"""Phase 5: Real-time Multi-Agent Consensus.

Implements a "Council of Timmys" for high-stakes decision making.
"""

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

logger = logging.getLogger(__name__)

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

    async def reach_consensus(self, task: str, agent_count: int = 3) -> Dict[str, Any]:
        """Spawns multiple agents to debate a task and reaches consensus."""
        logger.info(f"Reaching consensus for task: {task} with {agent_count} agents.")
        
        # 1. Spawn agents and get their perspectives
        tasks = []
        for i in range(agent_count):
            prompt = f"Provide your perspective on the following task: {task}"
            tasks.append(self.adapter.generate(
                model="gemini-3.1-pro-preview",
                prompt=prompt,
                system_instruction=f"You are Timmy Agent #{i+1}. Provide a unique perspective on the task."
            ))
        
        perspectives = await asyncio.gather(*tasks)
        
        # 2. Moderate the debate
        debate_prompt = "The following are different perspectives on the task:\n"
        for i, p in enumerate(perspectives):
            debate_prompt += f"Agent #{i+1}: {p['text']}\n"
        
        debate_prompt += "\nSynthesize these perspectives and provide a final, consensus-based decision."
        
        result = self.adapter.generate(
            model="gemini-3.1-pro-preview",
            prompt=debate_prompt,
            system_instruction="You are the Council Moderator. Your goal is to synthesize multiple perspectives into a single, high-fidelity decision.",
            thinking=True
        )
        
        return {
            "task": task,
            "perspectives": [p['text'] for p in perspectives],
            "consensus": result["text"]
        }