Update app.py

app.py

@@ -12,6 +12,80 @@ 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"""
 
+import pytesseract  # Assuming Tesseract OCR is used for image processing
+
+def analyze_reports(files, num_reports):
+    """
+    Process and analyze the uploaded reports.
+
+    Args:
+    files (list): List of uploaded files (PDFs and images).
+    num_reports (int): Number of reports to analyze.
+
+    Returns:
+    str: Analysis results in a formatted text.
+    """
+    # Check if the number of files matches num_reports
+    if len(files) != num_reports:
+        return "Number of uploaded files does not match the specified number of reports."
+
+    # Initialize a list to hold text from each report
+    report_texts = []
+
+    for file in files:
+        # Check file type and process accordingly
+        if file.name.endswith('.pdf'):
+            # Process PDF file
+            pdf_text = pdf_to_text(file.name)
+            report_texts.extend(pdf_text)
+        else:
+            # Process Image file
+            image_text = image_to_text(file)
+            report_texts.append(image_text)
+
+    # Combine texts from all reports
+    combined_text = ' '.join(report_texts)
+
+    # Analyze the combined text (Placeholder for actual analysis logic)
+    analysis_results = analyze_text(combined_text)  # This function needs to be implemented
+
+    return analysis_results
+
+def image_to_text(image_file):
+    """
+    Extract text from an image file using OCR.
+
+    Args:
+    image_file (file): An image file.
+
+    Returns:
+    str: Extracted text from the image.
+    """
+    try:
+        # Read the image file
+        image = Image.open(image_file)
+        # Extract text using OCR
+        extracted_text = pytesseract.image_to_string(image)
+        return extracted_text
+    except Exception as e:
+        return f"Error in text extraction from image: {e}"
+
+def analyze_text(text):
+    """
+    Analyze the extracted text and generate insights.
+
+    Args:
+    text (str): Combined text from all reports.
+
+    Returns:
+    str: Analysis results based on the text.
+    """
+    # Placeholder for text analysis logic
+    # This could involve calling an AI model, processing the text, etc.
+    # Returning a dummy response for demonstration purposes
+    return "Analysis results based on the processed text."
+
+
 with gr.Blocks(css="""#chatbot { font-size: 14px; min-height: 1200; }""") as demo:
 
     gr.Markdown(f'<center><h3>{title}</h3></center>')