Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load the Microsoft BioGPT text generation pipeline
+generator = pipeline("text-generation", model="microsoft/BioGPT")
+
+def generate_medical_text(prompt, temperature, top_p, max_length):
+    # Clamp temperature to at least 0.01 to avoid division by zero errors
+    temperature = max(0.01, float(temperature))
+    
+    # Generate text using the pipeline
+    results = generator(
+        prompt,
+        max_length=int(max_length),
+        temperature=temperature,
+        top_p=float(top_p),
+        do_sample=True,
+        num_return_sequences=1,
+        truncation=True,
+        pad_token_id=generator.tokenizer.eos_token_id # Prevents padding warnings
+    )
+    
+    return results[0]["generated_text"]
+
+# Define interface text
+title = "Medical Text Generator"
+description = (
+    "Designed for experimenting with medical and health-related text — "
+    "clinical notes, symptom descriptions, patient scenarios, and health explanations. "
+    "Powered by Microsoft's `BioGPT` model, which was trained on millions of biomedical research articles."
+)
+
+# Define preset examples (Format: [prompt, temperature, top_p, max_length])
+examples = [["The patient presented with symptoms of", 0.5, 0.9, 120],["Common side effects of this medication include", 0.5, 0.9, 120],["The doctor examined the test results and concluded", 0.5, 0.9, 120],["A healthy diet for someone with diabetes should", 0.5, 0.9, 120],["The difference between a virus and a bacteria is", 0.5, 0.9, 120]
+]
+
+# Build the Gradio interface
+demo = gr.Interface(
+    fn=generate_medical_text,
+    inputs=[
+        gr.Textbox(
+            lines=3, 
+            label="Prompt", 
+            placeholder="Enter a medical prompt here..."
+        ),
+        gr.Slider(
+            minimum=0.1, maximum=2.0, value=0.5, step=0.1, 
+            label="Temperature", 
+            info="Controls how creative/wild the writing is"
+        ),
+        gr.Slider(
+            minimum=0.1, maximum=1.0, value=0.9, step=0.05, 
+            label="Top-p", 
+            info="Controls word diversity"
+        ),
+        gr.Slider(
+            minimum=20, maximum=200, value=120, step=1, 
+            label="Max Length", 
+            info="Controls how much text it generates"
+        )
+    ],
+    outputs=gr.Textbox(label="Generated Text", lines=8),
+    title=title,
+    description=description,
+    examples=examples
+)
+
+if __name__ == "__main__":
+    demo.launch()