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BytesAgain β€Ί Skills β€Ί alphaear-predictor
πŸ¦€ ClawHub

alphaear-predictor

by @zhouzhonglu8-png

Market prediction skill using Kronos. Use when user needs finance market time-series forecasting or news-aware finance market adjustments.

Versionv1.0.0
Downloads680
#legal
TERMINAL
clawhub install alphaear-predictor

πŸ“– About This Skill

name: alphaear-predictor slug: alphaear-predictor version: 1.0.0 description: Market prediction skill using Kronos. Use when user needs finance market time-series forecasting or news-aware finance market adjustments.

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):

    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 scan for the kronos_news_*.pt pattern. Ensure you only place trusted checkpoints in this directory.

    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

    • βš™οΈ 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 scan for the kronos_news_*.pt pattern. Ensure you only place trusted checkpoints in this directory.

    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.