This pull request includes updates to the
`docs/docs/integrations/chat/perplexity.ipynb` file to enhance the
documentation for `ChatPerplexity`. The changes focus on demonstrating
the use of Perplexity-specific parameters and supporting structured
outputs for Tier 3+ users.
Enhancements to documentation:
* Added a new markdown cell explaining the use of Perplexity-specific
parameters through the `ChatPerplexity` class, including parameters like
`search_domain_filter`, `return_images`, `return_related_questions`, and
`search_recency_filter` using the `extra_body` parameter.
* Added a new code cell demonstrating how to invoke `ChatPerplexity`
with the `extra_body` parameter to filter search recency.
Support for structured outputs:
* Added a new markdown cell explaining that `ChatPerplexity` supports
structured outputs for Tier 3+ users.
* Added a new code cell demonstrating how to use `ChatPerplexity` with
structured outputs by defining a `BaseModel` class and invoking the chat
with structured output.[Copilot is generating a summary...]Thank you for
contributing to LangChain!
---------
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>
Hi @ccurme!
Thanks so much for helping with getting the Contextual documentation
merged last time. We added the reranker to our provider's documentation!
Please let me know if there's any issues with it! Would love to also
work with your team on an announcement for this! 🙏
Thank you for contributing to LangChain!
- [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"
- [x] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** updates contextual provider documentation to include
information about our reranker, also includes documentation for
contextual's reranker in the retrievers section
- **Twitter handle:** https://x.com/ContextualAI/highlights
docs have been added
- [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: ccurme <chester.curme@gmail.com>
Description: Update vector store tab inits to match either the docs or
api_ref (whichever was more comprehensive)
List of changes per vector stores:
- In-memory
- no change
- AstraDB
- match to docs - docs/api_refs match (excluding embeddings)
- Chroma
- match to docs - api_refs is less descriptive
- FAISS
- match to docs - docs/api_refs match (excluding embeddings)
- Milvus
- match to docs to use Milvus Lite with Flat index - api_refs does not
have index_param for generalization
- MongoDB
- match to docs - api_refs are sparser
- PGVector
- match to api_ref
- changed to include docker cmd directly in code
- docs/api_ref has comment to view docker command in separate code block
- Pinecone
- match to api_refs - docs have code dispersed
- Qdrant
- match to api_ref - docs has size=3072, api_ref has size=1536
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Fix several typos in docs/docs/how_to/split_html.ipynb
* `structered` should be `structured`
* `signifcant` should be `significant`
* `seperator` should be `separator`
- **Description:** This PR updates the [MLflow
integration](https://python.langchain.com/docs/integrations/providers/mlflow_tracking/)
docs. This PR is based on feedback and suggestions from @efriis on
#29612 . This proposed revision is much shorter, does not contain
images, and links out to the MLflow docs rather than providing lengthy
descriptions directly within these docs. Thank you for taking another
look!
- **Issue:** NA
- **Dependencies:** NA
---------
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>
Thank you for contributing to LangChain!
- [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"
- [x] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: If you're adding a new integration, 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, eyurtsev, ccurme, vbarda, hwchase17.
---------
Signed-off-by: pudongair <744355276@qq.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
- [x] **PR title**
- [x] **PR message**:
- **Description:** Updated the sparse and hybrid vector search due to
changes in the Qdrant API, and cleaned up the notebook
- [x] **Add tests and docs**:
- N/A
- [x] **Lint and test**
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: Mark Perfect <mark.anthony.perfect1@gmail.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>
## Description:
- Removed deprecated `initialize_agent()` usage in AWS Lambda
integration.
- Replaced it with `AgentExecutor` for compatibility with LangChain
v0.3.
- Fixed documentation linting errors.
## Issue:
- No specific issue linked, but this resolves the use of deprecated
agent initialization.
## Dependencies:
- No new dependencies added.
## Request for Review:
- Please verify if the implementation is correct.
- If approved and merged, I will proceed with updating other related
files.
## Twitter Handle (Optional):
I don't have a Twitter but here is my LinkedIn instead
(https://www.linkedin.com/in/aryan1227/)
The former link led to a site that explains that the docs have moved,
but did not redirect the user to the actual site automatically. I just
copied the provided url, checked that it works and updated the link to
the current version.
**Description:** Updated the link to Unstructured Docs at
https://docs.unstructured.io
**Issue:** #30315
**Dependencies:** None
**Twitter handle:** @lahoramaker
- Support features from recent update:
https://www.anthropic.com/news/token-saving-updates (mostly adding
support for built-in tools in `bind_tools`
- Add documentation around prompt caching, token-efficient tool use, and
built-in tools.
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"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: If you're adding a new integration, 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, eyurtsev, ccurme, vbarda, hwchase17.
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"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: If you're adding a new integration, 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, eyurtsev, ccurme, vbarda, hwchase17.
```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>
