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54 Commits

Author SHA1 Message Date
copilot-swe-agent[bot]
0ecdd6a174 Add cohere partner package structure for API reference documentation
Co-authored-by: mdrxy <61371264+mdrxy@users.noreply.github.com>
2025-07-28 13:43:33 +00:00
copilot-swe-agent[bot]
940ad63c63 Initial plan 2025-07-28 13:30:34 +00:00
Mason Daugherty
12c0e9b7d8 fix(docs): local API reference documentation build (#32271)
ensure all relevant packages are correctly processed - cli wasn't
included, also fix ValueError
2025-07-28 00:50:20 -04:00
Mason Daugherty
ed682ae62d fix: explicitly tell uv to copy when using devcontainer (#32267) 2025-07-28 00:01:06 -04:00
Mason Daugherty
caf1919217 fix: devcontainer to use volume to store the workspace (#32266)
should resolve the file sharing issue for users on macOS.
2025-07-27 23:43:06 -04:00
Mason Daugherty
904066f1ec feat: add VSCode configuration files for Python development (#32263) 2025-07-27 23:37:59 -04:00
Mason Daugherty
96cbd90cba fix: formatting issues in docstrings (#32265)
Ensures proper reStructuredText formatting by adding the required blank
line before closing docstring quotes, which resolves the "Block quote
ends without a blank line; unexpected unindent" warning.
2025-07-27 23:37:47 -04:00
Mason Daugherty
a8a2cff129 Merge branch 'master' of github.com:langchain-ai/langchain 2025-07-27 23:34:59 -04:00
Mason Daugherty
f4ff4514ef fix: update workspace folder path in devcontainer configuration 2025-07-27 23:34:57 -04:00
Mason Daugherty
d1679cec91 chore: add .editorconfig for consistent coding styles across files (#32261)
Following existing codebase conventions
2025-07-27 23:25:30 -04:00
Mason Daugherty
5295f2add0 fix: update dev container name to match service name 2025-07-27 22:30:16 -04:00
Mason Daugherty
5f5b87e9a3 fix: update service name in devcontainer configuration 2025-07-27 22:28:47 -04:00
Mason Daugherty
e0ef98dac0 feat: add markdownlint configuration file (#32264) 2025-07-27 22:24:58 -04:00
Mason Daugherty
62212c7ee2 fix: update links in SECURITY.md to use markdown format 2025-07-27 21:54:25 -04:00
Mason Daugherty
9d38f170ce refactor: enhance workflow names and descriptions for clarity (#32262) 2025-07-27 21:31:59 -04:00
Mason Daugherty
c6cb1fae61 fix: devcontainer (#32260) 2025-07-27 20:24:16 -04:00
Kanav Bansal
e42b1d23dc docs(docs): update RAG tutorials link to point to correct path (#32256)
- **Description:** This PR updates the internal documentation link for
the RAG tutorials to reflect the updated path. Previously, the link
pointed to the root `/docs/tutorials/`, which was generic. It now
correctly routes to the RAG-specific tutorial page.
  - **Issue:** N/A
  - **Dependencies:** None
  - **Twitter handle:** N/A
2025-07-27 20:00:41 -04:00
Mason Daugherty
53d0bfe9cd refactor: markdownlint (#32259) 2025-07-27 20:00:16 -04:00
Mason Daugherty
eafab52483 refactor: markdownlint SECURITY.md (#32258) 2025-07-27 19:55:25 -04:00
Christophe Bornet
efdfa00d10 chore(langchain): add ruff rules ARG (#32110)
See https://docs.astral.sh/ruff/rules/#flake8-unused-arguments-arg

Co-authored-by: Mason Daugherty <mason@langchain.dev>
2025-07-26 18:32:34 -04:00
Christophe Bornet
a2ad5aca41 chore(langchain): add ruff rules TC (#31921)
See https://docs.astral.sh/ruff/rules/#flake8-type-checking-tc
2025-07-26 18:27:26 -04:00
Mason Daugherty
5ecbb5f277 fix(docs): temporary workaround until the underlying dependency issues in the AI21 package ecosystem are resolved. (#32248) 2025-07-25 15:12:44 -04:00
Mason Daugherty
c1028171af fix(docs): update protobuf version constraint to <5.0 in vercel_overrides.txt (#32247) 2025-07-25 15:08:44 -04:00
ccurme
f6236d9f12 fix(infra): add pypdf to vercel overrides (#32242)
>   × No solution found when resolving dependencies:
  ╰─▶ Because only langchain-neo4j==0.5.0 is available and
langchain-neo4j==0.5.0 depends on neo4j-graphrag>=1.9.0, we can conclude
that all versions of langchain-neo4j depend on neo4j-graphrag>=1.9.0.
      And because only neo4j-graphrag<=1.9.0 is available and
neo4j-graphrag==1.9.0 depends on pypdf>=5.1.0,<6.0.0, we can conclude
that all versions of langchain-neo4j depend on pypdf>=5.1.0,<6.0.0.
And because langchain-upstage==0.6.0 depends on pypdf>=4.2.0,<5.0.0
and only langchain-upstage==0.6.0 is available, we can conclude that
all versions of langchain-neo4j and all versions of langchain-upstage
      are incompatible.
And because you require langchain-neo4j and langchain-upstage, we can
      conclude that your requirements are unsatisfiable.

---------

Co-authored-by: Mason Daugherty <mason@langchain.dev>
2025-07-25 15:05:21 -04:00
Mason Daugherty
df20f111a8 fix(docs): add validation for repository format and name in API docs build workflow (#32246)
for build
2025-07-25 15:05:06 -04:00
Eugene Yurtsev
db22311094 ci(infra): no need for . in the regexp (#32245)
No need for allowing `.`
2025-07-25 15:02:02 -04:00
Mason Daugherty
f624ad489a feat(docs): improve devx, fix Makefile targets (#32237)
**TL;DR much of the provided `Makefile` targets were broken, and any
time I wanted to preview changes locally I either had to refer to a
command Chester gave me or try waiting on a Vercel preview deployment.
With this PR, everything should behave like normal.**

Significant updates to the `Makefile` and documentation files, focusing
on improving usability, adding clear messaging, and fixing/enhancing
documentation workflows.

### Updates to `Makefile`:

#### Enhanced build and cleaning processes:
- Added informative messages (e.g., "📚 Building LangChain
documentation...") to makefile targets like `docs_build`, `docs_clean`,
and `api_docs_build` for better user feedback during execution.
- Introduced a `clean-cache` target to the `docs` `Makefile` to clear
cached dependencies and ensure clean builds.

#### Improved dependency handling:
- Modified `install-py-deps` to create a `.venv/deps_installed` marker,
preventing redundant/duplicate dependency installations and improving
efficiency.

#### Streamlined file generation and infrastructure setup:
- Added caching for the LangServe README download and parallelized
feature table generation
- Added user-friendly completion messages for targets like `copy-infra`
and `render`.

#### Documentation server updates:
- Enhanced the `start` target with messages indicating server start and
URL for local documentation viewing.

---

### Documentation Improvements:

#### Content clarity and consistency:
- Standardized section titles for consistency across documentation
files.
[[1]](diffhunk://#diff-9b1a85ea8a9dcf79f58246c88692cd7a36316665d7e05a69141cfdc50794c82aL1-R1)
[[2]](diffhunk://#diff-944008ad3a79d8a312183618401fcfa71da0e69c75803eff09b779fc8e03183dL1-R1)
- Refined phrasing and formatting in sections like "Dependency
management" and "Formatting and linting" for better readability.
[[1]](diffhunk://#diff-2069d4f956ab606ae6d51b191439283798adaf3a6648542c409d258131617059L6-R6)
[[2]](diffhunk://#diff-2069d4f956ab606ae6d51b191439283798adaf3a6648542c409d258131617059L84-R82)

#### Enhanced workflows:
- Updated instructions for building and viewing documentation locally,
including tips for specifying server ports and handling API reference
previews.
[[1]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L60-R94)
[[2]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L82-R126)
- Expanded guidance on cleaning documentation artifacts and using
linting tools effectively.
[[1]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L82-R126)
[[2]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L107-R142)

#### API reference documentation:
- Improved instructions for generating and formatting in-code
documentation, highlighting best practices for docstring writing.
[[1]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L107-R142)
[[2]](diffhunk://#diff-048deddcfd44b242e5b23aed9f2e9ec73afc672244ce14df2a0a316d95840c87L144-R186)

---

### Minor Changes:
- Added support for a new package name (`langchain_v1`) in the API
documentation generation script.
- Fixed minor capitalization and formatting issues in documentation
files.
[[1]](diffhunk://#diff-2069d4f956ab606ae6d51b191439283798adaf3a6648542c409d258131617059L40-R40)
[[2]](diffhunk://#diff-2069d4f956ab606ae6d51b191439283798adaf3a6648542c409d258131617059L166-R160)

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2025-07-25 14:49:03 -04:00
Eugene Yurtsev
549ecd3e78 chore(infra): harden api docs build workflow (#32243)
Harden permissions for api docs build workflow
2025-07-25 14:40:20 -04:00
dishaprakash
a0671676ae feat(docs): add PGVectorStore (#30950)
Thank you for contributing to LangChain!

-  **Adding documentation for PGVectorStore**: 
docs: Adding documentation for the new PGVectorStore as a part of
langchain-postgres

- **Add docs**: The notebook for PGVectorStore is now added to the
directory `docs/docs/integrations`.
As a part of this change, we've also updated the VectorStore features
table and VectorStoreTabs

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
2025-07-25 13:22:58 -04:00
Christophe Bornet
12ae42c5e9 chore(langchain): add ruff rules D1 (except D100 and D104) (#32123) 2025-07-25 11:59:48 -04:00
Christophe Bornet
e1238b8085 chore(langchain): add ruff rules SLF (#32112)
See https://docs.astral.sh/ruff/rules/private-member-access/
2025-07-25 11:56:40 -04:00
Chaitanya varma
8f5ec20ccf chore(langchain): strip_ansi fucntion to remove ANSI escape sequences (#32200)
**Description:** 
Fixes a bug in the file callback test where ANSI escape codes were
causing test failures. The improved test now properly handles ANSI
escape sequences by:
- Using exact string comparison instead of substring checking
- Applying the `strip_ansi` function consistently to all file contents
- Adding descriptive assertion messages
- Maintaining test coverage and backward compatibility

The changes ensure tests pass reliably even when terminal control
sequences are present in the output

**Issue:** Fixes #32150

**Dependencies:** None required - uses existing dependencies only.

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
2025-07-25 15:53:19 +00:00
niceg
0d6f915442 fix: LLM mimicking Unicode responses due to forced Unicode conversion of non-ASCII characters. (#32222)
fix: Fix LLM mimicking Unicode responses due to forced Unicode
conversion of non-ASCII characters.

- **Description:** This PR fixes an issue where the LLM would mimic
Unicode responses due to forced Unicode conversion of non-ASCII
characters in tool calls. The fix involves disabling the `ensure_ascii`
flag in `json.dumps()` when converting tool calls to OpenAI format.
- **Issue:** Fixes ↓↓↓
input:
```json
{'role': 'assistant', 'tool_calls': [{'type': 'function', 'id': 'call_nv9trcehdpihr21zj9po19vq', 'function': {'name': 'create_customer', 'arguments': '{"customer_name": "你好啊集团"}'}}]}
```
output:
```json
{'role': 'assistant', 'tool_calls': [{'type': 'function', 'id': 'call_nv9trcehdpihr21zj9po19vq', 'function': {'name': 'create_customer', 'arguments': '{"customer_name": "\\u4f60\\u597d\\u554a\\u96c6\\u56e2"}'}}]}
```
then:
llm will mimic outputting unicode. Unicode's vast number of symbols can
lengthen LLM responses, leading to slower performance.
<img width="686" height="277" alt="image"
src="https://github.com/user-attachments/assets/28f3b007-3964-4455-bee2-68f86ac1906d"
/>

---------

Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
2025-07-24 17:01:31 -04:00
Mason Daugherty
d53ebf367e fix(docs): capitalization, codeblock formatting, and hyperlinks, note blocks (#32235)
widespread cleanup attempt
2025-07-24 16:55:04 -04:00
Copilot
54542b9385 docs(openai): add comprehensive documentation and examples for extra_body + others (#32149)
This PR addresses the common issue where users struggle to pass custom
parameters to OpenAI-compatible APIs like LM Studio, vLLM, and others.
The problem occurs when users try to use `model_kwargs` for custom
parameters, which causes API errors.

## Problem

Users attempting to pass custom parameters (like LM Studio's `ttl`
parameter) were getting errors:

```python
#  This approach fails
llm = ChatOpenAI(
    base_url="http://localhost:1234/v1",
    model="mlx-community/QwQ-32B-4bit",
    model_kwargs={"ttl": 5}  # Causes TypeError: unexpected keyword argument 'ttl'
)
```

## Solution

The `extra_body` parameter is the correct way to pass custom parameters
to OpenAI-compatible APIs:

```python
#  This approach works correctly
llm = ChatOpenAI(
    base_url="http://localhost:1234/v1",
    model="mlx-community/QwQ-32B-4bit",
    extra_body={"ttl": 5}  # Custom parameters go in extra_body
)
```

## Changes Made

1. **Enhanced Documentation**: Updated the `extra_body` parameter
docstring with comprehensive examples for LM Studio, vLLM, and other
providers

2. **Added Documentation Section**: Created a new "OpenAI-compatible
APIs" section in the main class docstring with practical examples

3. **Unit Tests**: Added tests to verify `extra_body` functionality
works correctly:
- `test_extra_body_parameter()`: Verifies custom parameters are included
in request payload
- `test_extra_body_with_model_kwargs()`: Ensures `extra_body` and
`model_kwargs` work together

4. **Clear Guidance**: Documented when to use `extra_body` vs
`model_kwargs`

## Examples Added

**LM Studio with TTL (auto-eviction):**
```python
ChatOpenAI(
    base_url="http://localhost:1234/v1",
    api_key="lm-studio",
    model="mlx-community/QwQ-32B-4bit",
    extra_body={"ttl": 300}  # Auto-evict after 5 minutes
)
```

**vLLM with custom sampling:**
```python
ChatOpenAI(
    base_url="http://localhost:8000/v1",
    api_key="EMPTY",
    model="meta-llama/Llama-2-7b-chat-hf",
    extra_body={
        "use_beam_search": True,
        "best_of": 4
    }
)
```

## Why This Works

- `model_kwargs` parameters are passed directly to the OpenAI client's
`create()` method, causing errors for non-standard parameters
- `extra_body` parameters are included in the HTTP request body, which
is exactly what OpenAI-compatible APIs expect for custom parameters

Fixes #32115.

<!-- START COPILOT CODING AGENT TIPS -->
---

💬 Share your feedback on Copilot coding agent for the chance to win a
$200 gift card! Click
[here](https://survey.alchemer.com/s3/8343779/Copilot-Coding-agent) to
start the survey.

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: mdrxy <61371264+mdrxy@users.noreply.github.com>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
2025-07-24 16:43:16 -04:00
Mason Daugherty
7d2a13f519 fix: various typos (#32231) 2025-07-24 12:35:08 -04:00
Christophe Bornet
0b34be4ce5 refactor(langchain): refactor unit test stub classes (#32209)
See
https://github.com/langchain-ai/langchain/pull/32098#discussion_r2225961563
2025-07-24 11:05:56 -04:00
Mason Daugherty
6f3169eb49 chore: update copilot development guidelines for clarity and structure (#32230) 2025-07-24 15:05:09 +00:00
Eugene Yurtsev
7995c719c5 chore(langchain_v1): clean anything uncertain (#32228)
Further clean up of namespace:

- Removed prompts (we'll re-add in a separate commit)
- Remove LocalFileStore until we can review whether all the
implementation details are necessary
- Remove message processing logic from memory (we'll figure out where to
expose it)
- Remove `Tool` primitive (should be sufficient to use `BaseTool` for
typing purposes)
- Remove utilities to create kv stores. Unclear if they've had much
usage outside MultiparentRetriever
2025-07-24 14:41:05 +00:00
Mason Daugherty
bdf1cd383c fix(langchain): update deps 2025-07-24 10:37:08 -04:00
Mason Daugherty
77c981999e fix(text-splitters): update langchain-core version to 0.3.72 2025-07-24 10:35:07 -04:00
Mason Daugherty
7f015b6f14 fix(text-splitters): update lock for release 2025-07-24 10:32:04 -04:00
Mason Daugherty
71ad451e1f Merge branch 'master' of github.com:langchain-ai/langchain 2025-07-24 10:24:17 -04:00
Mason Daugherty
2c42893703 fix(langchain): update langchain-core version to 0.3.72 2025-07-24 10:24:04 -04:00
Mason Daugherty
0e139fb9a6 release(langchain): 0.3.27 (#32227) 2025-07-24 10:20:20 -04:00
tanwirahmad
622bb05751 fix(langchain): class HTMLSemanticPreservingSplitter ignores the text inside the div tag (#32213)
**Description:** We collect the text from the "html", "body", "div", and
"main" nodes, if they have any.

**Issue:** Fixes #32206.
2025-07-24 10:09:03 -04:00
Eugene Yurtsev
56dde3ade3 feat(langchain): v1 scaffolding (#32166)
This PR adds scaffolding for langchain 1.0 entry package.

Most contents have been removed. 

Currently remaining entrypoints for:

* chat models
* embedding models
* memory -> trimming messages, filtering messages and counting tokens
[we may remove this]
* prompts -> we may remove some prompts
* storage: primarily to support cache backed embeddings, may remove the
kv store
* tools -> report tool primitives

Things to be added:

* Selected agent implementations
* Selected workflows
* Common primitives: messages, Document
* Primitives for type hinting: BaseChatModel, BaseEmbeddings
* Selected retrievers
* Selected text splitters

Things to be removed:

* Globals needs to be removed (needs an update in langchain core)


Todos: 

* TBD indexing api (requires sqlalchemy which we don't want as a
dependency)
* Be explicit about public/private interfaces (e.g., likely rename
chat_models.base.py to something more internal)
* Remove dockerfiles
* Update module doc-strings and README.md
2025-07-24 09:47:48 -04:00
Mason Daugherty
bd3d6496f3 release(core): 0.3.72 (#32214)
fixes #32170
2025-07-23 20:33:48 -04:00
jmaillefaud
fb5da8384e fix(core): Dereference Refs for pydantic schema fails in tool schema generation (#32203)
The `_dereference_refs_helper` in `langchain_core.utils.json_schema`
incorrectly handled objects with a reference and other fields.

**Issue**: #32170

# Description

We change the check so that it accepts other keys in the object.
2025-07-23 20:28:27 -04:00
Maxime Grenu
a7d0e42f3f docs: fix typos in documentation (#32201)
## Summary
- Fixed redundant word "done" in SECURITY.md line 69  
- Fixed grammar errors in Fireworks README.md line 77: "how it fares
compares" → "how it compares" and "in terms just" → "in terms of"

## Test plan
- [x] Verified changes improve readability and correct grammar
- [x] No functional changes, documentation only

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-authored-by: Claude <claude@anthropic.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-07-23 10:43:25 -04:00
Christophe Bornet
3496e1739e feat(langchain): add ruff rules PL (#32079)
See https://docs.astral.sh/ruff/rules/#pylint-pl
2025-07-22 23:55:32 -04:00
Jacob Lee
0f39155f62 docs: Specify environment variables for BedrockConverse (#32194) 2025-07-22 17:37:47 -04:00
ccurme
6aeda24a07 docs(chroma): update feature table (#32193)
Supports multi-tenancy.
2025-07-22 20:55:07 +00:00
Mason Daugherty
3ed804a5f3 fix(perplexity): undo xfails (#32192) 2025-07-22 16:29:37 -04:00
464 changed files with 16868 additions and 5417 deletions

View File

@@ -5,26 +5,31 @@ This project includes a [dev container](https://containers.dev/), which lets you
You can use the dev container configuration in this folder to build and run the app without needing to install any of its tools locally! You can use it in [GitHub Codespaces](https://github.com/features/codespaces) or the [VS Code Dev Containers extension](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers).
## GitHub Codespaces
[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/langchain-ai/langchain)
You may use the button above, or follow these steps to open this repo in a Codespace:
1. Click the **Code** drop-down menu at the top of https://github.com/langchain-ai/langchain.
1. Click the **Code** drop-down menu at the top of <https://github.com/langchain-ai/langchain>.
1. Click on the **Codespaces** tab.
1. Click **Create codespace on master**.
For more info, check out the [GitHub documentation](https://docs.github.com/en/free-pro-team@latest/github/developing-online-with-codespaces/creating-a-codespace#creating-a-codespace).
## VS Code Dev Containers
[![Open in Dev Containers](https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchain)
Note: If you click the link above you will open the main repo (langchain-ai/langchain) and not your local cloned repo. This is fine if you only want to run and test the library, but if you want to contribute you can use the link below and replace with your username and cloned repo name:
```
https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/<yourusername>/<yourclonedreponame>
> [!NOTE]
> If you click the link above you will open the main repo (`langchain-ai/langchain`) and *not* your local cloned repo. This is fine if you only want to run and test the library, but if you want to contribute you can use the link below and replace with your username and cloned repo name:
```txt
https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/&lt;YOUR_USERNAME&gt;/&lt;YOUR_CLONED_REPO_NAME&gt;
```
Then you will have a local cloned repo where you can contribute and then create pull requests.
If you already have VS Code and Docker installed, you can use the button above to get started. This will cause VS Code to automatically install the Dev Containers extension if needed, clone the source code into a container volume, and spin up a dev container for use.
If you already have VS Code and Docker installed, you can use the button above to get started. This will use VSCode to automatically install the Dev Containers extension if needed, clone the source code into a container volume, and spin up a dev container for use.
Alternatively you can also follow these steps to open this repo in a container using the VS Code Dev Containers extension:
@@ -40,5 +45,5 @@ You can learn more in the [Dev Containers documentation](https://code.visualstud
## Tips and tricks
* If you are working with the same repository folder in a container and Windows, you'll want consistent line endings (otherwise you may see hundreds of changes in the SCM view). The `.gitattributes` file in the root of this repo will disable line ending conversion and should prevent this. See [tips and tricks](https://code.visualstudio.com/docs/devcontainers/tips-and-tricks#_resolving-git-line-ending-issues-in-containers-resulting-in-many-modified-files) for more info.
* If you'd like to review the contents of the image used in this dev container, you can check it out in the [devcontainers/images](https://github.com/devcontainers/images/tree/main/src/python) repo.
- If you are working with the same repository folder in a container and Windows, you'll want consistent line endings (otherwise you may see hundreds of changes in the SCM view). The `.gitattributes` file in the root of this repo will disable line ending conversion and should prevent this. See [tips and tricks](https://code.visualstudio.com/docs/devcontainers/tips-and-tricks#_resolving-git-line-ending-issues-in-containers-resulting-in-many-modified-files) for more info.
- If you'd like to review the contents of the image used in this dev container, you can check it out in the [devcontainers/images](https://github.com/devcontainers/images/tree/main/src/python) repo.

View File

@@ -1,36 +1,58 @@
// For format details, see https://aka.ms/devcontainer.json. For config options, see the
// README at: https://github.com/devcontainers/templates/tree/main/src/docker-existing-docker-compose
{
// Name for the dev container
"name": "langchain",
// Point to a Docker Compose file
"dockerComposeFile": "./docker-compose.yaml",
// Required when using Docker Compose. The name of the service to connect to once running
"service": "langchain",
// The optional 'workspaceFolder' property is the path VS Code should open by default when
// connected. This is typically a file mount in .devcontainer/docker-compose.yml
"workspaceFolder": "/workspaces/langchain",
// Prevent the container from shutting down
"overrideCommand": true
// Features to add to the dev container. More info: https://containers.dev/features
// "features": {
// "ghcr.io/devcontainers-contrib/features/poetry:2": {}
// }
// Use 'forwardPorts' to make a list of ports inside the container available locally.
// "forwardPorts": [],
// Uncomment the next line to run commands after the container is created.
// "postCreateCommand": "cat /etc/os-release",
// Configure tool-specific properties.
// "customizations": {},
// Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
// "remoteUser": "root"
// Name for the dev container
"name": "langchain",
// Point to a Docker Compose file
"dockerComposeFile": "./docker-compose.yaml",
// Required when using Docker Compose. The name of the service to connect to once running
"service": "langchain",
// The optional 'workspaceFolder' property is the path VS Code should open by default when
// connected. This is typically a file mount in .devcontainer/docker-compose.yml
"workspaceFolder": "/workspaces/langchain",
"mounts": [
"source=langchain-workspaces,target=/workspaces/langchain,type=volume"
],
// Prevent the container from shutting down
"overrideCommand": true,
// Features to add to the dev container. More info: https://containers.dev/features
"features": {
"ghcr.io/devcontainers/features/git:1": {},
"ghcr.io/devcontainers/features/github-cli:1": {}
},
"containerEnv": {
"UV_LINK_MODE": "copy"
},
// Use 'forwardPorts' to make a list of ports inside the container available locally.
// "forwardPorts": [],
// Run commands after the container is created
"postCreateCommand": "uv sync && echo 'LangChain (Python) dev environment ready!'",
// Configure tool-specific properties.
"customizations": {
"vscode": {
"extensions": [
"ms-python.python",
"ms-python.debugpy",
"ms-python.mypy-type-checker",
"ms-python.isort",
"unifiedjs.vscode-mdx",
"davidanson.vscode-markdownlint",
"ms-toolsai.jupyter",
"GitHub.copilot",
"GitHub.copilot-chat"
],
"settings": {
"python.defaultInterpreterPath": ".venv/bin/python",
"python.formatting.provider": "none",
"[python]": {
"editor.formatOnSave": true,
"editor.codeActionsOnSave": {
"source.organizeImports": true
}
}
}
}
}
// Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
// "remoteUser": "root"
}

View File

@@ -4,26 +4,9 @@ services:
build:
dockerfile: libs/langchain/dev.Dockerfile
context: ..
volumes:
# Update this to wherever you want VS Code to mount the folder of your project
- ..:/workspaces/langchain:cached
networks:
- langchain-network
# environment:
# MONGO_ROOT_USERNAME: root
# MONGO_ROOT_PASSWORD: example123
# depends_on:
# - mongo
# mongo:
# image: mongo
# restart: unless-stopped
# environment:
# MONGO_INITDB_ROOT_USERNAME: root
# MONGO_INITDB_ROOT_PASSWORD: example123
# ports:
# - "27017:27017"
# networks:
# - langchain-network
networks:
langchain-network:

52
.editorconfig Normal file
View File

@@ -0,0 +1,52 @@
# top-most EditorConfig file
root = true
# All files
[*]
charset = utf-8
end_of_line = lf
insert_final_newline = true
trim_trailing_whitespace = true
# Python files
[*.py]
indent_style = space
indent_size = 4
max_line_length = 88
# JSON files
[*.json]
indent_style = space
indent_size = 2
# YAML files
[*.{yml,yaml}]
indent_style = space
indent_size = 2
# Markdown files
[*.md]
indent_style = space
indent_size = 2
trim_trailing_whitespace = false
# Configuration files
[*.{toml,ini,cfg}]
indent_style = space
indent_size = 4
# Shell scripts
[*.sh]
indent_style = space
indent_size = 2
# Makefile
[Makefile]
indent_style = tab
indent_size = 4
# Jupyter notebooks
[*.ipynb]
# Jupyter may include trailing whitespace in cell
# outputs that's semantically meaningful
trim_trailing_whitespace = false

View File

@@ -1,72 +1,116 @@
### 1. Avoid Breaking Changes (Stable Public Interfaces)
# Global Development Guidelines for LangChain Projects
* Carefully preserve **function signatures**, argument positions, and names for any exported/public methods.
* Be cautious when **renaming**, **removing**, or **reordering** arguments — even small changes can break downstream consumers.
* Use keyword-only arguments or clearly mark experimental features to isolate unstable APIs.
## Core Development Principles
Bad:
### 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:
**Good - Stable Interface:**
```python
def get_user(user_id: str, verbose: bool = False): # Maintains stable interface
def get_user(user_id: str, verbose: bool = False) -> User:
"""Retrieve user by ID with optional verbose output."""
pass
```
🧠 *Ask yourself:* “Would this change break someone's code if they used it last week?”
**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 reStructuredText, like `.. warning::`)
### 2. Simplify Code and Use Clear Variable Names
🧠 *Ask yourself:* "Would this change break someone's code if they used it last week?"
* Prefer descriptive, **self-explanatory variable names**. Avoid overly short or cryptic identifiers.
* Break up overly long or deeply nested functions for **readability and maintainability**.
* Avoid unnecessary abstraction or premature optimization.
* All generated Python code must include type hints and return types.
### 2. Code Quality Standards
Bad:
**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:
**Good:**
```python
def filter_unknown_users(users: List[str], known_users: Set[str]) -> List[str]:
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:**
### 3. Ensure Unit Tests Cover New and Updated Functionality
- 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
* Every new feature or bugfix should be **covered by a unit test**.
* Test edge cases and failure conditions.
* Use `pytest`, `unittest`, or the projects existing framework consistently.
### 3. Testing Requirements
Checklist:
**Every new feature or bugfix MUST be covered by unit tests.**
* [ ] 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?
**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
### 4. Look for Suspicious or Risky Code
**Test Quality Checklist:**
* Watch out for:
- [ ] 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)
* Use of `eval()`, `exec()`, or `pickle` on user-controlled input.
* Silent failure modes (`except: pass`).
* Unreachable code or commented-out blocks.
* Race conditions or resource leaks (file handles, sockets, threads).
Checklist questions:
Bad:
- [ ] 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):
@@ -74,7 +118,7 @@ def load_config(path):
return eval(f.read()) # ⚠️ Never eval config
```
Good:
**Good:**
```python
import json
@@ -84,68 +128,198 @@ def load_config(path: str) -> dict:
return json.load(f)
```
---
### 5. Documentation Standards
### 5. Use Google-Style Docstrings (with Args section)
**Use Google-style docstrings with Args section for all public functions.**
* All public functions should include a **Google-style docstring**.
* Include an `Args:` section where relevant.
* Types should NOT be written in the docstring — use type hints instead.
Bad:
**Insufficient Documentation:**
```python
def send_email(to, msg):
"""Send an email to a recipient."""
```
Good:
**Complete Documentation:**
```python
def send_email(to: str, msg: str) -> None:
def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
"""
Sends an email to a recipient.
Send an email to a recipient with specified priority.
Args:
to: The email address of the recipient.
msg: The message body.
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
- Use reStructuredText for docstrings to enable rich formatting
📌 *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
---
### 6. Propose Better Designs When Applicable
## Quick Reference Checklist
* If there's a **cleaner**, **more scalable**, or **simpler** design, highlight it.
* Suggest improvements, even if they require some refactoring — especially if the new code would:
Before submitting code changes:
* Reduce duplication
* Make unit testing easier
* Improve separation of concerns
* Add clarity without adding complexity
Instead of:
```python
def save(data, db_conn):
# manually serializes fields
```
You might suggest:
```python
# Suggest using dataclasses or Pydantic for automatic serialization and validation
```
### 7. Misc
* When suggesting package installation commands, use `uv pip install` as this project uses `uv`.
* When creating tools for agents, use the @tool decorator from langchain_core.tools. The tool's docstring serves as its functional description for the agent.
* Avoid suggesting deprecated components, such as the legacy LLMChain.
* We use Conventional Commits format for pull request titles. 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
- [ ] **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

@@ -16,6 +16,7 @@ LANGCHAIN_DIRS = [
"libs/core",
"libs/text-splitters",
"libs/langchain",
"libs/langchain_v1",
]
# when set to True, we are ignoring core dependents

View File

@@ -73,6 +73,7 @@ def main():
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
@@ -82,6 +83,7 @@ def main():
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

View File

@@ -1,4 +1,4 @@
name: compile-integration-test
name: '🔗 Compile Integration Tests'
on:
workflow_call:
@@ -25,24 +25,24 @@ jobs:
working-directory: ${{ inputs.working-directory }}
runs-on: ubuntu-latest
timeout-minutes: 20
name: "uv run pytest -m compile tests/integration_tests #${{ inputs.python-version }}"
name: 'Python ${{ inputs.python-version }}'
steps:
- uses: actions/checkout@v4
- name: Set up Python ${{ inputs.python-version }} + uv
- name: '🐍 Set up Python ${{ inputs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ inputs.python-version }}
- name: Install integration dependencies
- name: '📦 Install Integration Dependencies'
shell: bash
run: uv sync --group test --group test_integration
- name: Check integration tests compile
- name: '🔗 Check Integration Tests Compile'
shell: bash
run: uv run pytest -m compile tests/integration_tests
- name: Ensure the tests did not create any additional files
- name: '🧹 Verify Clean Working Directory'
shell: bash
run: |
set -eu

View File

@@ -1,4 +1,4 @@
name: Integration Tests
name: '🚀 Integration Tests'
on:
workflow_dispatch:
@@ -24,20 +24,20 @@ jobs:
run:
working-directory: ${{ inputs.working-directory }}
runs-on: ubuntu-latest
name: Python ${{ inputs.python-version }}
name: '🚀 Integration Tests (Python ${{ inputs.python-version }})'
steps:
- uses: actions/checkout@v4
- name: Set up Python ${{ inputs.python-version }} + uv
- name: '🐍 Set up Python ${{ inputs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ inputs.python-version }}
- name: Install dependencies
- name: '📦 Install Integration Dependencies'
shell: bash
run: uv sync --group test --group test_integration
- name: Run integration tests
- name: '🚀 Run Integration Tests'
shell: bash
env:
AI21_API_KEY: ${{ secrets.AI21_API_KEY }}

View File

@@ -1,4 +1,6 @@
name: lint
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:
@@ -24,19 +26,21 @@ env:
UV_FROZEN: "true"
jobs:
# Linting job - runs quality checks on package and test code
build:
name: "make lint #${{ inputs.python-version }}"
name: 'Python ${{ inputs.python-version }}'
runs-on: ubuntu-latest
timeout-minutes: 20
steps:
- uses: actions/checkout@v4
- name: '📋 Checkout Code'
uses: actions/checkout@v4
- name: Set up Python ${{ inputs.python-version }} + uv
- name: '🐍 Set up Python ${{ inputs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ inputs.python-version }}
- name: Install dependencies
- 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:
@@ -49,12 +53,12 @@ jobs:
run: |
uv sync --group lint --group typing
- name: Analysing the code with our lint
- name: '🔍 Analyze Package Code with Linters'
working-directory: ${{ inputs.working-directory }}
run: |
make lint_package
- name: Install unit test dependencies
- 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:
@@ -67,13 +71,13 @@ jobs:
working-directory: ${{ inputs.working-directory }}
run: |
uv sync --inexact --group test
- name: Install unit+integration test dependencies
- name: '📦 Install Unit + Integration Test Dependencies'
if: ${{ startsWith(inputs.working-directory, 'libs/partners/') }}
working-directory: ${{ inputs.working-directory }}
run: |
uv sync --inexact --group test --group test_integration
- name: Analysing the code with our lint
- name: '🔍 Analyze Test Code with Linters'
working-directory: ${{ inputs.working-directory }}
run: |
make lint_tests

View File

@@ -1,5 +1,5 @@
name: Release
run-name: Release ${{ inputs.working-directory }} by @${{ github.actor }}
name: '🚀 Package Release'
run-name: '🚀 Release ${{ inputs.working-directory }} by @${{ github.actor }}'
on:
workflow_call:
inputs:
@@ -18,7 +18,7 @@ on:
required: false
type: boolean
default: false
description: "Release from a non-master branch (danger!)"
description: "Release from a non-master branch (danger!) - Only use for hotfixes"
env:
PYTHON_VERSION: "3.11"
@@ -26,6 +26,8 @@ env:
UV_NO_SYNC: "true"
jobs:
# Build the distribution package and extract version info
# Runs in isolated environment with minimal permissions for security
build:
if: github.ref == 'refs/heads/master' || inputs.dangerous-nonmaster-release
environment: Scheduled testing

View File

@@ -1,4 +1,6 @@
name: test
name: '🧪 Unit Testing'
# Runs unit tests with both current and minimum supported dependency versions
# to ensure compatibility across the supported range
on:
workflow_call:
@@ -20,31 +22,33 @@ env:
UV_NO_SYNC: "true"
jobs:
# Main test job - runs unit tests with current deps, then retests with minimum versions
build:
defaults:
run:
working-directory: ${{ inputs.working-directory }}
runs-on: ubuntu-latest
timeout-minutes: 20
name: "make test #${{ inputs.python-version }}"
name: 'Python ${{ inputs.python-version }}'
steps:
- uses: actions/checkout@v4
- name: '📋 Checkout Code'
uses: actions/checkout@v4
- name: Set up Python ${{ inputs.python-version }} + uv
- name: '🐍 Set up Python ${{ inputs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
id: setup-python
with:
python-version: ${{ inputs.python-version }}
- name: Install dependencies
- name: '📦 Install Test Dependencies'
shell: bash
run: uv sync --group test --dev
- name: Run core tests
- name: '🧪 Run Core Unit Tests'
shell: bash
run: |
make test
- name: Get minimum versions
- name: '🔍 Calculate Minimum Dependency Versions'
working-directory: ${{ inputs.working-directory }}
id: min-version
shell: bash
@@ -55,7 +59,7 @@ jobs:
echo "min-versions=$min_versions" >> "$GITHUB_OUTPUT"
echo "min-versions=$min_versions"
- name: Run unit tests with minimum dependency versions
- name: '🧪 Run Tests with Minimum Dependencies'
if: ${{ steps.min-version.outputs.min-versions != '' }}
env:
MIN_VERSIONS: ${{ steps.min-version.outputs.min-versions }}
@@ -64,7 +68,7 @@ jobs:
make tests
working-directory: ${{ inputs.working-directory }}
- name: Ensure the tests did not create any additional files
- name: '🧹 Verify Clean Working Directory'
shell: bash
run: |
set -eu

View File

@@ -1,4 +1,4 @@
name: test_doc_imports
name: '📑 Documentation Import Testing'
on:
workflow_call:
@@ -18,29 +18,30 @@ jobs:
build:
runs-on: ubuntu-latest
timeout-minutes: 20
name: "check doc imports #${{ inputs.python-version }}"
name: '🔍 Check Doc Imports (Python ${{ inputs.python-version }})'
steps:
- uses: actions/checkout@v4
- name: '📋 Checkout Code'
uses: actions/checkout@v4
- name: Set up Python ${{ inputs.python-version }} + uv
- name: '🐍 Set up Python ${{ inputs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ inputs.python-version }}
- name: Install dependencies
- name: '📦 Install Test Dependencies'
shell: bash
run: uv sync --group test
- name: Install langchain editable
- name: '📦 Install LangChain in Editable Mode'
run: |
VIRTUAL_ENV=.venv uv pip install langchain-experimental langchain-community -e libs/core libs/langchain
- name: Check doc imports
- name: '🔍 Validate Documentation Import Statements'
shell: bash
run: |
uv run python docs/scripts/check_imports.py
- name: Ensure the test did not create any additional files
- name: '🧹 Verify Clean Working Directory'
shell: bash
run: |
set -eu

View File

@@ -1,4 +1,4 @@
name: test pydantic intermediate versions
name: '🐍 Pydantic Version Testing'
on:
workflow_call:
@@ -31,29 +31,30 @@ jobs:
working-directory: ${{ inputs.working-directory }}
runs-on: ubuntu-latest
timeout-minutes: 20
name: "make test # pydantic: ~=${{ inputs.pydantic-version }}, python: ${{ inputs.python-version }}, "
name: 'Pydantic ~=${{ inputs.pydantic-version }}'
steps:
- uses: actions/checkout@v4
- name: '📋 Checkout Code'
uses: actions/checkout@v4
- name: Set up Python ${{ inputs.python-version }} + uv
- name: '🐍 Set up Python ${{ inputs.python-version }} + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ inputs.python-version }}
- name: Install dependencies
- name: '📦 Install Test Dependencies'
shell: bash
run: uv sync --group test
- name: Overwrite pydantic version
- name: '🔄 Install Specific Pydantic Version'
shell: bash
run: VIRTUAL_ENV=.venv uv pip install pydantic~=${{ inputs.pydantic-version }}
- name: Run core tests
- name: '🧪 Run Core Tests'
shell: bash
run: |
make test
- name: Ensure the tests did not create any additional files
- name: '🧹 Verify Clean Working Directory'
shell: bash
run: |
set -eu

View File

@@ -1,4 +1,4 @@
name: test-release
name: '🧪 Test Release Package'
on:
workflow_call:
@@ -29,7 +29,7 @@ jobs:
steps:
- uses: actions/checkout@v4
- name: Set up Python + uv
- name: '🐍 Set up Python + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ env.PYTHON_VERSION }}
@@ -45,17 +45,17 @@ jobs:
# > 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
- name: '📦 Build Project for Distribution'
run: uv build
working-directory: ${{ inputs.working-directory }}
- name: Upload build
- name: '⬆️ Upload Build Artifacts'
uses: actions/upload-artifact@v4
with:
name: test-dist
path: ${{ inputs.working-directory }}/dist/
- name: Check Version
- name: '🔍 Extract Version Information'
id: check-version
shell: python
working-directory: ${{ inputs.working-directory }}

View File

@@ -1,17 +1,20 @@
name: API Docs Build
name: '📚 API Documentation Build'
# Runs daily or can be triggered manually for immediate updates
on:
workflow_dispatch:
schedule:
- cron: '0 13 * * *'
- 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: write-all
permissions:
contents: read
steps:
- uses: actions/checkout@v4
with:
@@ -22,7 +25,7 @@ jobs:
path: langchain-api-docs-html
token: ${{ secrets.TOKEN_GITHUB_API_DOCS_HTML }}
- name: Get repos with yq
- name: '📋 Extract Repository List with yq'
id: get-unsorted-repos
uses: mikefarah/yq@master
with:
@@ -41,7 +44,7 @@ jobs:
| .repo
' langchain/libs/packages.yml
- name: Parse YAML and checkout repos
- name: '📋 Parse YAML & Checkout Repositories'
env:
REPOS_UNSORTED: ${{ steps.get-unsorted-repos.outputs.result }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -49,48 +52,59 @@ jobs:
# Get unique repositories
REPOS=$(echo "$REPOS_UNSORTED" | sort -u)
# Checkout each unique repository that is in langchain-ai org
# Checkout each unique repository
for repo in $REPOS; do
# Validate repository format (allow any org with proper format)
if [[ ! "$repo" =~ ^[a-zA-Z0-9_.-]+/[a-zA-Z0-9_.-]+$ ]]; then
echo "Error: Invalid repository format: $repo"
exit 1
fi
REPO_NAME=$(echo $repo | cut -d'/' -f2)
# Additional validation for repo name
if [[ ! "$REPO_NAME" =~ ^[a-zA-Z0-9_.-]+$ ]]; then
echo "Error: Invalid repository name: $REPO_NAME"
exit 1
fi
echo "Checking out $repo to $REPO_NAME"
git clone --depth 1 https://github.com/$repo.git $REPO_NAME
done
- name: Setup Python ${{ env.PYTHON_VERSION }}
- name: '🐍 Setup Python ${{ env.PYTHON_VERSION }}'
uses: actions/setup-python@v5
id: setup-python
with:
python-version: ${{ env.PYTHON_VERSION }}
- name: Install initial py deps
- 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: Move libs
- name: '📦 Organize Library Directories'
run: python langchain/.github/scripts/prep_api_docs_build.py
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Rm old html
- name: '🧹 Remove Old HTML Files'
run:
rm -rf langchain-api-docs-html/api_reference_build/html
- name: Install dependencies
- name: '📦 Install Documentation Dependencies'
working-directory: langchain
run: |
python -m uv pip install $(ls ./libs/partners | xargs -I {} echo "./libs/partners/{}") --overrides ./docs/vercel_overrides.txt
python -m uv pip install libs/core libs/langchain libs/text-splitters libs/community libs/experimental libs/standard-tests
python -m uv pip install -r docs/api_reference/requirements.txt
- name: Set Git config
- 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 docs
- name: '📚 Build API Documentation'
working-directory: langchain
run: |
python docs/api_reference/create_api_rst.py

View File

@@ -1,4 +1,4 @@
name: Check Broken Links
name: '🔗 Check Broken Links'
on:
workflow_dispatch:
@@ -14,15 +14,15 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Use Node.js 18.x
- 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 dependencies
- name: '📦 Install Node Dependencies'
run: yarn install --immutable --mode=skip-build
working-directory: ./docs
- name: Check broken links
- name: '🔍 Scan Documentation for Broken Links'
run: yarn check-broken-links
working-directory: ./docs

View File

@@ -1,4 +1,6 @@
name: Check `core` 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:
@@ -16,7 +18,7 @@ jobs:
steps:
- uses: actions/checkout@v4
- name: Check version equality
- name: '✅ Verify pyproject.toml & version.py Match'
run: |
PYPROJECT_VERSION=$(grep -Po '(?<=^version = ")[^"]*' libs/core/pyproject.toml)
VERSION_PY_VERSION=$(grep -Po '(?<=^VERSION = ")[^"]*' libs/core/langchain_core/version.py)

View File

@@ -1,4 +1,4 @@
name: CI
name: '🔧 CI'
on:
push:
@@ -6,6 +6,7 @@ on:
pull_request:
merge_group:
# Optimizes CI performance by canceling redundant workflow runs
# 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.
#
@@ -24,16 +25,23 @@ env:
UV_NO_SYNC: "true"
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'
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
- name: '📋 Checkout Code'
uses: actions/checkout@v4
- name: '🐍 Setup Python 3.11'
uses: actions/setup-python@v5
with:
python-version: '3.11'
- id: files
- name: '📂 Get Changed Files'
id: files
uses: Ana06/get-changed-files@v2.3.0
- id: set-matrix
- name: '🔍 Analyze Changed Files & Generate Build Matrix'
id: set-matrix
run: |
python -m pip install packaging requests
python .github/scripts/check_diff.py ${{ steps.files.outputs.all }} >> $GITHUB_OUTPUT
@@ -45,8 +53,8 @@ jobs:
dependencies: ${{ steps.set-matrix.outputs.dependencies }}
test-doc-imports: ${{ steps.set-matrix.outputs.test-doc-imports }}
test-pydantic: ${{ steps.set-matrix.outputs.test-pydantic }}
# Run linting only on packages that have changed files
lint:
name: cd ${{ matrix.job-configs.working-directory }}
needs: [ build ]
if: ${{ needs.build.outputs.lint != '[]' }}
strategy:
@@ -59,8 +67,8 @@ jobs:
python-version: ${{ matrix.job-configs.python-version }}
secrets: inherit
# Run unit tests only on packages that have changed files
test:
name: cd ${{ matrix.job-configs.working-directory }}
needs: [ build ]
if: ${{ needs.build.outputs.test != '[]' }}
strategy:
@@ -73,8 +81,8 @@ jobs:
python-version: ${{ matrix.job-configs.python-version }}
secrets: inherit
# Test compatibility with different Pydantic versions for affected packages
test-pydantic:
name: cd ${{ matrix.job-configs.working-directory }}
needs: [ build ]
if: ${{ needs.build.outputs.test-pydantic != '[]' }}
strategy:
@@ -95,12 +103,12 @@ jobs:
job-configs: ${{ fromJson(needs.build.outputs.test-doc-imports) }}
fail-fast: false
uses: ./.github/workflows/_test_doc_imports.yml
secrets: inherit
with:
python-version: ${{ matrix.job-configs.python-version }}
secrets: inherit
# Verify integration tests compile without actually running them (faster feedback)
compile-integration-tests:
name: cd ${{ matrix.job-configs.working-directory }}
needs: [ build ]
if: ${{ needs.build.outputs.compile-integration-tests != '[]' }}
strategy:
@@ -113,8 +121,9 @@ jobs:
python-version: ${{ matrix.job-configs.python-version }}
secrets: inherit
# Run extended test suites that require additional dependencies
extended-tests:
name: "cd ${{ matrix.job-configs.working-directory }} / make extended_tests #${{ matrix.job-configs.python-version }}"
name: 'Extended Tests'
needs: [ build ]
if: ${{ needs.build.outputs.extended-tests != '[]' }}
strategy:
@@ -130,12 +139,12 @@ jobs:
steps:
- 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: ${{ matrix.job-configs.python-version }}
- name: Install dependencies and run extended tests
- name: '📦 Install Dependencies & Run Extended Tests'
shell: bash
run: |
echo "Running extended tests, installing dependencies with uv..."
@@ -144,7 +153,7 @@ jobs:
VIRTUAL_ENV=.venv uv pip install -r extended_testing_deps.txt
VIRTUAL_ENV=.venv make extended_tests
- name: Ensure the tests did not create any additional files
- name: '🧹 Verify Clean Working Directory'
shell: bash
run: |
set -eu
@@ -156,8 +165,9 @@ jobs:
# and `set -e` above will cause the step to fail.
echo "$STATUS" | grep 'nothing to commit, working tree clean'
# Final status check - ensures all required jobs passed before allowing merge
ci_success:
name: "CI Success"
name: '✅ CI Success'
needs: [build, lint, test, compile-integration-tests, extended-tests, test-doc-imports, test-pydantic]
if: |
always()
@@ -167,7 +177,7 @@ jobs:
RESULTS_JSON: ${{ toJSON(needs.*.result) }}
EXIT_CODE: ${{!contains(needs.*.result, 'failure') && !contains(needs.*.result, 'cancelled') && '0' || '1'}}
steps:
- name: "CI Success"
- name: '🎉 All Checks Passed'
run: |
echo $JOBS_JSON
echo $RESULTS_JSON

View File

@@ -1,4 +1,4 @@
name: Integration Docs Lint
name: '📑 Integration Docs Lint'
on:
push:
@@ -33,6 +33,6 @@ jobs:
*.ipynb
*.md
*.mdx
- name: Check new docs
- name: '🔍 Check New Documentation Templates'
run: |
python docs/scripts/check_templates.py ${{ steps.files.outputs.added }}

View File

@@ -1,35 +0,0 @@
name: CI / cd . / make spell_check
on:
push:
branches: [master, v0.1, v0.2]
pull_request:
permissions:
contents: read
jobs:
codespell:
name: (Check for spelling errors)
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v4
- name: Install Dependencies
run: |
pip install toml
- name: Extract Ignore Words List
run: |
# Use a Python script to extract the ignore words list from pyproject.toml
python .github/workflows/extract_ignored_words_list.py
id: extract_ignore_words
# - name: Codespell
# uses: codespell-project/actions-codespell@v2
# with:
# skip: guide_imports.json,*.ambr,./cookbook/data/imdb_top_1000.csv,*.lock
# ignore_words_list: ${{ steps.extract_ignore_words.outputs.ignore_words_list }}
# exclude_file: ./.github/workflows/codespell-exclude

View File

@@ -1,4 +1,4 @@
name: CodSpeed
name: '⚡ CodSpeed'
on:
push:
@@ -18,7 +18,7 @@ env:
jobs:
codspeed:
name: Run benchmarks
name: 'Benchmark'
runs-on: ubuntu-latest
strategy:
matrix:
@@ -38,7 +38,7 @@ jobs:
- uses: actions/checkout@v4
# We have to use 3.12 as 3.13 is not yet supported
- name: Install uv
- name: '📦 Install UV Package Manager'
uses: astral-sh/setup-uv@v6
with:
python-version: "3.12"
@@ -47,11 +47,11 @@ jobs:
with:
python-version: "3.12"
- name: Install dependencies
- name: '📦 Install Test Dependencies'
run: uv sync --group test
working-directory: ${{ matrix.working-directory }}
- name: Run benchmarks ${{ matrix.working-directory }}
- name: '⚡ Run Benchmarks: ${{ matrix.working-directory }}'
uses: CodSpeedHQ/action@v3
with:
token: ${{ secrets.CODSPEED_TOKEN }}

View File

@@ -1,4 +1,4 @@
name: LangChain People
name: '👥 LangChain People'
on:
schedule:
@@ -14,13 +14,13 @@ jobs:
permissions:
contents: write
steps:
- name: Dump GitHub context
- 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
- 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:

View File

@@ -4,6 +4,7 @@
# 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>
@@ -45,7 +46,7 @@
# • Conventional Commits spec: https://www.conventionalcommits.org/en/v1.0.0/
# -----------------------------------------------------------------------------
name: PR Title Lint
name: '🏷️ PR Title Lint'
permissions:
pull-requests: read
@@ -55,11 +56,12 @@ on:
types: [opened, edited, synchronize]
jobs:
# Validates that PR title follows Conventional Commits specification
lint-pr-title:
name: Validate PR Title
name: 'Validate PR Title Format'
runs-on: ubuntu-latest
steps:
- name: Validate PR Title
- name: '✅ Validate Conventional Commits Format'
uses: amannn/action-semantic-pull-request@v5
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -81,6 +83,7 @@ jobs:
core
cli
langchain
langchain_v1
standard-tests
text-splitters
docs

View File

@@ -1,4 +1,4 @@
name: Run Notebooks
name: '📝 Run Documentation Notebooks'
on:
workflow_dispatch:
@@ -24,43 +24,43 @@ jobs:
build:
runs-on: ubuntu-latest
if: github.repository == 'langchain-ai/langchain' || github.event_name != 'schedule'
name: "Test docs"
name: '📑 Test Documentation Notebooks'
steps:
- uses: actions/checkout@v4
- name: Set up Python + uv
- name: '🐍 Set up Python + UV'
uses: "./.github/actions/uv_setup"
with:
python-version: ${{ github.event.inputs.python_version || '3.11' }}
- name: 'Authenticate to Google Cloud'
- name: '🔐 Authenticate to Google Cloud'
id: 'auth'
uses: google-github-actions/auth@v2
with:
credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
- name: Configure AWS 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
- name: '📦 Install Dependencies'
run: |
uv sync --group dev --group test
- name: Pre-download files
- 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
- 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: Run notebooks
- name: '🚀 Execute Notebooks'
env:
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}

View File

@@ -1,7 +1,7 @@
name: Scheduled Tests
name: '⏰ Scheduled Integration Tests'
on:
workflow_dispatch: # Allows to trigger the workflow manually in GitHub UI
workflow_dispatch: # Allows maintainers to trigger the workflow manually in GitHub UI
inputs:
working-directory-force:
type: string
@@ -10,7 +10,7 @@ on:
type: string
description: "Python version to use - defaults to 3.9 and 3.11 in matrix - example value: 3.9"
schedule:
- cron: '0 13 * * *'
- cron: '0 13 * * *' # Runs daily at 1PM UTC (9AM EDT/6AM PDT)
permissions:
contents: read
@@ -22,14 +22,16 @@ env:
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 matrix
name: '📋 Compute Test Matrix'
outputs:
matrix: ${{ steps.set-matrix.outputs.matrix }}
steps:
- name: Set matrix
- name: '🔢 Generate Python & Library Matrix'
id: set-matrix
env:
DEFAULT_LIBS: ${{ env.DEFAULT_LIBS }}
@@ -50,9 +52,11 @@ jobs:
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 }}
name: '🐍 Python ${{ matrix.python-version }}: ${{ matrix.working-directory }}'
runs-on: ubuntu-latest
needs: [compute-matrix]
timeout-minutes: 20
@@ -75,7 +79,7 @@ jobs:
repository: langchain-ai/langchain-aws
path: langchain-aws
- name: Move libs
- name: '📦 Organize External Libraries'
run: |
rm -rf \
langchain/libs/partners/google-genai \
@@ -84,7 +88,7 @@ jobs:
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 }} with poetry
- name: '🐍 Set up Python ${{ matrix.python-version }} + Poetry'
if: contains(env.POETRY_LIBS, matrix.working-directory)
uses: "./langchain/.github/actions/poetry_setup"
with:
@@ -93,40 +97,40 @@ jobs:
working-directory: langchain/${{ matrix.working-directory }}
cache-key: scheduled
- name: Set up Python ${{ matrix.python-version }} + uv
- 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: ${{ matrix.python-version }}
- name: 'Authenticate to Google Cloud'
- name: '🔐 Authenticate to Google Cloud'
id: 'auth'
uses: google-github-actions/auth@v2
with:
credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
- name: Configure AWS 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: ${{ secrets.AWS_REGION }}
- name: Install dependencies (poetry)
- name: '📦 Install Dependencies (Poetry)'
if: contains(env.POETRY_LIBS, matrix.working-directory)
run: |
echo "Running scheduled tests, installing dependencies with poetry..."
cd langchain/${{ matrix.working-directory }}
poetry install --with=test_integration,test
- name: Install dependencies (uv)
- 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
- name: '🚀 Run Integration Tests'
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
@@ -155,14 +159,15 @@ jobs:
cd langchain/${{ matrix.working-directory }}
make integration_tests
- name: Remove external libraries
- 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: Ensure tests did not create additional files
- name: '🧹 Verify Clean Working Directory'
working-directory: langchain
run: |
set -eu

1
.gitignore vendored
View File

@@ -1,5 +1,4 @@
.vs/
.vscode/
.idea/
# Byte-compiled / optimized / DLL files
__pycache__/

14
.markdownlint.json Normal file
View File

@@ -0,0 +1,14 @@
{
"MD013": false,
"MD024": {
"siblings_only": true
},
"MD025": false,
"MD033": false,
"MD034": false,
"MD036": false,
"MD041": false,
"MD046": {
"style": "fenced"
}
}

View File

@@ -1,111 +1,111 @@
repos:
- repo: local
hooks:
- id: core
name: format core
language: system
entry: make -C libs/core format
files: ^libs/core/
pass_filenames: false
- id: langchain
name: format langchain
language: system
entry: make -C libs/langchain format
files: ^libs/langchain/
pass_filenames: false
- id: standard-tests
name: format standard-tests
language: system
entry: make -C libs/standard-tests format
files: ^libs/standard-tests/
pass_filenames: false
- id: text-splitters
name: format text-splitters
language: system
entry: make -C libs/text-splitters format
files: ^libs/text-splitters/
pass_filenames: false
- id: anthropic
name: format partners/anthropic
language: system
entry: make -C libs/partners/anthropic format
files: ^libs/partners/anthropic/
pass_filenames: false
- id: chroma
name: format partners/chroma
language: system
entry: make -C libs/partners/chroma format
files: ^libs/partners/chroma/
pass_filenames: false
- id: couchbase
name: format partners/couchbase
language: system
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 partners/fireworks
language: system
entry: make -C libs/partners/fireworks format
files: ^libs/partners/fireworks/
pass_filenames: false
- id: groq
name: format partners/groq
language: system
entry: make -C libs/partners/groq format
files: ^libs/partners/groq/
pass_filenames: false
- id: huggingface
name: format partners/huggingface
language: system
entry: make -C libs/partners/huggingface format
files: ^libs/partners/huggingface/
pass_filenames: false
- id: mistralai
name: format partners/mistralai
language: system
entry: make -C libs/partners/mistralai format
files: ^libs/partners/mistralai/
pass_filenames: false
- id: nomic
name: format partners/nomic
language: system
entry: make -C libs/partners/nomic format
files: ^libs/partners/nomic/
pass_filenames: false
- id: ollama
name: format partners/ollama
language: system
entry: make -C libs/partners/ollama format
files: ^libs/partners/ollama/
pass_filenames: false
- id: openai
name: format partners/openai
language: system
entry: make -C libs/partners/openai format
files: ^libs/partners/openai/
pass_filenames: false
- id: prompty
name: format partners/prompty
language: system
entry: make -C libs/partners/prompty format
files: ^libs/partners/prompty/
pass_filenames: false
- id: qdrant
name: format partners/qdrant
language: system
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
- repo: local
hooks:
- id: core
name: format core
language: system
entry: make -C libs/core format
files: ^libs/core/
pass_filenames: false
- id: langchain
name: format langchain
language: system
entry: make -C libs/langchain format
files: ^libs/langchain/
pass_filenames: false
- id: standard-tests
name: format standard-tests
language: system
entry: make -C libs/standard-tests format
files: ^libs/standard-tests/
pass_filenames: false
- id: text-splitters
name: format text-splitters
language: system
entry: make -C libs/text-splitters format
files: ^libs/text-splitters/
pass_filenames: false
- id: anthropic
name: format partners/anthropic
language: system
entry: make -C libs/partners/anthropic format
files: ^libs/partners/anthropic/
pass_filenames: false
- id: chroma
name: format partners/chroma
language: system
entry: make -C libs/partners/chroma format
files: ^libs/partners/chroma/
pass_filenames: false
- id: couchbase
name: format partners/couchbase
language: system
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 partners/fireworks
language: system
entry: make -C libs/partners/fireworks format
files: ^libs/partners/fireworks/
pass_filenames: false
- id: groq
name: format partners/groq
language: system
entry: make -C libs/partners/groq format
files: ^libs/partners/groq/
pass_filenames: false
- id: huggingface
name: format partners/huggingface
language: system
entry: make -C libs/partners/huggingface format
files: ^libs/partners/huggingface/
pass_filenames: false
- id: mistralai
name: format partners/mistralai
language: system
entry: make -C libs/partners/mistralai format
files: ^libs/partners/mistralai/
pass_filenames: false
- id: nomic
name: format partners/nomic
language: system
entry: make -C libs/partners/nomic format
files: ^libs/partners/nomic/
pass_filenames: false
- id: ollama
name: format partners/ollama
language: system
entry: make -C libs/partners/ollama format
files: ^libs/partners/ollama/
pass_filenames: false
- id: openai
name: format partners/openai
language: system
entry: make -C libs/partners/openai format
files: ^libs/partners/openai/
pass_filenames: false
- id: prompty
name: format partners/prompty
language: system
entry: make -C libs/partners/prompty format
files: ^libs/partners/prompty/
pass_filenames: false
- id: qdrant
name: format partners/qdrant
language: system
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

View File

@@ -13,7 +13,7 @@ build:
# Build documentation in the docs/ directory with Sphinx
sphinx:
configuration: docs/api_reference/conf.py
configuration: docs/api_reference/conf.py
# If using Sphinx, optionally build your docs in additional formats such as PDF
formats:
@@ -21,5 +21,5 @@ formats:
# Optionally declare the Python requirements required to build your docs
python:
install:
- requirements: docs/api_reference/requirements.txt
install:
- requirements: docs/api_reference/requirements.txt

21
.vscode/extensions.json vendored Normal file
View File

@@ -0,0 +1,21 @@
{
"recommendations": [
"ms-python.python",
"charliermarsh.ruff",
"ms-python.mypy-type-checker",
"ms-toolsai.jupyter",
"ms-toolsai.jupyter-keymap",
"ms-toolsai.jupyter-renderers",
"ms-toolsai.vscode-jupyter-cell-tags",
"ms-toolsai.vscode-jupyter-slideshow",
"yzhang.markdown-all-in-one",
"davidanson.vscode-markdownlint",
"bierner.markdown-mermaid",
"bierner.markdown-preview-github-styles",
"eamodio.gitlens",
"github.vscode-pull-request-github",
"github.vscode-github-actions",
"redhat.vscode-yaml",
"editorconfig.editorconfig",
],
}

80
.vscode/settings.json vendored Normal file
View File

@@ -0,0 +1,80 @@
{
"python.analysis.include": [
"libs/**",
"docs/**",
"cookbook/**"
],
"python.analysis.exclude": [
"**/node_modules",
"**/__pycache__",
"**/.pytest_cache",
"**/.*",
"_dist/**",
"docs/_build/**",
"docs/api_reference/_build/**"
],
"python.analysis.autoImportCompletions": true,
"python.analysis.typeCheckingMode": "basic",
"python.testing.cwd": "${workspaceFolder}",
"python.linting.enabled": true,
"python.linting.ruffEnabled": true,
"[python]": {
"editor.formatOnSave": true,
"editor.codeActionsOnSave": {
"source.organizeImports": "explicit",
"source.fixAll": "explicit"
},
"editor.defaultFormatter": "charliermarsh.ruff"
},
"editor.rulers": [
88
],
"editor.tabSize": 4,
"editor.insertSpaces": true,
"editor.trimAutoWhitespace": true,
"files.trimTrailingWhitespace": true,
"files.insertFinalNewline": true,
"files.exclude": {
"**/__pycache__": true,
"**/.pytest_cache": true,
"**/*.pyc": true,
"**/.mypy_cache": true,
"**/.ruff_cache": true,
"_dist/**": true,
"docs/_build/**": true,
"docs/api_reference/_build/**": true,
"**/node_modules": true,
"**/.git": false
},
"search.exclude": {
"**/__pycache__": true,
"**/*.pyc": true,
"_dist/**": true,
"docs/_build/**": true,
"docs/api_reference/_build/**": true,
"**/node_modules": true,
"**/.git": true,
"uv.lock": true,
"yarn.lock": true
},
"git.autofetch": true,
"git.enableSmartCommit": true,
"jupyter.askForKernelRestart": false,
"jupyter.interactiveWindow.textEditor.executeSelection": true,
"[markdown]": {
"editor.wordWrap": "on",
"editor.quickSuggestions": {
"comments": "off",
"strings": "off",
"other": "off"
}
},
"[yaml]": {
"editor.tabSize": 2,
"editor.insertSpaces": true
},
"[json]": {
"editor.tabSize": 2,
"editor.insertSpaces": true
},
}

View File

@@ -7,5 +7,5 @@ Please see the following guides for migrating LangChain code:
* Migrating from [LangChain 0.0.x Chains](https://python.langchain.com/docs/versions/migrating_chains/)
* Upgrade to [LangGraph Memory](https://python.langchain.com/docs/versions/migrating_memory/)
The [LangChain CLI](https://python.langchain.com/docs/versions/v0_3/#migrate-using-langchain-cli) can help you automatically upgrade your code to use non-deprecated imports.
The [LangChain CLI](https://python.langchain.com/docs/versions/v0_3/#migrate-using-langchain-cli) can help you automatically upgrade your code to use non-deprecated imports.
This will be especially helpful if you're still on either version 0.0.x or 0.1.x of LangChain.

View File

@@ -8,9 +8,6 @@ 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/^/ /'
## all: Default target, shows help.
all: help
## clean: Clean documentation and API documentation artifacts.
clean: docs_clean api_docs_clean
@@ -19,49 +16,79 @@ clean: docs_clean api_docs_clean
######################
## docs_build: Build the documentation.
docs_build:
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:
uv run --no-group test linkchecker _dist/docs/ --ignore-url node_modules
@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:
uv run --no-group test python docs/api_reference/create_api_rst.py
cd docs/api_reference && uv run --no-group test make html
uv run --no-group test python docs/api_reference/scripts/custom_formatter.py docs/api_reference/_build/html/
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:
uv run --no-group test python docs/api_reference/create_api_rst.py $(API_PKG)
cd docs/api_reference && uv run make html
uv run --no-group test python docs/api_reference/scripts/custom_formatter.py docs/api_reference/_build/html/
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:
uv run --no-group test linkchecker docs/api_reference/_build/html/index.html
@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:
uv run --no-group test codespell --toml pyproject.toml
@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:
uv run --no-group test codespell --toml pyproject.toml -w
@echo "✏️ Fixing spelling errors across project..."
uv run --group codespell codespell --toml pyproject.toml -w
@echo "✅ Spelling errors fixed"
######################
# LINTING AND FORMATTING
@@ -69,6 +96,7 @@ spell_fix:
## 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
@@ -76,11 +104,16 @@ lint lint_package lint_tests:
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"

View File

@@ -40,9 +40,10 @@ 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.
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.
@@ -52,9 +53,10 @@ frontier evolves, adapt quickly — LangChains abstractions keep you moving w
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.
applications.
To improve your LLM application development, pair LangChain with:
@@ -73,6 +75,7 @@ teams — and iterate quickly with visual prototyping in
[LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
## Additional resources
- [Tutorials](https://python.langchain.com/docs/tutorials/): Simple walkthroughs with
guided examples on getting started with LangChain.
- [How-to Guides](https://python.langchain.com/docs/how_to/): Quick, actionable code

View File

@@ -11,6 +11,7 @@ When building such applications developers should remember to follow good securi
* [**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.
Risks of not doing so include, but are not limited to:
* Data corruption or loss.
* Unauthorized access to confidential information.
* Compromised performance or availability of critical resources.
@@ -27,10 +28,10 @@ design and secure your applications.
## Reporting OSS Vulnerabilities
LangChain is partnered with [huntr by Protect AI](https://huntr.com/) to provide
a bounty program for our open source projects.
LangChain is partnered with [huntr by Protect AI](https://huntr.com/) to provide
a bounty program for our open source projects.
Please report security vulnerabilities associated with the LangChain
Please report security vulnerabilities associated with the LangChain
open source projects [here](https://huntr.com/bounties/disclose/?target=https%3A%2F%2Fgithub.com%2Flangchain-ai%2Flangchain&validSearch=true).
Before reporting a vulnerability, please review:
@@ -45,39 +46,39 @@ Before reporting a vulnerability, please review:
The following packages and repositories are eligible for bug bounties:
- langchain-core
- langchain (see exceptions)
- langchain-community (see exceptions)
- langgraph
- langserve
* langchain-core
* langchain (see exceptions)
* langchain-community (see exceptions)
* langgraph
* langserve
### Out of Scope Targets
All out of scope targets defined by huntr as well as:
- **langchain-experimental**: This repository is for experimental code and is not
* **langchain-experimental**: This repository is for experimental code and is not
eligible for bug bounties (see [package warning](https://pypi.org/project/langchain-experimental/)), bug reports to it will be marked as interesting or waste of
time and published with no bounty attached.
- **tools**: Tools in either langchain or langchain-community are not eligible for bug
* **tools**: Tools in either langchain or langchain-community are not eligible for bug
bounties. This includes the following directories
- libs/langchain/langchain/tools
- libs/community/langchain_community/tools
- Please review the [Best Practices](#best-practices)
* libs/langchain/langchain/tools
* libs/community/langchain_community/tools
* Please review the [Best Practices](#best-practices)
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 done on a case by
* 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)).
* Any LangSmith related repositories or APIs (see [Reporting LangSmith Vulnerabilities](#reporting-langsmith-vulnerabilities)).
## Reporting LangSmith Vulnerabilities
Please report security vulnerabilities associated with LangSmith by email to `security@langchain.dev`.
- LangSmith site: https://smith.langchain.com
- SDK client: https://github.com/langchain-ai/langsmith-sdk
* LangSmith site: [https://smith.langchain.com](https://smith.langchain.com)
* SDK client: [https://github.com/langchain-ai/langsmith-sdk](https://github.com/langchain-ai/langsmith-sdk)
### Other Security Concerns

View File

@@ -20,11 +20,7 @@
"cell_type": "markdown",
"id": "5939a54c-3198-4ba4-8346-1cc088c473c0",
"metadata": {},
"source": [
"##### You can embed text in the same VectorDB space as images, and retreive text and images as well based on input text or image.\n",
"##### Following link demonstrates that.\n",
"<a> https://python.langchain.com/v0.2/docs/integrations/text_embedding/open_clip/ </a>"
]
"source": "##### You can embed text in the same VectorDB space as images, and retrieve text and images as well based on input text or image.\n##### Following link demonstrates that.\n<a> https://python.langchain.com/v0.2/docs/integrations/text_embedding/open_clip/ </a>"
},
{
"cell_type": "markdown",
@@ -600,4 +596,4 @@
},
"nbformat": 4,
"nbformat_minor": 5
}
}

View File

@@ -552,9 +552,7 @@
"cell_type": "markdown",
"id": "77deb6a0-0950-450a-916a-f2a029676c20",
"metadata": {},
"source": [
"**Appending all retreived documents in a single document**"
]
"source": "**Appending all retrieved documents in a single document**"
},
{
"cell_type": "code",
@@ -758,4 +756,4 @@
},
"nbformat": 4,
"nbformat_minor": 5
}
}

View File

@@ -1,9 +1,9 @@
# 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"
# 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
@@ -18,32 +18,45 @@ 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:
python3 -m venv .venv
$(PYTHON) -m pip install -q --upgrade pip
$(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 $$($(PYTHON) scripts/partner_deps_list.py) --overrides vercel_overrides.txt
@echo "📦 Installing Python dependencies..."
@if [ ! -d .venv ]; then python3 -m venv .venv; fi
@if [ ! -f .venv/deps_installed ]; then \
$(PYTHON) -m pip install -q --upgrade pip --disable-pip-version-check; \
$(PYTHON) -m pip install -q --upgrade uv; \
$(PYTHON) -m uv pip install -q --pre -r vercel_requirements.txt; \
$(PYTHON) -m uv pip install -q --pre $$($(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)
$(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)
curl https://raw.githubusercontent.com/langchain-ai/langserve/main/README.md | sed 's/<=/\&lt;=/g' > $(INTERMEDIATE_DIR)/langserve.md
@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
$(PYTHON) scripts/resolve_local_links.py $(INTERMEDIATE_DIR)/langserve.md https://github.com/langchain-ai/langserve/tree/main/
@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)
@@ -55,15 +68,22 @@ copy-infra:
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)
@@ -71,6 +91,10 @@ generate-references:
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
@@ -84,4 +108,9 @@ vercel-build: install-vercel-deps build generate-references
NODE_OPTIONS="--max-old-space-size=5000" yarn run docusaurus build
start:
cd $(OUTPUT_NEW_DIR) && yarn && yarn start --port=$(PORT)
@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)

View File

@@ -262,6 +262,8 @@ 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

View File

@@ -202,6 +202,12 @@ def _load_package_modules(
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
@@ -495,15 +501,7 @@ def _package_namespace(package_name: str) -> str:
def _package_dir(package_name: str = "langchain") -> Path:
"""Return the path to the directory containing the documentation."""
if package_name in (
"langchain",
"experimental",
"community",
"core",
"cli",
"text-splitters",
"standard-tests",
):
if (ROOT_DIR / "libs" / package_name).exists():
return ROOT_DIR / "libs" / package_name / _package_namespace(package_name)
else:
return (
@@ -592,7 +590,12 @@ For the legacy API reference hosted on ReadTheDocs see [https://api.python.langc
if integrations:
integration_headers = [
" ".join(
custom_names.get(x, x.title().replace("ai", "AI").replace("db", "DB"))
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
@@ -660,18 +663,12 @@ def main(dirs: Optional[list] = None) -> None:
print("Starting to build API reference files.")
if not dirs:
dirs = [
dir_
for dir_ in os.listdir(ROOT_DIR / "libs")
if dir_ not in ("cli", "partners", "packages.yml")
and "pyproject.toml" in os.listdir(ROOT_DIR / "libs" / dir_)
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")
]
dirs += [
dir_
for dir_ in os.listdir(ROOT_DIR / "libs" / "partners")
if os.path.isdir(ROOT_DIR / "libs" / "partners" / dir_)
and "pyproject.toml" in os.listdir(ROOT_DIR / "libs" / "partners" / dir_)
]
for dir_ in dirs:
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.
@@ -682,7 +679,7 @@ def main(dirs: Optional[list] = None) -> None:
print("Building package:", dir_)
_build_rst_file(package_name=dir_)
_build_index(dirs)
_build_index(sorted(dirs))
print("API reference files built.")

View File

@@ -1,4 +1,4 @@
# Contribute Code
# Contribute code
If you would like to add a new feature or update an existing one, please read the resources below before getting started:

View File

@@ -3,7 +3,7 @@
This guide walks through how to run the repository locally and check in your first code.
For a [development container](https://containers.dev/), see the [.devcontainer folder](https://github.com/langchain-ai/langchain/tree/master/.devcontainer).
## Dependency Management: `uv` and other env/dependency managers
## Dependency management: `uv` and other env/dependency managers
This project utilizes [uv](https://docs.astral.sh/uv/) v0.5+ as a dependency manager.
@@ -37,7 +37,7 @@ For this quickstart, start with `langchain`:
cd libs/langchain
```
## Local Development Dependencies
## Local development dependencies
Install development requirements (for running langchain, running examples, linting, formatting, tests, and coverage):
@@ -64,12 +64,6 @@ To run unit tests:
make test
```
To run unit tests in Docker:
```bash
make docker_tests
```
There are also [integration tests and code-coverage](../testing.mdx) available.
### Developing langchain_core
@@ -81,11 +75,11 @@ cd libs/core
make test
```
## Formatting and Linting
## Formatting and linting
Run these locally before submitting a PR; the CI system will check also.
### Code Formatting
### Code formatting
Formatting for this project is done via [ruff](https://docs.astral.sh/ruff/rules/).
@@ -163,7 +157,7 @@ If codespell is incorrectly flagging a word, you can skip spellcheck for that wo
ignore-words-list = 'momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogyny,unsecure'
```
## Working with Optional Dependencies
## Working with optional dependencies
`langchain`, `langchain-community`, and `langchain-experimental` rely on optional dependencies to keep these packages lightweight.

View File

@@ -1,4 +1,4 @@
# Contribute Documentation
# Contribute documentation
Documentation is a vital part of LangChain. We welcome both new documentation for new features and
community improvements to our current documentation. Please read the resources below before getting started:

View File

@@ -12,12 +12,11 @@ It covers a wide array of topics, including tutorials, use cases, integrations,
and more, offering extensive guidance on building with LangChain.
The content for this documentation lives in the `/docs` directory of the monorepo.
2. In-code Documentation: This is documentation of the codebase itself, which is also
used to generate the externally facing [API Reference](https://python.langchain.com/api_reference/langchain/index.html).
used to generate the externally facing [API Reference](https://python.langchain.com/api_reference/).
The content for the API reference is autogenerated by scanning the docstrings in the codebase. For this reason we ask that
developers document their code well.
The `API Reference` is largely autogenerated by [sphinx](https://www.sphinx-doc.org/en/master/)
from the code and is hosted by [Read the Docs](https://readthedocs.org/).
The API Reference is largely autogenerated by [sphinx](https://www.sphinx-doc.org/en/master/) from the code.
We appreciate all contributions to the documentation, whether it be fixing a typo,
adding a new tutorial or example and whether it be in the main documentation or the API Reference.
@@ -25,7 +24,7 @@ adding a new tutorial or example and whether it be in the main documentation or
Similar to linting, we recognize documentation can be annoying. If you do not want
to do it, please contact a project maintainer, and they can help you with it. We do not want this to be a blocker for good code getting contributed.
## 📜 Main Documentation
## 📜 Main documentation
The content for the main documentation is located in the `/docs` directory of the monorepo.
@@ -42,7 +41,7 @@ After modifying the documentation:
3. Make a pull request with the changes.
4. You can preview and verify that the changes are what you wanted by clicking the `View deployment` or `Visit Preview` buttons on the pull request `Conversation` page. This will take you to a preview of the documentation changes.
## ⚒️ Linting and Building Documentation Locally
## ⚒️ Linting and building documentation locally
After writing up the documentation, you may want to lint and build the documentation
locally to ensure that it looks good and is free of errors.
@@ -57,20 +56,44 @@ The code that builds the documentation is located in the `/docs` directory of th
In the following commands, the prefix `api_` indicates that those are operations for the API Reference.
Before building the documentation, it is always a good idea to clean the build directory:
```bash
make docs_clean
make api_docs_clean
```
Next, you can build the documentation as outlined below:
You can build the documentation as outlined below:
```bash
make docs_build
make api_docs_build
```
### Viewing documentation locally
After building the main documentation, you can view it locally by starting a development server:
```bash
# For main documentation (after running `make docs_build`)
cd docs && make start
```
This will start a development server where you can view the documentation in your browser. The exact url will be shown to you during the start process. The server will automatically reload when you make changes to the documentation files under the `build/` directory (e.g. for temporary tests - changes you wish to persist should be put under `docs/docs/`).
:::tip
You can specify a different port by setting the `PORT` environment variable:
```bash
cd docs && PORT=3000 make start
```
:::
The API Reference documentation is built as static HTML files and will be automatically opened directly in your browser.
You can also view the API Reference for a specific package by specifying the package name and installing the package if necessary dependencies:
```bash
# Opens the API Reference for the `ollama` package in your default browser
uv pip install -e libs/partners/ollama
make api_docs_quick_preview API_PKG=ollama
```
:::tip
The `make api_docs_build` command takes a long time. If you're making cosmetic changes to the API docs and want to see how they look, use:
@@ -79,18 +102,28 @@ The `make api_docs_build` command takes a long time. If you're making cosmetic c
make api_docs_quick_preview
```
which will just build a small subset of the API reference.
which will just build a small subset of the API reference (the `text-splitters` package).
:::
Finally, run the link checker to ensure all links are valid:
Finally, run the link checker from the project root to ensure all links are valid:
```bash
make docs_linkcheck
make api_docs_linkcheck
```
### Linting and Formatting
To clean up the documentation build artifacts, you can run:
```bash
make clean
# Or to clean specific documentation artifacts
make docs_clean
make api_docs_clean
```
### Formatting and linting
The Main Documentation is linted from the **monorepo root**. To lint the main documentation, run the following from there:
@@ -104,9 +137,9 @@ If you have formatting-related errors, you can fix them automatically with:
make format
```
## ⌨️ In-code Documentation
## ⌨️ In-code documentation
The in-code documentation is largely autogenerated by [sphinx](https://www.sphinx-doc.org/en/master/) from the code and is hosted by [Read the Docs](https://readthedocs.org/).
The in-code documentation is largely autogenerated by [sphinx](https://www.sphinx-doc.org/en/master/) from the code following [reStructuredText](https://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html).
For the API reference to be useful, the codebase must be well-documented. This means that all functions, classes, and methods should have a docstring that explains what they do, what the arguments are, and what the return value is. This is a good practice in general, but it is especially important for LangChain because the API reference is the primary resource for developers to understand how to use the codebase.
@@ -141,16 +174,16 @@ def my_function(arg1: int, arg2: str) -> float:
return 3.14
```
### Linting and Formatting
### Formatting and linting
The in-code documentation is linted from the directories belonging to the packages
being documented.
For example, if you're working on the `langchain-community` package, you would change
the working directory to the `langchain-community` directory:
For example, if you're working on the `langchain-ollama` package, you would change
the working directory to the the package directory:
```bash
cd [root]/libs/langchain-community
cd [root]/libs/partners/ollama
```
Then you can run the following commands to lint and format the in-code documentation:
@@ -160,9 +193,9 @@ make format
make lint
```
## Verify Documentation Changes
## Verify documentation changes
After pushing documentation changes to the repository, you can preview and verify that the changes are
what you wanted by clicking the `View deployment` or `Visit Preview` buttons on the pull request `Conversation` page.
This will take you to a preview of the documentation changes.
This preview is created by [Vercel](https://vercel.com/docs/getting-started-with-vercel).
This preview is created by [Vercel](https://vercel.com/docs/getting-started-with-vercel).

View File

@@ -2,7 +2,7 @@
sidebar_class_name: "hidden"
---
# Documentation Style Guide
# Documentation style guide
As LangChain continues to grow, the amount of documentation required to cover the various concepts and integrations continues to grow too.
This page provides guidelines for anyone writing documentation for LangChain and outlines some of our philosophies around
@@ -158,3 +158,5 @@ Be concise, including in code samples.
- Use bullet points and numbered lists to break down information into easily digestible chunks
- Use tables (especially for **Reference** sections) and diagrams often to present information visually
- Include the table of contents for longer documentation pages to help readers navigate the content, but hide it for shorter pages
Next, see the [documentation setup guide](setup.mdx) to get started with writing documentation for LangChain.

View File

@@ -1,4 +1,4 @@
# How-to Guides
# How-to guides
- [**Documentation**](documentation/index.mdx): Help improve our docs, including this one!
- [**Code**](code/index.mdx): Help us write code, fix bugs, or improve our infrastructure.

View File

@@ -3,7 +3,7 @@ pagination_prev: null
pagination_next: contributing/how_to/integrations/package
---
# Contribute Integrations
# Contribute integrations
Integrations are a core component of LangChain.
LangChain provides standard interfaces for several different components (language models, vector stores, etc) that are crucial when building LLM applications.
@@ -16,7 +16,7 @@ LangChain provides standard interfaces for several different components (languag
- **Best Practices:** Through their standard interface, LangChain components encourage and facilitate best practices (streaming, async, etc)
## Components to Integrate
## Components to integrate
:::info
@@ -71,7 +71,7 @@ In order to contribute an integration, you should follow these steps:
5. [Optional] Open and merge a PR to add documentation for your integration to the official LangChain docs.
6. [Optional] Engage with the LangChain team for joint co-marketing ([see below](#co-marketing)).
## Co-Marketing
## Co-marketing
With over 20 million monthly downloads, LangChain has a large audience of developers
building LLM applications. Beyond just listing integrations, we aim to highlight
@@ -87,5 +87,5 @@ Here are some heuristics for types of content we are excited to promote:
- **End-to-end applications:** End-to-end applications are great resources for developers looking to build. We prefer to highlight applications that are more complex/agentic in nature, and that use [LangGraph](https://github.com/langchain-ai/langgraph) as the orchestration framework. We get particularly excited about anything involving long-term memory, human-in-the-loop interaction patterns, or multi-agent architectures.
- **Research:** We love highlighting novel research! Whether it is research built on top of LangChain or that integrates with it.
## Further Reading
## Further reading
To get started, let's learn [how to implement an integration package](/docs/contributing/how_to/integrations/package/) for LangChain.

View File

@@ -358,7 +358,7 @@ a schema for the LLM to fill out when calling the tool. Similar to the `name` an
description (part of `Field(..., description="description")`) are passed to the LLM,
and the values in these fields should be concise and LLM-usable.
### Run Methods
### Run methods
`_run` is the main method that should be implemented in the subclass. This method
takes in the arguments from `args_schema` and runs the tool, returning a string
@@ -469,6 +469,6 @@ import RetrieverSource from '/src/theme/integration_template/integration_templat
---
## Next Steps
## Next steps
Now that you've implemented your package, you can move on to [testing your integration](../standard_tests) for your integration and successfully run them.

View File

@@ -10,7 +10,7 @@ Unit tests run on every pull request, so they should be fast and reliable.
Integration tests run once a day, and they require more setup, so they should be reserved for confirming interface points with external services.
## Unit Tests
## Unit tests
Unit tests cover modular logic that does not require calls to outside APIs.
If you add new logic, please add a unit test.
@@ -27,19 +27,13 @@ To run unit tests:
make test
```
To run unit tests in Docker:
```bash
make docker_tests
```
To run a specific test:
```bash
TEST_FILE=tests/unit_tests/test_imports.py make test
```
## Integration Tests
## Integration tests
Integration tests cover logic that requires making calls to outside APIs (often integration with other services).
If you add support for a new external API, please add a new integration test.

View File

@@ -12,7 +12,7 @@ More coming soon! We are working on tutorials to help you make your first contri
- [**Make your first docs PR**](tutorials/docs.mdx)
## How-to Guides
## How-to guides
- [**Documentation**](how_to/documentation/index.mdx): Help improve our docs, including this one!
- [**Code**](how_to/code/index.mdx): Help us write code, fix bugs, or improve our infrastructure.

View File

@@ -50,7 +50,7 @@ There are other files in the root directory level, but their presence should be
## Documentation
The `/docs` directory contains the content for the documentation that is shown
at https://python.langchain.com/ and the associated API Reference https://python.langchain.com/api_reference/langchain/index.html.
at [python.langchain.com](https://python.langchain.com/) and the associated [API Reference](https://python.langchain.com/api_reference/).
See the [documentation](../how_to/documentation/index.mdx) guidelines to learn how to contribute to the documentation.

View File

@@ -8,7 +8,7 @@ This tutorial will guide you through making a simple documentation edit, like co
---
## Editing a Documentation Page on GitHub
## Editing a documentation page on GitHub
Sometimes you want to make a small change, like fixing a typo, and the easiest way to do this is to use GitHub's editor directly.
@@ -42,10 +42,14 @@ Sometimes you want to make a small change, like fixing a typo, and the easiest w
- Give your PR a title like `docs: Fix typo in X section`.
- Follow the checklist in the PR description template.
## Getting a Review
## Getting a review
Once you've submitted the pull request, it will be reviewed by the maintainers. You may receive feedback or requests for changes. Keep an eye on the PR to address any comments.
Docs PRs are typically reviewed within a few days, but it may take longer depending on the complexity of the change and the availability of maintainers.
For more information on reviews, see the [Review Process](../reference/review_process.mdx).
## More information
See our [how-to guides](../how_to/documentation/index.mdx) for more information on contributing to documentation:

View File

@@ -51,7 +51,31 @@
"\n",
"### Credentials\n",
"\n",
"Head to the [AWS docs](https://docs.aws.amazon.com/bedrock/latest/userguide/setting-up.html) to sign up to AWS and setup your credentials. You'll also need to turn on model access for your account, which you can do by following [these instructions](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access.html)."
"Head to the [AWS docs](https://docs.aws.amazon.com/bedrock/latest/userguide/setting-up.html) to sign up to AWS and setup your credentials.\n",
"\n",
"Alternatively, `ChatBedrockConverse` will read from the following environment variables by default:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0f65be92",
"metadata": {},
"outputs": [],
"source": [
"# os.environ[\"AWS_ACCESS_KEY_ID\"] = \"...\"\n",
"# os.environ[\"AWS_SECRET_ACCESS_KEY\"] = \"...\"\n",
"\n",
"# Not required unless using temporary credentials.\n",
"# os.environ[\"AWS_SESSION_TOKEN\"] = \"...\""
]
},
{
"cell_type": "markdown",
"id": "3baad5a9",
"metadata": {},
"source": [
"You'll also need to turn on model access for your account, which you can do by following [these instructions](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access.html)."
]
},
{
@@ -114,6 +138,10 @@
"\n",
"llm = ChatBedrockConverse(\n",
" model_id=\"anthropic.claude-3-5-sonnet-20240620-v1:0\",\n",
" # region_name=...,\n",
" # aws_access_key_id=...,\n",
" # aws_secret_access_key=...,\n",
" # aws_session_token=...,\n",
" # temperature=...,\n",
" # max_tokens=...,\n",
" # other params...\n",

View File

@@ -92,7 +92,7 @@ the support of DB2 vector store and vector search.
See detailed usage examples in the guide [here](/docs/integrations/vectorstores/db2).
Installation: This is a seperate package for vector store feature only and can be run
Installation: This is a separate package for vector store feature only and can be run
without the `langchain-ibm` package.
```bash
pip install -U langchain-db2

View File

@@ -20,7 +20,7 @@ pip install langchain-predictionguard
|---|---|---|---------------------------------------------------------|-------------------------------------------------------------------------------|
|Chat|Build Chat Bots|[Chat](https://docs.predictionguard.com/api-reference/api-reference/chat-completions)| `from langchain_predictionguard import ChatPredictionGuard` | [ChatPredictionGuard.ipynb](/docs/integrations/chat/predictionguard) |
|Completions|Generate Text|[Completions](https://docs.predictionguard.com/api-reference/api-reference/completions)| `from langchain_predictionguard import PredictionGuard` | [PredictionGuard.ipynb](/docs/integrations/llms/predictionguard) |
|Text Embedding|Embed String to Vectores|[Embeddings](https://docs.predictionguard.com/api-reference/api-reference/embeddings)| `from langchain_predictionguard import PredictionGuardEmbeddings` | [PredictionGuardEmbeddings.ipynb](/docs/integrations/text_embedding/predictionguard) |
|Text Embedding|Embed String to Vectors|[Embeddings](https://docs.predictionguard.com/api-reference/api-reference/embeddings)| `from langchain_predictionguard import PredictionGuardEmbeddings` | [PredictionGuardEmbeddings.ipynb](/docs/integrations/text_embedding/predictionguard) |
## Getting Started

View File

@@ -1,7 +1,6 @@
# PremAI
[PremAI](https://premai.io/) is an all-in-one platform that simplifies the creation of robust, production-ready applications powered by Generative AI. By streamlining the development process, PremAI allows you to concentrate on enhancing user experience and driving overall growth for your application. You can quickly start using our platform [here](https://docs.premai.io/quick-start).
[PremAI](https://premai.io/) is an all-in-one platform that simplifies the creation of robust, production-ready applications powered by Generative AI. By streamlining the development process, PremAI allows you to concentrate on enhancing user experience and driving overall growth for your application. You can quickly start using [our platform](https://docs.premai.io/quick-start).
## ChatPremAI
@@ -26,10 +25,9 @@ from langchain_community.chat_models import ChatPremAI
Once we imported our required modules, let's setup our client. For now let's assume that our `project_id` is `8`. But make sure you use your project-id, otherwise it will throw error.
To use langchain with prem, you do not need to pass any model name or set any parameters with our chat-client. By default it will use the model name and parameters used in the [LaunchPad](https://docs.premai.io/get-started/launchpad).
> Note: If you change the `model` or any other parameters like `temperature` or `max_tokens` while setting the client, it will override existing default configurations, that was used in LaunchPad.
To use langchain with prem, you do not need to pass any model name or set any parameters with our chat-client. By default it will use the model name and parameters used in the [LaunchPad](https://docs.premai.io/get-started/launchpad).
> Note: If you change the `model` or any other parameters like `temperature` or `max_tokens` while setting the client, it will override existing default configurations, that was used in LaunchPad.
```python
import os
@@ -43,9 +41,9 @@ chat = ChatPremAI(project_id=1234, model_name="gpt-4o")
### Chat Completions
`ChatPremAI` supports two methods: `invoke` (which is the same as `generate`) and `stream`.
`ChatPremAI` supports two methods: `invoke` (which is the same as `generate`) and `stream`.
The first one will give us a static result. Whereas the second one will stream tokens one by one. Here's how you can generate chat-like completions.
The first one will give us a static result. Whereas the second one will stream tokens one by one. Here's how you can generate chat-like completions.
```python
human_message = HumanMessage(content="Who are you?")
@@ -72,18 +70,17 @@ chat.invoke(
)
```
> If you are going to place system prompt here, then it will override your system prompt that was fixed while deploying the application from the platform.
> If you are going to place system prompt here, then it will override your system prompt that was fixed while deploying the application from the platform.
> You can find all the optional parameters [here](https://docs.premai.io/get-started/sdk#optional-parameters). Any parameters other than [these supported parameters](https://docs.premai.io/get-started/sdk#optional-parameters) will be automatically removed before calling the model.
### Native RAG Support with Prem Repositories
Prem Repositories which allows users to upload documents (.txt, .pdf etc) and connect those repositories to the LLMs. You can think Prem repositories as native RAG, where each repository can be considered as a vector database. You can connect multiple repositories. You can learn more about repositories [here](https://docs.premai.io/get-started/repositories).
Repositories are also supported in langchain premai. Here is how you can do it.
Repositories are also supported in langchain premai. Here is how you can do it.
```python
```python
query = "Which models are used for dense retrieval"
repository_ids = [1985,]
@@ -94,13 +91,13 @@ repositories = dict(
)
```
First we start by defining our repository with some repository ids. Make sure that the ids are valid repository ids. You can learn more about how to get the repository id [here](https://docs.premai.io/get-started/repositories).
First we start by defining our repository with some repository ids. Make sure that the ids are valid repository ids. You can learn more about how to get the repository id [here](https://docs.premai.io/get-started/repositories).
> Please note: Similar like `model_name` when you invoke the argument `repositories`, then you are potentially overriding the repositories connected in the launchpad.
> Please note: Similar like `model_name` when you invoke the argument `repositories`, then you are potentially overriding the repositories connected in the launchpad.
Now, we connect the repository with our chat object to invoke RAG based generations.
Now, we connect the repository with our chat object to invoke RAG based generations.
```python
```python
import json
response = chat.invoke(query, max_tokens=100, repositories=repositories)
@@ -109,7 +106,7 @@ print(response.content)
print(json.dumps(response.response_metadata, indent=4))
```
This is how an output looks like.
This is how an output looks like.
```bash
Dense retrieval models typically include:
@@ -134,11 +131,11 @@ Dense retrieval models typically include:
So, this also means that you do not need to make your own RAG pipeline when using the Prem Platform. Prem uses it's own RAG technology to deliver best in class performance for Retrieval Augmented Generations.
> Ideally, you do not need to connect Repository IDs here to get Retrieval Augmented Generations. You can still get the same result if you have connected the repositories in prem platform.
> Ideally, you do not need to connect Repository IDs here to get Retrieval Augmented Generations. You can still get the same result if you have connected the repositories in prem platform.
### Streaming
In this section, let's see how we can stream tokens using langchain and PremAI. Here's how you do it.
In this section, let's see how we can stream tokens using langchain and PremAI. Here's how you do it.
```python
import sys
@@ -163,16 +160,15 @@ for chunk in chat.stream(
This will stream tokens one after the other.
> Please note: As of now, RAG with streaming is not supported. However we still support it with our API. You can learn more about that [here](https://docs.premai.io/get-started/chat-completion-sse).
> Please note: As of now, RAG with streaming is not supported. However we still support it with our API. You can learn more about that [here](https://docs.premai.io/get-started/chat-completion-sse).
## Prem Templates
Writing Prompt Templates can be super messy. Prompt templates are long, hard to manage, and must be continuously tweaked to improve and keep the same throughout the application.
Writing Prompt Templates can be super messy. Prompt templates are long, hard to manage, and must be continuously tweaked to improve and keep the same throughout the application.
With **Prem**, writing and managing prompts can be super easy. The **_Templates_** tab inside the [launchpad](https://docs.premai.io/get-started/launchpad) helps you write as many prompts you need and use it inside the SDK to make your application running using those prompts. You can read more about Prompt Templates [here](https://docs.premai.io/get-started/prem-templates).
With **Prem**, writing and managing prompts can be super easy. The **_Templates_** tab inside the [launchpad](https://docs.premai.io/get-started/launchpad) helps you write as many prompts you need and use it inside the SDK to make your application running using those prompts. You can read more about Prompt Templates [here](https://docs.premai.io/get-started/prem-templates).
To use Prem Templates natively with LangChain, you need to pass an id the `HumanMessage`. This id should be the name the variable of your prompt template. the `content` in `HumanMessage` should be the value of that variable.
To use Prem Templates natively with LangChain, you need to pass an id the `HumanMessage`. This id should be the name the variable of your prompt template. the `content` in `HumanMessage` should be the value of that variable.
let's say for example, if your prompt template was this:
@@ -198,7 +194,7 @@ template_id = "78069ce8-xxxxx-xxxxx-xxxx-xxx"
response = chat.invoke([human_message], template_id=template_id)
```
Prem Templates are also available for Streaming too.
Prem Templates are also available for Streaming too.
## Prem Embeddings
@@ -215,7 +211,7 @@ if os.environ.get("PREMAI_API_KEY") is None:
```
We support lots of state of the art embedding models. You can view our list of supported LLMs and embedding models [here](https://docs.premai.io/get-started/supported-models). For now let's go for `text-embedding-3-large` model for this example. .
We support lots of state of the art embedding models. You can view our list of supported LLMs and embedding models [here](https://docs.premai.io/get-started/supported-models). For now let's go for `text-embedding-3-large` model for this example. .
```python
@@ -231,7 +227,7 @@ print(query_result[:5])
```
:::note
Setting `model_name` argument in mandatory for PremAIEmbeddings unlike chat.
Setting `model_name` argument in mandatory for PremAIEmbeddings unlike chat.
:::
Finally, let's embed some sample document
@@ -254,11 +250,13 @@ print(doc_result[0][:5])
```python
print(f"Dimension of embeddings: {len(query_result)}")
```
Dimension of embeddings: 3072
```python
doc_result[:5]
```
>Result:
>
>[-0.02129288576543331,
@@ -269,20 +267,20 @@ doc_result[:5]
## Tool/Function Calling
LangChain PremAI supports tool/function calling. Tool/function calling allows a model to respond to a given prompt by generating output that matches a user-defined schema.
LangChain PremAI supports tool/function calling. Tool/function calling allows a model to respond to a given prompt by generating output that matches a user-defined schema.
- You can learn all about tool calling in details [in our documentation here](https://docs.premai.io/get-started/function-calling).
- You can learn more about langchain tool calling in [this part of the docs](https://python.langchain.com/v0.1/docs/modules/model_io/chat/function_calling).
**NOTE:**
> The current version of LangChain ChatPremAI do not support function/tool calling with streaming support. Streaming support along with function calling will come soon.
> The current version of LangChain ChatPremAI do not support function/tool calling with streaming support. Streaming support along with function calling will come soon.
### Passing tools to model
In order to pass tools and let the LLM choose the tool it needs to call, we need to pass a tool schema. A tool schema is the function definition along with proper docstring on what does the function do, what each argument of the function is etc. Below are some simple arithmetic functions with their schema.
In order to pass tools and let the LLM choose the tool it needs to call, we need to pass a tool schema. A tool schema is the function definition along with proper docstring on what does the function do, what each argument of the function is etc. Below are some simple arithmetic functions with their schema.
**NOTE:**
**NOTE:**
> When defining function/tool schema, do not forget to add information around the function arguments, otherwise it would throw error.
```python
@@ -320,27 +318,28 @@ def multiply(a: int, b: int) -> int:
### Binding tool schemas with our LLM
We will now use the `bind_tools` method to convert our above functions to a "tool" and binding it with the model. This means we are going to pass these tool information everytime we invoke the model.
We will now use the `bind_tools` method to convert our above functions to a "tool" and binding it with the model. This means we are going to pass these tool information every time we invoke the model.
```python
tools = [add, multiply]
llm_with_tools = chat.bind_tools(tools)
```
After this, we get the response from the model which is now binded with the tools.
After this, we get the response from the model which is now binded with the tools.
```python
```python
query = "What is 3 * 12? Also, what is 11 + 49?"
messages = [HumanMessage(query)]
ai_msg = llm_with_tools.invoke(messages)
```
As we can see, when our chat model is binded with tools, then based on the given prompt, it calls the correct set of the tools and sequentially.
As we can see, when our chat model is binded with tools, then based on the given prompt, it calls the correct set of the tools and sequentially.
```python
```python
ai_msg.tool_calls
```
**Output**
```python
@@ -352,15 +351,15 @@ ai_msg.tool_calls
'id': 'call_MPKYGLHbf39csJIyb5BZ9xIk'}]
```
We append this message shown above to the LLM which acts as a context and makes the LLM aware that what all functions it has called.
We append this message shown above to the LLM which acts as a context and makes the LLM aware that what all functions it has called.
```python
```python
messages.append(ai_msg)
```
Since tool calling happens into two phases, where:
1. in our first call, we gathered all the tools that the LLM decided to tool, so that it can get the result as an added context to give more accurate and hallucination free result.
1. in our first call, we gathered all the tools that the LLM decided to tool, so that it can get the result as an added context to give more accurate and hallucination free result.
2. in our second call, we will parse those set of tools decided by LLM and run them (in our case it will be the functions we defined, with the LLM's extracted arguments) and pass this result to the LLM
@@ -373,12 +372,13 @@ for tool_call in ai_msg.tool_calls:
messages.append(ToolMessage(tool_output, tool_call_id=tool_call["id"]))
```
Finally, we call the LLM (binded with the tools) with the function response added in it's context.
Finally, we call the LLM (binded with the tools) with the function response added in it's context.
```python
response = llm_with_tools.invoke(messages)
print(response.content)
```
**Output**
```txt
@@ -425,4 +425,4 @@ chain.invoke(query)
[multiply(a=3, b=12), add(a=11, b=49)]
```
Now, as done above, we parse this and run this functions and call the LLM once again to get the result.
Now, as done above, we parse this and run this functions and call the LLM once again to get the result.

View File

@@ -265,13 +265,7 @@
"cell_type": "markdown",
"id": "08437fa2",
"metadata": {},
"source": [
"## Instantiation\n",
"\n",
"### Vector search\n",
"\n",
"Dense vector retrival using fake embeddings in this example."
]
"source": "## Instantiation\n\n### Vector search\n\nDense vector retrieval using fake embeddings in this example."
},
{
"cell_type": "code",
@@ -713,4 +707,4 @@
},
"nbformat": 4,
"nbformat_minor": 5
}
}

View File

@@ -638,7 +638,7 @@
"\n",
"For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n",
"\n",
"- [Tutorials](/docs/tutorials/)\n",
"- [Tutorials](/docs/tutorials/rag)\n",
"- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n",
"- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval)"
]

File diff suppressed because one or more lines are too long

View File

@@ -447,11 +447,7 @@
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"We'll define a helper funciton to create a uuid for a document and associated vector embedding based on its timestamp. We'll use this function to create a uuid for each git log entry.\n",
"\n",
"Important note: If you are working with documents and want the current date and time associated with vector for time-based search, you can skip this step. A uuid will be automatically generated when the documents are ingested by default."
]
"source": "We'll define a helper function to create a uuid for a document and associated vector embedding based on its timestamp. We'll use this function to create a uuid for each git log entry.\n\nImportant note: If you are working with documents and want the current date and time associated with vector for time-based search, you can skip this step. A uuid will be automatically generated when the documents are ingested by default."
},
{
"cell_type": "code",
@@ -1729,4 +1725,4 @@
},
"nbformat": 4,
"nbformat_minor": 4
}
}

View File

@@ -1,9 +1,6 @@
import sys
from pathlib import Path
from langchain_community import document_loaders
from langchain_core.document_loaders.base import BaseLoader
KV_STORE_TEMPLATE = """\
---
sidebar_class_name: hidden

View File

@@ -175,8 +175,23 @@ def _modify_frontmatter(
def _convert_notebook(
notebook_path: Path, output_path: Path, intermediate_docs_dir: Path
) -> Path:
with open(notebook_path) as f:
nb = nbformat.read(f, as_version=4)
import json
import uuid
with open(notebook_path, "r", encoding="utf-8") as f:
nb_json = json.load(f)
# Fix missing and duplicate cell IDs before nbformat validation
seen_ids = set()
for cell in nb_json.get("cells", []):
if "id" not in cell or not cell.get("id") or cell.get("id") in seen_ids:
cell["id"] = str(uuid.uuid4())[:8]
seen_ids.add(cell["id"])
nb = nbformat.reads(json.dumps(nb_json), as_version=4)
# Upgrade notebook format
nb = nbformat.v4.upgrade(nb)
body, resources = exporter.from_notebook_node(nb)

View File

@@ -10,6 +10,7 @@ from langchain_couchbase import CouchbaseSearchVectorStore
from langchain_milvus import Milvus
from langchain_mongodb import MongoDBAtlasVectorSearch
from langchain_pinecone import PineconeVectorStore
from langchain_postgres import PGVectorStore
from langchain_qdrant import QdrantVectorStore
vectorstore_list = [
@@ -22,6 +23,7 @@ vectorstore_list = [
]
from_partners = [
("PGVectorStore", PGVectorStore),
("Chroma", Chroma),
("AstraDBVectorStore", AstraDBVectorStore),
("QdrantVectorStore", QdrantVectorStore),
@@ -52,6 +54,17 @@ The table below lists the features for some of our most popular vector stores.
def get_vectorstore_table():
vectorstore_feat_table = {
"PGVectorStore": {
"Delete by ID": True,
"Filtering": True,
"similarity_search_by_vector": True,
"similarity_search_with_score": True,
"asearch": True,
"Passes Standard Tests": True,
"Multi Tenancy": False,
"Local/Cloud": "Local",
"IDs in add Documents": True,
},
"FAISS": {
"Delete by ID": True,
"Filtering": True,

View File

@@ -315,8 +315,8 @@ module.exports = {
},
],
link: {
type: "doc",
id: "integrations/stores/index",
type: "generated-index",
slug: "integrations/stores",
},
},
{

View File

@@ -1040,7 +1040,7 @@ const FEATURE_TABLES = {
searchWithScore: true,
async: true,
passesStandardTests: true,
multiTenancy: false,
multiTenancy: true,
local: true,
idsInAddDocuments: true,
},
@@ -1174,6 +1174,19 @@ const FEATURE_TABLES = {
local: true,
idsInAddDocuments: true,
},
{
name: "PGVectorStore",
link: "pgvectorstore",
deleteById: true,
filtering: true,
searchByVector: true,
searchWithScore: true,
async: true,
passesStandardTests: true,
multiTenancy: false,
local: true,
idsInAddDocuments: true,
},
{
name: "PineconeVectorStore",
link: "pinecone",

View File

@@ -60,6 +60,13 @@ export default function VectorStoreTabs(props) {
packageName: "langchain-postgres",
default: false,
},
{
value: "PGVectorStore",
label: "PGVectorStore",
text: `from langchain_postgres import PGEngine, PGVectorStore\n${useFakeEmbeddings ? fakeEmbeddingsString : ""}\n$engine = PGEngine.from_connection_string(\n url="postgresql+psycopg://..."\n)\n\n${vectorStoreVarName} = PGVectorStore.create_sync(\n engine=pg_engine,\n table_name='test_table',\n embedding_service=embedding\n)`,
packageName: "langchain-postgres",
default: false,
},
{
value: "Pinecone",
label: "Pinecone",

View File

@@ -1,6 +1,13 @@
httpx
grpcio
aiohttp<3.11
protobuf<3.21
protobuf<5.0
tenacity
urllib3
pypdf
# Fix numpy conflicts between langchain-astradb and langchain-chroma
numpy>=1.26.0,<2.0.0
# Fix simsimd build error in langchain-weaviate
simsimd>=5.0.0
# Fix sentencepiece build error - use newer version that supports modern CMake
sentencepiece>=0.2.1

View File

@@ -67,12 +67,11 @@ def serve(
] = None,
) -> None:
"""Start the LangServe app, whether it's a template or an app."""
# see if is a template
try:
project_dir = get_package_root()
pyproject = project_dir / "pyproject.toml"
get_langserve_export(pyproject)
except KeyError:
except (KeyError, FileNotFoundError):
# not a template
app_namespace.serve(port=port, host=host)
else:

View File

@@ -1,4 +1,4 @@
.PHONY: all format lint test tests integration_tests docker_tests help extended_tests
.PHONY: all format lint test tests integration_tests help extended_tests
# Default target executed when no arguments are given to make.
all: help

View File

@@ -61,6 +61,7 @@ class __ModuleName__Loader(BaseLoader):
.. code-block:: python
TODO: Example output
""" # noqa: E501
# TODO: This method must be implemented to load documents.

View File

@@ -61,6 +61,7 @@ class __ModuleName__Tool(BaseTool): # type: ignore[override]
.. code-block:: python
# TODO: output of invocation
""" # noqa: E501
# TODO: Set tool name and description

View File

@@ -56,7 +56,6 @@ select = [
"C4", # flake8-comprehensions
"COM", # flake8-commas
"D", # pydocstyle
"DOC", # pydoclint
"E", # pycodestyle error
"EM", # flake8-errmsg
"F", # pyflakes

1420
libs/cli/uv.lock generated

File diff suppressed because it is too large Load Diff

View File

@@ -1,4 +1,4 @@
.PHONY: all format lint test tests test_watch integration_tests docker_tests help extended_tests
.PHONY: all format lint test tests test_watch integration_tests help extended_tests
# Default target executed when no arguments are given to make.
all: help

View File

@@ -70,6 +70,7 @@ def beta(
@beta
def the_function_to_annotate():
pass
"""
def beta(

View File

@@ -136,6 +136,7 @@ def deprecated(
@deprecated('1.4.0')
def the_function_to_deprecate():
pass
"""
_validate_deprecation_params(
removal, alternative, alternative_import, pending=pending
@@ -549,6 +550,7 @@ def rename_parameter(
@_api.rename_parameter("3.1", "bad_name", "good_name")
def func(good_name): ...
"""
def decorator(f: Callable[_P, _R]) -> Callable[_P, _R]:

View File

@@ -363,6 +363,7 @@ class Context:
print(output["result"]) # Output: "hello"
print(output["context"]) # Output: "What's your name?"
print(output["input"]) # Output: "What's your name?
"""
@staticmethod

View File

@@ -53,6 +53,7 @@ class FileCallbackHandler(BaseCallbackHandler):
When not used as a context manager, a deprecation warning will be issued
on first use. The file will be opened immediately in ``__init__`` and closed
in ``__del__`` or when ``close()`` is called explicitly.
"""
def __init__(

View File

@@ -105,6 +105,7 @@ def trace_as_chain_group(
# Use the callback manager for the chain group
res = llm.invoke(llm_input, {"callbacks": manager})
manager.on_chain_end({"output": res})
""" # noqa: E501
from langchain_core.tracers.context import _get_trace_callbacks
@@ -186,6 +187,7 @@ async def atrace_as_chain_group(
# Use the async callback manager for the chain group
res = await llm.ainvoke(llm_input, {"callbacks": manager})
await manager.on_chain_end({"output": res})
""" # noqa: E501
from langchain_core.tracers.context import _get_trace_callbacks
@@ -2575,6 +2577,7 @@ async def adispatch_custom_event(
behalf.
.. versionadded:: 0.2.15
"""
from langchain_core.runnables.config import (
ensure_config,
@@ -2645,6 +2648,7 @@ def dispatch_custom_event(
foo_.invoke({"a": "1"}, {"callbacks": [CustomCallbackManager()]})
.. versionadded:: 0.2.15
"""
from langchain_core.runnables.config import (
ensure_config,

View File

@@ -44,6 +44,7 @@ class UsageMetadataCallbackHandler(BaseCallbackHandler):
'input_token_details': {'cache_read': 0, 'cache_creation': 0}}}
.. versionadded:: 0.3.49
"""
def __init__(self) -> None:
@@ -98,7 +99,7 @@ def get_usage_metadata_callback(
Args:
name (str): The name of the context variable. Defaults to
``"usage_metadata_callback"``.
``'usage_metadata_callback'``.
Example:
.. code-block:: python
@@ -127,6 +128,7 @@ def get_usage_metadata_callback(
'input_token_details': {'cache_read': 0, 'cache_creation': 0}}}
.. versionadded:: 0.3.49
"""
from langchain_core.tracers.context import register_configure_hook

View File

@@ -91,6 +91,7 @@ class BaseChatMessageHistory(ABC):
def clear(self):
with open(os.path.join(storage_path, session_id), "w") as f:
f.write("[]")
"""
messages: list[BaseMessage]

View File

@@ -36,6 +36,7 @@ class LangSmithLoader(BaseLoader):
# -> [Document("...", metadata={"inputs": {...}, "outputs": {...}, ...}), ...]
.. versionadded:: 0.2.34
""" # noqa: E501
def __init__(
@@ -61,7 +62,7 @@ class LangSmithLoader(BaseLoader):
Args:
dataset_id: The ID of the dataset to filter by. Defaults to None.
dataset_name: The name of the dataset to filter by. Defaults to None.
content_key: The inputs key to set as Document page content. ``"."`` characters
content_key: The inputs key to set as Document page content. ``'.'`` characters
are interpreted as nested keys. E.g. ``content_key="first.second"`` will
result in
``Document(page_content=format_content(example.inputs["first"]["second"]))``

View File

@@ -102,6 +102,7 @@ class Blob(BaseMedia):
# Read the blob as a byte stream
with blob.as_bytes_io() as f:
print(f.read())
"""
data: Union[bytes, str, None] = None
@@ -265,6 +266,7 @@ class Document(BaseMedia):
page_content="Hello, world!",
metadata={"source": "https://example.com"}
)
"""
page_content: str

View File

@@ -46,6 +46,7 @@ class FakeEmbeddings(Embeddings, BaseModel):
2
[-0.5670477847544458, -0.31403828652395727, -0.5840547508955257]
"""
size: int
@@ -103,6 +104,7 @@ class DeterministicFakeEmbedding(Embeddings, BaseModel):
2
[-0.5670477847544458, -0.31403828652395727, -0.5840547508955257]
"""
size: int

View File

@@ -51,6 +51,7 @@ def _parse_data_uri(uri: str) -> Optional[dict]:
"mime_type": "image/jpeg",
"data": "/9j/4AAQSkZJRg...",
}
"""
regex = r"^data:(?P<mime_type>[^;]+);base64,(?P<data>.+)$"
match = re.match(regex, uri)

View File

@@ -1367,12 +1367,13 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
"""Model wrapper that returns outputs formatted to match the given schema.
Args:
schema:
The output schema. Can be passed in as:
- an OpenAI function/tool schema,
- a JSON Schema,
- a TypedDict class,
- or a Pydantic class.
schema: The output schema. Can be passed in as:
- an OpenAI function/tool schema,
- a JSON Schema,
- a TypedDict class,
- or a Pydantic class.
If ``schema`` is a Pydantic class then the model output will be a
Pydantic instance of that class, and the model-generated fields will be
validated by the Pydantic class. Otherwise the model output will be a
@@ -1386,7 +1387,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
then both the raw model response (a BaseMessage) and the parsed model
response will be returned. If an error occurs during output parsing it
will be caught and returned as well. The final output is always a dict
with keys "raw", "parsed", and "parsing_error".
with keys ``'raw'``, ``'parsed'``, and ``'parsing_error'``.
Returns:
A Runnable that takes same inputs as a :class:`langchain_core.language_models.chat.BaseChatModel`.
@@ -1397,9 +1398,10 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
Otherwise, if ``include_raw`` is False then Runnable outputs a dict.
If ``include_raw`` is True, then Runnable outputs a dict with keys:
- ``"raw"``: BaseMessage
- ``"parsed"``: None if there was a parsing error, otherwise the type depends on the ``schema`` as described above.
- ``"parsing_error"``: Optional[BaseException]
- ``'raw'``: BaseMessage
- ``'parsed'``: None if there was a parsing error, otherwise the type depends on the ``schema`` as described above.
- ``'parsing_error'``: Optional[BaseException]
Example: Pydantic schema (include_raw=False):
.. code-block:: python
@@ -1465,6 +1467,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
.. versionchanged:: 0.2.26
Added support for TypedDict class.
""" # noqa: E501
_ = kwargs.pop("method", None)
_ = kwargs.pop("strict", None)

View File

@@ -1418,6 +1418,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
.. code-block:: python
llm.save(file_path="path/llm.yaml")
"""
# Convert file to Path object.
save_path = Path(file_path)

View File

@@ -53,6 +53,7 @@ class BaseMemory(Serializable, ABC):
def clear(self) -> None:
pass
""" # noqa: E501
model_config = ConfigDict(

View File

@@ -57,6 +57,7 @@ class InputTokenDetails(TypedDict, total=False):
.. versionadded:: 0.3.9
May also hold extra provider-specific keys.
"""
audio: int
@@ -89,6 +90,7 @@ class OutputTokenDetails(TypedDict, total=False):
}
.. versionadded:: 0.3.9
"""
audio: int
@@ -128,6 +130,7 @@ class UsageMetadata(TypedDict):
.. versionchanged:: 0.3.9
Added ``input_token_details`` and ``output_token_details``.
"""
input_tokens: int

View File

@@ -28,6 +28,7 @@ class HumanMessage(BaseMessage):
# Instantiate a chat model and invoke it with the messages
model = ...
print(model.invoke(messages))
"""
example: bool = False

View File

@@ -59,6 +59,7 @@ class ToolMessage(BaseMessage, ToolOutputMixin):
The tool_call_id field is used to associate the tool call request with the
tool call response. This is useful in situations where a chat model is able
to request multiple tool calls in parallel.
""" # noqa: E501
tool_call_id: str
@@ -191,6 +192,7 @@ class ToolCall(TypedDict):
This represents a request to call the tool named "foo" with arguments {"a": 1}
and an identifier of "123".
"""
name: str
@@ -240,6 +242,7 @@ class ToolCallChunk(TypedDict):
AIMessageChunk(content="", tool_call_chunks=left_chunks)
+ AIMessageChunk(content="", tool_call_chunks=right_chunks)
).tool_call_chunks == [ToolCallChunk(name='foo', args='{"a":1}', index=0)]
"""
name: Optional[str]

View File

@@ -111,6 +111,7 @@ def get_buffer_string(
]
get_buffer_string(messages)
# -> "Human: Hi, how are you?\nAI: Good, how are you?"
"""
string_messages = []
for m in messages:
@@ -463,6 +464,7 @@ def filter_messages(
SystemMessage("you're a good assistant."),
HumanMessage("what's your name", id="foo", name="example_user"),
]
""" # noqa: E501
messages = convert_to_messages(messages)
filtered: list[BaseMessage] = []
@@ -869,6 +871,7 @@ def trim_messages(
HumanMessage("This is a 4 token text. The full message is 10 tokens.", id="first"),
AIMessage( [{"type": "text", "text": "This is the FIRST 4 token block."}], id="second"),
]
""" # noqa: E501
# Validate arguments
if start_on and strategy == "first":
@@ -1176,7 +1179,9 @@ def convert_to_openai_messages(
"id": block["id"],
"function": {
"name": block["name"],
"arguments": json.dumps(block["input"]),
"arguments": json.dumps(
block["input"], ensure_ascii=False
),
},
}
)
@@ -1550,7 +1555,7 @@ def _convert_to_openai_tool_calls(tool_calls: list[ToolCall]) -> list[dict]:
"id": tool_call["id"],
"function": {
"name": tool_call["name"],
"arguments": json.dumps(tool_call["args"]),
"arguments": json.dumps(tool_call["args"], ensure_ascii=False),
},
}
for tool_call in tool_calls

View File

@@ -155,6 +155,7 @@ class BaseOutputParser(
@property
def _type(self) -> str:
return "boolean_output_parser"
""" # noqa: E501
@property

View File

@@ -214,6 +214,7 @@ class PydanticOutputFunctionsParser(OutputFunctionsParser):
pydantic_schema={"cookie": Cookie, "dog": Dog}
)
result = parser.parse_result([chat_generation])
"""
pydantic_schema: Union[type[BaseModel], dict[str, type[BaseModel]]]

View File

@@ -46,7 +46,10 @@ class LLMResult(BaseModel):
relevant information from standardized fields present in AIMessage.
"""
run: Optional[list[RunInfo]] = None
"""List of metadata info for model call for each input."""
"""List of metadata info for model call for each input.
See :class:`~langchain_core.outputs.run_info.RunInfo` for details.
"""
type: Literal["LLMResult"] = "LLMResult"
"""Type is used exclusively for serialization purposes."""

View File

@@ -307,6 +307,7 @@ class BasePromptTemplate(
.. code-block:: python
prompt.format(variable1="foo")
"""
async def aformat(self, **kwargs: Any) -> FormatOutputType:
@@ -323,6 +324,7 @@ class BasePromptTemplate(
.. code-block:: python
await prompt.aformat(variable1="foo")
"""
return self.format(**kwargs)
@@ -363,6 +365,7 @@ class BasePromptTemplate(
.. code-block:: python
prompt.save(file_path="path/prompt.yaml")
"""
if self.partial_variables:
msg = "Cannot save prompt with partial variables."
@@ -442,6 +445,7 @@ def format_document(doc: Document, prompt: BasePromptTemplate[str]) -> str:
prompt = PromptTemplate.from_template("Page {page}: {page_content}")
format_document(doc, prompt)
>>> "Page 1: This is a joke"
"""
return prompt.format(**_get_document_info(doc, prompt))

View File

@@ -126,6 +126,7 @@ class MessagesPlaceholder(BaseMessagePromptTemplate):
# -> [
# HumanMessage(content="Hello!"),
# ]
"""
variable_name: str
@@ -1164,6 +1165,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
Returns:
a chat prompt template.
"""
return cls(messages, template_format=template_format)
@@ -1248,6 +1250,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
template2 = template.partial(user="Lucy", name="R2D2")
template2.format_messages(input="hello")
"""
prompt_dict = self.__dict__.copy()
prompt_dict["input_variables"] = list(

View File

@@ -357,6 +357,7 @@ class FewShotChatMessagePromptTemplate(
from langchain_core.chat_models import ChatAnthropic
chain = final_prompt | ChatAnthropic(model="claude-3-haiku-20240307")
chain.invoke({"input": "What's 3+3?"})
"""
input_variables: list[str] = Field(default_factory=list)

View File

@@ -122,6 +122,7 @@ class FewShotPromptWithTemplates(StringPromptTemplate):
.. code-block:: python
prompt.format(variable1="foo")
"""
kwargs = self._merge_partial_and_user_variables(**kwargs)
# Get the examples to use.

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