import streamlit as st
from langchain_google_genai import ChatGoogleGenerativeAI 
from dotenv import load_dotenv
import os

# Load environment variables
load_dotenv()

# Initialize the language model
llm = ChatGoogleGenerativeAI(model="gemini-1.5-pro",
                             temperature=0.6,
                             google_api_key=os.getenv("GOOGLE_API_KEY"))

# Set Streamlit page configuration
st.set_page_config(page_title="Q&A Chatbot", page_icon="🤖", layout="centered", initial_sidebar_state="auto")

# Main application interface
st.header("Quest Bot")

# Function to handle user input and model response
def chat(input_question):
    try:
        # Get response from the model
        with st.spinner("getting response..."):
            response = llm.invoke(input_question)
            return response.content
    except ValueError as ve:
        st.error(f"ValueError: {str(ve)}")
    except Exception as e:
        st.error(f"Error: {str(e)}")
    return None

# Initialize conversation history
conversation = []

# User input for the question
input_question = st.text_input("Input your question here: ")

# Button to submit the question
if st.button("Ask"):
    if input_question:
        st.spinner("getting response...")
        # Add user input to conversation history
        conversation.append(f"You: {input_question}")
        
        # Get response from the model
        response = chat(input_question)
        
        if response:
            # Add model response to conversation history
            conversation.append(f"Quest Bot: {response}")
            
            # Display conversation history
            st.subheader("Conversation")
            for message in conversation:
                st.write(message)
    else:
        # Show a warning if no question is input
        st.warning("Please input a question.")