Create app.py

app.py

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+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()