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9 Commits

Author SHA1 Message Date
Philippe PRADOS
9aabb446c5
community[minor]: Add SQL storage implementation (#22207) 
Hello @eyurtsev

- package: langchain-comminity
- **Description**: Add SQL implementation for docstore. A new
implementation, in line with my other PR ([async
PGVector](https://github.com/langchain-ai/langchain-postgres/pull/32),
[SQLChatMessageMemory](https://github.com/langchain-ai/langchain/pull/22065))
- Twitter handler: pprados

---------

Signed-off-by: ChengZi <chen.zhang@zilliz.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Piotr Mardziel <piotrm@gmail.com>
Co-authored-by: ChengZi <chen.zhang@zilliz.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
 2024-06-07 21:17:02 +00:00
Christophe Bornet
74947ec894
community[minor]: Add Cassandra ByteStore (#22064) 2024-05-23 10:46:23 -04:00
Christophe Bornet
e92e96193f
community[minor]: Add async methods to the AstraDB BaseStore (#16872) 
---------

Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
 2024-02-19 10:11:49 -08:00
Qihui Xie
5738143d4b
add mongodb_store (#13801) 
# Add MongoDB storage
  - **Description:** 
  Add MongoDB Storage as an option for large doc store. 

Example usage: 
```Python
# Instantiate the MongodbStore with a MongoDB connection
from langchain.storage import MongodbStore

mongo_conn_str = "mongodb://localhost:27017/"
mongodb_store = MongodbStore(mongo_conn_str, db_name="test-db",
                                collection_name="test-collection")

# Set values for keys
doc1 = Document(page_content='test1')
doc2 = Document(page_content='test2')
mongodb_store.mset([("key1", doc1), ("key2", doc2)])

# Get values for keys
values = mongodb_store.mget(["key1", "key2"])
# [doc1, doc2]

# Iterate over keys
for key in mongodb_store.yield_keys():
    print(key)

# Delete keys
mongodb_store.mdelete(["key1", "key2"])
 ```

  - **Dependencies:**
  Use `mongomock` for integration test.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
 2024-02-13 22:33:22 -05:00
Harrison Chase
4eda647fdd
infra: add -p to mkdir in lint steps (#17013) 
Previously, if this did not find a mypy cache then it wouldnt run

this makes it always run

adding mypy ignore comments with existing uncaught issues to unblock other prs

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
 2024-02-05 11:22:06 -08:00
Erick Friis
b1a847366c
community: revert SQL Stores (#16912) 
This reverts commit cfc225ecb3.


https://github.com/langchain-ai/langchain/pull/15909#issuecomment-1922418097

These will have existed in langchain-community 0.0.16 and 0.0.17.
 2024-02-01 16:37:40 -08:00
gcheron
cfc225ecb3
community: SQLStrStore/SQLDocStore provide an easy SQL alternative to InMemoryStore to persist data remotely in a SQL storage (#15909) 
**Description:**

- Implement `SQLStrStore` and `SQLDocStore` classes that inherits from
`BaseStore` to allow to persist data remotely on a SQL server.
- SQL is widely used and sometimes we do not want to install a caching
solution like Redis.
- Multiple issues/comments complain that there is no easy remote and
persistent solution that are not in memory (users want to replace
InMemoryStore), e.g.,
https://github.com/langchain-ai/langchain/issues/14267,
https://github.com/langchain-ai/langchain/issues/15633,
https://github.com/langchain-ai/langchain/issues/14643,
https://stackoverflow.com/questions/77385587/persist-parentdocumentretriever-of-langchain
- This is particularly painful when wanting to use
`ParentDocumentRetriever `
- This implementation is particularly useful when:
     * it's expensive to construct an InMemoryDocstore/dict
     * you want to retrieve documents from remote sources
     * you just want to reuse existing objects
- This implementation integrates well with PGVector, indeed, when using
PGVector, you already have a SQL instance running. `SQLDocStore` is a
convenient way of using this instance to store documents associated to
vectors. An integration example with ParentDocumentRetriever and
PGVector is provided in docs/docs/integrations/stores/sql.ipynb or
[here](https://github.com/gcheron/langchain/blob/sql-store/docs/docs/integrations/stores/sql.ipynb).
- It persists `str` and `Document` objects but can be easily extended.

 **Issue:**

Provide an easy SQL alternative to `InMemoryStore`.

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
 2024-01-23 16:50:48 -08:00
Christophe Bornet
81d1ba05dc
Add a BaseStore backed by AstraDB (#15812) 
- **Description:** this change adds a `BaseStore` backed by AstraDB
  - **Twitter handle:** cbornet_
 2024-01-11 21:41:24 -08:00
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
 2023-12-11 13:53:30 -08:00