Skip to content

Latest commit

 

History

History
240 lines (185 loc) · 6.79 KB

README.md

File metadata and controls

240 lines (185 loc) · 6.79 KB

ChittyTrace-CC

ChittyCorp License: MIT Python 3.11+

ChittyTrace-CC for Cook County Illinois (Chicago) - Financial Document Analysis & Court Ready Exhibit Package Development

Specialized version for Cook County Circuit Court with local attorney optimizations

A comprehensive AI-powered financial forensics platform optimized specifically for Cook County attorneys and legal professionals.

Developed by ChittyCorp, LLC - Part of the Chitty ecosystem of AI-powered business solutions.

Features

Core Capabilities

  • Document Processing: Recursive scanning and indexing of all financial documents
  • AI-Powered Analysis: Claude integration for intelligent document querying
  • Interactive Timeline: Visual timeline with document linking
  • Exhibit Generation: Cook County court-compliant exhibit packages
  • Form Automation: Automated filling of legal and financial forms
  • Command Execution: Complex analysis commands (fund tracing, pattern detection)
  • Database Integration: Neon PostgreSQL with vector search capabilities
  • Email Ingestion: Cloudflare Worker integration for email processing
  • Database Integration: Neon PostgreSQL with vector search

Supported Document Types

  • Financial statements (PDF, Excel, CSV)
  • Bank statements
  • Wire transfer records
  • Property documents
  • Legal filings
  • Tax documents
  • Email communications (.eml, .msg)
  • Archive files (.zip, .tar, etc.)
  • Office documents (.doc, .docx, .rtf)

Installation

  1. Clone the repository:
cd /flow_analyzer
  1. Create virtual environment:
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
  1. Install dependencies:
pip install -r requirements.txt
  1. Set up environment variables:
cp .env.example .env
# Edit .env with your API keys and configuration
  1. Initialize database (if using Neon):
# The schema will be automatically applied on first run

Usage

1. Streamlit GUI Application

Launch the interactive web interface:

streamlit run app.py

Features available in GUI:

  • Document scanning and indexing
  • Natural language queries
  • Interactive timeline visualization
  • Exhibit package generation
  • Form filling interface
  • Command execution center
  • Data visualizations
  • Document browser

2. API Extension for Claude/OpenAI

Start the API server:

python claude_openai_extension.py

The API runs on http://localhost:8000 and provides endpoints for:

  • /documents/scan - Scan and index documents
  • /documents/query - Query documents with natural language
  • /timeline/extract - Extract timeline events
  • /exhibits/generate - Generate court exhibit packages
  • /forms/fill - Fill form templates
  • /commands/execute - Execute analysis commands

3. Command Line Usage

from flow_analyzer import FlowAnalyzer

# Initialize analyzer
analyzer = FlowAnalyzer(api_key="your_anthropic_key")

# Scan documents
documents = analyzer.scan_all_documents()

# Query documents
result = analyzer.query("Trace funds from USAA to Colombia property")

# Generate exhibit package
package = analyzer.generate_exhibit_package(
    documents=selected_docs,
    case_info={
        "case_number": "2024-CH-00001",
        "caption": "Your Case Name v. Defendant",
        "affiant": "Your Name"
    },
    purpose="Property funding documentation"
)

Cook County Exhibit Requirements

The system automatically formats exhibits according to Cook County Circuit Court requirements:

  • Page Size: 8.5" x 11"
  • Margins: 1 inch on all sides
  • Font: Times New Roman or Arial, 12pt
  • Line Spacing: Double-spaced
  • Exhibit Stickers: Bottom right corner with:
    • Exhibit Number
    • Case Number
    • Date
  • Authentication: Notarized affidavit required
  • Package Components:
    • Cover sheet
    • Table of contents
    • Certificate of service
    • Sequential exhibit numbering

Database Schema

The system uses PostgreSQL with vector extensions for semantic search:

Main Tables

  • documents - Scanned documents with content and embeddings
  • timeline_events - Extracted financial events
  • court_exhibits - Exhibit preparation and tracking
  • analysis_queries - Query history and responses
  • exhibit_packages - Complete exhibit packages

Neon Database Integration

The system integrates with Neon PostgreSQL databases for:

  • Document storage and indexing
  • Timeline event tracking
  • Cross-referencing transactions
  • Vector-based semantic search
  • Exhibit package management

Email Ingestion

Configure Cloudflare Worker for email ingestion:

  1. Set CLOUDFLARE_WORKER_URL in .env
  2. Set CLOUDFLARE_WORKER_TOKEN for authentication
  3. The system will automatically ingest emails from:

Advanced Features

Pattern Detection

result = analyzer.execute_command("detect_patterns", {
    "pattern_type": "structured_transactions",
    "threshold": {"amount": 10000, "frequency": "daily"}
})

Fund Flow Visualization

chart = analyzer.execute_command("generate_fund_flow_chart", {
    "start_date": "2023-01-01",
    "end_date": "2023-12-31",
    "accounts": ["USAA", "Fidelity", "Mercury"]
})

Property Chain Analysis

analysis = analyzer.execute_command("analyze_property_chain", {
    "property_address": "123 Main St, Chicago, IL"
})

Security

  • API endpoints are protected with bearer token authentication
  • Database connections use SSL
  • Sensitive data is never logged
  • File uploads are validated and sandboxed

Troubleshooting

Common Issues

  1. Import errors: Ensure all dependencies are installed
  2. API key errors: Check .env configuration
  3. Database connection: Verify DATABASE_URL format
  4. Large files: Files over 100MB are skipped by default

Logs

Check logs/ directory for detailed error messages and debugging information.

About ChittyCorp

This project is developed and maintained by ChittyCorp, LLC, a technology company specializing in AI-powered solutions for legal, financial, and business intelligence applications.

Support

For issues, questions, or commercial licensing inquiries:

License

This project is licensed under the MIT License - see the LICENSE file for details.

Copyright (c) 2025 ChittyCorp, LLC