| import re |
|
|
| def _assert_section_schema( |
| spec: dict, section_name: str, expected_schema: dict |
| ) -> None: |
| """ |
| Asserts that spec[section_name] is a dict containing all expected |
| field names with their required data types. |
| """ |
| section = spec.get(section_name) |
| if not isinstance(section, dict): |
| raise ValueError( |
| f"Missing or invalid object '{section_name}' in workable_spec" |
| ) |
|
|
| for field_name, expected_type in expected_schema.items(): |
| if field_name not in section: |
| raise ValueError(f"Missing '{section_name}' key: {field_name}") |
|
|
| field_value = section[field_name] |
| if isinstance(expected_type, list): |
| element_type = expected_type[0] |
| valid_list = isinstance(field_value, list) and all( |
| isinstance(item, element_type) for item in field_value |
| ) |
| if not valid_list: |
| raise ValueError( |
| f"Key '{field_name}' in '{section_name}' must be a list of " |
| f"{element_type.__name__}" |
| ) |
| elif not isinstance(field_value, expected_type): |
| raise ValueError( |
| f"Key '{field_name}' in '{section_name}' must be of type " |
| f"{expected_type.__name__}" |
| ) |
|
|
| def validate_triage_result(data: dict) -> None: |
| """ |
| Validates the structure of the LLM triage result. |
| Expects an already-parsed dictionary (json.loads is called upstream |
| by the triage orchestrator before invoking this validator). |
| Ensures required metadata, effort estimates, and nested schemas |
| are present when quality is OK. |
| """ |
| if "triage_metadata" not in data: |
| raise ValueError("Missing 'triage_metadata'") |
| |
| metadata = data["triage_metadata"] |
| valid_qualities = ["SPAM", "EMPTY", "NEEDS_INFO", "FEATURE", "OK"] |
| if metadata.get("quality") not in valid_qualities: |
| raise ValueError( |
| f"Invalid or missing 'quality': {metadata.get('quality')}" |
| ) |
|
|
| if metadata.get("quality") == "NEEDS_INFO": |
| comment = metadata.get("comment") |
| if not isinstance(comment, str) or not comment.strip(): |
| metadata["comment"] = ( |
| "Thank you for opening this issue! Additional information (such as " |
| "reproduction steps, environment details, or error logs) is required " |
| "to help us triage and investigate. Please provide any relevant details " |
| "so we can assist you." |
| ) |
|
|
| if metadata.get("quality") == "OK": |
| effort = metadata.get("effort_estimate") |
| if effort not in ["SMALL", "MEDIUM", "LARGE"]: |
| raise ValueError( |
| f"Invalid or missing 'effort_estimate': {effort}" |
| ) |
|
|
| spec = data.get("workable_spec") |
| if not isinstance(spec, dict): |
| raise ValueError("Missing 'workable_spec'") |
| |
| issue_id = spec.get("issue_id") |
| pattern = r"^[a-zA-Z0-9_.-]+/[a-zA-Z0-9_.-]+#[0-9]+$" |
| valid_id = isinstance(issue_id, str) and bool( |
| re.match(pattern, issue_id) |
| ) |
| if not valid_id: |
| raise ValueError( |
| f"Invalid or missing 'issue_id' format: {issue_id}" |
| ) |
|
|
| _assert_section_schema(spec, "summary", { |
| "problem": str, |
| "root_cause": str, |
| "context": str, |
| }) |
| _assert_section_schema(spec, "implementation_plan", { |
| "files_to_modify": [str], |
| "steps": [str], |
| }) |
| _assert_section_schema(spec, "testing_strategy", { |
| "test_file": str, |
| "expected_behavior": str, |
| "verification_steps": [str], |
| "framework": str, |
| }) |
