app.py

import gradio as gr

# Import modules
from models.image_analyzer import ImageAnalyzer
from models.multimodal_fusion import MultimodalFusion
from models.text_analyzer import TextAnalyzer
from utils.visualization import create_combined_visualization


def process_input(image, medical_report):
    """Process the image and text inputs and provide combined analysis"""
    # Initialize analyzers
    image_analyzer = ImageAnalyzer()
    text_analyzer = TextAnalyzer()
    fusion_model = MultimodalFusion()

    # Analyze inputs
    image_results = image_analyzer.analyze(image)
    text_results = text_analyzer.analyze(medical_report)

    # Fuse insights
    combined_results = fusion_model.fuse_insights(image_results, text_results)

    # Visualize results
    visualization = create_combined_visualization(
        image, image_results, text_results, combined_results
    )

    # Format results for display
    image_findings = "\n".join(
        [
            f"{k}: {v:.2f}" if isinstance(v, float) else f"{k}: {v}"
            for k, v in image_results.items()
        ]
    )
    text_findings = "\n".join(
        [f"{k}: {v}" for k, v in text_results.items() if k != "Entities"]
    )
    entities = ", ".join(text_results.get("Entities", []))

    recommendation = combined_results.get("Recommendation", "No recommendation")
    confidence = combined_results.get("Confidence", "N/A")

    return (
        visualization,
        image_findings,
        text_findings,
        entities,
        recommendation,
        confidence,
    )


# Create Gradio interface
with gr.Blocks(title="MediSync: Multi-Modal Medical Analysis System") as demo:
    gr.Markdown("# MediSync: Multi-Modal Medical Analysis System")
    gr.Markdown(
        "Upload a chest X-ray image and provide a medical report for comprehensive analysis"
    )

    with gr.Row():
        with gr.Column():
            image_input = gr.Image(type="pil", label="Upload X-ray Image")
            text_input = gr.Textbox(lines=10, label="Enter Medical Report")
            submit_btn = gr.Button("Analyze")

        with gr.Column():
            output_image = gr.Image(type="pil", label="Visualization")

            with gr.Tab("Summary"):
                recommendation_output = gr.Textbox(label="Recommendation")
                confidence_output = gr.Textbox(label="Confidence Score")

            with gr.Tab("Detailed Results"):
                image_output = gr.Textbox(label="Image Analysis")
                text_output = gr.Textbox(label="Text Analysis")
                entities_output = gr.Textbox(label="Detected Medical Entities")

    submit_btn.click(
        process_input,
        inputs=[image_input, text_input],
        outputs=[
            output_image,
            image_output,
            text_output,
            entities_output,
            recommendation_output,
            confidence_output,
        ],
    )

    gr.Markdown("""
    ## About MediSync
    
    MediSync is an AI-powered healthcare solution that combines X-ray image analysis with patient report text processing 
    to provide comprehensive medical insights.
    
    **Note:** This system is designed as a support tool and should not replace professional medical diagnosis. 
    Always consult with healthcare professionals for medical decisions.
    """)

# Launch the app
if __name__ == "__main__":
    demo.launch()