File size: 2,461 Bytes
b0e350e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | 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() |