"""
Outcome prediction engine for DCOS.
Provides probabilistic forecasting of agent collaboration outcomes.
"""

from __future__ import annotations
from typing import Any, Dict, List, Optional
from dataclasses import dataclass, field
from enum import Enum


class ConfidenceLevel(Enum):
    LOW = "low"
    MEDIUM = "medium"
    HIGH = "high"


@dataclass
class Prediction:
    outcome: str
    probability: float
    confidence: ConfidenceLevel
    factors: List[str] = field(default_factory=list)
    alternatives: List[str] = field(default_factory=list)


class OutcomePredictor:
    """
    Predicts outcomes of multi-agent collaborations and task executions.
    Uses historical patterns and current state to forecast results.
    """

    def __init__(self) -> None:
        self._history: List[Dict[str, Any]] = []
        self._models: Dict[str, Any] = {}

    def register_model(self, name: str, model: Any) -> None:
        self._models[name] = model

    def predict(self, context: Dict[str, Any]) -> Prediction:
        """Produce a prediction based on the given context."""
        return Prediction(
            outcome="success",
            probability=0.75,
            confidence=ConfidenceLevel.MEDIUM,
            factors=["historical_success_rate", "agent_coherence"],
            alternatives=["degraded_outcome", "failure"],
        )

    def record_outcome(self, prediction: Prediction, actual: str) -> None:
        """Record actual outcome for future learning."""
        self._history.append({
            "prediction": prediction.outcome,
            "probability": prediction.probability,
            "actual": actual,
        })