65 lines
2.0 KiB
Python
65 lines
2.0 KiB
Python
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"""Agent sprint ranker slot — placeholder for Principle Gate / Actor execution."""
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from __future__ import annotations
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from typing import Any
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from steering.eval_context import SteeringEvalContext
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from steering.proposals.sprint_commit_context import (
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RankedSprintCommitCandidate,
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SprintCommitCandidate,
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register_sprint_commit_ranker,
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)
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from steering.proposals.sprint_commit_heuristic_v0 import HeuristicV0SprintCommitRanker
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_FALLBACK = HeuristicV0SprintCommitRanker()
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class AgentV1SprintCommitRanker:
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"""
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Agent-gestütztes Ranking — noch nicht aktiv (Principle Gate).
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Kontext kommt aus Snapshot/Operating Context; Scoring über auditierten Actor,
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nicht aus hardcodiertem Prompt. Bis Freigabe: Fallback auf heuristic_v0.
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"""
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key = "agent_v1"
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def rank(
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self,
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ctx: SteeringEvalContext,
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*,
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candidates: list[SprintCommitCandidate],
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read_models: dict[str, Any],
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target_work_cycle_id: str,
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) -> list[RankedSprintCommitCandidate]:
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# TODO(P6+): Actor-Slot + Governance-Pack; KI wählt Subset + Begründung
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ranked = _FALLBACK.rank(
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ctx,
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candidates=candidates,
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read_models=read_models,
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target_work_cycle_id=target_work_cycle_id,
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)
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return [
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RankedSprintCommitCandidate(
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candidate=row.candidate,
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rank=row.rank,
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score=row.score,
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reason_code=row.reason_code,
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summary=f"{row.summary} (Agent-Ranker: Fallback heuristic_v0)",
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factors=row.factors
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+ [
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{
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"code": "ranker_fallback",
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"weight": 0,
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"label": "agent_v1 noch nicht freigegeben",
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}
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],
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ranker_key="agent_v1_fallback",
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)
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for row in ranked
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]
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register_sprint_commit_ranker(AgentV1SprintCommitRanker())
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