agents/reply_agent.py

# agents/reply_agent.py
import os
from groq import AsyncGroq
from dotenv import load_dotenv

load_dotenv()

client = AsyncGroq(api_key=os.getenv("GROQ_API_KEY"))

async def generate_smart_reply(text: str, sender: str, tone: str) -> str:
    """
    Generates a context-aware email reply using Groq's fast inference.
    """
    prompt = f"""
    You are a highly intelligent email assistant helping Ayoub draft a reply.
    
    Original Email from {sender}:
    \"\"\"
    {text}
    \"\"\"
    
    Task: Draft a complete, ready-to-send reply.
    Tone: {tone}
    
    Strict Instructions:
    - Go straight to the email body. Do not include conversational preambles like "Here is the draft:".
    - Sign off the email as Ayoub.
    - Ensure there are absolutely no placeholder brackets (like [Insert Name Here]).
    - Keep it concise and professional.
    """
    
    try:
        response = await client.chat.completions.create(
            messages=[
                {"role": "system", "content": "You are an expert email communicator."},
                {"role": "user", "content": prompt}
            ],
            # --- FIX: Updated to the currently supported, lightning-fast Llama 3.1 model ---
            model="llama-3.1-8b-instant", 
            temperature=0.6, 
            max_tokens=500
        )
        
        return response.choices[0].message.content.strip()
        
    except Exception as e:
        print(f"⚠️ Groq API Error: {e}")
        raise e