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# 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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| cassandra_synonym_caching | ||
| .env.template | ||
| poetry.lock | ||
| pyproject.toml | ||
| README.md | ||
cassandra-synonym-caching
This template provides a simple chain template showcasing the usage of LLM Caching backed by Apache Cassandra® or Astra DB through CQL.
Environment Setup
To set up your environment, you will need the following:
- an Astra Vector Database (free tier is fine!). You need a Database Administrator token, in particular the string starting with
AstraCS:...; - likewise, get your Database ID ready, you will have to enter it below;
- an OpenAI API Key. (More info here, note that out-of-the-box this demo supports OpenAI unless you tinker with the code.)
Note: you can alternatively use a regular Cassandra cluster: to do so, make sure you provide the USE_CASSANDRA_CLUSTER entry as shown in .env.template and the subsequent environment variables to specify how to connect to it.
Usage
To use this package, you should first have the LangChain CLI installed:
pip install -U langchain-cli
To create a new LangChain project and install this as the only package, you can do:
langchain app new my-app --package cassandra-synonym-caching
If you want to add this to an existing project, you can just run:
langchain app add cassandra-synonym-caching
And add the following code to your server.py file:
from cassandra_synonym_caching import chain as cassandra_synonym_caching_chain
add_routes(app, cassandra_synonym_caching_chain, path="/cassandra-synonym-caching")
(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/cassandra-synonym-caching/playground
We can access the template from code with:
from langserve.client import RemoteRunnable
runnable = RemoteRunnable("http://localhost:8000/cassandra-synonym-caching")
Reference
Stand-alone LangServe template repo: here.