This full-stack mini-application helps you effortlessly manage your expenses by uploading receipts and bills, automatically extracting key data, and providing insightful financial analytics.

• Intelligent Data Extraction
  Automatically parses Vendor/Biller, Date, Amount, Category, and Currency from .jpg, .png, .pdf, and .txt files.

• Interactive Dashboard
  A user-friendly Streamlit interface for managing and visualizing your expenses.

• Powerful Search & Filter
  Efficiently find transactions using keywords, amount/date ranges, and vendor patterns.

• Comprehensive Analytics
  Visualizes total spend, mean/median, category/vendor distributions, and monthly spending trends.

-Manual Field Correction via UI: Users can edit and correct parsed data directly in the interactive table presented in the Streamlit UI.

• Data Export
  Export summaries and raw data to CSV and JSON formats.

• Currency & Multi-Language OCR Support
  Backend designed for currency detection and potential multi-language receipt processing

• Python: Core language
• FastAPI: High-performance web framework for REST APIs
• SQLAlchemy: ORM for SQLite database interaction
• Pydantic: Data validation
• pytesseract & opencv-python: For OCR and image processing
• pdf2image: For PDF processing (requires Poppler)

• Streamlit: Python framework for building interactive web applications
• requests: For API communication with the backend
• pandas: For data manipulation and display

• Git & GitHub: Version control and hosting
• Tesseract OCR Engine: External OCR software
• Poppler: External PDF rendering library

The application uses a client-server architecture:

• A FastAPI Backend handles all data processing (OCR, parsing, database operations) and exposes RESTful APIs.
• A Streamlit Frontend provides the interactive user interface, consuming data from the FastAPI backend.

1. Clone the Repository
git clone https://github.com/mohdirfan-code/Receipt-bill-analyzer.git
cd Receipt-bill-analyzer

2. Set Up Virtual Environment & Install Dependencies
cd backend
python -m venv venv
.\venv\Scripts\activate  # PowerShell
# OR
.\venv\Scripts\activate.bat  # CMD

pip install -r requirements.txt


3. Run FastAPI Backend
cd backend
.\venv\Scripts\activate
cd ..
uvicorn backend.main:app --reload 

4. Run Streamlit Frontend
cd backend
.\venv\Scripts\activate
cd ../frontend_streamlit
streamlit run app.py

❤️ Developed by Mohd Irfan.