Update app.py

app.py

@@ -52,11 +52,7 @@ def index():
 @app.route('/process', methods=['GET','POST'])
 def upload_file():
     try:
-        # Log the headers and request body for debugging
-        #print("Request headers:", request.headers)
-        #print("Request form:", request.form)
-        #print("Request files:", request.files)
-        
+       
         # Check if the 'files' part exists in the request
         if 'files' not in request.files:
             print("No 'files' part in the request")
@@ -87,7 +83,7 @@ def upload_file():
 
         session['uploaded_files'] = uploaded_files  # Store uploaded files in session
         logging.info(f"Files successfully uploaded: {uploaded_files}")
-        return process_file(uploaded_files)
+        return process_file(uploaded_files), 200
 
     except Exception as e:
         logging.error(f"An error occurred during file upload: {e}")
@@ -118,8 +114,6 @@ def process_file(filename):
             logging.warning("No files selected for processing")
             return redirect(url_for('index'))
 
-        BASE_DIR = 'uploads/'
-
         # Joining the base and the requested path
         file_paths = [os.path.join(app.config['UPLOAD_FOLDER'], filename) for filename in uploaded_files]
         logging.info(f"Processing files: {file_paths}")
@@ -133,12 +127,17 @@ def process_file(filename):
             logging.info(f"Extracted text: {extracted_text}")
             logging.info(f"Processed images: {processed_Img}")
 
-            llmText = json_to_llm_str(extracted_text)
-            logging.info(f"LLM text: {llmText}")
-            
-            LLMdata = Data_Extractor(llmText)
-            print("Json Output from model------------>",LLMdata)
-            logging.info(f"LLM data: {LLMdata}")
+            #run the model code only if the text is extracted.
+            if extracted_text:
+                llmText = json_to_llm_str(extracted_text)
+                logging.info(f"LLM text: {llmText}")
+
+                #run the model code only if the text is extracted.
+                LLMdata = Data_Extractor(llmText)
+                print("Json Output from model------------>",LLMdata)
+                logging.info(f"LLM data: {LLMdata}")
+            else:
+                raise ('The text is not detected in the OCR')
 
         except Exception as model_error:
             logging.error(f"Error during LLM processing: {model_error}")