This project implements a mixture of predictive agents to forecast Bitcoin prices. It utilizes various language models through Ollama to generate predictions based on historical price data and current market conditions.
Here's a sample of what the output looks like:
- 💰 Fetches current Bitcoin price from CoinGecko API
- 📅 Uses historical Bitcoin price data (30 days) for trend analysis
- 🤖 Employs multiple language models for diverse predictions:
- llama3
- deepseek-coder-v2
- mistral
- codellama
- qween2
- llava:latest
- 🧮 Aggregates predictions and provides summary statistics
- 🛠️ Implements error handling and logging for robustness
- Python 3.7+
- Ollama installed and configured
- Required Python packages (install via
pip install -r requirements.txt):- dotenv
- requests
- rich
The script will fetch the current Bitcoin price, use various models to make predictions, and display the results in a formatted table along with summary statistics.
The script provides:
- Current Bitcoin price
- Individual model predictions
- A summary table of all predictions
- Aggregated results including:
- Average predicted price
- Corrected prediction (4% lower)
- Price deltas and accuracy percentages
The script logs its operations to a file for debugging and monitoring purposes. Check the log file for detailed information about each run.
Contributions are welcome! Please feel free to submit a Pull Request.
This tool is for educational and research purposes only. Do not use it for actual trading or financial decisions. Always consult with a qualified financial advisor before making investment decisions.