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HOA Document Analysis AI Agent

An intelligent document analysis system that leverages OpenAI's Assistant API to extract, analyze and summarize key information from Homeowners Association (HOA) documents.

Features

  • Automated processing of multiple document formats (PDF, Word, TXT, MD)
  • Smart information extraction using authority-based ranking system
  • Vector store integration for efficient document search
  • Comprehensive analysis across 20 key HOA topics
  • Detailed answers and concise summaries for each topic
  • JSON output for easy integration

Key Capabilities

  • Document hierarchy enforcement based on authority ranking
  • Intelligent handling of conflicting information
  • Citation tracking and source documentation
  • Token limit management through iterative processing
  • Error handling and retry mechanisms

Configuration

Key settings in main.py:

HOA_DOCS_DIR = "./input/hoa_documents"  # Input documents location
MODEL_NAME = "gpt-4o-mini"              # AI model selection
TEMPERATURE = 0.1                       # Response determinism (lower = more focused)
OUTPUT_DIR = "./output"                 # Results location

Usage

  1. Place HOA documents in the input/hoa_documents directory
  2. Run the analysis:

python main.py
  1. Find results in the output directory:
  • {timestamp}-summary.json: Condensed findings by category
  • {timestamp}-answers.json: Detailed analysis with sources

Document Authority Ranking

Documents are prioritized in this order (1 = highest authority):

  1. CC&R Amendments
  2. CC&Rs
  3. Bylaws
  4. Articles of Incorporation
  5. Operating Rules [...]

Analysis Categories

The system analyzes 20 key areas including:

  • HOA Name and Official Details
  • Financial Information (Dues, Increases, Health)
  • Rules and Policies
  • Management and Operations
  • Community Features and Maintenance
  • Legal and Insurance Matters

Requirements

  • Python 3.x
  • OpenAI API access
  • Required packages:
    • openai
    • python-docx
    • PyPDF2 (for PDF processing)

Output Format

The system generates two JSON files:

  1. Summary Table:
[
  {
    "Category": "Category Name",
    "Findings": "Concise summary",
    "Source": "Source document path"
  }
]
  1. Detailed Answers:
[
  {
    "question": "Original question",
    "answer": "Detailed response",
    "summary": "Brief summary",
    "source": "Source documents",
    "source_ids": ["file_ids"]
  }
]