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Receipt and Refund Request Tracker

A comprehensive application for managing receipts and processing refund requests, featuring AI-powered audio and image processing capabilities.

Features

Receipt Processing

  • Upload and store receipt images
  • Extract amount information from receipts
  • Store receipt data in Supabase database

Audio Processing

  • Process audio files from refund requests using Groq's whisper-large-v3-turbo model
  • Automatic transcription of audio content
  • AI-powered summarization of transcriptions
  • Support for direct URL audio file processing

Database Integration

  • Supabase backend for secure data storage
  • Real-time data synchronization
  • Efficient query operations

Setup

  1. Install required packages:
pip install streamlit supabase langchain-groq requests python-dotenv
  1. Set up environment variables in .env:
GROQ_API_KEY=your_groq_api_key
SUPABASE_URL=your_supabase_url
SUPABASE_KEY=your_supabase_key
  1. Launch the application:
streamlit run app.py

Usage

Processing Refund Requests

  1. Upload receipt images through the Streamlit interface
  2. Record or upload audio explanations for refund requests
  3. View processed results including:
    • Extracted receipt amounts
    • Audio transcriptions
    • AI-generated summaries

Audio Processing Features

  • Automatic download and processing of audio files
  • High-accuracy transcription using Groq's whisper model
  • Concise summaries of audio content
  • Batch processing capabilities
  • Comprehensive error handling

Technical Details

Database Schema

  • refund_requests table:
    • id: Primary key
    • amount: Numeric (receipt amount)
    • image_url: Text (receipt image location)
    • audio_url: Text (refund request audio location)

Key Components

  1. app.py: Main Streamlit application
  2. audio_processor.py: Audio processing functionality
  3. database_operations.py: Supabase database interactions
  4. receipt_processor.py: Receipt image processing

Error Handling

  • Robust error management for file operations
  • Graceful handling of processing failures
  • Detailed error reporting
  • Automatic cleanup of temporary files

Security

  • Secure handling of API keys through environment variables
  • Safe temporary file management
  • Secure URL processing
  • Protected database operations

Requirements

  • Python 3.7+
  • Streamlit
  • Supabase
  • langchain-groq
  • requests
  • python-dotenv

Support

For issues and feature requests, please create an issue in the repository.

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