Add async mode for pgvector

[pprados]

This PR adds the async approach for pgvector.

Some remarks:

• We use assert to check invocations and not if. Thus, in production, it is possible to remove these checks with python -O ...
• We propose a public session_maker attribute. This is very important for resilient scenarios.

In a RAG architecture, it is necessary to import document chunks.

To keep track of the links between chunks and documents, we can use the index() API. This API proposes to use an SQL-type record manager.

In a classic use case, using SQLRecordManager and a vector database, it is impossible to guarantee the consistency of the import.

Indeed, if a crash occurs during the import, there is an inconsistency between the SQL database and the vector database.

PGVector is the solution to this problem.

Indeed, it is possible to use a single database (and not a two-phase commit with 2 technologies, if they are both compatible). But, for this, it is necessary to be able to combine the transactions between the use of SQLRecordManager and PGVector as a vector database.

This is only possible if it is possible to intervene on the session_maker.

This is why we propose to make this attribute public. By unifying the session_maker of SQLRecordManager and PGVector, it is possible to guarantee that all processes will be executed in a single transaction.

This is, moreover, the only solution we know of to guarantee the consistency of the import of chunks into a vector database. It's possible only if the outer session is built with the connection.

def main():
    db_url = "postgresql+psycopg://postgres:password_postgres@localhost:5432/"
    engine = create_engine(db_url, echo=True)
    embeddings = FakeEmbeddings()
    pgvector:VectorStore = PGVector(
        embeddings=embeddings,
        connection=engine,
    )

    record_manager = SQLRecordManager(
        namespace="namespace",
        engine=engine,
    )
    record_manager.create_schema()

    with engine.connect() as connection:
        session_maker = scoped_session(sessionmaker(bind=connection))
        # NOTE: Update session_factories
        record_manager.session_factory = session_maker
        pgvector.session_maker = session_maker
        with connection.begin():
            loader = CSVLoader(
                    "data/faq/faq.csv",
                    source_column="source",
                    autodetect_encoding=True,
                )
            result = index(
                source_id_key="source",
                docs_source=loader.load()[:1],
                cleanup="incremental",
                vector_store=pgvector,
                record_manager=record_manager,
            )
            print(result)

The same thing is possible asynchronously, but a bug in sql_record_manager.py in _amake_session() must first be fixed (See PR ).

    async def _amake_session(self) -> AsyncGenerator[AsyncSession, None]:
        """Create a session and close it after use."""

        # FIXME: REMOVE if not isinstance(self.session_factory, async_sessionmaker):~~
        if not isinstance(self.engine, AsyncEngine):
            raise AssertionError("This method is not supported for sync engines.")

        async with self.session_factory() as session:
            yield session

Then, it is possible to do the same thing asynchronously:

async def main():
    db_url = "postgresql+psycopg://postgres:password_postgres@localhost:5432/"
    engine = create_async_engine(db_url, echo=True)
    embeddings = FakeEmbeddings()
    pgvector:VectorStore = PGVector(
        embeddings=embeddings,
        connection=engine,
    )
    record_manager = SQLRecordManager(
        namespace="namespace",
        engine=engine,
        async_mode=True,
    )
    await record_manager.acreate_schema()

    async with engine.connect() as connection:
        session_maker = async_scoped_session(
            async_sessionmaker(bind=connection),
            scopefunc=current_task)
        record_manager.session_factory = session_maker
        pgvector.session_maker = session_maker
        async with connection.begin():
            loader = CSVLoader(
                "data/faq/faq.csv",
                source_column="source",
                autodetect_encoding=True,
            )
            result = await aindex(
                source_id_key="source",
                docs_source=loader.load()[:1],
                cleanup="incremental",
                vector_store=pgvector,
                record_manager=record_manager,
            )
            print(result)


asyncio.run(main())