import streamlit as st
from groq import Groq
import os

# 🔐 Get API key from Hugging Face secrets
api_key = os.getenv("GROQ_API_KEY")

# Create client
client = Groq(api_key=api_key)

# 🔤 Manual Tokenizer
def manual_tokenizer(text):
    text = text.lower()
    text = text.replace(".", "").replace(",", "").replace("!", "").replace("?", "")
    tokens = text.split()
    return tokens

# 🤖 Chat Function
def chat_with_groq(user_input, messages):
    tokens = manual_tokenizer(user_input)
    processed_text = " ".join(tokens)

    messages.append({"role": "user", "content": processed_text})

    response = client.chat.completions.create(
        model="llama-3.1-8b-instant",
        messages=messages
    )

    reply = response.choices[0].message.content
    messages.append({"role": "assistant", "content": reply})

    return reply

# 🎨 Streamlit UI
st.set_page_config(page_title="Chatbot", page_icon="💬")

st.title("💬 AI Chatbot (Groq + Streamlit)")

# Session state for memory
if "messages" not in st.session_state:
    st.session_state.messages = [
        {"role": "system", "content": "You are a helpful chatbot."}
    ]

# Chat input
user_input = st.text_input("You:")

if st.button("Send") and user_input:
    reply = chat_with_groq(user_input, st.session_state.messages)

# Display chat
for msg in st.session_state.messages[1:]:
    if msg["role"] == "user":
        st.write(f"👤 You: {msg['content']}")
    else:
        st.write(f"🤖 Bot: {msg['content']}")