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72 lines
1.8 KiB
Python
72 lines
1.8 KiB
Python
from typing import Any, Dict, List, Optional
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from pydantic import Field
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from cognee.infrastructure.engine import DataPoint
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UNSCORED_SKILL_RUN_SCORE = 0.5
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class ToolCall(DataPoint):
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"""A single tool invocation within a skill run."""
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tool_name: str
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tool_input: Optional[Dict[str, Any]] = None
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tool_output: Optional[str] = None
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success: bool = True
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duration_ms: int = 0
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metadata: dict = {"index_fields": []}
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class CandidateSkill(DataPoint):
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"""A skill considered during routing, with its retrieval score and signals."""
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skill_id: str
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skill_name: str = ""
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skill_description: str = ""
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skill_text: str = ""
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score: float = 0.0
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signals: Optional[Dict[str, Any]] = None
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metadata: dict = {"index_fields": ["skill_description"]}
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class SkillRun(DataPoint):
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"""Record of a skill execution within a session."""
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run_id: str
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session_id: str
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cognee_session_id: str = ""
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task_text: str
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result_summary: str = ""
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success_score: float = UNSCORED_SKILL_RUN_SCORE # 0.0 to 1.0
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# Routing decision
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candidate_skills: List[CandidateSkill] = Field(default_factory=list)
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selected_skill: Optional["Skill"] = None
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selected_skill_id: str = ""
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selected_skill_name: str = ""
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dataset_scope: List[str] = Field(default_factory=list)
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task_pattern_id: str = ""
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router_version: str = ""
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tool_trace: List[ToolCall] = Field(default_factory=list)
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error_type: str = ""
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error_message: str = ""
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started_at_ms: int = 0
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latency_ms: int = 0
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feedback: float = 0.0 # -1.0 to 1.0, 0 = no feedback
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previous_run: Optional["SkillRun"] = None
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metadata: dict = {
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"index_fields": ["task_text", "result_summary"],
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"identity_fields": ["run_id"],
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}
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from .Skill import Skill # noqa: E402
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SkillRun.model_rebuild()
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