https://github.com/junayed-hasan/llendify
LLendify leverages large language models (LLMs) to analyze bank statements and provide instant loan eligibility insights. Upload your bank statement PDF to receive AI-powered loan recommendation, analysis of income patterns, spending habits, and creditworthiness. Get comprehensive financial assessments and loan recommendations in seconds.
https://github.com/junayed-hasan/llendify
artificial-intelligence banking-applications fastapi fintech langchain large-language-models openai-api pypdf2 reactjs software-engineering
Last synced: 17 days ago
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LLendify leverages large language models (LLMs) to analyze bank statements and provide instant loan eligibility insights. Upload your bank statement PDF to receive AI-powered loan recommendation, analysis of income patterns, spending habits, and creditworthiness. Get comprehensive financial assessments and loan recommendations in seconds.
- Host: GitHub
- URL: https://github.com/junayed-hasan/llendify
- Owner: junayed-hasan
- License: mit
- Created: 2025-01-24T20:21:15.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-25T04:18:48.000Z (about 1 year ago)
- Last Synced: 2025-03-04T14:51:39.405Z (about 1 year ago)
- Topics: artificial-intelligence, banking-applications, fastapi, fintech, langchain, large-language-models, openai-api, pypdf2, reactjs, software-engineering
- Language: JavaScript
- Homepage:
- Size: 57.7 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# LLendify - LLM-Driven Loan Insights
LLendify leverages LLM technology to analyze bank statements and provide instant loan eligibility insights. Upload your bank statement PDF to receive AI-powered analysis of income patterns, spending habits, and creditworthiness. Get comprehensive financial assessments and loan recommendations in seconds.
## 🚀 Features
- 📊 Instant AI-powered loan analysis
- 🔒 Secure document processing with encryption
- 💡 Smart financial insights and recommendations
- 📱 Responsive design for all devices
- ⬇️ Downloadable analysis reports
- 🛡️ Data privacy focused
## 🛠️ Tech Stack
### Frontend
- React.js
- Tailwind CSS
- Lucide Icons
- Axios for API calls
- File handling utilities
### Backend
- FastAPI
- Python 3.9+
- LangChain
- PyPDF2 for PDF processing
- Custom PDF parsing pipeline
## 📁 Project Structure
### Frontend (`/bank-analyzer-ui`)
```
bank-analyzer-ui/
├── public/
├── src/
│ ├── components/
│ │ ├── common/
│ │ │ └── Modal.jsx
│ │ └── layout/
│ │ ├── Footer.jsx
│ │ ├── Layout.jsx
│ │ └── Navbar.jsx
│ ├── utils/
│ │ └── downloadUtils.js
│ ├── styles/
│ │ └── globals.css
│ ├── App.jsx
│ └── index.js
└── package.json
```
### Backend (`/src`)
```
src/
├── analysis_pipeline.py
├── api.py
├── app.py
├── pdf_parser.py
├── prompt_templates.py
├── Bank_statement_1.pdf
├── Bank_statement_2.pdf
├── Bank_statement_3.pdf
├── Bank_statement_4.pdf
└── .env
```
## 🚀 Getting Started
### Prerequisites
- Node.js (v14 or higher)
- Python 3.9+
- pip
- Git
- OpenAI API key
### Frontend Setup
1. Clone the repository
```bash
git clone https://github.com/junayed-hasan/llendify.git
cd llendify/bank-analyzer-ui
```
2. Install dependencies
```bash
npm install
```
3. Start the development server
```bash
npm start
```
The frontend will be available at `http://localhost:3000`
### Backend Setup
1. Navigate to the backend directory
```bash
cd src
```
2. Create and activate a virtual environment
```bash
python -m venv venv
source venv/bin/activate # On Windows, use: venv\Scripts\activate
```
3. Install dependencies
```bash
pip install -r requirements.txt
```
4. Create a `.env` file in the src directory (if not exists)
```bash
touch .env
```
5. Add your OpenAI API key to the `.env` file
```
OPENAI_API_KEY=your_api_key_here
```
6. Start the FastAPI server
```bash
uvicorn app:app --reload
```
The API will be available at `http://localhost:8000`
## 🧪 Testing
### Frontend Testing
1. Run the test suite
```bash
npm test
```
### Backend Testing
1. Ensure your virtual environment is activated
2. Make sure your `.env` file contains the OpenAI API key
3. Sample bank statements are available in the src directory:
- Bank_statement_1.pdf
- Bank_statement_2.pdf
- Bank_statement_3.pdf
- Bank_statement_4.pdf
4. Test the API endpoints using these sample files
### Testing with Sample Files
1. Use any of the provided sample PDF files in the src directory
2. Upload through the UI (file should be a PDF)
3. The analysis results will be displayed and can be downloaded
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
1. Fork the project
2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
## 📞 Contact
Mohammad Junayed Hasan
- Email: junayedhasan100@gmail.com
- LinkedIn: [mjhasan21](https://www.linkedin.com/in/mjhasan21/)