app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_name = "thrishala/mental_health_chatbot"
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

def generate_response(user_input):
    inputs = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors="pt")
    output = model.generate(inputs, max_length=250, pad_token_id=tokenizer.eos_token_id)
    response = tokenizer.decode(output[:, inputs.shape[-1]:][0], skip_special_tokens=True)
    return response

interface = gr.Interface(
    fn=generate_response,
    inputs="text",
    outputs="text",
    title="Mental Health Chatbot",
    description="A chatbot providing empathetic support and resources for mental health."
)

if __name__ == "__main__":
    interface.launch()