Update app.py

app.py

@@ -22,12 +22,9 @@ qwen_model = Qwen2VLForConditionalGeneration.from_pretrained(
 # Processor for Qwen2-VL
 processor = AutoProcessor.from_pretrained("Qwen/Qwen2-VL-7B-Instruct", trust_remote_code=True)
 
-# Global variable to store extracted text
-extracted_text = ""
-
+# Function for OCR and text extraction
 @spaces.GPU(duration=120)  # Increased GPU duration to 120 seconds
 def ocr_and_extract(image):
-    global extracted_text
     try:
         # Save the uploaded image temporarily
         temp_image_path = "temp_image.jpg"
@@ -88,7 +85,7 @@ def ocr_and_extract(image):
         traceback.print_exc()
         return f"Error: {error_message}"
 
-def search_keywords(keywords):
+def search_keywords(extracted_text, keywords):
     if not extracted_text:
         return "No text extracted yet. Please upload an image."
 
@@ -105,7 +102,7 @@ with gr.Blocks() as iface:
     # Image upload and text extraction section
     with gr.Column():
         img_input = gr.Image(type="pil", label="Upload an Image")
-        extracted_output = gr.HTML(label="Extracted Text")  # Removed 'interactive' argument
+        extracted_output = gr.Textbox(label="Extracted Text", interactive=False)  # Use Textbox to store text
 
         # Functionality to trigger the OCR and extraction
         img_button = gr.Button("Extract Text")
@@ -118,6 +115,6 @@ with gr.Blocks() as iface:
 
         # Functionality to search within the extracted text
         search_button = gr.Button("Search")
-        search_button.click(fn=search_keywords, inputs=search_input, outputs=search_output)
+        search_button.click(fn=search_keywords, inputs=[extracted_output, search_input], outputs=search_output)
 
 iface.launch()