Create Your LLM Agents Leveraging Tools with Unity Catalog Functions
Demo Type
Product Tutorial
Duration
self-paced
Related Links
What you’ll learn
AI systems require diverse capabilities to answer business use cases and provide values within each industry.
In this demo, we will build a Compound AI System composed of multiple tools (Unity Catalog Functions) and reasoning agents. A tool typically fetches extra information or executes a computation, such as:
- Getting the latest customer order status (to answer questions related to an online order)
- Getting the current weather
- Calling external Machine Learning model for recommendation
- Call a Vector Search Index to find relevant information/documents to provide better answers (RAG)
- Executing specialized routine/LLM queries with specialized prompts or fine-tuned model
- Execution python script
- Mathematical operation
Install this demo to discover step-by-step instructions on how to build your first Compound AI System!
To run the demo, get a free Databricks workspace and execute the following two commands in a Python notebook:
%pip install dbdemos
import dbdemos
dbdemos.install('llm-tools-functions', catalog='main', schema='dbdemos_agent_tools')
Disclaimer: This tutorial leverages features that are currently in private preview. Databricks Private Preview terms apply.
For more details, open the introduction notebook.