This project demonstrates one way of leveraging LLM as a copilot in assisting data record classification task. The approach employs prompt engineering technique called "ReAct" as a reasoning module that enables our Agent to be able to interact with external information beyond LLM knowledge scope.
-
make sure you have
conda
installed -
create
.env
in this folder containing the following keys to set LLM API key:
TYPHOON_API_KEY=...
- setup python environment
$ make setup-env
- setup python dependencies
$ make setup-deps
- attach
agent_llm.ipynb
to conda envgenai_share
to run the notebook.