core[minor]: Adds an in-memory implementation of RecordManager #13200
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- [Add a Wrapper vectorstore, compatible with SelfQueryRetriever](langchain-ai/langchain#13190) - [Adds an in-memory implementation of RecordStore](langchain-ai/langchain#13200) - [Add SQLDocStore](langchain-ai/langchain#13181)
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No. All is async, because all method works in memories. Without IO. |
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libs/community/langchain_community/indexes/memory_recordmanager.py
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@eyurtsev with |
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@eyurtsev It has nothing to do with my patch |
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@pprados please review I reused the existing implementation of the in memory record manager from unit tests.
It's moved to base.py together with the abstract interface. We can move it into a separate module as well (doesn't really matter), we just need it to be a non private module for it to appear in the API Reference documentation. The typical name for memory implementations is "InMemory" |
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…22065) # package community: Fix SQLChatMessageHistory ## Description Here is a rewrite of `SQLChatMessageHistory` to properly implement the asynchronous approach. The code circumvents [issue 22021](#22021) by accepting a synchronous call to `def add_messages()` in an asynchronous scenario. This bypasses the bug. For the same reasons as in [PR 22](langchain-ai/langchain-postgres#32) of `langchain-postgres`, we use a lazy strategy for table creation. Indeed, the promise of the constructor cannot be fulfilled without this. It is not possible to invoke a synchronous call in a constructor. We compensate for this by waiting for the next asynchronous method call to create the table. The goal of the `PostgresChatMessageHistory` class (in `langchain-postgres`) is, among other things, to be able to recycle database connections. The implementation of the class is problematic, as we have demonstrated in [issue 22021](#22021). Our new implementation of `SQLChatMessageHistory` achieves this by using a singleton of type (`Async`)`Engine` for the database connection. The connection pool is managed by this singleton, and the code is then reentrant. We also accept the type `str` (optionally complemented by `async_mode`. I know you don't like this much, but it's the only way to allow an asynchronous connection string). In order to unify the different classes handling database connections, we have renamed `connection_string` to `connection`, and `Session` to `session_maker`. Now, a single transaction is used to add a list of messages. Thus, a crash during this write operation will not leave the database in an unstable state with a partially added message list. This makes the code resilient. We believe that the `PostgresChatMessageHistory` class is no longer necessary and can be replaced by: ``` PostgresChatMessageHistory = SQLChatMessageHistory ``` This also fixes the bug. ## Issue - [issue 22021](#22021) - Bug in _exit_history() - Bugs in PostgresChatMessageHistory and sync usage - Bugs in PostgresChatMessageHistory and async usage - [issue 36](langchain-ai/langchain-postgres#36) ## Twitter handle: pprados ## Tests - libs/community/tests/unit_tests/chat_message_histories/test_sql.py (add async test) @baskaryan, @eyurtsev or @hwchase17 can you check this PR ? And, I've been waiting a long time for validation from other PRs. Can you take a look? - [PR 32](langchain-ai/langchain-postgres#32) - [PR 15575](#15575) - [PR 13200](#13200) --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
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**Description:** langchain offers three technologies to save data: - [vectorstore](https://python.langchain.com/docs/modules/data_connection/vectorstores/) - [docstore](https://js.langchain.com/docs/api/schema/classes/Docstore) - [record manager](https://python.langchain.com/docs/modules/data_connection/indexing) If you want to combine these technologies in a sample persistence stategy you need a common implementation for each. `DocStore` propose `InMemoryDocstore`. We propose the class `MemoryRecordManager` to complete the system. This is the prelude to another full-request, which needs a consistent combination of persistence components. **Tag maintainer:** @baskaryan **Twitter handle:** @pprados --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
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Description:
langchain offers three technologies to save data:
If you want to combine these technologies in a sample persistence stategy you need a common implementation for each.
DocStoreproposeInMemoryDocstore.We propose the class
MemoryRecordManagerto complete the system.This is the prelude to another full-request, which needs a consistent combination of persistence components.
Tag maintainer:
@baskaryan
Twitter handle:
@pprados