Receipt Analyzer LLM is an AI-powered application that uses Qwen 2.5 models to extract and analyze shopping receipts.
It parses receipts from PDF or image files, stores them in a database, and allows users to ask natural language questions about their spending, stores, or items.
The system combines document parsing, structured storage, and large language model reasoning.
Users can upload receipts, automatically extract information, and interact with their data through a Gradio-based chat interface.
- Receipt extraction from PDF and image files
- Qwen2.5-1.5B and Qwen2.5-7B LLM support for reasoning
- Local SQLite database for structured storage
- Natural language queries about spend, stores, and items
- Off-topic question filtering
- Comparative evaluation of model accuracy and latency
# Clone repository
git clone https://github.com/YOUR_USERNAME/receipt-analyzer-llm.git
cd receipt-analyzer-llm
# (Optional) create virtual environment
python -m venv venv
source venv/bin/activate # or venv\Scripts\activate on Windows
# Install dependencies
pip install -r requirements.txt