app.py

# Install necessary libraries
# pip install gradio transformers

from transformers import pipeline
import gradio as gr

# Load the text-generation pipeline
pipe = pipeline("text-generation", model="thrishala/mental_health_chatbot")

# Define the chatbot function
def chatbot_response(input_text):
    # Generate a response using the model
    response = pipe(input_text, max_length=150, num_return_sequences=1, pad_token_id=50256)
    return response[0]['generated_text']

# Create a Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# Mental Health Chatbot")
    gr.Markdown("This chatbot is designed to provide responses for mental health-related queries.")
    
    with gr.Row():
        with gr.Column():
            input_text = gr.Textbox(label="Your Question", placeholder="Ask me anything...")
            submit_button = gr.Button("Submit")
        
        with gr.Column():
            output_text = gr.Textbox(label="Chatbot Response", placeholder="The chatbot will respond here...")
    
    submit_button.click(fn=chatbot_response, inputs=input_text, outputs=output_text)

# Launch the app
demo.launch()