FinSight GPT is an AI-powered financial analysis system that transforms how investment decisions are made. By combining Google's Gemini Pro AI, advanced ML forecasting models, and real-time market data, it provides instant insights, predictions, and actionable investment recommendations for Microsoft (MSFT) stock.

Features

Stage 1: Document Q&A & Analysis

•⁠ ⁠💬 AI-Powered Q&A: Ask questions about Microsoft's financials in natural language

•⁠ ⁠📊 Sentiment Analysis: Real-time market sentiment scoring

•⁠ ⁠🔍 Anomaly Detection: Automatic flagging of unusual financial metrics

•⁠ ⁠📈 Key Insights: Revenue growth, cloud performance, profitability metrics

Stage 2: Financial Forecasting

•⁠ ⁠📉 Multi-Model Predictions: Prophet, Random Forest, and Linear Regression

•⁠ ⁠📅 Flexible Timeframes: 7, 30, and 90-day forecasts

•⁠ ⁠📊 Technical Indicators: RSI, SMA20, SMA50, trend analysis

•⁠ ⁠🎯 Confidence Intervals: Upper and lower bounds for predictions

Stage 3: Investment Strategy

•⁠ ⁠🤖 Automated Recommendations: Clear BUY/SELL/HOLD decisions

•⁠ ⁠💯 Confidence Scoring: 0-100% confidence in recommendations

•⁠ ⁠📋 Investment Rationale: AI-generated explanations

•⁠ ⁠⚠️ Risk Assessment: Identified risks with severity levels

Technology Stack

•⁠ ⁠Backend: FastAPI, Python 3.11

•⁠ ⁠AI/ML: Google Gemini Pro, Prophet, scikit-learn

•⁠ ⁠Frontend: HTML5, JavaScript, Chart.js, Tailwind CSS

•⁠ ⁠Data Sources: Yahoo Finance, Alpha Vantage

•⁠ ⁠NLP: TextBlob for sentiment analysis

Prerequisites

•⁠ ⁠Python 3.11+

•⁠ ⁠API Keys:

Google Gemini API Key (openly available)

Alpha Vantage API Key (openly available)

Quick Start:

1.⁠ ⁠Clone the Repository

bash git clone https://github.com/yourusername/findocgpt.git cd findocgpt

##2.⁠ ⁠Set Up Backend

bash

Navigate to backend

cd backend

Create virtual environment

python -m venv venv

Activate virtual environment

On Mac/Linux:

source venv/bin/activate

On Windows:

venv\Scripts\activate

Install dependencies

pip install -r requirements.txt

Create .env file

echo "GEMINI_API_KEY=your_gemini_api_key_here" > .env echo "ALPHA_VANTAGE_KEY=your_alpha_vantage_key_here" >> .env

Run the backend

python main.py

Set Up Frontend

bash

Open a new terminal and navigate to frontend

cd frontend

Serve the frontend

Option 1: Using Python

python -m http.server 3000

Option 2: Using Node.js

npx serve -p 3000

Option 3: Simply open in browser

open index.html # Mac start index.html # Windows

Configuration

Environment Variables

Create a .env file in the backend directory:

env

GEMINI_API_KEY=your_gemini_api_key_here

ALPHA_VANTAGE_KEY=your_alpha_vantage_key_here # Optional

📊 Performance Metrics

•⁠ ⁠Q&A Accuracy: 100% for predefined financial queries

•⁠ ⁠Prediction Models: 3 different algorithms with fallbacks

•⁠ ⁠API Response Time: <2 seconds average

•⁠ ⁠Frontend Load Time: <1 second

•⁠ ⁠Auto-refresh: Every 30 seconds

🤝 Contributing

1.⁠ ⁠Fork the repository

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

🏆 Acknowledgments

•⁠ ⁠Built for the AkashX.ai Global AI Hackathon 2025

•⁠ ⁠Powered by Google Gemini Pro AI

•⁠ ⁠Financial data from Yahoo Finance and Alpha Vantage

•⁠ ⁠UI components from Tailwind CSS and Chart.js

👥 Team