AlphaEar Predictor Skill

Overview

This skill utilizes the Kronos model (via KronosPredictorUtility) to perform time-series forecasting and adjust predictions based on news sentiment.

Capabilities

1. Forecast Market Trends

Use scripts/kronos_predictor.py to generate forecasts.

Key Methods:

• predict(ticker, horizon): Generate price forecast.
• adjust_forecast(original_forecast, news_sentiment): Adjust forecast based on recent news sentiment.

Example Usage (Python):

from scripts.utils.kronos_predictor import KronosPredictorUtility
from scripts.utils.database_manager import DatabaseManager

db = DatabaseManager()
predictor = KronosPredictorUtility()

# Forecast
forecast = predictor.predict("600519", horizon="7d")
print(forecast)

Configuration

This skill requires the Kronos model and an embedding model.

1. Kronos Model:

   • Ensure exports/models directory exists in the project root.
   • Place trained news projector weights (e.g., kronos_news_v1.pt) in exports/models/.
   • Or depend on the base model (automatically downloaded).

2. Environment Variables:

   • EMBEDDING_MODEL: Path or name of the embedding model (default: sentence-transformers/all-MiniLM-L6-v2).
   • KRONOS_MODEL_PATH: Optional path to override model loading.

Dependencies

• torch
• transformers
• sentence-transformers
• pandas
• numpy
• scikit-learn