⚡ Stock Insights AI - Multi-Agent Research Terminal

Stock Insights AI is an advanced financial analytics platform powered by CrewAI and Google Gemini 2.5 Flash. It utilizes a multi-agent system to perform deep-dive equity research and real-time market trend scanning, mimicking the workflow of a professional hedge fund investment committee.

You can try the live app here: Stock Insights AI on Streamlit

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🚀 Features

1. Single Ticker Deep Dive

• 4-Agent Crew: Sentiment Analyst, Fundamental Analyst, Technical Analyst, and Portfolio Manager.
• Comprehensive Report: Generates a structured investment memo with "Buy/Sell/Hold" recommendations.
• Live Data: Real-time price charts, P/E ratios, Market Cap, and Volatility metrics via Yahoo Finance.
• Sentiment Analysis: Analyzes news headlines using Alpha Vantage to gauge market mood.

2. Market Trend Scanner

• Automated Screening: Instantly fetches the day's Top Gainers using Alpha Vantage API.
• Strategic Analysis: Uses a specialized 2-Agent Crew to explain why stocks are moving and provide short-term trading signals.
• Visual Dashboard: Interactive metric cards showing % returns and price movement.

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🛠️ Tech Stack

• Core Framework: Python 3.13
• AI Orchestration: CrewAI (Multi-Agent Framework)
• LLM Engine: Google Gemini 2.5 Flash (via litellm)
• Frontend: Streamlit (Custom CSS for Dark/Neon Glassmorphism UI)
• Data Sources:
  • Yahoo Finance (yfinance): Price history, technical indicators, fundamental data.
  • Alpha Vantage: News sentiment, top market movers list.
• Visualization: Plotly (Interactive Candlestick charts)

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⚙️ Installation & Setup

Prerequisites

• Python 3.13 installed
• Google Gemini API Key (Free tier available at Google AI Studio)
• Alpha Vantage API Key (Free tier available at Alpha Vantage)

Step 1: Clone the Repository

git clone https://github.com/pathu11/Stock-market-analysis.git
cd Stock-market-analysis 

Step 2: Create Virtual Environment

# Windows
python -m venv venv
venv\Scripts\activate

# Mac/Linux
python3 -m venv venv
source venv/bin/activate

Step 3: Install Dependencies

pip install -r requirements.txt

Step 4: Configure Environment Variables

Create a file named .env in the root directory and add your keys:

# .env file
GOOGLE_API_KEY=your_google_gemini_key_here
ALPHA_VANTAGE_API_KEY=your_alpha_vantage_key_here

Step 5: Run the Application

streamlit run app.py

The application will launch in your browser at http://localhost:8501.

📂 Project Structure

stock-insights-ai/
│
├── agents.py             # Defines the CrewAI Agents, Tasks, and LLM configuration
├── tools.py              # Custom tools for fetching data (YFinance, Alpha Vantage)
├── app.py                # Main Streamlit UI application
├── requirements.txt      # Python dependencies
├── .env                  # API Keys (Not committed to repo)
└── README.md             # Documentation

⚠️ Important Note on API Limits

• Alpha Vantage Free Tier: Limited to 25 requests per day. Use the "Market Scanner" sparingly on the free tier.