import streamlit as st
from groq import Groq
import os
from dotenv import load_dotenv

# 🔐 Load .env file
load_dotenv()

# 🔐 Get API key safely
api_key = os.getenv("GROQ_API_KEY")

# ❌ Safety check (IMPORTANT)
if not api_key:
    st.error("GROQ_API_KEY not found. Please check your .env file.")
    st.stop()

# 🤖 Create Groq client
client = Groq(api_key=api_key)

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

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

# 💬 Input box
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 history
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']}")