SQL - Research assistant

This package does research over a SQL database

Usage

This package relies on multiple models, which have the following dependencies:

• OpenAI: set the OPENAI_API_KEY environment variables
• Ollama: install and run Ollama
• llama2 (on Ollama): ollama pull llama2 (otherwise you will get 404 errors from Ollama)

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 sql-research-assistant

If you want to add this to an existing project, you can just run:

langchain app add sql-research-assistant

And add the following code to your server.py file:

from sql_research_assistant import chain as sql_research_assistant_chain

add_routes(app, sql_research_assistant_chain, path="/sql-research-assistant")

(Optional) Let's now configure LangSmith. LangSmith will help us trace, monitor and debug LangChain applications. You can sign up for LangSmith 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/sql-research-assistant/playground

We can access the template from code with:

from langserve.client import RemoteRunnable

runnable = RemoteRunnable("http://localhost:8000/sql-research-assistant")