README.md

metadata

title: FinRobot - AI Agent Platform for Financial Analysis
emoji: 🤖
colorFrom: blue
colorTo: purple
sdk: streamlit
sdk_version: 1.28.0
app_file: app.py
pinned: false
license: apache-2.0
short_description: AI Agent Platform for Financial Analysis

🤖 FinRobot - AI Agent Platform for Financial Analysis

FinRobot is an AI Agent Platform that transcends the scope of FinGPT, representing a comprehensive solution meticulously designed for financial applications. It integrates a diverse array of AI technologies, extending beyond mere language models. This expansive vision highlights the platform's versatility and adaptability, addressing the multifaceted needs of the financial industry.

🌟 Key Features

1. Market Forecaster Agent 📈

• Predicts stock movements using company ticker, financials, and market news
• Real-time market analysis and sentiment tracking
• Advanced technical and fundamental analysis

2. Financial Analyst Agent 📋

• Generates comprehensive equity research reports from 10-K forms
• Financial statement analysis and risk assessment
• Automated PDF report generation

3. Trade Strategist Agent ⚡

• Advanced trading strategies with multimodal capabilities
• Real-time portfolio optimization
• Risk management and performance tracking

🚀 How to Use

1. Select Agent Type: Choose from Market Forecaster, Financial Analyst, or Trade Strategist
2. Configure Parameters: Enter company ticker, analysis type, or strategy preferences
3. Run Analysis: Click the analyze button to get AI-powered insights
4. View Results: Get detailed analysis, predictions, or reports

🏗️ Architecture

The overall framework of FinRobot is organized into four distinct layers:

1. Financial AI Agents Layer: Includes Financial Chain-of-Thought (CoT) prompting for complex analysis
2. Financial LLMs Algorithms Layer: Configures specially tuned models for specific domains
3. LLMOps and DataOps Layers: Multi-source integration strategy for optimal LLM selection
4. Multi-source LLM Foundation Models Layer: Supports plug-and-play functionality of various LLMs

🔧 Technical Stack

• Backend: Python, Streamlit
• AI Framework: AutoGen, LangChain
• Financial Data: Finnhub, Yahoo Finance, SEC API
• Visualization: Matplotlib, MPLFinance
• Document Processing: ReportLab, PyPDF2

📚 Documentation

For detailed documentation and tutorials, visit:

• GitHub Repository
• Whitepaper
• Discord Community

⚠️ Disclaimer

The codes and documents provided herein are released under the Apache-2.0 license. They should not be construed as financial counsel or recommendations for live trading. It is imperative to exercise caution and consult with qualified financial professionals prior to any trading or investment actions.

🤝 Contributing

We welcome contributions! Please see our Contributing Guidelines for details.

📄 License

This project is licensed under the Apache-2.0 License - see the LICENSE file for details.

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