app.py

import chainlit as cl
import google.generativeai as genai

# 🔐 Insert your Gemini API key temporarily for testing (never share publicly!)
GEMINI_API_KEY = "AIzaSyBo1mx-ghrH3EZcj1WrLT7x4L5etHx_Zws"
genai.configure(api_key=GEMINI_API_KEY)

# 🧠 In-memory chat memory
memory = {}

# 🎭 Roles
ROLES = {
    "customer": "You are NovaTech’s polite and empathetic customer support assistant.",
    "employee": "You are NovaTech’s helpful internal assistant for staff.",
    "manager": "You are NovaTech’s insightful business assistant. Be analytical and clear."
}

# ✅ This ensures Chainlit initializes properly
@cl.on_chat_start
async def on_chat_start():
    await cl.Message(
        content="👋 Welcome to **NovaTech Solutions Virtual Assistant!**\nPlease tell me your role: customer, employee, or manager."
    ).send()

@cl.on_message
async def on_message(message: cl.Message):
    user = message.author or "guest"
    user_state = memory.get(user, {"role": "customer", "history": ""})

    text = message.content.strip().lower()

    # If user defines role
    if text in ROLES:
        user_state["role"] = text
        memory[user] = user_state
        await cl.Message(content=f"✅ Got it! You are a **{text}**. How can I assist you today?").send()
        return

    # Build role-aware prompt
    prompt = f"""
{ROLES[user_state['role']]}
Conversation so far:
{user_state['history']}
User: {message.content}
Reply as NovaTech’s assistant with professionalism and empathy.
"""

    try:
        model = genai.GenerativeModel("gemini-1.5-flash")
        response = model.generate_content(prompt)
        reply = response.text.strip()
    except Exception as e:
        reply = f"⚠️ Something went wrong: {e}"

    # Update conversation memory
    user_state["history"] += f"User: {message.content}\nAI: {reply}\n"
    memory[user] = user_state

    await cl.Message(content=reply).send()

# 👇 This line ensures the app initializes correctly when running in Hugging Face
if __name__ == "__main__":
    cl.main()