alphaear-predictor

# 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 ### 1. Forecast Market Trends **Workflow:** 1. **Generate Base Forecast**: Use `scripts/kronos_predictor.py` (via `KronosPredictorUtility`) to generate the technical/quantitative forecast. 2. **Adjust Forecast (Agentic)**: Use the **Forecast Adjustment Prompt** in `references/PROMPTS.md` to subjectively adjust the numbers based on latest news/logic. **Key Tools:** - `KronosPredictorUtility.get_base_forecast(df, lookback, pred_len, news_text)`: Returns `List[KLinePoint]`. **Example Usage (Python):** ```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). > [!CAUTION] > **Model Security**: This skill loads model weights from `exports/models`. We use `weights_only=True` and only sca...