
workflow_call:
|
||||
|
||||
env:
|
||||
POETRY_VERSION: "1.7.1"
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
@@ -22,16 +19,17 @@ jobs:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Get changed files
|
||||
id: changed-files
|
||||
uses: Ana06/get-changed-files@v2.2.0
|
||||
uses: Ana06/get-changed-files@v2.3.0
|
||||
with:
|
||||
filter: "libs/cli/**"
|
||||
- name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
if: steps.changed-files.outputs.all
|
||||
uses: "./.github/actions/poetry_setup"
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
poetry-version: ${{ env.POETRY_VERSION }}
|
||||
cache-key: integration-test-cli
|
||||
enable-cache: true
|
||||
cache-suffix: "cli-integration-test"
|
||||
ignore-nothing-to-cache: true
|
||||
- name: Setup env
|
||||
if: steps.changed-files.outputs.all
|
||||
working-directory: libs/cli/examples
|
||||
@@ -39,22 +37,35 @@ jobs:
|
||||
- name: Install cli globally
|
||||
if: steps.changed-files.outputs.all
|
||||
run: pip install -e .
|
||||
- name: Start service A
|
||||
- name: Build and test service A
|
||||
if: steps.changed-files.outputs.all
|
||||
working-directory: libs/cli/examples
|
||||
run: |
|
||||
timeout 60 langgraph test -c examples/langgraph.json --verbose || (exit "$(($? == 124 ? 0 : $?))")
|
||||
- name: Start service B
|
||||
# The build-arg isn't used; just testing that we accept other args
|
||||
langgraph build -t langgraph-test-a --base-image "langchain/langgraph-trial"
|
||||
cp .env.example .envg
|
||||
timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -c langgraph.json -t langgraph-test-a
|
||||
- name: Build and test service B
|
||||
if: steps.changed-files.outputs.all
|
||||
working-directory: libs/cli/examples/graphs
|
||||
run: |
|
||||
timeout 60 langgraph test --verbose || (exit "$(($? == 124 ? 0 : $?))")
|
||||
- name: Start service C
|
||||
langgraph build -t langgraph-test-b --base-image "langchain/langgraph-trial"
|
||||
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-b
|
||||
- name: Build and test service C
|
||||
if: steps.changed-files.outputs.all
|
||||
working-directory: libs/cli/examples/graphs_reqs_a
|
||||
run: |
|
||||
timeout 60 langgraph test --verbose || (exit "$(($? == 124 ? 0 : $?))")
|
||||
- name: Start service D
|
||||
langgraph build -t langgraph-test-c --base-image "langchain/langgraph-trial"
|
||||
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-c
|
||||
- name: Build and test service D
|
||||
if: steps.changed-files.outputs.all
|
||||
working-directory: libs/cli/examples/graphs_reqs_b
|
||||
run: |
|
||||
timeout 60 langgraph test --verbose || (exit "$(($? == 124 ? 0 : $?))")
|
||||
langgraph build -t langgraph-test-d --base-image "langchain/langgraph-trial"
|
||||
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-d
|
||||
|
||||
- name: Build JS service
|
||||
if: steps.changed-files.outputs.all
|
||||
working-directory: libs/cli/js-examples
|
||||
run: |
|
||||
langgraph build -t langgraph-test-e
|
||||
|
||||
+10
-43
@@ -9,8 +9,6 @@ on:
|
||||
description: "From which folder this pipeline executes"
|
||||
|
||||
env:
|
||||
POETRY_VERSION: "1.7.1"
|
||||
|
||||
# This env var allows us to get inline annotations when ruff has complaints.
|
||||
RUFF_OUTPUT_FORMAT: github
|
||||
|
||||
@@ -27,49 +25,27 @@ jobs:
|
||||
# Starting new jobs is also relatively slow,
|
||||
# so linting on fewer versions makes CI faster.
|
||||
python-version:
|
||||
- "3.9"
|
||||
- "3.11"
|
||||
- "3.12"
|
||||
name: "lint #${{ matrix.python-version }}"
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Get changed files
|
||||
id: changed-files
|
||||
uses: Ana06/get-changed-files@v2.2.0
|
||||
uses: Ana06/get-changed-files@v2.3.0
|
||||
with:
|
||||
filter: "${{ inputs.working-directory }}/**"
|
||||
- name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
if: steps.changed-files.outputs.all
|
||||
uses: "./.github/actions/poetry_setup"
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
poetry-version: ${{ env.POETRY_VERSION }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
cache-key: lint-with-extras
|
||||
|
||||
- name: Check Poetry File
|
||||
if: steps.changed-files.outputs.all
|
||||
shell: bash
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: poetry check
|
||||
|
||||
- name: Check lock file
|
||||
if: steps.changed-files.outputs.all
|
||||
shell: bash
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: poetry lock --check
|
||||
enable-cache: true
|
||||
cache-suffix: lint-${{ inputs.working-directory }}
|
||||
|
||||
- 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: poetry install --with dev
|
||||
run: uv sync --frozen --group dev
|
||||
|
||||
- name: Get .mypy_cache to speed up mypy
|
||||
if: steps.changed-files.outputs.all
|
||||
@@ -79,7 +55,7 @@ jobs:
|
||||
with:
|
||||
path: |
|
||||
${{ inputs.working-directory }}/.mypy_cache
|
||||
key: mypy-lint-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}
|
||||
key: mypy-lint-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/uv.lock', inputs.working-directory)) }}
|
||||
|
||||
- name: Analysing package code with our lint
|
||||
if: steps.changed-files.outputs.all
|
||||
@@ -94,17 +70,8 @@ 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: |
|
||||
poetry install --with dev
|
||||
run: uv sync --group dev
|
||||
|
||||
- name: Get .mypy_cache_test to speed up mypy
|
||||
if: steps.changed-files.outputs.all
|
||||
@@ -114,7 +81,7 @@ jobs:
|
||||
with:
|
||||
path: |
|
||||
${{ inputs.working-directory }}/.mypy_cache_test
|
||||
key: mypy-test-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}
|
||||
key: mypy-test-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/uv.lock', inputs.working-directory)) }}
|
||||
|
||||
- name: Analysing tests with our lint
|
||||
if: steps.changed-files.outputs.all
|
||||
|
||||
+15
-12
@@ -8,9 +8,6 @@ on:
|
||||
type: string
|
||||
description: "From which folder this pipeline executes"
|
||||
|
||||
env:
|
||||
POETRY_VERSION: "1.7.1"
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
@@ -21,27 +18,33 @@ jobs:
|
||||
- "3.10"
|
||||
- "3.11"
|
||||
- "3.12"
|
||||
- "3.13"
|
||||
|
||||
name: "test #${{ matrix.python-version }}"
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
|
||||
uses: "./.github/actions/poetry_setup"
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
poetry-version: ${{ env.POETRY_VERSION }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
cache-key: core
|
||||
enable-cache: true
|
||||
cache-suffix: test-${{ inputs.working-directory }}
|
||||
- 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
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: poetry install --with dev
|
||||
run: uv sync --frozen --group dev
|
||||
|
||||
- name: Run core tests
|
||||
- name: Run tests
|
||||
shell: bash
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: |
|
||||
make test
|
||||
run: make test
|
||||
|
||||
- name: Ensure the tests did not create any additional files
|
||||
shell: bash
|
||||
|
||||
@@ -0,0 +1,55 @@
|
||||
name: test
|
||||
|
||||
on:
|
||||
workflow_call:
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
matrix:
|
||||
python-version:
|
||||
- "3.9"
|
||||
- "3.10"
|
||||
- "3.11"
|
||||
- "3.12"
|
||||
- "3.13"
|
||||
|
||||
defaults:
|
||||
run:
|
||||
working-directory: libs/langgraph
|
||||
name: "test #${{ matrix.python-version }}"
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
enable-cache: true
|
||||
cache-suffix: "test-langgraph"
|
||||
- name: Login to Docker Hub
|
||||
uses: docker/login-action@v3
|
||||
if: ${{ !github.event.pull_request.head.repo.fork }}
|
||||
with:
|
||||
username: ${{ secrets.DOCKERHUB_USERNAME }}
|
||||
password: ${{ secrets.DOCKERHUB_RO_TOKEN }}
|
||||
|
||||
- name: Install dependencies
|
||||
shell: bash
|
||||
run: uv sync --frozen --group dev
|
||||
|
||||
- name: Run tests
|
||||
shell: bash
|
||||
run: make test_parallel
|
||||
|
||||
- name: Ensure the tests did not create any additional files
|
||||
shell: bash
|
||||
run: |
|
||||
set -eu
|
||||
|
||||
STATUS="$(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'
|
||||
@@ -9,12 +9,11 @@ on:
|
||||
description: "From which folder this pipeline executes"
|
||||
|
||||
env:
|
||||
POETRY_VERSION: "1.7.1"
|
||||
PYTHON_VERSION: "3.10"
|
||||
|
||||
jobs:
|
||||
build:
|
||||
if: github.ref == 'refs/heads/main'
|
||||
if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/v0'
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
outputs:
|
||||
@@ -24,13 +23,12 @@ jobs:
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
|
||||
uses: "./.github/actions/poetry_setup"
|
||||
- name: Set up Python $${ env.PYTHON_VERSION }}
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: ${{ env.PYTHON_VERSION }}
|
||||
poetry-version: ${{ env.POETRY_VERSION }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
cache-key: release
|
||||
enable-cache: true
|
||||
cache-suffix: "release"
|
||||
|
||||
# We want to keep this build stage *separate* from the release stage,
|
||||
# so that there's no sharing of permissions between them.
|
||||
@@ -44,7 +42,7 @@ jobs:
|
||||
# > from the publish job.
|
||||
# https://github.com/pypa/gh-action-pypi-publish#non-goals
|
||||
- name: Build project for distribution
|
||||
run: poetry build
|
||||
run: uv build
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
- name: Upload build
|
||||
@@ -58,8 +56,8 @@ jobs:
|
||||
shell: bash
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: |
|
||||
echo pkg-name="$(poetry version | cut -d ' ' -f 1)" >> $GITHUB_OUTPUT
|
||||
echo version="$(poetry version --short)" >> $GITHUB_OUTPUT
|
||||
echo pkg-name=$(grep -m 1 "^name = " pyproject.toml | cut -d '"' -f 2)
|
||||
echo version=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
|
||||
|
||||
publish:
|
||||
needs:
|
||||
@@ -93,3 +91,5 @@ jobs:
|
||||
# This is *only for CI use* and is *extremely dangerous* otherwise!
|
||||
# https://github.com/pypa/gh-action-pypi-publish#tolerating-release-package-file-duplicates
|
||||
skip-existing: true
|
||||
# Temp workaround since attestations are on by default as of gh-action-pypi-publish v1.11.0
|
||||
attestations: false
|
||||
|
||||
@@ -0,0 +1,52 @@
|
||||
name: test
|
||||
|
||||
on:
|
||||
workflow_call:
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
matrix:
|
||||
python-version:
|
||||
- "3.11"
|
||||
- "3.12"
|
||||
|
||||
defaults:
|
||||
run:
|
||||
working-directory: libs/scheduler-kafka
|
||||
name: "test #${{ matrix.python-version }}"
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
enable-cache: true
|
||||
cache-suffix: "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: ${{ secrets.DOCKERHUB_RO_TOKEN }}
|
||||
|
||||
- name: Install dependencies
|
||||
shell: bash
|
||||
run: uv sync --frozen --group dev
|
||||
|
||||
- name: Run tests
|
||||
shell: bash
|
||||
run: make test
|
||||
|
||||
- name: Ensure the tests did not create any additional files
|
||||
shell: bash
|
||||
run: |
|
||||
set -eu
|
||||
|
||||
STATUS="$(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'
|
||||
@@ -0,0 +1,34 @@
|
||||
name: baseline
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
push:
|
||||
branches: [main]
|
||||
paths:
|
||||
- "libs/**"
|
||||
|
||||
jobs:
|
||||
benchmark:
|
||||
runs-on: ubuntu-latest
|
||||
defaults:
|
||||
run:
|
||||
working-directory: libs/langgraph
|
||||
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
|
||||
with:
|
||||
python-version: "3.11"
|
||||
enable-cache: true
|
||||
cache-suffix: "bench"
|
||||
- name: Install dependencies
|
||||
run: uv sync --group dev
|
||||
- name: Run benchmarks
|
||||
run: OUTPUT=out/benchmark-baseline.json make -s benchmark
|
||||
- name: Save outputs
|
||||
uses: actions/cache/save@v4
|
||||
with:
|
||||
key: ${{ runner.os }}-benchmark-baseline-${{ env.SHA }}
|
||||
path: |
|
||||
libs/langgraph/out/benchmark-baseline.json
|
||||
@@ -0,0 +1,68 @@
|
||||
name: bench
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
paths:
|
||||
- "libs/**"
|
||||
|
||||
jobs:
|
||||
benchmark:
|
||||
runs-on: ubuntu-latest
|
||||
defaults:
|
||||
run:
|
||||
working-directory: libs/langgraph
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- id: files
|
||||
name: Get changed files
|
||||
uses: Ana06/get-changed-files@v2.3.0
|
||||
with:
|
||||
format: json
|
||||
- name: Set up Python 3.11
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: "3.11"
|
||||
enable-cache: true
|
||||
cache-suffix: "bench"
|
||||
- name: Install dependencies
|
||||
run: uv sync --group dev
|
||||
- name: Download baseline
|
||||
uses: actions/cache/restore@v4
|
||||
with:
|
||||
key: ${{ runner.os }}-benchmark-baseline
|
||||
restore-keys: |
|
||||
${{ runner.os }}-benchmark-baseline-
|
||||
fail-on-cache-miss: true
|
||||
path: |
|
||||
libs/langgraph/out/benchmark-baseline.json
|
||||
- name: Run benchmarks
|
||||
id: benchmark
|
||||
run: |
|
||||
{
|
||||
echo 'OUTPUT<<EOF'
|
||||
make -s benchmark-fast
|
||||
echo EOF
|
||||
} >> "$GITHUB_OUTPUT"
|
||||
- name: Compare benchmarks
|
||||
id: compare
|
||||
run: |
|
||||
{
|
||||
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
|
||||
echo EOF
|
||||
} >> "$GITHUB_OUTPUT"
|
||||
- name: Annotation
|
||||
uses: actions/github-script@v7
|
||||
with:
|
||||
script: |
|
||||
const file = JSON.parse(`${{ steps.files.outputs.added_modified_renamed }}`)[0]
|
||||
core.notice(`${{ steps.benchmark.outputs.OUTPUT }}`, {
|
||||
title: 'Benchmark results',
|
||||
file,
|
||||
})
|
||||
core.notice(`${{ steps.compare.outputs.OUTPUT }}`, {
|
||||
title: 'Comparison against main',
|
||||
file,
|
||||
})
|
||||
+229
-109
@@ -1,114 +1,234 @@
|
||||
---
|
||||
name: CI
|
||||
name: CI
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [main]
|
||||
pull_request:
|
||||
on:
|
||||
push:
|
||||
branches: [main]
|
||||
pull_request:
|
||||
|
||||
# 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.
|
||||
#
|
||||
# There's no point in testing an outdated version of the code. GitHub only allows
|
||||
# a limited number of job runners to be active at the same time, so it's better to cancel
|
||||
# pointless jobs early so that more useful jobs can run sooner.
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.ref }}
|
||||
cancel-in-progress: true
|
||||
# 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.
|
||||
#
|
||||
# There's no point in testing an outdated version of the code. GitHub only allows
|
||||
# a limited number of job runners to be active at the same time, so it's better to cancel
|
||||
# pointless jobs early so that more useful jobs can run sooner.
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.ref }}
|
||||
cancel-in-progress: true
|
||||
|
||||
jobs:
|
||||
changes:
|
||||
runs-on: ubuntu-latest
|
||||
outputs:
|
||||
python: ${{ steps.filter.outputs.python }}
|
||||
sdk-js: ${{ steps.filter.outputs.sdk-js }}
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: dorny/paths-filter@v3
|
||||
id: filter
|
||||
with:
|
||||
filters: |
|
||||
python:
|
||||
- 'libs/langgraph/**'
|
||||
- 'libs/sdk-py/**'
|
||||
- 'libs/cli/**'
|
||||
- 'libs/checkpoint/**'
|
||||
- 'libs/checkpoint-sqlite/**'
|
||||
- 'libs/checkpoint-postgres/**'
|
||||
- 'libs/scheduler-kafka/**'
|
||||
- 'libs/prebuilt/**'
|
||||
sdk-js:
|
||||
- 'libs/sdk-js/**'
|
||||
|
||||
lint:
|
||||
needs: changes
|
||||
name: cd ${{ matrix.working-directory }}
|
||||
strategy:
|
||||
matrix:
|
||||
working-directory:
|
||||
[
|
||||
"libs/langgraph",
|
||||
"libs/sdk-py",
|
||||
"libs/cli",
|
||||
"libs/checkpoint",
|
||||
"libs/checkpoint-sqlite",
|
||||
"libs/checkpoint-postgres",
|
||||
"libs/scheduler-kafka",
|
||||
"libs/prebuilt",
|
||||
]
|
||||
if: needs.changes.outputs.python == 'true'
|
||||
uses: ./.github/workflows/_lint.yml
|
||||
with:
|
||||
working-directory: ${{ matrix.working-directory }}
|
||||
secrets: inherit
|
||||
|
||||
test:
|
||||
needs: changes
|
||||
name: cd ${{ matrix.working-directory }}
|
||||
strategy:
|
||||
matrix:
|
||||
working-directory:
|
||||
[
|
||||
"libs/cli",
|
||||
"libs/checkpoint",
|
||||
"libs/checkpoint-sqlite",
|
||||
"libs/checkpoint-postgres",
|
||||
"libs/prebuilt",
|
||||
]
|
||||
if: needs.changes.outputs.python == 'true'
|
||||
uses: ./.github/workflows/_test.yml
|
||||
with:
|
||||
working-directory: ${{ matrix.working-directory }}
|
||||
secrets: inherit
|
||||
|
||||
# NOTE: we're testing langgraph separately because it requires a different matrix
|
||||
test-langgraph:
|
||||
needs: changes
|
||||
if: needs.changes.outputs.python == 'true'
|
||||
name: "cd libs/langgraph"
|
||||
uses: ./.github/workflows/_test_langgraph.yml
|
||||
secrets: inherit
|
||||
|
||||
# NOTE: we're testing scheduler-kafka separately because it requires a different matrix
|
||||
test-scheduler-kafka:
|
||||
needs: changes
|
||||
if: needs.changes.outputs.python == 'true'
|
||||
name: "cd libs/scheduler-kafka"
|
||||
uses: ./.github/workflows/_test_scheduler_kafka.yml
|
||||
secrets: inherit
|
||||
|
||||
check-sdk-methods:
|
||||
needs: changes
|
||||
if: needs.changes.outputs.python == 'true'
|
||||
name: "Check SDK methods matching"
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.11"
|
||||
- name: Run check_sdk_methods script
|
||||
run: python .github/scripts/check_sdk_methods.py
|
||||
|
||||
check-schema:
|
||||
needs: changes
|
||||
if: needs.changes.outputs.python == 'true'
|
||||
name: "Check CLI schema hasn't changed #${{ matrix.python-version }}"
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
matrix:
|
||||
python-version:
|
||||
- "3.11"
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: "3.11"
|
||||
enable-cache: true
|
||||
cache-suffix: "schema-check-cli"
|
||||
- name: Install CLI dependencies
|
||||
run: |
|
||||
cd libs/cli
|
||||
uv sync
|
||||
- name: Generate schema and check for changes
|
||||
run: |
|
||||
cd libs/cli
|
||||
# Create a temporary copy of the current schema
|
||||
cp schemas/schema.json schemas/schema.current.json
|
||||
# Generate new schema
|
||||
uv run python generate_schema.py
|
||||
# Compare the new schema with the original
|
||||
if ! diff -q schemas/schema.json schemas/schema.current.json > /dev/null; then
|
||||
echo "Error: Langgraph.json configuration schema has changed. Please run 'uv run python generate_schema.py' in the libs/cli directory and commit the changes."
|
||||
diff schemas/schema.json schemas/schema.current.json
|
||||
exit 1
|
||||
fi
|
||||
echo "Schema check passed - no changes detected"
|
||||
|
||||
integration-test:
|
||||
needs: changes
|
||||
if: needs.changes.outputs.python == 'true'
|
||||
name: CLI integration test
|
||||
uses: ./.github/workflows/_integration_test.yml
|
||||
secrets: inherit
|
||||
|
||||
lint-js:
|
||||
needs: changes
|
||||
if: needs.changes.outputs.sdk-js == 'true'
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
matrix:
|
||||
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()
|
||||
runs-on: ubuntu-latest
|
||||
env:
|
||||
POETRY_VERSION: "1.7.1"
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.10'
|
||||
|
||||
lint:
|
||||
name: cd ${{ matrix.working-directory }}
|
||||
needs: [ build ]
|
||||
strategy:
|
||||
matrix:
|
||||
working-directory: [
|
||||
"libs/langgraph",
|
||||
"libs/sdk-py",
|
||||
"libs/cli",
|
||||
"libs/checkpoint",
|
||||
"libs/checkpoint-sqlite",
|
||||
"libs/checkpoint-postgres"
|
||||
]
|
||||
uses: ./.github/workflows/_lint.yml
|
||||
with:
|
||||
working-directory: ${{ matrix.working-directory }}
|
||||
secrets: inherit
|
||||
|
||||
test:
|
||||
name: cd ${{ matrix.working-directory }}
|
||||
needs: [ build ]
|
||||
strategy:
|
||||
matrix:
|
||||
working-directory: [
|
||||
"libs/langgraph",
|
||||
"libs/cli",
|
||||
"libs/checkpoint",
|
||||
"libs/checkpoint-sqlite",
|
||||
"libs/checkpoint-postgres"
|
||||
]
|
||||
uses: ./.github/workflows/_test.yml
|
||||
with:
|
||||
working-directory: ${{ matrix.working-directory }}
|
||||
secrets: inherit
|
||||
|
||||
integration-test:
|
||||
name: CLI integration test
|
||||
needs: [ build ]
|
||||
uses: ./.github/workflows/_integration_test.yml
|
||||
secrets: inherit
|
||||
|
||||
lint-js:
|
||||
runs-on: ubuntu-latest
|
||||
needs: [ build ]
|
||||
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
|
||||
|
||||
ci_success:
|
||||
name: "CI Success"
|
||||
needs: [build, lint, lint-js, test, integration-test]
|
||||
if: |
|
||||
always()
|
||||
runs-on: ubuntu-latest
|
||||
env:
|
||||
JOBS_JSON: ${{ toJSON(needs) }}
|
||||
RESULTS_JSON: ${{ toJSON(needs.*.result) }}
|
||||
EXIT_CODE: ${{!contains(needs.*.result, 'failure') && !contains(needs.*.result, 'cancelled') && '0' || '1'}}
|
||||
steps:
|
||||
- name: "CI Success"
|
||||
run: |
|
||||
echo $JOBS_JSON
|
||||
echo $RESULTS_JSON
|
||||
echo "Exiting with $EXIT_CODE"
|
||||
exit $EXIT_CODE
|
||||
|
||||
JOBS_JSON: ${{ toJSON(needs) }}
|
||||
RESULTS_JSON: ${{ toJSON(needs.*.result) }}
|
||||
EXIT_CODE: ${{!contains(needs.*.result, 'failure') && !contains(needs.*.result, 'cancelled') && '0' || '1'}}
|
||||
steps:
|
||||
- name: "CI Success"
|
||||
run: |
|
||||
echo $JOBS_JSON
|
||||
echo $RESULTS_JSON
|
||||
echo "Exiting with $EXIT_CODE"
|
||||
exit $EXIT_CODE
|
||||
|
||||
@@ -9,7 +9,11 @@
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
|
||||
defaults:
|
||||
run:
|
||||
working-directory: docs
|
||||
|
||||
jobs:
|
||||
codespell:
|
||||
name: (Check for spelling errors)
|
||||
@@ -21,18 +25,18 @@
|
||||
|
||||
- name: Install Dependencies
|
||||
run: |
|
||||
pip install toml codespell jupytext
|
||||
pip install toml codespell==2.3.0 jupytext
|
||||
|
||||
- name: Extract Ignore Words List
|
||||
run: |
|
||||
# Use a Python script to extract the ignore words list from pyproject.toml
|
||||
python .github/workflows/extract_ignored_words_list.py
|
||||
python ../.github/workflows/extract_ignored_words_list.py
|
||||
id: extract_ignore_words
|
||||
|
||||
- name: Codespell
|
||||
uses: codespell-project/actions-codespell@v2
|
||||
with:
|
||||
skip: '*.ambr,*.lock,*.ipynb'
|
||||
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
|
||||
|
||||
@@ -4,14 +4,13 @@ on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
- v0
|
||||
pull_request:
|
||||
branches:
|
||||
- main
|
||||
- v0
|
||||
workflow_dispatch:
|
||||
|
||||
env:
|
||||
POETRY_VERSION: "1.7.1"
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
pages: write
|
||||
@@ -21,48 +20,142 @@ concurrency:
|
||||
group: "pages"
|
||||
cancel-in-progress: false
|
||||
|
||||
defaults:
|
||||
run:
|
||||
working-directory: docs
|
||||
|
||||
jobs:
|
||||
deploy:
|
||||
get-changed-files:
|
||||
runs-on: ubuntu-latest
|
||||
outputs:
|
||||
changed-files: ${{ steps.changed-files.outputs.added_modified }}
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Get changed files
|
||||
id: changed-files
|
||||
uses: Ana06/get-changed-files@v2.3.0
|
||||
with:
|
||||
filter: "docs/docs/**"
|
||||
|
||||
# TODO: Uncomment this to run on PRs
|
||||
# run-changed-notebooks:
|
||||
# needs: get-changed-files
|
||||
# uses: ./.github/workflows/run_notebooks.yml
|
||||
# secrets: inherit
|
||||
# with:
|
||||
# changed-files: ${{ needs.get-changed-files.outputs.changed-files }}
|
||||
|
||||
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:
|
||||
GITHUB_TOKEN: ${{ secrets.MKDOCS_GITHUB_TOKEN }}
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
|
||||
- name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
|
||||
uses: "./.github/actions/poetry_setup"
|
||||
- name: Set up Python
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: "3.12"
|
||||
poetry-version: ${{ env.POETRY_VERSION }}
|
||||
cache-key: docs
|
||||
enable-cache: true
|
||||
cache-suffix: "docs"
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
poetry install --with docs
|
||||
yarn
|
||||
uv sync --all-groups
|
||||
# we run this installation only for internal PRs
|
||||
# as GITHUB_TOKEN is not available for PRs from outside contributors
|
||||
if [ -n "${GITHUB_TOKEN}" ]; then
|
||||
uv run pip install "git+https://${GITHUB_TOKEN}@github.com/langchain-ai/mkdocs-material-insiders.git"
|
||||
fi
|
||||
|
||||
- name: Run unit tests
|
||||
# Run unit tests on the docs build pipeline
|
||||
run: make tests
|
||||
- name: Lint Docs
|
||||
# This step lints the docs using the existing linting set up.
|
||||
# It should be very fast and should not require any external services.
|
||||
run: make lint-docs
|
||||
- name: Build llms-text
|
||||
run: make llms-text
|
||||
- name: Build site
|
||||
run: make build-docs
|
||||
run: |
|
||||
# If this is v0 branch, then we want to download stats. we do this
|
||||
# with the env variable DOWNLOAD_STATS=true
|
||||
if [ "${{ github.ref }}" == "refs/heads/v0" ]; then
|
||||
DOWNLOAD_STATS=true make build-docs
|
||||
else
|
||||
make build-docs
|
||||
fi
|
||||
env:
|
||||
MKDOCS_GIT_COMMITTERS_APIKEY: ${{ secrets.MKDOCS_GIT_COMMITTERS_APIKEY }}
|
||||
OPENAI_API_KEY: sf-proj-1234567890 # fake placeholder, shouldn't actually be used
|
||||
ANTHROPIC_API_KEY: sk-ant-api03-1234567890 # fake placeholder, shouldn't actually be used
|
||||
- name: Check links in notebooks
|
||||
env:
|
||||
LANGCHAIN_API_KEY: test
|
||||
if: github.event_name == 'schedule'
|
||||
run: |
|
||||
if [ "${{ github.event_name }}" == "schedule" ]; then
|
||||
echo "Running link check on all HTML files matching notebooks in docs directory..."
|
||||
uv run pytest -v \
|
||||
--check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
|
||||
--check-links-ignore "https://academy\.langchain\.com/.*" \
|
||||
--check-links-ignore "https://x.com/.*" \
|
||||
--check-links-ignore "https://twitter.com/.*" \
|
||||
--check-links-ignore "https://github\.com/.*" \
|
||||
--check-links-ignore "http://localhost:8123/.*" \
|
||||
--check-links-ignore "http://localhost:2024.*" \
|
||||
--check-links-ignore "http://127.0.0.1:.*" \
|
||||
--check-links-ignore "/.*\.(ipynb|html)$" \
|
||||
--check-links-ignore "https://python\.langchain\.com/.*" \
|
||||
--check-links-ignore "https://openai\.com/.*" \
|
||||
--check-links-ignore "https://www\.uber\.com/.*" \
|
||||
--check-links-ignore "https://pepy\.tech/.*" \
|
||||
--check-links-ignore "docs/docs/static/wordmark_*" \
|
||||
--check-links $(find site -name "index.html" | grep -v 'storm/index.html')
|
||||
|
||||
else
|
||||
echo "Fetching changes from origin/main..."
|
||||
git fetch origin main
|
||||
echo "Checking for changed notebook files..."
|
||||
CHANGED_FILES=$(git diff --name-only --diff-filter=d origin/main | grep 'docs/docs/.*\.ipynb$' | grep -v 'storm.ipynb' | sed -E 's|^docs/docs/|site/|; s/\.ipynb$/\/index.html/' || true)
|
||||
echo "Changed files: ${CHANGED_FILES}"
|
||||
if [ -n "${CHANGED_FILES}" ]; then
|
||||
echo "Running link check on HTML files matching changed notebook files..."
|
||||
uv run pytest -v \
|
||||
--check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
|
||||
--check-links-ignore "https://academy\.langchain\.com/.*" \
|
||||
--check-links-ignore "http://localhost:8123/.*" \
|
||||
--check-links-ignore "http://localhost:2024.*" \
|
||||
--check-links-ignore "http://127.0.0.1:.*" \
|
||||
--check-links-ignore "https://x.com/.*" \
|
||||
--check-links-ignore "https://twitter.com/.*" \
|
||||
--check-links-ignore "https://github\.com/.*" \
|
||||
--check-links-ignore "/.*\.(ipynb|html)$" \
|
||||
--check-links-ignore "docs/docs/static/wordmark_*" \
|
||||
--check-links ${CHANGED_FILES} \
|
||||
|| ([ $? = 5 ] && exit 0 || exit $?)
|
||||
else
|
||||
echo "No notebook files changed."
|
||||
fi
|
||||
fi
|
||||
|
||||
- name: Configure GitHub Pages
|
||||
if: github.ref == 'refs/heads/main'
|
||||
uses: actions/configure-pages@v4
|
||||
if: github.ref == 'refs/heads/v0'
|
||||
uses: actions/configure-pages@v5
|
||||
|
||||
- name: Upload Pages Artifact
|
||||
if: github.ref == 'refs/heads/main'
|
||||
# if: github.ref == 'refs/heads/main'
|
||||
uses: actions/upload-pages-artifact@v3
|
||||
with:
|
||||
path: ./docs/site/
|
||||
|
||||
- name: Deploy to GitHub Pages
|
||||
if: github.ref == 'refs/heads/main'
|
||||
if: github.ref == 'refs/heads/v0'
|
||||
id: deployment
|
||||
uses: actions/deploy-pages@v4
|
||||
|
||||
- name: Deploy Pull Request Preview
|
||||
if: github.event_name == 'pull_request'
|
||||
uses: actions/upload-artifact@v2
|
||||
with:
|
||||
name: pr-preview-${{ github.event.number }}
|
||||
path: ./docs/site/
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
import toml
|
||||
|
||||
pyproject_toml = toml.load("libs/langgraph/pyproject.toml")
|
||||
pyproject_toml = toml.load("pyproject.toml")
|
||||
|
||||
# Extract the ignore words list (adjust the key as per your TOML structure)
|
||||
ignore_words_list = (
|
||||
|
||||
@@ -11,9 +11,6 @@ on:
|
||||
- cron: "0 5 * * *"
|
||||
workflow_dispatch:
|
||||
|
||||
env:
|
||||
POETRY_VERSION: "1.7.1"
|
||||
|
||||
jobs:
|
||||
markdown-link-check:
|
||||
runs-on: ubuntu-latest
|
||||
@@ -26,49 +23,11 @@ jobs:
|
||||
- name: Check links in Markdown files
|
||||
uses: gaurav-nelson/github-action-markdown-link-check@v1
|
||||
with:
|
||||
folder-path: "examples/,docs/"
|
||||
folder-path: "docs/"
|
||||
check-modified-files-only: ${{ github.event_name != 'schedule' }}
|
||||
file-path: "./README.md"
|
||||
config-file: "./.markdown-link-check.config.json"
|
||||
|
||||
notebook-link-check:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v4
|
||||
- name: Set up Python 3.x + Poetry ${{ env.POETRY_VERSION }}
|
||||
uses: "./.github/actions/poetry_setup"
|
||||
with:
|
||||
python-version: "3.11"
|
||||
poetry-version: ${{ env.POETRY_VERSION }}
|
||||
cache-key: core
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
python -m pip install --upgrade pip
|
||||
poetry install --with docs
|
||||
poetry run pip install -U pytest pytest-check-links langsmith langchain GitPython
|
||||
|
||||
- name: Check links in notebooks
|
||||
env:
|
||||
LANGCHAIN_API_KEY: test
|
||||
run: |
|
||||
if [ "${{ github.event_name }}" == "schedule" ] || [ "${{ github.event_name }}" == "workflow_dispatch" ] || ([ "${{ github.event_name }}" == "push" ] && [ "${{ github.ref }}" == "refs/heads/main" ]); then
|
||||
echo "Running link check on all notebooks in examples directory..."
|
||||
poetry run pytest -v --check-links-ignore "https://(api|web)\.smith\.langchain\.com/.*" --check-links-ignore "https://x.com/.*" --check-links examples
|
||||
else
|
||||
echo "Fetching changes from origin/main..."
|
||||
git fetch origin main
|
||||
echo "Checking for changed notebook files..."
|
||||
CHANGED_FILES=$(git diff --name-only --diff-filter=d origin/main | grep '\.ipynb$' || true)
|
||||
echo "Changed files: ${CHANGED_FILES}"
|
||||
if [ -n "${CHANGED_FILES}" ]; then
|
||||
echo "Running link check on changed notebook files..."
|
||||
poetry run pytest -v --check-links-ignore "https://(api|web)\.smith\.langchain\.com/.*" --check-links-ignore "https://x.com/.*" --check-links ${CHANGED_FILES} || ([ $? = 5 ] && exit 0 || exit $?)
|
||||
else
|
||||
echo "No notebook files changed."
|
||||
fi
|
||||
fi
|
||||
check-readmes-synced:
|
||||
# This checks that the repo README.md is identical to the libs/langgraph/README.md
|
||||
runs-on: ubuntu-latest
|
||||
@@ -80,8 +39,8 @@ jobs:
|
||||
|
||||
- name: Check README.md is in sync
|
||||
run: |
|
||||
if ! diff -q README.md libs/langgraph/README.md >/dev/null; then
|
||||
echo "README.md is out of sync with libs/langgraph/README.md"
|
||||
diff -C 3 README.md libs/langgraph/README.md
|
||||
exit 1
|
||||
fi
|
||||
if ! diff -q README.md libs/langgraph/README.md >/dev/null; then
|
||||
echo "README.md is out of sync with libs/langgraph/README.md"
|
||||
diff -C 3 README.md libs/langgraph/README.md
|
||||
exit 1
|
||||
fi
|
||||
|
||||
@@ -10,11 +10,10 @@ on:
|
||||
|
||||
env:
|
||||
PYTHON_VERSION: "3.11"
|
||||
POETRY_VERSION: "1.7.1"
|
||||
|
||||
jobs:
|
||||
build:
|
||||
if: github.ref == 'refs/heads/main'
|
||||
if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/v0'
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
outputs:
|
||||
@@ -26,13 +25,12 @@ jobs:
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
|
||||
uses: "./.github/actions/poetry_setup"
|
||||
- name: Set up Python
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: ${{ env.PYTHON_VERSION }}
|
||||
poetry-version: ${{ env.POETRY_VERSION }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
cache-key: release
|
||||
enable-cache: true
|
||||
cache-suffix: "release"
|
||||
|
||||
# We want to keep this build stage *separate* from the release stage,
|
||||
# so that there's no sharing of permissions between them.
|
||||
@@ -46,7 +44,7 @@ jobs:
|
||||
# > from the publish job.
|
||||
# https://github.com/pypa/gh-action-pypi-publish#non-goals
|
||||
- name: Build project for distribution
|
||||
run: poetry build
|
||||
run: uv build
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
- name: Upload build
|
||||
@@ -60,8 +58,8 @@ jobs:
|
||||
shell: bash
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: |
|
||||
PKG_NAME="$(poetry version | cut -d ' ' -f 1)"
|
||||
VERSION="$(poetry version --short)"
|
||||
PKG_NAME=$(grep -m 1 "^name = " pyproject.toml | cut -d '"' -f 2)
|
||||
VERSION=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
|
||||
SHORT_PKG_NAME="$(echo "$PKG_NAME" | sed -e 's/langgraph//g' -e 's/-//g')"
|
||||
if [ -z $SHORT_PKG_NAME ]; then
|
||||
TAG="$VERSION"
|
||||
@@ -164,12 +162,11 @@ jobs:
|
||||
# - The package is published, and it breaks on the missing dependency when
|
||||
# used in the real world.
|
||||
|
||||
- name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
|
||||
uses: "./.github/actions/poetry_setup"
|
||||
- name: Set up Python
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: ${{ env.PYTHON_VERSION }}
|
||||
poetry-version: ${{ env.POETRY_VERSION }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
enable-cache: true
|
||||
|
||||
- name: Import published package
|
||||
shell: bash
|
||||
@@ -187,17 +184,21 @@ jobs:
|
||||
# - attempt install again after 5 seconds if it fails because there is
|
||||
# sometimes a delay in availability on test pypi
|
||||
run: |
|
||||
poetry run pip install \
|
||||
uv run pip install \
|
||||
--extra-index-url https://test.pypi.org/simple/ \
|
||||
"$PKG_NAME==$VERSION" || \
|
||||
( \
|
||||
sleep 5 && \
|
||||
poetry run pip install \
|
||||
uv run pip install \
|
||||
--extra-index-url https://test.pypi.org/simple/ \
|
||||
"$PKG_NAME==$VERSION" \
|
||||
)
|
||||
|
||||
if [[ "$PKG_NAME" == *checkpoint* ]]; then
|
||||
if [[ "$PKG_NAME" == *prebuilt* ]]; then
|
||||
uv run pip install langgraph
|
||||
fi
|
||||
|
||||
if [[ "$PKG_NAME" == *checkpoint* || "$PKG_NAME" == *prebuilt* ]]; then
|
||||
# since checkpoint packages are namespace packages, import them with . convention
|
||||
# i.e. import langgraph.checkpoint or langgraph.checkpoint.sqlite
|
||||
IMPORT_NAME="$(echo "$PKG_NAME" | sed s/-/./g)"
|
||||
@@ -207,10 +208,10 @@ jobs:
|
||||
IMPORT_NAME="$(echo "$PKG_NAME" | sed s/-/_/g)"
|
||||
fi
|
||||
|
||||
poetry run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
|
||||
uv run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
|
||||
|
||||
- name: Import test dependencies
|
||||
run: poetry install --with dev
|
||||
run: uv sync --group dev
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
# Overwrite the local version of the package with the test PyPI version.
|
||||
@@ -221,7 +222,7 @@ jobs:
|
||||
PKG_NAME: ${{ needs.build.outputs.pkg-name }}
|
||||
VERSION: ${{ needs.build.outputs.version }}
|
||||
run: |
|
||||
poetry run pip install \
|
||||
uv run pip install \
|
||||
--extra-index-url https://test.pypi.org/simple/ \
|
||||
"$PKG_NAME==$VERSION"
|
||||
|
||||
@@ -251,13 +252,12 @@ jobs:
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
|
||||
uses: "./.github/actions/poetry_setup"
|
||||
- name: Set up Python
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: ${{ env.PYTHON_VERSION }}
|
||||
poetry-version: ${{ env.POETRY_VERSION }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
cache-key: release
|
||||
enable-cache: true
|
||||
cache-suffix: "release"
|
||||
|
||||
- uses: actions/download-artifact@v4
|
||||
with:
|
||||
@@ -270,6 +270,8 @@ jobs:
|
||||
packages-dir: ${{ inputs.working-directory }}/dist/
|
||||
verbose: true
|
||||
print-hash: true
|
||||
# Temp workaround since attestations are on by default as of gh-action-pypi-publish v1.11.0
|
||||
attestations: false
|
||||
|
||||
mark-release:
|
||||
needs:
|
||||
@@ -291,13 +293,12 @@ jobs:
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
|
||||
uses: "./.github/actions/poetry_setup"
|
||||
- name: Set up Python
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: ${{ env.PYTHON_VERSION }}
|
||||
poetry-version: ${{ env.POETRY_VERSION }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
cache-key: release
|
||||
enable-cache: true
|
||||
cache-suffix: "release"
|
||||
|
||||
- uses: actions/download-artifact@v4
|
||||
with:
|
||||
|
||||
@@ -0,0 +1,82 @@
|
||||
name: Run notebooks
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
workflow_call:
|
||||
inputs:
|
||||
changed-files:
|
||||
required: false
|
||||
type: string
|
||||
description: "JSON string of changed files"
|
||||
schedule:
|
||||
- cron: "0 13 * * *"
|
||||
|
||||
defaults:
|
||||
run:
|
||||
working-directory: docs
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
matrix:
|
||||
lib-version:
|
||||
- "development"
|
||||
- "latest"
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up Python + Poetry
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
python-version: "3.11"
|
||||
enable-cache: true
|
||||
cache-suffix: "test-langgraph-notebooks"
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
uv sync --group test
|
||||
uv run pip install jupyter
|
||||
|
||||
- name: Start services
|
||||
run: make start-services
|
||||
|
||||
- name: Pre-download tiktoken files
|
||||
run: |
|
||||
uv run python _scripts/download_tiktoken.py
|
||||
|
||||
- name: Prepare notebooks
|
||||
run: |
|
||||
if [ "${{ matrix.lib-version }}" = "development" ]; then
|
||||
uv run python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
|
||||
else
|
||||
uv run python _scripts/prepare_notebooks_for_ci.py
|
||||
fi
|
||||
|
||||
- name: Run notebooks
|
||||
env:
|
||||
# these won't actually be used because of the VCR cassettes
|
||||
# but need to set them to avoid triggering getpass()
|
||||
OPENAI_API_KEY: "very-secret-key"
|
||||
ANTHROPIC_API_KEY: "very-secret-key"
|
||||
TAVILY_API_KEY: "very-secret-key"
|
||||
LANGSMITH_API_KEY: "very-secret-key"
|
||||
NOMIC_API_KEY: "very-secret-key"
|
||||
COHERE_API_KEY: "very-secret-key"
|
||||
FIREWORKS_API_KEY: "very-secret-key"
|
||||
run: |
|
||||
if [ "${{ github.event_name }}" = "workflow_dispatch" ] || [ "${{ github.event_name }}" = "schedule" ]; then
|
||||
echo "Running all notebooks"
|
||||
./_scripts/execute_notebooks.sh
|
||||
else
|
||||
CHANGED_FILES=$(echo '${{ inputs.changed-files }}' | tr ' ' '\n' | sed 's|^docs/docs/|docs/|' | grep '\.ipynb$' || true)
|
||||
if [ -n "$CHANGED_FILES" ]; then
|
||||
echo "Running changed notebooks: $CHANGED_FILES"
|
||||
./_scripts/execute_notebooks.sh $CHANGED_FILES
|
||||
else
|
||||
echo "No notebook files changed, skipping execution"
|
||||
fi
|
||||
fi
|
||||
|
||||
- name: Stop services
|
||||
run: make stop-services
|
||||
@@ -1,28 +0,0 @@
|
||||
name: Check File Size
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
pull_request:
|
||||
branches:
|
||||
- main
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
file-size-check:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Get changed files
|
||||
id: changed-files
|
||||
uses: tj-actions/changed-files@v44
|
||||
- name: Filter by size
|
||||
run: |
|
||||
large_added_files=$(find ${{ steps.changed-files.outputs.added_files }} -maxdepth 0 -size +1M)
|
||||
if [ -n "$large_added_files" ]; then
|
||||
echo "Large files added: $large_added_files"
|
||||
echo "# Large files added:" >> $GITHUB_STEP_SUMMARY
|
||||
echo "$large_added_files" >> $GITHUB_STEP_SUMMARY
|
||||
exit 1
|
||||
fi
|
||||
@@ -177,3 +177,7 @@ docs/docs_skeleton/yarn.lock
|
||||
Untitled*.ipynb
|
||||
|
||||
Chinook.db
|
||||
|
||||
.vercel
|
||||
.turbo
|
||||
.editorconfig
|
||||
|
||||
+3
-2
@@ -49,7 +49,7 @@ gain understanding of concepts and how they interact by showing one way to achie
|
||||
|
||||
They should **avoid** giving
|
||||
multiple permutations of ways to achieve that goal in-depth. Choice is burdensome. Instead, they should guide a new user through a recommended path to accomplishing a concrete goal. While the end result of a tutorial does not necessarily need to
|
||||
be completely production-ready, it should be useful and practically satisfy the the goal that you clearly stated in the tutorial's introduction.
|
||||
be completely production-ready, it should be useful and practically satisfy the goal that you clearly stated in the tutorial's introduction.
|
||||
|
||||
To quote the Diataxis website:
|
||||
|
||||
@@ -153,7 +153,7 @@ Each category serves a distinct purpose and requires a specific approach to writ
|
||||
|
||||
Here are some other guidelines you should think about when writing and organizing documentation.
|
||||
|
||||
We generally do not merge new tutorials from outside contributors without an actue need.
|
||||
We generally do not merge new tutorials from outside contributors without an actual need.
|
||||
We welcome updates as well as new integration docs, how-tos, and references.
|
||||
|
||||
### Avoid duplication
|
||||
@@ -227,6 +227,7 @@ see a preview of the documentation on the pull request page.
|
||||
|
||||
From the **monorepo root**, run the following command to install the dependencies:
|
||||
|
||||
<!-- TODO -->
|
||||
```bash
|
||||
poetry install --with docs --no-root
|
||||
```
|
||||
|
||||
@@ -1,28 +0,0 @@
|
||||
.PHONY: build-docs serve-docs serve-clean-docs clean-docs codespell build-typedoc
|
||||
|
||||
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/docs/cloud/reference/sdk/js_ts_sdk_ref.md > temp_file && mv temp_file docs/docs/cloud/reference/sdk/js_ts_sdk_ref.md
|
||||
|
||||
|
||||
|
||||
build-docs: build-typedoc
|
||||
poetry run python docs/_scripts/copy_notebooks.py
|
||||
poetry run python -m mkdocs build --clean -f docs/mkdocs.yml --strict
|
||||
|
||||
serve-clean-docs: clean-docs
|
||||
poetry run python docs/_scripts/copy_notebooks.py
|
||||
poetry run python -m mkdocs serve -c -f docs/mkdocs.yml --strict -w ./libs/langgraph
|
||||
|
||||
serve-docs: build-typedoc
|
||||
poetry run python docs/_scripts/copy_notebooks.py
|
||||
poetry run python -m mkdocs serve -f docs/mkdocs.yml -w ./libs/langgraph --dirty
|
||||
|
||||
clean-docs:
|
||||
find ./docs/docs -name "*.ipynb" -type f -delete
|
||||
rm -rf docs/site
|
||||
|
||||
codespell:
|
||||
./docs/codespell_notebooks.sh .
|
||||
@@ -1,231 +1,84 @@
|
||||
# 🦜🕸️LangGraph
|
||||
<picture class="github-only">
|
||||
<source media="(prefers-color-scheme: light)" srcset="https://langchain-ai.github.io/langgraph/static/wordmark_dark.svg">
|
||||
<source media="(prefers-color-scheme: dark)" srcset="https://langchain-ai.github.io/langgraph/static/wordmark_light.svg">
|
||||
<img alt="LangGraph Logo" src="https://langchain-ai.github.io/langgraph/static/wordmark_dark.svg" width="80%">
|
||||
</picture>
|
||||
|
||||

|
||||
<div>
|
||||
<br>
|
||||
</div>
|
||||
|
||||
[](https://pypi.org/project/langgraph/)
|
||||
[](https://pepy.tech/project/langgraph)
|
||||
[](https://github.com/langchain-ai/langgraph/issues)
|
||||
[](https://langchain-ai.github.io/langgraph/)
|
||||
[](https://gitmcp.io/langchain-ai/langgraph)
|
||||
|
||||
⚡ Building language agents as graphs ⚡
|
||||
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? Click [here](https://github.com/langchain-ai/langgraphjs) ([JS docs](https://langchain-ai.github.io/langgraphjs/)).
|
||||
## Get started
|
||||
|
||||
## Overview
|
||||
Install LangGraph:
|
||||
|
||||
[LangGraph](https://langchain-ai.github.io/langgraph/) is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application, crucial for creating reliable agents. Additionally, LangGraph includes built-in persistence, enabling advanced human-in-the-loop and memory features.
|
||||
|
||||
LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
|
||||
|
||||
### Key Features
|
||||
|
||||
- **Cycles and Branching**: Implement loops and conditionals in your apps.
|
||||
- **Persistence**: Automatically save state after each step in the graph. Pause and resume the graph execution at any point to support error recovery, human-in-the-loop workflows, time travel and more.
|
||||
- **Human-in-the-Loop**: Interrupt graph execution to approve or edit next action planned by the agent.
|
||||
- **Streaming Support**: Stream outputs as they are produced by each node (including token streaming).
|
||||
- **Integration with LangChain**: LangGraph integrates seamlessly with [LangChain](https://github.com/langchain-ai/langchain/) and [LangSmith](https://docs.smith.langchain.com/) (but does not require them).
|
||||
|
||||
|
||||
## Installation
|
||||
|
||||
```shell
|
||||
```
|
||||
pip install -U langgraph
|
||||
```
|
||||
|
||||
## Example
|
||||
|
||||
One of the central concepts of LangGraph is state. Each graph execution creates a state that is passed between nodes in the graph as they execute, and each node updates this internal state with its return value after it executes. The way that the graph updates its internal state is defined by either the type of graph chosen or a custom function.
|
||||
|
||||
Let's take a look at a simple example of an agent that can use a search tool.
|
||||
|
||||
```shell
|
||||
pip install langchain-anthropic
|
||||
```
|
||||
|
||||
```shell
|
||||
export ANTHROPIC_API_KEY=sk-...
|
||||
```
|
||||
|
||||
Optionally, we can set up [LangSmith](https://docs.smith.langchain.com/) for best-in-class observability.
|
||||
|
||||
```shell
|
||||
export LANGSMITH_TRACING=true
|
||||
export LANGSMITH_API_KEY=lsv2_sk_...
|
||||
```
|
||||
Then, create an agent [using prebuilt components](https://langchain-ai.github.io/langgraph/agents/agents/):
|
||||
|
||||
```python
|
||||
from typing import Annotated, Literal, TypedDict
|
||||
# pip install -qU "langchain[anthropic]" to call the model
|
||||
|
||||
from langchain_core.messages import HumanMessage
|
||||
from langchain_anthropic import ChatAnthropic
|
||||
from langchain_core.tools import tool
|
||||
from langgraph.checkpoint.memory import MemorySaver
|
||||
from langgraph.graph import END, START, StateGraph, MessagesState
|
||||
from langgraph.prebuilt import ToolNode
|
||||
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}!"
|
||||
|
||||
# Define the tools for the agent to use
|
||||
@tool
|
||||
def search(query: str):
|
||||
"""Call to surf the web."""
|
||||
# This is a placeholder, but don't tell the LLM that...
|
||||
if "sf" in query.lower() or "san francisco" in query.lower():
|
||||
return "It's 60 degrees and foggy."
|
||||
return "It's 90 degrees and sunny."
|
||||
|
||||
|
||||
tools = [search]
|
||||
|
||||
tool_node = ToolNode(tools)
|
||||
|
||||
model = ChatAnthropic(model="claude-3-5-sonnet-20240620", temperature=0).bind_tools(tools)
|
||||
|
||||
# Define the function that determines whether to continue or not
|
||||
def should_continue(state: MessagesState) -> Literal["tools", END]:
|
||||
messages = state['messages']
|
||||
last_message = messages[-1]
|
||||
# If the LLM makes a tool call, then we route to the "tools" node
|
||||
if last_message.tool_calls:
|
||||
return "tools"
|
||||
# Otherwise, we stop (reply to the user)
|
||||
return END
|
||||
|
||||
|
||||
# Define the function that calls the model
|
||||
def call_model(state: MessagesState):
|
||||
messages = state['messages']
|
||||
response = model.invoke(messages)
|
||||
# We return a list, because this will get added to the existing list
|
||||
return {"messages": [response]}
|
||||
|
||||
|
||||
# Define a new graph
|
||||
workflow = StateGraph(MessagesState)
|
||||
|
||||
# Define the two nodes we will cycle between
|
||||
workflow.add_node("agent", call_model)
|
||||
workflow.add_node("tools", tool_node)
|
||||
|
||||
# Set the entrypoint as `agent`
|
||||
# This means that this node is the first one called
|
||||
workflow.add_edge(START, "agent")
|
||||
|
||||
# We now add a conditional edge
|
||||
workflow.add_conditional_edges(
|
||||
# First, we define the start node. We use `agent`.
|
||||
# This means these are the edges taken after the `agent` node is called.
|
||||
"agent",
|
||||
# Next, we pass in the function that will determine which node is called next.
|
||||
should_continue,
|
||||
agent = create_react_agent(
|
||||
model="anthropic:claude-3-7-sonnet-latest",
|
||||
tools=[get_weather],
|
||||
prompt="You are a helpful assistant"
|
||||
)
|
||||
|
||||
# We now add a normal edge from `tools` to `agent`.
|
||||
# This means that after `tools` is called, `agent` node is called next.
|
||||
workflow.add_edge("tools", 'agent')
|
||||
|
||||
# Initialize memory to persist state between graph runs
|
||||
checkpointer = MemorySaver()
|
||||
|
||||
# Finally, we compile it!
|
||||
# This compiles it into a LangChain Runnable,
|
||||
# meaning you can use it as you would any other runnable.
|
||||
# Note that we're (optionally) passing the memory when compiling the graph
|
||||
app = workflow.compile(checkpointer=checkpointer)
|
||||
|
||||
# Use the Runnable
|
||||
final_state = app.invoke(
|
||||
{"messages": [HumanMessage(content="what is the weather in sf")]},
|
||||
config={"configurable": {"thread_id": 42}}
|
||||
# Run the agent
|
||||
agent.invoke(
|
||||
{"messages": [{"role": "user", "content": "what is the weather in sf"}]}
|
||||
)
|
||||
final_state["messages"][-1].content
|
||||
```
|
||||
|
||||
```
|
||||
"Based on the search results, I can tell you that the current weather in San Francisco is:\n\nTemperature: 60 degrees Fahrenheit\nConditions: Foggy\n\nSan Francisco is known for its microclimates and frequent fog, especially during the summer months. The temperature of 60°F (about 15.5°C) is quite typical for the city, which tends to have mild temperatures year-round. The fog, often referred to as "Karl the Fog" by locals, is a characteristic feature of San Francisco\'s weather, particularly in the mornings and evenings.\n\nIs there anything else you\'d like to know about the weather in San Francisco or any other location?"
|
||||
```
|
||||
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/).
|
||||
|
||||
Now when we pass the same `"thread_id"`, the conversation context is retained via the saved state (i.e. stored list of messages)
|
||||
## Core benefits
|
||||
|
||||
```python
|
||||
final_state = app.invoke(
|
||||
{"messages": [HumanMessage(content="what about ny")]},
|
||||
config={"configurable": {"thread_id": 42}}
|
||||
)
|
||||
final_state["messages"][-1].content
|
||||
```
|
||||
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:
|
||||
|
||||
```
|
||||
"Based on the search results, I can tell you that the current weather in New York City is:\n\nTemperature: 90 degrees Fahrenheit (approximately 32.2 degrees Celsius)\nConditions: Sunny\n\nThis weather is quite different from what we just saw in San Francisco. New York is experiencing much warmer temperatures right now. Here are a few points to note:\n\n1. The temperature of 90°F is quite hot, typical of summer weather in New York City.\n2. The sunny conditions suggest clear skies, which is great for outdoor activities but also means it might feel even hotter due to direct sunlight.\n3. This kind of weather in New York often comes with high humidity, which can make it feel even warmer than the actual temperature suggests.\n\nIt's interesting to see the stark contrast between San Francisco's mild, foggy weather and New York's hot, sunny conditions. This difference illustrates how varied weather can be across different parts of the United States, even on the same day.\n\nIs there anything else you'd like to know about the weather in New York or any other location?"
|
||||
```
|
||||
- [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.
|
||||
|
||||
### Step-by-step Breakdown
|
||||
## LangGraph’s ecosystem
|
||||
|
||||
1. <details>
|
||||
<summary>Initialize the model and tools.</summary>
|
||||
While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents. To improve your LLM application development, pair LangGraph with:
|
||||
|
||||
- we use `ChatAnthropic` as our LLM. **NOTE:** we need make sure the model knows that it has these tools available to call. We can do this by converting the LangChain tools into the format for OpenAI tool calling using the `.bind_tools()` method.
|
||||
- we define the tools we want to use - a search tool in our case. It is really easy to create your own tools - see documentation here on how to do that [here](https://python.langchain.com/docs/modules/agents/tools/custom_tools).
|
||||
</details>
|
||||
- [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.
|
||||
|
||||
2. <details>
|
||||
<summary>Initialize graph with state.</summary>
|
||||
> [!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/).
|
||||
|
||||
- we initialize graph (`StateGraph`) by passing state schema (in our case `MessagesState`)
|
||||
- `MessagesState` is a prebuilt state schema that has one attribute -- a list of LangChain `Message` objects, as well as logic for merging the updates from each node into the state
|
||||
</details>
|
||||
## Additional resources
|
||||
|
||||
3. <details>
|
||||
<summary>Define graph nodes.</summary>
|
||||
- [Guides](https://langchain-ai.github.io/langgraph/how-tos/): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
|
||||
- [Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
|
||||
- [Examples](https://langchain-ai.github.io/langgraph/tutorials/overview/): Guided examples on getting started with LangGraph.
|
||||
- [LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph): Learn the basics of LangGraph in our free, structured course.
|
||||
- [Templates](https://langchain-ai.github.io/langgraph/concepts/template_applications/): Pre-built reference apps for common agentic workflows (e.g. ReAct agent, memory, retrieval etc.) that can be cloned and adapted.
|
||||
- [Case studies](https://www.langchain.com/built-with-langgraph): Hear how industry leaders use LangGraph to ship AI applications at scale.
|
||||
|
||||
There are two main nodes we need:
|
||||
## Acknowledgements
|
||||
|
||||
- The `agent` node: responsible for deciding what (if any) actions to take.
|
||||
- The `tools` node that invokes tools: if the agent decides to take an action, this node will then execute that action.
|
||||
</details>
|
||||
|
||||
4. <details>
|
||||
<summary>Define entry point and graph edges.</summary>
|
||||
|
||||
First, we need to set the entry point for graph execution - `agent` node.
|
||||
|
||||
Then we define one normal and one conditional edge. Conditional edge means that the destination depends on the contents of the graph's state (`MessageState`). In our case, the destination is not known until the agent (LLM) decides.
|
||||
|
||||
- Conditional edge: after the agent is called, we should either:
|
||||
- a. Run tools if the agent said to take an action, OR
|
||||
- b. Finish (respond to the user) if the agent did not ask to run tools
|
||||
- Normal edge: after the tools are invoked, the graph should always return to the agent to decide what to do next
|
||||
</details>
|
||||
|
||||
5. <details>
|
||||
<summary>Compile the graph.</summary>
|
||||
|
||||
- When we compile the graph, we turn it into a LangChain [Runnable](https://python.langchain.com/v0.2/docs/concepts/#runnable-interface), which automatically enables calling `.invoke()`, `.stream()` and `.batch()` with your inputs
|
||||
- We can also optionally pass checkpointer object for persisting state between graph runs, and enabling memory, human-in-the-loop workflows, time travel and more. In our case we use `MemorySaver` - a simple in-memory checkpointer
|
||||
</details>
|
||||
|
||||
6. <details>
|
||||
<summary>Execute the graph.</summary>
|
||||
|
||||
1. LangGraph adds the input message to the internal state, then passes the state to the entrypoint node, `"agent"`.
|
||||
2. The `"agent"` node executes, invoking the chat model.
|
||||
3. The chat model returns an `AIMessage`. LangGraph adds this to the state.
|
||||
4. Graph cycles the following steps until there are no more `tool_calls` on `AIMessage`:
|
||||
|
||||
- If `AIMessage` has `tool_calls`, `"tools"` node executes
|
||||
- The `"agent"` node executes again and returns `AIMessage`
|
||||
|
||||
5. Execution progresses to the special `END` value and outputs the final state.
|
||||
And as a result, we get a list of all our chat messages as output.
|
||||
</details>
|
||||
|
||||
|
||||
## Documentation
|
||||
|
||||
* [Tutorials](https://langchain-ai.github.io/langgraph/tutorials/): Learn to build with LangGraph through guided examples.
|
||||
* [How-to Guides](https://langchain-ai.github.io/langgraph/how-tos/): Accomplish specific things within LangGraph, from streaming, to adding memory & persistence, to common design patterns (branching, subgraphs, etc.), these are the place to go if you want to copy and run a specific code snippet.
|
||||
* [Conceptual Guides](https://langchain-ai.github.io/langgraph/concepts/): In-depth explanations of the key concepts and principles behind LangGraph, such as nodes, edges, state and more.
|
||||
* [API Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Review important classes and methods, simple examples of how to use the graph and checkpointing APIs, higher-level prebuilt components and more.
|
||||
* [Cloud (beta)](https://langchain-ai.github.io/langgraph/cloud/): With one click, deploy LangGraph applications to LangGraph Cloud.
|
||||
|
||||
## Contributing
|
||||
|
||||
For more information on how to contribute, see [here](https://github.com/langchain-ai/langgraph/blob/main/CONTRIBUTING.md).
|
||||
LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
|
||||
|
||||
+2
-2
@@ -1,4 +1,4 @@
|
||||
*.ipynb
|
||||
site/
|
||||
docs/tutorials/**/*.png
|
||||
docs/cloud/reference/sdk/js_ts_sdk_ref.md
|
||||
|
||||
.vercel
|
||||
|
||||
@@ -0,0 +1,72 @@
|
||||
.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.
|
||||
# Looks up download stats for each of the prebuilt packages and
|
||||
# generates the final prebuilt page.
|
||||
@if [ "$(DOWNLOAD_STATS)" = "true" ]; then \
|
||||
set -x; \
|
||||
uv run python -m _scripts.third_party_page.get_download_stats stats.yml; \
|
||||
set +x; \
|
||||
else \
|
||||
set -x; \
|
||||
uv run python -m _scripts.third_party_page.get_download_stats --fake stats.yml; \
|
||||
set +x; \
|
||||
fi
|
||||
uv run python -m _scripts.third_party_page.create_third_party_page stats.yml docs/agents/prebuilt.md --language python
|
||||
|
||||
build-docs: build-typedoc build-prebuilt
|
||||
uv run python -m mkdocs build --clean -f mkdocs.yml --strict
|
||||
|
||||
llms-text:
|
||||
uv run python -m _scripts.generate_llms_text docs/llms-full.txt
|
||||
|
||||
install-vercel-deps:
|
||||
curl -sL "https://astral.sh/uv/install.sh" | bash -s
|
||||
export PATH="${HOME}/.cargo/bin:${PATH}"
|
||||
uv venv --python 3.11
|
||||
uv sync --all-groups
|
||||
|
||||
tests:
|
||||
# Run unit tests
|
||||
uv run pytest tests/unit_tests
|
||||
|
||||
|
||||
vercel-build-docs: install-vercel-deps
|
||||
make build-docs
|
||||
|
||||
|
||||
serve-clean-docs: clean-docs
|
||||
uv run python -m mkdocs serve -c -f mkdocs.yml --strict -w ../libs/langgraph
|
||||
|
||||
serve-docs: build-typedoc
|
||||
uv run python -m mkdocs serve -f mkdocs.yml -w ../libs/langgraph -w ../libs/checkpoint -w ../libs/sdk-py --dirty
|
||||
|
||||
clean-docs:
|
||||
find ./docs -name "*.ipynb" -type f -delete
|
||||
rm -rf site
|
||||
|
||||
## Run format against the project documentation.
|
||||
format-docs:
|
||||
uv run ruff format docs
|
||||
uv run ruff check --fix docs
|
||||
|
||||
# Check the docs for linting violations
|
||||
lint-docs:
|
||||
uv run ruff format --check docs
|
||||
uv run ruff check docs
|
||||
|
||||
codespell:
|
||||
./codespell_notebooks.sh .
|
||||
|
||||
start-services:
|
||||
docker compose -f test-compose.yml up -V --force-recreate --wait --remove-orphans
|
||||
|
||||
stop-services:
|
||||
docker compose -f test-compose.yml down
|
||||
@@ -0,0 +1,61 @@
|
||||
# Setup
|
||||
|
||||
To setup requirements for building docs you can run:
|
||||
|
||||
```bash
|
||||
uv sync --group test
|
||||
```
|
||||
|
||||
## Serving documentation locally
|
||||
|
||||
To run the documentation server locally you can run:
|
||||
|
||||
```bash
|
||||
make serve-docs
|
||||
```
|
||||
|
||||
This will start the documentation server on [http://127.0.0.1:8000/langgraph/](http://127.0.0.1:8000/langgraph/).
|
||||
|
||||
## Execute notebooks
|
||||
|
||||
If you would like to automatically execute all of the notebooks, to mimic the "Run notebooks" GHA, you can run:
|
||||
|
||||
```bash
|
||||
python _scripts/prepare_notebooks_for_ci.py
|
||||
./_scripts/execute_notebooks.sh
|
||||
```
|
||||
|
||||
**Note**: if you want to run the notebooks without `%pip install` cells, you can run:
|
||||
|
||||
```bash
|
||||
python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
|
||||
./_scripts/execute_notebooks.sh
|
||||
```
|
||||
|
||||
`prepare_notebooks_for_ci.py` script will add VCR cassette context manager for each cell in the notebook, so that:
|
||||
* when the notebook is run for the first time, cells with network requests will be recorded to a VCR cassette file
|
||||
* when the notebook is run subsequently, the cells with network requests will be replayed from the cassettes
|
||||
|
||||
## Adding new notebooks
|
||||
|
||||
If you are adding a notebook with API requests, it's **recommended** to record network requests so that they can be subsequently replayed. If this is not done, the notebook runner will make API requests every time the notebook is run, which can be costly and slow.
|
||||
|
||||
To record network requests, please make sure to first run `prepare_notebooks_for_ci.py` script.
|
||||
|
||||
Then, run
|
||||
|
||||
```bash
|
||||
jupyter execute <path_to_notebook>
|
||||
```
|
||||
|
||||
Once the notebook is executed, you should see the new VCR cassettes recorded in `cassettes` directory and discard the updated notebook.
|
||||
|
||||
## Updating existing notebooks
|
||||
|
||||
If you are updating an existing notebook, please make sure to remove any existing cassettes for the notebook in `cassettes` directory (each cassette is prefixed with the notebook name), and then run the steps from the "Adding new notebooks" section above.
|
||||
|
||||
To delete cassettes for a notebook, you can run:
|
||||
|
||||
```bash
|
||||
rm cassettes/<notebook_name>*
|
||||
```
|
||||
@@ -0,0 +1,93 @@
|
||||
import functools
|
||||
|
||||
from urllib3 import __version__ as urllib3version # type: ignore[import-untyped]
|
||||
from urllib3 import connection # type: ignore[import-untyped]
|
||||
|
||||
|
||||
def _ensure_str(s, encoding="utf-8", errors="strict") -> str:
|
||||
if isinstance(s, str):
|
||||
return s
|
||||
|
||||
if isinstance(s, bytes):
|
||||
return s.decode(encoding, errors)
|
||||
return str(s)
|
||||
|
||||
|
||||
# Copied from https://github.com/urllib3/urllib3/blob/1c994dfc8c5d5ecaee8ed3eb585d4785f5febf6e/src/urllib3/connection.py#L231
|
||||
def request(self, method, url, body=None, headers=None):
|
||||
"""Make the request.
|
||||
|
||||
This function is based on the urllib3 request method, with modifications
|
||||
to handle potential issues when using vcrpy in concurrent workloads.
|
||||
|
||||
Args:
|
||||
self: The HTTPConnection instance.
|
||||
method (str): The HTTP method (e.g., 'GET', 'POST').
|
||||
url (str): The URL for the request.
|
||||
body (Optional[Any]): The body of the request.
|
||||
headers (Optional[dict]): Headers to send with the request.
|
||||
|
||||
Returns:
|
||||
The result of calling the parent request method.
|
||||
"""
|
||||
# Update the inner socket's timeout value to send the request.
|
||||
# This only triggers if the connection is reused.
|
||||
if getattr(self, "sock", None) is not None:
|
||||
self.sock.settimeout(self.timeout)
|
||||
|
||||
if headers is None:
|
||||
headers = {}
|
||||
else:
|
||||
# Avoid modifying the headers passed into .request()
|
||||
headers = headers.copy()
|
||||
if "user-agent" not in (_ensure_str(k.lower()) for k in headers):
|
||||
headers["User-Agent"] = connection._get_default_user_agent()
|
||||
# The above is all the same ^^^
|
||||
# The following is different:
|
||||
return self._parent_request(method, url, body=body, headers=headers)
|
||||
|
||||
|
||||
_PATCHED = False
|
||||
|
||||
|
||||
def patch_urllib3():
|
||||
"""Patch the request method of urllib3 to avoid type errors when using vcrpy.
|
||||
|
||||
In concurrent workloads (such as the tracing background queue), the
|
||||
connection pool can get in a state where an HTTPConnection is created
|
||||
before vcrpy patches the HTTPConnection class. In urllib3 >= 2.0 this isn't
|
||||
a problem since they use the proper super().request(...) syntax, but in older
|
||||
versions, super(HTTPConnection, self).request is used, resulting in a TypeError
|
||||
since self is no longer a subclass of "HTTPConnection" (which at this point
|
||||
is vcr.stubs.VCRConnection).
|
||||
|
||||
This method patches the class to fix the super() syntax to avoid mixed inheritance.
|
||||
In the case of the LangSmith tracing logic, it doesn't really matter since we always
|
||||
exclude cache checks for calls to LangSmith.
|
||||
|
||||
The patch is only applied for urllib3 versions older than 2.0.
|
||||
"""
|
||||
global _PATCHED
|
||||
if _PATCHED:
|
||||
return
|
||||
from packaging import version
|
||||
|
||||
if version.parse(urllib3version) >= version.parse("2.0"):
|
||||
_PATCHED = True
|
||||
return
|
||||
|
||||
# Lookup the parent class and its request method
|
||||
parent_class = connection.HTTPConnection.__bases__[0]
|
||||
parent_request = parent_class.request
|
||||
|
||||
def new_request(self, *args, **kwargs):
|
||||
"""Handle parent request.
|
||||
|
||||
This method binds the parent's request method to self and then
|
||||
calls our modified request function.
|
||||
"""
|
||||
self._parent_request = functools.partial(parent_request, self)
|
||||
return request(self, *args, **kwargs)
|
||||
|
||||
connection.HTTPConnection.request = new_request
|
||||
_PATCHED = True
|
||||
@@ -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)
|
||||
@@ -1,223 +0,0 @@
|
||||
import json
|
||||
import os
|
||||
import re
|
||||
import shutil
|
||||
from pathlib import Path
|
||||
|
||||
root_dir = Path(__file__).resolve().parents[2]
|
||||
|
||||
examples_dir = root_dir / "examples"
|
||||
docs_dir = root_dir / "docs/docs"
|
||||
how_tos_dir = docs_dir / "how-tos"
|
||||
tutorials_dir = docs_dir / "tutorials"
|
||||
cloud_how_tos_dir = docs_dir / "cloud/how-tos"
|
||||
cloud_sdk_dir = docs_dir / "cloud"
|
||||
|
||||
_MANUAL = {
|
||||
"how-tos": [
|
||||
"state-context-key.ipynb",
|
||||
"async.ipynb",
|
||||
"stream-values.ipynb",
|
||||
"stream-updates.ipynb",
|
||||
"stream-multiple.ipynb",
|
||||
"streaming-tokens.ipynb",
|
||||
"streaming-tokens-without-langchain.ipynb",
|
||||
"streaming-content.ipynb",
|
||||
"streaming-events-from-within-tools.ipynb",
|
||||
"streaming-events-from-within-tools-without-langchain.ipynb",
|
||||
"streaming-from-final-node.ipynb",
|
||||
"persistence.ipynb",
|
||||
"input_output_schema.ipynb",
|
||||
"pass_private_state.ipynb",
|
||||
"memory/manage-conversation-history.ipynb",
|
||||
"memory/delete-messages.ipynb",
|
||||
"memory/add-summary-conversation-history.ipynb",
|
||||
"persistence_postgres.ipynb",
|
||||
"persistence_mongodb.ipynb",
|
||||
"persistence_redis.ipynb",
|
||||
"visualization.ipynb",
|
||||
"state-model.ipynb",
|
||||
"subgraph.ipynb",
|
||||
"force-calling-a-tool-first.ipynb",
|
||||
"pass-run-time-values-to-tools.ipynb",
|
||||
"tool-calling.ipynb",
|
||||
"tool-calling-errors.ipynb",
|
||||
"pass-config-to-tools.ipynb",
|
||||
"many-tools.ipynb",
|
||||
"dynamic-returning-direct.ipynb",
|
||||
"managing-agent-steps.ipynb",
|
||||
"respond-in-format.ipynb",
|
||||
"branching.ipynb",
|
||||
"dynamically-returning-directly.ipynb",
|
||||
"configuration.ipynb",
|
||||
"map-reduce.ipynb",
|
||||
"create-react-agent.ipynb",
|
||||
"create-react-agent-system-prompt.ipynb",
|
||||
"create-react-agent-memory.ipynb",
|
||||
"create-react-agent-hitl.ipynb",
|
||||
"human_in_the_loop/breakpoints.ipynb",
|
||||
"human_in_the_loop/dynamic_breakpoints.ipynb",
|
||||
"human_in_the_loop/time-travel.ipynb",
|
||||
"human_in_the_loop/edit-graph-state.ipynb",
|
||||
"human_in_the_loop/wait-user-input.ipynb",
|
||||
"human_in_the_loop/review-tool-calls.ipynb",
|
||||
"node-retries.ipynb",
|
||||
],
|
||||
"tutorials": [
|
||||
"introduction.ipynb",
|
||||
"customer-support/customer-support.ipynb",
|
||||
"tutorials/tnt-llm/tnt-llm.ipynb",
|
||||
"tutorials/sql-agent.ipynb",
|
||||
],
|
||||
}
|
||||
_MANUAL_INVERSE = {v: docs_dir / k for k, vs in _MANUAL.items() for v in vs}
|
||||
_HOW_TOS = {"agent_executor", "chat_agent_executor_with_function_calling", "docs"}
|
||||
_HIDE = set(
|
||||
str(examples_dir / f)
|
||||
for f in [
|
||||
"agent_executor/base.ipynb",
|
||||
"agent_executor/force-calling-a-tool-first.ipynb",
|
||||
"agent_executor/high-level.ipynb",
|
||||
"agent_executor/human-in-the-loop.ipynb",
|
||||
"agent_executor/managing-agent-steps.ipynb",
|
||||
"chat_agent_executor_with_function_calling/anthropic.ipynb",
|
||||
"chat_agent_executor_with_function_calling/base.ipynb",
|
||||
"chat_agent_executor_with_function_calling/dynamically-returning-directly.ipynb",
|
||||
"chat_agent_executor_with_function_calling/force-calling-a-tool-first.ipynb",
|
||||
"chat_agent_executor_with_function_calling/high-level-tools.ipynb",
|
||||
"chat_agent_executor_with_function_calling/high-level.ipynb",
|
||||
"chat_agent_executor_with_function_calling/human-in-the-loop.ipynb",
|
||||
"chat_agent_executor_with_function_calling/managing-agent-steps.ipynb",
|
||||
"chat_agent_executor_with_function_calling/prebuilt-tool-node.ipynb",
|
||||
"chat_agent_executor_with_function_calling/respond-in-format.ipynb",
|
||||
"chatbots/customer-support.ipynb",
|
||||
"rag/langgraph_rag_agent_llama3_local.ipynb",
|
||||
"rag/langgraph_self_rag_pinecone_movies.ipynb",
|
||||
"rag/langgraph_adaptive_rag_cohere.ipynb",
|
||||
"dynamically-returning-directly.ipynb",
|
||||
"force-calling-a-tool-first.ipynb",
|
||||
"managing-agent-steps.ipynb",
|
||||
"respond-in-format.ipynb",
|
||||
"quickstart.ipynb",
|
||||
"human-in-the-loop.ipynb",
|
||||
"learning.ipynb",
|
||||
"docs/quickstart.ipynb",
|
||||
"tutorials/rag-agent-testing.ipynb",
|
||||
"tutorials/rag-agent-testing-local.ipynb",
|
||||
"tutorials/tool-calling-agent-local.ipynb",
|
||||
"time-travel.ipynb",
|
||||
"code_assistant/langgraph_code_assistant_mistral.ipynb",
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
def clean_notebooks():
|
||||
roots = (how_tos_dir, tutorials_dir)
|
||||
for dir_ in roots:
|
||||
traversed = []
|
||||
for root, dirs, files in os.walk(dir_):
|
||||
for file in files:
|
||||
if file.endswith(".ipynb"):
|
||||
os.remove(os.path.join(root, file))
|
||||
# Now delete the dir if it is empty now
|
||||
if root not in roots:
|
||||
traversed.append(root)
|
||||
|
||||
for root in reversed(traversed):
|
||||
if not os.listdir(root):
|
||||
os.rmdir(root)
|
||||
|
||||
|
||||
def update_notebook_links(notebook_path):
|
||||
with open(notebook_path, "r", encoding="utf-8") as f:
|
||||
notebook = json.load(f)
|
||||
|
||||
for cell in notebook["cells"]:
|
||||
if cell["cell_type"] == "markdown":
|
||||
for i, source in enumerate(cell["source"]):
|
||||
# Update relative notebook links
|
||||
cell["source"][i] = re.sub(
|
||||
r"\[([^\]]+)\]\(([^:)]+\.ipynb)\)",
|
||||
lambda m: transform_link(m.group(1), m.group(2)),
|
||||
source,
|
||||
)
|
||||
|
||||
with open(notebook_path, "w", encoding="utf-8") as f:
|
||||
json.dump(notebook, f, indent=2)
|
||||
|
||||
|
||||
def transform_link(text, link):
|
||||
dir_path, filename = os.path.split(link)
|
||||
|
||||
# Remove the .ipynb extension
|
||||
filename_without_ext = os.path.splitext(filename)[0]
|
||||
|
||||
# If it's a local link (starts with ./)
|
||||
if link.startswith("./"):
|
||||
# Change to parent directory and remove ./ prefix
|
||||
new_link = f"../{filename_without_ext}/"
|
||||
elif dir_path:
|
||||
# If there's a directory path, keep it and add one more level up
|
||||
new_link = f"../{dir_path}/{filename_without_ext}/"
|
||||
else:
|
||||
# If it's just a filename, simply go one level up
|
||||
new_link = f"../{filename_without_ext}/"
|
||||
|
||||
return f"[{text}]({new_link})"
|
||||
|
||||
|
||||
def copy_notebooks():
|
||||
# Nested ones are mostly tutorials rn
|
||||
for root, dirs, files in os.walk(examples_dir):
|
||||
if any(
|
||||
path.startswith(".") or path.startswith("__") for path in root.split(os.sep)
|
||||
):
|
||||
continue
|
||||
if any(path in _HOW_TOS for path in root.split(os.sep)):
|
||||
dst_dir = how_tos_dir
|
||||
elif "sdk" in root.split(os.sep):
|
||||
dst_dir = cloud_sdk_dir
|
||||
elif "cloud_examples" in root.split(os.sep):
|
||||
dst_dir = cloud_how_tos_dir
|
||||
else:
|
||||
dst_dir = tutorials_dir
|
||||
for file in files:
|
||||
dst_dir_ = dst_dir
|
||||
if file.endswith((".ipynb", ".png")):
|
||||
src_path = os.path.join(root, file)
|
||||
if src_path in _HIDE:
|
||||
print("Hiding:", src_path)
|
||||
continue
|
||||
dst_path = os.path.join(
|
||||
dst_dir, os.path.relpath(src_path, examples_dir)
|
||||
)
|
||||
for k in _MANUAL_INVERSE:
|
||||
if src_path.endswith(k):
|
||||
overridden_dir = _MANUAL_INVERSE[k]
|
||||
dst_path = os.path.join(
|
||||
overridden_dir, os.path.relpath(src_path, examples_dir)
|
||||
)
|
||||
print(f"Overriding: {src_path} to {dst_path}")
|
||||
break
|
||||
# Avoid double nesting.
|
||||
dst_path = dst_path.replace("tutorials/tutorials", "tutorials").replace(
|
||||
"how-tos/how-tos", "how-tos"
|
||||
)
|
||||
os.makedirs(os.path.dirname(dst_path), exist_ok=True)
|
||||
print(f"Copying: {src_path} to {dst_path}")
|
||||
shutil.copy(src_path, dst_path)
|
||||
# Convert all ./img/* to ../img/*
|
||||
if file.endswith(".ipynb"):
|
||||
with open(dst_path, "r") as f:
|
||||
content = f.read()
|
||||
content = content.replace("(./img/", "(../img/")
|
||||
content = content.replace('src=\\"./img/', 'src=\\"../img/')
|
||||
with open(dst_path, "w") as f:
|
||||
f.write(content)
|
||||
update_notebook_links(dst_path)
|
||||
dst_dir = dst_dir_
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
clean_notebooks()
|
||||
copy_notebooks()
|
||||
@@ -0,0 +1,5 @@
|
||||
import tiktoken
|
||||
|
||||
# This will trigger the download and caching of the necessary files
|
||||
for encoding in ("gpt2", "gpt-3.5"):
|
||||
tiktoken.encoding_for_model(encoding)
|
||||
Executable
+36
@@ -0,0 +1,36 @@
|
||||
#!/bin/bash
|
||||
|
||||
# Read the list of notebooks to skip from the JSON file
|
||||
SKIP_NOTEBOOKS=$(python -c "import json; print('\n'.join(json.load(open('notebooks_no_execution.json'))))")
|
||||
|
||||
# Function to execute a single notebook
|
||||
execute_notebook() {
|
||||
file="$1"
|
||||
echo "Starting execution of $file"
|
||||
start_time=$(date +%s)
|
||||
if ! output=$(time uv run jupyter execute "$file" 2>&1); then
|
||||
end_time=$(date +%s)
|
||||
execution_time=$((end_time - start_time))
|
||||
echo "Error in $file. Execution time: $execution_time seconds"
|
||||
echo "Error details: $output"
|
||||
exit 1
|
||||
fi
|
||||
end_time=$(date +%s)
|
||||
execution_time=$((end_time - start_time))
|
||||
echo "Finished $file. Execution time: $execution_time seconds"
|
||||
}
|
||||
|
||||
export -f execute_notebook
|
||||
|
||||
# Check if custom notebook paths are provided
|
||||
if [ $# -gt 0 ]; then
|
||||
notebooks=$(echo "$@" | tr ' ' '\n' | grep -vFf <(echo "$SKIP_NOTEBOOKS"))
|
||||
else
|
||||
# Find all notebooks and filter out those in the skip list
|
||||
notebooks=$(find docs/tutorials docs/how-tos -name "*.ipynb" | grep -v ".ipynb_checkpoints" | grep -vFf <(echo "$SKIP_NOTEBOOKS"))
|
||||
fi
|
||||
|
||||
# Execute notebooks sequentially
|
||||
for file in $notebooks; do
|
||||
execute_notebook "$file"
|
||||
done
|
||||
@@ -0,0 +1,284 @@
|
||||
import ast
|
||||
import importlib
|
||||
import logging
|
||||
import re
|
||||
from functools import lru_cache
|
||||
from typing import List, Optional
|
||||
|
||||
from typing_extensions import TypedDict
|
||||
|
||||
logging.basicConfig(level=logging.INFO)
|
||||
logger = logging.getLogger(__name__)
|
||||
# Base URL for all class documentation
|
||||
_LANGCHAIN_API_REFERENCE = "https://python.langchain.com/api_reference/"
|
||||
_LANGGRAPH_API_REFERENCE = "https://langchain-ai.github.io/langgraph/reference/"
|
||||
|
||||
|
||||
# (alias/re-exported modules, source module, class, docs namespace)
|
||||
MANUAL_API_REFERENCES_LANGGRAPH = [
|
||||
(
|
||||
["langgraph.prebuilt"],
|
||||
"langgraph.prebuilt.chat_agent_executor",
|
||||
"create_react_agent",
|
||||
"prebuilt",
|
||||
),
|
||||
(
|
||||
[],
|
||||
"langgraph.prebuilt.chat_agent_executor",
|
||||
"AgentState",
|
||||
"prebuilt",
|
||||
),
|
||||
(["langgraph.prebuilt"], "langgraph.prebuilt.tool_node", "ToolNode", "prebuilt"),
|
||||
(
|
||||
["langgraph.prebuilt"],
|
||||
"langgraph.prebuilt.tool_node",
|
||||
"tools_condition",
|
||||
"prebuilt",
|
||||
),
|
||||
(
|
||||
["langgraph.prebuilt"],
|
||||
"langgraph.prebuilt.tool_node",
|
||||
"InjectedState",
|
||||
"prebuilt",
|
||||
),
|
||||
# Graph
|
||||
(["langgraph.graph"], "langgraph.graph.message", "add_messages", "graphs"),
|
||||
(["langgraph.graph"], "langgraph.graph.state", "StateGraph", "graphs"),
|
||||
(["langgraph.graph"], "langgraph.graph.state", "CompiledStateGraph", "graphs"),
|
||||
(["langgraph.graph"], "langgraph.constants", "START", "constants"),
|
||||
(["langgraph.graph"], "langgraph.constants", "END", "constants"),
|
||||
(["langgraph.constants"], "langgraph.types", "Send", "types"),
|
||||
(["langgraph.constants"], "langgraph.types", "Interrupt", "types"),
|
||||
(["langgraph.constants"], "langgraph.types", "interrupt", "types"),
|
||||
(["langgraph.constants"], "langgraph.types", "Command", "types"),
|
||||
(["langgraph.config"], "langgraph.config", "get_stream_writer", "config"),
|
||||
(["langgraph.config"], "langgraph.config", "get_store", "config"),
|
||||
(["langgraph.func"], "langgraph.func", "entrypoint", "func"),
|
||||
(["langgraph.func"], "langgraph.func", "task", "func"),
|
||||
(["langgraph.types"], "langgraph.types", "RetryPolicy", "types"),
|
||||
(["langgraph.types"], "langgraph.types", "StreamMode", "types"),
|
||||
(["langgraph.types"], "langgraph.types", "StreamWriter", "types"),
|
||||
([], "langgraph.checkpoint.base", "Checkpoint", "checkpoints"),
|
||||
([], "langgraph.checkpoint.base", "CheckpointMetadata", "checkpoints"),
|
||||
([], "langgraph.checkpoint.base", "BaseCheckpointSaver", "checkpoints"),
|
||||
([], "langgraph.checkpoint.base", "SerializerProtocol", "checkpoints"),
|
||||
([], "langgraph.checkpoint.serde.jsonplus", "JsonPlusSerializer", "checkpoints"),
|
||||
([], "langgraph.checkpoint.memory", "MemorySaver", "checkpoints"),
|
||||
([], "langgraph.checkpoint.memory", "InMemorySaver", "checkpoints"),
|
||||
([], "langgraph.checkpoint.sqlite.aio", "AsyncSqliteSaver", "checkpoints"),
|
||||
([], "langgraph.checkpoint.sqlite", "SqliteSaver", "checkpoints"),
|
||||
([], "langgraph.checkpoint.postgres.aio", "AsyncPostgresSaver", "checkpoints"),
|
||||
([], "langgraph.checkpoint.postgres", "PostgresSaver", "checkpoints"),
|
||||
# other prebuilts
|
||||
(["langgraph_supervisor"], "langgraph_supervisor.supervisor", "create_supervisor", "supervisor"),
|
||||
(["langgraph_supervisor"], "langgraph_supervisor.handoff", "create_handoff_tool", "supervisor"),
|
||||
([], "langgraph_supervisor.handoff", "create_forward_message_tool", "supervisor"),
|
||||
(["langgraph_swarm"], "langgraph_swarm.swarm", "create_swarm", "swarm"),
|
||||
(["langgraph_swarm"], "langgraph_swarm.swarm", "add_active_agent_router", "swarm"),
|
||||
(["langgraph_swarm"], "langgraph_swarm.swarm", "SwarmState", "swarm"),
|
||||
(["langgraph_swarm"], "langgraph_swarm.handoff", "create_handoff_tool", "swarm"),
|
||||
([], "langchain_mcp_adapters.client", "MultiServerMCPClient", "mcp"),
|
||||
([], "langchain_mcp_adapters.tools", "load_mcp_tools", "mcp"),
|
||||
([], "langchain_mcp_adapters.prompts", "load_mcp_prompt", "mcp"),
|
||||
([], "langchain_mcp_adapters.resources", "load_mcp_resources", "mcp"),
|
||||
]
|
||||
|
||||
WELL_KNOWN_LANGGRAPH_OBJECTS = {
|
||||
(module_, class_): (source_module, namespace)
|
||||
for (modules, source_module, class_, namespace) in MANUAL_API_REFERENCES_LANGGRAPH
|
||||
for module_ in modules + [source_module]
|
||||
}
|
||||
|
||||
|
||||
@lru_cache(maxsize=10_000)
|
||||
def _get_full_module_name(module_path: str, class_name: str) -> Optional[str]:
|
||||
"""Get full module name using inspect, with LRU cache to memoize results."""
|
||||
try:
|
||||
module = importlib.import_module(module_path)
|
||||
symbol = getattr(module, class_name)
|
||||
# First check the __module__ attribute on the symbol.
|
||||
mod_name = getattr(symbol, "__module__", None)
|
||||
# If __module__ is not set or comes from typing,
|
||||
# assume the definition is in module_path.
|
||||
if mod_name is None or mod_name.startswith("typing"):
|
||||
return module_path
|
||||
return mod_name
|
||||
except AttributeError as e:
|
||||
logger.warning(f"API Reference: Could not find module for {class_name}, {e}")
|
||||
return None
|
||||
except ImportError as e:
|
||||
logger.warning(f"API Reference: Failed to load for class {class_name}, {e}")
|
||||
return None
|
||||
|
||||
|
||||
class ImportInformation(TypedDict):
|
||||
imported: str # The name of the class that was imported.
|
||||
source: str # The full module path from which the class was imported.
|
||||
docs: str # The URL pointing to the class's documentation.
|
||||
path: str # The path of the file where the markdown content originated.
|
||||
|
||||
|
||||
def get_imports(code: str, path: str) -> List[ImportInformation]:
|
||||
"""Retrieve all import references from the given code for specified ecosystems.
|
||||
|
||||
Args:
|
||||
code: The source code from which to extract import references.
|
||||
path: The path of the file where the markdown content originated.
|
||||
|
||||
Returns:
|
||||
A list of import information for each import found.
|
||||
"""
|
||||
# Parse the code into an AST.
|
||||
try:
|
||||
tree = ast.parse(code)
|
||||
except SyntaxError:
|
||||
return []
|
||||
|
||||
found_imports = []
|
||||
|
||||
# Walk through the AST and process ImportFrom nodes.
|
||||
for node in ast.walk(tree):
|
||||
if isinstance(node, ast.ImportFrom):
|
||||
# node.module is the source module.
|
||||
if node.module is None:
|
||||
continue
|
||||
for alias in node.names:
|
||||
if not (
|
||||
node.module.startswith("langchain")
|
||||
or node.module.startswith("langgraph")
|
||||
):
|
||||
continue
|
||||
|
||||
found_imports.append(
|
||||
{
|
||||
"source": node.module,
|
||||
# alias.name is the original name even if an alias exists.
|
||||
"imported": alias.name,
|
||||
}
|
||||
)
|
||||
|
||||
imports: list[ImportInformation] = []
|
||||
|
||||
for found_import in found_imports:
|
||||
module = found_import["source"]
|
||||
|
||||
if module.startswith("langchain_mcp_adapters"):
|
||||
package_ecosystem = "langgraph"
|
||||
elif module.startswith("langchain"):
|
||||
# Handles things like `langchain` or `langchain_anthropic`
|
||||
package_ecosystem = "langchain"
|
||||
elif module.startswith("langgraph"):
|
||||
package_ecosystem = "langgraph"
|
||||
else:
|
||||
continue
|
||||
|
||||
class_name = found_import["imported"]
|
||||
module_path = _get_full_module_name(module, class_name)
|
||||
if not module_path:
|
||||
continue
|
||||
if len(module_path.split(".")) < 2:
|
||||
continue
|
||||
|
||||
if package_ecosystem == "langchain":
|
||||
pkg = module_path.split(".")[0].replace("langchain_", "")
|
||||
top_level_mod = module_path.split(".")[1]
|
||||
|
||||
url = (
|
||||
_LANGCHAIN_API_REFERENCE
|
||||
+ pkg
|
||||
+ "/"
|
||||
+ top_level_mod
|
||||
+ "/"
|
||||
+ module_path
|
||||
+ "."
|
||||
+ class_name
|
||||
+ ".html"
|
||||
)
|
||||
elif package_ecosystem == "langgraph":
|
||||
if (module, class_name) not in WELL_KNOWN_LANGGRAPH_OBJECTS:
|
||||
# Likely not documented yet
|
||||
continue
|
||||
|
||||
source_module, namespace = WELL_KNOWN_LANGGRAPH_OBJECTS[
|
||||
(module, class_name)
|
||||
]
|
||||
url = (
|
||||
_LANGGRAPH_API_REFERENCE
|
||||
+ namespace
|
||||
+ "/#"
|
||||
+ source_module
|
||||
+ "."
|
||||
+ class_name
|
||||
)
|
||||
else:
|
||||
raise ValueError(f"Invalid package ecosystem: {package_ecosystem}")
|
||||
|
||||
# Add the import information to our list
|
||||
imports.append(
|
||||
{
|
||||
"imported": class_name,
|
||||
"source": module,
|
||||
"docs": url,
|
||||
"path": path,
|
||||
}
|
||||
)
|
||||
|
||||
return imports
|
||||
|
||||
|
||||
def update_markdown_with_imports(markdown: str, path: str) -> str:
|
||||
"""Update markdown to include API reference links for imports in Python code blocks.
|
||||
|
||||
This function scans the markdown content for Python code blocks, extracts any
|
||||
imports, and appends links to their API documentation.
|
||||
|
||||
Args:
|
||||
markdown: The markdown content to process.
|
||||
path: The path of the file where the markdown content originated.
|
||||
|
||||
Returns:
|
||||
Updated markdown with API reference links prepended to Python code blocks.
|
||||
|
||||
Example:
|
||||
Given a markdown with a Python code block:
|
||||
|
||||
```python
|
||||
from langchain.nlp import TextGenerator
|
||||
```
|
||||
This function will append an API reference link to the `TextGenerator` class
|
||||
from the `langchain.nlp` module if it's recognized.
|
||||
"""
|
||||
code_block_pattern = re.compile(
|
||||
r"(?P<indent>[ \t]*)```(?P<language>python|py)\n(?P<code>.*?)\n(?P=indent)```",
|
||||
re.DOTALL,
|
||||
)
|
||||
|
||||
def replace_code_block(match: re.Match) -> str:
|
||||
"""Replace the matched code block with additional API reference links if imports are found.
|
||||
|
||||
Args:
|
||||
match (re.Match): The regex match object containing the code block.
|
||||
|
||||
Returns:
|
||||
str: The modified code block with API reference links prepended if applicable.
|
||||
"""
|
||||
indent = match.group("indent")
|
||||
code_block = match.group("code")
|
||||
# Retrieve import information from the code block
|
||||
imports = get_imports(code_block, "__unused__")
|
||||
|
||||
original_code_block = match.group(0)
|
||||
# If no imports are found, return the original code block
|
||||
if not imports:
|
||||
return original_code_block
|
||||
|
||||
# Generate API reference links for each import
|
||||
api_links = " | ".join(
|
||||
f'<a href="{imp["docs"]}">{imp["imported"]}</a>' for imp in imports
|
||||
)
|
||||
# Return the code block with prepended API reference links
|
||||
return f"{indent}<sup><i>API Reference: {api_links}</i></sup>\n\n{original_code_block}"
|
||||
|
||||
# Apply the replace_code_block function to all matches in the markdown
|
||||
updated_markdown = code_block_pattern.sub(replace_code_block, markdown)
|
||||
return updated_markdown
|
||||
@@ -0,0 +1,295 @@
|
||||
"""Experimental script to generate consolidated llms text from the docs."""
|
||||
|
||||
import asyncio
|
||||
import glob
|
||||
import os
|
||||
from typing import TypedDict, List, Optional
|
||||
import pydantic
|
||||
import re
|
||||
from pydantic import BaseModel, Field
|
||||
from langchain_core.rate_limiters import InMemoryRateLimiter
|
||||
|
||||
import yaml
|
||||
from langchain.chat_models import init_chat_model
|
||||
from mkdocs.structure.files import File
|
||||
from mkdocs.structure.pages import Page
|
||||
from yaml import SafeLoader
|
||||
|
||||
from _scripts.notebook_hooks import _on_page_markdown_with_config
|
||||
|
||||
HERE = os.path.dirname(os.path.abspath(__file__))
|
||||
# Get source directory (parent of HERE / docs)
|
||||
SOURCE_DIR = os.path.abspath(os.path.join(os.path.dirname(HERE), "docs"))
|
||||
|
||||
|
||||
async def convert_ipynb_to_md(file_path: str) -> Optional[str]:
|
||||
"""Process a file (markdown or notebook) to markdown format.
|
||||
|
||||
Args:
|
||||
file_path: Path to the file to process
|
||||
|
||||
Returns:
|
||||
Processed markdown content if successful, None otherwise
|
||||
"""
|
||||
rel_path = os.path.relpath(file_path, SOURCE_DIR)
|
||||
|
||||
# Create File and Page objects to match mkdocs structure
|
||||
file_obj = File(
|
||||
path=rel_path, src_dir=SOURCE_DIR, dest_dir="", use_directory_urls=True
|
||||
)
|
||||
page = Page(
|
||||
title="",
|
||||
file=file_obj,
|
||||
config={},
|
||||
)
|
||||
|
||||
try:
|
||||
# Read raw content
|
||||
with open(file_path, "r", encoding="utf-8") as f:
|
||||
content = f.read()
|
||||
|
||||
# Convert to markdown without logic to resolve API references
|
||||
processed_content = _on_page_markdown_with_config(
|
||||
content, page, add_api_references=False, remove_base64_images=True
|
||||
)
|
||||
# Remove self-closing img tags <img ... />
|
||||
processed_content = re.sub(r"<img[^>]*/>", "", processed_content)
|
||||
# Remove img tags with content <img ...>...</img>
|
||||
processed_content = re.sub(
|
||||
r"<img[^>]*>.*?</img>", "", processed_content, flags=re.DOTALL
|
||||
)
|
||||
return processed_content
|
||||
except Exception as e:
|
||||
print(f"Error processing file {file_path}: {e}")
|
||||
return None
|
||||
|
||||
|
||||
async def generate_full_llms_text(output_file: str) -> None:
|
||||
"""Generate a consolidated text file from markdown/notebook files for LLM training.
|
||||
|
||||
Args:
|
||||
output_file: Path to output the consolidated text file
|
||||
"""
|
||||
# Collect all markdown and notebook files
|
||||
all_files = glob.glob(os.path.join(SOURCE_DIR, "how-tos/*.md"), recursive=True)
|
||||
all_files.extend(
|
||||
glob.glob(os.path.join(SOURCE_DIR, "how-tos/*.ipynb"), recursive=True)
|
||||
)
|
||||
all_files.extend(
|
||||
glob.glob(os.path.join(SOURCE_DIR, "concepts/*.md"), recursive=True)
|
||||
)
|
||||
all_files.extend(
|
||||
glob.glob(os.path.join(SOURCE_DIR, "concepts/*.ipynb"), recursive=True)
|
||||
)
|
||||
|
||||
all_content = []
|
||||
|
||||
# Process files concurrently
|
||||
tasks = [convert_ipynb_to_md(file_path) for file_path in all_files]
|
||||
results = await asyncio.gather(*tasks)
|
||||
|
||||
# Combine results with file paths
|
||||
for file_path, processed_content in zip(all_files, results):
|
||||
if processed_content:
|
||||
rel_path = os.path.relpath(file_path, SOURCE_DIR)
|
||||
# Add file name
|
||||
all_content.append(f"---\n{rel_path}\n---")
|
||||
# Add content
|
||||
all_content.append(processed_content)
|
||||
|
||||
# Write consolidated output
|
||||
with open(output_file, "w", encoding="utf-8") as f:
|
||||
f.write("\n\n".join(all_content))
|
||||
|
||||
|
||||
def no_op_constructor(*args):
|
||||
"""No-op"""
|
||||
|
||||
|
||||
SafeLoader.add_multi_constructor(
|
||||
"tag:yaml.org,2002:python/name",
|
||||
no_op_constructor,
|
||||
)
|
||||
|
||||
|
||||
class NavItem(TypedDict):
|
||||
title: str
|
||||
url: str
|
||||
hierarchy: tuple[str, ...]
|
||||
description: str
|
||||
|
||||
|
||||
def _flatten_nav(
|
||||
nav: list[dict[str, str | list] | str], path: tuple[str, ...] = ()
|
||||
) -> list[NavItem]:
|
||||
flat: List[NavItem] = []
|
||||
for item in nav:
|
||||
if isinstance(item, dict):
|
||||
for title, node in item.items():
|
||||
new_path = path + (title,)
|
||||
if isinstance(node, str):
|
||||
# Leaf page
|
||||
flat.append(
|
||||
{
|
||||
"title": title,
|
||||
"url": node,
|
||||
"hierarchy": new_path,
|
||||
"description": "",
|
||||
}
|
||||
)
|
||||
elif isinstance(node, list):
|
||||
# Dive in, carrying along the updated path
|
||||
flat.extend(_flatten_nav(node, new_path))
|
||||
else:
|
||||
raise TypeError(
|
||||
f"Unexpected node type {type(node)} under {title!r}"
|
||||
)
|
||||
elif isinstance(item, str):
|
||||
# Bare string entry → use itself as title, and as URL
|
||||
new_path = path + (item,)
|
||||
flat.append(
|
||||
{"title": item, "url": item, "hierarchy": new_path, "description": ""}
|
||||
)
|
||||
else:
|
||||
raise TypeError(f"Unexpected item type {type(item)} in nav")
|
||||
return flat
|
||||
|
||||
|
||||
class PageInfo(BaseModel):
|
||||
title: str = Field(description="The title of the page")
|
||||
description: str = Field(
|
||||
description="A short description of the page no longer than 3 sentences "
|
||||
"explaining the kind of content that can be found in the page."
|
||||
)
|
||||
|
||||
|
||||
async def process_nav_items(nav_items: list[NavItem]) -> list[NavItem]:
|
||||
"""Open the contents of each nav item and come up with a better title and description."""
|
||||
rate_limiter = InMemoryRateLimiter(requests_per_second=10)
|
||||
model = init_chat_model("gpt-4o-mini", temperature=0.0, rate_limiter=rate_limiter)
|
||||
model = model.with_structured_output(PageInfo)
|
||||
|
||||
async def process_single_item(item: NavItem) -> NavItem:
|
||||
path = item["url"]
|
||||
file_path = os.path.join(SOURCE_DIR, path)
|
||||
|
||||
# Process the file content (handles both markdown and notebooks)
|
||||
if path.endswith(".ipynb"):
|
||||
content = await convert_ipynb_to_md(file_path)
|
||||
else:
|
||||
with open(file_path, "r", encoding="utf-8") as f:
|
||||
content = f.read()
|
||||
|
||||
if not content:
|
||||
return item
|
||||
|
||||
# Generate a better title and description
|
||||
response = await model.ainvoke(
|
||||
[
|
||||
{
|
||||
"role": "system",
|
||||
"content": "You are a technical documentation writer. "
|
||||
"You are given a markdown page of documentation. "
|
||||
"Please come up with an appropriate title and "
|
||||
"description for the page. The description should "
|
||||
"be a short summary of the page content that is "
|
||||
"no longer than 3 sentences.",
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": "The markdown page is as follows:\n\n" + content,
|
||||
},
|
||||
]
|
||||
)
|
||||
return {
|
||||
"title": response.title,
|
||||
"url": item["url"],
|
||||
"hierarchy": item["hierarchy"],
|
||||
"description": response.description,
|
||||
}
|
||||
|
||||
# Remove any items that start with http:// or https:// looking only for
|
||||
# local file at this stages.
|
||||
nav_items = [
|
||||
item for item in nav_items if not item["url"].startswith(("http://", "https://"))
|
||||
]
|
||||
# Process items in parallel
|
||||
tasks = [process_single_item(item) for item in nav_items]
|
||||
new_nav_items = await asyncio.gather(*tasks)
|
||||
return new_nav_items
|
||||
|
||||
|
||||
async def generate_nav_links_text(
|
||||
output_file: str, *, replace_links: bool = False
|
||||
) -> None:
|
||||
"""Generate llms.txt from mkdocs.yaml."""
|
||||
# Get path to mkdocs.yaml relative to this script
|
||||
script_dir = os.path.dirname(os.path.abspath(__file__))
|
||||
mkdocs_path = os.path.join(os.path.dirname(script_dir), "mkdocs.yml")
|
||||
|
||||
# Load and parse yaml
|
||||
with open(mkdocs_path, "r") as f:
|
||||
config = yaml.safe_load(f)
|
||||
|
||||
# Extract nav section
|
||||
nav = config.get("nav", [])
|
||||
flattened = _flatten_nav(nav)
|
||||
|
||||
processed_nav = await process_nav_items(flattened)
|
||||
|
||||
with open(output_file, "w") as f:
|
||||
current_section = None
|
||||
for item in processed_nav:
|
||||
# Get the top-level section (first item in hierarchy)
|
||||
section = item["hierarchy"][0]
|
||||
|
||||
if section not in {"Guides", "Examples", "Resources"}:
|
||||
continue
|
||||
|
||||
# If we're starting a new section, add a heading
|
||||
if section != current_section:
|
||||
f.write(f"\n# {section}\n\n")
|
||||
current_section = section
|
||||
|
||||
title = item["title"]
|
||||
# Process URL based on replace_links flag
|
||||
url = item["url"]
|
||||
if replace_links:
|
||||
# Remove .md extension and ensure single trailing slash
|
||||
url = url.removesuffix(".md")
|
||||
url = url.removesuffix(".ipynb")
|
||||
url = url.rstrip("/") + "/"
|
||||
url = f"https://langchain-ai.github.io/langgraph/{url}"
|
||||
|
||||
f.write(f"- [{title}]({url}): {item['description']}\n")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import argparse
|
||||
|
||||
parser = argparse.ArgumentParser(
|
||||
description=(
|
||||
"Generate consolidated text file from markdown/notebook files for LLMs."
|
||||
)
|
||||
)
|
||||
parser.add_argument("output_file", help="Path to output the consolidated text file")
|
||||
parser.add_argument(
|
||||
"--link-only",
|
||||
action="store_true",
|
||||
help="Only include link references in the output",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--replace-links",
|
||||
action="store_true",
|
||||
help="Replace markdown links with full URLs in the output",
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
if args.link_only:
|
||||
coro = generate_nav_links_text(
|
||||
args.output_file, replace_links=args.replace_links
|
||||
)
|
||||
else:
|
||||
coro = generate_full_llms_text(args.output_file)
|
||||
|
||||
asyncio.run(coro)
|
||||
@@ -0,0 +1,382 @@
|
||||
import ast
|
||||
import os
|
||||
import re
|
||||
from typing import Literal
|
||||
|
||||
import nbformat
|
||||
from nbconvert.exporters import MarkdownExporter
|
||||
from nbconvert.preprocessors import Preprocessor
|
||||
|
||||
|
||||
def _uses_input(source: str) -> bool:
|
||||
"""Parse the source code to determine if it uses the input() function."""
|
||||
try:
|
||||
tree = ast.parse(source)
|
||||
except SyntaxError:
|
||||
# If there's a syntax error, assume input() might be present to be safe.
|
||||
return False
|
||||
|
||||
for node in ast.walk(tree):
|
||||
if isinstance(node, ast.Call):
|
||||
# Check if the function called is named 'input'
|
||||
if isinstance(node.func, ast.Name) and node.func.id == "input":
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def _rewrite_cell_magic(code: str) -> str:
|
||||
"""Process a code block that uses cell magic.
|
||||
|
||||
- Lines starting with "%%capture" are ignored.
|
||||
- Lines starting with "%pip" are rewritten by removing the leading "%" character.
|
||||
- Any other non-empty line causes a NotImplementedError.
|
||||
|
||||
Args:
|
||||
code (str): The original code block.
|
||||
|
||||
Returns:
|
||||
str: The transformed code block.
|
||||
|
||||
Raises:
|
||||
NotImplementedError: If a line doesn't start with either "%%capture" or "%pip".
|
||||
"""
|
||||
rewritten_lines = []
|
||||
|
||||
for line in code.splitlines():
|
||||
stripped = line.strip()
|
||||
# Skip empty lines
|
||||
if not stripped:
|
||||
continue
|
||||
# Ignore %%capture lines
|
||||
if stripped.startswith("%%capture"):
|
||||
continue
|
||||
# Rewrite %pip lines by dropping the '%'
|
||||
elif stripped.startswith("%") or stripped.startswith("!"):
|
||||
# Drop the leading '%' character and then drop all leading whitespace
|
||||
stripped = stripped.lstrip("%! \t")
|
||||
# Check if the line starts with "pip"
|
||||
if stripped.startswith("pip"):
|
||||
rewritten_lines.append(stripped)
|
||||
else:
|
||||
raise NotImplementedError(f"Unhandled line: {line}")
|
||||
else:
|
||||
raise NotImplementedError(f"Unhandled line: {line}")
|
||||
|
||||
return "\n".join(rewritten_lines)
|
||||
|
||||
|
||||
class PrintCallVisitor(ast.NodeVisitor):
|
||||
"""
|
||||
This visitor sets self.has_print to True if it encounters a call
|
||||
to a print within the global scope.
|
||||
|
||||
This should catch calls to print(), print_stream(), etc. (Prefixed with "print").
|
||||
|
||||
May have some false positives, but it's not meant to be perfect.
|
||||
|
||||
Temporary code for notebook conversion.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self.has_print = False
|
||||
self.scope_level = 0 # counter to track whether we're inside a def/lambda
|
||||
|
||||
def visit_FunctionDef(self, node):
|
||||
self.scope_level += 1
|
||||
self.generic_visit(node)
|
||||
self.scope_level -= 1
|
||||
|
||||
def visit_AsyncFunctionDef(self, node):
|
||||
self.scope_level += 1
|
||||
self.generic_visit(node)
|
||||
self.scope_level -= 1
|
||||
|
||||
def visit_Lambda(self, node):
|
||||
self.scope_level += 1
|
||||
self.generic_visit(node)
|
||||
self.scope_level -= 1
|
||||
|
||||
def visit_ClassDef(self, node):
|
||||
self.scope_level += 1
|
||||
self.generic_visit(node)
|
||||
self.scope_level -= 1
|
||||
|
||||
def visit_Call(self, node):
|
||||
# Only consider calls when not inside a function definition.
|
||||
if self.scope_level == 0:
|
||||
if isinstance(node.func, ast.Name) and node.func.id.startswith("print"):
|
||||
self.has_print = True
|
||||
self.generic_visit(node)
|
||||
|
||||
|
||||
def _has_output(source: str) -> bool:
|
||||
"""Determine if the code block is expected to produce output.
|
||||
|
||||
Args:
|
||||
source (str): The source code of the code block.
|
||||
|
||||
Returns:
|
||||
True if the code block is expected to produce output, False otherwise.
|
||||
|
||||
Must meet the following conditions:
|
||||
|
||||
1. There is a call to a printing function (name starts with "print")
|
||||
that is not inside a function definition.
|
||||
2. The last top-level statement is an expression that is valid if:
|
||||
- It is any expression (including calls) AND
|
||||
- It is NOT a call to `display(...)`.
|
||||
|
||||
`display` isn't handled currently by markdown-exec
|
||||
"""
|
||||
try:
|
||||
tree = ast.parse(source)
|
||||
except SyntaxError:
|
||||
return False
|
||||
|
||||
# Condition (1): Check for a global print-like call.
|
||||
visitor = PrintCallVisitor()
|
||||
visitor.visit(tree)
|
||||
condition_a = visitor.has_print
|
||||
|
||||
# Condition (2): Check the last top-level statement.
|
||||
condition_b = False
|
||||
if tree.body:
|
||||
last_stmt = tree.body[-1]
|
||||
if isinstance(last_stmt, ast.Expr):
|
||||
# If the expression is a call, ensure it's not a call to "display"
|
||||
if isinstance(last_stmt.value, ast.Call):
|
||||
if (
|
||||
isinstance(last_stmt.value.func, ast.Name)
|
||||
and last_stmt.value.func.id == "display"
|
||||
):
|
||||
condition_b = False # exclude display-wrapped expressions
|
||||
else:
|
||||
condition_b = True
|
||||
else:
|
||||
# Any other expression qualifies.
|
||||
condition_b = True
|
||||
|
||||
return condition_a or condition_b
|
||||
|
||||
|
||||
def _convert_links_in_markdown(markdown: str) -> str:
|
||||
"""Convert links present in notebook markdown cells to standardized format.
|
||||
|
||||
We want to update markdown links code cells by linking to markdown
|
||||
files rather than assuming that the link is to the finalized HTML.
|
||||
|
||||
This code is needed temporarily since the markdown links that are present
|
||||
in ipython notebooks do not follow the same conventions as regular markdown
|
||||
files in mkdocs (which should link to a .md file).
|
||||
"""
|
||||
|
||||
# Define the regex pattern in parts for clarity:
|
||||
pattern = (
|
||||
r"(?<!!)" # Negative lookbehind: ensure the link is not an image (i.e., doesn't start with "!")
|
||||
r"\[" # Literal '[' indicating the start of the link text.
|
||||
r"(?P<text>[^\]]*)" # Named group 'text': match any characters except ']', representing the link text.
|
||||
r"\]" # Literal ']' indicating the end of the link text.
|
||||
r"\(" # Literal '(' indicating the start of the URL.
|
||||
r"(?![^\)]*//)" # Negative lookahead: ensure that the URL does not contain '//' (skip absolute URLs).
|
||||
r"(?P<url>[^)]*)" # Named group 'url': match any characters except ')', representing the URL.
|
||||
r"\)" # Literal ')' indicating the end of the URL.
|
||||
)
|
||||
|
||||
def custom_replacement(match):
|
||||
"""logic will correct the link format used in ipython notebooks
|
||||
|
||||
Ipython notebooks were being converted directly into HTML links
|
||||
instead of markdown links that retain the markdown extension.
|
||||
|
||||
It needs to handle the following cases:
|
||||
- optional fragments (e.g., `#section`)
|
||||
e.g., `[text](url/#section)` -> `[text](url.md#section)`
|
||||
e.g., `[text](url#section)` -> `[text](url.md#section)`
|
||||
- relative paths (e.g., `../path/to/file`) need to be denested by 1 level
|
||||
"""
|
||||
text = match.group("text")
|
||||
url = match.group("url")
|
||||
|
||||
if url.startswith("../"):
|
||||
# we strip the "../" from the start of the URL
|
||||
# We only need to denest one level.
|
||||
url = url[3:]
|
||||
|
||||
url = url.rstrip("/") # Strip `/` from the end of the URL
|
||||
|
||||
# if url has a fragment
|
||||
if "#" in url:
|
||||
url, fragment = url.split("#")
|
||||
url = url.rstrip("/")
|
||||
# Strip `/` from the end of the URL
|
||||
return f"[{text}]({url}.md#{fragment})"
|
||||
# Otherwise add the .md extension
|
||||
return f"[{text}]({url}.md)"
|
||||
|
||||
return re.sub(
|
||||
pattern,
|
||||
custom_replacement,
|
||||
markdown,
|
||||
)
|
||||
|
||||
|
||||
class HideCellTagPreprocessor(Preprocessor):
|
||||
"""
|
||||
Removes cells that have '# hide-cell' at the beginning of the cell content.
|
||||
This allows authors to include cells in the notebook that should not
|
||||
appear in the generated markdown output.
|
||||
"""
|
||||
|
||||
def preprocess(self, nb, resources):
|
||||
# Filter out cells with the '# hide-cell' comment at the beginning
|
||||
nb.cells = [
|
||||
cell
|
||||
for cell in nb.cells
|
||||
if not (cell.source.strip().startswith("# hide-cell"))
|
||||
]
|
||||
|
||||
return nb, resources
|
||||
|
||||
|
||||
class EscapePreprocessor(Preprocessor):
|
||||
def __init__(self, markdown_exec_migration: bool = False, **kwargs) -> None:
|
||||
super().__init__(**kwargs)
|
||||
self.markdown_exec_migration = markdown_exec_migration
|
||||
|
||||
def preprocess_cell(self, cell, resources, cell_index):
|
||||
if cell.cell_type == "markdown":
|
||||
if not self.markdown_exec_migration:
|
||||
# Old logic is to convert ipynb links to HTML links
|
||||
cell.source = re.sub(
|
||||
r"(?<!!)\[([^\]]*)\]\((?![^\)]*//)([^)]*)(?:\.ipynb)?\)",
|
||||
r'<a href="\2">\1</a>',
|
||||
cell.source,
|
||||
)
|
||||
else:
|
||||
cell.source = _convert_links_in_markdown(cell.source)
|
||||
|
||||
# Fix image paths in <img> tags
|
||||
cell.source = re.sub(
|
||||
r'<img\s+src="\.?/img/([^"]+)"', r'<img src="../img/\1"', cell.source
|
||||
)
|
||||
|
||||
elif cell.cell_type == "code":
|
||||
# Determine if the cell has bash or cell magic
|
||||
source = cell.source
|
||||
is_exec = not (
|
||||
source.startswith("%") or source.startswith("!") or _uses_input(source)
|
||||
)
|
||||
cell.metadata["exec"] = is_exec
|
||||
|
||||
# For markdown exec migration we'll re-write cell magic as bash commands
|
||||
if source.startswith("%%"):
|
||||
cell.source = _rewrite_cell_magic(source)
|
||||
cell.metadata["language"] = "shell"
|
||||
|
||||
# Remove noqa comments
|
||||
cell.source = re.sub(r"#\s*noqa.*$", "", cell.source, flags=re.MULTILINE)
|
||||
# escape ``` in code
|
||||
# This is needed because the markdown exporter will wrap code blocks in
|
||||
# triple backticks, which will break the markdown output if the code block
|
||||
# contains triple backticks.
|
||||
cell.source = cell.source.replace("```", r"\`\`\`")
|
||||
# escape ``` in output
|
||||
if "outputs" in cell:
|
||||
filter_out = set()
|
||||
for i, output in enumerate(cell["outputs"]):
|
||||
if "text" in output:
|
||||
if not output["text"].strip():
|
||||
filter_out.add(i)
|
||||
continue
|
||||
|
||||
value = output["text"].replace("```", r"\`\`\`")
|
||||
# handle a funky case w/ references in text
|
||||
value = re.sub(r"\[(\d+)\](?=\[(\d+)\])", r"[\1]\\", value)
|
||||
output["text"] = value
|
||||
elif "data" in output:
|
||||
for key, value in output["data"].items():
|
||||
if isinstance(value, str):
|
||||
value = value.replace("```", r"\`\`\`")
|
||||
# handle a funky case w/ references in text
|
||||
output["data"][key] = re.sub(
|
||||
r"\[(\d+)\](?=\[(\d+)\])", r"[\1]\\", value
|
||||
)
|
||||
cell["outputs"] = [
|
||||
output
|
||||
for i, output in enumerate(cell["outputs"])
|
||||
if i not in filter_out
|
||||
]
|
||||
|
||||
return cell, resources
|
||||
|
||||
|
||||
class ExtractAttachmentsPreprocessor(Preprocessor):
|
||||
"""
|
||||
Extracts all of the outputs from the notebook file. The extracted
|
||||
outputs are returned in the 'resources' dictionary.
|
||||
"""
|
||||
|
||||
def preprocess_cell(self, cell, resources, cell_index):
|
||||
"""
|
||||
Apply a transformation on each cell,
|
||||
Parameters
|
||||
----------
|
||||
cell : NotebookNode cell
|
||||
Notebook cell being processed
|
||||
resources : dictionary
|
||||
Additional resources used in the conversion process. Allows
|
||||
preprocessors to pass variables into the Jinja engine.
|
||||
cell_index : int
|
||||
Index of the cell being processed (see base.py)
|
||||
"""
|
||||
|
||||
# Get files directory if it has been specified
|
||||
|
||||
# Make sure outputs key exists
|
||||
if not isinstance(resources["outputs"], dict):
|
||||
resources["outputs"] = {}
|
||||
|
||||
# Loop through all of the attachments in the cell
|
||||
for name, attach in cell.get("attachments", {}).items():
|
||||
for mime, data in attach.items():
|
||||
if mime not in {
|
||||
"image/png",
|
||||
"image/jpeg",
|
||||
"image/svg+xml",
|
||||
"application/pdf",
|
||||
}:
|
||||
continue
|
||||
|
||||
# attachments are pre-rendered. Only replace markdown-formatted
|
||||
# images with the following logic
|
||||
attach_str = f"({name})"
|
||||
if attach_str in cell.source:
|
||||
data = f"(data:{mime};base64,{data})"
|
||||
cell.source = cell.source.replace(attach_str, data)
|
||||
|
||||
return cell, resources
|
||||
|
||||
|
||||
exporter = MarkdownExporter(
|
||||
preprocessors=[
|
||||
HideCellTagPreprocessor,
|
||||
EscapePreprocessor,
|
||||
ExtractAttachmentsPreprocessor,
|
||||
],
|
||||
template_name="mdoutput",
|
||||
extra_template_basedirs=[
|
||||
os.path.join(os.path.dirname(__file__), "notebook_convert_templates")
|
||||
],
|
||||
)
|
||||
|
||||
|
||||
def convert_notebook(
|
||||
notebook_path: str,
|
||||
mode: Literal["markdown", "exec"] = "markdown",
|
||||
) -> str:
|
||||
with open(notebook_path) as f:
|
||||
nb = nbformat.read(f, as_version=4)
|
||||
|
||||
nb.metadata.mode = mode
|
||||
body, _ = exporter.from_notebook_node(nb)
|
||||
return body
|
||||
@@ -0,0 +1,5 @@
|
||||
{
|
||||
"mimetypes": {
|
||||
"text/markdown": true
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,50 @@
|
||||
{% extends 'markdown/index.md.j2' %}
|
||||
|
||||
{% block input %}{# cell.metadata.language is an addition of our docs pipeline. #}
|
||||
```{%- if 'language' in cell.metadata -%}
|
||||
{{ cell.metadata.language }}
|
||||
{%- elif 'magics_language' in cell.metadata -%}
|
||||
{{ cell.metadata.magics_language }}
|
||||
{%- elif 'name' in nb.metadata.get('language_info', {}) -%}
|
||||
{{ nb.metadata.language_info.name }}
|
||||
{%- endif %}
|
||||
{{ cell.source }}
|
||||
```
|
||||
{% endblock input %}
|
||||
|
||||
|
||||
{%- block traceback_line -%}
|
||||
```output
|
||||
{{ line.rstrip() | strip_ansi }}
|
||||
```
|
||||
{%- endblock traceback_line -%}
|
||||
|
||||
{%- block stream -%}
|
||||
```output
|
||||
{{ output.text.rstrip() | strip_ansi }}
|
||||
```
|
||||
{%- endblock stream -%}
|
||||
|
||||
{%- block data_text scoped -%}
|
||||
```output
|
||||
{{ output.data['text/plain'].rstrip() | strip_ansi }}
|
||||
```
|
||||
{%- endblock data_text -%}
|
||||
|
||||
{%- block data_html scoped -%}
|
||||
```html
|
||||
{{ output.data['text/html'] | safe }}
|
||||
```
|
||||
{%- endblock data_html -%}
|
||||
|
||||
{%- block data_jpg scoped -%}
|
||||
<p>
|
||||
<img src="data:image/jpg;base64,{{ output.data['image/jpeg'] }}" />
|
||||
</p>
|
||||
{%- endblock data_jpg -%}
|
||||
|
||||
{%- block data_png scoped -%}
|
||||
<p>
|
||||
<img src="data:image/png;base64,{{ output.data['image/png'] }}" />
|
||||
</p>
|
||||
{%- endblock data_png -%}
|
||||
@@ -0,0 +1,379 @@
|
||||
"""mkdocs hooks for adding custom logic to documentation pipeline.
|
||||
|
||||
Lifecycle events: https://www.mkdocs.org/dev-guide/plugins/#events
|
||||
"""
|
||||
|
||||
import logging
|
||||
import os
|
||||
import posixpath
|
||||
import re
|
||||
from typing import Any, Dict
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
from mkdocs.config.defaults import MkDocsConfig
|
||||
from mkdocs.structure.files import Files, File
|
||||
from mkdocs.structure.pages import Page
|
||||
|
||||
from _scripts.generate_api_reference_links import update_markdown_with_imports
|
||||
from _scripts.notebook_convert import convert_notebook
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
logging.basicConfig()
|
||||
logger.setLevel(logging.INFO)
|
||||
DISABLED = os.getenv("DISABLE_NOTEBOOK_CONVERT") in ("1", "true", "True")
|
||||
|
||||
|
||||
REDIRECT_MAP = {
|
||||
# lib redirects
|
||||
"how-tos/stream-values.ipynb": "how-tos/streaming.md#stream-graph-state",
|
||||
"how-tos/stream-updates.ipynb": "how-tos/streaming.md#stream-graph-state",
|
||||
"how-tos/streaming-content.ipynb": "how-tos/streaming.md",
|
||||
"how-tos/stream-multiple.ipynb": "how-tos/streaming.md#stream-multiple-nodes",
|
||||
"how-tos/streaming-tokens-without-langchain.ipynb": "how-tos/streaming.md#use-with-any-llm",
|
||||
"how-tos/streaming-from-final-node.ipynb": "how-tos/streaming-specific-nodes.ipynb",
|
||||
"how-tos/streaming-events-from-within-tools-without-langchain.ipynb": "how-tos/streaming-events-from-within-tools.ipynb#example-without-langchain",
|
||||
# graph-api
|
||||
"how-tos/state-reducers.ipynb": "how-tos/graph-api#define-and-update-state",
|
||||
"how-tos/sequence.ipynb": "how-tos/graph-api#create-a-sequence-of-steps",
|
||||
"how-tos/branching.ipynb": "how-tos/graph-api#create-branches",
|
||||
"how-tos/recursion-limit.ipynb": "how-tos/graph-api#create-and-control-loops",
|
||||
"how-tos/visualization.ipynb": "how-tos/graph-api#visualize-your-graph",
|
||||
"how-tos/input_output_schema.ipynb": "how-tos/graph-api#define-input-and-output-schemas",
|
||||
"how-tos/pass_private_state.ipynb": "how-tos/graph-api#pass-private-state-between-nodes",
|
||||
"how-tos/state-model.ipynb": "how-tos/graph-api#use-pydantic-models-for-graph-state",
|
||||
"how-tos/map-reduce.ipynb": "how-tos/graph-api/#map-reduce-and-the-send-api",
|
||||
"how-tos/command.ipynb": "how-tos/graph-api/#combine-control-flow-and-state-updates-with-command",
|
||||
"how-tos/configuration.ipynb": "how-tos/graph-api/#add-runtime-configuration",
|
||||
"how-tos/node-retries.ipynb": "how-tos/graph-api/#add-retry-policies",
|
||||
"how-tos/return-when-recursion-limit-hits.ipynb": "how-tos/graph-api/#impose-a-recursion-limit",
|
||||
"how-tos/async.ipynb": "how-tos/graph-api/#async",
|
||||
# memory how-tos
|
||||
"how-tos/memory/manage-conversation-history.ipynb": "how-tos/memory.ipynb",
|
||||
"how-tos/memory/delete-messages.ipynb": "how-tos/memory.ipynb#delete-messages",
|
||||
"how-tos/memory/add-summary-conversation-history.ipynb": "how-tos/memory.ipynb#summarize-messages",
|
||||
# subgraph how-tos
|
||||
"how-tos/subgraph-transform-state.ipynb": "how-tos/subgraph.ipynb#different-state-schemas",
|
||||
"how-tos/subgraphs-manage-state.ipynb": "how-tos/subgraph.ipynb#add-persistence",
|
||||
# persistence how-tos
|
||||
"how-tos/persistence_postgres.ipynb": "how-tos/persistence.ipynb#use-in-production",
|
||||
"how-tos/persistence_mongodb.ipynb": "how-tos/persistence.ipynb#use-in-production",
|
||||
"how-tos/persistence_redis.ipynb": "how-tos/persistence.ipynb#use-in-production",
|
||||
"how-tos/subgraph-persistence.ipynb": "how-tos/persistence.ipynb#use-with-subgraphs",
|
||||
"how-tos/cross-thread-persistence.ipynb": "how-tos/persistence.ipynb#add-long-term-memory",
|
||||
"cloud/how-tos/copy_threads": "cloud/how-tos/use_threads",
|
||||
# tool calling how-tos
|
||||
"how-tos/tool-calling-errors.ipynb": "how-tos/tool-calling.ipynb#handle-errors",
|
||||
"how-tos/pass-config-to-tools.ipynb": "how-tos/tool-calling.ipynb#access-config",
|
||||
"how-tos/pass-run-time-values-to-tools.ipynb": "how-tos/tool-calling.ipynb#read-state",
|
||||
"how-tos/update-state-from-tools.ipynb": "how-tos/tool-calling.ipynb#update-state",
|
||||
# multi-agent how-tos
|
||||
"how-tos/agent-handoffs.ipynb": "how-tos/multi_agent.ipynb#handoffs",
|
||||
"how-tos/multi-agent-network.ipynb": "how-tos/multi_agent.ipynb#use-in-a-multi-agent-system",
|
||||
"how-tos/multi-agent-multi-turn-convo.ipynb": "how-tos/multi_agent.ipynb#multi-turn-conversation",
|
||||
# cloud redirects
|
||||
"cloud/index.md": "index.md",
|
||||
"cloud/how-tos/index.md": "concepts/langgraph_platform",
|
||||
"cloud/concepts/api.md": "concepts/langgraph_server.md",
|
||||
"cloud/concepts/cloud.md": "concepts/langgraph_cloud.md",
|
||||
"cloud/faq/studio.md": "concepts/langgraph_studio.md#studio-faqs",
|
||||
"cloud/how-tos/human_in_the_loop_edit_state.md": "cloud/how-tos/add-human-in-the-loop.md",
|
||||
"cloud/how-tos/human_in_the_loop_user_input.md": "cloud/how-tos/add-human-in-the-loop.md",
|
||||
"concepts/platform_architecture.md": "concepts/langgraph_cloud#architecture",
|
||||
# cloud streaming redirects
|
||||
"cloud/how-tos/stream_values.md": "cloud/how-tos/streaming.md#stream-graph-state",
|
||||
"cloud/how-tos/stream_updates.md": "cloud/how-tos/streaming.md#stream-graph-state",
|
||||
"cloud/how-tos/stream_messages.md": "cloud/how-tos/streaming.md#messages",
|
||||
"cloud/how-tos/stream_events.md": "cloud/how-tos/streaming.md#stream-events",
|
||||
"cloud/how-tos/stream_debug.md": "cloud/how-tos/streaming.md#debug",
|
||||
"cloud/how-tos/stream_multiple.md": "cloud/how-tos/streaming.md#stream-multiple-modes",
|
||||
# prebuit redirects
|
||||
"how-tos/create-react-agent.ipynb": "agents/agents.md#basic-configuration",
|
||||
"how-tos/create-react-agent-memory.ipynb": "agents/memory.md",
|
||||
"how-tos/create-react-agent-system-prompt.ipynb": "agents/context.md#prompts",
|
||||
"how-tos/create-react-agent-hitl.ipynb": "agents/human-in-the-loop.md",
|
||||
"how-tos/create-react-agent-structured-output.ipynb": "agents/agents.md#structured-output",
|
||||
# Time-travel
|
||||
"how-tos/human_in_the_loop/edit-graph-state.ipynb": "how-tos/human_in_the_loop/time-travel.ipynb",
|
||||
# breakpoints
|
||||
"how-tos/human_in_the_loop/dynamic_breakpoints.ipynb": "how-tos/human_in_the_loop/breakpoints.ipynb",
|
||||
# misc
|
||||
"prebuilt.md": "agents/prebuilt.md",
|
||||
"reference/prebuilt.md": "reference/agents.md",
|
||||
"concepts/high_level.md": "index.md",
|
||||
"concepts/index.md": "index.md",
|
||||
"concepts/v0-human-in-the-loop.md": "concepts/human-in-the-loop.md",
|
||||
"how-tos/index.md": "index.md",
|
||||
"tutorials/introduction.ipynb": "concepts/why-langgraph.md",
|
||||
# deployment redirects
|
||||
"how-tos/deploy-self-hosted.md": "cloud/deployment/self_hosted_data_plane.md",
|
||||
"concepts/self_hosted.md": "concepts/langgraph_self_hosted_data_plane.md",
|
||||
# assistant redirects
|
||||
"cloud/how-tos/assistant_versioning.md": "cloud/how-tos/configuration_cloud.md",
|
||||
}
|
||||
|
||||
|
||||
class NotebookFile(File):
|
||||
def is_documentation_page(self):
|
||||
return True
|
||||
|
||||
|
||||
def on_files(files: Files, **kwargs: Dict[str, Any]):
|
||||
if DISABLED:
|
||||
return files
|
||||
new_files = Files([])
|
||||
for file in files:
|
||||
if file.src_path.endswith(".ipynb"):
|
||||
new_file = NotebookFile(
|
||||
path=file.src_path,
|
||||
src_dir=file.src_dir,
|
||||
dest_dir=file.dest_dir,
|
||||
use_directory_urls=file.use_directory_urls,
|
||||
)
|
||||
new_files.append(new_file)
|
||||
else:
|
||||
new_files.append(file)
|
||||
return new_files
|
||||
|
||||
|
||||
def _add_path_to_code_blocks(markdown: str, page: Page) -> str:
|
||||
"""Add the path to the code blocks."""
|
||||
code_block_pattern = re.compile(
|
||||
r"(?P<indent>[ \t]*)```(?P<language>\w+)[ ]*(?P<attributes>[^\n]*)\n"
|
||||
r"(?P<code>((?:.*\n)*?))" # Capture the code inside the block using named group
|
||||
r"(?P=indent)```" # Match closing backticks with the same indentation
|
||||
)
|
||||
|
||||
def replace_code_block_header(match: re.Match) -> str:
|
||||
indent = match.group("indent")
|
||||
language = match.group("language")
|
||||
attributes = match.group("attributes").rstrip()
|
||||
|
||||
if 'exec="on"' not in attributes:
|
||||
# Return original code block
|
||||
return match.group(0)
|
||||
|
||||
code = match.group("code")
|
||||
return f'{indent}```{language} {attributes} path="{page.file.src_path}"\n{code}{indent}```'
|
||||
|
||||
return code_block_pattern.sub(replace_code_block_header, markdown)
|
||||
|
||||
|
||||
def _highlight_code_blocks(markdown: str) -> str:
|
||||
"""Find code blocks with highlight comments and add hl_lines attribute.
|
||||
|
||||
Args:
|
||||
markdown: The markdown content to process.
|
||||
|
||||
Returns:
|
||||
updated Markdown code with code blocks containing highlight comments
|
||||
updated to use the hl_lines attribute.
|
||||
"""
|
||||
# Pattern to find code blocks with highlight comments and without
|
||||
# existing hl_lines for Python and JavaScript
|
||||
# Pattern to find code blocks with highlight comments, handling optional indentation
|
||||
code_block_pattern = re.compile(
|
||||
r"(?P<indent>[ \t]*)```(?P<language>\w+)[ ]*(?P<attributes>[^\n]*)\n"
|
||||
r"(?P<code>((?:.*\n)*?))" # Capture the code inside the block using named group
|
||||
r"(?P=indent)```" # Match closing backticks with the same indentation
|
||||
)
|
||||
|
||||
def replace_highlight_comments(match: re.Match) -> str:
|
||||
indent = match.group("indent")
|
||||
language = match.group("language")
|
||||
code_block = match.group("code")
|
||||
attributes = match.group("attributes").rstrip()
|
||||
|
||||
# Account for a case where hl_lines is manually specified
|
||||
if "hl_lines" in attributes:
|
||||
# Return original code block
|
||||
return match.group(0)
|
||||
|
||||
lines = code_block.split("\n")
|
||||
highlighted_lines = []
|
||||
|
||||
# Skip initial empty lines
|
||||
while lines and not lines[0].strip():
|
||||
lines.pop(0)
|
||||
|
||||
lines_to_keep = []
|
||||
|
||||
comment_syntax = (
|
||||
"# highlight-next-line"
|
||||
if language in ["py", "python"]
|
||||
else "// highlight-next-line"
|
||||
)
|
||||
|
||||
for line in lines:
|
||||
if comment_syntax in line:
|
||||
count = len(lines_to_keep) + 1
|
||||
highlighted_lines.append(str(count))
|
||||
else:
|
||||
lines_to_keep.append(line)
|
||||
|
||||
# Reconstruct the new code block
|
||||
new_code_block = "\n".join(lines_to_keep)
|
||||
|
||||
# Construct the full code block that also includes
|
||||
# the fenced code block syntax.
|
||||
opening_fence = f"```{language}"
|
||||
|
||||
if attributes:
|
||||
opening_fence += f" {attributes}"
|
||||
|
||||
if highlighted_lines:
|
||||
opening_fence += f" hl_lines=\"{' '.join(highlighted_lines)}\""
|
||||
|
||||
return (
|
||||
# The indent and opening fence
|
||||
f"{indent}{opening_fence}\n"
|
||||
# The indent and terminating \n is already included in the code block
|
||||
f"{new_code_block}"
|
||||
f"{indent}```"
|
||||
)
|
||||
|
||||
# Replace all code blocks in the markdown
|
||||
markdown = code_block_pattern.sub(replace_highlight_comments, markdown)
|
||||
return markdown
|
||||
|
||||
|
||||
def _on_page_markdown_with_config(
|
||||
markdown: str,
|
||||
page: Page,
|
||||
*,
|
||||
add_api_references: bool = True,
|
||||
remove_base64_images: bool = False,
|
||||
**kwargs: Any,
|
||||
) -> str:
|
||||
if DISABLED:
|
||||
return markdown
|
||||
|
||||
if page.file.src_path.endswith(".ipynb"):
|
||||
# logger.info("Processing Jupyter notebook: %s", page.file.src_path)
|
||||
markdown = convert_notebook(page.file.abs_src_path)
|
||||
|
||||
# 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)
|
||||
|
||||
# Add file path as an attribute to code blocks that are executable.
|
||||
# This file path is used to associate fixtures with the executable code
|
||||
# which can be used in CI to test the docs without making network requests.
|
||||
markdown = _add_path_to_code_blocks(markdown, page)
|
||||
|
||||
if remove_base64_images:
|
||||
# Remove base64 encoded images from markdown
|
||||
markdown = re.sub(r"!\[.*?\]\(data:image/[^;]+;base64,[^)]+\)", "", markdown)
|
||||
|
||||
return markdown
|
||||
|
||||
|
||||
def on_page_markdown(markdown: str, page: Page, **kwargs: Dict[str, Any]):
|
||||
return _on_page_markdown_with_config(
|
||||
markdown,
|
||||
page,
|
||||
add_api_references=True,
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
|
||||
# redirects
|
||||
|
||||
HTML_TEMPLATE = """
|
||||
<!doctype html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8">
|
||||
<title>Redirecting...</title>
|
||||
<link rel="canonical" href="{url}">
|
||||
<meta name="robots" content="noindex">
|
||||
<script>var anchor=window.location.hash.substr(1);location.href="{url}"+(anchor?"#"+anchor:"")</script>
|
||||
<meta http-equiv="refresh" content="0; url={url}">
|
||||
</head>
|
||||
<body>
|
||||
Redirecting...
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
|
||||
|
||||
def _write_html(site_dir, old_path, new_path):
|
||||
"""Write an HTML file in the site_dir with a meta redirect to the new page"""
|
||||
# Determine all relevant paths
|
||||
old_path_abs = os.path.join(site_dir, old_path)
|
||||
old_dir_abs = os.path.dirname(old_path_abs)
|
||||
|
||||
# Create parent directories if they don't exist
|
||||
if not os.path.exists(old_dir_abs):
|
||||
os.makedirs(old_dir_abs)
|
||||
|
||||
# Write the HTML redirect file in place of the old file
|
||||
content = HTML_TEMPLATE.format(url=new_path)
|
||||
with open(old_path_abs, "w", encoding="utf-8") as f:
|
||||
f.write(content)
|
||||
|
||||
|
||||
def _inject_gtm(html: str) -> str:
|
||||
"""Inject Google Tag Manager code into the HTML.
|
||||
|
||||
Code to inject Google Tag Manager noscript tag immediately after <body>.
|
||||
|
||||
This is done via hooks rather than via a template because the MkDocs material
|
||||
theme does not seem to allow placing the code immediately after the <body> tag
|
||||
without modifying the template files directly.
|
||||
|
||||
Args:
|
||||
html: The HTML content to modify.
|
||||
|
||||
Returns:
|
||||
The modified HTML content with GTM code injected.
|
||||
"""
|
||||
# Code was copied from Google Tag Manager setup instructions.
|
||||
gtm_code = """
|
||||
<!-- Google Tag Manager (noscript) -->
|
||||
<noscript><iframe src="https://www.googletagmanager.com/ns.html?id=GTM-T35S4S46"
|
||||
height="0" width="0" style="display:none;visibility:hidden"></iframe></noscript>
|
||||
<!-- End Google Tag Manager (noscript) -->
|
||||
"""
|
||||
soup = BeautifulSoup(html, "html.parser")
|
||||
body = soup.body
|
||||
if body:
|
||||
# Insert the GTM code as raw HTML at the top of <body>
|
||||
body.insert(0, BeautifulSoup(gtm_code, "html.parser"))
|
||||
return str(soup)
|
||||
else:
|
||||
return html # fallback if no <body> found
|
||||
|
||||
|
||||
def on_post_page(output: str, page: Page, config: MkDocsConfig) -> str:
|
||||
"""Inject Google Tag Manager noscript tag immediately after <body>.
|
||||
|
||||
Args:
|
||||
output: The HTML output of the page.
|
||||
page: The page instance.
|
||||
config: The MkDocs configuration object.
|
||||
|
||||
Returns:
|
||||
modified HTML output with GTM code injected.
|
||||
"""
|
||||
return _inject_gtm(output)
|
||||
|
||||
|
||||
# Create HTML files for redirects after site dir has been built
|
||||
def on_post_build(config):
|
||||
use_directory_urls = config.get("use_directory_urls")
|
||||
for page_old, page_new in REDIRECT_MAP.items():
|
||||
page_old = page_old.replace(".ipynb", ".md")
|
||||
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)
|
||||
@@ -0,0 +1,263 @@
|
||||
"""Preprocess notebooks for CI. Currently adds VCR cassettes and optionally removes pip install cells."""
|
||||
|
||||
import logging
|
||||
import os
|
||||
import json
|
||||
import click
|
||||
import nbformat
|
||||
import re
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
NOTEBOOK_DIRS = ("docs/how-tos","docs/tutorials")
|
||||
DOCS_PATH = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
|
||||
CASSETTES_PATH = os.path.join(DOCS_PATH, "cassettes")
|
||||
|
||||
BLOCKLIST_COMMANDS = (
|
||||
# skip if has WebBaseLoader to avoid caching web pages
|
||||
"WebBaseLoader",
|
||||
# skip if has draw_mermaid_png to avoid generating mermaid images via API
|
||||
"draw_mermaid_png",
|
||||
)
|
||||
|
||||
NOTEBOOKS_NO_CASSETTES = (
|
||||
"docs/how-tos/visualization.ipynb",
|
||||
)
|
||||
|
||||
NOTEBOOKS_NO_EXECUTION = [
|
||||
# this uses a user provided project name for langsmith
|
||||
"docs/tutorials/tnt-llm/tnt-llm.ipynb",
|
||||
# this uses langsmith datasets
|
||||
"docs/tutorials/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb",
|
||||
# this uses browser APIs
|
||||
"docs/tutorials/web-navigation/web_voyager.ipynb",
|
||||
# these RAG guides use an ollama model
|
||||
"docs/tutorials/rag/langgraph_adaptive_rag_local.ipynb",
|
||||
"docs/tutorials/rag/langgraph_crag_local.ipynb",
|
||||
"docs/tutorials/rag/langgraph_self_rag_local.ipynb",
|
||||
# this loads a massive dataset from gcp
|
||||
"docs/tutorials/usaco/usaco.ipynb",
|
||||
# TODO: figure out why autogen notebook is not runnable (they are just hanging. possible due to code execution?)
|
||||
"docs/how-tos/autogen-integration.ipynb",
|
||||
"docs/how-tos/autogen-integration-functional.ipynb",
|
||||
# TODO: need to update these notebooks to make sure they are runnable in CI
|
||||
"docs/tutorials/storm/storm.ipynb", # issues only when running with VCR
|
||||
"docs/tutorials/lats/lats.ipynb", # issues only when running with VCR
|
||||
"docs/tutorials/rag/langgraph_crag.ipynb", # flakiness from tavily
|
||||
"docs/tutorials/rag/langgraph_adaptive_rag.ipynb", # flakiness only when running in GHA
|
||||
"docs/tutorials/rag/langgraph_self_rag.ipynb", # flakiness only when running in GHA
|
||||
"docs/tutorials/rag/langgraph_agentic_rag.ipynb", # flakiness only when running in GHA
|
||||
"docs/how-tos/map-reduce.ipynb", # flakiness from structured output, only when running with VCR
|
||||
"docs/tutorials/tot/tot.ipynb",
|
||||
"docs/how-tos/visualization.ipynb",
|
||||
"docs/how-tos/streaming-specific-nodes.ipynb",
|
||||
"docs/tutorials/llm-compiler/LLMCompiler.ipynb",
|
||||
"docs/tutorials/customer-support/customer-support.ipynb", # relies on openai embeddings, doesn't play well w/ VCR
|
||||
"docs/how-tos/many-tools.ipynb", # relies on openai embeddings, doesn't play well w/ VCR
|
||||
]
|
||||
|
||||
|
||||
def comment_install_cells(notebook: nbformat.NotebookNode) -> nbformat.NotebookNode:
|
||||
for cell in notebook.cells:
|
||||
if cell.cell_type != "code":
|
||||
continue
|
||||
|
||||
if "pip install" in cell.source:
|
||||
# Comment out the lines in cells containing "pip install"
|
||||
cell.source = "\n".join(
|
||||
f"# {line}" if line.strip() else line
|
||||
for line in cell.source.splitlines()
|
||||
)
|
||||
|
||||
return notebook
|
||||
|
||||
|
||||
def is_magic_command(code: str) -> bool:
|
||||
return code.strip().startswith("%") or code.strip().startswith("!")
|
||||
|
||||
|
||||
def is_comment(code: str) -> bool:
|
||||
return code.strip().startswith("#")
|
||||
|
||||
|
||||
def has_blocklisted_command(code: str, metadata: dict) -> bool:
|
||||
if 'hide_from_vcr' in metadata:
|
||||
return True
|
||||
|
||||
code = code.strip()
|
||||
for blocklisted_pattern in BLOCKLIST_COMMANDS:
|
||||
if blocklisted_pattern in code:
|
||||
return True
|
||||
return False
|
||||
|
||||
MERMAID_PATTERN = re.compile(r'display\(Image\((\w+)\.get_graph\(\)\.draw_mermaid_png\(\)\)\)')
|
||||
|
||||
def remove_mermaid(code: str) -> str:
|
||||
return MERMAID_PATTERN.sub('print()', code)
|
||||
|
||||
|
||||
def add_vcr_to_notebook(
|
||||
notebook: nbformat.NotebookNode, cassette_prefix: str
|
||||
) -> nbformat.NotebookNode:
|
||||
"""Inject `with vcr.cassette` into each code cell of the notebook."""
|
||||
|
||||
uses_langsmith = False
|
||||
# Inject VCR context manager into each code cell
|
||||
for idx, cell in enumerate(notebook.cells):
|
||||
if cell.cell_type != "code":
|
||||
continue
|
||||
|
||||
lines = cell.source.splitlines()
|
||||
# remove the special tag for hidden cells
|
||||
lines = [line for line in lines if not line.strip().startswith("# hide-cell")]
|
||||
# skip if empty cell
|
||||
if not lines:
|
||||
continue
|
||||
|
||||
are_magic_lines = [is_magic_command(line) for line in lines]
|
||||
|
||||
# skip if all magic
|
||||
if all(are_magic_lines):
|
||||
continue
|
||||
|
||||
if any(are_magic_lines):
|
||||
raise ValueError(
|
||||
"Cannot process code cells with mixed magic and non-magic code."
|
||||
)
|
||||
|
||||
# skip if just comments
|
||||
if all(is_comment(line) or not line.strip() for line in lines):
|
||||
continue
|
||||
|
||||
if has_blocklisted_command(cell.source, cell.metadata):
|
||||
continue
|
||||
|
||||
cell_id = cell.get("id", idx)
|
||||
cassette_name = f"{cassette_prefix}_{cell_id}.msgpack.zlib"
|
||||
cell.source = f"with custom_vcr.use_cassette('{cassette_name}', filter_headers=['x-api-key', 'authorization'], record_mode='once', serializer='advanced_compressed'):\n" + "\n".join(
|
||||
f" {line}" for line in lines
|
||||
)
|
||||
|
||||
if any("hub.pull" in line or "from langsmith import" in line for line in lines):
|
||||
uses_langsmith = True
|
||||
|
||||
# Add import statement
|
||||
vcr_import_lines = []
|
||||
if uses_langsmith:
|
||||
vcr_import_lines.extend([
|
||||
# patch urllib3 to handle vcr errors, see more here:
|
||||
# https://github.com/langchain-ai/langsmith-sdk/blob/main/python/langsmith/_internal/_patch.py
|
||||
"import sys",
|
||||
f"sys.path.insert(0, '{os.path.join(DOCS_PATH, '_scripts')}')",
|
||||
"import _patch as patch_urllib3",
|
||||
"patch_urllib3.patch_urllib3()",
|
||||
])
|
||||
|
||||
vcr_import_lines.extend([
|
||||
"import nest_asyncio",
|
||||
"nest_asyncio.apply()",
|
||||
"import vcr",
|
||||
"import msgpack",
|
||||
"import base64",
|
||||
"import zlib",
|
||||
"import os",
|
||||
"os.environ.pop(\"LANGCHAIN_TRACING_V2\", None)",
|
||||
"custom_vcr = vcr.VCR()",
|
||||
"",
|
||||
"def compress_data(data, compression_level=9):",
|
||||
" packed = msgpack.packb(data, use_bin_type=True)",
|
||||
" compressed = zlib.compress(packed, level=compression_level)",
|
||||
" return base64.b64encode(compressed).decode('utf-8')",
|
||||
"",
|
||||
"def decompress_data(compressed_string):",
|
||||
" decoded = base64.b64decode(compressed_string)",
|
||||
" decompressed = zlib.decompress(decoded)",
|
||||
" return msgpack.unpackb(decompressed, raw=False)",
|
||||
"",
|
||||
"class AdvancedCompressedSerializer:",
|
||||
" def serialize(self, cassette_dict):",
|
||||
" return compress_data(cassette_dict)",
|
||||
"",
|
||||
" def deserialize(self, cassette_string):",
|
||||
" return decompress_data(cassette_string)",
|
||||
"",
|
||||
"custom_vcr.register_serializer('advanced_compressed', AdvancedCompressedSerializer())",
|
||||
"custom_vcr.serializer = 'advanced_compressed'",
|
||||
])
|
||||
|
||||
import_cell = nbformat.v4.new_code_cell(source="\n".join(vcr_import_lines))
|
||||
import_cell.pop("id", None)
|
||||
notebook.cells.insert(0, import_cell)
|
||||
return notebook
|
||||
|
||||
|
||||
def remove_mermaid_from_notebook(notebook: nbformat.NotebookNode) -> nbformat.NotebookNode:
|
||||
for cell in notebook.cells:
|
||||
if cell.cell_type != "code":
|
||||
continue
|
||||
|
||||
cell.source = remove_mermaid(cell.source)
|
||||
|
||||
# skip the cell entirely if it contains PYPPETEER
|
||||
if "PYPPETEER" in cell.source:
|
||||
cell.source = ""
|
||||
|
||||
return notebook
|
||||
|
||||
|
||||
def process_notebooks(should_comment_install_cells: bool) -> None:
|
||||
for directory in NOTEBOOK_DIRS:
|
||||
for root, _, files in os.walk(directory):
|
||||
for file in files:
|
||||
if not file.endswith(".ipynb") or "ipynb_checkpoints" in root:
|
||||
continue
|
||||
|
||||
notebook_path = os.path.join(root, file)
|
||||
try:
|
||||
notebook = nbformat.read(notebook_path, as_version=4)
|
||||
|
||||
if should_comment_install_cells:
|
||||
notebook = comment_install_cells(notebook)
|
||||
|
||||
base_filename = os.path.splitext(os.path.basename(file))[0]
|
||||
cassette_prefix = os.path.join(CASSETTES_PATH, base_filename)
|
||||
if notebook_path not in NOTEBOOKS_NO_CASSETTES:
|
||||
notebook = add_vcr_to_notebook(
|
||||
notebook, cassette_prefix=cassette_prefix
|
||||
)
|
||||
|
||||
notebook = remove_mermaid_from_notebook(notebook)
|
||||
|
||||
if notebook_path in NOTEBOOKS_NO_EXECUTION:
|
||||
# Add a cell at the beginning to indicate that this notebook should not be executed
|
||||
warning_cell = nbformat.v4.new_markdown_cell(
|
||||
source="**Warning:** This notebook is not meant to be executed automatically."
|
||||
)
|
||||
notebook.cells.insert(0, warning_cell)
|
||||
|
||||
# Add a special tag to the first code cell
|
||||
if notebook.cells and notebook.cells[1].cell_type == "code":
|
||||
notebook.cells[1].metadata["tags"] = notebook.cells[1].metadata.get("tags", []) + ["no_execution"]
|
||||
|
||||
nbformat.write(notebook, notebook_path)
|
||||
logger.info(f"Processed: {notebook_path}")
|
||||
except Exception as e:
|
||||
logger.error(f"Error processing {notebook_path}: {e}")
|
||||
|
||||
with open("notebooks_no_execution.json", "w") as f:
|
||||
json.dump(NOTEBOOKS_NO_EXECUTION, f)
|
||||
|
||||
|
||||
@click.command()
|
||||
@click.option(
|
||||
"--comment-install-cells",
|
||||
is_flag=True,
|
||||
default=False,
|
||||
help="Whether to comment out install cells",
|
||||
)
|
||||
def main(comment_install_cells):
|
||||
process_notebooks(should_comment_install_cells=comment_install_cells)
|
||||
logger.info("All notebooks processed successfully.")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
+138
@@ -0,0 +1,138 @@
|
||||
#!/usr/bin/env python
|
||||
"""Create the third party page for the documentation."""
|
||||
|
||||
import argparse
|
||||
from typing import List
|
||||
from typing import TypedDict
|
||||
|
||||
import yaml
|
||||
|
||||
MARKDOWN = """\
|
||||
[//]: # (This file is automatically generated using a script in docs/_scripts. Do not edit this file directly!)
|
||||
# Community Agents
|
||||
|
||||
If you’re looking for other prebuilt libraries, explore the community-built options
|
||||
below. These libraries can extend LangGraph's functionality in various ways.
|
||||
|
||||
## 📚 Available Libraries
|
||||
|
||||
[//]: # (This file is automatically generated using a script in docs/_scripts. Do not edit this file directly!)
|
||||
{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 (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! 🚀
|
||||
"""
|
||||
|
||||
|
||||
class ResolvedPackage(TypedDict):
|
||||
name: str
|
||||
"""The name of the package."""
|
||||
repo: str
|
||||
"""Repository ID within github. Format is: [orgname]/[repo_name]."""
|
||||
weekly_downloads: int | None
|
||||
"""The weekly download count of the package."""
|
||||
description: str
|
||||
"""A brief description of what the package does."""
|
||||
|
||||
|
||||
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
|
||||
)
|
||||
rows = [
|
||||
"| Name | GitHub URL | Description | Weekly Downloads | Stars |",
|
||||
"| --- | --- | --- | --- | --- |",
|
||||
]
|
||||
for package in sorted_packages:
|
||||
name = f"**{package['name']}**"
|
||||
repo_url = f"[{package['repo']}](https://github.com/{package['repo']})"
|
||||
stars_badge = (
|
||||
f"https://img.shields.io/github/stars/{package['repo']}?style=social"
|
||||
)
|
||||
stars = f""
|
||||
downloads = package["weekly_downloads"] or "-"
|
||||
row = f"| {name} | {repo_url} | {package['description']} | {downloads} | {stars}"
|
||||
rows.append(row)
|
||||
markdown_content = MARKDOWN.format(
|
||||
library_list="\n".join(rows), langgraph_url=langgraph_url
|
||||
)
|
||||
return markdown_content
|
||||
|
||||
|
||||
def main(input_file: str, output_file: str, language: str) -> None:
|
||||
"""Main function to create the third party page.
|
||||
|
||||
Args:
|
||||
input_file: Path to the input YAML file containing resolved package information.
|
||||
output_file: Path to the output file for the third party page.
|
||||
language: The language for which to generate the third party page.
|
||||
"""
|
||||
# Parse the input YAML file
|
||||
with open(input_file, "r") as f:
|
||||
resolved_packages: List[ResolvedPackage] = yaml.safe_load(f)
|
||||
|
||||
markdown_content = generate_markdown(resolved_packages, language)
|
||||
|
||||
# Write the markdown content to the output file
|
||||
with open(output_file, "w", encoding="utf-8") as f:
|
||||
f.write(markdown_content)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser(description="Create the third party page.")
|
||||
parser.add_argument(
|
||||
"input_file",
|
||||
help="Path to the input YAML file containing resolved package information.",
|
||||
)
|
||||
parser.add_argument(
|
||||
"output_file", help="Path to the output file for the third party page."
|
||||
)
|
||||
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, args.language)
|
||||
+142
@@ -0,0 +1,142 @@
|
||||
#!/usr/bin/env python
|
||||
"""Retrieve download count for a list of Python packages from PyPI."""
|
||||
|
||||
import argparse
|
||||
from datetime import datetime
|
||||
from typing import TypedDict
|
||||
import pathlib
|
||||
|
||||
import requests
|
||||
import yaml
|
||||
|
||||
|
||||
class Package(TypedDict):
|
||||
"""A TypedDict representing a package"""
|
||||
|
||||
name: str
|
||||
"""The name of the package."""
|
||||
repo: str
|
||||
"""Repository ID within github. Format is: [orgname]/[repo_name]."""
|
||||
description: str
|
||||
"""A brief description of what the package does."""
|
||||
|
||||
|
||||
class ResolvedPackage(Package):
|
||||
weekly_downloads: int | None
|
||||
|
||||
|
||||
HERE = pathlib.Path(__file__).parent
|
||||
PACKAGES_FILE = HERE / "packages.yml"
|
||||
PACKAGES = yaml.safe_load(PACKAGES_FILE.read_text())['packages']
|
||||
|
||||
|
||||
def _get_weekly_downloads(packages: list[Package], fake: bool) -> list[ResolvedPackage]:
|
||||
"""Retrieve the monthly download count for a list of packages from PyPIStats."""
|
||||
resolved_packages: list[ResolvedPackage] = []
|
||||
|
||||
if fake:
|
||||
# To avoid making network requests during testing, return fake download counts
|
||||
for package in packages:
|
||||
resolved_packages.append(
|
||||
{
|
||||
"name": package["name"],
|
||||
"repo": package["repo"],
|
||||
"weekly_downloads": -12345,
|
||||
"description": package["description"],
|
||||
}
|
||||
)
|
||||
return resolved_packages
|
||||
|
||||
for package in packages:
|
||||
# First check if package exists on PyPI
|
||||
pypi_url = f"https://pypi.org/pypi/{package['name']}/json"
|
||||
try:
|
||||
pypi_response = requests.get(pypi_url)
|
||||
pypi_response.raise_for_status()
|
||||
except requests.exceptions.HTTPError:
|
||||
raise AssertionError(f"Package {package['name']} does not exist on PyPI")
|
||||
|
||||
# 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.
|
||||
"""
|
||||
resolved_packages: list[ResolvedPackage] = _get_weekly_downloads(PACKAGES, fake)
|
||||
|
||||
if not output_file.endswith(".yml"):
|
||||
raise ValueError("Output file must have a .yml extension")
|
||||
|
||||
with open(output_file, "w") as f:
|
||||
f.write("# This file is auto-generated. Do not edit.\n")
|
||||
yaml.dump(resolved_packages, f)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Generate package download information."
|
||||
)
|
||||
parser.add_argument(
|
||||
"output_file",
|
||||
help=(
|
||||
"Path to the output YAML file. Example: python generate_downloads.py "
|
||||
"downloads.yml"
|
||||
),
|
||||
)
|
||||
parser.add_argument(
|
||||
"--fake",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help=(
|
||||
"Generate fake download counts for testing purposes. "
|
||||
"This option will not make any network requests."
|
||||
),
|
||||
)
|
||||
args = parser.parse_args()
|
||||
|
||||
main(args.output_file, args.fake)
|
||||
@@ -0,0 +1,41 @@
|
||||
#A list of third-party packages to surface on the third-party page.
|
||||
packages:
|
||||
- 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."
|
||||
+1
File diff suppressed because one or more lines are too long
+1
@@ -0,0 +1 @@
|
||||
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Reference in New Issue
Block a user