import logging
from backend.services.nvidia_vault import nvidia_key_manager

async def generate_intelligent_follow_up(persona: str, daily_summary: dict) -> str:
    """
    1. Retrieve latest uploaded audio.
    2. Retrieve latest cloud transcript.
    3. Analyze transcript.
    4. Analyze emotional tone.
    5. Analyze activity patterns.
    6. Analyze productivity patterns.
    7. Analyze conversation history.
    8. Analyze Master Vault context.
    9. Analyze Assistant Identity.
    """
    logging.info("Gathering metrics for Intelligent Day Review Greeting...")
    
    # In a full implementation, these would query the actual databases
    # For now, we extract the metadata from the daily_summary passed in
    activity = daily_summary.get("total_events", 0)

    # Classify activity level (used in fallback response selection below)
    if activity > 50:
        activity_pattern = "highly active"
    elif activity > 10:
        activity_pattern = "moderately active"
    else:
        activity_pattern = "quiet day"

    # Use NVIDIA Router logic to execute this specific agentic task
    active_key = nvidia_key_manager.get_healthy_key()
    if active_key:
        logging.info("Using NVIDIA key for Intelligent Greeting generation.")
        # Prompt for full production call (NvidiaModel.GLM_5_1):
        # prompt = (
        #     f"You are {persona.upper()}, acting with a {tone} tone. "
        #     f"Activity: {activity_pattern} ({activity} events)\n"
        #     f"Productivity: {productivity}\nConversations: {conversations}\nVault Context: {vault_context}\n"
        #     "Generate a brief, natural follow-up response."
        # )
        # return call_nvidia_api(NvidiaModel.GLM_5_1, prompt, active_key)
        
    # Fallback simulation
    if activity_pattern == "quiet day":
        return "Looking at today's conversations, it seems today was a quieter day focused mostly on development work and system planning. How did your day go?"
    else:
        return "Today seemed more active than usual with several problem-solving sessions and project discussions. What was the highlight of your day?"