app.py

import urllib.request 
import fitz
import re
import numpy as np
import tensorflow_hub as hub
import openai
import gradio as gr
import os
from sklearn.neighbors import NearestNeighbors


title = 'MediDiagnostix AI'
description = """MediDiagnostix AI allows you to upload medical reports for analysis. Just click a picture of your medical report or upload a pdf report, it will 
 extract, analyze and provide you the medical interpretations of the report, potential diagnoses, and recommended follow-up actions. Furthermore, you can save diagnosis for future reference"""

with gr.Blocks(css="""#chatbot { font-size: 14px; min-height: 1200; }""") as demo:

    gr.Markdown(f'<center><h3>{title}</h3></center>')
    gr.Markdown(description)

    with gr.Row():
        
        with gr.Group():
            gr.Markdown(f'<p style="text-align:center">Enter the number of reports to analyze</p>')
            num_reports = gr.Number(label='Number of Reports', value=1)
            
            with gr.Accordion("Upload Reports"):
                file_upload = gr.File(label='Upload Reports (PDF/Image)', file_types=['.pdf', '.jpg', '.png'], interactive=True, type="file", allow_multiple=True)
            
            analyze_button = gr.Button(value='Analyze Reports')

        with gr.Group():
            analysis_results = gr.Textbox(label='Analysis Results', placeholder="Results will appear here after analysis", lines=20)

    analyze_button.click(
        func=analyze_reports,  # This function needs to be defined to handle the report analysis.
        inputs=[file_upload, num_reports],
        outputs=[analysis_results],
    )

demo.launch()