app.py

import os
import streamlit as st
from transformers import pipeline

# Set the Hugging Face API key in the environment (if required)
HUGGINGFACE_API_KEY = st.secrets["huggingface_api_key"]
os.environ["HF_HOME"] = HUGGINGFACE_API_KEY  # Set the Hugging Face API key

# Initialize the text generation pipeline (without passing api_key)
chatbot = pipeline("text-generation", model="microsoft/DialoGPT-medium")

# Initialize the conversation history
if "history" not in st.session_state:
    st.session_state["history"] = []

# Function to get response from the model
def get_chatbot_response(user_input):
    try:
        # Prepare the conversation history for the model
        conversation_history = ""
        for user_input, response in st.session_state["history"][-5:]:  # Limit history to last 5 exchanges
            conversation_history += f"User: {user_input}\nBot: {response}\n"
        
        # Add the current user input to the conversation
        conversation_history += f"User: {user_input}\n"
        
        # Debug: Print the conversation history
        print("Conversation History (Trimmed if Necessary):")
        print(conversation_history)
        
        # Generate response from the model
        response = chatbot(conversation_history, max_length=1000, pad_token_id=50256, num_return_sequences=1)[0]["generated_text"]
        
        # Debug: Print the full response generated by the model
        print("Generated Response (Before Stripping User Input):")
        print(response)
        
        # Remove the user input from the generated response (optional)
        response = response[len(conversation_history):].strip()
        
        # Debug: Print the final response
        print("Final Response (After Stripping User Input):")
        print(response)
        
        return response
    except Exception as e:
        return f"Error: {str(e)}"

# Streamlit interface setup
st.set_page_config(page_title="Smart ChatBot", layout="centered")

# Custom CSS for chat bubbles with full width and emojis
st.markdown("""
    <style>
    .chat-container {
        display: flex;
        flex-direction: column;
        width: 100%;
    }
    .chat-bubble {
        width: 100%;
        padding: 15px;
        margin: 10px 0;
        border-radius: 10px;
        font-size: 18px;
        color: white;
        display: inline-block;
        line-height: 1.5;
    }
    .user-bubble {
        background: #6a82fb; /* Soft blue */
        align-self: flex-end;
        border-radius: 10px 10px 10px 10px;
    }
    .bot-bubble {
        background: #fc5c7d; /* Soft pink */
        align-self: flex-start;
        border-radius: 10px 10px 10px 10px;
    }
    .chat-header {
        text-align: center;
        font-size: 35px;
        font-weight: bold;
        margin-bottom: 20px;
        color: #3d3d3d;
    }
    .emoji {
        font-size: 22px;
        margin-right: 10px;
    }
    </style>
""", unsafe_allow_html=True)

st.markdown('<div class="chat-header">Gemini Chatbot-Your AI Companion 💻</div>', unsafe_allow_html=True)
st.write("Powered by Hugging Face’s DialoGPT model for smart, engaging conversations. 🤖")

with st.form(key="chat_form", clear_on_submit=True):
    user_input = st.text_input("Your message here... ✍️", max_chars=2000, label_visibility="collapsed")
    submit_button = st.form_submit_button("Send 🚀")

    if submit_button:
        if user_input:
            response = get_chatbot_response(user_input)
            if response:
                st.session_state.history.append((user_input, response))
            else:
                st.warning("Bot returned an empty response.")
        else:
            st.warning("Please Enter A Prompt 😅")

if st.session_state["history"]:
    st.markdown('<div class="chat-container">', unsafe_allow_html=True)
    for user_input, response in st.session_state["history"]:
        st.markdown(f'<div class="chat-bubble user-bubble"><span class="emoji">👤</span>You: {user_input}</div>', unsafe_allow_html=True)
        st.markdown(f'<div class="chat-bubble bot-bubble"><span class="emoji">🤖</span>Bot: {response}</div>', unsafe_allow_html=True)
    st.markdown('</div>', unsafe_allow_html=True)