# Install necessary libraries (add these to requirements.txt):
# streamlit, groq, python-dotenv

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

# Load environment variables from .env
load_dotenv()

# Get the API key
API_KEY = os.getenv("GROQ_API_KEY")
if not API_KEY:
    st.error("API key not found. Please set GROQ_API_KEY in the .env file.")

# Initialize the Groq client
client = Groq(api_key=API_KEY)

# Streamlit app configuration
st.set_page_config(page_title="General Information Chatbot", layout="centered")
st.title("General Information Chatbot")
st.subheader("Ask me anything! I'm here to help you with any kind of information.")

# User input
user_input = st.text_input("Enter your question or query:", "")

# Chatbot logic
if st.button("Ask"):
    if not user_input.strip():
        st.warning("Please enter a valid question.")
    else:
        try:
            # Send the user's query to the LLaMA model
            response = client.chat.completions.create(
                messages=[
                    {"role": "system", "content": "You are a helpful assistant capable of answering general knowledge and informational queries."},
                    {"role": "user", "content": user_input},
                ],
                model="llama-3.3-70b-versatile",  # Correct model name
                temperature=1,
                max_tokens=1024,
                top_p=1,
            )
            # Extract and display the response
            chatbot_response = response.choices[0].message.content
            st.success(f"Chatbot: {chatbot_response}")
        except Exception as e:
            st.error(f"An error occurred: {e}")

# Footer
st.markdown(
    """
    **Disclaimer:** This chatbot is for informational purposes only. 
    Please verify critical information from reliable sources.
    """
)