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:

Generate Base Forecast

Use

scripts/kronos_predictor.py

(via

KronosPredictorUtility

) to generate the technical/quantitative forecast.

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.

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).

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