**Library Repo Path Update **: "langchain-cloudflare"
We recently changed our `langchain-cloudflare` repo to allow for future
libraries.
Created a `libs` folder to hold `langchain-cloudflare` python package.
https://github.com/cloudflare/langchain-cloudflare/tree/main/libs/langchain-cloudflare
On `langchain`, updating `packages.yaml` to point to new
`libs/langchain-cloudflare` library folder.
This PR brings several improvements and modernizations to the
documentation around the Astra DB partner package.
- language alignment for better matching with the terms used in the
Astra DB docs
- updated several links to pages on said documentation
- for the `AstraDBVectorStore`, added mentions of the new features in
the overall `astra.mdx`
- for the vector store, rewritten/upgraded most of the usage example
notebook for a more straightforward experience able to highlight the
main usage patterns (including new ones such as the newly-introduced
"autodetect feature")
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
This PR includes the following documentation fixes for the SAP HANA
Cloud vector store integration:
- Removed stale output from the `%pip install` code cell.
- Replaced an unrelated vectorstore documentation link on the provider
overview page.
- Renamed the provider from "SAP HANA" to "SAP HANA Cloud"
- **Description:**
This PR marks the `HanaDB` vector store (and related utilities) in
`langchain_community` as deprecated using the `@deprecated` annotation.
- Set `since="0.1.0"` and `removal="1.0"`
- Added a clear migration path and a link to the SAP-maintained
replacement in the
[`langchain_hana`](https://github.com/SAP/langchain-integration-for-sap-hana-cloud)
package.
Additionally, the example notebook has been updated to use the new
`HanaDB` class from `langchain_hana`, ensuring users follow the
recommended integration moving forward.
- **Issue:** None
- **Dependencies:** None
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
PR title:
docs: add Valyu integration documentation
Description:
This PR adds documentation and example notebooks for the Valyu
integration, including retriever and tool usage.
Issue:
N/A
Dependencies:
No new dependencies.
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
- [ ] **PR title**: "docs: adding Smabbler's Galaxia integration"
- [ ] **PR message**: **Twitter handle:** @Galaxia_graph
I'm adding docs here + added the package to the packages.yml. I didn't
add a unit test, because this integration is just a thin wrapper on top
of our API. There isn't much left to test if you mock it away.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Description:
This PR adds documentation for the langchain-cloudflare integration
package.
Issue:
N/A
Dependencies:
No new dependencies are required.
Tests and Docs:
Added an example notebook demonstrating the usage of the
langchain-cloudflare package, located in docs/docs/integrations.
Added a new package to libs/packages.yml.
Lint and Format:
Successfully ran make format and make lint.
---------
Co-authored-by: Collier King <collier@cloudflare.com>
Co-authored-by: Collier King <collierking99@gmail.com>
LangChain QwQ allows non-Tongyi users to access thinking models with
extra capabilities which serve as an extension to Alibaba Cloud.
Hi @ccurme I'm back with the updated PR this time with documentation and
a finished package.
- [x] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core, etc. is
being modified. Use "docs: ..." for purely docs changes, "infra: ..."
for CI changes.
- Example: "community: add foobar LLM"
- **Description:** adds documentation of `langchain-qwq` integration
package. Also adds it to Alibaba Cloud provider
- **Issue:** #30580#30317#30579
- **Dependencies:** openai, json-repair
- **Twitter handle:** YigitBekir
- [x] **Add tests and docs**: If you're adding a new integration, please
include
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, eyurtsev, ccurme, vbarda, hwchase17.
## Description:
This PR adds the necessary documentation for the `langchain-runpod`
partner package integration. It includes:
* A provider page (`docs/docs/integrations/providers/runpod.ipynb`)
explaining the overall setup.
* An LLM component page (`docs/docs/integrations/llms/runpod.ipynb`)
detailing the `RunPod` class usage.
* A Chat Model component page
(`docs/docs/integrations/chat/runpod.ipynb`) detailing the `ChatRunPod`
class usage, including a feature support table.
These documentation files reflect the latest features of the
`langchain-runpod` package (v0.2.0+) such as async support and API
polling logic.
This work also addresses the review feedback provided on the previous
attempt in PR #30246 by:
* Removing all TODOs from documentation.
* Adding the required links between provider and component pages.
* Completing the feature support table in the chat documentation.
* Linking to the source code on GitHub for API reference.
Finally, it registers the `langchain-runpod` package in
`libs/packages.yml`.
## Dependencies:
None added to the core LangChain repository by these documentation
changes. The required dependency (`langchain-runpod`) is managed as a
separate package.
## Twitter handle:
@runpod_io
---------
Co-authored-by: Max Forsey <maxpod@maxpod.local>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Plus, some accompanying docs updates
Some compelling usage:
```py
from langchain_perplexity import ChatPerplexity
chat = ChatPerplexity(model="llama-3.1-sonar-small-128k-online")
response = chat.invoke(
"What were the most significant newsworthy events that occurred in the US recently?",
extra_body={"search_recency_filter": "week"},
)
print(response.content)
# > Here are the top significant newsworthy events in the US recently: ...
```
Also, some confirmation of structured outputs:
```py
from langchain_perplexity import ChatPerplexity
from pydantic import BaseModel
class AnswerFormat(BaseModel):
first_name: str
last_name: str
year_of_birth: int
num_seasons_in_nba: int
messages = [
{"role": "system", "content": "Be precise and concise."},
{
"role": "user",
"content": (
"Tell me about Michael Jordan. "
"Please output a JSON object containing the following fields: "
"first_name, last_name, year_of_birth, num_seasons_in_nba. "
),
},
]
llm = ChatPerplexity(model="llama-3.1-sonar-small-128k-online")
structured_llm = llm.with_structured_output(AnswerFormat)
response = structured_llm.invoke(messages)
print(repr(response))
#> AnswerFormat(first_name='Michael', last_name='Jordan', year_of_birth=1963, num_seasons_in_nba=15)
```
Description:
This PR adds documentation for the langchain-oxylabs integration
package.
The documentation includes instructions for configuring Oxylabs
credentials and provides example code demonstrating how to use the
package.
Issue:
N/A
Dependencies:
No new dependencies are required.
Tests and Docs:
Added an example notebook demonstrating the usage of the
Langchain-Oxylabs package, located in docs/docs/integrations.
Added a provider page in docs/docs/providers.
Added a new package to libs/packages.yml.
Lint and Test:
Successfully ran make format, make lint, and make test.
Thank you for contributing to LangChain!
**Description:**
Since we just implemented
[langchain-memgraph](https://pypi.org/project/langchain-memgraph/)
integration, we are adding basic docs to [your site based on this
comment](https://github.com/langchain-ai/langchain/pull/30197#pullrequestreview-2671616410)
from @ccurme .
**Twitter handle:**
[@memgraphdb](https://x.com/memgraphdb)
- [x] **Add tests and docs**: If you're adding a new integration, please
include
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, eyurtsev, ccurme, vbarda, hwchase17.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Hello!
I have reopened a pull request for tool integration.
Please refer to the previous
[PR](https://github.com/langchain-ai/langchain/pull/30248).
I understand that for the tool integration, a separate package should be
created, and only the documentation should be added under docs/docs/. If
there are any other procedures, please let me know.
[langchain-naver-community](https://github.com/e7217/langchain-naver-community)
cc: @ccurme
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
**Description**
This contribution adds a retriever for the Zotero API.
[Zotero](https://www.zotero.org/) is an open source reference management
for bibliographic data and related research materials. A retriever will
allow langchain applications to retrieve relevant documents from
personal or shared group libraries, which I believe will be helpful for
numerous applications, such as RAG systems, personal research
assistants, etc. Tests and docs were added.
The documentation provided assumes the retriever will be part of the
langchain-community package, as this seemed customary. Please let me
know if this is not the preferred way to do it. I also uploaded the
implementation to PyPI.
**Dependencies**
The retriever requires the `pyzotero` package for API access. This
dependency is stated in the docs, and the retriever will return an error
if the package is not found. However, this dependency is not added to
the langchain package itself.
**Twitter handle**
I'm no longer using Twitter, but I'd appreciate a shoutout on
[Bluesky](https://bsky.app/profile/koenigt.bsky.social) or
[LinkedIn](https://www.linkedin.com/in/dr-tim-k%C3%B6nig-534aa2324/)!
Let me know if there are any issues, I'll gladly try and sort them out!
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
This pull request includes a change to the following
- docs/docs/integrations/tools/tavily_search.ipynb
- docs/docs/integrations/tools/tavily_extract.ipynb
- added docs/docs/integrations/providers/tavily.mdx
---------
Co-authored-by: pulvedu <dustin@tavily.com>
# Description
Adds documentation on LangChain website for a Dell specific document
loader for on-prem storage devices. Additional details on what the
document loader is described in the PR as well as on our github repo:
[https://github.com/dell/powerscale-rag-connector](https://github.com/dell/powerscale-rag-connector)
This PR also creates a category on the document loader webpage as no
existing category exists for on-prem. This follows the existing pattern
already established as the website has a category for cloud providers.
# Issue:
New release, no issue.
# Dependencies:
None
# Twitter handle:
DellTech
---------
Signed-off-by: Adam Brenner <adam@aeb.io>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
```markdown
**Description:**
This PR integrates Valthera into LangChain, introducing an framework designed to send highly personalized nudges by an LLM agent. This is modeled after Dr. BJ Fogg's Behavior Model. This integration includes:
- Custom data connectors for HubSpot, PostHog, and Snowflake.
- A unified data aggregator that consolidates user data.
- Scoring configurations to compute motivation and ability scores.
- A reasoning engine that determines the appropriate user action.
- A trigger generator to create personalized messages for user engagement.
**Issue:**
N/A
**Dependencies:**
N/A
**Twitter handle:**
- `@vselvarajijay`
**Tests and Docs:**
- `docs/docs/integrations/tools/valthera`
- `https://github.com/valthera/langchain-valthera/tree/main/tests`
```
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Thank you for contributing to LangChain!
**Description:** adds ContextualAI's `langchain-contextual` package's
documentation
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
docs: New integration for LangChain - ads4gpts-langchain
Description: Tools and Toolkit for Agentic integration natively within
LangChain with ADS4GPTs, in order to help applications monetize with
advertising.
Twitter handle: @ads4gpts
Co-authored-by: knitlydevaccount <loom+github@knitly.app>
- **Description: a notebook showing langchain and langraph agents using
the new langchain_tableau tool
- **Twitter handle: @joe_constantin0
---------
Co-authored-by: Joe Constantino <joe@constantino.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
This PR adds documentation for the langchain-taiga Tool integration,
including an example notebook at
'docs/docs/integrations/tools/taiga.ipynb' and updates to
'libs/packages.yml' to track the new package.
Issue:
N/A
Dependencies:
None
Twitter handle:
N/A
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
## PyMuPDF4LLM integration to LangChain for PDF content extraction in
Markdown format
### Description
[PyMuPDF4LLM](https://github.com/pymupdf/RAG) makes it easier to extract
PDF content in Markdown format, needed for LLM & RAG applications.
(License: GNU Affero General Public License v3.0)
[langchain-pymupdf4llm](https://github.com/lakinduboteju/langchain-pymupdf4llm)
integrates PyMuPDF4LLM to LangChain as a Document Loader.
(License: MIT License)
This pull request introduces the integration of
[PyMuPDF4LLM](https://pymupdf.readthedocs.io/en/latest/pymupdf4llm) into
the LangChain project as an integration package:
[`langchain-pymupdf4llm`](https://github.com/lakinduboteju/langchain-pymupdf4llm).
The most important changes include adding new Jupyter notebooks to
document the integration and updating the package configuration file to
include the new package.
### Documentation:
* `docs/docs/integrations/providers/pymupdf4llm.ipynb`: Added a new
Jupyter notebook to document the integration of `PyMuPDF4LLM` with
LangChain, including installation instructions and class imports.
* `docs/docs/integrations/document_loaders/pymupdf4llm.ipynb`: Added a
new Jupyter notebook to document the usage of `langchain-pymupdf4llm` as
a LangChain integration package in detail.
### Package registration:
* `libs/packages.yml`: Updated the package configuration file to include
the `langchain-pymupdf4llm` package.
### Additional information
* Related to: https://github.com/langchain-ai/langchain/pull/29848
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
## Which area of LangChain is being modified?
- This PR adds a new "Permit" integration to the `docs/integrations/`
folder.
- Introduces two new Tools (`LangchainJWTValidationTool` and
`LangchainPermissionsCheckTool`)
- Introduces two new Retrievers (`PermitSelfQueryRetriever` and
`PermitEnsembleRetriever`)
- Adds demo scripts in `examples/` showcasing usage.
## Description of Changes
- Created `langchain_permit/tools.py` for JWT validation and permission
checks with Permit.
- Created `langchain_permit/retrievers.py` for custom Permit-based
retrievers.
- Added documentation in `docs/integrations/providers/permit.ipynb` (or
`.mdx`) to explain setup, usage, and examples.
- Provided sample scripts in `examples/demo_scripts/` to illustrate
usage of these tools and retrievers.
- Ensured all code is linted and tested locally.
Thank you again for reviewing!
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core, etc. is
being modified. Use "docs: ..." for purely docs changes, "infra: ..."
for CI changes.
- Example: "community: add foobar LLM"
- [ ] **Add tests and docs**: If you're adding a new integration, please
include
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
This PR adds a new cognee integration, knowledge graph based retrieval
enabling developers to ingest documents into cognee’s knowledge graph,
process them, and then retrieve context via CogneeRetriever.
It includes:
- langchain_cognee package with a CogneeRetriever class
- a test for the integration, demonstrating how to create, process, and
retrieve with cognee
- an example notebook showing its use. It lives in
`docs/docs/integrations` directory.
Followed additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
Thank you for the review!
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
This PR adds documentation for the Azure AI package in Langchain to the
main mono-repo
No issue connected or updated dependencies.
Utilises existing tests and makes updates to the docs
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
