reasoning/confidence.py

from core.constants import TOKEN_RATES
from database.db import DatabaseManager
from schemas.enums import DecisionStage, MissionStatus
from schemas.models import EvidenceScore


class ConfidenceEngine:
    """Calculates objective confidence metrics based on evidence attributes."""

    @staticmethod
    def calculate_confidence(
        credibility: float, freshness: float, authority: float, agreement: float, conflict: float
    ) -> EvidenceScore:
        weighted_score = (credibility * 0.30) + (freshness * 0.20) + (authority * 0.25) + (agreement * 0.25)
        penalty = conflict * 0.35
        overall = max(0.0, min(100.0, weighted_score - penalty))

        return EvidenceScore(
            credibility=credibility,
            freshness=freshness,
            authority=authority,
            agreement=agreement,
            conflict=conflict,
            overall_confidence=round(overall, 2),
        )


class TokenCostEngine:
    """Estimates and records operational token usage and cost metrics."""

    RATES = TOKEN_RATES

    @classmethod
    async def track_usage(
        cls,
        db: DatabaseManager,
        mission_id: str,
        agent_id: str,
        prompt_tokens: int = 0,
        completion_tokens: int = 0,
        reasoning_tokens: int = 0,
        vision_tokens: int = 0,
    ) -> float:
        cost = (
            (prompt_tokens * cls.RATES["prompt"])
            + (completion_tokens * cls.RATES["completion"])
            + (reasoning_tokens * cls.RATES["reasoning"])
            + (vision_tokens * cls.RATES["vision"])
        )
        await db.record_tokens(
            mission_id=mission_id,
            agent_id=agent_id,
            prompt_tokens=prompt_tokens,
            completion_tokens=completion_tokens,
            reasoning_tokens=reasoning_tokens,
            vision_tokens=vision_tokens,
            cost_usd=cost,
        )
        await db.save_mission(
            mission_id=mission_id, topic="", status=MissionStatus.IN_PROGRESS, stage=DecisionStage.EXECUTE, total_cost=cost
        )
        return cost