mirror of
https://github.com/google-gemini/gemini-cli.git
synced 2026-07-11 02:20:48 -07:00
Chad
100 lines
3.7 KiB
Python
100 lines
3.7 KiB
Python
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,
|
|
}) |