📈 Stock Agents - AI Stock Analysis

Welcome to Stock Agents, a Python-based project developed during the "IA na Prática" event hosted by Rocketseat. This project leverages AI and custom agents to analyze market trends, historical stock prices, and recent news for stocks listed on U.S. exchanges.

🚀 Project Overview

Stock Agents is designed to provide insights into a specific stock's market trends by combining historical data and news analysis. The project uses the following custom agents:

• Data Collector Agent: Fetches historical stock price data using the Yahoo Finance API.
• News Collector Agent: Gathers recent news related to the stock using the DuckDuckGo API.
• Trend Analyst Agent: Analyzes the data and news to predict the stock's future trend (up, down, or sideways).

The result is a comprehensive report, including a summary of the market sentiment and predictions about the stock's near-term performance.

🎯 Features

• Stock Price Analysis: Fetches and plots the closing prices of a specified stock over the past year.
• News Analysis: Searches for the latest news articles about the stock to provide context and additional insight.
• Trend Prediction: Combines data and news analysis to predict the stock's trend and provides a fear/greed score based on the news sentiment.
• User-Friendly Interface: Built with Streamlit, offering an easy-to-use interface for interacting with the agents.

🛠️ Technologies Used

• CrewAI: For creating and managing custom agents.
• LangChain: To facilitate the integration between tools and the GPT-3.5-turbo model.
• OpenAI GPT-3.5-turbo: The core language model powering the agents' decision-making and analysis.
• Yahoo Finance: For retrieving historical stock price data.
• DuckDuckGo Search: For collecting recent news articles about the stock.
• Streamlit: For the web-based user interface.

⚙️ Installation

To run this project locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/muriloguerreiro/stocks-ai-agent.git
   cd stocks-ai-agent

2. Create a virtual environment (optional but recommended):

   python3 -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables:

   • Create a .env file in the project root directory and add your OpenAI API key:

     OPENAI_API_KEY=your-openai-api-key

5. Run the project:

   streamlit run main.py

🌐 Live Demo

Check out the live demo of the project:

🔗 Deploy Link