This template enables a user to interact with a SQL database using natural language.
To set up the environment, use the following steps:
conda create -n llama python=3.9.16
conda activate /Users/rlm/miniforge3/envs/llama
CMAKE_ARGS="-DLLAMA_METAL=on" FORCE_CMAKE=1 pip install -U llama-cpp-python --no-cache-dir
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-llamacpp
If you want to add this to an existing project, you can just run:
langchain app add sql-llamacpp
And add the following code to your
from sql_llamacpp import chain as sql_llamacpp_chain
add_routes(app, sql_llamacpp_chain, path="/sql-llamacpp")
This package includes an example DB of 2023 NBA rosters. You can see instructions to build this DB here.
(Optional) Configure LangSmith for tracing, monitoring and debugging 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 running locally at http://localhost:8000
You can access the template from code with:
from langserve.client import RemoteRunnable
runnable = RemoteRunnable("http://localhost:8000/sql-llamacpp")