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27 Commits

Author SHA1 Message Date
Chester Curme
d3b05c1753 x 2025-08-11 13:03:57 -04:00
Chester Curme
fb4996ccda x 2025-08-11 13:02:20 -04:00
ccurme
45a067509f fix(core): fix tracing for PDFs in v1 messages (#32434) 2025-08-11 12:18:32 -04:00
Mason Daugherty
23c3fa65d4 feat(docs): enhance ResponseMetadata documentation with provider field usage notes (#32472) 2025-08-11 09:16:16 -04:00
Mason Daugherty
13d67cf37e fix(ollama): reasoning should come before text content (#32476) 2025-08-08 19:34:36 -04:00
Mason Daugherty
7f989d3c3b feat(docs): clarify ToolMessage contentfield usage 2025-08-08 13:02:59 -04:00
Mason Daugherty
b7968c2b7d feat(docs): add link to artifact usage in ToolMessage 2025-08-08 12:51:15 -04:00
Mason Daugherty
2f0c6421a1 Merge branch 'master' into wip-v0.4 2025-08-08 10:21:44 -04:00
Chester Curme
cfe13f673a Merge branch 'master' into wip-v0.4
# Conflicts:
#	libs/core/langchain_core/version.py
#	libs/core/pyproject.toml
#	libs/core/uv.lock
#	libs/partners/openai/tests/integration_tests/chat_models/test_responses_api.py
#	libs/partners/openai/uv.lock
2025-08-08 09:04:57 -04:00
Mason Daugherty
5599c59d4a chore: formatting across codebase (#32456)
To prevent polluting future PRs
2025-08-07 22:09:26 -04:00
Mason Daugherty
11d68a0b9e bump locks 2025-08-07 15:51:36 -04:00
Mason Daugherty
566774a893 Merge branch 'wip-v0.4' of github.com:langchain-ai/langchain into wip-v0.4 2025-08-07 15:50:40 -04:00
Mason Daugherty
255a6d668a feat: allow bypassing CI using PR label 2025-08-07 15:50:15 -04:00
Mason Daugherty
cbf4c0e565 Merge branch 'master' into wip-v0.4 2025-08-07 15:33:12 -04:00
Mason Daugherty
dc66737f03 fix: docs and formatting (#32448) 2025-08-07 15:17:25 -04:00
Christophe Bornet
499dc35cfb chore(core): bump mypy version to 1.17 (#32390)
Co-authored-by: Mason Daugherty <mason@langchain.dev>
2025-08-07 13:26:29 -04:00
Mason Daugherty
42c1159991 feat: add TextAccessor, deprecate .text() as method (#32441)
Adds backward compat for `.text()` on messages while keeping `.text`
access

_The kicker:_

Any previous use of `.text()` will now need a `# type: ignore[operator]`
to silence type checkers. However, it will still behave as expected at
runtime. Deprecating in v0.4.0, to be removed in v2.0.0.
2025-08-07 12:16:31 -04:00
Mason Daugherty
cc6139860c fix: docs typing issues 2025-08-06 23:50:33 -04:00
Mason Daugherty
ae8f58ac6f fix(settings): update Python terminal settings and default interpreter path 2025-08-06 23:37:40 -04:00
Mason Daugherty
346731544b Merge branch 'master' into wip-v0.4 2025-08-06 18:24:10 -04:00
Mason Daugherty
c1b86cc929 feat: minor core work, v1 standard tests & (most of) v1 ollama (#32315)
Resolves #32215

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Nuno Campos <nuno@langchain.dev>
2025-08-06 18:22:02 -04:00
Mason Daugherty
376f70be96 sync wip with master (#32436)
Co-authored-by: Kanav Bansal <13186335+bansalkanav@users.noreply.github.com>
Co-authored-by: Pranav Bhartiya <124018094+pranauww@users.noreply.github.com>
Co-authored-by: Nelson Sproul <nelson.sproul@gmail.com>
Co-authored-by: John Bledsoe <jmbledsoe@gmail.com>
2025-08-06 17:57:05 -04:00
ccurme
ac2de920b1 chore: increment versions for 0.4 branch (#32419) 2025-08-05 15:39:37 -04:00
ccurme
e02eed5489 feat: standard outputs (#32287)
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Nuno Campos <nuno@langchain.dev>
2025-08-05 15:17:32 -04:00
Chester Curme
5414527236 Merge branch 'master' into wip-v0.4 2025-08-04 11:55:14 -04:00
Chester Curme
881c6534a6 Merge branch 'master' into wip-v0.4
# Conflicts:
#	.github/workflows/_integration_test.yml
#	.github/workflows/_release.yml
#	.github/workflows/api_doc_build.yml
#	.github/workflows/people.yml
#	.github/workflows/run_notebooks.yml
#	.github/workflows/scheduled_test.yml
#	SECURITY.md
#	docs/docs/integrations/vectorstores/pgvectorstore.ipynb
#	libs/langchain_v1/langchain/chat_models/base.py
#	libs/langchain_v1/tests/integration_tests/chat_models/test_base.py
#	libs/langchain_v1/tests/unit_tests/chat_models/test_chat_models.py
2025-07-30 13:16:17 -04:00
Mason Daugherty
5e9eb19a83 chore: update branch with changes from master (#32277)
Co-authored-by: Maxime Grenu <69890511+cluster2600@users.noreply.github.com>
Co-authored-by: Claude <claude@anthropic.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: jmaillefaud <jonathan.maillefaud@evooq.ch>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: tanwirahmad <tanwirahmad@users.noreply.github.com>
Co-authored-by: Christophe Bornet <cbornet@hotmail.com>
Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>
Co-authored-by: niceg <79145285+growmuye@users.noreply.github.com>
Co-authored-by: Chaitanya varma <varmac301@gmail.com>
Co-authored-by: dishaprakash <57954147+dishaprakash@users.noreply.github.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Kanav Bansal <13186335+bansalkanav@users.noreply.github.com>
Co-authored-by: Aleksandr Filippov <71711753+alex-feel@users.noreply.github.com>
Co-authored-by: Alex Feel <afilippov@spotware.com>
2025-07-28 10:39:41 -04:00
5059 changed files with 555535 additions and 123350 deletions

View File

@@ -1,15 +0,0 @@
{
"permissions": {
"allow": [
"Bash(uv run:*)",
"Bash(make:*)",
"WebSearch",
"WebFetch(domain:ai.pydantic.dev)",
"WebFetch(domain:openai.github.io)",
"Bash(uv run:*)",
"Bash(python3:*)"
],
"deny": [],
"ask": []
}
}

2
.github/CODEOWNERS vendored
View File

@@ -1,3 +1,3 @@
/.github/ @baskaryan @ccurme @eyurtsev
/libs/core/ @eyurtsev
/libs/partners/ @ccurme @mdrxy
/libs/packages.yml @ccurme

View File

@@ -3,4 +3,8 @@
Hi there! Thank you for even being interested in contributing to LangChain.
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether they involve new features, improved infrastructure, better documentation, or bug fixes.
To learn how to contribute to LangChain, please follow the [contribution guide here](https://docs.langchain.com/oss/python/contributing).
To learn how to contribute to LangChain, please follow the [contribution guide here](https://python.langchain.com/docs/contributing/).
## New features
For new features, please start a new [discussion](https://forum.langchain.com/), where the maintainers will help with scoping out the necessary changes.

View File

@@ -1,7 +1,6 @@
name: "\U0001F41B Bug Report"
description: Report a bug in LangChain. To report a security issue, please instead use the security option below. For questions, please use the LangChain forum.
labels: ["bug"]
type: bug
body:
- type: markdown
attributes:
@@ -14,8 +13,10 @@ body:
if there's another way to solve your problem:
* [LangChain Forum](https://forum.langchain.com/),
* [LangChain documentation with the integrated search](https://docs.langchain.com/oss/python/langchain/overview),
* [API Reference](https://reference.langchain.com/python/),
* [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue),
* [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
* [LangChain how-to guides](https://python.langchain.com/docs/how_to/),
* [API Reference](https://python.langchain.com/api_reference/),
* [LangChain ChatBot](https://chat.langchain.com/)
* [GitHub search](https://github.com/langchain-ai/langchain),
- type: checkboxes
@@ -24,7 +25,7 @@ body:
label: Checked other resources
description: Please confirm and check all the following options.
options:
- label: This is a bug, not a usage question.
- label: This is a bug, not a usage question. For questions, please use the LangChain Forum (https://forum.langchain.com/).
required: true
- label: I added a clear and descriptive title that summarizes this issue.
required: true
@@ -34,8 +35,6 @@ body:
required: true
- label: The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).
required: true
- label: This is not related to the langchain-community package.
required: true
- label: I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
required: true
- label: I posted a self-contained, minimal, reproducible example. A maintainer can copy it and run it AS IS.

View File

@@ -1,9 +1,6 @@
blank_issues_enabled: false
version: 2.1
contact_links:
- name: 📚 Documentation
url: https://github.com/langchain-ai/docs/issues/new?template=langchain.yml
about: Report an issue related to the LangChain documentation
- name: 💬 LangChain Forum
url: https://forum.langchain.com/
about: General community discussions and support
- name: LangChain Forum
url: https://forum.langchain.com/
about: General community discussions, support, and feature requests

View File

@@ -0,0 +1,59 @@
name: Documentation
description: Report an issue related to the LangChain documentation.
title: "docs: <Please write a comprehensive title after the 'docs: ' prefix>"
labels: [documentation]
body:
- type: markdown
attributes:
value: |
Thank you for taking the time to report an issue in the documentation.
Only report issues with documentation here, explain if there are
any missing topics or if you found a mistake in the documentation.
Do **NOT** use this to ask usage questions or reporting issues with your code.
If you have usage questions or need help solving some problem,
please use the [LangChain Forum](https://forum.langchain.com/).
If you're in the wrong place, here are some helpful links to find a better
place to ask your question:
* [LangChain Forum](https://forum.langchain.com/),
* [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue),
* [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
* [LangChain how-to guides](https://python.langchain.com/docs/how_to/),
* [API Reference](https://python.langchain.com/api_reference/),
* [LangChain ChatBot](https://chat.langchain.com/)
* [GitHub search](https://github.com/langchain-ai/langchain),
- type: input
id: url
attributes:
label: URL
description: URL to documentation
validations:
required: false
- type: checkboxes
id: checks
attributes:
label: Checklist
description: Please confirm and check all the following options.
options:
- label: I added a very descriptive title to this issue.
required: true
- label: I included a link to the documentation page I am referring to (if applicable).
required: true
- type: textarea
attributes:
label: "Issue with current documentation:"
description: >
Please make sure to leave a reference to the document/code you're
referring to. Feel free to include names of classes, functions, methods
or concepts you'd like to see documented more.
- type: textarea
attributes:
label: "Idea or request for content:"
description: >
Please describe as clearly as possible what topics you think are missing
from the current documentation.

View File

@@ -1,118 +0,0 @@
name: "✨ Feature Request"
description: Request a new feature or enhancement for LangChain. For questions, please use the LangChain forum.
labels: ["feature request"]
type: feature
body:
- type: markdown
attributes:
value: |
Thank you for taking the time to request a new feature.
Use this to request NEW FEATURES or ENHANCEMENTS in LangChain. For bug reports, please use the bug report template. For usage questions and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
Relevant links to check before filing a feature request to see if your request has already been made or
if there's another way to achieve what you want:
* [LangChain Forum](https://forum.langchain.com/),
* [LangChain documentation with the integrated search](https://docs.langchain.com/oss/python/langchain/overview),
* [API Reference](https://reference.langchain.com/python/),
* [LangChain ChatBot](https://chat.langchain.com/)
* [GitHub search](https://github.com/langchain-ai/langchain),
- type: checkboxes
id: checks
attributes:
label: Checked other resources
description: Please confirm and check all the following options.
options:
- label: This is a feature request, not a bug report or usage question.
required: true
- label: I added a clear and descriptive title that summarizes the feature request.
required: true
- label: I used the GitHub search to find a similar feature request and didn't find it.
required: true
- label: I checked the LangChain documentation and API reference to see if this feature already exists.
required: true
- label: This is not related to the langchain-community package.
required: true
- type: textarea
id: feature-description
validations:
required: true
attributes:
label: Feature Description
description: |
Please provide a clear and concise description of the feature you would like to see added to LangChain.
What specific functionality are you requesting? Be as detailed as possible.
placeholder: |
I would like LangChain to support...
This feature would allow users to...
- type: textarea
id: use-case
validations:
required: true
attributes:
label: Use Case
description: |
Describe the specific use case or problem this feature would solve.
Why do you need this feature? What problem does it solve for you or other users?
placeholder: |
I'm trying to build an application that...
Currently, I have to work around this by...
This feature would help me/users to...
- type: textarea
id: proposed-solution
validations:
required: false
attributes:
label: Proposed Solution
description: |
If you have ideas about how this feature could be implemented, please describe them here.
This is optional but can be helpful for maintainers to understand your vision.
placeholder: |
I think this could be implemented by...
The API could look like...
```python
# Example of how the feature might work
```
- type: textarea
id: alternatives
validations:
required: false
attributes:
label: Alternatives Considered
description: |
Have you considered any alternative solutions or workarounds?
What other approaches have you tried or considered?
placeholder: |
I've tried using...
Alternative approaches I considered:
1. ...
2. ...
But these don't work because...
- type: textarea
id: additional-context
validations:
required: false
attributes:
label: Additional Context
description: |
Add any other context, screenshots, examples, or references that would help explain your feature request.
placeholder: |
Related issues: #...
Similar features in other libraries:
- ...
Additional context or examples:
- ...

View File

@@ -4,7 +4,12 @@ body:
- type: markdown
attributes:
value: |
If you are not a LangChain maintainer, employee, or were not asked directly by a maintainer to create an issue, then please start the conversation on the [LangChain Forum](https://forum.langchain.com/) instead.
Thanks for your interest in LangChain! 🚀
If you are not a LangChain maintainer or were not asked directly by a maintainer to create an issue, then please start the conversation on the [LangChain Forum](https://forum.langchain.com/) instead.
You are a LangChain maintainer if you maintain any of the packages inside of the LangChain repository
or are a regular contributor to LangChain with previous merged pull requests.
- type: checkboxes
id: privileged
attributes:

View File

@@ -1,91 +0,0 @@
name: "📋 Task"
description: Create a task for project management and tracking by LangChain maintainers. If you are not a maintainer, please use other templates or the forum.
labels: ["task"]
type: task
body:
- type: markdown
attributes:
value: |
Thanks for creating a task to help organize LangChain development.
This template is for **maintainer tasks** such as project management, development planning, refactoring, documentation updates, and other organizational work.
If you are not a LangChain maintainer or were not asked directly by a maintainer to create a task, then please start the conversation on the [LangChain Forum](https://forum.langchain.com/) instead or use the appropriate bug report or feature request templates on the previous page.
- type: checkboxes
id: maintainer
attributes:
label: Maintainer task
description: Confirm that you are allowed to create a task here.
options:
- label: I am a LangChain maintainer, or was asked directly by a LangChain maintainer to create a task here.
required: true
- type: textarea
id: task-description
attributes:
label: Task Description
description: |
Provide a clear and detailed description of the task.
What needs to be done? Be specific about the scope and requirements.
placeholder: |
This task involves...
The goal is to...
Specific requirements:
- ...
- ...
validations:
required: true
- type: textarea
id: acceptance-criteria
attributes:
label: Acceptance Criteria
description: |
Define the criteria that must be met for this task to be considered complete.
What are the specific deliverables or outcomes expected?
placeholder: |
This task will be complete when:
- [ ] ...
- [ ] ...
- [ ] ...
validations:
required: true
- type: textarea
id: context
attributes:
label: Context and Background
description: |
Provide any relevant context, background information, or links to related issues/PRs.
Why is this task needed? What problem does it solve?
placeholder: |
Background:
- ...
Related issues/PRs:
- #...
Additional context:
- ...
validations:
required: false
- type: textarea
id: dependencies
attributes:
label: Dependencies
description: |
List any dependencies or blockers for this task.
Are there other tasks, issues, or external factors that need to be completed first?
placeholder: |
This task depends on:
- [ ] Issue #...
- [ ] PR #...
- [ ] External dependency: ...
Blocked by:
- ...
validations:
required: false

View File

@@ -1,5 +1,3 @@
(Replace this entire block of text)
Thank you for contributing to LangChain! Follow these steps to mark your pull request as ready for review. **If any of these steps are not completed, your PR will not be considered for review.**
- [ ] **PR title**: Follows the format: {TYPE}({SCOPE}): {DESCRIPTION}
@@ -10,19 +8,25 @@ Thank you for contributing to LangChain! Follow these steps to mark your pull re
- Allowed `{TYPE}` values:
- feat, fix, docs, style, refactor, perf, test, build, ci, chore, revert, release
- Allowed `{SCOPE}` values (optional):
- core, cli, langchain, standard-tests, text-splitters, docs, anthropic, chroma, deepseek, exa, fireworks, groq, huggingface, mistralai, nomic, ollama, openai, perplexity, prompty, qdrant, xai, infra
- core, cli, langchain, standard-tests, docs, anthropic, chroma, deepseek, exa, fireworks, groq, huggingface, mistralai, nomic, ollama, openai, perplexity, prompty, qdrant, xai
- Note: the `{DESCRIPTION}` must not start with an uppercase letter.
- Once you've written the title, please delete this checklist item; do not include it in the PR.
- [ ] **PR message**: ***Delete this entire checklist*** and replace with
- **Description:** a description of the change. Include a [closing keyword](https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword) if applicable to a relevant issue.
- **Issue:** the issue # it fixes, if applicable (e.g. Fixes #123)
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a mention, we'll gladly shout you out!
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. **We will not consider a PR unless these three are passing in CI.** See [contribution guidelines](https://docs.langchain.com/oss/python/contributing) for more.
- [ ] **Add tests and docs**: If you're adding a new integration, you must include:
1. A test for the integration, preferably unit tests that do not rely on network access,
2. An example notebook showing its use. It lives in `docs/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. **We will not consider a PR unless these three are passing in CI.** See [contribution guidelines](https://python.langchain.com/docs/contributing/) for more.
Additional guidelines:
- Most PRs should not touch more than one package.
- Please do not add dependencies to `pyproject.toml` files (even optional ones) unless they are **required** for unit tests. Likewise, please do not update the `uv.lock` files unless you are adding a required dependency.
- Changes should be backwards compatible.
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to `pyproject.toml` files (even optional ones) unless they are **required** for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.

7
.github/actions/people/Dockerfile vendored Normal file
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@@ -0,0 +1,7 @@
FROM python:3.9
RUN pip install httpx PyGithub "pydantic==2.0.2" pydantic-settings "pyyaml>=5.3.1,<6.0.0"
COPY ./app /app
CMD ["python", "/app/main.py"]

11
.github/actions/people/action.yml vendored Normal file
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@@ -0,0 +1,11 @@
# Adapted from https://github.com/tiangolo/fastapi/blob/master/.github/actions/people/action.yml
name: "Generate LangChain People"
description: "Generate the data for the LangChain People page"
author: "Jacob Lee <jacob@langchain.dev>"
inputs:
token:
description: "User token, to read the GitHub API. Can be passed in using {{ secrets.LANGCHAIN_PEOPLE_GITHUB_TOKEN }}"
required: true
runs:
using: "docker"
image: "Dockerfile"

646
.github/actions/people/app/main.py vendored Normal file
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@@ -0,0 +1,646 @@
# Adapted from https://github.com/tiangolo/fastapi/blob/master/.github/actions/people/app/main.py
import logging
import subprocess
import sys
from collections import Counter
from datetime import datetime, timedelta, timezone
from pathlib import Path
from typing import Any, Container, Dict, List, Set, Union
import httpx
import yaml
from github import Github
from pydantic import BaseModel, SecretStr
from pydantic_settings import BaseSettings
github_graphql_url = "https://api.github.com/graphql"
questions_category_id = "DIC_kwDOIPDwls4CS6Ve"
# discussions_query = """
# query Q($after: String, $category_id: ID) {
# repository(name: "langchain", owner: "langchain-ai") {
# discussions(first: 100, after: $after, categoryId: $category_id) {
# edges {
# cursor
# node {
# number
# author {
# login
# avatarUrl
# url
# }
# title
# createdAt
# comments(first: 100) {
# nodes {
# createdAt
# author {
# login
# avatarUrl
# url
# }
# isAnswer
# replies(first: 10) {
# nodes {
# createdAt
# author {
# login
# avatarUrl
# url
# }
# }
# }
# }
# }
# }
# }
# }
# }
# }
# """
# issues_query = """
# query Q($after: String) {
# repository(name: "langchain", owner: "langchain-ai") {
# issues(first: 100, after: $after) {
# edges {
# cursor
# node {
# number
# author {
# login
# avatarUrl
# url
# }
# title
# createdAt
# state
# comments(first: 100) {
# nodes {
# createdAt
# author {
# login
# avatarUrl
# url
# }
# }
# }
# }
# }
# }
# }
# }
# """
prs_query = """
query Q($after: String) {
repository(name: "langchain", owner: "langchain-ai") {
pullRequests(first: 100, after: $after, states: MERGED) {
edges {
cursor
node {
changedFiles
additions
deletions
number
labels(first: 100) {
nodes {
name
}
}
author {
login
avatarUrl
url
... on User {
twitterUsername
}
}
title
createdAt
state
reviews(first:100) {
nodes {
author {
login
avatarUrl
url
... on User {
twitterUsername
}
}
state
}
}
}
}
}
}
}
"""
class Author(BaseModel):
login: str
avatarUrl: str
url: str
twitterUsername: Union[str, None] = None
# Issues and Discussions
class CommentsNode(BaseModel):
createdAt: datetime
author: Union[Author, None] = None
class Replies(BaseModel):
nodes: List[CommentsNode]
class DiscussionsCommentsNode(CommentsNode):
replies: Replies
class Comments(BaseModel):
nodes: List[CommentsNode]
class DiscussionsComments(BaseModel):
nodes: List[DiscussionsCommentsNode]
class IssuesNode(BaseModel):
number: int
author: Union[Author, None] = None
title: str
createdAt: datetime
state: str
comments: Comments
class DiscussionsNode(BaseModel):
number: int
author: Union[Author, None] = None
title: str
createdAt: datetime
comments: DiscussionsComments
class IssuesEdge(BaseModel):
cursor: str
node: IssuesNode
class DiscussionsEdge(BaseModel):
cursor: str
node: DiscussionsNode
class Issues(BaseModel):
edges: List[IssuesEdge]
class Discussions(BaseModel):
edges: List[DiscussionsEdge]
class IssuesRepository(BaseModel):
issues: Issues
class DiscussionsRepository(BaseModel):
discussions: Discussions
class IssuesResponseData(BaseModel):
repository: IssuesRepository
class DiscussionsResponseData(BaseModel):
repository: DiscussionsRepository
class IssuesResponse(BaseModel):
data: IssuesResponseData
class DiscussionsResponse(BaseModel):
data: DiscussionsResponseData
# PRs
class LabelNode(BaseModel):
name: str
class Labels(BaseModel):
nodes: List[LabelNode]
class ReviewNode(BaseModel):
author: Union[Author, None] = None
state: str
class Reviews(BaseModel):
nodes: List[ReviewNode]
class PullRequestNode(BaseModel):
number: int
labels: Labels
author: Union[Author, None] = None
changedFiles: int
additions: int
deletions: int
title: str
createdAt: datetime
state: str
reviews: Reviews
# comments: Comments
class PullRequestEdge(BaseModel):
cursor: str
node: PullRequestNode
class PullRequests(BaseModel):
edges: List[PullRequestEdge]
class PRsRepository(BaseModel):
pullRequests: PullRequests
class PRsResponseData(BaseModel):
repository: PRsRepository
class PRsResponse(BaseModel):
data: PRsResponseData
class Settings(BaseSettings):
input_token: SecretStr
github_repository: str
httpx_timeout: int = 30
def get_graphql_response(
*,
settings: Settings,
query: str,
after: Union[str, None] = None,
category_id: Union[str, None] = None,
) -> Dict[str, Any]:
headers = {"Authorization": f"token {settings.input_token.get_secret_value()}"}
# category_id is only used by one query, but GraphQL allows unused variables, so
# keep it here for simplicity
variables = {"after": after, "category_id": category_id}
response = httpx.post(
github_graphql_url,
headers=headers,
timeout=settings.httpx_timeout,
json={"query": query, "variables": variables, "operationName": "Q"},
)
if response.status_code != 200:
logging.error(
f"Response was not 200, after: {after}, category_id: {category_id}"
)
logging.error(response.text)
raise RuntimeError(response.text)
data = response.json()
if "errors" in data:
logging.error(f"Errors in response, after: {after}, category_id: {category_id}")
logging.error(data["errors"])
logging.error(response.text)
raise RuntimeError(response.text)
return data
# def get_graphql_issue_edges(*, settings: Settings, after: Union[str, None] = None):
# data = get_graphql_response(settings=settings, query=issues_query, after=after)
# graphql_response = IssuesResponse.model_validate(data)
# return graphql_response.data.repository.issues.edges
# def get_graphql_question_discussion_edges(
# *,
# settings: Settings,
# after: Union[str, None] = None,
# ):
# data = get_graphql_response(
# settings=settings,
# query=discussions_query,
# after=after,
# category_id=questions_category_id,
# )
# graphql_response = DiscussionsResponse.model_validate(data)
# return graphql_response.data.repository.discussions.edges
def get_graphql_pr_edges(*, settings: Settings, after: Union[str, None] = None):
if after is None:
print("Querying PRs...")
else:
print(f"Querying PRs with cursor {after}...")
data = get_graphql_response(settings=settings, query=prs_query, after=after)
graphql_response = PRsResponse.model_validate(data)
return graphql_response.data.repository.pullRequests.edges
# def get_issues_experts(settings: Settings):
# issue_nodes: List[IssuesNode] = []
# issue_edges = get_graphql_issue_edges(settings=settings)
# while issue_edges:
# for edge in issue_edges:
# issue_nodes.append(edge.node)
# last_edge = issue_edges[-1]
# issue_edges = get_graphql_issue_edges(settings=settings, after=last_edge.cursor)
# commentors = Counter()
# last_month_commentors = Counter()
# authors: Dict[str, Author] = {}
# now = datetime.now(tz=timezone.utc)
# one_month_ago = now - timedelta(days=30)
# for issue in issue_nodes:
# issue_author_name = None
# if issue.author:
# authors[issue.author.login] = issue.author
# issue_author_name = issue.author.login
# issue_commentors = set()
# for comment in issue.comments.nodes:
# if comment.author:
# authors[comment.author.login] = comment.author
# if comment.author.login != issue_author_name:
# issue_commentors.add(comment.author.login)
# for author_name in issue_commentors:
# commentors[author_name] += 1
# if issue.createdAt > one_month_ago:
# last_month_commentors[author_name] += 1
# return commentors, last_month_commentors, authors
# def get_discussions_experts(settings: Settings):
# discussion_nodes: List[DiscussionsNode] = []
# discussion_edges = get_graphql_question_discussion_edges(settings=settings)
# while discussion_edges:
# for discussion_edge in discussion_edges:
# discussion_nodes.append(discussion_edge.node)
# last_edge = discussion_edges[-1]
# discussion_edges = get_graphql_question_discussion_edges(
# settings=settings, after=last_edge.cursor
# )
# commentors = Counter()
# last_month_commentors = Counter()
# authors: Dict[str, Author] = {}
# now = datetime.now(tz=timezone.utc)
# one_month_ago = now - timedelta(days=30)
# for discussion in discussion_nodes:
# discussion_author_name = None
# if discussion.author:
# authors[discussion.author.login] = discussion.author
# discussion_author_name = discussion.author.login
# discussion_commentors = set()
# for comment in discussion.comments.nodes:
# if comment.author:
# authors[comment.author.login] = comment.author
# if comment.author.login != discussion_author_name:
# discussion_commentors.add(comment.author.login)
# for reply in comment.replies.nodes:
# if reply.author:
# authors[reply.author.login] = reply.author
# if reply.author.login != discussion_author_name:
# discussion_commentors.add(reply.author.login)
# for author_name in discussion_commentors:
# commentors[author_name] += 1
# if discussion.createdAt > one_month_ago:
# last_month_commentors[author_name] += 1
# return commentors, last_month_commentors, authors
# def get_experts(settings: Settings):
# (
# discussions_commentors,
# discussions_last_month_commentors,
# discussions_authors,
# ) = get_discussions_experts(settings=settings)
# commentors = discussions_commentors
# last_month_commentors = discussions_last_month_commentors
# authors = {**discussions_authors}
# return commentors, last_month_commentors, authors
def _logistic(x, k):
return x / (x + k)
def get_contributors(settings: Settings):
pr_nodes: List[PullRequestNode] = []
pr_edges = get_graphql_pr_edges(settings=settings)
while pr_edges:
for edge in pr_edges:
pr_nodes.append(edge.node)
last_edge = pr_edges[-1]
pr_edges = get_graphql_pr_edges(settings=settings, after=last_edge.cursor)
contributors = Counter()
contributor_scores = Counter()
recent_contributor_scores = Counter()
reviewers = Counter()
authors: Dict[str, Author] = {}
for pr in pr_nodes:
pr_reviewers: Set[str] = set()
for review in pr.reviews.nodes:
if review.author:
authors[review.author.login] = review.author
pr_reviewers.add(review.author.login)
for reviewer in pr_reviewers:
reviewers[reviewer] += 1
if pr.author:
authors[pr.author.login] = pr.author
contributors[pr.author.login] += 1
files_changed = pr.changedFiles
lines_changed = pr.additions + pr.deletions
score = _logistic(files_changed, 20) + _logistic(lines_changed, 100)
contributor_scores[pr.author.login] += score
three_months_ago = datetime.now(timezone.utc) - timedelta(days=3 * 30)
if pr.createdAt > three_months_ago:
recent_contributor_scores[pr.author.login] += score
return (
contributors,
contributor_scores,
recent_contributor_scores,
reviewers,
authors,
)
def get_top_users(
*,
counter: Counter,
min_count: int,
authors: Dict[str, Author],
skip_users: Container[str],
):
users = []
for commentor, count in counter.most_common():
if commentor in skip_users:
continue
if count >= min_count:
author = authors[commentor]
users.append(
{
"login": commentor,
"count": count,
"avatarUrl": author.avatarUrl,
"twitterUsername": author.twitterUsername,
"url": author.url,
}
)
return users
if __name__ == "__main__":
logging.basicConfig(level=logging.INFO)
settings = Settings()
logging.info(f"Using config: {settings.model_dump_json()}")
g = Github(settings.input_token.get_secret_value())
repo = g.get_repo(settings.github_repository)
# question_commentors, question_last_month_commentors, question_authors = get_experts(
# settings=settings
# )
(
contributors,
contributor_scores,
recent_contributor_scores,
reviewers,
pr_authors,
) = get_contributors(settings=settings)
# authors = {**question_authors, **pr_authors}
authors = {**pr_authors}
maintainers_logins = {
"hwchase17",
"agola11",
"baskaryan",
"hinthornw",
"nfcampos",
"efriis",
"eyurtsev",
"rlancemartin",
"ccurme",
"vbarda",
}
hidden_logins = {
"dev2049",
"vowelparrot",
"obi1kenobi",
"langchain-infra",
"jacoblee93",
"isahers1",
"dqbd",
"bracesproul",
"akira",
}
bot_names = {"dosubot", "github-actions", "CodiumAI-Agent"}
maintainers = []
for login in maintainers_logins:
user = authors[login]
maintainers.append(
{
"login": login,
"count": contributors[login], # + question_commentors[login],
"avatarUrl": user.avatarUrl,
"twitterUsername": user.twitterUsername,
"url": user.url,
}
)
# min_count_expert = 10
# min_count_last_month = 3
min_score_contributor = 1
min_count_reviewer = 5
skip_users = maintainers_logins | bot_names | hidden_logins
# experts = get_top_users(
# counter=question_commentors,
# min_count=min_count_expert,
# authors=authors,
# skip_users=skip_users,
# )
# last_month_active = get_top_users(
# counter=question_last_month_commentors,
# min_count=min_count_last_month,
# authors=authors,
# skip_users=skip_users,
# )
top_recent_contributors = get_top_users(
counter=recent_contributor_scores,
min_count=min_score_contributor,
authors=authors,
skip_users=skip_users,
)
top_contributors = get_top_users(
counter=contributor_scores,
min_count=min_score_contributor,
authors=authors,
skip_users=skip_users,
)
top_reviewers = get_top_users(
counter=reviewers,
min_count=min_count_reviewer,
authors=authors,
skip_users=skip_users,
)
people = {
"maintainers": maintainers,
# "experts": experts,
# "last_month_active": last_month_active,
"top_recent_contributors": top_recent_contributors,
"top_contributors": top_contributors,
"top_reviewers": top_reviewers,
}
people_path = Path("./docs/data/people.yml")
people_old_content = people_path.read_text(encoding="utf-8")
new_people_content = yaml.dump(
people, sort_keys=False, width=200, allow_unicode=True
)
if people_old_content == new_people_content:
logging.info("The LangChain People data hasn't changed, finishing.")
sys.exit(0)
people_path.write_text(new_people_content, encoding="utf-8")
logging.info("Setting up GitHub Actions git user")
subprocess.run(["git", "config", "user.name", "github-actions"], check=True)
subprocess.run(
["git", "config", "user.email", "github-actions@github.com"], check=True
)
branch_name = "langchain/langchain-people"
logging.info(f"Creating a new branch {branch_name}")
subprocess.run(["git", "checkout", "-B", branch_name], check=True)
logging.info("Adding updated file")
subprocess.run(["git", "add", str(people_path)], check=True)
logging.info("Committing updated file")
message = "👥 Update LangChain people data"
result = subprocess.run(["git", "commit", "-m", message], check=True)
logging.info("Pushing branch")
subprocess.run(["git", "push", "origin", branch_name, "-f"], check=True)
logging.info("Creating PR")
pr = repo.create_pull(title=message, body=message, base="master", head=branch_name)
logging.info(f"Created PR: {pr.number}")
logging.info("Finished")

View File

@@ -1,24 +1,12 @@
# Helper to set up Python and uv with caching
# TODO: https://docs.astral.sh/uv/guides/integration/github/#caching
name: uv-install
description: Set up Python and uv with caching
description: Set up Python and uv
inputs:
python-version:
description: Python version, supporting MAJOR.MINOR only
required: true
enable-cache:
description: Enable caching for uv dependencies
required: false
default: "true"
cache-suffix:
description: Custom cache key suffix for cache invalidation
required: false
default: ""
working-directory:
description: Working directory for cache glob scoping
required: false
default: "**"
env:
UV_VERSION: "0.5.25"
@@ -27,13 +15,7 @@ runs:
using: composite
steps:
- name: Install uv and set the python version
uses: astral-sh/setup-uv@v6
uses: astral-sh/setup-uv@v5
with:
version: ${{ env.UV_VERSION }}
python-version: ${{ inputs.python-version }}
enable-cache: ${{ inputs.enable-cache }}
cache-dependency-glob: |
${{ inputs.working-directory }}/pyproject.toml
${{ inputs.working-directory }}/uv.lock
${{ inputs.working-directory }}/requirements*.txt
cache-suffix: ${{ inputs.cache-suffix }}

View File

@@ -26,7 +26,7 @@ def get_user(user_id: str, verbose: bool = False) -> User:
- Check if the function/class is exported in `__init__.py`
- Look for existing usage patterns in tests and examples
- Use keyword-only arguments for new parameters: `*, new_param: str = "default"`
- Mark experimental features clearly with docstring admonitions (using MkDocs Material, like `!!! warning`)
- Mark experimental features clearly with docstring warnings (using reStructuredText, like `.. warning::`)
🧠 *Ask yourself:* "Would this change break someone's code if they used it last week?"
@@ -130,7 +130,7 @@ def load_config(path: str) -> dict:
### 5. Documentation Standards
**Use Google-style docstrings with Args and Returns sections for all public functions.**
**Use Google-style docstrings with Args section for all public functions.**
**Insufficient Documentation:**
@@ -149,7 +149,7 @@ def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
Args:
to: The email address of the recipient.
msg: The message body to send.
priority: Email priority level.
priority: Email priority level (``'low'``, ``'normal'``, ``'high'``).
Returns:
True if email was sent successfully, False otherwise.
@@ -166,6 +166,7 @@ def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
- Focus on "why" rather than "what" in descriptions
- Document all parameters, return values, and exceptions
- Keep descriptions concise but clear
- Use reStructuredText for docstrings to enable rich formatting
📌 *Tip:* Keep descriptions concise but clear. Only document return values if non-obvious.
@@ -203,14 +204,7 @@ class DataProcessor:
self.email = email_client
def process(self, data: List[dict]) -> ProcessingResult:
"""Process and store data with notifications.
Args:
data: List of data items to process.
Returns:
ProcessingResult with details of the operation.
"""
"""Process and store data with notifications."""
validated = self._validate_data(data)
result = self.db.save(validated)
self._notify_completion(result)
@@ -297,15 +291,16 @@ def search_database(query: str) -> str:
**Use Conventional Commits format for PR titles:**
- `feat(core): add multi-tenant support`
- `!fix(cli): resolve flag parsing error` (breaking change uses exclamation mark)
- `fix(cli): resolve flag parsing error`
- `docs: update API usage examples`
- `docs(openai): update API usage examples`
## Framework-Specific Guidelines
- Follow the existing patterns in `langchain_core` for base abstractions
- Follow the existing patterns in `langchain-core` for base abstractions
- Use `langchain_core.callbacks` for execution tracking
- Implement proper streaming support where applicable
- Avoid deprecated components
- Avoid deprecated components like legacy `LLMChain`
### Partner Integrations

View File

@@ -1,84 +0,0 @@
# Label PRs (config)
# Automatically applies labels based on changed files and branch patterns
# Core packages
core:
- changed-files:
- any-glob-to-any-file:
- "libs/core/**/*"
langchain:
- changed-files:
- any-glob-to-any-file:
- "libs/langchain/**/*"
- "libs/langchain_v1/**/*"
v1:
- changed-files:
- any-glob-to-any-file:
- "libs/langchain_v1/**/*"
cli:
- changed-files:
- any-glob-to-any-file:
- "libs/cli/**/*"
standard-tests:
- changed-files:
- any-glob-to-any-file:
- "libs/standard-tests/**/*"
text-splitters:
- changed-files:
- any-glob-to-any-file:
- "libs/text-splitters/**/*"
# Partner integrations
integration:
- changed-files:
- any-glob-to-any-file:
- "libs/partners/**/*"
# Infrastructure and DevOps
infra:
- changed-files:
- any-glob-to-any-file:
- ".github/**/*"
- "Makefile"
- ".pre-commit-config.yaml"
- "scripts/**/*"
- "docker/**/*"
- "Dockerfile*"
github_actions:
- changed-files:
- any-glob-to-any-file:
- ".github/workflows/**/*"
- ".github/actions/**/*"
dependencies:
- changed-files:
- any-glob-to-any-file:
- "**/pyproject.toml"
- "uv.lock"
- "**/requirements*.txt"
- "**/poetry.lock"
# Documentation
documentation:
- changed-files:
- any-glob-to-any-file:
- "**/*.md"
- "**/*.rst"
- "**/README*"
# Security related changes
security:
- changed-files:
- any-glob-to-any-file:
- "**/*security*"
- "**/*auth*"
- "**/*credential*"
- "**/*secret*"
- "**/*token*"
- ".github/workflows/security*"

View File

@@ -1,41 +0,0 @@
# PR title labeler config
#
# Labels PRs based on conventional commit patterns in titles
#
# Format: type(scope): description or type!: description (breaking)
add-missing-labels: true
clear-prexisting: false
include-commits: false
include-title: true
label-for-breaking-changes: breaking
label-mapping:
documentation: ["docs"]
feature: ["feat"]
fix: ["fix"]
infra: ["build", "ci", "chore"]
integration:
[
"anthropic",
"chroma",
"deepseek",
"exa",
"fireworks",
"groq",
"huggingface",
"mistralai",
"nomic",
"ollama",
"openai",
"perplexity",
"prompty",
"qdrant",
"xai",
]
linting: ["style"]
performance: ["perf"]
refactor: ["refactor"]
release: ["release"]
revert: ["revert"]
tests: ["test"]

View File

@@ -1,18 +1,3 @@
"""Analyze git diffs to determine which directories need to be tested.
Intelligently determines which LangChain packages and directories need to be tested,
linted, or built based on the changes. Handles dependency relationships between
packages, maps file changes to appropriate CI job configurations, and outputs JSON
configurations for GitHub Actions.
- Maps changed files to affected package directories (libs/core, libs/partners/*, etc.)
- Builds dependency graph to include dependent packages when core components change
- Generates test matrix configurations with appropriate Python versions
- Handles special cases for Pydantic version testing and performance benchmarks
Used as part of the check_diffs workflow.
"""
import glob
import json
import os
@@ -32,7 +17,7 @@ LANGCHAIN_DIRS = [
"libs/langchain_v1",
]
# When set to True, we are ignoring core dependents
# when set to True, we are ignoring core dependents
# in order to be able to get CI to pass for each individual
# package that depends on core
# e.g. if you touch core, we don't then add textsplitters/etc to CI
@@ -50,6 +35,10 @@ IGNORED_PARTNERS = [
"prompty",
]
PY_312_MAX_PACKAGES = [
"libs/partners/chroma", # https://github.com/chroma-core/chroma/issues/4382
]
def all_package_dirs() -> Set[str]:
return {
@@ -60,9 +49,9 @@ def all_package_dirs() -> Set[str]:
def dependents_graph() -> dict:
"""Construct a mapping of package -> dependents
Done such that we can run tests on all dependents of a package when a change is made.
"""
Construct a mapping of package -> dependents, such that we can
run tests on all dependents of a package when a change is made.
"""
dependents = defaultdict(set)
@@ -132,21 +121,23 @@ def _get_configs_for_single_dir(job: str, dir_: str) -> List[Dict[str, str]]:
if job == "codspeed":
py_versions = ["3.12"] # 3.13 is not yet supported
elif dir_ == "libs/core":
py_versions = ["3.10", "3.11", "3.12", "3.13"]
py_versions = ["3.9", "3.10", "3.11", "3.12", "3.13"]
# custom logic for specific directories
elif dir_ == "libs/partners/milvus":
# milvus doesn't allow 3.12 because they declare deps in funny way
py_versions = ["3.9", "3.11"]
elif dir_ in PY_312_MAX_PACKAGES:
py_versions = ["3.9", "3.12"]
elif dir_ == "libs/langchain" and job == "extended-tests":
py_versions = ["3.10", "3.13"]
elif dir_ == "libs/langchain_v1":
py_versions = ["3.10", "3.13"]
elif dir_ in {"libs/cli"}:
py_versions = ["3.10", "3.13"]
py_versions = ["3.9", "3.13"]
elif dir_ == ".":
# unable to install with 3.13 because tokenizers doesn't support 3.13 yet
py_versions = ["3.10", "3.12"]
py_versions = ["3.9", "3.12"]
else:
py_versions = ["3.10", "3.13"]
py_versions = ["3.9", "3.13"]
return [{"working-directory": dir_, "python-version": py_v} for py_v in py_versions]
@@ -259,9 +250,10 @@ if __name__ == "__main__":
):
# add all LANGCHAIN_DIRS for infra changes
dirs_to_run["extended-test"].update(LANGCHAIN_DIRS)
dirs_to_run["lint"].add(".")
if file.startswith("libs/core"):
dirs_to_run["codspeed"].add("libs/core")
dirs_to_run["codspeed"].add(f"libs/core")
if any(file.startswith(dir_) for dir_ in LANGCHAIN_DIRS):
# add that dir and all dirs after in LANGCHAIN_DIRS
# for extended testing
@@ -302,21 +294,19 @@ if __name__ == "__main__":
dirs_to_run["test"].add(f"libs/partners/{partner_dir}")
dirs_to_run["codspeed"].add(f"libs/partners/{partner_dir}")
# Skip if the directory was deleted or is just a tombstone readme
elif file == "libs/packages.yml":
continue
elif file.startswith("libs/"):
# Check if this is a root-level file in libs/ (e.g., libs/README.md)
file_parts = file.split("/")
if len(file_parts) == 2:
# Root-level file in libs/, skip it (no tests needed)
continue
raise ValueError(
f"Unknown lib: {file}. check_diff.py likely needs "
"an update for this new library!"
)
elif file in [
elif file.startswith("docs/") or file in [
"pyproject.toml",
"uv.lock",
]: # root uv files
]: # docs or root uv files
docs_edited = True
dirs_to_run["lint"].add(".")
dependents = dependents_graph()
@@ -334,6 +324,9 @@ if __name__ == "__main__":
"codspeed",
]
}
map_job_to_configs["test-doc-imports"] = (
[{"python-version": "3.12"}] if docs_edited else []
)
for key, value in map_job_to_configs.items():
json_output = json.dumps(value)

View File

@@ -1,5 +1,3 @@
"""Check that no dependencies allow prereleases unless we're releasing a prerelease."""
import sys
import tomllib
@@ -8,14 +6,15 @@ if __name__ == "__main__":
# Get the TOML file path from the command line argument
toml_file = sys.argv[1]
# read toml file
with open(toml_file, "rb") as file:
toml_data = tomllib.load(file)
# See if we're releasing an rc or dev version
# see if we're releasing an rc
version = toml_data["project"]["version"]
releasing_rc = "rc" in version or "dev" in version
# If not, iterate through dependencies and make sure none allow prereleases
# if not, iterate through dependencies and make sure none allow prereleases
if not releasing_rc:
dependencies = toml_data["project"]["dependencies"]
for dep_version in dependencies:

View File

@@ -1,5 +1,3 @@
"""Get minimum versions of dependencies from a pyproject.toml file."""
import sys
from collections import defaultdict
from typing import Optional
@@ -7,7 +5,7 @@ from typing import Optional
if sys.version_info >= (3, 11):
import tomllib
else:
# For Python 3.10 and below, which doesnt have stdlib tomllib
# for python 3.10 and below, which doesnt have stdlib tomllib
import tomli as tomllib
import re
@@ -36,13 +34,14 @@ SKIP_IF_PULL_REQUEST = [
def get_pypi_versions(package_name: str) -> List[str]:
"""Fetch all available versions for a package from PyPI.
"""
Fetch all available versions for a package from PyPI.
Args:
package_name: Name of the package
package_name (str): Name of the package
Returns:
List of all available versions
List[str]: List of all available versions
Raises:
requests.exceptions.RequestException: If PyPI API request fails
@@ -55,23 +54,24 @@ def get_pypi_versions(package_name: str) -> List[str]:
def get_minimum_version(package_name: str, spec_string: str) -> Optional[str]:
"""Find the minimum published version that satisfies the given constraints.
"""
Find the minimum published version that satisfies the given constraints.
Args:
package_name: Name of the package
spec_string: Version specification string (e.g., ">=0.2.43,<0.4.0,!=0.3.0")
package_name (str): Name of the package
spec_string (str): Version specification string (e.g., ">=0.2.43,<0.4.0,!=0.3.0")
Returns:
Minimum compatible version or None if no compatible version found
Optional[str]: Minimum compatible version or None if no compatible version found
"""
# Rewrite occurrences of ^0.0.z to 0.0.z (can be anywhere in constraint string)
# rewrite occurrences of ^0.0.z to 0.0.z (can be anywhere in constraint string)
spec_string = re.sub(r"\^0\.0\.(\d+)", r"0.0.\1", spec_string)
# Rewrite occurrences of ^0.y.z to >=0.y.z,<0.y+1 (can be anywhere in constraint string)
# rewrite occurrences of ^0.y.z to >=0.y.z,<0.y+1 (can be anywhere in constraint string)
for y in range(1, 10):
spec_string = re.sub(
rf"\^0\.{y}\.(\d+)", rf">=0.{y}.\1,<0.{y + 1}", spec_string
)
# Rewrite occurrences of ^x.y.z to >=x.y.z,<x+1.0.0 (can be anywhere in constraint string)
# rewrite occurrences of ^x.y.z to >=x.y.z,<x+1.0.0 (can be anywhere in constraint string)
for x in range(1, 10):
spec_string = re.sub(
rf"\^{x}\.(\d+)\.(\d+)", rf">={x}.\1.\2,<{x + 1}", spec_string
@@ -154,25 +154,22 @@ def get_min_version_from_toml(
def check_python_version(version_string, constraint_string):
"""Check if the given Python version matches the given constraints.
"""
Check if the given Python version matches the given constraints.
Args:
version_string: A string representing the Python version (e.g. "3.8.5").
constraint_string: A string representing the package's Python version
constraints (e.g. ">=3.6, <4.0").
Returns:
True if the version matches the constraints
:param version_string: A string representing the Python version (e.g. "3.8.5").
:param constraint_string: A string representing the package's Python version constraints (e.g. ">=3.6, <4.0").
:return: True if the version matches the constraints, False otherwise.
"""
# Rewrite occurrences of ^0.0.z to 0.0.z (can be anywhere in constraint string)
# rewrite occurrences of ^0.0.z to 0.0.z (can be anywhere in constraint string)
constraint_string = re.sub(r"\^0\.0\.(\d+)", r"0.0.\1", constraint_string)
# Rewrite occurrences of ^0.y.z to >=0.y.z,<0.y+1.0 (can be anywhere in constraint string)
# rewrite occurrences of ^0.y.z to >=0.y.z,<0.y+1.0 (can be anywhere in constraint string)
for y in range(1, 10):
constraint_string = re.sub(
rf"\^0\.{y}\.(\d+)", rf">=0.{y}.\1,<0.{y + 1}.0", constraint_string
)
# Rewrite occurrences of ^x.y.z to >=x.y.z,<x+1.0.0 (can be anywhere in constraint string)
# rewrite occurrences of ^x.y.z to >=x.y.z,<x+1.0.0 (can be anywhere in constraint string)
for x in range(1, 10):
constraint_string = re.sub(
rf"\^{x}\.0\.(\d+)", rf">={x}.0.\1,<{x + 1}.0.0", constraint_string

112
.github/scripts/prep_api_docs_build.py vendored Normal file
View File

@@ -0,0 +1,112 @@
#!/usr/bin/env python
"""Script to sync libraries from various repositories into the main langchain repository."""
import os
import shutil
from pathlib import Path
from typing import Any, Dict
import yaml
def load_packages_yaml() -> Dict[str, Any]:
"""Load and parse the packages.yml file."""
with open("langchain/libs/packages.yml", "r") as f:
return yaml.safe_load(f)
def get_target_dir(package_name: str) -> Path:
"""Get the target directory for a given package."""
package_name_short = package_name.replace("langchain-", "")
base_path = Path("langchain/libs")
if package_name_short == "experimental":
return base_path / "experimental"
if package_name_short == "community":
return base_path / "community"
return base_path / "partners" / package_name_short
def clean_target_directories(packages: list) -> None:
"""Remove old directories that will be replaced."""
for package in packages:
target_dir = get_target_dir(package["name"])
if target_dir.exists():
print(f"Removing {target_dir}")
shutil.rmtree(target_dir)
def move_libraries(packages: list) -> None:
"""Move libraries from their source locations to the target directories."""
for package in packages:
repo_name = package["repo"].split("/")[1]
source_path = package["path"]
target_dir = get_target_dir(package["name"])
# Handle root path case
if source_path == ".":
source_dir = repo_name
else:
source_dir = f"{repo_name}/{source_path}"
print(f"Moving {source_dir} to {target_dir}")
# Ensure target directory exists
os.makedirs(os.path.dirname(target_dir), exist_ok=True)
try:
# Move the directory
shutil.move(source_dir, target_dir)
except Exception as e:
print(f"Error moving {source_dir} to {target_dir}: {e}")
def main():
"""Main function to orchestrate the library sync process."""
try:
# Load packages configuration
package_yaml = load_packages_yaml()
# Clean target directories
clean_target_directories(
[
p
for p in package_yaml["packages"]
if (
p["repo"].startswith("langchain-ai/") or p.get("include_in_api_ref")
)
and p["repo"] != "langchain-ai/langchain"
and p["name"]
!= "langchain-ai21" # Skip AI21 due to dependency conflicts
]
)
# Move libraries to their new locations
move_libraries(
[
p
for p in package_yaml["packages"]
if not p.get("disabled", False)
and (
p["repo"].startswith("langchain-ai/") or p.get("include_in_api_ref")
)
and p["repo"] != "langchain-ai/langchain"
and p["name"]
!= "langchain-ai21" # Skip AI21 due to dependency conflicts
]
)
# Delete ones without a pyproject.toml
for partner in Path("langchain/libs/partners").iterdir():
if partner.is_dir() and not (partner / "pyproject.toml").exists():
print(f"Removing {partner} as it does not have a pyproject.toml")
shutil.rmtree(partner)
print("Library sync completed successfully!")
except Exception as e:
print(f"Error during library sync: {e}")
raise
if __name__ == "__main__":
main()

View File

@@ -1,11 +1,3 @@
# Validates that a package's integration tests compile without syntax or import errors.
#
# (If an integration test fails to compile, it won't run.)
#
# Called as part of check_diffs.yml workflow
#
# Runs pytest with compile marker to check syntax/imports.
name: '🔗 Compile Integration Tests'
on:
@@ -35,14 +27,12 @@ jobs:
timeout-minutes: 20
name: 'Python ${{ inputs.python-version }}'
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v4
- name: '🐍 Set up Python ${{ inputs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ inputs.python-version }}
cache-suffix: compile-integration-tests-${{ inputs.working-directory }}
working-directory: ${{ inputs.working-directory }}
- name: '📦 Install Integration Dependencies'
shell: bash

94
.github/workflows/_integration_test.yml vendored Normal file
View File

@@ -0,0 +1,94 @@
name: '🚀 Integration Tests'
run-name: 'Test ${{ inputs.working-directory }} on Python ${{ inputs.python-version }}'
on:
workflow_dispatch:
inputs:
working-directory:
required: true
type: string
description: "From which folder this pipeline executes"
python-version:
required: true
type: string
description: "Python version to use"
default: "3.11"
permissions:
contents: read
env:
UV_FROZEN: "true"
jobs:
build:
defaults:
run:
working-directory: ${{ inputs.working-directory }}
runs-on: ubuntu-latest
name: 'Python ${{ inputs.python-version }}'
steps:
- uses: actions/checkout@v4
- name: '🐍 Set up Python ${{ inputs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ inputs.python-version }}
- name: '📦 Install Integration Dependencies'
shell: bash
run: uv sync --group test --group test_integration
- name: '🚀 Run Integration Tests'
shell: bash
env:
AI21_API_KEY: ${{ secrets.AI21_API_KEY }}
FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
ANTHROPIC_FILES_API_IMAGE_ID: ${{ secrets.ANTHROPIC_FILES_API_IMAGE_ID }}
ANTHROPIC_FILES_API_PDF_ID: ${{ secrets.ANTHROPIC_FILES_API_PDF_ID }}
AZURE_OPENAI_API_VERSION: ${{ secrets.AZURE_OPENAI_API_VERSION }}
AZURE_OPENAI_API_BASE: ${{ secrets.AZURE_OPENAI_API_BASE }}
AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_CHAT_DEPLOYMENT_NAME }}
AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME }}
AZURE_OPENAI_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }}
TOGETHER_API_KEY: ${{ secrets.TOGETHER_API_KEY }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
NVIDIA_API_KEY: ${{ secrets.NVIDIA_API_KEY }}
GOOGLE_SEARCH_API_KEY: ${{ secrets.GOOGLE_SEARCH_API_KEY }}
GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }}
HUGGINGFACEHUB_API_TOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}
EXA_API_KEY: ${{ secrets.EXA_API_KEY }}
NOMIC_API_KEY: ${{ secrets.NOMIC_API_KEY }}
WATSONX_APIKEY: ${{ secrets.WATSONX_APIKEY }}
WATSONX_PROJECT_ID: ${{ secrets.WATSONX_PROJECT_ID }}
ASTRA_DB_API_ENDPOINT: ${{ secrets.ASTRA_DB_API_ENDPOINT }}
ASTRA_DB_APPLICATION_TOKEN: ${{ secrets.ASTRA_DB_APPLICATION_TOKEN }}
ASTRA_DB_KEYSPACE: ${{ secrets.ASTRA_DB_KEYSPACE }}
ES_URL: ${{ secrets.ES_URL }}
ES_CLOUD_ID: ${{ secrets.ES_CLOUD_ID }}
ES_API_KEY: ${{ secrets.ES_API_KEY }}
MONGODB_ATLAS_URI: ${{ secrets.MONGODB_ATLAS_URI }}
COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
UPSTAGE_API_KEY: ${{ secrets.UPSTAGE_API_KEY }}
XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
PPLX_API_KEY: ${{ secrets.PPLX_API_KEY }}
run: |
make integration_tests
- name: Ensure the tests did not create any additional files
shell: bash
run: |
set -eu
STATUS="$(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'

View File

@@ -1,11 +1,6 @@
# Runs linting.
#
# Uses the package's Makefile to run the checks, specifically the
# `lint_package` and `lint_tests` targets.
#
# Called as part of check_diffs.yml workflow.
name: '🧹 Linting'
name: '🧹 Code Linting'
# Runs code quality checks using ruff, mypy, and other linting tools
# Checks both package code and test code for consistency
on:
workflow_call:
@@ -38,16 +33,22 @@ jobs:
timeout-minutes: 20
steps:
- name: '📋 Checkout Code'
uses: actions/checkout@v5
uses: actions/checkout@v4
- name: '🐍 Set up Python ${{ inputs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ inputs.python-version }}
cache-suffix: lint-${{ inputs.working-directory }}
working-directory: ${{ inputs.working-directory }}
- name: '📦 Install Lint & Typing Dependencies'
# Also installs dev/lint/test/typing dependencies, to ensure we have
# type hints for as many of our libraries as possible.
# This helps catch errors that require dependencies to be spotted, for example:
# https://github.com/langchain-ai/langchain/pull/10249/files#diff-935185cd488d015f026dcd9e19616ff62863e8cde8c0bee70318d3ccbca98341
#
# If you change this configuration, make sure to change the `cache-key`
# in the `poetry_setup` action above to stop using the old cache.
# It doesn't matter how you change it, any change will cause a cache-bust.
working-directory: ${{ inputs.working-directory }}
run: |
uv sync --group lint --group typing
@@ -57,13 +58,20 @@ jobs:
run: |
make lint_package
- name: '📦 Install Test Dependencies (non-partners)'
# (For directories NOT starting with libs/partners/)
- name: '📦 Install Unit Test Dependencies'
# 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.
if: ${{ ! startsWith(inputs.working-directory, 'libs/partners/') }}
working-directory: ${{ inputs.working-directory }}
run: |
uv sync --inexact --group test
- name: '📦 Install Test Dependencies'
- name: '📦 Install Unit + Integration Test Dependencies'
if: ${{ startsWith(inputs.working-directory, 'libs/partners/') }}
working-directory: ${{ inputs.working-directory }}
run: |

View File

@@ -1,11 +1,5 @@
# Builds and publishes LangChain packages to PyPI.
#
# Manually triggered, though can be used as a reusable workflow (workflow_call).
#
# Handles version bumping, building, and publishing to PyPI with authentication.
name: "🚀 Package Release"
run-name: "Release ${{ inputs.working-directory }} ${{ inputs.release-version }}"
name: '🚀 Package Release'
run-name: 'Release ${{ inputs.working-directory }} ${{ inputs.release-version }}'
on:
workflow_call:
inputs:
@@ -19,11 +13,11 @@ on:
required: true
type: string
description: "From which folder this pipeline executes"
default: "libs/langchain"
default: 'libs/langchain'
release-version:
required: true
type: string
default: "0.1.0"
default: '0.1.0'
description: "New version of package being released"
dangerous-nonmaster-release:
required: false
@@ -36,9 +30,6 @@ env:
UV_FROZEN: "true"
UV_NO_SYNC: "true"
permissions:
contents: write # Required for creating GitHub releases
jobs:
# Build the distribution package and extract version info
# Runs in isolated environment with minimal permissions for security
@@ -46,15 +37,13 @@ jobs:
if: github.ref == 'refs/heads/master' || inputs.dangerous-nonmaster-release
environment: Scheduled testing
runs-on: ubuntu-latest
permissions:
contents: read
outputs:
pkg-name: ${{ steps.check-version.outputs.pkg-name }}
version: ${{ steps.check-version.outputs.version }}
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v4
- name: Set up Python + uv
uses: "./.github/actions/uv_setup"
@@ -63,8 +52,8 @@ jobs:
# We want to keep this build stage *separate* from the release stage,
# so that there's no sharing of permissions between them.
# (Release stage has trusted publishing and GitHub repo contents write access,
#
# The release stage has trusted publishing and GitHub repo contents write access,
# and we want to keep the scope of that access limited just to the release job.
# Otherwise, a malicious `build` step (e.g. via a compromised dependency)
# could get access to our GitHub or PyPI credentials.
#
@@ -100,12 +89,10 @@ jobs:
needs:
- build
runs-on: ubuntu-latest
permissions:
contents: read
outputs:
release-body: ${{ steps.generate-release-body.outputs.release-body }}
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v4
with:
repository: langchain-ai/langchain
path: langchain
@@ -196,36 +183,13 @@ jobs:
needs:
- build
- release-notes
runs-on: ubuntu-latest
permissions:
# This permission is used for trusted publishing:
# https://blog.pypi.org/posts/2023-04-20-introducing-trusted-publishers/
#
# Trusted publishing has to also be configured on PyPI for each package:
# https://docs.pypi.org/trusted-publishers/adding-a-publisher/
id-token: write
steps:
- uses: actions/checkout@v5
- uses: actions/download-artifact@v5
with:
name: dist
path: ${{ inputs.working-directory }}/dist/
- name: Publish to test PyPI
uses: pypa/gh-action-pypi-publish@release/v1
with:
packages-dir: ${{ inputs.working-directory }}/dist/
verbose: true
print-hash: true
repository-url: https://test.pypi.org/legacy/
# We overwrite any existing distributions with the same name and version.
# 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
uses:
./.github/workflows/_test_release.yml
permissions: write-all
with:
working-directory: ${{ inputs.working-directory }}
dangerous-nonmaster-release: ${{ inputs.dangerous-nonmaster-release }}
secrets: inherit
pre-release-checks:
needs:
@@ -233,11 +197,9 @@ jobs:
- release-notes
- test-pypi-publish
runs-on: ubuntu-latest
permissions:
contents: read
timeout-minutes: 20
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v4
# We explicitly *don't* set up caching here. This ensures our tests are
# maximally sensitive to catching breakage.
@@ -258,7 +220,7 @@ jobs:
with:
python-version: ${{ env.PYTHON_VERSION }}
- uses: actions/download-artifact@v5
- uses: actions/download-artifact@v4
with:
name: dist
path: ${{ inputs.working-directory }}/dist/
@@ -303,19 +265,16 @@ jobs:
run: |
VIRTUAL_ENV=.venv uv pip install dist/*.whl
- name: Check for prerelease versions
# Block release if any dependencies allow prerelease versions
# (unless this is itself a prerelease version)
working-directory: ${{ inputs.working-directory }}
run: |
uv run python $GITHUB_WORKSPACE/.github/scripts/check_prerelease_dependencies.py pyproject.toml
- name: Run unit tests
run: make tests
working-directory: ${{ inputs.working-directory }}
- name: Check for prerelease versions
working-directory: ${{ inputs.working-directory }}
run: |
uv run python $GITHUB_WORKSPACE/.github/scripts/check_prerelease_dependencies.py pyproject.toml
- name: Get minimum versions
# Find the minimum published versions that satisfies the given constraints
working-directory: ${{ inputs.working-directory }}
id: min-version
run: |
@@ -330,8 +289,7 @@ jobs:
env:
MIN_VERSIONS: ${{ steps.min-version.outputs.min-versions }}
run: |
VIRTUAL_ENV=.venv uv pip install --force-reinstall --editable .
VIRTUAL_ENV=.venv uv pip install --force-reinstall $MIN_VERSIONS
VIRTUAL_ENV=.venv uv pip install --force-reinstall $MIN_VERSIONS --editable .
make tests
working-directory: ${{ inputs.working-directory }}
@@ -340,7 +298,6 @@ jobs:
working-directory: ${{ inputs.working-directory }}
- name: Run integration tests
# Uses the Makefile's `integration_tests` target for the specified package
if: ${{ startsWith(inputs.working-directory, 'libs/partners/') }}
env:
AI21_API_KEY: ${{ secrets.AI21_API_KEY }}
@@ -381,22 +338,17 @@ jobs:
working-directory: ${{ inputs.working-directory }}
# Test select published packages against new core
# Done when code changes are made to langchain-core
test-prior-published-packages-against-new-core:
# Installs the new core with old partners: Installs the new unreleased core
# alongside the previously published partner packages and runs integration tests
needs:
- build
- release-notes
- test-pypi-publish
- pre-release-checks
runs-on: ubuntu-latest
permissions:
contents: read
strategy:
matrix:
partner: [openai, anthropic]
fail-fast: false # Continue testing other partners if one fails
fail-fast: false # Continue testing other partners if one fails
env:
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
ANTHROPIC_FILES_API_IMAGE_ID: ${{ secrets.ANTHROPIC_FILES_API_IMAGE_ID }}
@@ -410,11 +362,10 @@ jobs:
AZURE_OPENAI_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v4
# We implement this conditional as Github Actions does not have good support
# for conditionally needing steps. https://github.com/actions/runner/issues/491
# TODO: this seems to be resolved upstream, so we can probably remove this workaround
- name: Check if libs/core
run: |
if [ "${{ startsWith(inputs.working-directory, 'libs/core') }}" != "true" ]; then
@@ -428,7 +379,7 @@ jobs:
with:
python-version: ${{ env.PYTHON_VERSION }}
- uses: actions/download-artifact@v5
- uses: actions/download-artifact@v4
if: startsWith(inputs.working-directory, 'libs/core')
with:
name: dist
@@ -442,7 +393,7 @@ jobs:
git ls-remote --tags origin "langchain-${{ matrix.partner }}*" \
| awk '{print $2}' \
| sed 's|refs/tags/||' \
| grep -E '[0-9]+\.[0-9]+\.[0-9]+([a-zA-Z]+[0-9]+)?$' \
| grep -Ev '==[^=]*(\.?dev[0-9]*|\.?rc[0-9]*)$' \
| sort -Vr \
| head -n 1
)"
@@ -469,7 +420,6 @@ jobs:
make integration_tests
publish:
# Publishes the package to PyPI
needs:
- build
- release-notes
@@ -490,14 +440,14 @@ jobs:
working-directory: ${{ inputs.working-directory }}
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v4
- name: Set up Python + uv
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ env.PYTHON_VERSION }}
- uses: actions/download-artifact@v5
- uses: actions/download-artifact@v4
with:
name: dist
path: ${{ inputs.working-directory }}/dist/
@@ -512,7 +462,6 @@ jobs:
attestations: false
mark-release:
# Marks the GitHub release with the new version tag
needs:
- build
- release-notes
@@ -522,7 +471,7 @@ jobs:
runs-on: ubuntu-latest
permissions:
# This permission is needed by `ncipollo/release-action` to
# create the GitHub release/tag
# create the GitHub release.
contents: write
defaults:
@@ -530,14 +479,14 @@ jobs:
working-directory: ${{ inputs.working-directory }}
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v4
- name: Set up Python + uv
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ env.PYTHON_VERSION }}
- uses: actions/download-artifact@v5
- uses: actions/download-artifact@v4
with:
name: dist
path: ${{ inputs.working-directory }}/dist/

View File

@@ -1,7 +1,6 @@
# Runs unit tests with both current and minimum supported dependency versions
# to ensure compatibility across the supported range.
name: '🧪 Unit Testing'
# Runs unit tests with both current and minimum supported dependency versions
# to ensure compatibility across the supported range
on:
workflow_call:
@@ -33,16 +32,13 @@ jobs:
name: 'Python ${{ inputs.python-version }}'
steps:
- name: '📋 Checkout Code'
uses: actions/checkout@v5
uses: actions/checkout@v4
- name: '🐍 Set up Python ${{ inputs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
id: setup-python
with:
python-version: ${{ inputs.python-version }}
cache-suffix: test-${{ inputs.working-directory }}
working-directory: ${{ inputs.working-directory }}
- name: '📦 Install Test Dependencies'
shell: bash
run: uv sync --group test --dev

54
.github/workflows/_test_doc_imports.yml vendored Normal file
View File

@@ -0,0 +1,54 @@
name: '📑 Documentation Import Testing'
on:
workflow_call:
inputs:
python-version:
required: true
type: string
description: "Python version to use"
permissions:
contents: read
env:
UV_FROZEN: "true"
jobs:
build:
runs-on: ubuntu-latest
timeout-minutes: 20
name: '🔍 Check Doc Imports (Python ${{ inputs.python-version }})'
steps:
- name: '📋 Checkout Code'
uses: actions/checkout@v4
- name: '🐍 Set up Python ${{ inputs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ inputs.python-version }}
- name: '📦 Install Test Dependencies'
shell: bash
run: uv sync --group test
- name: '📦 Install LangChain in Editable Mode'
run: |
VIRTUAL_ENV=.venv uv pip install langchain-experimental langchain-community -e libs/core libs/langchain
- name: '🔍 Validate Documentation Import Statements'
shell: bash
run: |
uv run python docs/scripts/check_imports.py
- name: '🧹 Verify Clean Working Directory'
shell: bash
run: |
set -eu
STATUS="$(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'

View File

@@ -1,5 +1,3 @@
# Facilitate unit testing against different Pydantic versions for a provided package.
name: '🐍 Pydantic Version Testing'
on:
@@ -36,14 +34,12 @@ jobs:
name: 'Pydantic ~=${{ inputs.pydantic-version }}'
steps:
- name: '📋 Checkout Code'
uses: actions/checkout@v5
uses: actions/checkout@v4
- name: '🐍 Set up Python ${{ inputs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ inputs.python-version }}
cache-suffix: test-pydantic-${{ inputs.working-directory }}
working-directory: ${{ inputs.working-directory }}
- name: '📦 Install Test Dependencies'
shell: bash

106
.github/workflows/_test_release.yml vendored Normal file
View File

@@ -0,0 +1,106 @@
name: '🧪 Test Release Package'
on:
workflow_call:
inputs:
working-directory:
required: true
type: string
description: "From which folder this pipeline executes"
dangerous-nonmaster-release:
required: false
type: boolean
default: false
description: "Release from a non-master branch (danger!)"
env:
PYTHON_VERSION: "3.11"
UV_FROZEN: "true"
jobs:
build:
if: github.ref == 'refs/heads/master' || inputs.dangerous-nonmaster-release
runs-on: ubuntu-latest
outputs:
pkg-name: ${{ steps.check-version.outputs.pkg-name }}
version: ${{ steps.check-version.outputs.version }}
steps:
- uses: actions/checkout@v4
- name: '🐍 Set up Python + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ env.PYTHON_VERSION }}
# We want to keep this build stage *separate* from the release stage,
# so that there's no sharing of permissions between them.
# The release stage has trusted publishing and GitHub repo contents write access,
# and we want to keep the scope of that access limited just to the release job.
# Otherwise, a malicious `build` step (e.g. via a compromised dependency)
# could get access to our GitHub or PyPI credentials.
#
# Per the trusted publishing GitHub Action:
# > It is strongly advised to separate jobs for building [...]
# > from the publish job.
# https://github.com/pypa/gh-action-pypi-publish#non-goals
- name: '📦 Build Project for Distribution'
run: uv build
working-directory: ${{ inputs.working-directory }}
- name: '⬆️ Upload Build Artifacts'
uses: actions/upload-artifact@v4
with:
name: test-dist
path: ${{ inputs.working-directory }}/dist/
- name: '🔍 Extract Version Information'
id: check-version
shell: python
working-directory: ${{ inputs.working-directory }}
run: |
import os
import tomllib
with open("pyproject.toml", "rb") as f:
data = tomllib.load(f)
pkg_name = data["project"]["name"]
version = data["project"]["version"]
with open(os.environ["GITHUB_OUTPUT"], "a") as f:
f.write(f"pkg-name={pkg_name}\n")
f.write(f"version={version}\n")
publish:
needs:
- build
runs-on: ubuntu-latest
permissions:
# This permission is used for trusted publishing:
# https://blog.pypi.org/posts/2023-04-20-introducing-trusted-publishers/
#
# Trusted publishing has to also be configured on PyPI for each package:
# https://docs.pypi.org/trusted-publishers/adding-a-publisher/
id-token: write
steps:
- uses: actions/checkout@v4
- uses: actions/download-artifact@v4
with:
name: test-dist
path: ${{ inputs.working-directory }}/dist/
- name: Publish to test PyPI
uses: pypa/gh-action-pypi-publish@release/v1
with:
packages-dir: ${{ inputs.working-directory }}/dist/
verbose: true
print-hash: true
repository-url: https://test.pypi.org/legacy/
# We overwrite any existing distributions with the same name and version.
# 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

View File

@@ -1,46 +1,36 @@
# Build the API reference documentation for v0.3 branch.
#
# Manual trigger only.
#
# Built HTML pushed to langchain-ai/langchain-api-docs-html.
#
# Looks for langchain-ai org repos in packages.yml and checks them out.
# Calls prep_api_docs_build.py.
name: "📚 API Docs (v0.3)"
run-name: "Build & Deploy API Reference (v0.3)"
name: '📚 API Docs'
run-name: 'Build & Deploy API Reference'
# Runs daily or can be triggered manually for immediate updates
on:
workflow_dispatch:
schedule:
- cron: '0 13 * * *' # Daily at 1PM UTC
env:
PYTHON_VERSION: "3.11"
jobs:
# Only runs on main repository to prevent unnecessary builds on forks
build:
if: github.repository == 'langchain-ai/langchain' || github.event_name != 'schedule'
runs-on: ubuntu-latest
permissions:
contents: read
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v4
with:
ref: v0.3
path: langchain
- uses: actions/checkout@v5
- uses: actions/checkout@v4
with:
repository: langchain-ai/langchain-api-docs-html
path: langchain-api-docs-html
token: ${{ secrets.TOKEN_GITHUB_API_DOCS_HTML }}
- name: "📋 Extract Repository List with yq"
- name: '📋 Extract Repository List with yq'
id: get-unsorted-repos
uses: mikefarah/yq@master
with:
cmd: |
# Extract repos from packages.yml that are in the langchain-ai org
# (excluding 'langchain' itself)
yq '
.packages[]
| select(
@@ -55,7 +45,7 @@ jobs:
| .repo
' langchain/libs/packages.yml
- name: "📋 Parse YAML & Checkout Repositories"
- name: '📋 Parse YAML & Checkout Repositories'
env:
REPOS_UNSORTED: ${{ steps.get-unsorted-repos.outputs.result }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -81,72 +71,50 @@ jobs:
git clone --depth 1 https://github.com/$repo.git $REPO_NAME
done
- name: "🐍 Setup Python ${{ env.PYTHON_VERSION }}"
uses: actions/setup-python@v6
- name: '🐍 Setup Python ${{ env.PYTHON_VERSION }}'
uses: actions/setup-python@v5
id: setup-python
with:
python-version: ${{ env.PYTHON_VERSION }}
- name: "📦 Install Initial Python Dependencies using uv"
- name: '📦 Install Initial Python Dependencies'
working-directory: langchain
run: |
python -m pip install -U uv
python -m uv pip install --upgrade --no-cache-dir pip setuptools pyyaml
- name: "📦 Organize Library Directories"
# Places cloned partner packages into libs/partners structure
- name: '📦 Organize Library Directories'
run: python langchain/.github/scripts/prep_api_docs_build.py
- name: "🧹 Clear Prior Build"
- name: '🧹 Remove Old HTML Files'
run:
# Remove artifacts from prior docs build
rm -rf langchain-api-docs-html/api_reference_build/html
- name: "📦 Install Documentation Dependencies using uv"
- name: '📦 Install Documentation Dependencies'
working-directory: langchain
run: |
# Install all partner packages in editable mode with overrides
python -m uv pip install $(ls ./libs/partners | xargs -I {} echo "./libs/partners/{}") --overrides ./docs/vercel_overrides.txt
# Install core langchain and other main packages
python -m uv pip install libs/core libs/langchain libs/text-splitters libs/community libs/experimental libs/standard-tests
# Install Sphinx and related packages for building docs
python -m uv pip install -r docs/api_reference/requirements.txt
- name: "🔧 Configure Git Settings"
- name: '🔧 Configure Git Settings'
working-directory: langchain
run: |
git config --local user.email "actions@github.com"
git config --local user.name "Github Actions"
- name: "📚 Build API Documentation"
- name: '📚 Build API Documentation'
working-directory: langchain
run: |
# Generate the API reference RST files
python docs/api_reference/create_api_rst.py
# Build the HTML documentation using Sphinx
# -T: show full traceback on exception
# -E: don't use cached environment (force rebuild, ignore cached doctrees)
# -b html: build HTML docs (vs PDS, etc.)
# -d: path for the cached environment (parsed document trees / doctrees)
# - Separate from output dir for faster incremental builds
# -c: path to conf.py
# -j auto: parallel build using all available CPU cores
python -m sphinx -T -E -b html -d ../langchain-api-docs-html/_build/doctrees -c docs/api_reference docs/api_reference ../langchain-api-docs-html/api_reference_build/html -j auto
# Post-process the generated HTML
python docs/api_reference/scripts/custom_formatter.py ../langchain-api-docs-html/api_reference_build/html
# Default index page is blank so we copy in the actual home page.
cp ../langchain-api-docs-html/api_reference_build/html/{reference,index}.html
# Removes Sphinx's intermediate build artifacts after the build is complete.
rm -rf ../langchain-api-docs-html/_build/
# Commit and push changes to langchain-api-docs-html repo
# https://github.com/marketplace/actions/add-commit
- uses: EndBug/add-and-commit@v9
with:
cwd: langchain-api-docs-html
message: "Update API docs build from v0.3 branch"
message: 'Update API docs build'

View File

@@ -0,0 +1,28 @@
name: '🔗 Check Broken Links'
on:
workflow_dispatch:
schedule:
- cron: '0 13 * * *'
permissions:
contents: read
jobs:
check-links:
if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: '🟢 Setup Node.js 18.x'
uses: actions/setup-node@v4
with:
node-version: 18.x
cache: "yarn"
cache-dependency-path: ./docs/yarn.lock
- name: '📦 Install Node Dependencies'
run: yarn install --immutable --mode=skip-build
working-directory: ./docs
- name: '🔍 Scan Documentation for Broken Links'
run: yarn check-broken-links
working-directory: ./docs

View File

@@ -1,8 +1,6 @@
# Ensures version numbers in pyproject.toml and version.py stay in sync.
#
# (Prevents releases with mismatched version numbers)
name: '🔍 Check Version Equality'
name: '🔍 Check `core` Version Equality'
# Ensures version numbers in pyproject.toml and version.py stay in sync
# Prevents releases with mismatched version numbers
on:
pull_request:
@@ -18,34 +16,19 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v4
- name: '✅ Verify pyproject.toml & version.py Match'
run: |
# Check core versions
CORE_PYPROJECT_VERSION=$(grep -Po '(?<=^version = ")[^"]*' libs/core/pyproject.toml)
CORE_VERSION_PY_VERSION=$(grep -Po '(?<=^VERSION = ")[^"]*' libs/core/langchain_core/version.py)
PYPROJECT_VERSION=$(grep -Po '(?<=^version = ")[^"]*' libs/core/pyproject.toml)
VERSION_PY_VERSION=$(grep -Po '(?<=^VERSION = ")[^"]*' libs/core/langchain_core/version.py)
# Compare core versions
if [ "$CORE_PYPROJECT_VERSION" != "$CORE_VERSION_PY_VERSION" ]; then
# Compare the two versions
if [ "$PYPROJECT_VERSION" != "$VERSION_PY_VERSION" ]; then
echo "langchain-core versions in pyproject.toml and version.py do not match!"
echo "pyproject.toml version: $CORE_PYPROJECT_VERSION"
echo "version.py version: $CORE_VERSION_PY_VERSION"
echo "pyproject.toml version: $PYPROJECT_VERSION"
echo "version.py version: $VERSION_PY_VERSION"
exit 1
else
echo "Core versions match: $CORE_PYPROJECT_VERSION"
fi
# Check langchain_v1 versions
LANGCHAIN_PYPROJECT_VERSION=$(grep -Po '(?<=^version = ")[^"]*' libs/langchain_v1/pyproject.toml)
LANGCHAIN_INIT_PY_VERSION=$(grep -Po '(?<=^__version__ = ")[^"]*' libs/langchain_v1/langchain/__init__.py)
# Compare langchain_v1 versions
if [ "$LANGCHAIN_PYPROJECT_VERSION" != "$LANGCHAIN_INIT_PY_VERSION" ]; then
echo "langchain_v1 versions in pyproject.toml and __init__.py do not match!"
echo "pyproject.toml version: $LANGCHAIN_PYPROJECT_VERSION"
echo "version.py version: $LANGCHAIN_INIT_PY_VERSION"
exit 1
else
echo "Langchain v1 versions match: $LANGCHAIN_PYPROJECT_VERSION"
echo "Versions match: $PYPROJECT_VERSION"
fi

View File

@@ -1,18 +1,4 @@
# Primary CI workflow.
#
# Only runs against packages that have changed files.
#
# Runs:
# - Linting (_lint.yml)
# - Unit Tests (_test.yml)
# - Pydantic compatibility tests (_test_pydantic.yml)
# - Integration test compilation checks (_compile_integration_test.yml)
# - Extended test suites that require additional dependencies
# - Codspeed benchmarks (if not labeled 'codspeed-ignore')
#
# Reports status to GitHub checks and PR status.
name: "🔧 CI"
name: '🔧 CI'
on:
push:
@@ -25,8 +11,8 @@ on:
# 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.
# 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
@@ -42,20 +28,20 @@ jobs:
# This job analyzes which files changed and creates a dynamic test matrix
# to only run tests/lints for the affected packages, improving CI efficiency
build:
name: "Detect Changes & Set Matrix"
name: 'Detect Changes & Set Matrix'
runs-on: ubuntu-latest
if: ${{ !contains(github.event.pull_request.labels.*.name, 'ci-ignore') }}
steps:
- name: "📋 Checkout Code"
uses: actions/checkout@v5
- name: "🐍 Setup Python 3.11"
uses: actions/setup-python@v6
- name: '📋 Checkout Code'
uses: actions/checkout@v4
- name: '🐍 Setup Python 3.11'
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: "📂 Get Changed Files"
python-version: '3.11'
- name: '📂 Get Changed Files'
id: files
uses: Ana06/get-changed-files@v2.3.0
- name: "🔍 Analyze Changed Files & Generate Build Matrix"
- name: '🔍 Analyze Changed Files & Generate Build Matrix'
id: set-matrix
run: |
python -m pip install packaging requests
@@ -66,11 +52,11 @@ jobs:
extended-tests: ${{ steps.set-matrix.outputs.extended-tests }}
compile-integration-tests: ${{ steps.set-matrix.outputs.compile-integration-tests }}
dependencies: ${{ steps.set-matrix.outputs.dependencies }}
test-doc-imports: ${{ steps.set-matrix.outputs.test-doc-imports }}
test-pydantic: ${{ steps.set-matrix.outputs.test-pydantic }}
codspeed: ${{ steps.set-matrix.outputs.codspeed }}
# Run linting only on packages that have changed files
lint:
needs: [build]
needs: [ build ]
if: ${{ needs.build.outputs.lint != '[]' }}
strategy:
matrix:
@@ -84,7 +70,7 @@ jobs:
# Run unit tests only on packages that have changed files
test:
needs: [build]
needs: [ build ]
if: ${{ needs.build.outputs.test != '[]' }}
strategy:
matrix:
@@ -98,7 +84,7 @@ jobs:
# Test compatibility with different Pydantic versions for affected packages
test-pydantic:
needs: [build]
needs: [ build ]
if: ${{ needs.build.outputs.test-pydantic != '[]' }}
strategy:
matrix:
@@ -110,10 +96,21 @@ jobs:
pydantic-version: ${{ matrix.job-configs.pydantic-version }}
secrets: inherit
test-doc-imports:
needs: [ build ]
if: ${{ needs.build.outputs.test-doc-imports != '[]' }}
strategy:
matrix:
job-configs: ${{ fromJson(needs.build.outputs.test-doc-imports) }}
fail-fast: false
uses: ./.github/workflows/_test_doc_imports.yml
with:
python-version: ${{ matrix.job-configs.python-version }}
secrets: inherit
# Verify integration tests compile without actually running them (faster feedback)
compile-integration-tests:
name: "Compile Integration Tests"
needs: [build]
needs: [ build ]
if: ${{ needs.build.outputs.compile-integration-tests != '[]' }}
strategy:
matrix:
@@ -127,8 +124,8 @@ jobs:
# Run extended test suites that require additional dependencies
extended-tests:
name: "Extended Tests"
needs: [build]
name: 'Extended Tests'
needs: [ build ]
if: ${{ needs.build.outputs.extended-tests != '[]' }}
strategy:
matrix:
@@ -141,16 +138,14 @@ jobs:
run:
working-directory: ${{ matrix.job-configs.working-directory }}
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v4
- name: "🐍 Set up Python ${{ matrix.job-configs.python-version }} + UV"
- name: '🐍 Set up Python ${{ matrix.job-configs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ matrix.job-configs.python-version }}
cache-suffix: extended-tests-${{ matrix.job-configs.working-directory }}
working-directory: ${{ matrix.job-configs.working-directory }}
- name: "📦 Install Dependencies & Run Extended Tests"
- name: '📦 Install Dependencies & Run Extended Tests'
shell: bash
run: |
echo "Running extended tests, installing dependencies with uv..."
@@ -159,7 +154,7 @@ jobs:
VIRTUAL_ENV=.venv uv pip install -r extended_testing_deps.txt
VIRTUAL_ENV=.venv make extended_tests
- name: "🧹 Verify Clean Working Directory"
- name: '🧹 Verify Clean Working Directory'
shell: bash
run: |
set -eu
@@ -171,81 +166,10 @@ jobs:
# and `set -e` above will cause the step to fail.
echo "$STATUS" | grep 'nothing to commit, working tree clean'
# Run codspeed benchmarks only on packages that have changed files
codspeed:
name: "⚡ CodSpeed Benchmarks"
needs: [build]
if: ${{ needs.build.outputs.codspeed != '[]' && !contains(github.event.pull_request.labels.*.name, 'codspeed-ignore') }}
runs-on: ubuntu-latest
strategy:
matrix:
job-configs: ${{ fromJson(needs.build.outputs.codspeed) }}
fail-fast: false
steps:
- uses: actions/checkout@v5
# We have to use 3.12 as 3.13 is not yet supported
- name: "📦 Install UV Package Manager"
uses: astral-sh/setup-uv@v6
with:
python-version: "3.12"
- uses: actions/setup-python@v6
with:
python-version: "3.12"
- name: "📦 Install Test Dependencies"
run: uv sync --group test
working-directory: ${{ matrix.job-configs.working-directory }}
- name: "⚡ Run Benchmarks: ${{ matrix.job-configs.working-directory }}"
uses: CodSpeedHQ/action@v4
env:
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
ANTHROPIC_FILES_API_IMAGE_ID: ${{ secrets.ANTHROPIC_FILES_API_IMAGE_ID }}
ANTHROPIC_FILES_API_PDF_ID: ${{ secrets.ANTHROPIC_FILES_API_PDF_ID }}
AZURE_OPENAI_API_VERSION: ${{ secrets.AZURE_OPENAI_API_VERSION }}
AZURE_OPENAI_API_BASE: ${{ secrets.AZURE_OPENAI_API_BASE }}
AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_CHAT_DEPLOYMENT_NAME }}
AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME }}
AZURE_OPENAI_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
DEEPSEEK_API_KEY: ${{ secrets.DEEPSEEK_API_KEY }}
EXA_API_KEY: ${{ secrets.EXA_API_KEY }}
FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
HUGGINGFACEHUB_API_TOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}
MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }}
NOMIC_API_KEY: ${{ secrets.NOMIC_API_KEY }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
PPLX_API_KEY: ${{ secrets.PPLX_API_KEY }}
XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
with:
token: ${{ secrets.CODSPEED_TOKEN }}
run: |
cd ${{ matrix.job-configs.working-directory }}
if [ "${{ matrix.job-configs.working-directory }}" = "libs/core" ]; then
uv run --no-sync pytest ./tests/benchmarks --codspeed
else
uv run --no-sync pytest ./tests/ --codspeed
fi
mode: ${{ matrix.job-configs.working-directory == 'libs/core' && 'walltime' || 'instrumentation' }}
# Final status check - ensures all required jobs passed before allowing merge
ci_success:
name: "✅ CI Success"
needs:
[
build,
lint,
test,
compile-integration-tests,
extended-tests,
test-pydantic,
codspeed,
]
name: '✅ CI Success'
needs: [build, lint, test, compile-integration-tests, extended-tests, test-doc-imports, test-pydantic]
if: |
always()
runs-on: ubuntu-latest
@@ -254,7 +178,7 @@ jobs:
RESULTS_JSON: ${{ toJSON(needs.*.result) }}
EXIT_CODE: ${{!contains(needs.*.result, 'failure') && !contains(needs.*.result, 'cancelled') && '0' || '1'}}
steps:
- name: "🎉 All Checks Passed"
- name: '🎉 All Checks Passed'
run: |
echo $JOBS_JSON
echo $RESULTS_JSON

38
.github/workflows/check_new_docs.yml vendored Normal file
View File

@@ -0,0 +1,38 @@
name: '📑 Integration Docs Lint'
on:
push:
branches: [master]
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
permissions:
contents: read
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.10'
- id: files
uses: Ana06/get-changed-files@v2.3.0
with:
filter: |
*.ipynb
*.md
*.mdx
- name: '🔍 Check New Documentation Templates'
run: |
python docs/scripts/check_templates.py ${{ steps.files.outputs.added }}

66
.github/workflows/codspeed.yml vendored Normal file
View File

@@ -0,0 +1,66 @@
name: '⚡ CodSpeed'
on:
push:
branches:
- master
pull_request:
workflow_dispatch:
permissions:
contents: read
env:
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: foo
AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME: foo
DEEPSEEK_API_KEY: foo
FIREWORKS_API_KEY: foo
jobs:
codspeed:
name: 'Benchmark'
runs-on: ubuntu-latest
if: ${{ !contains(github.event.pull_request.labels.*.name, 'codspeed-ignore') }}
strategy:
matrix:
include:
- working-directory: libs/core
mode: walltime
- working-directory: libs/partners/openai
- working-directory: libs/partners/anthropic
- working-directory: libs/partners/deepseek
- working-directory: libs/partners/fireworks
- working-directory: libs/partners/xai
- working-directory: libs/partners/mistralai
- working-directory: libs/partners/groq
fail-fast: false
steps:
- uses: actions/checkout@v4
# We have to use 3.12 as 3.13 is not yet supported
- name: '📦 Install UV Package Manager'
uses: astral-sh/setup-uv@v6
with:
python-version: "3.12"
- uses: actions/setup-python@v5
with:
python-version: "3.12"
- name: '📦 Install Test Dependencies'
run: uv sync --group test
working-directory: ${{ matrix.working-directory }}
- name: '⚡ Run Benchmarks: ${{ matrix.working-directory }}'
uses: CodSpeedHQ/action@v3
with:
token: ${{ secrets.CODSPEED_TOKEN }}
run: |
cd ${{ matrix.working-directory }}
if [ "${{ matrix.working-directory }}" = "libs/core" ]; then
uv run --no-sync pytest ./tests/benchmarks --codspeed
else
uv run --no-sync pytest ./tests/ --codspeed
fi
mode: ${{ matrix.mode || 'instrumentation' }}

View File

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

View File

@@ -1,201 +0,0 @@
# Routine integration tests against partner libraries with live API credentials.
#
# Uses `make integration_tests` for each library in the matrix.
#
# Runs daily. Can also be triggered manually for immediate updates.
name: "⏰ Integration Tests"
run-name: "Run Integration Tests - ${{ inputs.working-directory-force || 'all libs' }} (Python ${{ inputs.python-version-force || '3.10, 3.13' }})"
on:
workflow_dispatch:
inputs:
working-directory-force:
type: string
description: "From which folder this pipeline executes - defaults to all in matrix - example value: libs/partners/anthropic"
python-version-force:
type: string
description: "Python version to use - defaults to 3.10 and 3.13 in matrix - example value: 3.11"
schedule:
- cron: "0 13 * * *" # Runs daily at 1PM UTC (9AM EDT/6AM PDT)
permissions:
contents: read
env:
POETRY_VERSION: "1.8.4"
UV_FROZEN: "true"
DEFAULT_LIBS: '["libs/partners/openai", "libs/partners/anthropic", "libs/partners/fireworks", "libs/partners/groq", "libs/partners/mistralai", "libs/partners/xai", "libs/partners/google-vertexai", "libs/partners/google-genai", "libs/partners/aws"]'
POETRY_LIBS: ("libs/partners/aws")
jobs:
# Generate dynamic test matrix based on input parameters or defaults
# Only runs on the main repo (for scheduled runs) or when manually triggered
compute-matrix:
if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
runs-on: ubuntu-latest
name: "📋 Compute Test Matrix"
outputs:
matrix: ${{ steps.set-matrix.outputs.matrix }}
steps:
- name: "🔢 Generate Python & Library Matrix"
id: set-matrix
env:
DEFAULT_LIBS: ${{ env.DEFAULT_LIBS }}
WORKING_DIRECTORY_FORCE: ${{ github.event.inputs.working-directory-force || '' }}
PYTHON_VERSION_FORCE: ${{ github.event.inputs.python-version-force || '' }}
run: |
# echo "matrix=..." where matrix is a json formatted str with keys python-version and working-directory
# python-version should default to 3.10 and 3.13, but is overridden to [PYTHON_VERSION_FORCE] if set
# working-directory should default to DEFAULT_LIBS, but is overridden to [WORKING_DIRECTORY_FORCE] if set
python_version='["3.10", "3.13"]'
working_directory="$DEFAULT_LIBS"
if [ -n "$PYTHON_VERSION_FORCE" ]; then
python_version="[\"$PYTHON_VERSION_FORCE\"]"
fi
if [ -n "$WORKING_DIRECTORY_FORCE" ]; then
working_directory="[\"$WORKING_DIRECTORY_FORCE\"]"
fi
matrix="{\"python-version\": $python_version, \"working-directory\": $working_directory}"
echo $matrix
echo "matrix=$matrix" >> $GITHUB_OUTPUT
# Run integration tests against partner libraries with live API credentials
# Tests are run with Poetry or UV depending on the library's setup
build:
if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
name: "🐍 Python ${{ matrix.python-version }}: ${{ matrix.working-directory }}"
runs-on: ubuntu-latest
needs: [compute-matrix]
timeout-minutes: 30
strategy:
fail-fast: false
matrix:
python-version: ${{ fromJSON(needs.compute-matrix.outputs.matrix).python-version }}
working-directory: ${{ fromJSON(needs.compute-matrix.outputs.matrix).working-directory }}
steps:
- uses: actions/checkout@v5
with:
path: langchain
- uses: actions/checkout@v5
with:
repository: langchain-ai/langchain-google
path: langchain-google
- uses: actions/checkout@v5
with:
repository: langchain-ai/langchain-aws
path: langchain-aws
- name: "📦 Organize External Libraries"
run: |
rm -rf \
langchain/libs/partners/google-genai \
langchain/libs/partners/google-vertexai
mv langchain-google/libs/genai langchain/libs/partners/google-genai
mv langchain-google/libs/vertexai langchain/libs/partners/google-vertexai
mv langchain-aws/libs/aws langchain/libs/partners/aws
- name: "🐍 Set up Python ${{ matrix.python-version }} + Poetry"
if: contains(env.POETRY_LIBS, matrix.working-directory)
uses: "./langchain/.github/actions/poetry_setup"
with:
python-version: ${{ matrix.python-version }}
poetry-version: ${{ env.POETRY_VERSION }}
working-directory: langchain/${{ matrix.working-directory }}
cache-key: scheduled
- name: "🐍 Set up Python ${{ matrix.python-version }} + UV"
if: "!contains(env.POETRY_LIBS, matrix.working-directory)"
uses: "./langchain/.github/actions/uv_setup"
with:
python-version: ${{ matrix.python-version }}
- name: "🔐 Authenticate to Google Cloud"
id: "auth"
uses: google-github-actions/auth@v3
with:
credentials_json: "${{ secrets.GOOGLE_CREDENTIALS }}"
- name: "🔐 Configure AWS Credentials"
uses: aws-actions/configure-aws-credentials@v5
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: ${{ secrets.AWS_REGION }}
- name: "📦 Install Dependencies (Poetry)"
if: contains(env.POETRY_LIBS, matrix.working-directory)
run: |
echo "Running scheduled tests, installing dependencies with poetry..."
cd langchain/${{ matrix.working-directory }}
poetry install --with=test_integration,test
- name: "📦 Install Dependencies (UV)"
if: "!contains(env.POETRY_LIBS, matrix.working-directory)"
run: |
echo "Running scheduled tests, installing dependencies with uv..."
cd langchain/${{ matrix.working-directory }}
uv sync --group test --group test_integration
- name: "🚀 Run Integration Tests"
env:
AI21_API_KEY: ${{ secrets.AI21_API_KEY }}
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
ANTHROPIC_FILES_API_IMAGE_ID: ${{ secrets.ANTHROPIC_FILES_API_IMAGE_ID }}
ANTHROPIC_FILES_API_PDF_ID: ${{ secrets.ANTHROPIC_FILES_API_PDF_ID }}
ASTRA_DB_API_ENDPOINT: ${{ secrets.ASTRA_DB_API_ENDPOINT }}
ASTRA_DB_APPLICATION_TOKEN: ${{ secrets.ASTRA_DB_APPLICATION_TOKEN }}
ASTRA_DB_KEYSPACE: ${{ secrets.ASTRA_DB_KEYSPACE }}
AZURE_OPENAI_API_VERSION: ${{ secrets.AZURE_OPENAI_API_VERSION }}
AZURE_OPENAI_API_BASE: ${{ secrets.AZURE_OPENAI_API_BASE }}
AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_CHAT_DEPLOYMENT_NAME }}
AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME }}
AZURE_OPENAI_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
DEEPSEEK_API_KEY: ${{ secrets.DEEPSEEK_API_KEY }}
ES_URL: ${{ secrets.ES_URL }}
ES_CLOUD_ID: ${{ secrets.ES_CLOUD_ID }}
ES_API_KEY: ${{ secrets.ES_API_KEY }}
EXA_API_KEY: ${{ secrets.EXA_API_KEY }}
FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
GOOGLE_SEARCH_API_KEY: ${{ secrets.GOOGLE_SEARCH_API_KEY }}
GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }}
GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
HUGGINGFACEHUB_API_TOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}
MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }}
MONGODB_ATLAS_URI: ${{ secrets.MONGODB_ATLAS_URI }}
NOMIC_API_KEY: ${{ secrets.NOMIC_API_KEY }}
NVIDIA_API_KEY: ${{ secrets.NVIDIA_API_KEY }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
PPLX_API_KEY: ${{ secrets.PPLX_API_KEY }}
TOGETHER_API_KEY: ${{ secrets.TOGETHER_API_KEY }}
UPSTAGE_API_KEY: ${{ secrets.UPSTAGE_API_KEY }}
WATSONX_APIKEY: ${{ secrets.WATSONX_APIKEY }}
WATSONX_PROJECT_ID: ${{ secrets.WATSONX_PROJECT_ID }}
XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
run: |
cd langchain/${{ matrix.working-directory }}
make integration_tests
- name: "🧹 Clean up External Libraries"
# Clean up external libraries to avoid affecting the following git status check
run: |
rm -rf \
langchain/libs/partners/google-genai \
langchain/libs/partners/google-vertexai \
langchain/libs/partners/aws
- name: "🧹 Verify Clean Working Directory"
working-directory: langchain
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'

28
.github/workflows/people.yml vendored Normal file
View File

@@ -0,0 +1,28 @@
name: '👥 LangChain People'
run-name: 'Update People Data'
# This workflow updates the LangChain People data by fetching the latest information from the LangChain Git
on:
schedule:
- cron: "0 14 1 * *"
push:
branches: [jacob/people]
workflow_dispatch:
jobs:
langchain-people:
if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- name: '📋 Dump GitHub Context'
env:
GITHUB_CONTEXT: ${{ toJson(github) }}
run: echo "$GITHUB_CONTEXT"
- uses: actions/checkout@v4
# Ref: https://github.com/actions/runner/issues/2033
- name: '🔧 Fix Git Safe Directory in Container'
run: mkdir -p /home/runner/work/_temp/_github_home && printf "[safe]\n\tdirectory = /github/workspace" > /home/runner/work/_temp/_github_home/.gitconfig
- uses: ./.github/actions/people
with:
token: ${{ secrets.LANGCHAIN_PEOPLE_GITHUB_TOKEN }}

View File

@@ -1,28 +0,0 @@
# Label PRs based on changed files.
#
# See `.github/pr-file-labeler.yml` to see rules for each label/directory.
name: "🏷️ Pull Request Labeler"
on:
# Safe since we're not checking out or running the PR's code
# Never check out the PR's head in a pull_request_target job
pull_request_target:
types: [opened, synchronize, reopened, edited]
jobs:
labeler:
name: 'label'
permissions:
contents: read
pull-requests: write
issues: write
runs-on: ubuntu-latest
steps:
- name: Label Pull Request
uses: actions/labeler@v6
with:
repo-token: "${{ secrets.GITHUB_TOKEN }}"
configuration-path: .github/pr-file-labeler.yml
sync-labels: false

View File

@@ -1,28 +0,0 @@
# Label PRs based on their titles.
#
# See `.github/pr-title-labeler.yml` to see rules for each label/title pattern.
name: "🏷️ PR Title Labeler"
on:
# Safe since we're not checking out or running the PR's code
# Never check out the PR's head in a pull_request_target job
pull_request_target:
types: [opened, synchronize, reopened, edited]
jobs:
pr-title-labeler:
name: 'label'
permissions:
contents: read
pull-requests: write
issues: write
runs-on: ubuntu-latest
steps:
- name: Label PR based on title
# Archived repo; latest commit (v0.1.0)
uses: grafana/pr-labeler-action@f19222d3ef883d2ca5f04420fdfe8148003763f0
with:
token: ${{ secrets.GITHUB_TOKEN }}
configuration-path: .github/pr-title-labeler.yml

View File

@@ -1,48 +1,52 @@
# PR title linting.
# -----------------------------------------------------------------------------
# PR Title Lint Workflow
#
# FORMAT (Conventional Commits 1.0.0):
# Purpose:
# Enforces Conventional Commits format for pull request titles to maintain a
# clear, consistent, and machine-readable change history across our repository.
# This helps with automated changelog generation and semantic versioning.
#
# Enforced Commit Message Format (Conventional Commits 1.0.0):
# <type>[optional scope]: <description>
# [optional body]
# [optional footer(s)]
#
# Examples:
# feat(core): add multitenant support
# fix(cli): resolve flag parsing error
# docs: update API usage examples
# docs(openai): update API usage examples
#
# Allowed Types:
# * feat — a new feature (MINOR)
# * fix — a bug fix (PATCH)
# * docs — documentation only changes
# * style — formatting, linting, etc.; no code change or typing refactors
# * refactor — code change that neither fixes a bug nor adds a feature
# * perf — code change that improves performance
# * test — adding tests or correcting existing
# * build — changes that affect the build system/external dependencies
# * ci — continuous integration/configuration changes
# * chore — other changes that don't modify source or test files
# * revert — reverts a previous commit
# * release — prepare a new release
# feat — a new feature (MINOR bump)
# fix — a bug fix (PATCH bump)
# docs — documentation only changes
# style — formatting, missing semi-colons, etc.; no code change
# refactor — code change that neither fixes a bug nor adds a feature
# perf — code change that improves performance
# test — adding missing tests or correcting existing tests
# build — changes that affect the build system or external dependencies
# ci — continuous integration/configuration changes
# chore — other changes that don't modify src or test files
# revert — reverts a previous commit
# release — prepare a new release
#
# Allowed Scopes (optional):
# core, cli, langchain, langchain_v1, langchain_legacy, standard-tests,
# text-splitters, docs, anthropic, chroma, deepseek, exa, fireworks, groq,
# huggingface, mistralai, nomic, ollama, openai, perplexity, prompty, qdrant,
# xai, infra
# core, cli, langchain, standard-tests, docs, anthropic, chroma, deepseek,
# exa, fireworks, groq, huggingface, mistralai, nomic, ollama, openai,
# perplexity, prompty, qdrant, xai
#
# Rules:
# 1. The 'Type' must start with a lowercase letter.
# 2. Breaking changes: append "!" after type/scope (e.g., feat!: drop x support)
# 3. When releasing (updating the pyproject.toml and uv.lock), the commit message
# should be: `release(scope): x.y.z` (e.g., `release(core): 1.2.0` with no
# body, footer, or preceeding/proceeding text).
# Rules & Tips for New Committers:
# 1. Subject (type) must start with a lowercase letter and, if possible, be
# followed by a scope wrapped in parenthesis `(scope)`
# 2. Breaking changes:
# Append "!" after type/scope (e.g., feat!: drop Node 12 support)
# Or include a footer "BREAKING CHANGE: <details>"
# 3. Example PR titles:
# feat(core): add multitenant support
# fix(cli): resolve flag parsing error
# docs: update API usage examples
# docs(openai): update API usage examples
#
# Enforces Conventional Commits format for pull request titles to maintain a clear and
# machine-readable change history.
# Resources:
# • Conventional Commits spec: https://www.conventionalcommits.org/en/v1.0.0/
# -----------------------------------------------------------------------------
name: "🏷️ PR Title Lint"
name: '🏷️ PR Title Lint'
permissions:
pull-requests: read
@@ -52,13 +56,13 @@ on:
types: [opened, edited, synchronize]
jobs:
# Validates that PR title follows Conventional Commits 1.0.0 specification
# Validates that PR title follows Conventional Commits specification
lint-pr-title:
name: "validate format"
name: 'Validate PR Title Format'
runs-on: ubuntu-latest
steps:
- name: "✅ Validate Conventional Commits Format"
uses: amannn/action-semantic-pull-request@v6
- name: '✅ Validate Conventional Commits Format'
uses: amannn/action-semantic-pull-request@v5
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
@@ -80,7 +84,6 @@ jobs:
cli
langchain
langchain_v1
langchain_legacy
standard-tests
text-splitters
docs

75
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@@ -0,0 +1,75 @@
name: '📓 Validate Documentation Notebooks'
run-name: 'Test notebooks in ${{ inputs.working-directory }}'
on:
workflow_dispatch:
inputs:
python_version:
description: 'Python version'
required: false
default: '3.11'
working-directory:
description: 'Working directory or subset (e.g., docs/docs/tutorials/llm_chain.ipynb or docs/docs/how_to)'
required: false
default: 'all'
schedule:
- cron: '0 13 * * *'
permissions:
contents: read
env:
UV_FROZEN: "true"
jobs:
build:
runs-on: ubuntu-latest
if: github.repository == 'langchain-ai/langchain' || github.event_name != 'schedule'
name: '📑 Test Documentation Notebooks'
steps:
- uses: actions/checkout@v4
- name: '🐍 Set up Python + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ github.event.inputs.python_version || '3.11' }}
- name: '🔐 Authenticate to Google Cloud'
id: 'auth'
uses: google-github-actions/auth@v2
with:
credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
- name: '🔐 Configure AWS Credentials'
uses: aws-actions/configure-aws-credentials@v4
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: ${{ secrets.AWS_REGION }}
- name: '📦 Install Dependencies'
run: |
uv sync --group dev --group test
- name: '📦 Pre-download Test Files'
run: |
uv run python docs/scripts/cache_data.py
curl -s https://raw.githubusercontent.com/lerocha/chinook-database/master/ChinookDatabase/DataSources/Chinook_Sqlite.sql | sqlite3 docs/docs/how_to/Chinook.db
cp docs/docs/how_to/Chinook.db docs/docs/tutorials/Chinook.db
- name: '🔧 Prepare Notebooks for CI'
run: |
uv run python docs/scripts/prepare_notebooks_for_ci.py --comment-install-cells --working-directory ${{ github.event.inputs.working-directory || 'all' }}
- name: '🚀 Execute Notebooks'
env:
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
TAVILY_API_KEY: ${{ secrets.TAVILY_API_KEY }}
TOGETHER_API_KEY: ${{ secrets.TOGETHER_API_KEY }}
WORKING_DIRECTORY: ${{ github.event.inputs.working-directory || 'all' }}
run: |
./docs/scripts/execute_notebooks.sh $WORKING_DIRECTORY

181
.github/workflows/scheduled_test.yml vendored Normal file
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@@ -0,0 +1,181 @@
name: '⏰ Scheduled Integration Tests'
run-name: "Run Integration Tests - ${{ inputs.working-directory-force || 'all libs' }} (Python ${{ inputs.python-version-force || '3.9, 3.11' }})"
on:
workflow_dispatch: # Allows maintainers to trigger the workflow manually in GitHub UI
inputs:
working-directory-force:
type: string
description: "From which folder this pipeline executes - defaults to all in matrix - example value: libs/partners/anthropic"
python-version-force:
type: string
description: "Python version to use - defaults to 3.9 and 3.11 in matrix - example value: 3.9"
schedule:
- cron: '0 13 * * *' # Runs daily at 1PM UTC (9AM EDT/6AM PDT)
permissions:
contents: read
env:
POETRY_VERSION: "1.8.4"
UV_FROZEN: "true"
DEFAULT_LIBS: '["libs/partners/openai", "libs/partners/anthropic", "libs/partners/fireworks", "libs/partners/groq", "libs/partners/mistralai", "libs/partners/xai", "libs/partners/google-vertexai", "libs/partners/google-genai", "libs/partners/aws"]'
POETRY_LIBS: ("libs/partners/google-vertexai" "libs/partners/google-genai" "libs/partners/aws")
jobs:
# Generate dynamic test matrix based on input parameters or defaults
# Only runs on the main repo (for scheduled runs) or when manually triggered
compute-matrix:
if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
runs-on: ubuntu-latest
name: '📋 Compute Test Matrix'
outputs:
matrix: ${{ steps.set-matrix.outputs.matrix }}
steps:
- name: '🔢 Generate Python & Library Matrix'
id: set-matrix
env:
DEFAULT_LIBS: ${{ env.DEFAULT_LIBS }}
WORKING_DIRECTORY_FORCE: ${{ github.event.inputs.working-directory-force || '' }}
PYTHON_VERSION_FORCE: ${{ github.event.inputs.python-version-force || '' }}
run: |
# echo "matrix=..." where matrix is a json formatted str with keys python-version and working-directory
# python-version should default to 3.9 and 3.11, but is overridden to [PYTHON_VERSION_FORCE] if set
# working-directory should default to DEFAULT_LIBS, but is overridden to [WORKING_DIRECTORY_FORCE] if set
python_version='["3.9", "3.11"]'
working_directory="$DEFAULT_LIBS"
if [ -n "$PYTHON_VERSION_FORCE" ]; then
python_version="[\"$PYTHON_VERSION_FORCE\"]"
fi
if [ -n "$WORKING_DIRECTORY_FORCE" ]; then
working_directory="[\"$WORKING_DIRECTORY_FORCE\"]"
fi
matrix="{\"python-version\": $python_version, \"working-directory\": $working_directory}"
echo $matrix
echo "matrix=$matrix" >> $GITHUB_OUTPUT
# Run integration tests against partner libraries with live API credentials
# Tests are run with both Poetry and UV depending on the library's setup
build:
if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
name: '🐍 Python ${{ matrix.python-version }}: ${{ matrix.working-directory }}'
runs-on: ubuntu-latest
needs: [compute-matrix]
timeout-minutes: 20
strategy:
fail-fast: false
matrix:
python-version: ${{ fromJSON(needs.compute-matrix.outputs.matrix).python-version }}
working-directory: ${{ fromJSON(needs.compute-matrix.outputs.matrix).working-directory }}
steps:
- uses: actions/checkout@v4
with:
path: langchain
- uses: actions/checkout@v4
with:
repository: langchain-ai/langchain-google
path: langchain-google
- uses: actions/checkout@v4
with:
repository: langchain-ai/langchain-aws
path: langchain-aws
- name: '📦 Organize External Libraries'
run: |
rm -rf \
langchain/libs/partners/google-genai \
langchain/libs/partners/google-vertexai
mv langchain-google/libs/genai langchain/libs/partners/google-genai
mv langchain-google/libs/vertexai langchain/libs/partners/google-vertexai
mv langchain-aws/libs/aws langchain/libs/partners/aws
- name: '🐍 Set up Python ${{ matrix.python-version }} + Poetry'
if: contains(env.POETRY_LIBS, matrix.working-directory)
uses: "./langchain/.github/actions/poetry_setup"
with:
python-version: ${{ matrix.python-version }}
poetry-version: ${{ env.POETRY_VERSION }}
working-directory: langchain/${{ matrix.working-directory }}
cache-key: scheduled
- name: '🐍 Set up Python ${{ matrix.python-version }} + UV'
if: "!contains(env.POETRY_LIBS, matrix.working-directory)"
uses: "./langchain/.github/actions/uv_setup"
with:
python-version: ${{ matrix.python-version }}
- name: '🔐 Authenticate to Google Cloud'
id: 'auth'
uses: google-github-actions/auth@v2
with:
credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
- name: '🔐 Configure AWS Credentials'
uses: aws-actions/configure-aws-credentials@v4
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: ${{ secrets.AWS_REGION }}
- name: '📦 Install Dependencies (Poetry)'
if: contains(env.POETRY_LIBS, matrix.working-directory)
run: |
echo "Running scheduled tests, installing dependencies with poetry..."
cd langchain/${{ matrix.working-directory }}
poetry install --with=test_integration,test
- name: '📦 Install Dependencies (UV)'
if: "!contains(env.POETRY_LIBS, matrix.working-directory)"
run: |
echo "Running scheduled tests, installing dependencies with uv..."
cd langchain/${{ matrix.working-directory }}
uv sync --group test --group test_integration
- name: '🚀 Run Integration Tests'
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
ANTHROPIC_FILES_API_IMAGE_ID: ${{ secrets.ANTHROPIC_FILES_API_IMAGE_ID }}
ANTHROPIC_FILES_API_PDF_ID: ${{ secrets.ANTHROPIC_FILES_API_PDF_ID }}
AZURE_OPENAI_API_VERSION: ${{ secrets.AZURE_OPENAI_API_VERSION }}
AZURE_OPENAI_API_BASE: ${{ secrets.AZURE_OPENAI_API_BASE }}
AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_CHAT_DEPLOYMENT_NAME }}
AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME }}
AZURE_OPENAI_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
DEEPSEEK_API_KEY: ${{ secrets.DEEPSEEK_API_KEY }}
FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
HUGGINGFACEHUB_API_TOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}
MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }}
XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
NVIDIA_API_KEY: ${{ secrets.NVIDIA_API_KEY }}
GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
GOOGLE_SEARCH_API_KEY: ${{ secrets.GOOGLE_SEARCH_API_KEY }}
GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }}
PPLX_API_KEY: ${{ secrets.PPLX_API_KEY }}
run: |
cd langchain/${{ matrix.working-directory }}
make integration_tests
- name: '🧹 Clean up External Libraries'
# Clean up external libraries to avoid affecting git status check
run: |
rm -rf \
langchain/libs/partners/google-genai \
langchain/libs/partners/google-vertexai \
langchain/libs/partners/aws
- name: '🧹 Verify Clean Working Directory'
working-directory: langchain
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'

View File

@@ -1,8 +0,0 @@
With the deprecation of v0 docs, the following files will need to be migrated/supported
in the new docs repo:
- run_notebooks.yml: New repo should run Integration tests on code snippets?
- people.yml: Need to fix and somehow display on the new docs site
- Subsequently, `.github/actions/people/`
- _test_doc_imports.yml
- check-broken-links.yml

23
.gitignore vendored
View File

@@ -77,6 +77,10 @@ instance/
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
docs/docs/_build/
# PyBuilder
target/
@@ -157,6 +161,25 @@ data_map*
*replit*
node_modules
docs/.yarn/
docs/node_modules/
docs/.docusaurus/
docs/.cache-loader/
docs/_dist
docs/api_reference/*api_reference.rst
docs/api_reference/*.md
docs/api_reference/_build
docs/api_reference/*/
!docs/api_reference/_static/
!docs/api_reference/templates/
!docs/api_reference/themes/
!docs/api_reference/_extensions/
!docs/api_reference/scripts/
docs/docs/build
docs/docs/node_modules
docs/docs/yarn.lock
_dist
docs/docs/templates
prof
virtualenv/

View File

@@ -2,98 +2,110 @@ repos:
- repo: local
hooks:
- id: core
name: format and lint core
name: format core
language: system
entry: make -C libs/core format lint
entry: make -C libs/core format
files: ^libs/core/
pass_filenames: false
- id: langchain
name: format and lint langchain
name: format langchain
language: system
entry: make -C libs/langchain format lint
entry: make -C libs/langchain format
files: ^libs/langchain/
pass_filenames: false
- id: standard-tests
name: format and lint standard-tests
name: format standard-tests
language: system
entry: make -C libs/standard-tests format lint
entry: make -C libs/standard-tests format
files: ^libs/standard-tests/
pass_filenames: false
- id: text-splitters
name: format and lint text-splitters
name: format text-splitters
language: system
entry: make -C libs/text-splitters format lint
entry: make -C libs/text-splitters format
files: ^libs/text-splitters/
pass_filenames: false
- id: anthropic
name: format and lint partners/anthropic
name: format partners/anthropic
language: system
entry: make -C libs/partners/anthropic format lint
entry: make -C libs/partners/anthropic format
files: ^libs/partners/anthropic/
pass_filenames: false
- id: chroma
name: format and lint partners/chroma
name: format partners/chroma
language: system
entry: make -C libs/partners/chroma format lint
entry: make -C libs/partners/chroma format
files: ^libs/partners/chroma/
pass_filenames: false
- id: exa
name: format and lint partners/exa
- id: couchbase
name: format partners/couchbase
language: system
entry: make -C libs/partners/exa format lint
entry: make -C libs/partners/couchbase format
files: ^libs/partners/couchbase/
pass_filenames: false
- id: exa
name: format partners/exa
language: system
entry: make -C libs/partners/exa format
files: ^libs/partners/exa/
pass_filenames: false
- id: fireworks
name: format and lint partners/fireworks
name: format partners/fireworks
language: system
entry: make -C libs/partners/fireworks format lint
entry: make -C libs/partners/fireworks format
files: ^libs/partners/fireworks/
pass_filenames: false
- id: groq
name: format and lint partners/groq
name: format partners/groq
language: system
entry: make -C libs/partners/groq format lint
entry: make -C libs/partners/groq format
files: ^libs/partners/groq/
pass_filenames: false
- id: huggingface
name: format and lint partners/huggingface
name: format partners/huggingface
language: system
entry: make -C libs/partners/huggingface format lint
entry: make -C libs/partners/huggingface format
files: ^libs/partners/huggingface/
pass_filenames: false
- id: mistralai
name: format and lint partners/mistralai
name: format partners/mistralai
language: system
entry: make -C libs/partners/mistralai format lint
entry: make -C libs/partners/mistralai format
files: ^libs/partners/mistralai/
pass_filenames: false
- id: nomic
name: format and lint partners/nomic
name: format partners/nomic
language: system
entry: make -C libs/partners/nomic format lint
entry: make -C libs/partners/nomic format
files: ^libs/partners/nomic/
pass_filenames: false
- id: ollama
name: format and lint partners/ollama
name: format partners/ollama
language: system
entry: make -C libs/partners/ollama format lint
entry: make -C libs/partners/ollama format
files: ^libs/partners/ollama/
pass_filenames: false
- id: openai
name: format and lint partners/openai
name: format partners/openai
language: system
entry: make -C libs/partners/openai format lint
entry: make -C libs/partners/openai format
files: ^libs/partners/openai/
pass_filenames: false
- id: prompty
name: format and lint partners/prompty
name: format partners/prompty
language: system
entry: make -C libs/partners/prompty format lint
entry: make -C libs/partners/prompty format
files: ^libs/partners/prompty/
pass_filenames: false
- id: qdrant
name: format and lint partners/qdrant
name: format partners/qdrant
language: system
entry: make -C libs/partners/qdrant format lint
entry: make -C libs/partners/qdrant format
files: ^libs/partners/qdrant/
pass_filenames: false
- id: root
name: format docs, cookbook
language: system
entry: make format
files: ^(docs|cookbook)/
pass_filenames: false

25
.readthedocs.yaml Normal file
View File

@@ -0,0 +1,25 @@
# Read the Docs configuration file
# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
version: 2
# Set the version of Python and other tools you might need
build:
os: ubuntu-22.04
tools:
python: "3.11"
commands:
- mkdir -p $READTHEDOCS_OUTPUT
- cp -r api_reference_build/* $READTHEDOCS_OUTPUT
# Build documentation in the docs/ directory with Sphinx
sphinx:
configuration: docs/api_reference/conf.py
# If using Sphinx, optionally build your docs in additional formats such as PDF
formats:
- pdf
# Optionally declare the Python requirements required to build your docs
python:
install:
- requirements: docs/api_reference/requirements.txt

14
.vscode/settings.json vendored
View File

@@ -1,6 +1,7 @@
{
"python.analysis.include": [
"libs/**",
"docs/**",
"cookbook/**"
],
"python.analysis.exclude": [
@@ -9,6 +10,8 @@
"**/.pytest_cache",
"**/.*",
"_dist/**",
"docs/_build/**",
"docs/api_reference/_build/**"
],
"python.analysis.autoImportCompletions": true,
"python.analysis.typeCheckingMode": "basic",
@@ -38,6 +41,8 @@
"**/.mypy_cache": true,
"**/.ruff_cache": true,
"_dist/**": true,
"docs/_build/**": true,
"docs/api_reference/_build/**": true,
"**/node_modules": true,
"**/.git": false
},
@@ -45,6 +50,8 @@
"**/__pycache__": true,
"**/*.pyc": true,
"_dist/**": true,
"docs/_build/**": true,
"docs/api_reference/_build/**": true,
"**/node_modules": true,
"**/.git": true,
"uv.lock": true,
@@ -71,10 +78,5 @@
"editor.insertSpaces": true
},
"python.terminal.activateEnvironment": false,
"python.defaultInterpreterPath": "./.venv/bin/python",
"github.copilot.chat.commitMessageGeneration.instructions": [
{
"file": ".github/workflows/pr_lint.yml"
}
]
"python.defaultInterpreterPath": "./.venv/bin/python"
}

324
AGENTS.md
View File

@@ -1,324 +0,0 @@
# Global Development Guidelines for LangChain Projects
## Core Development Principles
### 1. Maintain Stable Public Interfaces ⚠️ CRITICAL
**Always attempt to preserve function signatures, argument positions, and names for exported/public methods.**
**Bad - Breaking Change:**
```python
def get_user(id, verbose=False): # Changed from `user_id`
pass
```
**Good - Stable Interface:**
```python
def get_user(user_id: str, verbose: bool = False) -> User:
"""Retrieve user by ID with optional verbose output."""
pass
```
**Before making ANY changes to public APIs:**
- Check if the function/class is exported in `__init__.py`
- Look for existing usage patterns in tests and examples
- Use keyword-only arguments for new parameters: `*, new_param: str = "default"`
- Mark experimental features clearly with docstring warnings (using MkDocs Material admonitions, like `!!! warning`)
🧠 *Ask yourself:* "Would this change break someone's code if they used it last week?"
### 2. Code Quality Standards
**All Python code MUST include type hints and return types.**
**Bad:**
```python
def p(u, d):
return [x for x in u if x not in d]
```
**Good:**
```python
def filter_unknown_users(users: list[str], known_users: set[str]) -> list[str]:
"""Filter out users that are not in the known users set.
Args:
users: List of user identifiers to filter.
known_users: Set of known/valid user identifiers.
Returns:
List of users that are not in the known_users set.
"""
return [user for user in users if user not in known_users]
```
**Style Requirements:**
- Use descriptive, **self-explanatory variable names**. Avoid overly short or cryptic identifiers.
- Attempt to break up complex functions (>20 lines) into smaller, focused functions where it makes sense
- Avoid unnecessary abstraction or premature optimization
- Follow existing patterns in the codebase you're modifying
### 3. Testing Requirements
**Every new feature or bugfix MUST be covered by unit tests.**
**Test Organization:**
- Unit tests: `tests/unit_tests/` (no network calls allowed)
- Integration tests: `tests/integration_tests/` (network calls permitted)
- Use `pytest` as the testing framework
**Test Quality Checklist:**
- [ ] Tests fail when your new logic is broken
- [ ] Happy path is covered
- [ ] Edge cases and error conditions are tested
- [ ] Use fixtures/mocks for external dependencies
- [ ] Tests are deterministic (no flaky tests)
Checklist questions:
- [ ] Does the test suite fail if your new logic is broken?
- [ ] Are all expected behaviors exercised (happy path, invalid input, etc)?
- [ ] Do tests use fixtures or mocks where needed?
```python
def test_filter_unknown_users():
"""Test filtering unknown users from a list."""
users = ["alice", "bob", "charlie"]
known_users = {"alice", "bob"}
result = filter_unknown_users(users, known_users)
assert result == ["charlie"]
assert len(result) == 1
```
### 4. Security and Risk Assessment
**Security Checklist:**
- No `eval()`, `exec()`, or `pickle` on user-controlled input
- Proper exception handling (no bare `except:`) and use a `msg` variable for error messages
- Remove unreachable/commented code before committing
- Race conditions or resource leaks (file handles, sockets, threads).
- Ensure proper resource cleanup (file handles, connections)
**Bad:**
```python
def load_config(path):
with open(path) as f:
return eval(f.read()) # ⚠️ Never eval config
```
**Good:**
```python
import json
def load_config(path: str) -> dict:
with open(path) as f:
return json.load(f)
```
### 5. Documentation Standards
**Use Google-style docstrings with Args section for all public functions.**
**Insufficient Documentation:**
```python
def send_email(to, msg):
"""Send an email to a recipient."""
```
**Complete Documentation:**
```python
def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
"""
Send an email to a recipient with specified priority.
Args:
to: The email address of the recipient.
msg: The message body to send.
priority: Email priority level (``'low'``, ``'normal'``, ``'high'``).
Returns:
True if email was sent successfully, False otherwise.
Raises:
InvalidEmailError: If the email address format is invalid.
SMTPConnectionError: If unable to connect to email server.
"""
```
**Documentation Guidelines:**
- Types go in function signatures, NOT in docstrings
- Focus on "why" rather than "what" in descriptions
- Document all parameters, return values, and exceptions
- Keep descriptions concise but clear
📌 *Tip:* Keep descriptions concise but clear. Only document return values if non-obvious.
### 6. Architectural Improvements
**When you encounter code that could be improved, suggest better designs:**
**Poor Design:**
```python
def process_data(data, db_conn, email_client, logger):
# Function doing too many things
validated = validate_data(data)
result = db_conn.save(validated)
email_client.send_notification(result)
logger.log(f"Processed {len(data)} items")
return result
```
**Better Design:**
```python
@dataclass
class ProcessingResult:
"""Result of data processing operation."""
items_processed: int
success: bool
errors: List[str] = field(default_factory=list)
class DataProcessor:
"""Handles data validation, storage, and notification."""
def __init__(self, db_conn: Database, email_client: EmailClient):
self.db = db_conn
self.email = email_client
def process(self, data: List[dict]) -> ProcessingResult:
"""Process and store data with notifications."""
validated = self._validate_data(data)
result = self.db.save(validated)
self._notify_completion(result)
return result
```
**Design Improvement Areas:**
If there's a **cleaner**, **more scalable**, or **simpler** design, highlight it and suggest improvements that would:
- Reduce code duplication through shared utilities
- Make unit testing easier
- Improve separation of concerns (single responsibility)
- Make unit testing easier through dependency injection
- Add clarity without adding complexity
- Prefer dataclasses for structured data
## Development Tools & Commands
### Package Management
```bash
# Add package
uv add package-name
# Sync project dependencies
uv sync
uv lock
```
### Testing
```bash
# Run unit tests (no network)
make test
# Don't run integration tests, as API keys must be set
# Run specific test file
uv run --group test pytest tests/unit_tests/test_specific.py
```
### Code Quality
```bash
# Lint code
make lint
# Format code
make format
# Type checking
uv run --group lint mypy .
```
### Dependency Management Patterns
**Local Development Dependencies:**
```toml
[tool.uv.sources]
langchain-core = { path = "../core", editable = true }
langchain-tests = { path = "../standard-tests", editable = true }
```
**For tools, use the `@tool` decorator from `langchain_core.tools`:**
```python
from langchain_core.tools import tool
@tool
def search_database(query: str) -> str:
"""Search the database for relevant information.
Args:
query: The search query string.
"""
# Implementation here
return results
```
## Commit Standards
**Use Conventional Commits format for PR titles:**
- `feat(core): add multi-tenant support`
- `fix(cli): resolve flag parsing error`
- `docs: update API usage examples`
- `docs(openai): update API usage examples`
## Framework-Specific Guidelines
- Follow the existing patterns in `langchain-core` for base abstractions
- Use `langchain_core.callbacks` for execution tracking
- Implement proper streaming support where applicable
- Avoid deprecated components like legacy `LLMChain`
### Partner Integrations
- Follow the established patterns in existing partner libraries
- Implement standard interfaces (`BaseChatModel`, `BaseEmbeddings`, etc.)
- Include comprehensive integration tests
- Document API key requirements and authentication
---
## Quick Reference Checklist
Before submitting code changes:
- [ ] **Breaking Changes**: Verified no public API changes
- [ ] **Type Hints**: All functions have complete type annotations
- [ ] **Tests**: New functionality is fully tested
- [ ] **Security**: No dangerous patterns (eval, silent failures, etc.)
- [ ] **Documentation**: Google-style docstrings for public functions
- [ ] **Code Quality**: `make lint` and `make format` pass
- [ ] **Architecture**: Suggested improvements where applicable
- [ ] **Commit Message**: Follows Conventional Commits format

View File

@@ -26,7 +26,7 @@ def get_user(user_id: str, verbose: bool = False) -> User:
- Check if the function/class is exported in `__init__.py`
- Look for existing usage patterns in tests and examples
- Use keyword-only arguments for new parameters: `*, new_param: str = "default"`
- Mark experimental features clearly with docstring warnings (using MkDocs Material admonitions, like `!!! warning`)
- Mark experimental features clearly with docstring warnings (using reStructuredText, like `.. warning::`)
🧠 *Ask yourself:* "Would this change break someone's code if they used it last week?"
@@ -166,6 +166,7 @@ def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
- Focus on "why" rather than "what" in descriptions
- Document all parameters, return values, and exceptions
- Keep descriptions concise but clear
- Use reStructuredText for docstrings to enable rich formatting
📌 *Tip:* Keep descriptions concise but clear. Only document return values if non-obvious.

119
Makefile Normal file
View File

@@ -0,0 +1,119 @@
.PHONY: all clean help docs_build docs_clean docs_linkcheck api_docs_build api_docs_clean api_docs_linkcheck spell_check spell_fix lint lint_package lint_tests format format_diff
.EXPORT_ALL_VARIABLES:
UV_FROZEN = true
## help: Show this help info.
help: Makefile
@printf "\n\033[1mUsage: make <TARGETS> ...\033[0m\n\n\033[1mTargets:\033[0m\n\n"
@sed -n 's/^## //p' $< | awk -F':' '{printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}' | sort | sed -e 's/^/ /'
## clean: Clean documentation and API documentation artifacts.
clean: docs_clean api_docs_clean
######################
# DOCUMENTATION
######################
## docs_build: Build the documentation.
docs_build: docs_clean
@echo "📚 Building LangChain documentation..."
cd docs && make build
@echo "✅ Documentation build complete!"
## docs_clean: Clean the documentation build artifacts.
docs_clean:
@echo "🧹 Cleaning documentation artifacts..."
cd docs && make clean
@echo "✅ LangChain documentation cleaned"
## docs_linkcheck: Run linkchecker on the documentation.
docs_linkcheck:
@echo "🔗 Checking documentation links..."
@if [ -d _dist/docs ]; then \
uv run --group test linkchecker _dist/docs/ --ignore-url node_modules; \
else \
echo "⚠️ Documentation not built. Run 'make docs_build' first."; \
exit 1; \
fi
@echo "✅ Link check complete"
## api_docs_build: Build the API Reference documentation.
api_docs_build: clean
@echo "📖 Building API Reference documentation..."
uv pip install -e libs/cli
uv run --group docs python docs/api_reference/create_api_rst.py
cd docs/api_reference && uv run --group docs make html
uv run --group docs python docs/api_reference/scripts/custom_formatter.py docs/api_reference/_build/html/
@echo "✅ API documentation built"
@echo "🌐 Opening documentation in browser..."
open docs/api_reference/_build/html/reference.html
API_PKG ?= text-splitters
api_docs_quick_preview: clean
@echo "⚡ Building quick API preview for $(API_PKG)..."
uv run --group docs python docs/api_reference/create_api_rst.py $(API_PKG)
cd docs/api_reference && uv run --group docs make html
uv run --group docs python docs/api_reference/scripts/custom_formatter.py docs/api_reference/_build/html/
@echo "🌐 Opening preview in browser..."
open docs/api_reference/_build/html/reference.html
## api_docs_clean: Clean the API Reference documentation build artifacts.
api_docs_clean:
@echo "🧹 Cleaning API documentation artifacts..."
find ./docs/api_reference -name '*_api_reference.rst' -delete
git clean -fdX ./docs/api_reference
rm -f docs/api_reference/index.md
@echo "✅ API documentation cleaned"
## api_docs_linkcheck: Run linkchecker on the API Reference documentation.
api_docs_linkcheck:
@echo "🔗 Checking API documentation links..."
@if [ -f docs/api_reference/_build/html/index.html ]; then \
uv run --group test linkchecker docs/api_reference/_build/html/index.html; \
else \
echo "⚠️ API documentation not built. Run 'make api_docs_build' first."; \
exit 1; \
fi
@echo "✅ API link check complete"
## spell_check: Run codespell on the project.
spell_check:
@echo "✏️ Checking spelling across project..."
uv run --group codespell codespell --toml pyproject.toml
@echo "✅ Spell check complete"
## spell_fix: Run codespell on the project and fix the errors.
spell_fix:
@echo "✏️ Fixing spelling errors across project..."
uv run --group codespell codespell --toml pyproject.toml -w
@echo "✅ Spelling errors fixed"
######################
# LINTING AND FORMATTING
######################
## lint: Run linting on the project.
lint lint_package lint_tests:
@echo "🔍 Running code linting and checks..."
uv run --group lint ruff check docs cookbook
uv run --group lint ruff format docs cookbook cookbook --diff
git --no-pager grep 'from langchain import' docs cookbook | grep -vE 'from langchain import (hub)' && echo "Error: no importing langchain from root in docs, except for hub" && exit 1 || exit 0
git --no-pager grep 'api.python.langchain.com' -- docs/docs ':!docs/docs/additional_resources/arxiv_references.mdx' ':!docs/docs/integrations/document_loaders/sitemap.ipynb' || exit 0 && \
echo "Error: you should link python.langchain.com/api_reference, not api.python.langchain.com in the docs" && \
exit 1
@echo "✅ Linting complete"
## format: Format the project files.
format format_diff:
@echo "🎨 Formatting project files..."
uv run --group lint ruff format docs cookbook
uv run --group lint ruff check --fix docs cookbook
@echo "✅ Formatting complete"
update-package-downloads:
@echo "📊 Updating package download statistics..."
uv run python docs/scripts/packages_yml_get_downloads.py
@echo "✅ Package downloads updated"

114
README.md
View File

@@ -1,77 +1,87 @@
<p align="center">
<picture>
<source media="(prefers-color-scheme: light)" srcset=".github/images/logo-dark.svg">
<source media="(prefers-color-scheme: dark)" srcset=".github/images/logo-light.svg">
<img alt="LangChain Logo" src=".github/images/logo-dark.svg" width="80%">
</picture>
</p>
<picture>
<source media="(prefers-color-scheme: light)" srcset="docs/static/img/logo-dark.svg">
<source media="(prefers-color-scheme: dark)" srcset="docs/static/img/logo-light.svg">
<img alt="LangChain Logo" src="docs/static/img/logo-dark.svg" width="80%">
</picture>
<p align="center">
The platform for reliable agents.
</p>
<div>
<br>
</div>
<p align="center">
<a href="https://opensource.org/licenses/MIT" target="_blank">
<img src="https://img.shields.io/pypi/l/langchain-core?style=flat-square" alt="PyPI - License">
</a>
<a href="https://pypistats.org/packages/langchain-core" target="_blank">
<img src="https://img.shields.io/pepy/dt/langchain" alt="PyPI - Downloads">
</a>
<a href="https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchain" target="_blank">
<img src="https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode&style=flat-square" alt="Open in Dev Containers">
</a>
<a href="https://codespaces.new/langchain-ai/langchain" target="_blank">
<img src="https://github.com/codespaces/badge.svg" alt="Open in Github Codespace" title="Open in Github Codespace" width="150" height="20">
</a>
<a href="https://codspeed.io/langchain-ai/langchain" target="_blank">
<img src="https://img.shields.io/endpoint?url=https://codspeed.io/badge.json" alt="CodSpeed Badge">
</a>
<a href="https://twitter.com/langchainai" target="_blank">
<img src="https://img.shields.io/twitter/url/https/twitter.com/langchainai.svg?style=social&label=Follow%20%40LangChainAI" alt="Twitter / X">
</a>
</p>
[![Release Notes](https://img.shields.io/github/release/langchain-ai/langchain?style=flat-square)](https://github.com/langchain-ai/langchain/releases)
[![CI](https://github.com/langchain-ai/langchain/actions/workflows/check_diffs.yml/badge.svg)](https://github.com/langchain-ai/langchain/actions/workflows/check_diffs.yml)
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[<img src="https://github.com/codespaces/badge.svg" alt="Open in Github Codespace" title="Open in Github Codespace" width="150" height="20">](https://codespaces.new/langchain-ai/langchain)
[![Twitter](https://img.shields.io/twitter/url/https/twitter.com/langchainai.svg?style=social&label=Follow%20%40LangChainAI)](https://twitter.com/langchainai)
[![CodSpeed Badge](https://img.shields.io/endpoint?url=https://codspeed.io/badge.json)](https://codspeed.io/langchain-ai/langchain)
LangChain is a framework for building LLM-powered applications. It helps you chain together interoperable components and third-party integrations to simplify AI application development — all while future-proofing decisions as the underlying technology evolves.
> [!NOTE]
> Looking for the JS/TS library? Check out [LangChain.js](https://github.com/langchain-ai/langchainjs).
LangChain is a framework for building LLM-powered applications. It helps you chain
together interoperable components and third-party integrations to simplify AI
application development — all while future-proofing decisions as the underlying
technology evolves.
```bash
pip install -U langchain
```
---
**Documentation**: To learn more about LangChain, check out [the docs](https://docs.langchain.com/).
If you're looking for more advanced customization or agent orchestration, check out [LangGraph](https://langchain-ai.github.io/langgraph/), our framework for building controllable agent workflows.
> [!NOTE]
> Looking for the JS/TS library? Check out [LangChain.js](https://github.com/langchain-ai/langchainjs).
To learn more about LangChain, check out
[the docs](https://python.langchain.com/docs/introduction/). If youre looking for more
advanced customization or agent orchestration, check out
[LangGraph](https://langchain-ai.github.io/langgraph/), our framework for building
controllable agent workflows.
## Why use LangChain?
LangChain helps developers build applications powered by LLMs through a standard interface for models, embeddings, vector stores, and more.
LangChain helps developers build applications powered by LLMs through a standard
interface for models, embeddings, vector stores, and more.
Use LangChain for:
- **Real-time data augmentation**. Easily connect LLMs to diverse data sources and external/internal systems, drawing from LangChains vast library of integrations with model providers, tools, vector stores, retrievers, and more.
- **Model interoperability**. Swap models in and out as your engineering team experiments to find the best choice for your applications needs. As the industry frontier evolves, adapt quickly — LangChains abstractions keep you moving without losing momentum.
- **Real-time data augmentation**. Easily connect LLMs to diverse data sources and
external / internal systems, drawing from LangChains vast library of integrations with
model providers, tools, vector stores, retrievers, and more.
- **Model interoperability**. Swap models in and out as your engineering team
experiments to find the best choice for your applications needs. As the industry
frontier evolves, adapt quickly — LangChains abstractions keep you moving without
losing momentum.
## LangChains ecosystem
While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications.
While the LangChain framework can be used standalone, it also integrates seamlessly
with any LangChain product, giving developers a full suite of tools when building LLM
applications.
To improve your LLM application development, pair LangChain with:
- [LangSmith](https://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](https://langchain-ai.github.io/langgraph/) - Build agents that can reliably handle complex tasks with LangGraph, our low-level agent orchestration framework. LangGraph offers customizable architecture, long-term memory, and human-in-the-loop workflows — and is trusted in production by companies like LinkedIn, Uber, Klarna, and GitLab.
- [LangGraph Platform](https://docs.langchain.com/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/).
- [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](https://langchain-ai.github.io/langgraph/) - Build agents that can
reliably handle complex tasks with LangGraph, our low-level agent orchestration
framework. LangGraph offers customizable architecture, long-term memory, and
human-in-the-loop workflows — and is trusted in production by companies like LinkedIn,
Uber, Klarna, and GitLab.
- [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/).
## Additional resources
- [Conceptual Guides](https://docs.langchain.com/oss/python/langchain/overview): Explanations of key
concepts behind the LangChain framework.
- [Tutorials](https://docs.langchain.com/oss/python/learn): Simple walkthroughs with
- [Tutorials](https://python.langchain.com/docs/tutorials/): Simple walkthroughs with
guided examples on getting started with LangChain.
- [API Reference](https://reference.langchain.com/python/): Detailed reference on
navigating base packages and integrations for LangChain.
- [How-to Guides](https://python.langchain.com/docs/how_to/): Quick, actionable code
snippets for topics such as tool calling, RAG use cases, and more.
- [Conceptual Guides](https://python.langchain.com/docs/concepts/): Explanations of key
concepts behind the LangChain framework.
- [LangChain Forum](https://forum.langchain.com/): Connect with the community and share all of your technical questions, ideas, and feedback.
- [Chat LangChain](https://chat.langchain.com/): Ask questions & chat with our documentation.
- [API Reference](https://python.langchain.com/api_reference/): Detailed reference on
navigating base packages and integrations for LangChain.

View File

@@ -4,9 +4,9 @@ LangChain has a large ecosystem of integrations with various external resources
## Best practices
When building such applications, developers should remember to follow good security practices:
When building such applications developers should remember to follow good security practices:
* [**Limit Permissions**](https://en.wikipedia.org/wiki/Principle_of_least_privilege): Scope permissions specifically to the application's need. Granting broad or excessive permissions can introduce significant security vulnerabilities. To avoid such vulnerabilities, consider using read-only credentials, disallowing access to sensitive resources, using sandboxing techniques (such as running inside a container), specifying proxy configurations to control external requests, etc., as appropriate for your application.
* [**Limit Permissions**](https://en.wikipedia.org/wiki/Principle_of_least_privilege): Scope permissions specifically to the application's need. Granting broad or excessive permissions can introduce significant security vulnerabilities. To avoid such vulnerabilities, consider using read-only credentials, disallowing access to sensitive resources, using sandboxing techniques (such as running inside a container), specifying proxy configurations to control external requests, etc. as appropriate for your application.
* **Anticipate Potential Misuse**: Just as humans can err, so can Large Language Models (LLMs). Always assume that any system access or credentials may be used in any way allowed by the permissions they are assigned. For example, if a pair of database credentials allows deleting data, it's safest to assume that any LLM able to use those credentials may in fact delete data.
* [**Defense in Depth**](https://en.wikipedia.org/wiki/Defense_in_depth_(computing)): No security technique is perfect. Fine-tuning and good chain design can reduce, but not eliminate, the odds that a Large Language Model (LLM) may make a mistake. It's best to combine multiple layered security approaches rather than relying on any single layer of defense to ensure security. For example: use both read-only permissions and sandboxing to ensure that LLMs are only able to access data that is explicitly meant for them to use.
@@ -22,7 +22,9 @@ Example scenarios with mitigation strategies:
* A user may ask an agent with write access to an external API to write malicious data to the API, or delete data from that API. To mitigate, give the agent read-only API keys, or limit it to only use endpoints that are already resistant to such misuse.
* A user may ask an agent with access to a database to drop a table or mutate the schema. To mitigate, scope the credentials to only the tables that the agent needs to access and consider issuing READ-ONLY credentials.
If you're building applications that access external resources like file systems, APIs or databases, consider speaking with your company's security team to determine how to best design and secure your applications.
If you're building applications that access external resources like file systems, APIs
or databases, consider speaking with your company's security team to determine how to best
design and secure your applications.
## Reporting OSS Vulnerabilities
@@ -35,8 +37,10 @@ open source projects at [huntr](https://huntr.com/bounties/disclose/?target=http
Before reporting a vulnerability, please review:
1) In-Scope Targets and Out-of-Scope Targets below.
2) The [langchain-ai/langchain](https://docs.langchain.com/oss/python/contributing/code#repository-structure) monorepo structure.
3) The [Best Practices](#best-practices) above to understand what we consider to be a security vulnerability vs. developer responsibility.
2) The [langchain-ai/langchain](https://python.langchain.com/docs/contributing/repo_structure) monorepo structure.
3) The [Best Practices](#best-practices) above to
understand what we consider to be a security vulnerability vs. developer
responsibility.
### In-Scope Targets
@@ -63,7 +67,8 @@ All out of scope targets defined by huntr as well as:
for more details, but generally tools interact with the real world. Developers are
expected to understand the security implications of their code and are responsible
for the security of their tools.
* Code documented with security notices. This will be decided on a case-by-case basis, but likely will not be eligible for a bounty as the code is already
* Code documented with security notices. This will be decided on a case by
case basis, but likely will not be eligible for a bounty as the code is already
documented with guidelines for developers that should be followed for making their
application secure.
* Any LangSmith related repositories or APIs (see [Reporting LangSmith Vulnerabilities](#reporting-langsmith-vulnerabilities)).

View File

@@ -64,4 +64,3 @@ Notebook | Description
[visual_RAG_vdms.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/visual_RAG_vdms.ipynb) | Performs Visual Retrieval-Augmented-Generation (RAG) using videos and scene descriptions generated by open source models.
[contextual_rag.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/contextual_rag.ipynb) | Performs contextual retrieval-augmented generation (RAG) prepending chunk-specific explanatory context to each chunk before embedding.
[rag-agents-locally-on-intel-cpu.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/local_rag_agents_intel_cpu.ipynb) | Build a RAG agent locally with open source models that routes questions through one of two paths to find answers. The agent generates answers based on documents retrieved from either the vector database or retrieved from web search. If the vector database lacks relevant information, the agent opts for web search. Open-source models for LLM and embeddings are used locally on an Intel Xeon CPU to execute this pipeline.
[rag_mlflow_tracking_evaluation.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/rag_mlflow_tracking_evaluation.ipynb) | Guide on how to create a RAG pipeline and track + evaluate it with MLflow.

View File

@@ -79,17 +79,6 @@
"tool_executor = ToolExecutor(tools)"
]
},
{
"cell_type": "markdown",
"id": "168152fc",
"metadata": {},
"source": [
"📘 **Note on `SystemMessage` usage with LangGraph-based agents**\n",
"\n",
"When constructing the `messages` list for an agent, you *must* manually include any `SystemMessage`s.\n",
"Unlike some agent executors in LangChain that set a default, LangGraph requires explicit inclusion."
]
},
{
"cell_type": "markdown",
"id": "fe6e8f78-1ef7-42ad-b2bf-835ed5850553",

View File

@@ -47,12 +47,10 @@
"source": [
"### Prerequisites\n",
"\n",
"You'll need to install `langchain-oracledb` with `python -m pip install -U langchain-oracledb` to use this integration.\n",
"\n",
"The `python-oracledb` driver is installed automatically as a dependency of langchain-oracledb.\n",
"Please install the Oracle Database [python-oracledb driver](https://pypi.org/project/oracledb/) to use LangChain with Oracle AI Vector Search:\n",
"\n",
"```\n",
"$ python -m pip install -U langchain-oracledb\n",
"$ python -m pip install --upgrade oracledb\n",
"```"
]
},
@@ -219,7 +217,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_oracledb.embeddings.oracleai import OracleEmbeddings\n",
"from langchain_community.embeddings.oracleai import OracleEmbeddings\n",
"\n",
"# please update with your related information\n",
"# make sure that you have onnx file in the system\n",
@@ -298,7 +296,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_oracledb.document_loaders.oracleai import OracleDocLoader\n",
"from langchain_community.document_loaders.oracleai import OracleDocLoader\n",
"from langchain_core.documents import Document\n",
"\n",
"# loading from Oracle Database table\n",
@@ -356,7 +354,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_oracledb.utilities.oracleai import OracleSummary\n",
"from langchain_community.utilities.oracleai import OracleSummary\n",
"from langchain_core.documents import Document\n",
"\n",
"# using 'database' provider\n",
@@ -397,7 +395,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_oracledb.document_loaders.oracleai import OracleTextSplitter\n",
"from langchain_community.document_loaders.oracleai import OracleTextSplitter\n",
"from langchain_core.documents import Document\n",
"\n",
"# split by default parameters\n",
@@ -454,7 +452,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_oracledb.embeddings.oracleai import OracleEmbeddings\n",
"from langchain_community.embeddings.oracleai import OracleEmbeddings\n",
"from langchain_core.documents import Document\n",
"\n",
"# using ONNX model loaded to Oracle Database\n",
@@ -500,14 +498,14 @@
"import sys\n",
"\n",
"import oracledb\n",
"from langchain_oracledb.document_loaders.oracleai import (\n",
"from langchain_community.document_loaders.oracleai import (\n",
" OracleDocLoader,\n",
" OracleTextSplitter,\n",
")\n",
"from langchain_oracledb.embeddings.oracleai import OracleEmbeddings\n",
"from langchain_oracledb.utilities.oracleai import OracleSummary\n",
"from langchain_oracledb.vectorstores import oraclevs\n",
"from langchain_oracledb.vectorstores.oraclevs import OracleVS\n",
"from langchain_community.embeddings.oracleai import OracleEmbeddings\n",
"from langchain_community.utilities.oracleai import OracleSummary\n",
"from langchain_community.vectorstores import oraclevs\n",
"from langchain_community.vectorstores.oraclevs import OracleVS\n",
"from langchain_community.vectorstores.utils import DistanceStrategy\n",
"from langchain_core.documents import Document"
]
@@ -679,19 +677,19 @@
"outputs": [],
"source": [
"query = \"What is Oracle AI Vector Store?\"\n",
"db_filter = {\"document_id\": \"1\"}\n",
"filter = {\"document_id\": [\"1\"]}\n",
"\n",
"# Similarity search without a filter\n",
"print(vectorstore.similarity_search(query, 1))\n",
"\n",
"# Similarity search with a filter\n",
"print(vectorstore.similarity_search(query, 1, filter=db_filter))\n",
"print(vectorstore.similarity_search(query, 1, filter=filter))\n",
"\n",
"# Similarity search with relevance score\n",
"print(vectorstore.similarity_search_with_score(query, 1))\n",
"\n",
"# Similarity search with relevance score with filter\n",
"print(vectorstore.similarity_search_with_score(query, 1, filter=db_filter))\n",
"print(vectorstore.similarity_search_with_score(query, 1, filter=filter))\n",
"\n",
"# Max marginal relevance search\n",
"print(vectorstore.max_marginal_relevance_search(query, 1, fetch_k=20, lambda_mult=0.5))\n",
@@ -699,7 +697,7 @@
"# Max marginal relevance search with filter\n",
"print(\n",
" vectorstore.max_marginal_relevance_search(\n",
" query, 1, fetch_k=20, lambda_mult=0.5, filter=db_filter\n",
" query, 1, fetch_k=20, lambda_mult=0.5, filter=filter\n",
" )\n",
")"
]

View File

@@ -1,455 +0,0 @@
{
"cells": [
{
"cell_type": "markdown",
"id": "3716230e",
"metadata": {},
"source": [
"# RAG Pipeline with MLflow Tracking, Tracing & Evaluation\n",
"\n",
"This notebook demonstrates how to build a complete Retrieval-Augmented Generation (RAG) pipeline using LangChain and integrate it with MLflow for experiment tracking, tracing, and evaluation.\n",
"\n",
"\n",
"- **RAG Pipeline Construction**: Build a complete RAG system using LangChain components\n",
"- **MLflow Integration**: Track experiments, parameters, and artifacts\n",
"- **Tracing**: Monitor inputs, outputs, retrieved documents, scores, prompts, and timings\n",
"- **Evaluation**: Use MLflow's built-in scorers to assess RAG performance\n",
"- **Best Practices**: Implement proper configuration management and reproducible experiments\n",
"\n",
"We'll build a RAG system that can answer questions about academic papers by:\n",
"1. Loading and chunking documents from ArXiv\n",
"2. Creating embeddings and a vector store\n",
"3. Setting up a retrieval-augmented generation chain\n",
"4. Tracking all experiments with MLflow\n",
"5. Evaluating the system's performance\n",
"\n",
"![System Diagram](https://miro.medium.com/v2/resize:fit:720/format:webp/1*eiw86PP4hrBBxhjTjP0JUQ.png)"
]
},
{
"cell_type": "markdown",
"id": "2f7561c4",
"metadata": {},
"source": [
"#### Setup"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0814ebe9",
"metadata": {},
"outputs": [],
"source": [
"%pip install -U langchain mlflow langchain-community arxiv pymupdf langchain-text-splitters langchain-openai"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "747399b6",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import mlflow\n",
"from mlflow.genai.scorers import RelevanceToQuery, Correctness, ExpectationsGuidelines\n",
"from langchain_community.document_loaders import ArxivLoader\n",
"from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
"from langchain_core.vectorstores import InMemoryVectorStore\n",
"from langchain_openai import OpenAIEmbeddings, ChatOpenAI\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
"from langchain_core.output_parsers import StrOutputParser"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4141ee05",
"metadata": {},
"outputs": [],
"source": [
"os.environ[\"OPENAI_API_KEY\"] = \"<YOUR OPENAI API KEY>\"\n",
"\n",
"mlflow.set_experiment(\"LangChain-RAG-MLflow\")\n",
"mlflow.langchain.autolog()"
]
},
{
"cell_type": "markdown",
"id": "dd5eb41b",
"metadata": {},
"source": [
"Define all hyperparameters and configuration in a centralized dictionary. This makes it easy to:\n",
"- Track different experiment configurations\n",
"- Reproduce results\n",
"- Perform hyperparameter tuning\n",
"\n",
"**Key Parameters**:\n",
"- `chunk_size`: Size of text chunks for document splitting\n",
"- `chunk_overlap`: Overlap between consecutive chunks\n",
"- `retriever_k`: Number of documents to retrieve\n",
"- `embeddings_model`: OpenAI embedding model\n",
"- `llm`: Language model for generation\n",
"- `temperature`: Sampling temperature for the LLM"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "6dcdc5d8",
"metadata": {},
"outputs": [],
"source": [
"CONFIG = {\n",
" \"chunk_size\": 400,\n",
" \"chunk_overlap\": 80,\n",
" \"retriever_k\": 3,\n",
" \"embeddings_model\": \"text-embedding-3-small\",\n",
" \"system_prompt\": \"You are a helpful assistant. Use the following context to answer the question. Use three sentences maximum and keep the answer concise.\",\n",
" \"llm\": \"gpt-5-nano\",\n",
" \"temperature\": 0,\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "8a2985f1",
"metadata": {},
"source": [
"#### ArXiv Dcoument Loading and Processing"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "1f32aa36",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'Published': '2023-08-02', 'Title': 'Attention Is All You Need', 'Authors': 'Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin', 'Summary': 'The dominant sequence transduction models are based on complex recurrent or\\nconvolutional neural networks in an encoder-decoder configuration. The best\\nperforming models also connect the encoder and decoder through an attention\\nmechanism. We propose a new simple network architecture, the Transformer, based\\nsolely on attention mechanisms, dispensing with recurrence and convolutions\\nentirely. Experiments on two machine translation tasks show these models to be\\nsuperior in quality while being more parallelizable and requiring significantly\\nless time to train. Our model achieves 28.4 BLEU on the WMT 2014\\nEnglish-to-German translation task, improving over the existing best results,\\nincluding ensembles by over 2 BLEU. On the WMT 2014 English-to-French\\ntranslation task, our model establishes a new single-model state-of-the-art\\nBLEU score of 41.8 after training for 3.5 days on eight GPUs, a small fraction\\nof the training costs of the best models from the literature. We show that the\\nTransformer generalizes well to other tasks by applying it successfully to\\nEnglish constituency parsing both with large and limited training data.'}\n"
]
}
],
"source": [
"# Load documents from ArXiv\n",
"loader = ArxivLoader(\n",
" query=\"1706.03762\",\n",
" load_max_docs=1,\n",
")\n",
"docs = loader.load()\n",
"print(docs[0].metadata)\n",
"\n",
"# Split documents into chunks\n",
"splitter = RecursiveCharacterTextSplitter(\n",
" chunk_size=CONFIG[\"chunk_size\"],\n",
" chunk_overlap=CONFIG[\"chunk_overlap\"],\n",
")\n",
"chunks = splitter.split_documents(docs)\n",
"\n",
"\n",
"# Join chunks into a single string\n",
"def join_chunks(chunks):\n",
" return \"\\n\\n\".join([chunk.page_content for chunk in chunks])"
]
},
{
"cell_type": "markdown",
"id": "6e194ab4",
"metadata": {},
"source": [
"#### Vector Store and Retriever Setup"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "26dfbeaa",
"metadata": {},
"outputs": [],
"source": [
"# Create embeddings\n",
"embeddings = OpenAIEmbeddings(model=CONFIG[\"embeddings_model\"])\n",
"\n",
"# Create vector store from documents\n",
"vectorstore = InMemoryVectorStore.from_documents(\n",
" chunks,\n",
" embedding=embeddings,\n",
")\n",
"\n",
"# Create retriever\n",
"retriever = vectorstore.as_retriever(search_kwargs={\"k\": CONFIG[\"retriever_k\"]})"
]
},
{
"cell_type": "markdown",
"id": "bc1f181b",
"metadata": {},
"source": [
"#### RAG Chain Construction using [LCEL](https://python.langchain.com/docs/concepts/lcel/)\n",
"\n",
"Flow:\n",
"1. Query → Retriever (finds relevant chunks)\n",
"2. Chunks → join_chunks (creates context)\n",
"3. Context + Query → Prompt Template\n",
"4. Prompt → Language Model → Response\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "6a810dc3",
"metadata": {},
"outputs": [],
"source": [
"# Initialize the language model\n",
"llm = ChatOpenAI(model=CONFIG[\"llm\"], temperature=CONFIG[\"temperature\"])\n",
"\n",
"# Create the prompt template\n",
"prompt = ChatPromptTemplate.from_messages(\n",
" [\n",
" (\"system\", CONFIG[\"system_prompt\"] + \"\\n\\nContext:\\n{context}\\n\\n\"),\n",
" (\"human\", \"\\n{question}\\n\"),\n",
" ]\n",
")\n",
"\n",
"# Construct the RAG chain\n",
"rag_chain = (\n",
" {\n",
" \"context\": retriever | RunnableLambda(join_chunks),\n",
" \"question\": RunnablePassthrough(),\n",
" }\n",
" | prompt\n",
" | llm\n",
" | StrOutputParser()\n",
")"
]
},
{
"cell_type": "markdown",
"id": "c04bd019",
"metadata": {},
"source": [
"#### Prediction Function with MLflow Tracing\n",
"\n",
"Create a prediction function decorated with `@mlflow.trace` to automatically log:\n",
"- Input queries\n",
"- Retrieved documents\n",
"- Generated responses\n",
"- Execution time\n",
"- Chain intermediate steps"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "7b45fc04",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Question: What is the main idea of the paper?\n",
"Response: The main idea is to replace recurrent/convolutional sequence models with a pure attention-based architecture called the Transformer. It uses self-attention to model dependencies between all positions in the input and output, enabling full parallelization and better handling of long-range relations. This approach achieves strong results on translation and can extend to other modalities.\n"
]
}
],
"source": [
"@mlflow.trace\n",
"def predict_fn(question: str) -> str:\n",
" return rag_chain.invoke(question)\n",
"\n",
"\n",
"# Test the prediction function\n",
"sample_question = \"What is the main idea of the paper?\"\n",
"response = predict_fn(sample_question)\n",
"print(f\"Question: {sample_question}\")\n",
"print(f\"Response: {response}\")"
]
},
{
"cell_type": "markdown",
"id": "421469de",
"metadata": {},
"source": [
"#### Evaluation Dataset and Scoring\n",
"\n",
"Define an evaluation dataset and run systematic evaluation using [MLflow's built-in scorers](https://mlflow.org/docs/latest/genai/eval-monitor/scorers/llm-judge/predefined/#available-scorers):\n",
"\n",
"<u>Evaluation Components:</u>\n",
"- **Dataset**: Questions with expected concepts and facts\n",
"- **Scorers**: \n",
" - `RelevanceToQuery`: Measures how relevant the response is to the question\n",
" - `Correctness`: Evaluates factual accuracy of the response\n",
" - `ExpectationsGuidelines`: Checks that output matches expectation guidelines\n",
"\n",
"<u>Best Practices:</u>\n",
"- Create diverse test cases covering different query types\n",
"- Include expected concepts to guide evaluation\n",
"- Use multiple scoring metrics for comprehensive assessment"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "5c1dc4f2",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2025/08/23 20:14:39 INFO mlflow.models.evaluation.utils.trace: Auto tracing is temporarily enabled during the model evaluation for computing some metrics and debugging. To disable tracing, call `mlflow.autolog(disable=True)`.\n",
"2025/08/23 20:14:39 INFO mlflow.genai.utils.data_validation: Testing model prediction with the first sample in the dataset.\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "2b6c6687efa24796b39c7951d589d481",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Evaluating: 0%| | 0/3 [Elapsed: 00:00, Remaining: ?] "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"✨ Evaluation completed.\n",
"\n",
"Metrics and evaluation results are logged to the MLflow run:\n",
" Run name: \u001b[94mbaseline_eval\u001b[0m\n",
" Run ID: \u001b[94ma2218d9f24c9415f8040d3b77af103a9\u001b[0m\n",
"\n",
"To view the detailed evaluation results with sample-wise scores,\n",
"open the \u001b[93m\u001b[1mTraces\u001b[0m tab in the Run page in the MLflow UI.\n",
"\n"
]
}
],
"source": [
"# Define evaluation dataset\n",
"eval_dataset = [\n",
" {\n",
" \"inputs\": {\"question\": \"What is the main idea of the paper?\"},\n",
" \"expectations\": {\n",
" \"key_concepts\": [\"attention mechanism\", \"transformer\", \"neural network\"],\n",
" \"expected_facts\": [\n",
" \"attention mechanism is a key component of the transformer model\"\n",
" ],\n",
" \"guidelines\": [\"The response must be factual and concise\"],\n",
" },\n",
" },\n",
" {\n",
" \"inputs\": {\n",
" \"question\": \"What's the difference between a transformer and a recurrent neural network?\"\n",
" },\n",
" \"expectations\": {\n",
" \"key_concepts\": [\"sequential\", \"attention mechanism\", \"hidden state\"],\n",
" \"expected_facts\": [\n",
" \"transformer processes data in parallel while RNN processes data sequentially\"\n",
" ],\n",
" \"guidelines\": [\n",
" \"The response must be factual and focus on the difference between the two models\"\n",
" ],\n",
" },\n",
" },\n",
" {\n",
" \"inputs\": {\"question\": \"What does the attention mechanism do?\"},\n",
" \"expectations\": {\n",
" \"key_concepts\": [\"query\", \"key\", \"value\", \"relationship\", \"similarity\"],\n",
" \"expected_facts\": [\n",
" \"attention allows the model to weigh the importance of different parts of the input sequence when processing it\"\n",
" ],\n",
" \"guidelines\": [\n",
" \"The response must be factual and explain the concept of attention\"\n",
" ],\n",
" },\n",
" },\n",
"]\n",
"\n",
"# Run evaluation with MLflow\n",
"with mlflow.start_run(run_name=\"baseline_eval\") as run:\n",
" # Log configuration parameters\n",
" mlflow.log_params(CONFIG)\n",
"\n",
" # Run evaluation\n",
" results = mlflow.genai.evaluate(\n",
" data=eval_dataset,\n",
" predict_fn=predict_fn,\n",
" scorers=[RelevanceToQuery(), Correctness(), ExpectationsGuidelines()],\n",
" )"
]
},
{
"cell_type": "markdown",
"id": "52b137c7",
"metadata": {},
"source": [
"#### Launch MLflow UI to check out the results\n",
"\n",
"<u>What you'll see in the UI:</u>\n",
"- **Experiments**: Compare different RAG configurations\n",
"- **Runs**: Individual experiment runs with metrics and parameters\n",
"- **Traces**: Detailed execution traces showing retrieval and generation steps\n",
"- **Evaluation Results**: Scoring metrics and detailed comparisons\n",
"- **Artifacts**: Saved models, datasets, and other files\n",
"\n",
"Navigate to `http://localhost:5000` after running the command below."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "817c3799",
"metadata": {},
"outputs": [],
"source": [
"!mlflow ui"
]
},
{
"cell_type": "markdown",
"id": "c75861e3",
"metadata": {},
"source": [
"You should see something like this\n",
"\n",
"![MLflow UI image](https://miro.medium.com/v2/resize:fit:720/format:webp/1*Cx7MMy53pAP7150x_hvztA.png)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "venv",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

3
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/.quarto/
src/supabase.d.ts
build

1
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nodeLinker: node-modules

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# We build the docs in these stages:
# 1. Install vercel and python dependencies
# 2. Copy files from "source dir" to "intermediate dir"
# 2. Generate files like model feat table, etc in "intermediate dir"
# 3. Copy files to their right spots (e.g. langserve readme) in "intermediate dir"
# 4. Build the docs from "intermediate dir" to "output dir"
SOURCE_DIR = docs/
INTERMEDIATE_DIR = build/intermediate/docs
OUTPUT_NEW_DIR = build/output-new
OUTPUT_NEW_DOCS_DIR = $(OUTPUT_NEW_DIR)/docs
PYTHON = .venv/bin/python
PORT ?= 3001
clean:
rm -rf build
clean-cache:
rm -rf build .venv/deps_installed
install-vercel-deps:
yum -y -q update
yum -y -q install gcc bzip2-devel libffi-devel zlib-devel wget tar gzip rsync -y
install-py-deps:
@echo "📦 Installing Python dependencies..."
@if [ ! -d .venv ]; then python3 -m venv .venv; fi
@if [ ! -f .venv/deps_installed ]; then \
$(PYTHON) -m pip install -q --upgrade pip --disable-pip-version-check; \
$(PYTHON) -m pip install -q --upgrade uv; \
$(PYTHON) -m uv pip install -q --pre -r vercel_requirements.txt; \
$(PYTHON) -m uv pip install -q --pre $$($(PYTHON) scripts/partner_deps_list.py) --overrides vercel_overrides.txt; \
touch .venv/deps_installed; \
fi
@echo "✅ Dependencies installed"
generate-files:
@echo "📄 Generating documentation files..."
mkdir -p $(INTERMEDIATE_DIR)
cp -rp $(SOURCE_DIR)/* $(INTERMEDIATE_DIR)
@if [ ! -f build/langserve_readme_cache.md ] || [ $$(find build/langserve_readme_cache.md -mtime +1 -print) ]; then \
echo "🌐 Downloading LangServe README..."; \
curl -s https://raw.githubusercontent.com/langchain-ai/langserve/main/README.md | sed 's/<=/\&lt;=/g' > build/langserve_readme_cache.md; \
fi
cp build/langserve_readme_cache.md $(INTERMEDIATE_DIR)/langserve.md
cp ../SECURITY.md $(INTERMEDIATE_DIR)/security.md
@echo "🔧 Generating feature tables and processing links..."
$(PYTHON) scripts/tool_feat_table.py $(INTERMEDIATE_DIR) & \
$(PYTHON) scripts/kv_store_feat_table.py $(INTERMEDIATE_DIR) & \
$(PYTHON) scripts/partner_pkg_table.py $(INTERMEDIATE_DIR) & \
$(PYTHON) scripts/resolve_local_links.py $(INTERMEDIATE_DIR)/langserve.md https://github.com/langchain-ai/langserve/tree/main/ & \
wait
@echo "✅ Files generated"
copy-infra:
@echo "📂 Copying infrastructure files..."
mkdir -p $(OUTPUT_NEW_DIR)
cp -r src $(OUTPUT_NEW_DIR)
cp vercel.json $(OUTPUT_NEW_DIR)
cp babel.config.js $(OUTPUT_NEW_DIR)
cp -r data $(OUTPUT_NEW_DIR)
cp docusaurus.config.js $(OUTPUT_NEW_DIR)
cp package.json $(OUTPUT_NEW_DIR)
cp sidebars.js $(OUTPUT_NEW_DIR)
cp -r static $(OUTPUT_NEW_DIR)
cp -r ../libs/cli/langchain_cli/integration_template $(OUTPUT_NEW_DIR)/src/theme
cp yarn.lock $(OUTPUT_NEW_DIR)
@echo "✅ Infrastructure files copied"
render:
@echo "📓 Converting notebooks (this may take a while)..."
$(PYTHON) scripts/notebook_convert.py $(INTERMEDIATE_DIR) $(OUTPUT_NEW_DOCS_DIR)
@echo "✅ Notebooks converted"
md-sync:
@echo "📝 Syncing markdown files..."
rsync -avmq --include="*/" --include="*.mdx" --include="*.md" --include="*.png" --include="*/_category_.yml" --exclude="*" $(INTERMEDIATE_DIR)/ $(OUTPUT_NEW_DOCS_DIR)
@echo "✅ Markdown files synced"
append-related:
@echo "🔗 Appending related links..."
$(PYTHON) scripts/append_related_links.py $(OUTPUT_NEW_DOCS_DIR)
@echo "✅ Related links appended"
generate-references:
$(PYTHON) scripts/generate_api_reference_links.py --docs_dir $(OUTPUT_NEW_DOCS_DIR)
update-md: generate-files md-sync
build: install-py-deps generate-files copy-infra render md-sync append-related
@echo ""
@echo "🎉 Documentation build complete!"
@echo "📖 To view locally, run: cd docs && make start"
@echo ""
vercel-build: install-vercel-deps build generate-references
rm -rf docs
mv $(OUTPUT_NEW_DOCS_DIR) docs
cp -r ../libs/cli/langchain_cli/integration_template src/theme
rm -rf build
mkdir static/api_reference
git clone --depth=1 https://github.com/langchain-ai/langchain-api-docs-html.git
mv langchain-api-docs-html/api_reference_build/html/* static/api_reference/
rm -rf langchain-api-docs-html
NODE_OPTIONS="--max-old-space-size=5000" yarn run docusaurus build
start:
@echo "🚀 Starting documentation server on port $(PORT)..."
@echo "📖 Installing Node.js dependencies..."
cd $(OUTPUT_NEW_DIR) && yarn install --silent
@echo "🌐 Starting server at http://localhost:$(PORT)"
@echo "Press Ctrl+C to stop the server"
cd $(OUTPUT_NEW_DIR) && yarn start --port=$(PORT)

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# LangChain Documentation
For more information on contributing to our documentation, see the [Documentation Contributing Guide](https://python.langchain.com/docs/contributing/how_to/documentation)

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# Minimal makefile for Sphinx documentation
#
# You can set these variables from the command line, and also
# from the environment for the first two.
SPHINXOPTS ?= -j auto
SPHINXBUILD ?= sphinx-build
SPHINXAUTOBUILD ?= sphinx-autobuild
SOURCEDIR = .
BUILDDIR = _build
# Put it first so that "make" without argument is like "make help".
help:
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
.PHONY: help Makefile
# Catch-all target: route all unknown targets to Sphinx using the new
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
%: Makefile
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

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"""A directive to generate a gallery of images from structured data.
Generating a gallery of images that are all the same size is a common
pattern in documentation, and this can be cumbersome if the gallery is
generated programmatically. This directive wraps this particular use-case
in a helper-directive to generate it with a single YAML configuration file.
It currently exists for maintainers of the pydata-sphinx-theme,
but might be abstracted into a standalone package if it proves useful.
"""
from pathlib import Path
from typing import Any, ClassVar, Dict, List
from docutils import nodes
from docutils.parsers.rst import directives
from sphinx.application import Sphinx
from sphinx.util import logging
from sphinx.util.docutils import SphinxDirective
from yaml import safe_load
logger = logging.getLogger(__name__)
TEMPLATE_GRID = """
`````{{grid}} {columns}
{options}
{content}
`````
"""
GRID_CARD = """
````{{grid-item-card}} {title}
{options}
{content}
````
"""
class GalleryGridDirective(SphinxDirective):
"""A directive to show a gallery of images and links in a Bootstrap grid.
The grid can be generated from a YAML file that contains a list of items, or
from the content of the directive (also formatted in YAML). Use the parameter
"class-card" to add an additional CSS class to all cards. When specifying the grid
items, you can use all parameters from "grid-item-card" directive to customize
individual cards + ["image", "header", "content", "title"].
Danger:
This directive can only be used in the context of a Myst documentation page as
the templates use Markdown flavored formatting.
"""
name = "gallery-grid"
has_content = True
required_arguments = 0
optional_arguments = 1
final_argument_whitespace = True
option_spec: ClassVar[dict[str, Any]] = {
# A class to be added to the resulting container
"grid-columns": directives.unchanged,
"class-container": directives.unchanged,
"class-card": directives.unchanged,
}
def run(self) -> List[nodes.Node]:
"""Create the gallery grid."""
if self.arguments:
# If an argument is given, assume it's a path to a YAML file
# Parse it and load it into the directive content
path_data_rel = Path(self.arguments[0])
path_doc, _ = self.get_source_info()
path_doc = Path(path_doc).parent
path_data = (path_doc / path_data_rel).resolve()
if not path_data.exists():
logger.info(f"Could not find grid data at {path_data}.")
nodes.text("No grid data found at {path_data}.")
return
yaml_string = path_data.read_text()
else:
yaml_string = "\n".join(self.content)
# Use all the element with an img-bottom key as sites to show
# and generate a card item for each of them
grid_items = []
for item in safe_load(yaml_string):
# remove parameters that are not needed for the card options
title = item.pop("title", "")
# build the content of the card using some extra parameters
header = f"{item.pop('header')} \n^^^ \n" if "header" in item else ""
image = f"![image]({item.pop('image')}) \n" if "image" in item else ""
content = f"{item.pop('content')} \n" if "content" in item else ""
# optional parameter that influence all cards
if "class-card" in self.options:
item["class-card"] = self.options["class-card"]
loc_options_str = "\n".join(f":{k}: {v}" for k, v in item.items()) + " \n"
card = GRID_CARD.format(
options=loc_options_str, content=header + image + content, title=title
)
grid_items.append(card)
# Parse the template with Sphinx Design to create an output container
# Prep the options for the template grid
class_ = "gallery-directive" + f" {self.options.get('class-container', '')}"
options = {"gutter": 2, "class-container": class_}
options_str = "\n".join(f":{k}: {v}" for k, v in options.items())
# Create the directive string for the grid
grid_directive = TEMPLATE_GRID.format(
columns=self.options.get("grid-columns", "1 2 3 4"),
options=options_str,
content="\n".join(grid_items),
)
# Parse content as a directive so Sphinx Design processes it
container = nodes.container()
self.state.nested_parse([grid_directive], 0, container)
# Sphinx Design outputs a container too, so just use that
return [container.children[0]]
def setup(app: Sphinx) -> Dict[str, Any]:
"""Add custom configuration to sphinx app.
Args:
app: the Sphinx application
Returns:
the 2 parallel parameters set to ``True``.
"""
app.add_directive("gallery-grid", GalleryGridDirective)
return {
"parallel_read_safe": True,
"parallel_write_safe": True,
}

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@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;700&display=swap');
/*******************************************************************************
* master color map. Only the colors that actually differ between light and dark
* themes are specified separately.
*
* To see the full list of colors see https://www.figma.com/file/rUrrHGhUBBIAAjQ82x6pz9/PyData-Design-system---proposal-for-implementation-(2)?node-id=1234%3A765&t=ifcFT1JtnrSshGfi-1
*/
/**
* Function to get items from nested maps
*/
/* Assign base colors for the PyData theme */
:root {
--pst-teal-50: #f4fbfc;
--pst-teal-100: #e9f6f8;
--pst-teal-200: #d0ecf1;
--pst-teal-300: #abdde6;
--pst-teal-400: #3fb1c5;
--pst-teal-500: #0a7d91;
--pst-teal-600: #085d6c;
--pst-teal-700: #064752;
--pst-teal-800: #042c33;
--pst-teal-900: #021b1f;
--pst-violet-50: #f4eefb;
--pst-violet-100: #e0c7ff;
--pst-violet-200: #d5b4fd;
--pst-violet-300: #b780ff;
--pst-violet-400: #9c5ffd;
--pst-violet-500: #8045e5;
--pst-violet-600: #6432bd;
--pst-violet-700: #4b258f;
--pst-violet-800: #341a61;
--pst-violet-900: #1e0e39;
--pst-gray-50: #f9f9fa;
--pst-gray-100: #f3f4f5;
--pst-gray-200: #e5e7ea;
--pst-gray-300: #d1d5da;
--pst-gray-400: #9ca4af;
--pst-gray-500: #677384;
--pst-gray-600: #48566b;
--pst-gray-700: #29313d;
--pst-gray-800: #222832;
--pst-gray-900: #14181e;
--pst-pink-50: #fcf8fd;
--pst-pink-100: #fcf0fa;
--pst-pink-200: #f8dff5;
--pst-pink-300: #f3c7ee;
--pst-pink-400: #e47fd7;
--pst-pink-500: #c132af;
--pst-pink-600: #912583;
--pst-pink-700: #6e1c64;
--pst-pink-800: #46123f;
--pst-pink-900: #2b0b27;
--pst-foundation-white: #ffffff;
--pst-foundation-black: #14181e;
--pst-green-10: #f1fdfd;
--pst-green-50: #E0F7F6;
--pst-green-100: #B3E8E6;
--pst-green-200: #80D6D3;
--pst-green-300: #4DC4C0;
--pst-green-400: #4FB2AD;
--pst-green-500: #287977;
--pst-green-600: #246161;
--pst-green-700: #204F4F;
--pst-green-800: #1C3C3C;
--pst-green-900: #0D2427;
--pst-lilac-50: #f4eefb;
--pst-lilac-100: #DAD6FE;
--pst-lilac-200: #BCB2FD;
--pst-lilac-300: #9F8BFA;
--pst-lilac-400: #7F5CF6;
--pst-lilac-500: #6F3AED;
--pst-lilac-600: #6028D9;
--pst-lilac-700: #5021B6;
--pst-lilac-800: #431D95;
--pst-lilac-900: #1e0e39;
--pst-header-height: 2.5rem;
}
html {
--pst-font-family-base: 'Inter';
--pst-font-family-heading: 'Inter Tight', sans-serif;
--pst-icon-versionmodified-deprecated: var(--pst-icon-exclamation-triangle);
}
/*******************************************************************************
* write the color rules for each theme (light/dark)
*/
/* NOTE:
* Mixins enable us to reuse the same definitions for the different modes
* https://sass-lang.com/documentation/at-rules/mixin
* something inserts a variable into a CSS selector or property name
* https://sass-lang.com/documentation/interpolation
*/
/* Defaults to light mode if data-theme is not set */
html:not([data-theme]), html[data-theme=light] {
--pst-color-primary: #287977;
--pst-color-primary-bg: #80D6D3;
--pst-color-secondary: #6F3AED;
--pst-color-secondary-bg: #DAD6FE;
--pst-color-accent: #c132af;
--pst-color-accent-bg: #f8dff5;
--pst-color-info: #276be9;
--pst-color-info-bg: #dce7fc;
--pst-color-warning: #f66a0a;
--pst-color-warning-bg: #f8e3d0;
--pst-color-success: #00843f;
--pst-color-success-bg: #d6ece1;
--pst-color-attention: var(--pst-color-warning);
--pst-color-attention-bg: var(--pst-color-warning-bg);
--pst-color-danger: #d72d47;
--pst-color-danger-bg: #f9e1e4;
--pst-color-text-base: #222832;
--pst-color-text-muted: #48566b;
--pst-color-heading-color: #ffffff;
--pst-color-shadow: rgba(0, 0, 0, 0.1);
--pst-color-border: #d1d5da;
--pst-color-border-muted: rgba(23, 23, 26, 0.2);
--pst-color-inline-code: #912583;
--pst-color-inline-code-links: #246161;
--pst-color-target: #f3cf95;
--pst-color-background: #ffffff;
--pst-color-on-background: #F4F9F8;
--pst-color-surface: #F4F9F8;
--pst-color-on-surface: #222832;
--pst-color-deprecated: #f47d2e;
--pst-color-deprecated-bg: #fff3e8;
}
html[data-theme=dark] {
--pst-color-primary: #4FB2AD;
--pst-color-primary-bg: #1C3C3C;
--pst-color-secondary: #7F5CF6;
--pst-color-secondary-bg: #431D95;
--pst-color-accent: #e47fd7;
--pst-color-accent-bg: #46123f;
--pst-color-info: #79a3f2;
--pst-color-info-bg: #06245d;
--pst-color-warning: #ff9245;
--pst-color-warning-bg: #652a02;
--pst-color-success: #5fb488;
--pst-color-success-bg: #002f17;
--pst-color-attention: var(--pst-color-warning);
--pst-color-attention-bg: var(--pst-color-warning-bg);
--pst-color-danger: #e78894;
--pst-color-danger-bg: #4e111b;
--pst-color-text-base: #ced6dd;
--pst-color-text-muted: #9ca4af;
--pst-color-heading-color: #14181e;
--pst-color-shadow: rgba(0, 0, 0, 0.2);
--pst-color-border: #48566b;
--pst-color-border-muted: #29313d;
--pst-color-inline-code: #f3c7ee;
--pst-color-inline-code-links: #4FB2AD;
--pst-color-target: #675c04;
--pst-color-background: #14181e;
--pst-color-on-background: #222832;
--pst-color-surface: #29313d;
--pst-color-on-surface: #f3f4f5;
--pst-color-deprecated: #b46f3e;
--pst-color-deprecated-bg: #341906;
/* Adjust images in dark mode (unless they have class .only-dark or
* .dark-light, in which case assume they're already optimized for dark
* mode).
*/
/* Give images a light background in dark mode in case they have
* transparency and black text (unless they have class .only-dark or .dark-light, in
* which case assume they're already optimized for dark mode).
*/
color-scheme: dark;
}
html:not([data-theme]) {
--pst-color-link: var(--pst-color-primary);
--pst-color-link-hover: var(--pst-color-secondary);
}
html:not([data-theme]) .only-dark,
html:not([data-theme]) .only-dark ~ figcaption {
display: none !important;
}
/* NOTE: @each {...} is like a for-loop
* https://sass-lang.com/documentation/at-rules/control/each
*/
html[data-theme=light] {
color-scheme: light;
}
html[data-theme=light] {
--pst-color-link: var(--pst-color-primary);
--pst-color-link-hover: var(--pst-color-secondary);
}
html[data-theme=light] .only-dark,
html[data-theme=light] .only-dark ~ figcaption {
display: none !important;
}
html[data-theme=dark] {
--pst-color-link: var(--pst-color-primary);
--pst-color-link-hover: var(--pst-color-secondary);
}
html[data-theme=dark] .only-light,
html[data-theme=dark] .only-light ~ figcaption {
display: none !important;
}
html[data-theme=dark] img:not(.only-dark):not(.dark-light) {
filter: brightness(0.8) contrast(1.2);
}
html[data-theme=dark] .bd-content img:not(.only-dark):not(.dark-light) {
background: rgb(255, 255, 255);
border-radius: 0.25rem;
}
html[data-theme=dark] .MathJax_SVG * {
fill: var(--pst-color-text-base);
}
.pst-color-primary {
color: var(--pst-color-primary);
}
.pst-color-secondary {
color: var(--pst-color-secondary);
}
.pst-color-accent {
color: var(--pst-color-accent);
}
.pst-color-info {
color: var(--pst-color-info);
}
.pst-color-warning {
color: var(--pst-color-warning);
}
.pst-color-success {
color: var(--pst-color-success);
}
.pst-color-attention {
color: var(--pst-color-attention);
}
.pst-color-danger {
color: var(--pst-color-danger);
}
.pst-color-text-base {
color: var(--pst-color-text-base);
}
.pst-color-text-muted {
color: var(--pst-color-text-muted);
}
.pst-color-heading-color {
color: var(--pst-color-heading-color);
}
.pst-color-shadow {
color: var(--pst-color-shadow);
}
.pst-color-border {
color: var(--pst-color-border);
}
.pst-color-border-muted {
color: var(--pst-color-border-muted);
}
.pst-color-inline-code {
color: var(--pst-color-inline-code);
}
.pst-color-inline-code-links {
color: var(--pst-color-inline-code-links);
}
.pst-color-target {
color: var(--pst-color-target);
}
.pst-color-background {
color: var(--pst-color-background);
}
.pst-color-on-background {
color: var(--pst-color-on-background);
}
.pst-color-surface {
color: var(--pst-color-surface);
}
.pst-color-on-surface {
color: var(--pst-color-on-surface);
}
/* Adjust the height of the navbar */
.bd-header .bd-header__inner{
height: 52px; /* Adjust this value as needed */
}
.navbar-nav > li > a {
line-height: 52px; /* Vertically center the navbar links */
}
/* Make sure the navbar items align properly */
.navbar-nav {
display: flex;
}
.bd-header .navbar-header-items__start{
margin-left: 0rem
}
.bd-header button.primary-toggle {
margin-right: 0rem;
}
.bd-header ul.navbar-nav .dropdown .dropdown-menu {
overflow-y: auto; /* Enable vertical scrolling */
max-height: 80vh
}
.bd-sidebar-primary {
width: max-content; /* Adjust this value to your preference */
line-height: 1.4;
}
.bd-sidebar-secondary {
line-height: 1.4;
}
.toc-entry a.nav-link, .toc-entry a>code {
background-color: transparent;
border-color: transparent;
}
.bd-sidebar-primary code{
background-color: transparent;
border-color: transparent;
}
.toctree-wrapper li[class^=toctree-l1]>a {
font-size: 1.3em
}
.toctree-wrapper li[class^=toctree-l1] {
margin-bottom: 2em;
}
.toctree-wrapper li[class^=toctree-l]>ul {
margin-top: 0.5em;
font-size: 0.9em;
}
*, :after, :before {
font-style: normal;
}
div.deprecated {
margin-top: 0.5em;
margin-bottom: 2em;
background-color: var(--pst-color-deprecated-bg);
border-color: var(--pst-color-deprecated);
}
span.versionmodified.deprecated:before {
color: var(--pst-color-deprecated);
}
.admonition-beta.admonition, div.admonition-beta.admonition {
border-color: var(--pst-color-warning);
margin-top:0.5em;
margin-bottom: 2em;
}
.admonition-beta>.admonition-title, div.admonition-beta>.admonition-title {
background-color: var(--pst-color-warning-bg);
}
dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.glossary):not(.simple) dd {
margin-left: 1rem;
}
p {
font-size: 0.9rem;
margin-bottom: 0.5rem;
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docs/api_reference/conf.py Normal file
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"""Configuration file for the Sphinx documentation builder."""
# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
import json
import os
import sys
from datetime import datetime
from pathlib import Path
import toml
from docutils import nodes
from docutils.parsers.rst.directives.admonitions import BaseAdmonition
from docutils.statemachine import StringList
from sphinx.util.docutils import SphinxDirective
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
_DIR = Path(__file__).parent.absolute()
sys.path.insert(0, os.path.abspath("."))
sys.path.insert(0, os.path.abspath("../../libs/langchain"))
with (_DIR.parents[1] / "libs" / "langchain" / "pyproject.toml").open("r") as f:
data = toml.load(f)
with (_DIR / "guide_imports.json").open("r") as f:
imported_classes = json.load(f)
class ExampleLinksDirective(SphinxDirective):
"""Directive to generate a list of links to examples.
We have a script that extracts links to API reference docs
from our notebook examples. This directive uses that information
to backlink to the examples from the API reference docs."""
has_content = False
required_arguments = 1
def run(self):
"""Run the directive.
Called any time :example_links:`ClassName` is used
in the template *.rst files."""
class_or_func_name = self.arguments[0]
links = imported_classes.get(class_or_func_name, {})
list_node = nodes.bullet_list()
for doc_name, link in sorted(links.items()):
item_node = nodes.list_item()
para_node = nodes.paragraph()
link_node = nodes.reference()
link_node["refuri"] = link
link_node.append(nodes.Text(doc_name))
para_node.append(link_node)
item_node.append(para_node)
list_node.append(item_node)
if list_node.children:
title_node = nodes.rubric()
title_node.append(nodes.Text(f"Examples using {class_or_func_name}"))
return [title_node, list_node]
return [list_node]
class Beta(BaseAdmonition):
required_arguments = 0
node_class = nodes.admonition
def run(self):
self.content = self.content or StringList(
[
(
"This feature is in beta. It is actively being worked on, so the "
"API may change."
)
]
)
self.arguments = self.arguments or ["Beta"]
return super().run()
def setup(app):
app.add_directive("example_links", ExampleLinksDirective)
app.add_directive("beta", Beta)
app.connect("autodoc-skip-member", skip_private_members)
def skip_private_members(app, what, name, obj, skip, options):
if skip:
return True
if hasattr(obj, "__doc__") and obj.__doc__ and ":private:" in obj.__doc__:
return True
if name == "__init__" and obj.__objclass__ is object:
# dont document default init
return True
return None
# -- Project information -----------------------------------------------------
project = "🦜🔗 LangChain"
copyright = f"{datetime.now().year}, LangChain Inc"
author = "LangChain, Inc"
html_favicon = "_static/img/brand/favicon.png"
html_last_updated_fmt = "%b %d, %Y"
# -- General configuration ---------------------------------------------------
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = [
"sphinx.ext.autodoc",
"sphinx.ext.autodoc.typehints",
"sphinx.ext.autosummary",
"sphinx.ext.napoleon",
"sphinx.ext.viewcode",
"sphinxcontrib.autodoc_pydantic",
"IPython.sphinxext.ipython_console_highlighting",
"myst_parser",
"_extensions.gallery_directive",
"sphinx_design",
"sphinx_copybutton",
"sphinxcontrib.googleanalytics",
]
source_suffix = [".rst", ".md"]
# some autodoc pydantic options are repeated in the actual template.
# potentially user error, but there may be bugs in the sphinx extension
# with options not being passed through correctly (from either the location in the code)
autodoc_pydantic_model_show_json = False
autodoc_pydantic_field_list_validators = False
autodoc_pydantic_config_members = False
autodoc_pydantic_model_show_config_summary = False
autodoc_pydantic_model_show_validator_members = False
autodoc_pydantic_model_show_validator_summary = False
autodoc_pydantic_model_signature_prefix = "class"
autodoc_pydantic_field_signature_prefix = "param"
autodoc_member_order = "groupwise"
autoclass_content = "both"
autodoc_typehints_format = "short"
autodoc_typehints = "both"
# Add any paths that contain templates here, relative to this directory.
templates_path = ["templates"]
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
# This pattern also affects html_static_path and html_extra_path.
exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"]
# -- Options for HTML output -------------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
#
# The theme to use for HTML and HTML Help pages.
html_theme = "pydata_sphinx_theme"
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
html_theme_options = {
# # -- General configuration ------------------------------------------------
"sidebar_includehidden": True,
"use_edit_page_button": False,
# # "analytics": {
# # "plausible_analytics_domain": "scikit-learn.org",
# # "plausible_analytics_url": "https://views.scientific-python.org/js/script.js",
# # },
# # If "prev-next" is included in article_footer_items, then setting show_prev_next
# # to True would repeat prev and next links. See
# # https://github.com/pydata/pydata-sphinx-theme/blob/b731dc230bc26a3d1d1bb039c56c977a9b3d25d8/src/pydata_sphinx_theme/theme/pydata_sphinx_theme/layout.html#L118-L129
"show_prev_next": False,
"search_bar_text": "Search",
"navigation_with_keys": True,
"collapse_navigation": True,
"navigation_depth": 3,
"show_nav_level": 1,
"show_toc_level": 3,
"navbar_align": "left",
"header_links_before_dropdown": 5,
"header_dropdown_text": "Integrations",
"logo": {
"image_light": "_static/wordmark-api.svg",
"image_dark": "_static/wordmark-api-dark.svg",
},
"surface_warnings": True,
# # -- Template placement in theme layouts ----------------------------------
"navbar_start": ["navbar-logo"],
# # Note that the alignment of navbar_center is controlled by navbar_align
"navbar_center": ["navbar-nav"],
"navbar_end": ["langchain_docs", "theme-switcher", "navbar-icon-links"],
# # navbar_persistent is persistent right (even when on mobiles)
"navbar_persistent": ["search-field"],
"article_header_start": ["breadcrumbs"],
"article_header_end": [],
"article_footer_items": [],
"content_footer_items": [],
# # Use html_sidebars that map page patterns to list of sidebar templates
# "primary_sidebar_end": [],
"footer_start": ["copyright"],
"footer_center": [],
"footer_end": [],
# # When specified as a dictionary, the keys should follow glob-style patterns, as in
# # https://www.sphinx-doc.org/en/master/usage/configuration.html#confval-exclude_patterns
# # In particular, "**" specifies the default for all pages
# # Use :html_theme.sidebar_secondary.remove: for file-wide removal
# "secondary_sidebar_items": {"**": ["page-toc", "sourcelink"]},
# "show_version_warning_banner": True,
# "announcement": None,
"icon_links": [
{
# Label for this link
"name": "GitHub",
# URL where the link will redirect
"url": "https://github.com/langchain-ai/langchain", # required
# Icon class (if "type": "fontawesome"), or path to local image (if "type": "local")
"icon": "fa-brands fa-square-github",
# The type of image to be used (see below for details)
"type": "fontawesome",
},
{
"name": "X / Twitter",
"url": "https://twitter.com/langchainai",
"icon": "fab fa-twitter-square",
},
],
"icon_links_label": "Quick Links",
"external_links": [],
}
html_context = {
"display_github": True, # Integrate GitHub
"github_user": "langchain-ai", # Username
"github_repo": "langchain", # Repo name
"github_version": "master", # Version
"conf_py_path": "/docs/api_reference", # Path in the checkout to the docs root
}
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ["_static"]
# These paths are either relative to html_static_path
# or fully qualified paths (e.g. https://...)
html_css_files = ["css/custom.css"]
html_use_index = False
myst_enable_extensions = ["colon_fence"]
# generate autosummary even if no references
autosummary_generate = True
# Don't fail on autosummary import warnings
autosummary_ignore_module_all = False
html_copy_source = False
html_show_sourcelink = False
# Set canonical URL from the Read the Docs Domain
html_baseurl = os.environ.get("READTHEDOCS_CANONICAL_URL", "")
googleanalytics_id = "G-9B66JQQH2F"
# Tell Jinja2 templates the build is running on Read the Docs
if os.environ.get("READTHEDOCS", "") == "True":
html_context["READTHEDOCS"] = True
master_doc = "index"
# If a signatures length in characters exceeds 60,
# each parameter within the signature will be displayed on an individual logical line
maximum_signature_line_length = 60

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"""Script for auto-generating api_reference.rst."""
import importlib
import inspect
import os
import sys
import typing
from enum import Enum
from pathlib import Path
from typing import Dict, List, Literal, Optional, Sequence, TypedDict, Union
import toml
import typing_extensions
from langchain_core.runnables import Runnable, RunnableSerializable
from pydantic import BaseModel
ROOT_DIR = Path(__file__).parents[2].absolute()
HERE = Path(__file__).parent
ClassKind = Literal[
"TypedDict",
"Regular",
"Pydantic",
"enum",
"RunnablePydantic",
"RunnableNonPydantic",
]
class ClassInfo(TypedDict):
"""Information about a class."""
name: str
"""The name of the class."""
qualified_name: str
"""The fully qualified name of the class."""
kind: ClassKind
"""The kind of the class."""
is_public: bool
"""Whether the class is public or not."""
is_deprecated: bool
"""Whether the class is deprecated."""
class FunctionInfo(TypedDict):
"""Information about a function."""
name: str
"""The name of the function."""
qualified_name: str
"""The fully qualified name of the function."""
is_public: bool
"""Whether the function is public or not."""
is_deprecated: bool
"""Whether the function is deprecated."""
class ModuleMembers(TypedDict):
"""A dictionary of module members."""
classes_: Sequence[ClassInfo]
functions: Sequence[FunctionInfo]
def _load_module_members(module_path: str, namespace: str) -> ModuleMembers:
"""Load all members of a module.
Args:
module_path: Path to the module.
namespace: the namespace of the module.
Returns:
list: A list of loaded module objects.
"""
classes_: List[ClassInfo] = []
functions: List[FunctionInfo] = []
module = importlib.import_module(module_path)
if ":private:" in (module.__doc__ or ""):
return ModuleMembers(classes_=[], functions=[])
for name, type_ in inspect.getmembers(module):
if not hasattr(type_, "__module__"):
continue
if type_.__module__ != module_path:
continue
if ":private:" in (type_.__doc__ or ""):
continue
if inspect.isclass(type_):
# The type of the class is used to select a template
# for the object when rendering the documentation.
# See `templates` directory for defined templates.
# This is a hacky solution to distinguish between different
# kinds of thing that we want to render.
if type(type_) is typing_extensions._TypedDictMeta: # type: ignore
kind: ClassKind = "TypedDict"
elif type(type_) is typing._TypedDictMeta: # type: ignore
kind = "TypedDict"
elif (
issubclass(type_, Runnable)
and issubclass(type_, BaseModel)
and type_ is not Runnable
):
# RunnableSerializable subclasses from Pydantic which
# for which we use autodoc_pydantic for rendering.
# We need to distinguish these from regular Pydantic
# classes so we can hide inherited Runnable methods
# and provide a link to the Runnable interface from
# the template.
kind = "RunnablePydantic"
elif (
issubclass(type_, Runnable)
and not issubclass(type_, BaseModel)
and type_ is not Runnable
):
# These are not pydantic classes but are Runnable.
# We'll hide all the inherited methods from Runnable
# but use a regular class template to render.
kind = "RunnableNonPydantic"
elif issubclass(type_, Enum):
kind = "enum"
elif issubclass(type_, BaseModel):
kind = "Pydantic"
else:
kind = "Regular"
classes_.append(
ClassInfo(
name=name,
qualified_name=f"{namespace}.{name}",
kind=kind,
is_public=not name.startswith("_"),
is_deprecated=".. deprecated::" in (type_.__doc__ or ""),
)
)
elif inspect.isfunction(type_):
functions.append(
FunctionInfo(
name=name,
qualified_name=f"{namespace}.{name}",
is_public=not name.startswith("_"),
is_deprecated=".. deprecated::" in (type_.__doc__ or ""),
)
)
else:
continue
return ModuleMembers(
classes_=classes_,
functions=functions,
)
def _merge_module_members(
module_members: Sequence[ModuleMembers],
) -> ModuleMembers:
"""Merge module members."""
classes_: List[ClassInfo] = []
functions: List[FunctionInfo] = []
for module in module_members:
classes_.extend(module["classes_"])
functions.extend(module["functions"])
return ModuleMembers(
classes_=classes_,
functions=functions,
)
def _load_package_modules(
package_directory: Union[str, Path], submodule: Optional[str] = None
) -> Dict[str, ModuleMembers]:
"""Recursively load modules of a package based on the file system.
Traversal based on the file system makes it easy to determine which
of the modules/packages are part of the package vs. 3rd party or built-in.
Parameters:
package_directory (Union[str, Path]): Path to the package directory.
submodule (Optional[str]): Optional name of submodule to load.
Returns:
Dict[str, ModuleMembers]: A dictionary where keys are module names and values are ModuleMembers objects.
"""
package_path = (
Path(package_directory)
if isinstance(package_directory, str)
else package_directory
)
modules_by_namespace: Dict[str, ModuleMembers] = {}
# Get the high level package name
package_name = package_path.name
# If we are loading a submodule, add it in
if submodule is not None:
package_path = package_path / submodule
for file_path in package_path.rglob("*.py"):
if file_path.name.startswith("_"):
continue
if "integration_template" in file_path.parts:
continue
if "project_template" in file_path.parts:
continue
relative_module_name = file_path.relative_to(package_path)
# Skip if any module part starts with an underscore
if any(part.startswith("_") for part in relative_module_name.parts):
continue
# Get the full namespace of the module
namespace = str(relative_module_name).replace(".py", "").replace("/", ".")
# Keep only the top level namespace
# (but make special exception for content_blocks and v1.messages)
if namespace == "messages.content_blocks" or namespace == "v1.messages":
top_namespace = namespace # Keep full namespace for content_blocks
else:
top_namespace = namespace.split(".")[0]
try:
# If submodule is present, we need to construct the paths in a slightly
# different way
if submodule is not None:
module_members = _load_module_members(
f"{package_name}.{submodule}.{namespace}",
f"{submodule}.{namespace}",
)
else:
module_members = _load_module_members(
f"{package_name}.{namespace}", namespace
)
# Merge module members if the namespace already exists
if top_namespace in modules_by_namespace:
existing_module_members = modules_by_namespace[top_namespace]
_module_members = _merge_module_members(
[existing_module_members, module_members]
)
else:
_module_members = module_members
modules_by_namespace[top_namespace] = _module_members
except ImportError as e:
print(f"Error: Unable to import module '{namespace}' with error: {e}")
return modules_by_namespace
def _construct_doc(
package_namespace: str,
members_by_namespace: Dict[str, ModuleMembers],
package_version: str,
) -> List[typing.Tuple[str, str]]:
"""Construct the contents of the reference.rst file for the given package.
Args:
package_namespace: The package top level namespace
members_by_namespace: The members of the package, dict organized by top level
module contains a list of classes and functions
inside of the top level namespace.
Returns:
The contents of the reference.rst file.
"""
docs = []
index_doc = f"""\
:html_theme.sidebar_secondary.remove:
.. currentmodule:: {package_namespace}
.. _{package_namespace}:
======================================
{package_namespace.replace("_", "-")}: {package_version}
======================================
.. automodule:: {package_namespace}
:no-members:
:no-inherited-members:
.. toctree::
:hidden:
:maxdepth: 2
"""
index_autosummary = """
"""
namespaces = sorted(members_by_namespace)
for module in namespaces:
index_doc += f" {module}\n"
module_doc = f"""\
.. currentmodule:: {package_namespace}
.. _{package_namespace}_{module}:
"""
_members = members_by_namespace[module]
classes = [
el
for el in _members["classes_"]
if el["is_public"] and not el["is_deprecated"]
]
functions = [
el
for el in _members["functions"]
if el["is_public"] and not el["is_deprecated"]
]
deprecated_classes = [
el for el in _members["classes_"] if el["is_public"] and el["is_deprecated"]
]
deprecated_functions = [
el
for el in _members["functions"]
if el["is_public"] and el["is_deprecated"]
]
if not (classes or functions):
continue
section = f":mod:`{module}`"
underline = "=" * (len(section) + 1)
module_doc += f"""
{section}
{underline}
.. automodule:: {package_namespace}.{module}
:no-members:
:no-inherited-members:
"""
index_autosummary += f"""
:ref:`{package_namespace}_{module}`
{"^" * (len(package_namespace) + len(module) + 8)}
"""
if classes:
module_doc += f"""\
**Classes**
.. currentmodule:: {package_namespace}
.. autosummary::
:toctree: {module}
"""
index_autosummary += """
**Classes**
.. autosummary::
"""
for class_ in sorted(classes, key=lambda c: c["qualified_name"]):
if class_["kind"] == "TypedDict":
template = "typeddict.rst"
elif class_["kind"] == "enum":
template = "enum.rst"
elif class_["kind"] == "Pydantic":
template = "pydantic.rst"
elif class_["kind"] == "RunnablePydantic":
template = "runnable_pydantic.rst"
elif class_["kind"] == "RunnableNonPydantic":
template = "runnable_non_pydantic.rst"
else:
template = "class.rst"
module_doc += f"""\
:template: {template}
{class_["qualified_name"]}
"""
index_autosummary += f"""
{class_["qualified_name"]}
"""
if functions:
_functions = [f["qualified_name"] for f in functions]
fstring = "\n ".join(sorted(_functions))
module_doc += f"""\
**Functions**
.. currentmodule:: {package_namespace}
.. autosummary::
:toctree: {module}
:template: function.rst
{fstring}
"""
index_autosummary += f"""
**Functions**
.. autosummary::
{fstring}
"""
if deprecated_classes:
module_doc += f"""\
**Deprecated classes**
.. currentmodule:: {package_namespace}
.. autosummary::
:toctree: {module}
"""
index_autosummary += """
**Deprecated classes**
.. autosummary::
"""
for class_ in sorted(deprecated_classes, key=lambda c: c["qualified_name"]):
if class_["kind"] == "TypedDict":
template = "typeddict.rst"
elif class_["kind"] == "enum":
template = "enum.rst"
elif class_["kind"] == "Pydantic":
template = "pydantic.rst"
elif class_["kind"] == "RunnablePydantic":
template = "runnable_pydantic.rst"
elif class_["kind"] == "RunnableNonPydantic":
template = "runnable_non_pydantic.rst"
else:
template = "class.rst"
module_doc += f"""\
:template: {template}
{class_["qualified_name"]}
"""
index_autosummary += f"""
{class_["qualified_name"]}
"""
if deprecated_functions:
_functions = [f["qualified_name"] for f in deprecated_functions]
fstring = "\n ".join(sorted(_functions))
module_doc += f"""\
**Deprecated functions**
.. currentmodule:: {package_namespace}
.. autosummary::
:toctree: {module}
:template: function.rst
{fstring}
"""
index_autosummary += f"""
**Deprecated functions**
.. autosummary::
{fstring}
"""
docs.append((f"{module}.rst", module_doc))
docs.append(("index.rst", index_doc + index_autosummary))
return docs
def _build_rst_file(package_name: str = "langchain") -> None:
"""Create a rst file for building of documentation.
Args:
package_name: Can be either "langchain" or "core" or "experimental".
"""
package_dir = _package_dir(package_name)
package_members = _load_package_modules(package_dir)
package_version = _get_package_version(package_dir)
output_dir = _out_file_path(package_name)
os.mkdir(output_dir)
rsts = _construct_doc(
_package_namespace(package_name), package_members, package_version
)
for name, rst in rsts:
with open(output_dir / name, "w") as f:
f.write(rst)
def _package_namespace(package_name: str) -> str:
"""Returns the package name used.
Args:
package_name: Can be either "langchain" or "core" or "experimental".
Returns:
modified package_name: Can be either "langchain" or "langchain_{package_name}"
"""
if package_name == "langchain":
return "langchain"
if package_name == "standard-tests":
return "langchain_tests"
return f"langchain_{package_name.replace('-', '_')}"
def _package_dir(package_name: str = "langchain") -> Path:
"""Return the path to the directory containing the documentation."""
if (ROOT_DIR / "libs" / package_name).exists():
return ROOT_DIR / "libs" / package_name / _package_namespace(package_name)
else:
return (
ROOT_DIR
/ "libs"
/ "partners"
/ package_name
/ _package_namespace(package_name)
)
def _get_package_version(package_dir: Path) -> str:
"""Return the version of the package."""
try:
with open(package_dir.parent / "pyproject.toml", "r") as f:
pyproject = toml.load(f)
except FileNotFoundError as e:
print(
f"pyproject.toml not found in {package_dir.parent}.\n"
"You are either attempting to build a directory which is not a package or "
"the package is missing a pyproject.toml file which should be added."
"Aborting the build."
)
exit(1)
try:
# uses uv
return pyproject["project"]["version"]
except KeyError:
# uses poetry
return pyproject["tool"]["poetry"]["version"]
def _out_file_path(package_name: str) -> Path:
"""Return the path to the file containing the documentation."""
return HERE / f"{package_name.replace('-', '_')}"
def _build_index(dirs: List[str]) -> None:
custom_names = {
"aws": "AWS",
"ai21": "AI21",
"ibm": "IBM",
}
ordered = ["core", "langchain", "text-splitters", "community", "experimental"]
main_ = [dir_ for dir_ in ordered if dir_ in dirs]
integrations = sorted(dir_ for dir_ in dirs if dir_ not in main_)
doc = """# LangChain Python API Reference
Welcome to the LangChain Python API reference. This is a reference for all
`langchain-x` packages.
For user guides see [https://python.langchain.com](https://python.langchain.com).
For the legacy API reference hosted on ReadTheDocs see [https://api.python.langchain.com/](https://api.python.langchain.com/).
"""
if main_:
main_headers = [
" ".join(custom_names.get(x, x.title()) for x in dir_.split("-"))
for dir_ in main_
]
main_tree = "\n".join(
f"{header_name}<{dir_.replace('-', '_')}/index>"
for header_name, dir_ in zip(main_headers, main_)
)
main_grid = "\n".join(
f'- header: "**{header_name}**"\n content: "{_package_namespace(dir_).replace("_", "-")}: {_get_package_version(_package_dir(dir_))}"\n link: {dir_.replace("-", "_")}/index.html'
for header_name, dir_ in zip(main_headers, main_)
)
doc += f"""## Base packages
```{{gallery-grid}}
:grid-columns: "1 2 2 3"
{main_grid}
```
```{{toctree}}
:maxdepth: 2
:hidden:
:caption: Base packages
{main_tree}
```
"""
if integrations:
integration_headers = [
" ".join(
custom_names.get(
x,
x.title().replace("db", "DB")
if dir_ == "langchain_v1"
else x.title().replace("ai", "AI").replace("db", "DB"),
)
for x in dir_.split("-")
)
for dir_ in integrations
]
integration_tree = "\n".join(
f"{header_name}<{dir_.replace('-', '_')}/index>"
for header_name, dir_ in zip(integration_headers, integrations)
)
integration_grid = ""
integrations_to_show = [
"openai",
"anthropic",
"google-vertexai",
"aws",
"huggingface",
"mistralai",
]
for header_name, dir_ in sorted(
zip(integration_headers, integrations),
key=lambda h_d: (
integrations_to_show.index(h_d[1])
if h_d[1] in integrations_to_show
else len(integrations_to_show)
),
)[: len(integrations_to_show)]:
integration_grid += f'\n- header: "**{header_name}**"\n content: {_package_namespace(dir_).replace("_", "-")} {_get_package_version(_package_dir(dir_))}\n link: {dir_.replace("-", "_")}/index.html'
doc += f"""## Integrations
```{{gallery-grid}}
:grid-columns: "1 2 2 3"
{integration_grid}
```
See the full list of integrations in the Section Navigation.
```{{toctree}}
:maxdepth: 2
:hidden:
:caption: Integrations
{integration_tree}
```
"""
with open(HERE / "reference.md", "w") as f:
f.write(doc)
dummy_index = """\
# API reference
```{toctree}
:maxdepth: 3
:hidden:
Reference<reference>
```
"""
with open(HERE / "index.md", "w") as f:
f.write(dummy_index)
def main(dirs: Optional[list] = None) -> None:
"""Generate the api_reference.rst file for each package."""
print("Starting to build API reference files.")
if not dirs:
dirs = [
p.parent.name
for p in (ROOT_DIR / "libs").rglob("pyproject.toml")
# Exclude packages that are not directly under libs/ or libs/partners/
if p.parent.parent.name in ("libs", "partners")
]
for dir_ in sorted(dirs):
# Skip any hidden directories
# Some of these could be present by mistake in the code base
# e.g., .pytest_cache from running tests from the wrong location.
if dir_.startswith("."):
print("Skipping dir:", dir_)
continue
else:
print("Building package:", dir_)
_build_rst_file(package_name=dir_)
_build_index(sorted(dirs))
print("API reference files built.")
if __name__ == "__main__":
dirs = sys.argv[1:] or None
main(dirs=dirs)

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@ECHO OFF
pushd %~dp0
REM Command file for Sphinx documentation
if "%SPHINXBUILD%" == "" (
set SPHINXBUILD=sphinx-build
)
set SOURCEDIR=.
set BUILDDIR=_build
if "%1" == "" goto help
%SPHINXBUILD% >NUL 2>NUL
if errorlevel 9009 (
echo.
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
echo.installed, then set the SPHINXBUILD environment variable to point
echo.to the full path of the 'sphinx-build' executable. Alternatively you
echo.may add the Sphinx directory to PATH.
echo.
echo.If you don't have Sphinx installed, grab it from
echo.http://sphinx-doc.org/
exit /b 1
)
%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
goto end
:help
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
:end
popd

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autodoc_pydantic>=2,<3
sphinx>=8,<9
myst-parser>=3
sphinx-autobuild>=2024
pydata-sphinx-theme>=0.15
toml>=0.10.2
myst-nb>=1.1.1
pyyaml
sphinx-design
sphinx-copybutton
beautifulsoup4
sphinxcontrib-googleanalytics

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import sys
from glob import glob
from pathlib import Path
from bs4 import BeautifulSoup
CUR_DIR = Path(__file__).parents[1]
def process_toc_h3_elements(html_content: str) -> str:
"""Update Class.method() TOC headers to just method()."""
# Create a BeautifulSoup object
soup = BeautifulSoup(html_content, "html.parser")
# Find all <li> elements with class "toc-h3"
toc_h3_elements = soup.find_all("li", class_="toc-h3")
# Process each element
for element in toc_h3_elements:
try:
element = element.a.code.span
except Exception:
continue
# Get the text content of the element
content = element.get_text()
# Apply the regex substitution
modified_content = content.split(".")[-1]
# Update the element's content
element.string = modified_content
# Return the modified HTML
return str(soup)
if __name__ == "__main__":
dir = sys.argv[1]
for fn in glob(str(f"{dir.rstrip('/')}/**/*.html"), recursive=True):
with open(fn, "r") as f:
html = f.read()
processed_html = process_toc_h3_elements(html)
with open(fn, "w") as f:
f.write(processed_html)

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Copyright (c) 2007-2023 The scikit-learn developers.
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

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{{ objname }}
{{ underline }}==============
.. currentmodule:: {{ module }}
.. autoclass:: {{ objname }}
{% block attributes %}
{% if attributes %}
.. rubric:: {{ _('Attributes') }}
.. autosummary::
{% for item in attributes %}
~{{ item }}
{%- endfor %}
{% endif %}
{% endblock %}
{% block methods %}
{% if methods %}
.. rubric:: {{ _('Methods') }}
.. autosummary::
{% for item in methods %}
~{{ item }}
{%- endfor %}
{% for item in methods %}
.. automethod:: {{ item }}
{%- endfor %}
{% endif %}
{% endblock %}
.. example_links:: {{ objname }}

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{{ objname }}
{{ underline }}==============
.. currentmodule:: {{ module }}
.. autoclass:: {{ objname }}
{% block attributes %}
{% for item in attributes %}
.. autoattribute:: {{ item }}
{% endfor %}
{% endblock %}
.. example_links:: {{ objname }}

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{{ objname }}
{{ underline }}==============
.. currentmodule:: {{ module }}
.. autofunction:: {{ objname }}
.. example_links:: {{ objname }}

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@@ -0,0 +1,12 @@
<!-- This will display a link to LangChain docs -->
<head>
<style>
.text-link {
text-decoration: none; /* Remove underline */
color: inherit; /* Inherit color from parent element */
}
</style>
</head>
<body>
<a href="https://python.langchain.com/" class='text-link'>Docs</a>
</body>

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{{ objname }}
{{ underline }}==============
.. currentmodule:: {{ module }}
.. autopydantic_model:: {{ objname }}
:model-show-json: False
:model-show-config-summary: False
:model-show-validator-members: False
:model-show-field-summary: False
:field-signature-prefix: param
:members:
:undoc-members:
:inherited-members:
:member-order: groupwise
:show-inheritance: True
:special-members: __call__
:exclude-members: construct, copy, dict, from_orm, parse_file, parse_obj, parse_raw, schema, schema_json, update_forward_refs, validate, json, is_lc_serializable, to_json, to_json_not_implemented, lc_secrets, lc_attributes, lc_id, get_lc_namespace, model_construct, model_copy, model_dump, model_dump_json, model_parametrized_name, model_post_init, model_rebuild, model_validate, model_validate_json, model_validate_strings, model_extra, model_fields_set, model_json_schema
{% block attributes %}
{% endblock %}
.. example_links:: {{ objname }}

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{% set redirect = pathto(redirects[pagename]) %}
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta http-equiv="Refresh" content="0; url={{ redirect }}" />
<meta name="robots" content="follow, index">
<meta name="Description" content="Python API reference for LangChain.">
<link rel="canonical" href="{{ redirect }}" />
<title>LangChain Python API Reference Documentation.</title>
</head>
<body>
<p>You will be automatically redirected to the <a href="{{ redirect }}">new location of this page</a>.</p>
</body>
</html>

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{{ objname }}
{{ underline }}==============
.. currentmodule:: {{ module }}
.. autoclass:: {{ objname }}
.. NOTE:: {{objname}} implements the standard :py:class:`Runnable Interface <langchain_core.runnables.base.Runnable>`. 🏃
The :py:class:`Runnable Interface <langchain_core.runnables.base.Runnable>` has additional methods that are available on runnables, such as :py:meth:`with_config <langchain_core.runnables.base.Runnable.with_config>`, :py:meth:`with_types <langchain_core.runnables.base.Runnable.with_types>`, :py:meth:`with_retry <langchain_core.runnables.base.Runnable.with_retry>`, :py:meth:`assign <langchain_core.runnables.base.Runnable.assign>`, :py:meth:`bind <langchain_core.runnables.base.Runnable.bind>`, :py:meth:`get_graph <langchain_core.runnables.base.Runnable.get_graph>`, and more.
{% block attributes %}
{% if attributes %}
.. rubric:: {{ _('Attributes') }}
.. autosummary::
{% for item in attributes %}
~{{ item }}
{%- endfor %}
{% endif %}
{% endblock %}
{% block methods %}
{% if methods %}
.. rubric:: {{ _('Methods') }}
.. autosummary::
{% for item in methods %}
~{{ item }}
{%- endfor %}
{% for item in methods %}
.. automethod:: {{ item }}
{%- endfor %}
{% endif %}
{% endblock %}
.. example_links:: {{ objname }}

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{{ objname }}
{{ underline }}==============
.. currentmodule:: {{ module }}
.. autopydantic_model:: {{ objname }}
:model-show-json: False
:model-show-config-summary: False
:model-show-validator-members: False
:model-show-field-summary: False
:field-signature-prefix: param
:members:
:undoc-members:
:inherited-members:
:member-order: groupwise
:show-inheritance: True
:special-members: __call__
:exclude-members: construct, copy, dict, from_orm, parse_file, parse_obj, parse_raw, schema, schema_json, update_forward_refs, validate, json, is_lc_serializable, to_json_not_implemented, lc_secrets, lc_attributes, lc_id, get_lc_namespace, astream_log, transform, atransform, get_output_schema, get_prompts, config_schema, map, pick, pipe, InputType, OutputType, config_specs, output_schema, get_input_schema, get_graph, get_name, input_schema, name, assign, as_tool, get_config_jsonschema, get_input_jsonschema, get_output_jsonschema, model_construct, model_copy, model_dump, model_dump_json, model_parametrized_name, model_post_init, model_rebuild, model_validate, model_validate_json, model_validate_strings, to_json, model_extra, model_fields_set, model_json_schema, predict, apredict, predict_messages, apredict_messages, generate, generate_prompt, agenerate, agenerate_prompt, call_as_llm
.. NOTE:: {{objname}} implements the standard :py:class:`Runnable Interface <langchain_core.runnables.base.Runnable>`. 🏃
The :py:class:`Runnable Interface <langchain_core.runnables.base.Runnable>` has additional methods that are available on runnables, such as :py:meth:`with_config <langchain_core.runnables.base.Runnable.with_config>`, :py:meth:`with_types <langchain_core.runnables.base.Runnable.with_types>`, :py:meth:`with_retry <langchain_core.runnables.base.Runnable.with_retry>`, :py:meth:`assign <langchain_core.runnables.base.Runnable.assign>`, :py:meth:`bind <langchain_core.runnables.base.Runnable.bind>`, :py:meth:`get_graph <langchain_core.runnables.base.Runnable.get_graph>`, and more.
.. example_links:: {{ objname }}

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{{ objname }}
{{ underline }}==============
.. currentmodule:: {{ module }}
.. autoclass:: {{ objname }}
{% block attributes %}
{% for item in attributes %}
.. autoattribute:: {{ item }}
{% endfor %}
{% endblock %}
.. example_links:: {{ objname }}

12
docs/babel.config.js Normal file
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/**
* Copyright (c) Meta Platforms, Inc. and affiliates.
*
* This source code is licensed under the MIT license found in the
* LICENSE file in the root directory of this source tree.
*
* @format
*/
module.exports = {
presets: [require.resolve("@docusaurus/core/lib/babel/preset")],
};

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