91 lines
2.9 KiB
Python
91 lines
2.9 KiB
Python
import logging
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from datetime import datetime, timezone
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from typing import Optional
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from orchestrator.config import OrchestratorConfig
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from orchestrator.contracts.result_contract import FinalSignal, Signal
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logger = logging.getLogger(__name__)
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def _sign(x: float) -> int:
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"""Return +1, -1, or 0."""
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if x > 0:
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return 1
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elif x < 0:
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return -1
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return 0
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class SignalMerger:
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def __init__(self, config: OrchestratorConfig) -> None:
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self._config = config
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def merge(
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self,
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quant: Optional[Signal],
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llm: Optional[Signal],
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degradation_reasons: Optional[list[str]] = None,
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) -> FinalSignal:
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now = datetime.now(timezone.utc)
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reasons = tuple(dict.fromkeys(code for code in (degradation_reasons or []) if code))
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# 两者均失败
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if quant is None and llm is None:
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raise ValueError("both quant and llm signals are None")
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ticker = (quant or llm).ticker # type: ignore[union-attr]
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# 只有 LLM（quant 失败）
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if quant is None:
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return FinalSignal(
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ticker=ticker,
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direction=llm.direction,
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confidence=min(llm.confidence * self._config.llm_solo_penalty,
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self._config.llm_weight_cap),
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quant_signal=None,
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llm_signal=llm,
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timestamp=now,
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degrade_reason_codes=reasons,
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)
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# 只有 Quant（llm 失败）
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if llm is None:
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return FinalSignal(
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ticker=ticker,
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direction=quant.direction,
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confidence=min(quant.confidence * self._config.quant_solo_penalty,
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self._config.quant_weight_cap),
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quant_signal=quant,
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llm_signal=None,
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timestamp=now,
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degrade_reason_codes=reasons,
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)
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# 两者都有：加权合并
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# Cap each signal's contribution before merging
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quant_conf = min(quant.confidence, self._config.quant_weight_cap)
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llm_conf = min(llm.confidence, self._config.llm_weight_cap)
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weighted_sum = (
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quant.direction * quant_conf
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+ llm.direction * llm_conf
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)
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final_direction = _sign(weighted_sum)
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if final_direction == 0:
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logger.info(
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"SignalMerger: weighted_sum=0 for %s — signals cancel out, HOLD",
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ticker,
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)
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total_conf = quant_conf + llm_conf
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final_confidence = abs(weighted_sum) / total_conf if total_conf > 0 else 0.0
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return FinalSignal(
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ticker=ticker,
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direction=final_direction,
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confidence=final_confidence,
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quant_signal=quant,
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llm_signal=llm,
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timestamp=now,
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degrade_reason_codes=reasons,
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)
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