Create app.py

app for my health summarizer app.

app.py

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+import torch
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+MODEL_NAME = "google/flan-t5-small"
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME).to(DEVICE)
+
+DISCLAIMER = (
+    "Disclaimer: This tool provides general health information only. "
+    "It is not medical advice and does not replace consultation with a qualified healthcare professional. "
+    "For diagnosis, treatment, or emergencies, please see a doctor or visit a health facility immediately."
+)
+
+def generate_summary(text: str, max_tokens: int = 200) -> str:
+    prompt = (
+        "Summarize the following health information in simple language for a non-medical person:\n\n"
+        f"{text}\n\nSummary:"
+    )
+    inputs = tokenizer(
+        prompt,
+        return_tensors="pt",
+        truncation=True,
+        max_length=1024
+    ).to(DEVICE)
+
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=max_tokens,
+            num_beams=4,
+            early_stopping=True,
+        )
+
+    summary = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return summary.strip()
+
+def summarizer_interface(long_text: str) -> str:
+    if not long_text or len(long_text.strip()) == 0:
+        return "Please paste a health-related text to summarize."
+    summary = generate_summary(long_text)
+    return f"{summary}\n\n{DISCLAIMER}"
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 🩺 Health Document Summarizer (Educational Use Only)")
+    gr.Markdown(
+        "Paste any health-related text. "
+        "The model will summarize it in simpler language. "
+        "Do not use this tool for emergencies or as a replacement for a doctor."
+    )
+
+    input_box = gr.Textbox(
+        label="Input health text",
+        placeholder="Paste health information here...",
+        lines=10
+    )
+    output_box = gr.Textbox(
+        label="Summarized explanation",
+        lines=10
+    )
+    summarize_button = gr.Button("Summarize")
+
+    summarize_button.click(
+        summarizer_interface,
+        inputs=input_box,
+        outputs=output_box
+    )
+
+if __name__ == "__main__":
+    demo.launch()