app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

# Load your LOCAL model (update this path)
MODEL_PATH = "./aba-retrained-final"

# Initialize components
tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_PATH)

def ask_aba(question):
    inputs = tokenizer(f"question: {question}", return_tensors="pt")
    outputs = model.generate(**inputs, max_length=150)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# ABA Therapy Assistant")
    with gr.Row():
        question = gr.Textbox(label="Ask about ABA")
        output = gr.Textbox(label="Answer")
    gr.Examples(
        examples=["What is positive reinforcement?", "How to reduce tantrums?"],
        inputs=question
    )
    question.submit(ask_aba, inputs=question, outputs=output)

demo.launch()