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>
- [x] **PR title**: "docs: Fix typo in documentation"
- [x] **PR message**:
- **Description:** Fixed a typo in the documentation, changing "An
vectorstore" to "A vector store" for grammatical accuracy.
- **Issue:** N/A (no issue filed for this typo fix)
- **Dependencies:** None
- **Twitter handle:** N/A
- [x] **Add tests and docs**: This is a minor documentation fix that
doesn't require additional tests or example notebooks.
- [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/
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`
Fixed a broken link in `document_loader_markdown.ipynb` to point to the
updated documentation page for the Unstructured package.
Issue: N/A
Dependencies: None
…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/
Update model for one notebook that specified `gpt-4`.
Otherwise just updating cassettes.
---------
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
**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.
Add upstage document parse loader to pdf loaders
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
Problem:
"Optional" object is used in one example without importing, which raises
the following error when copying the example into IDE or Jupyter Lab
Solution:
Just importing Optional from typing_extensions module, this solves the
problem!
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
## 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>
This pull request updates the documentation in
`docs/docs/how_to/custom_tools.ipynb` to reflect the recommended
approach for generating JSON schemas in Pydantic. Specifically, it
replaces instances of the deprecated `schema()` method with the newer
and more versatile `model_json_schema()`.
## 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.
- Title: Fix typo to correct "embedding" to "embeddings" in PGVector
initialization example
- Problem: There is a typo in the example code for initializing the
PGVector class. The current parameter "embedding" is incorrect as the
class expects "embeddings".
- Correction: The corrected code snippet is:
vector_store = PGVector(
embeddings=embeddings,
collection_name="my_docs",
connection="postgresql+psycopg://...",
)
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!
