INDIAN-GST-chatbot-with-Invoice-analysis

RAG-Based GST Analysis Agent

Overview

This project is a Retrieval-Augmented Generation (RAG) based agent for GST (Goods and Services Tax) analysis. The system is designed to extract, process, and analyze GST-related data from various sources, including PDFs, images, and text inputs. It leverages large language models and advanced document parsing techniques to provide meaningful insights.

Key Features

• RAG-Based Architecture: Combines retrieval and generation for accurate GST analysis.
• Multi-Modal Input: Supports text, PDFs, and images.
• Advanced OCR & Table Extraction: Extracts structured data from scanned invoices and GST documents.
• Integration with O1-mini Model: Utilizes the O1-mini model for enhanced response generation.

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Installation

Prerequisites

Ensure you have the following dependencies installed:

• Python 3.12.3
• Pip
• Virtual Environment (recommended)

Setup

git clone

https://github.com/your-repo/gst-analysis-agent.git

cd gst-analysis-agent

• python -m venv botenv
• source botenv/bin/activate # On Windows, use: botenv\Scripts\activate
• pip install -r requirements.txt
• setup api key in .env (open api key)

how to run

• python app.py

API Endpoints

1. Upload Data:
   • Endpoint: <span>/UploadData</span>
   • Method: <span>POST</span>
   • Supports: Text, PDFs, Images
2. PDF Processing:
   • Uses <span>unstructured.partition.pdf</span> for structured data extraction.
   • Extracts tables and text separately.
3. Image Processing:
   • Uses <span>pytesseract</span> for OCR-based text extraction.
   • Object detection using <span>torchvision</span>.
4. Integration with O1-mini:
   • The system leverages the <span>O1-mini</span> model for intelligent text generation and reasoning over retrieved GST data.