"""
Eval prompt engine for prompt variation and tracking.

Foundation for eval prompt optimization (full A/B testing in Phase 3).
"""

import logging
from datetime import datetime
from typing import Any
from uuid import uuid4

from .evaluation_models import PromptVersion

logger = logging.getLogger(__name__)


class EvalPromptEngine:
    """
    Eval prompt template system with variation generation.
    
    Foundation for prompt optimization (Phase 2).
    Full A/B testing and learning implemented in Phase 3.
    """

    def __init__(self):
        """Initialize eval prompt engine."""
        self.templates: dict[str, str] = {}
        self.prompt_versions: dict[str, list[PromptVersion]] = {}

    def register_template(self, template_id: str, template: str) -> None:
        """Register an eval prompt template."""
        self.templates[template_id] = template

    def generate_prompt(
        self,
        template_id: str,
        context: dict[str, Any] | None = None,
        variation: int = 0,
    ) -> tuple[str, PromptVersion]:
        """
        Generate eval prompt from template.
        
        Args:
            template_id: Template identifier
            context: Optional context for prompt
            variation: Variation number (0 = base)
            
        Returns:
            Tuple of (prompt_text, PromptVersion)
        """
        template = self.templates.get(template_id, "")
        if not template:
            raise ValueError(f"Template not found: {template_id}")
        
        # Apply context substitutions
        prompt_text = template
        if context:
            for key, value in context.items():
                prompt_text = prompt_text.replace(f"{{{key}}}", str(value))
        
        # Generate variation (simple for now, enhanced in Phase 3)
        if variation > 0:
            prompt_text = self._apply_variation(prompt_text, variation)
        
        # Create prompt version
        version = PromptVersion(
            id=str(uuid4()),
            version=f"{template_id}_v{variation}",
            prompt_text=prompt_text,
            prompt_type="eval",
            created_at=datetime.now(),
            metadata={
                "template_id": template_id,
                "variation": variation,
                "context": context or {},
            },
        )
        
        # Track version
        if template_id not in self.prompt_versions:
            self.prompt_versions[template_id] = []
        self.prompt_versions[template_id].append(version)
        
        return prompt_text, version

    def _apply_variation(self, prompt: str, variation: int) -> str:
        """Apply variation to prompt (simplified for Phase 2)."""
        # Simple variations: adjust instruction style
        variations = [
            prompt,  # Base
            prompt + "\n\nFocus on critical issues first.",
            prompt + "\n\nBe thorough and detailed in your analysis.",
            prompt + "\n\nPrioritize actionable, specific feedback.",
        ]
        
        if variation < len(variations):
            return variations[variation]
        return prompt

    def get_version_history(self, template_id: str) -> list[PromptVersion]:
        """Get version history for a template."""
        return self.prompt_versions.get(template_id, [])

    def track_effectiveness(
        self, version_id: str, outcome: dict[str, Any]
    ) -> None:
        """
        Track prompt effectiveness (foundation for Phase 3).
        
        Args:
            version_id: Prompt version ID
            outcome: Outcome metrics (issues found, quality score, etc.)
        """
        # Store for later analysis (Phase 3)
        logger.debug(f"Tracking effectiveness for {version_id}: {outcome}")

