Commit Graph

34 Commits (a4bcb45f659d29e4c4ce715f70813413db9bad03)

Author SHA1 Message Date
Aayush Kataria 71811e0547
community[minor]: Adds a vector store for Azure Cosmos DB for NoSQL (#21676)
This PR add supports for Azure Cosmos DB for NoSQL vector store.

Summary:

Description: added vector store integration for Azure Cosmos DB for
NoSQL Vector Store,
Dependencies: azure-cosmos dependency,
Tag maintainer: @hwchase17, @baskaryan @efriis @eyurtsev

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
4 weeks ago
Pavlo Paliychuk 342df7cf83
community[minor]: Add Zep Cloud components + docs + examples (#21671)
Thank you for contributing to LangChain!

- [x] **PR title**: community: Add Zep Cloud components + docs +
examples

- [x] **PR message**: 
We have recently released our new zep-cloud sdks that are compatible
with Zep Cloud (not Zep Open Source). We have also maintained our Cloud
version of langchain components (ChatMessageHistory, VectorStore) as
part of our sdks. This PRs goal is to port these components to langchain
community repo, and close the gap with the existing Zep Open Source
components already present in community repo (added
ZepCloudMemory,ZepCloudVectorStore,ZepCloudRetriever).
Also added a ZepCloudChatMessageHistory components together with an
expression language example ported from our repo. We have left the
original open source components intact on purpose as to not introduce
any breaking changes.
    - **Issue:** -
- **Dependencies:** Added optional dependency of our new cloud sdk
`zep-cloud`
    - **Twitter handle:** @paulpaliychuk51


- [x] **Add tests and docs**


- [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, hwchase17.
1 month ago
Pavel Zloi fe26f937e4
community[minor]: ManticoreSearch engine added to vectorstore (#19117)
**Description:** ManticoreSearch engine added to vectorstores
**Issue:** no issue, just a new feature
**Dependencies:** https://pypi.org/project/manticoresearch-dev/
**Twitter handle:** @EvilFreelancer

- Example notebook with test integration:

https://github.com/EvilFreelancer/langchain/blob/manticore-search-vectorstore/docs/docs/integrations/vectorstores/manticore_search.ipynb

---------

Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
1 month ago
Bagatur 50186da0a1
infra: rm unused # noqa violations (#22049)
Updating #21137
1 month ago
Eugene Yurtsev 36813d2f00
community[patch]: Fix remaining __inits__ in community (#22037)
Fixes the __init__ files in community to use __all__ which is statically
defined.
2 months ago
Jesse S fc79b372cb
community[minor]: add aerospike vectorstore integration (#21735)
Please let me know if you see any possible areas of improvement. I would
very much appreciate your constructive criticism if time allows.

**Description:**
- Added a aerospike vector store integration that utilizes
[Aerospike-Vector-Search](https://aerospike.com/products/vector-database-search-llm/)
add-on.
- Added both unit tests and integration tests
- Added a docker compose file for spinning up a test environment
- Added a notebook

 **Dependencies:** any dependencies required for this change
- aerospike-vector-search

 **Twitter handle:** 
- No twitter, you can use my GitHub handle or LinkedIn if you'd like

Thanks!

---------

Co-authored-by: Jesse Schumacher <jschumacher@aerospike.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2 months ago
Yash cb31c3611f
Ndb enterprise (#21233)
Description: Adds NeuralDBClientVectorStore to the langchain, which is
our enterprise client.

---------

Co-authored-by: kartikTAI <129414343+kartikTAI@users.noreply.github.com>
Co-authored-by: Kartik Sarangmath <kartik@thirdai.com>
2 months ago
Rohan Aggarwal 8021d2a2ab
community[minor]: Oraclevs integration (#21123)
Thank you for contributing to LangChain!

- Oracle AI Vector Search 
Oracle AI Vector Search is designed for Artificial Intelligence (AI)
workloads that allows you to query data based on semantics, rather than
keywords. One of the biggest benefit of Oracle AI Vector Search is that
semantic search on unstructured data can be combined with relational
search on business data in one single system. This is not only powerful
but also significantly more effective because you don't need to add a
specialized vector database, eliminating the pain of data fragmentation
between multiple systems.


- Oracle AI Vector Search is designed for Artificial Intelligence (AI)
workloads that allows you to query data based on semantics, rather than
keywords. One of the biggest benefit of Oracle AI Vector Search is that
semantic search on unstructured data can be combined with relational
search on business data in one single system. This is not only powerful
but also significantly more effective because you don't need to add a
specialized vector database, eliminating the pain of data fragmentation
between multiple systems.
This Pull Requests Adds the following functionalities
Oracle AI Vector Search : Vector Store
Oracle AI Vector Search : Document Loader
Oracle AI Vector Search : Document Splitter
Oracle AI Vector Search : Summary
Oracle AI Vector Search : Oracle Embeddings


- We have added unit tests and have our own local unit test suite which
verifies all the code is correct. We have made sure to add guides for
each of the components and one end to end guide that shows how the
entire thing runs.


- We have made sure that make format and make lint run clean.

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, hwchase17.

---------

Co-authored-by: skmishraoracle <shailendra.mishra@oracle.com>
Co-authored-by: hroyofc <harichandan.roy@oracle.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2 months ago
Ismail Hossain Polas 1fdf63fa6c
community[patch]: update package name to bagelML (#19948)
**Description**
This pull request updates the Bagel Network package name from
"betabageldb" to "bagelML" to align with the latest changes made by the
Bagel Network team.

The following modifications have been made:

- Updated all references to the old package name ("betabageldb") with
the new package name ("bagelML") throughout the codebase.
- Modified the documentation, and any relevant scripts to reflect the
package name change.
- Tested the changes to ensure that the functionality remains intact and
no breaking changes were introduced.

By merging this pull request, our project will stay up to date with the
latest Bagel Network package naming convention, ensuring compatibility
and smooth integration with their updated library.

Please review the changes and provide any feedback or suggestions. Thank
you!
2 months ago
Charlie Marsh 8f38b7a725
multiple: Remove unnecessary Ruff suppression comments (#21050)
## Summary

I ran `ruff check --extend-select RUF100 -n` to identify `# noqa`
comments that weren't having any effect in Ruff, and then `ruff check
--extend-select RUF100 -n --fix` on select files to remove all of the
unnecessary `# noqa: F401` violations. It's possible that these were
needed at some point in the past, but they're not necessary in Ruff
v0.1.15 (used by LangChain) or in the latest release.

Co-authored-by: Erick Friis <erick@langchain.dev>
2 months ago
Cahid Arda Öz cc6191cb90
community[minor]: Add support for Upstash Vector (#20824)
## Description

Adding `UpstashVectorStore` to utilize [Upstash
Vector](https://upstash.com/docs/vector/overall/getstarted)!

#17012 was opened to add Upstash Vector to langchain but was closed to
wait for filtering. Now filtering is added to Upstash vector and we open
a new PR. Additionally, [embedding
feature](https://upstash.com/docs/vector/features/embeddingmodels) was
added and we add this to our vectorstore aswell.

## Dependencies

[upstash-vector](https://pypi.org/project/upstash-vector/) should be
installed to use `UpstashVectorStore`. Didn't update dependencies
because of [this comment in the previous
PR](https://github.com/langchain-ai/langchain/pull/17012#pullrequestreview-1876522450).

## Tests

Tests are added and they pass. Tests are naturally network bound since
Upstash Vector is offered through an API.

There was [a discussion in the previous PR about mocking the
unittests](https://github.com/langchain-ai/langchain/pull/17012#pullrequestreview-1891820567).
We didn't make changes to this end yet. We can update the tests if you
can explain how the tests should be mocked.

---------

Co-authored-by: ytkimirti <yusuftaha9@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2 months ago
Jingpan Xiong 1202017c56
community[minor]: Add relyt vector database (#20316)
Co-authored-by: kaka <kaka@zbyte-inc.cloud>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: jingsi <jingsi@leadincloud.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
2 months ago
sdan a7c5e41443
community[minor]: Added VLite as VectorStore (#20245)
Support [VLite](https://github.com/sdan/vlite) as a new VectorStore
type.

**Description**:
vlite is a simple and blazing fast vector database(vdb) made with numpy.
It abstracts a lot of the functionality around using a vdb in the
retrieval augmented generation(RAG) pipeline such as embeddings
generation, chunking, and file processing while still giving developers
the functionality to change how they're made/stored.

**Before submitting**:
Added tests
[here](c09c2ebd5c/libs/community/tests/integration_tests/vectorstores/test_vlite.py)
Added ipython notebook
[here](c09c2ebd5c/docs/docs/integrations/vectorstores/vlite.ipynb)
Added simple docs on how to use
[here](c09c2ebd5c/docs/docs/integrations/providers/vlite.mdx)

**Profiles**

Maintainers: @sdan
Twitter handles: [@sdand](https://x.com/sdand)

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
3 months ago
Leonid Ganeline 4cb5f4c353
community[patch]: import flattening fix (#20110)
This PR should make it easier for linters to do type checking and for IDEs to jump to definition of code.

See #20050 as a template for this PR.
- As a byproduct: Added 3 missed `test_imports`.
- Added missed `SolarChat` in to __init___.py Added it into test_import
ut.
- Added `# type: ignore` to fix linting. It is not clear, why linting
errors appear after ^ changes.

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
3 months ago
Jan Chorowski b8b42ccbc5
community[minor]: Pathway vectorstore(#14859)
- **Description:** Integration with pathway.com data processing pipeline
acting as an always updated vectorstore
  - **Issue:** not applicable
- **Dependencies:** optional dependency on
[`pathway`](https://pypi.org/project/pathway/)
  - **Twitter handle:** pathway_com

The PR provides and integration with `pathway` to provide an easy to use
always updated vector store:

```python
import pathway as pw
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import CharacterTextSplitter
from langchain.vectorstores import PathwayVectorClient, PathwayVectorServer

data_sources = []
data_sources.append(
    pw.io.gdrive.read(object_id="17H4YpBOAKQzEJ93xmC2z170l0bP2npMy", service_user_credentials_file="credentials.json", with_metadata=True))

text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
embeddings_model = OpenAIEmbeddings(openai_api_key=os.environ["OPENAI_API_KEY"])
vector_server = PathwayVectorServer(
    *data_sources,
    embedder=embeddings_model,
    splitter=text_splitter,
)
vector_server.run_server(host="127.0.0.1", port="8765", threaded=True, with_cache=False)
client = PathwayVectorClient(
    host="127.0.0.1",
    port="8765",
)
query = "What is Pathway?"
docs = client.similarity_search(query)
```

The `PathwayVectorServer` builds a data processing pipeline which
continusly scans documents in a given source connector (google drive,
s3, ...) and builds a vector store. The `PathwayVectorClient` implements
LangChain's `VectorStore` interface and connects to the server to
retrieve documents.

---------

Co-authored-by: Mateusz Lewandowski <lewymati@users.noreply.github.com>
Co-authored-by: mlewandowski <mlewandowski@MacBook-Pro-mlewandowski.local>
Co-authored-by: Berke <berkecanrizai1@gmail.com>
Co-authored-by: Adrian Kosowski <adrian@pathway.com>
Co-authored-by: mlewandowski <mlewandowski@macbook-pro-mlewandowski.home>
Co-authored-by: berkecanrizai <63911408+berkecanrizai@users.noreply.github.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: mlewandowski <mlewandowski@MBPmlewandowski.ht.home>
Co-authored-by: Szymon Dudycz <szymond@pathway.com>
Co-authored-by: Szymon Dudycz <szymon.dudycz@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
3 months ago
Chaunte W. Lacewell a31f692f4e
community[minor]: Add VDMS vectorstore (#19551)
- **Description:** Add support for Intel Lab's [Visual Data Management
System (VDMS)](https://github.com/IntelLabs/vdms) as a vector store
- **Dependencies:** `vdms` library which requires protobuf = "4.24.2".
There is a conflict with dashvector in `langchain` package but conflict
is resolved in `community`.
- **Contribution maintainer:** [@cwlacewe](https://github.com/cwlacewe)
- **Added tests:**
libs/community/tests/integration_tests/vectorstores/test_vdms.py
- **Added docs:** docs/docs/integrations/vectorstores/vdms.ipynb
- **Added cookbook:** cookbook/multi_modal_RAG_vdms.ipynb

---------

Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
3 months ago
yongheng.liu 7e29b6061f
community[minor]: integrate China Mobile Ecloud vector search (#15298)
- **Description:** integrate China Mobile Ecloud vector search, 
  - **Dependencies:** elasticsearch==7.10.1

Co-authored-by: liuyongheng <liuyongheng@cmss.chinamobile.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
3 months ago
Christophe Bornet 8595c3ab59
community[minor]: Add InMemoryVectorStore to module level imports (#19576) 3 months ago
Hugoberry 96dc180883
community[minor]: Add `DuckDB` as a vectorstore (#18916)
DuckDB has a cosine similarity function along list and array data types,
which can be used as a vector store.
- **Description:** The latest version of DuckDB features a cosine
similarity function, which can be used with its support for list or
array column types. This PR surfaces this functionality to langchain.
    - **Dependencies:** duckdb 0.10.0
    - **Twitter handle:** @igocrite

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
3 months ago
Nithish Raghunandanan 7ad0a3f2a7
community: add Couchbase Vector Store (#18994)
- **Description:** Added support for Couchbase Vector Search to
LangChain.
- **Dependencies:** couchbase>=4.1.12
- **Twitter handle:** @nithishr

---------

Co-authored-by: Nithish Raghunandanan <nithishr@users.noreply.github.com>
4 months ago
fengjial c922ea36cb
community[minor]: Add Baidu VectorDB as vector store (#17997)
Co-authored-by: fengjialin <fengjialin@MacBook-Pro.local>
4 months ago
Leonid Ganeline 9c8523b529
community[patch]: flattening imports 3 (#18939)
@eyurtsev
4 months ago
Ian 390ef6abe3
community[minor]: Add Initial Support for TiDB Vector Store (#15796)
This pull request introduces initial support for the TiDB vector store.
The current version is basic, laying the foundation for the vector store
integration. While this implementation provides the essential features,
we plan to expand and improve the TiDB vector store support with
additional enhancements in future updates.

Upcoming Enhancements:
* Support for Vector Index Creation: To enhance the efficiency and
performance of the vector store.
* Support for max marginal relevance search. 
* Customized Table Structure Support: Recognizing the need for
flexibility, we plan for more tailored and efficient data store
solutions.

Simple use case exmaple

```python
from typing import List, Tuple
from langchain.docstore.document import Document
from langchain_community.vectorstores import TiDBVectorStore
from langchain_openai import OpenAIEmbeddings

db = TiDBVectorStore.from_texts(
    embedding=embeddings,
    texts=['Andrew like eating oranges', 'Alexandra is from England', 'Ketanji Brown Jackson is a judge'],
    table_name="tidb_vector_langchain",
    connection_string=tidb_connection_url,
    distance_strategy="cosine",
)

query = "Can you tell me about Alexandra?"
docs_with_score: List[Tuple[Document, float]] = db.similarity_search_with_score(query)
for doc, score in docs_with_score:
    print("-" * 80)
    print("Score: ", score)
    print(doc.page_content)
    print("-" * 80)
```
4 months ago
Sam Khano 1b4dcf22f3
community[minor]: Add DocumentDBVectorSearch VectorStore (#17757)
**Description:**
- Added Amazon DocumentDB Vector Search integration (HNSW index)
- Added integration tests
- Updated AWS documentation with DocumentDB Vector Search instructions
- Added notebook for DocumentDB integration with example usage

---------

Co-authored-by: EC2 Default User <ec2-user@ip-172-31-95-226.ec2.internal>
4 months ago
Vittorio Rigamonti 51f3902bc4
community[minor]: Adding support for Infinispan as VectorStore (#17861)
**Description:**
This integrates Infinispan as a vectorstore.
Infinispan is an open-source key-value data grid, it can work as single
node as well as distributed.

Vector search is supported since release 15.x 

For more: [Infinispan Home](https://infinispan.org)

Integration tests are provided as well as a demo notebook
4 months ago
am-kinetica 9b8f6455b1
Langchain vectorstore integration with Kinetica (#18102)
- **Description:** New vectorstore integration with the Kinetica
database
  - **Issue:** 
- **Dependencies:** the Kinetica Python API `pip install
gpudb==7.2.0.1`,
  - **Tag maintainer:** @baskaryan, @hwchase17 
  - **Twitter handle:**

---------

Co-authored-by: Chad Juliano <cjuliano@kinetica.com>
4 months ago
Guangdong Liu 73edf17b4e
community[minor]: Add Apache Doris as vector store (#17527)
---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
5 months ago
Benito Geordie f3fdc5c5da
community: Added integrations for ThirdAI's NeuralDB with Retriever and VectorStore frameworks (#15280)
**Description:** Adds ThirdAI NeuralDB retriever and vectorstore
integration. NeuralDB is a CPU-friendly and fine-tunable text retrieval
engine.
5 months ago
Martin Kolb 04651f0248
community[minor]: VectorStore integration for SAP HANA Cloud Vector Engine (#16514)
- **Description:**
This PR adds a VectorStore integration for SAP HANA Cloud Vector Engine,
which is an upcoming feature in the SAP HANA Cloud database
(https://blogs.sap.com/2023/11/02/sap-hana-clouds-vector-engine-announcement/).

  - **Issue:** N/A
- **Dependencies:** [SAP HANA Python
Client](https://pypi.org/project/hdbcli/)
  - **Twitter handle:** @sapopensource

Implementation of the integration:
`libs/community/langchain_community/vectorstores/hanavector.py`

Unit tests:
`libs/community/tests/unit_tests/vectorstores/test_hanavector.py`

Integration tests:
`libs/community/tests/integration_tests/vectorstores/test_hanavector.py`

Example notebook:
`docs/docs/integrations/vectorstores/hanavector.ipynb`

Access credentials for execution of the integration tests can be
provided to the maintainers.

---------

Co-authored-by: sascha <sascha.stoll@sap.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
5 months ago
bu2kx ff3163297b
community[minor]: Add KDBAI vector store (#12797)
Addition of KDBAI vector store (https://kdb.ai).

Dependencies: `kdbai_client` v0.1.2 Python package.

Sample notebook: `docs/docs/integrations/vectorstores/kdbai.ipynb`

Tag maintainer: @bu2kx
Twitter handle: @kxsystems
5 months ago
Varik Matevosyan efe6cfafe2
community: Added Lantern as VectorStore (#12951)
Support [Lantern](https://github.com/lanterndata/lantern) as a new
VectorStore type.

- Added Lantern as VectorStore.
It will support 3 distance functions `l2 squared`, `cosine` and
`hamming` and will use `HNSW` index.
- Added tests
- Added example notebook
6 months ago
Ashley Xu 0ce7858529
feat: add Google BigQueryVectorSearch in vectorstore (#14829)
BigQuery vector search lets you use GoogleSQL to do semantic search,
using vector indexes for fast but approximate results, or using brute
force for exact results.

This PR integrates LangChain vectorstore with BigQuery Vector Search.

<!-- Thank you for contributing to LangChain!

Replace this entire comment with:
  - **Description:** a description of the change, 
  - **Issue:** the issue # it fixes (if applicable),
  - **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!

Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.

See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://python.langchain.com/docs/contributing/

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/extras`
directory.

If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
 -->

---------

Co-authored-by: Vlad Kolesnikov <vladkol@google.com>
6 months ago
Karim Lalani a0064330b1
community[minor]: Add SurrealDB vectorstore (#13331)
**Description:** Vectorstore implementation around
[SurrealDB](https://www.surrealdb.com)

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Bagatur ed58eeb9c5
community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463)
Moved the following modules to new package langchain-community in a backwards compatible fashion:

```
mv langchain/langchain/adapters community/langchain_community
mv langchain/langchain/callbacks community/langchain_community/callbacks
mv langchain/langchain/chat_loaders community/langchain_community
mv langchain/langchain/chat_models community/langchain_community
mv langchain/langchain/document_loaders community/langchain_community
mv langchain/langchain/docstore community/langchain_community
mv langchain/langchain/document_transformers community/langchain_community
mv langchain/langchain/embeddings community/langchain_community
mv langchain/langchain/graphs community/langchain_community
mv langchain/langchain/llms community/langchain_community
mv langchain/langchain/memory/chat_message_histories community/langchain_community
mv langchain/langchain/retrievers community/langchain_community
mv langchain/langchain/storage community/langchain_community
mv langchain/langchain/tools community/langchain_community
mv langchain/langchain/utilities community/langchain_community
mv langchain/langchain/vectorstores community/langchain_community
mv langchain/langchain/agents/agent_toolkits community/langchain_community
mv langchain/langchain/cache.py community/langchain_community
mv langchain/langchain/adapters community/langchain_community
mv langchain/langchain/callbacks community/langchain_community/callbacks
mv langchain/langchain/chat_loaders community/langchain_community
mv langchain/langchain/chat_models community/langchain_community
mv langchain/langchain/document_loaders community/langchain_community
mv langchain/langchain/docstore community/langchain_community
mv langchain/langchain/document_transformers community/langchain_community
mv langchain/langchain/embeddings community/langchain_community
mv langchain/langchain/graphs community/langchain_community
mv langchain/langchain/llms community/langchain_community
mv langchain/langchain/memory/chat_message_histories community/langchain_community
mv langchain/langchain/retrievers community/langchain_community
mv langchain/langchain/storage community/langchain_community
mv langchain/langchain/tools community/langchain_community
mv langchain/langchain/utilities community/langchain_community
mv langchain/langchain/vectorstores community/langchain_community
mv langchain/langchain/agents/agent_toolkits community/langchain_community
mv langchain/langchain/cache.py community/langchain_community
```

Moved the following to core
```
mv langchain/langchain/utils/json_schema.py core/langchain_core/utils
mv langchain/langchain/utils/html.py core/langchain_core/utils
mv langchain/langchain/utils/strings.py core/langchain_core/utils
cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py
rm langchain/langchain/utils/env.py
```

See .scripts/community_split/script_integrations.sh for all changes
7 months ago