# app.py
import streamlit as st
from models import load_model

# Load the model once
generator = load_model()

# Page configuration
st.set_page_config(
    page_title="DeepSeek Chatbot - ruslanmv.com",
    page_icon="🤖",
    layout="centered"
)

# Initialize session state for chat history
if "messages" not in st.session_state:
    st.session_state.messages = []

# Sidebar for model parameters
with st.sidebar:
    st.header("Model Configuration")
    
    # System message
    system_message = st.text_area(
        "System Message",
        value="You are a friendly Chatbot created by ruslanmv.com",
        height=100
    )
    
    # Generation parameters
    max_tokens = st.slider(
        "Max Tokens",
        min_value=1,
        max_value=4000,
        value=512,
        step=10
    )
    
    temperature = st.slider(
        "Temperature",
        min_value=0.1,
        max_value=4.0,
        value=0.7,
        step=0.1
    )
    
    top_p = st.slider(
        "Top-p (nucleus sampling)",
        min_value=0.1,
        max_value=1.0,
        value=0.9,
        step=0.1
    )

# Main chat interface
st.title("🤖 DeepSeek Chatbot")
st.caption("Powered by ruslanmv.com - Configure parameters in the sidebar")

# Display chat messages
for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

# Chat input
if prompt := st.chat_input("Type your message..."):
    # Add user message to chat history
    st.session_state.messages.append({"role": "user", "content": prompt})
    
    # Display user message
    with st.chat_message("user"):
        st.markdown(prompt)
    
    try:
        # Generate response using the model
        with st.spinner("Generating response..."):
            full_prompt = f"{system_message}\n\nUser: {prompt}\nAssistant:"
            response = generator(
                full_prompt,
                max_length=max_tokens,
                temperature=temperature,
                top_p=top_p,
                do_sample=True,
                num_return_sequences=1
            )[0]['generated_text']
            
            # Extract only the assistant's response
            assistant_response = response.split("Assistant:")[-1].strip()
        
        # Display assistant response
        with st.chat_message("assistant"):
            st.markdown(assistant_response)
        
        # Add assistant response to chat history
        st.session_state.messages.append({"role": "assistant", "content": assistant_response})
    
    except Exception as e:
        st.error(f"An error occurred: {str(e)}")