app.py

import os
import requests
import gradio as gr

# Load API Key
GROQ_API_KEY = os.getenv("GROQ_API_KEY")
GROQ_API_URL = "https://api.groq.com/openai/v1/chat/completions"
HEADERS = {
    "Authorization": f"Bearer {GROQ_API_KEY}",
    "Content-Type": "application/json"
}

# Core logic
def groq_chatbot(message, history):
    system_prompt = (
        "You are a helpful assistant. Always answer clearly and provide 3 follow-up suggestions at the end.\n\n"
        "Structure your response like:\n\n"
        "Answer:\n<response>\n\nSuggestions:\n1. <...>\n2. <...>\n3. <...>"
    )

    # Start with system prompt
    messages = [{"role": "system", "content": system_prompt}]

    # Add chat history
    for user_msg, bot_msg in history:
        messages.append({"role": "user", "content": user_msg})
        messages.append({"role": "assistant", "content": bot_msg})

    # Add the new user message
    messages.append({"role": "user", "content": message})

    # Prepare payload
    payload = {
        "model": "llama3-8b-8192",
        "messages": messages,
        "temperature": 0.7
    }

    # Send request
    response = requests.post(GROQ_API_URL, headers=HEADERS, json=payload)

    # Return result
    if response.status_code == 200:
        return response.json()["choices"][0]["message"]["content"]
    else:
        return "❌ Failed to get response from Groq API."

# Gradio ChatInterface
chatbot = gr.ChatInterface(
    fn=groq_chatbot,
    title="🧠 Groq ChatGPT Clone",
    description="Ask anything! Get a helpful answer and 3 smart follow-up suggestions.",
    theme="soft",
    examples=[
        "What is quantum computing?",
        "How does e-commerce logistics work?",
        "Explain photosynthesis"
    ]
)

if __name__ == "__main__":
    chatbot.launch()