**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>
Description: Add tool calling and structured output support for
SambaStudio chat models, docs included
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Fixes#26171:
- added some clarification text for the keyword argument
`breakpoint_threshold_amount`
- added min_chunk_size: together with `breakpoint_threshold_amount`, too
small/big chunk sizes can be avoided
Note: the langchain-experimental was moved to a separate repo, so only
the doc change stays here.
Thank you for contributing to LangChain!
- Added [full
text](https://learn.microsoft.com/en-us/azure/cosmos-db/gen-ai/full-text-search)
and [hybrid
search](https://learn.microsoft.com/en-us/azure/cosmos-db/gen-ai/hybrid-search)
support for Azure CosmosDB NoSql Vector Store
- Added a new enum called CosmosDBQueryType which supports the following
values:
- VECTOR = "vector"
- FULL_TEXT_SEARCH = "full_text_search"
- FULL_TEXT_RANK = "full_text_rank"
- HYBRID = "hybrid"
- User now needs to provide this query_type to the similarity_search
method for the vectorStore to make the correct query api call.
- Added a couple of work arounds as for the FULL_TEXT_RANK and HYBRID
query functions we don't support parameterized queries right now. I have
added TODO's in place, and will remove these work arounds by end of
January.
- Added necessary test cases and updated the
- [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.
---------
Co-authored-by: Erick Friis <erickfriis@gmail.com>
Issue: Here is an ambiguity about W&B integrations. There are two
existing provider pages.
Fix: Added the "root" W&B provider page. Added there the references to
the documentation in the W&B site. Cleaned up formats in existing pages.
Added one more integration reference.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Added Langchain complete tutorial playlist from total technology zonne
channel .In this playlist every video is focusing one specific use case
and hands on demo.All tutorials are equally good for every levels .
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.
---------
Co-authored-by: Erick Friis <erickfriis@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
~Note that this PR is now Draft, so I didn't add change to `aindex`
function and didn't add test codes for my change.
After we have an agreement on the direction, I will add commits.~
`batch_size` is very difficult to decide because setting a large number
like >10000 will impact VectorDB and RecordManager, while setting a
small number will delete records unnecessarily, leading to redundant
work, as the `IMPORTANT` section says.
On the other hand, we can't use `full` because the loader returns just a
subset of the dataset in our use case.
I guess many people are in the same situation as us.
So, as one of the possible solutions for it, I would like to introduce a
new argument, `scoped_full_cleanup`.
This argument will be valid only when `claneup` is Full. If True, Full
cleanup deletes all documents that haven't been updated AND that are
associated with source ids that were seen during indexing. Default is
False.
This change keeps backward compatibility.
---------
Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Thank you for contributing to LangChain!
- [x] **PR title**: community: add TablestoreVectorStore
- [x] **PR message**:
- **Description:** add TablestoreVectorStore
- **Dependencies:** none
- [x] **Add tests and docs**: If you're adding a new integration, please
include
1. a test for the integration: yes
2. an example notebook showing its use: yes
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
This PR resolves the conflicting information in the Chat models
documentation regarding structured output support for ChatOllama.
- The Featured Providers table has been updated to reflect the correct
status.
- Structured output support for ChatOllama was introduced on Dec 6,
2024.
- A note has been added to ensure users update to the latest Ollama
version for structured outputs.
**Issue:** Fixes#28691
Description:
snowflake.py
Add _stream and _stream_content methods to enable streaming
functionality
fix pydantic issues and added functionality with the overall langchain
version upgrade
added bind_tools method for agentic workflows support through langgraph
updated the _generate method to account for agentic workflows support
through langgraph
cosmetic changes to comments and if conditions
snowflake.ipynb
Added _stream example
cosmetic changes to comments
fixed lint errors
check_pydantic.sh
Decreased counter from 126 to 125 as suggested when formatting
---------
Co-authored-by: Prathamesh Nimkar <prathamesh.nimkar@snowflake.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
- [ ] Main note
- **Description:** I added notes on the Jina and LocalAI pages telling
users that they must be using this integrations with openai sdk version
0.x, because if they dont they will get an error saying that "openai has
no attribute error". This PR was recommended by @efriis
- **Issue:** warns people about the issue in #28529
- **Dependencies:** None
- **Twitter handle:** JoaqCore
- [ ] **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.
**Description:**
- **Memgraph** no longer relies on `Neo4jGraphStore` but **implements
`GraphStore`**, just like other graph databases.
- **Memgraph** no longer relies on `GraphQAChain`, but implements
`MemgraphQAChain`, just like other graph databases.
- The refresh schema procedure has been updated to try using `SHOW
SCHEMA INFO`. The fallback uses Cypher queries (a combination of schema
and Cypher) → **LangChain integration no longer relies on MAGE
library**.
- The **schema structure** has been reformatted. Regardless of the
procedures used to get schema, schema structure is the same.
- The `add_graph_documents()` method has been implemented. It transforms
`GraphDocument` into Cypher queries and creates a graph in Memgraph. It
implements the ability to use `baseEntityLabel` to improve speed
(`baseEntityLabel` has an index on the `id` property). It also
implements the ability to include sources by creating a `MENTIONS`
relationship to the source document.
- Jupyter Notebook for Memgraph has been updated.
- **Issue:** /
- **Dependencies:** /
- **Twitter handle:** supe_katarina (DX Engineer @ Memgraph)
Closes#25606
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"
Docs on how to do hybrid search with weaviate is covered
[here](https://python.langchain.com/docs/integrations/vectorstores/weaviate/)
@efriis
---------
Co-authored-by: pookam90 <pookam@microsoft.com>
Co-authored-by: Pooja Kamath <60406274+Pookam90@users.noreply.github.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:** Adding Documentation for new SQL Server Vector Store
Package.
Changed files -
Added new Vector Store -
docs\docs\integrations\vectorstores\sqlserver.ipynb
FeatureTable.Js - docs\src\theme\FeatureTables.js
Microsoft.mdx - docs\docs\integrations\providers\microsoft.mdx
Detailed documentation on API -
https://python.langchain.com/api_reference/sqlserver/index.html
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
## Description
First of all, thanks for the great framework that is LangChain!
At [Linkup](https://www.linkup.so/) we're working on an API to connect
LLMs and agents to the internet and our partner sources. We'd be super
excited to see our API integrated in LangChain! This essentially
consists in adding a LangChain retriever and tool, which is done in our
own [package](https://pypi.org/project/langchain-linkup/). Here we're
simply following the [integration
documentation](https://python.langchain.com/docs/contributing/how_to/integrations/)
and update the documentation of LangChain to mention the Linkup
integration.
We do have tests (both units & integration) in our [source
code](https://github.com/LinkupPlatform/langchain-linkup), and tried to
follow as close as possible the [integration
documentation](https://python.langchain.com/docs/contributing/how_to/integrations/)
which specifically requests to focus on documentation changes for an
integration PR, so I'm not adding tests here, even though the PR
checklist seems to suggest so. Feel free to correct me if I got this
wrong!
By the way, we would be thrilled by being mentioned in the list of
providers which have standalone packages
[here](https://langchain-git-fork-linkupplatform-cj-doc-langchain.vercel.app/docs/integrations/providers/),
is there something in particular for us to do for that? 🙂
## Twitter handle
Linkup_platform
<!--
## PR Checklist
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!
- [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.
--!>
Thank you for contributing to LangChain!
- [ ] **PR message**:
- **Description:**: We have launched the new **Solar Pro** model, and
the documentation has been updated to include its details and features.
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 Langchain team!
I'm the co-founder and mantainer at
[ScrapeGraphAI](https://scrapegraphai.com/).
By following the integration
[guide](https://python.langchain.com/docs/contributing/how_to/integrations/publish/)
on your site, I have created a new lib called
[langchain-scrapegraph](https://github.com/ScrapeGraphAI/langchain-scrapegraph).
With this PR I would like to integrate Scrapegraph as provider in
Langchain, adding the required documentation files.
Let me know if there are some changes to be made to be properly
integrated both in the lib and in the documentation.
Thank you 🕷️🦜
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
