Architecting the Adaptive Forecasting Pipeline

Design an end-to-end time series forecasting pipeline using Apache Airflow. Outline the DAGs required for data ingestion, preprocessing, semantic abstraction generation, LLM-based forecasting, and a feedback loop for continuous learning/adaptation. Specify how historical data, new observations, and contextual information (e.g., metadata, events) will flow through the system. Detail how Weights & Biases will be integrated to track experiments, monitor forecasting performance, and visualize the impact of adaptation steps.