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function main_v62

Maturity: 35

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

File:
/tf/active/vicechatdev/improved_project_victoria_generator.py
Lines:
789 - 793
Complexity:
moderate

Purpose

This function serves as the main entry point for running the improved disclosure generator system. It creates an instance of ImprovedProjectVictoriaGenerator, executes the full pipeline for generating disclosure documents (likely involving RAG-based document generation using embeddings and LLMs), and returns the path to the generated output file. This is typically used as the primary execution function when running the disclosure generation system.

Source Code

def main():
    """Main function to run the improved disclosure generator."""
    generator = ImprovedProjectVictoriaGenerator()
    output_path = generator.run_complete_pipeline()
    return output_path

Return Value

Returns a string representing the file path (output_path) where the generated disclosure document has been saved. The exact format and location depend on the ImprovedProjectVictoriaGenerator's configuration and run_complete_pipeline method implementation.

Dependencies

  • os
  • re
  • json
  • tiktoken
  • typing
  • datetime
  • chromadb
  • langchain_openai
  • sentence_transformers
  • fitz
  • OneCo_hybrid_RAG

Required Imports

import os
import re
import json
import tiktoken
from typing import List, Dict, Any, Tuple
from datetime import datetime
import chromadb
from langchain_openai import ChatOpenAI
from sentence_transformers import CrossEncoder
import fitz
from OneCo_hybrid_RAG import MyEmbeddingFunction

Usage Example

# Ensure all environment variables are set
import os
os.environ['OPENAI_API_KEY'] = 'your-api-key-here'

# Import the function (assuming it's in disclosure_generator.py)
from disclosure_generator import main

# Run the disclosure generator
output_file_path = main()
print(f'Disclosure document generated at: {output_file_path}')

Best Practices

  • Ensure all required environment variables (especially OPENAI_API_KEY) are set before calling this function
  • Verify that the ImprovedProjectVictoriaGenerator class is properly defined with a run_complete_pipeline method
  • Check that all required data sources and PDF files are accessible before execution
  • Handle the returned output_path appropriately, checking if the file was successfully created
  • Consider wrapping the call in try-except blocks to handle potential errors from the pipeline execution
  • Ensure sufficient disk space for ChromaDB storage and generated output files
  • Monitor API usage and costs when using OpenAI services through this function

Tags

entry-point main-function disclosure-generation RAG document-generation pipeline LLM embeddings chromadb langchain project-victoria

Similar Components

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  • function main_v58 91.9% similar

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