app.py

import gradio as gr
from transformers import AutoModel
from PIL import Image
import torch

# Load the model
model = AutoModel.from_pretrained("ECOFRI/CXR-LLAVA-v2", trust_remote_code=True)
model = model.to("cuda" if torch.cuda.is_available() else "cpu")

# Define the function to generate the report
def generate_report(image):
    image = Image.open(image).convert("RGB")
    response = model.write_radiologic_report(image)
    return response

# Create the Gradio interface
interface = gr.Interface(
    fn=generate_report,
    inputs=gr.inputs.Image(type="file", label="Upload Chest X-ray Image"),
    outputs=gr.outputs.Textbox(label="Radiologic Report"),
    title="Chest X-ray Report Generator",
    description="Upload a chest X-ray image to generate a radiologic report using the CXR-LLAVA-v2 model."
)

# Launch the interface
interface.launch()