FinGPT - AI-Powered Financial Assistant

FinGPT is an intelligent financial assistant chatbot built with Streamlit that helps users with finance-related queries, including stock market information, investment advice, insurance, retirement planning, and personal finance management.

Features

💬 AI-Powered Chat Interface

• Intelligent conversational AI trained on financial topics
• Real-time responses using Mixtral-8x7B-Instruct model from Hugging Face
• Context-aware responses with sentiment analysis

📈 Stock Market Integration

• Real-time stock price fetching using Yahoo Finance (yfinance)
• Interactive stock price charts with Plotly
• Automatic ticker detection from user queries

🎤 Voice Interaction

• Speech-to-text input for hands-free querying
• Text-to-speech output for audio responses
• Built-in microphone support

🧠 Advanced NLP Features

• Sentiment analysis of user messages
• Keyword extraction to identify main topics
• Tailored responses based on detected sentiment and keywords

📊 Custom Data Integration

• Upload and integrate custom fine-tuning data (TXT files)
• Import CSV data for personalized responses
• Pre-loaded financial Q&A knowledge base

💾 Conversation Management

• Persistent chat history within sessions
• Clear chat history functionality
• Conversation summarization feature

Prerequisites

• Python 3.8 or higher
• Hugging Face API token (for AI model access)
• Microphone (optional, for voice input)

Installation

1. Clone the repository:

git clone https://github.com/Reeva28/FinGPT.git
cd FinGPT

2. Install required dependencies:

pip install streamlit huggingface-hub python-dotenv pandas yfinance gtts speechrecognition plotly pyaudio

Note: pyaudio is required for microphone support. On some systems, you may need to install additional system dependencies first.

3. Create a .env file in the project root and add your Hugging Face API token:

HUGGING_FACE_TOKEN=your_hugging_face_token_here

Usage

1. Start the Streamlit application:

streamlit run basic_ai_template.py

2. Open your web browser and navigate to the URL shown in the terminal (typically http://localhost:8501)

3. Start chatting with the AI assistant about:

   • Stock market queries
   • Investment strategies
   • Insurance questions
   • Retirement planning
   • Personal finance management
   • Financial products and services

Voice Interaction

• Click the 🎤 button to use voice input
• Click the 🔊 button next to any message to hear it read aloud

Custom Data Upload

Use the sidebar to:

• Upload custom fine-tuning data (TXT format)
• Import CSV files with additional financial information
• View conversation summaries

Project Structure

FinGPT/
├── basic_ai_template.py      # Main Streamlit application
├── tune_data.txt              # Pre-loaded fine-tuning data (loaded at startup)
├── fine_tuning_data.txt       # User-uploaded training data (created from UI uploads)
├── bot_score.csv              # Sample CSV data (fitness scores and discounts)
├── data.csv                   # User-uploaded CSV data storage
├── .env                       # Environment variables (not in repo)
└── .gitignore                 # Git ignore file

Features Breakdown

Stock Query Examples

• "What's the current price of AAPL?"
• "Show me Tesla stock performance"
• "Tell me about $MSFT"

Financial Topics Covered

• Stock market analysis
• Mutual funds
• Investment banking
• Retirement planning (401k, annuities)
• Personal finance (budgeting, savings)
• Insurance (health, disability, umbrella, renters)
• Credit and loans (HELOC, mortgages)
• Financial products and services

Configuration

Environment Variables

• HUGGING_FACE_TOKEN: Your Hugging Face API token for accessing the AI model

Customizable Parameters

• Stock history period (default: 1 month)
• AI response max tokens (default: 150)
• Model: Mixtral-8x7B-Instruct-v0.1

Dependencies

• streamlit: Web application framework
• huggingface-hub: AI model integration
• python-dotenv: Environment variable management
• pandas: Data manipulation and CSV handling
• yfinance: Real-time stock data fetching
• gtts: Text-to-speech conversion
• speech_recognition: Speech-to-text conversion
• plotly: Interactive chart visualization

Limitations

• The AI assistant only responds to finance-related queries
• Stock data requires active internet connection
• Voice input requires microphone access
• API rate limits may apply based on your Hugging Face tier

Privacy & Security

• API tokens should be stored in .env file (not committed to version control)
• User conversations are stored only in session state
• No personal data is transmitted beyond the AI model API

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is open source and available for educational and personal use.

Support

For issues, questions, or suggestions, please open an issue on the GitHub repository.

Acknowledgments

• Powered by Hugging Face's Mixtral-8x7B-Instruct model
• Stock data provided by Yahoo Finance
• Built with Streamlit framework