edge-pipeline-orchestrator

You can automate the edge research pipeline by running the orchestration script with your raw OHLCV data. The pipeline manages the entire workflow from auto-detection and concept synthesis to strategy design, review, and final export.

Edge research orchestration coordinates the end-to-end workflow of developing trading strategies. It automates sequential stages including edge auto-detection, hint extraction, concept synthesis, strategy drafting, review, and executable plan export.

Yes, you need Python along with pandas, numpy, matplotlib, and pandas-datareader installed. These dependencies provide the necessary data manipulation, numerical computation, and visualization environment for executing the orchestration scripts.

Run the orchestrate_edge_pipeline.py script via the command line, passing your OHLCV CSV file path and an output directory. This executes the auto-detection, drafting, and review stages to generate and export final strategy reports.

Yes, this pipeline is designed to coordinate multi-stage edge computing research workflows. It facilitates managing the complete lifecycle from initial raw data processing to final executable trading strategy plans.

The pipeline requires specific Python dependencies including pandas and numpy, and operates via command-line script execution. It is tailored for OHLCV data inputs and outputs strategy reports to a specified directory structure.