design_task:
  description: >
    Take the high level requirements described here and prepare a detailed design for the engineer;
    everything should be in 1 python module, but outline the classes and methods in the module.
    Here are the requirements: {requirements}
    IMPORTANT: Only output the design in markdown format, laying out in detail the classes and functions in the module, describing the functionality.
  expected_output: >
    A detailed design for the engineer, identifying the classes and functions in the module.
  agent: engineering_lead
  output_file: src/ai_agentic_coder/output/{module_name}_design.md

code_task:
  description: >
    Write a python module that implements the design described by the engineering lead, in order to achieve the requirements.
    Here are the requirements: {requirements}
  expected_output: >
    A python module that implements the design and achieves the requirements.
    IMPORTANT: Output ONLY the raw Python code without any markdown formatting, code block delimiters, any non python code related text or backticks.
    The output should be valid Python code that can be directly saved to a file and executed.
  agent: backend_engineer
  context:
    - design_task
  output_file: src/ai_agentic_coder/output/{module_name}

frontend_task:
  description: >
    Write a gradio UI in a module app.py that demonstrates the given backend class in {module_name}.
    Assume there is only 1 user, and keep the UI very simple indeed - just a prototype or demo.
    Here are the requirements: {requirements}
  expected_output: >
    A gradio UI in module app.py that demonstrates the given backend class with a public link by setting the share flag to True.
    The file should be ready so that it can be run as-is, in the same directory as the backend module, and it should import the backend class from {module_name}.
    IMPORTANT: Output ONLY the raw Python code without any markdown formatting, code block delimiters, any non python code related text or backticks.
    The output should be valid Python code that can be directly saved to a file and executed.
  agent: frontend_engineer
  context:
    - code_task
  output_file: src/ai_agentic_coder/output/app.py

test_task:
  description: >
    Write unit tests for the given backend module {module_name} and create a test_{module_name} in the same directory as the backend module.
  expected_output: >
    A test_{module_name} module that tests the given backend module.
    IMPORTANT: Output ONLY the raw Python code without any markdown formatting, code block delimiters, or backticks.
    The output should be valid Python code that can be directly saved to a file and executed.
  agent: test_engineer
  context:
    - code_task
  output_file: src/ai_agentic_coder/output/test_{module_name}

python_code_run_task:
  description: >  
    Upload the zip to Google Cloud Storage and run the Python code that was generated.
  expected_output: >
    Signed URL of the zip uploaded to Google Cloud Storage and the live URL of the generated Gradio app.
    IMPORTANT: The tool returns both URLs, so return the exact output returned by the tool without any additional text or formatting.
  agent: python_code_runner
  context:
    - code_task
  output_file: src/ai_agentic_coder/output/gradio_public_url.txt