This template uses a csv agent with tools (Python REPL) and memory (vectorstore) for interaction (question-answering) with text data.
OPENAI_API_KEY environment variable to access the OpenAI models.
To set up the environment, the
ingest.py script should be run to handle the ingestion into a vectorstore.
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 csv-agent
If you want to add this to an existing project, you can just run:
langchain app add csv-agent
And add the following code to your
from csv_agent.agent import agent_executor as csv_agent_chain
add_routes(app, csv_agent_chain, path="/csv-agent")
(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_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:
This will start the FastAPI app with a server is running locally at http://localhost:8000
We can access the template from code with:
from langserve.client import RemoteRunnable
runnable = RemoteRunnable("http://localhost:8000/csv-agent")