"""Meta-Reasoning Layer for Hermes Agent.

Implements a sovereign self-correction loop where a 'strong' model (Gemini 3.1 Pro)
critiques the plans generated by the primary agent loop before execution.
"""

import logging
from typing import Any, Dict, List, Optional
from agent.gemini_adapter import GeminiAdapter

logger = logging.getLogger(__name__)

class MetaReasoningLayer:
    def __init__(self):
        self.adapter = GeminiAdapter()

    def critique_plan(self, goal: str, proposed_plan: str, context: str) -> Dict[str, Any]:
        """Critiques a proposed plan using Gemini's thinking capabilities."""
        prompt = f"""
Goal: {goal}

Context:
{context}

Proposed Plan:
{proposed_plan}

Please perform a deep symbolic and neuro-symbolic analysis of this plan.
Identify potential risks, logical fallacies, or missing steps.
Suggest improvements to make the plan more sovereign, cost-efficient, and robust.
"""
        try:
            result = self.adapter.generate(
                model="gemini-3.1-pro-preview",
                prompt=prompt,
                system_instruction="You are a Senior Meta-Reasoning Engine for the Hermes Agent. Your goal is to ensure the agent's plans are flawless and sovereign.",
                thinking=True,
                thinking_budget=8000
            )
            return {
                "critique": result["text"],
                "thoughts": result.get("thoughts", ""),
                "grounding": result.get("grounding")
            }
        except Exception as e:
            logger.error(f"Meta-reasoning failed: {e}")
            return {"critique": "Meta-reasoning unavailable.", "error": str(e)}