60 lines
1.5 KiB
Python
60 lines
1.5 KiB
Python
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from typing import Dict, List, Optional
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from pydantic import BaseModel, Field
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class TestItemEntry(BaseModel):
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id: str
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content: str
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class TestCaseEntry(BaseModel):
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id: str
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item_id: str
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operation_steps: List[str]
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test_content: str
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expected_result_placeholder: str
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class ExpectedResultEntry(BaseModel):
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id: str
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case_id: str
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result: str
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class StepLogEntry(BaseModel):
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step_name: str
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input_summary: str
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output_summary: str
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success: bool
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fallback_used: bool
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duration_ms: float
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class TestingPipelineRequest(BaseModel):
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requirement_text: str = Field(..., min_length=1)
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requirement_type: Optional[str] = None
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knowledge_base_ids: List[int] = []
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retrieval_top_k: int = Field(default=8, ge=1, le=20)
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knowledge_context: Optional[str] = None
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use_model_generation: bool = True
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max_items_per_group: int = Field(default=12, ge=4, le=30)
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cases_per_item: int = Field(default=2, ge=1, le=5)
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max_focus_points: int = Field(default=6, ge=3, le=12)
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max_llm_calls: int = Field(default=10, ge=0, le=100)
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debug: bool = False
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class TestingPipelineResponse(BaseModel):
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trace_id: str
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requirement_type: str
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reason: str
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candidates: List[str]
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test_items: Dict[str, List[TestItemEntry]]
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test_cases: Dict[str, List[TestCaseEntry]]
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expected_results: Dict[str, List[ExpectedResultEntry]]
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formatted_output: str
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pipeline_summary: str
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knowledge_used: bool = False
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step_logs: List[StepLogEntry] = []
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