op-task-extractor

To generate a self-contained task script from natural language, provide the operator description to automatically build a standardized {op_name}.py file. The output enforces dependency inlining and includes validation to ensure deterministic execution.

You need get_inputs() and get_init_inputs() functions in your operator automation workflow to ensure forward propagation remains repeatable. These standardized functions define initialization parameters and input data dynamically for the generated task script.

The best way to validate a generated operator task file for deterministic execution is to run the included validation script. This mandatory step executes the standardized single-file task to confirm it runs correctly and produces validated output.

Yes, you can convert an existing Python code file into a standardized single-file task script. Provide the code file path as input to automatically generate the {op_name}.py file with inlined dependencies and required input functions.

Yes, the task generation process strictly enforces inlining of external dependencies for operator scripts. This ensures the resulting single-file task code is fully self-contained and can execute deterministically without external package requirements.