End-to-end LLM Deployments in Databricks 😎

This repo demonstrates a simple end-to-end workflow for developing, evaluating, and deploying large language models (LLMS) on the Databricks platform.

A couple things:

• In /notebooks you will find some Databricks notebooks which can be used to develop and deploy a Llama-7B chat model to a serving endpoint. These notebooks were ran on a single-node GPU cluster with 32GB of VRAM using DBR 13.3 ML LTS.

• This POC uses Langchain, so you can quickly swap out the LLM you wish to use by simply redefining LLM in app.py

• To connect to a Databricks serving endpoint, DATABRICKS_HOST and DATABRICKS_TOKEN environment variables must be properly defined.

• To run the Gradio chat UI:

  python app.py