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AG2 Multi-Agent Document Processing with Unstructured

This example demonstrates how to use AG2 (formerly AutoGen) multi-agent conversations with Unstructured for intelligent document processing and analysis.

Overview

Two AG2 agents collaborate to process and analyze documents:

  • Document Agent -- Uses Unstructured to partition documents and extract structured elements (text, tables, titles, narrative)
  • Analyst Agent -- Analyzes the extracted content, answers questions, and produces summaries with source references

Prerequisites

  • Python >= 3.11
  • OpenAI API key
  • System dependencies: libmagic-dev, poppler-utils, tesseract-ocr (for PDF/image support)

Quick Start

# Install dependencies
pip install "unstructured[all-docs]" "ag2[openai]>=0.11.4,<1.0"

# Set API key
export OPENAI_API_KEY="your-api-key"

# Run the example (uses sample docs from example-docs/)
python run.py

# Or specify your own document
python run.py --file /path/to/your/document.pdf

How It Works

  1. Unstructured partitions a document into structured elements (Title, NarrativeText, Table, ListItem, etc.)
  2. AG2 Document Agent wraps Unstructured as a registered tool, callable by agents
  3. AG2 Analyst Agent receives extracted elements and produces analysis
  4. Agents collaborate via AG2 GroupChat with automatic tool execution

Tech Stack

  • AG2 -- Multi-agent conversation framework (500K+ monthly PyPI downloads)
  • Unstructured -- Document ETL for LLMs (25+ file types)