Add tools to interact with Dappier APIs with an example notebook.
For `DappierRealTimeSearchTool`, the tool can be invoked with:
```python
from langchain_dappier import DappierRealTimeSearchTool
tool = DappierRealTimeSearchTool()
tool.invoke({"query": "What happened at the last wimbledon"})
```
```
At the last Wimbledon in 2024, Carlos Alcaraz won the title by defeating Novak Djokovic. This victory marked Alcaraz's fourth Grand Slam title at just 21 years old! 🎉🏆🎾
```
For DappierAIRecommendationTool the tool can be invoked with:
```python
from langchain_dappier import DappierAIRecommendationTool
tool = DappierAIRecommendationTool(
data_model_id="dm_01j0pb465keqmatq9k83dthx34",
similarity_top_k=3,
ref="sportsnaut.com",
num_articles_ref=2,
search_algorithm="most_recent",
)
```
```
[{"author": "Matt Weaver", "image_url": "https://images.dappier.com/dm_01j0pb465keqmatq9k83dthx34...", "pubdate": "Fri, 17 Jan 2025 08:04:03 +0000", "source_url": "https://sportsnaut.com/chili-bowl-thursday-bell-column/", "summary": "The article highlights the thrilling unpredictability... ", "title": "Thursday proves why every lap of Chili Bowl..."},
{"author": "Matt Higgins", "image_url": "https://images.dappier.com/dm_01j0pb465keqmatq9k83dthx34...", "pubdate": "Fri, 17 Jan 2025 02:48:42 +0000", "source_url": "https://sportsnaut.com/new-york-mets-news-pete-alonso...", "summary": "The New York Mets are likely parting ways with star...", "title": "MLB insiders reveal New York Mets’ last-ditch..."},
{"author": "Jim Cerny", "image_url": "https://images.dappier.com/dm_01j0pb465keqmatq9k83dthx34...", "pubdate": "Fri, 17 Jan 2025 05:10:39 +0000", "source_url": "https://www.foreverblueshirts.com/new-york-rangers-news...", "summary": "The New York Rangers achieved a thrilling 5-3 comeback... ", "title": "Rangers score 3 times in 3rd period for stirring 5-3..."}]
```
The integration package can be found over here -
https://github.com/DappierAI/langchain-dappier
Expanded the Amazon Neptune documentation with new sections detailing
usage of chat message history with the
`create_neptune_opencypher_qa_chain` and
`create_neptune_sparql_qa_chain` functions.
Title: community: add Financial Modeling Prep (FMP) API integration
Description: Adding LangChain integration for Financial Modeling Prep
(FMP) API to enable semantic search and structured tool creation for
financial data endpoints. This integration provides semantic endpoint
search using vector stores and automatic tool creation with proper
typing and error handling. Users can discover relevant financial
endpoints using natural language queries and get properly typed
LangChain tools for discovered endpoints.
Issue: N/A
Dependencies:
fmp-data>=0.3.1
langchain-core>=0.1.0
faiss-cpu
tiktoken
Twitter handle: @mehdizarem
Unit tests and example notebook have been added:
Tests are in tests/integration_tests/est_tools.py and
tests/unit_tests/test_tools.py
Example notebook is in docs/tools.ipynb
All format, lint and test checks pass:
pytest
mypy .
Dependencies are imported within functions and not added to
pyproject.toml. The changes are backwards compatible and only affect the
community package.
---------
Co-authored-by: mehdizare <mehdizare@users.noreply.github.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Related: https://github.com/langchain-ai/langchain-aws/pull/322
The legacy `NeptuneOpenCypherQAChain` and `NeptuneSparqlQAChain` classes
are being replaced by the new LCEL format chains
`create_neptune_opencypher_qa_chain` and
`create_neptune_sparql_qa_chain`, respectively, in the `langchain_aws`
package.
This PR adds deprecation warnings to all Neptune classes and functions
that have been migrated to `langchain_aws`. All relevant documentation
has also been updated to replace `langchain_community` usage with the
new `langchain_aws` implementations.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
### Description
This PR adds docs for the
[langchain-hyperbrowser](https://pypi.org/project/langchain-hyperbrowser/)
package. It includes a document loader that uses Hyperbrowser to scrape
or crawl any urls and return formatted markdown or html content as well
as relevant metadata.
[Hyperbrowser](https://hyperbrowser.ai) is a platform for running and
scaling headless browsers. It lets you launch and manage browser
sessions at scale and provides easy to use solutions for any webscraping
needs, such as scraping a single page or crawling an entire site.
### Issue
None
### Dependencies
None
### Twitter Handle
`@hyperbrowser`
…angChain parser issue.
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, efriis, eyurtsev, ccurme, vbarda, hwchase17.
Thank you for contributing to LangChain!
Update presented model in `WatsonxRerank` documentation.
- [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/
**Description:**
Adding voyage-3-large model to the .ipynb file (its just extending a
list, so not even a code change)
- [ ] **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.
fix to word "can"
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, efriis, eyurtsev, ccurme, vbarda, hwchase17.
## Langchain Kùzu
### Description
This PR adds docs for the `langchain-kuzu` package [on
PyPI](https://pypi.org/project/langchain-kuzu/) that was recently
published, allowing Kùzu users to more easily use and work with
LangChain QA chains. The package will also make it easier for the Kùzu
team to continue supporting and updating the integration over future
releases.
### Twitter Handle
Please tag [@kuzudb](https://x.com/kuzudb) on Twitter once this PR is
merged, so LangChain users can be notified!
---------
Co-authored-by: Erick Friis <erickfriis@gmail.com>
- [x] **PR title**: "docs: add langchain-pull-md Markdown loader"
- [x] **PR message**:
- **Description:** This PR introduces the `langchain-pull-md` package to
the LangChain community. It includes a new document loader that utilizes
the pull.md service to convert URLs into Markdown format, particularly
useful for handling web pages rendered with JavaScript frameworks like
React, Angular, or Vue.js. This loader helps in efficient and reliable
Markdown conversion directly from URLs without local rendering, reducing
server load.
- **Issue:** NA
- **Dependencies:** requests >=2.25.1
- **Twitter handle:** https://x.com/eugeneevstafev?s=21
- [x] **Add tests and docs**:
1. Added unit tests to verify URL checking and conversion
functionalities.
2. Created a comprehensive example notebook detailing the usage of the
new loader.
- [x] **Lint and test**:
- Completed local testing using `make format`, `make lint`, and `make
test` commands as per the LangChain contribution guidelines.
**Related Links:**
- [Package Repository](https://github.com/chigwell/langchain-pull-md)
- [PyPI Package](https://pypi.org/project/langchain-pull-md/)
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
spell check
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, efriis, eyurtsev, ccurme, vbarda, hwchase17.
Add a retriever to interact with Dappier APIs with an example notebook.
The retriever can be invoked with:
```python
from langchain_dappier import DappierRetriever
retriever = DappierRetriever(
data_model_id="dm_01jagy9nqaeer9hxx8z1sk1jx6",
k=5
)
retriever.invoke("latest tech news")
```
To retrieve 5 documents related to latest news in the tech sector. The
included notebook also includes deeper details about controlling filters
such as selecting a data model, number of documents to return, site
domain reference, minimum articles from the reference domain, and search
algorithm, as well as including the retriever in a chain.
The integration package can be found over here -
https://github.com/DappierAI/langchain-dappier
## Description
This pull request updates the documentation for FAISS regarding filter
construction, following the changes made in commit `df5008f`.
## Issue
None. This is a follow-up PR for documentation of
[#28207](https://github.com/langchain-ai/langchain/pull/28207)
## Dependencies:
None.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
This commit updates the documentation and package registry for the
FalkorDB Chat Message History integration.
**Changes:**
- Added a comprehensive example notebook
falkordb_chat_message_history.ipynb demonstrating how to use FalkorDB
for session-based chat message storage.
- Added a provider notebook for FalkorDB
- Updated libs/packages.yml to register FalkorDB as an integration
package, following LangChain's new guidelines for community
integrations.
**Notes:**
- This update aligns with LangChain's process for registering new
integrations via documentation updates and package registry
modifications.
- No functional or core package changes were made in this commit.
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
## Description
To integrate ModelScope inference API endpoints for both Embeddings,
LLMs and ChatModels, install the package
`langchain-modelscope-integration` (as discussed in issue #28928 ). This
is necessary because the package name `langchain-modelscope` was already
registered by another party.
ModelScope is a premier platform designed to connect model checkpoints
with model applications. It provides the necessary infrastructure to
share open models and promote model-centric development. For more
information, visit GitHub page:
[ModelScope](https://github.com/modelscope).
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"
- **Description:** Update docs to add BoxBlobLoader and extra_fields to
all Box connectors.
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** @BoxPlatform
- [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, efriis, eyurtsev, ccurme, vbarda, hwchase17.
Hi Erick. Coming back from a previous attempt, we now made a separate
package for the CrateDB adapter, called `langchain-cratedb`, as advised.
Other than registering the package within `libs/packages.yml`, this
patch includes a minimal amount of documentation to accompany the advent
of this new package. Let us know about any mistakes we made, or changes
you would like to see. Thanks, Andreas.
## About
- **Description:** Register a new database adapter package,
`langchain-cratedb`, providing traditional vector store, document
loader, and chat message history features for a start.
- **Addressed to:** @efriis, @eyurtsev
- **References:** GH-27710
- **Preview:** [Providers » More »
CrateDB](https://langchain-git-fork-crate-workbench-register-la-4bf945-langchain.vercel.app/docs/integrations/providers/cratedb/)
## Status
- **PyPI:** https://pypi.org/project/langchain-cratedb/
- **GitHub:** https://github.com/crate/langchain-cratedb
- **Documentation (CrateDB):**
https://cratedb.com/docs/guide/integrate/langchain/
- **Documentation (LangChain):** _This PR._
## Backlog?
Is this applicable for this kind of patch?
> - [ ] **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.
## Q&A
1. Notebooks that use the LangChain CrateDB adapter are currently at
[CrateDB LangChain
Examples](https://github.com/crate/cratedb-examples/tree/main/topic/machine-learning/llm-langchain),
and the documentation refers to them. Because they are derived from very
old blueprints coming from LangChain 0.0.x times, we guess they need a
refresh before adding them to `docs/docs/integrations`. Is it applicable
to merge this minimal package registration + documentation patch, which
already includes valid code snippets in `cratedb.mdx`, and add
corresponding notebooks on behalf of a subsequent patch later?
2. How would it work getting into the tabular list of _Integration
Packages_ enumerated on the [documentation entrypoint page about
Providers](https://python.langchain.com/docs/integrations/providers/)?
/cc Please also review, @ckurze, @wierdvanderhaar, @kneth,
@simonprickett, if you can find the time. Thanks!
- **Description:** The aload function, contrary to its name, is not an
asynchronous function, so it cannot work concurrently with other
asynchronous functions.
- **Issue:** #28336
- **Test: **: Done
- **Docs: **
[here](e0a95e5646/docs/docs/integrations/document_loaders/web_base.ipynb (L201))
- **Lint: ** All checks passed
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>
- *[x] **PR title**: "community: adding langchain-predictionguard
partner package documentation"
- *[x] **PR message**:
- **Description:** This PR adds documentation for the
langchain-predictionguard package to main langchain repo, along with
deprecating current Prediction Guard LLMs package. The LLMs package was
previously broken, so I also updated it one final time to allow it to
continue working from this point onward. . This enables users to chat
with LLMs through the Prediction Guard ecosystem.
- **Package Links**:
- [PyPI](https://pypi.org/project/langchain-predictionguard/)
- [Github
Repo](https://www.github.com/predictionguard/langchain-predictionguard)
- **Issue:** None
- **Dependencies:** None
- **Twitter handle:** [@predictionguard](https://x.com/predictionguard)
- *[x] **Add tests and docs**: All docs have been added for the partner
package, and the current LLMs package test was updated to reflect
changes.
- *[x] **Lint and test**: Linting tests are all passing.
---------
Co-authored-by: ccurme <chester.curme@gmail.com>
Issue: several Google integrations are implemented on the
[github.com/googleapis](https://github.com/googleapis) organization
repos and these integrations are almost lost. But they are essential
integrations.
Change: added a list of all packages that have Google integrations.
Added a description of this situation.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: ccurme <chester.curme@gmail.com>
Thank you for contributing to LangChain!
- [x] **PR title**: "package: description"
- "community: 1. add new parameter `default_headers` for oci model
deployments and oci chat model deployments. 2. updated k parameter in
OCIModelDeploymentLLM class."
- [x] **PR message**:
- **Description:** 1. add new parameters `default_headers` for oci model
deployments and oci chat model deployments. 2. updated k parameter in
OCIModelDeploymentLLM class.
- [x] **Add tests and docs**:
1. unit tests
2. notebook
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
## Overview
This PR adds documentation for the `langchain-yt-dlp` package, a YouTube
document loader that uses `yt-dlp` for Youtube videos metadata
extraaction.
## Changes
- Added documentation notebook for YoutubeLoader
- Updated packages.yml to include langchain-yt-dlp
## Motivation
The existing LangChain YoutubeLoader was unable to fetch YouTube
metadata due to changes in YouTube's structure. This package resolves
those issues by leveraging the `yt-dlp` library.
## Features
- Reliable YouTube metadata extraction
## Related
- Package Repository: https://github.com/aqib0770/langchain-yt-dlp
- PyPI Package: https://pypi.org/project/langchain-yt-dlp/
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Hi, langchain team! I'm a maintainer of
[OceanBase](https://github.com/oceanbase/oceanbase).
With the integration guidance, I create a python lib named
[langchain-oceanbase](https://github.com/oceanbase/langchain-oceanbase)
to integrate `Oceanbase Vector Store` with `Langchain`.
So I'd like to add the required docs. I will appreciate your feedback.
Thank you!
---------
Signed-off-by: shanhaikang.shk <shanhaikang.shk@oceanbase.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
- [X] **PR title**:
community: Add new model and structured output support
- [X] **PR message**:
- **Description:** add support for meta llama 3.2 image handling, and
JSON mode for structured output
- **Issue:** NA
- **Dependencies:** NA
- **Twitter handle:** NA
- [x] **Add tests and docs**:
1. we have updated our unit tests,
2. no changes required for documentation.
- [x] **Lint and test**:
make format, make lint and make test we run successfully
---------
Co-authored-by: Arthur Cheng <arthur.cheng@oracle.com>
Co-authored-by: ccurme <chester.curme@gmail.com>
**Description**: Some confluence instances don't support personal access
token, then cookie is a convenient way to authenticate. This PR adds
support for Confluence cookies.
**Twitter handle**: soulmachine
Issue: the current
[Cache](https://python.langchain.com/docs/integrations/llm_caching/)
page has an inconsistent heading.
Mixed terms are used; mixed casing; and mixed `selecting`. Excessively
long titles make right-side ToC hard to read and unnecessarily long.
Changes: consitent and more-readable ToC
**Description:** Added support for FalkorDB Vector Store, including its
implementation, unit tests, documentation, and an example notebook. The
FalkorDB integration allows users to efficiently manage and query
embeddings in a vector database, with relevance scoring and maximal
marginal relevance search. The following components were implemented:
- Core implementation for FalkorDBVector store.
- Unit tests ensuring proper functionality and edge case coverage.
- Example notebook demonstrating an end-to-end setup, search, and
retrieval using FalkorDB.
**Twitter handle:** @tariyekorogha
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Update to OpenLLM 0.6, which we decides to make use of OpenLLM's
OpenAI-compatible endpoint. Thus, OpenLLM will now just become a thin
wrapper around OpenAI wrapper.
Signed-off-by: Aaron Pham <contact@aarnphm.xyz>
---------
Signed-off-by: Aaron Pham <contact@aarnphm.xyz>
Co-authored-by: ccurme <chester.curme@gmail.com>
**Description:**
This PR addresses the `TypeError: sequence item 0: expected str
instance, FluentValue found` error when invoking `WikidataQueryRun`. The
root cause was an incompatible version of the
`wikibase-rest-api-client`, which caused the tool to fail when handling
`FluentValue` objects instead of strings.
The current implementation only supports `wikibase-rest-api-client<0.2`,
but the latest version is `0.2.1`, where the current implementation
breaks. Additionally, the error message advises users to install the
latest version: [code
reference](https://github.com/langchain-ai/langchain/blob/master/libs/community/langchain_community/utilities/wikidata.py#L125C25-L125C32).
Therefore, this PR updates the tool to support the latest version of
`wikibase-rest-api-client`.
Key changes:
- Updated the handling of `FluentValue` objects to ensure compatibility
with the latest `wikibase-rest-api-client`.
- Removed the restriction to `wikibase-rest-api-client<0.2` and updated
to support the latest version (`0.2.1`).
**Issue:**
Fixes [#24093](https://github.com/langchain-ai/langchain/issues/24093) –
`TypeError: sequence item 0: expected str instance, FluentValue found`.
**Dependencies:**
- Upgraded `wikibase-rest-api-client` to the latest version to resolve
the issue.
---------
Co-authored-by: peiwen_zhang <peiwen_zhang@email.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
