4f4b020582
# Astra DB Vector store integration - **Description:** This PR adds a `VectorStore` implementation for DataStax Astra DB using its HTTP API - **Issue:** (no related issue) - **Dependencies:** A new required dependency is `astrapy` (`>=0.5.3`) which was added to pyptoject.toml, optional, as per guidelines - **Tag maintainer:** I recently mentioned to @baskaryan this integration was coming - **Twitter handle:** `@rsprrs` if you want to mention me This PR introduces the `AstraDB` vector store class, extensive integration test coverage, a reworking of the documentation which conflates Cassandra and Astra DB on a single "provider" page and a new, completely reworked vector-store example notebook (common to the Cassandra store, since parts of the flow is shared by the two APIs). I also took care in ensuring docs (and redirects therein) are behaving correctly. All style, linting, typechecks and tests pass as far as the `AstraDB` integration is concerned. I could build the documentation and check it all right (but ran into trouble with the `api_docs_build` makefile target which I could not verify: `Error: Unable to import module 'plan_and_execute.agent_executor' with error: No module named 'langchain_experimental'` was the first of many similar errors) Thank you for a review! Stefano --------- Co-authored-by: Erick Friis <erick@langchain.dev>
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rag-astradb
This template will perform RAG using Astra DB (AstraDB vector store class)
Environment Setup
An Astra DB database is required; free tier is fine.
- You need the database API endpoint (such as
https://0123...-us-east1.apps.astra.datastax.com) ... - ... and a token (
AstraCS:...).
Also, an OpenAI API Key is required. Note that out-of-the-box this demo supports OpenAI only, unless you tinker with the code.
Provide the connection parameters and secrets through environment variables. Please refer to .env.template for the variable names.
Usage
To use this package, you should first have the LangChain CLI installed:
pip install -U "langchain-cli[serve]"
To create a new LangChain project and install this as the only package, you can do:
langchain app new my-app --package rag-astradb
If you want to add this to an existing project, you can just run:
langchain app add rag-astradb
And add the following code to your server.py file:
from astradb_entomology_rag import chain as astradb_entomology_rag_chain
add_routes(app, astradb_entomology_rag_chain, path="/rag-astradb")
(Optional) Let's now configure LangSmith. LangSmith will help us trace, monitor and debug LangChain applications. LangSmith is currently in private beta, you can sign up here. If you don't have access, you can skip this section
export LANGCHAIN_TRACING_V2=true
export LANGCHAIN_API_KEY=<your-api-key>
export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
If you are inside this directory, then you can spin up a LangServe instance directly by:
langchain serve
This will start the FastAPI app with a server is running locally at http://localhost:8000
We can see all templates at http://127.0.0.1:8000/docs We can access the playground at http://127.0.0.1:8000/rag-astradb/playground
We can access the template from code with:
from langserve.client import RemoteRunnable
runnable = RemoteRunnable("http://localhost:8000/rag-astradb")
Reference
Stand-alone repo with LangServe chain: here.