Update app.py

app.py

@@ -527,7 +527,7 @@ def handle_file_upload_and_analyze(file_obj, mode: str, classifier) -> tuple:
     Handle file upload, OCR processing, and text analysis
     
     Args:
-        file_obj: Uploaded file object from Gradio
+        file_obj: Uploaded file object from Gradio (bytes when using type="binary")
         mode: Analysis mode (quick or detailed)
         classifier: The TextClassifier instance
         
@@ -541,11 +541,33 @@ def handle_file_upload_and_analyze(file_obj, mode: str, classifier) -> tuple:
             "No file uploaded for analysis"
         )
     
-    # Create a temporary file
-    with tempfile.NamedTemporaryFile(delete=False, suffix=Path(file_obj.name).suffix) as temp_file:
+    # Create a temporary file with an appropriate extension based on content
+    # Since we don't have the original filename when using binary mode,
+    # we'll use a generic extension based on simple content detection
+    
+    # Simple content type detection
+    content_start = file_obj[:20]  # Look at the first few bytes
+    
+    # Default to .bin extension
+    file_ext = ".bin"
+    
+    # Try to detect PDF files
+    if content_start.startswith(b'%PDF'):
+        file_ext = ".pdf"
+    # For images, detect by common magic numbers
+    elif content_start.startswith(b'\xff\xd8'):  # JPEG
+        file_ext = ".jpg"
+    elif content_start.startswith(b'\x89PNG'):  # PNG
+        file_ext = ".png"
+    elif content_start.startswith(b'GIF'):      # GIF
+        file_ext = ".gif"
+    # Add more content type detection as needed
+    
+    # Create a temporary file with the detected extension
+    with tempfile.NamedTemporaryFile(delete=False, suffix=file_ext) as temp_file:
         temp_file_path = temp_file.name
-        # Write uploaded file to the temporary file
-        temp_file.write(file_obj.read())
+        # Write uploaded file data to the temporary file
+        temp_file.write(file_obj)
     
     try:
         # Process the file with OCR