🔍 Code Extractor

Entry point function that orchestrates the Project Victoria disclosure analysis by initializing the generator, running the complete analysis, and displaying results with next steps.

Purpose

This function serves as the main entry point for the Project Victoria Disclosure Generator application. It provides a user-friendly command-line interface that initializes the disclosure generator, executes the complete analysis workflow, and provides feedback on success or failure along with actionable next steps for the user. It's designed to be called directly when running the script as a standalone application.

Source Code

def main():
    """Main function to run the Project Victoria disclosure analysis."""
    print("Project Victoria Disclosure Generator")
    print("====================================")
    
    # Initialize generator
    generator = ProjectVictoriaDisclosureGenerator()
    
    # Run complete analysis
    output_file = generator.run_complete_analysis()
    
    if output_file:
        print(f"\\n✅ Disclosure report generated: {output_file}")
        print("\\nNext steps:")
        print("1. Review the generated disclosures")
        print("2. Verify accuracy against source documents")
        print("3. Add any additional information as needed")
        print("4. Format for final legal documentation")
    else:
        print("\\n❌ Analysis failed. Please check error messages above.")

Return Value

This function does not return any value (implicitly returns None). It produces side effects by printing output to the console and generating a disclosure report file through the ProjectVictoriaDisclosureGenerator instance.

Dependencies

• os
• re
• json
• pandas
• numpy
• typing
• datetime
• tiktoken
• chromadb
• langchain_openai
• langchain
• warnings
• fitz
• sentence_transformers
• openai
• traceback

Required Imports

from typing import List, Dict, Any, Tuple, Optional
import os
import re
import json
import pandas as pd
import numpy as np
from datetime import datetime
import tiktoken
import chromadb
from chromadb import Documents, EmbeddingFunction, Embeddings
from langchain_openai import ChatOpenAI
from langchain.prompts import PromptTemplate
import warnings
import fitz
from sentence_transformers import CrossEncoder
from openai import OpenAI
import traceback

Usage Example

# Assuming ProjectVictoriaDisclosureGenerator is defined in the same module
# and all required environment variables and data files are set up

if __name__ == '__main__':
    main()

# Expected console output:
# Project Victoria Disclosure Generator
# ====================================
# [Processing messages from generator]
# ✅ Disclosure report generated: disclosure_report_20240115_143022.docx
# 
# Next steps:
# 1. Review the generated disclosures
# 2. Verify accuracy against source documents
# 3. Add any additional information as needed
# 4. Format for final legal documentation

Best Practices

• This function should be called within an if __name__ == '__main__': block to prevent execution when the module is imported
• Ensure ProjectVictoriaDisclosureGenerator is properly initialized with all required dependencies before calling this function
• Set up proper error handling in ProjectVictoriaDisclosureGenerator.run_complete_analysis() as this function relies on its return value
• Verify all required environment variables and configuration files are present before execution
• Consider adding command-line argument parsing if the function needs to support different execution modes or parameters
• The function provides user-friendly output but does not handle exceptions - ensure the generator class handles errors gracefully
• Review the generated output file path and ensure it's accessible to the user running the script

Tags

Similar Components

AI-powered semantic similarity - components with related functionality:

• function main_v61 87.9% similar

  Entry point function that instantiates an ImprovedProjectVictoriaGenerator and executes its complete pipeline to generate disclosure documents.

  From: /tf/active/vicechatdev/improved_project_victoria_generator.py

• function main_v57 84.9% similar

  Entry point function that instantiates a FixedProjectVictoriaGenerator and executes its complete pipeline to generate fixed disclosure documents.

  From: /tf/active/vicechatdev/fixed_project_victoria_generator.py

• class ProjectVictoriaDisclosureGenerator 67.7% similar

  Main class for generating Project Victoria disclosures from warranty claims.

  From: /tf/active/vicechatdev/project_victoria_disclosure_generator.py

• function main_v5 67.0% similar

  Main entry point function that orchestrates the contract validity analysis workflow by loading configuration, setting up logging, initializing the analyzer, running analysis, and reporting results.

  From: /tf/active/vicechatdev/contract_validity_analyzer/core/analyzer.py

• function main_v4 65.9% similar

  Main entry point function for the Contract Validity Analyzer application that orchestrates configuration loading, logging setup, FileCloud connection, and contract analysis execution.

  From: /tf/active/vicechatdev/contract_validity_analyzer/main.py