app.py

import streamlit as st
from transformers import pipeline

# Function to generate a message
def generate_message():
    return "Hello, this is a generated message!"

# Function to load Hugging Face chatbot model
def load_chatbot_model():
pipe = pipeline("conversational", model="alpindale/goliath-120b")
return pipeline
# Use a pipeline as a high-level helper


    

# Main Page with Chatbot
def main():
    st.title("Main Page with Chatbot")
    st.write("Welcome to the Main Page! Type your message to chat with our virtual therapist.")

    # Load the chatbot model
    chatbot_model = load_chatbot_model()

    # User input for the chatbot
    user_input = st.text_input("You: ")

    # Generate response when user enters input
    if user_input:
        response = chatbot_model(user_input, max_length=50, num_return_sequences=1)[0]['generated_text']
        st.text_area("Therapist:", response, height=100)

    # Button to open a new page
    if st.button("Open New Page"):
        open_new_page()

    # Button to generate and show a message
    if st.button("Generate Message"):
        generate_and_show_message()

# Function to open a new page
def open_new_page():
    st.title("New Page")
    st.write("This is the New Page!")

# Function to generate and show a message
def generate_and_show_message():
    message = generate_message()
    st.title("Generated Message")
    st.write(f"This message was generated: {message}")

if __name__ == "__main__":
    main()