NVIDIA Technical Blog

Build an LLM-Powered Data Agent for Data Analysis

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Building an LLM-Powered Data Agent for Data Analysis

Introduction

This section provides an overview of LLM agents and explains the main types required for building an accurate LLM application for handling data analysis tasks.

LLM Agent Types for Data Analysis Tasks

  • API or Execution Agents: Designed for an execution goal and involve chaining Excel APIs together to perform tasks.
  • Agent Swarms: Involves multiple data agents and API agents collaborating in a decentralized manner to solve complex problems.

Building a Data Analyst Agent

This section delves into building a data agent for talking to an SQL database for inventory management, explaining the iterative greedy approach for decision-making.

Data Agent Example

  • Step 1: QueryDB Tool
    • Generate SQL query database
    • Store results in memory
  • Step 2: Calculator Tool
    • Solve math problem using LLM
    • Store results in memory
  • Step 3: Final Answer Generation
    • Prompt the agent's core LLM after SQL generation for the final answer.

Summary

This post has provided insights into building an LLM agent application for data analytics, familiarizing the reader with the concepts behind constructing agents.