Update app.py

app.py

@@ -8,7 +8,7 @@ import io
 import base64
 import google.generativeai as genai
 import pytesseract  # OCR library for extracting text from images
-import markdown  # add this import at the top
+import markdown  # Convert markdown to HTML
 
 app = Flask(__name__)
 app.secret_key = 'your_secret_key_here'
@@ -97,7 +97,7 @@ def index():
                 logging.debug(f"Saving file to {file_path}")
                 file.save(file_path)
                 
-                # Extract text
+                # Extract text from PDF
                 text = ""
                 with open(file_path, "rb") as pdf_file:
                     pdf_reader = PyPDF2.PdfReader(pdf_file)
@@ -107,7 +107,7 @@ def index():
                             text += page_text
                         logging.debug(f"Extracted text from page {page_num}")
                 
-                # Handle image upload
+                # Handle image upload (if provided)
                 image_text = ""
                 if 'image' in request.files:
                     image_file = request.files['image']
@@ -124,15 +124,15 @@ def index():
                 # Determine scan type
                 scan_type = get_scan_type(combined_text)
                 
-                # Extract images
+                # Extract images from PDF
                 images_data = extract_images_from_pdf(file_path)
                 image_count = len(images_data)
                 logging.debug(f"Extracted {image_count} images from PDF")
                 
-                # Construct the content for Gemini API
+                # Construct the prompt for the Gemini API
                 prompt = f"""
                 You are a professional medical imaging specialist analyzing a {scan_type} scan report.
-                Please provide a comprehensive analysis of this report just tell directly about following points no intro , including:
+                Please provide a comprehensive analysis of this report just tell directly about following points no intro, including:
                 1. Key findings and observations
                 2. Any significant abnormalities or concerns
                 3. Technical quality of the scan
@@ -145,21 +145,22 @@ def index():
                 Please note any limitations in your analysis if the image quality or content is unclear.
                 """
                 
-                # Initialize Gemini client
-                client = genai.Client(api_key="AIzaSyArihOGcyK5KcQR4ntIqNga6bSoq7kM7Yo")
+                # Configure the Gemini API key
+                genai.configure(api_key="AIzaSyArihOGcyK5KcQR4ntIqNga6bSoq7kM7Yo")
                 
                 logging.debug("Calling Gemini API for content generation.")
-                response = client.models.generate_content(
+                response = genai.generate_text(
                     model="gemini-2.0-flash",
-                    contents=prompt
+                    prompt=prompt
                 )
                 
-                analysis_text = response.text
+                # Access the generated content (adjust attribute as needed; here we use 'result')
+                analysis_text = response.result  
                 analysis_html = markdown.markdown(analysis_text)  # convert markdown to HTML
 
                 result = {
-                    'analysis': analysis_text,        # original text (if needed)
-                    'analysis_html': analysis_html,     # HTML version for rendering
+                    'analysis': analysis_text,
+                    'analysis_html': analysis_html,
                     'scan_type': scan_type,
                     'image_count': image_count,
                     'images': images_data
@@ -171,7 +172,7 @@ def index():
                 flash(f"Error processing file: {str(e)}", 'error')
                 return redirect(request.url)
             finally:
-                # Clean up
+                # Clean up the uploaded file
                 if os.path.exists(file_path):
                     os.remove(file_path)
                 logging.debug("Temporary file removed after processing.")