Semantic Frame

Token-efficient semantic compression for numerical data

Converts raw numerical data from NumPy, Pandas, and Polars arrays into natural language descriptions optimized for LLM consumption. Performs trend detection, volatility analysis, anomaly detection, seasonality assessment, and data quality checks. Achieves 95%+ token reduction by replacing thousands of data points with concise semantic summaries. Includes specialized trading module for financial applications.