Make PROGRESS output messages visible without --debug flag

vidai/worker_analysis.py

@@ -194,8 +194,7 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id_int=None,
             'message': 'Initializing analysis job'
         })
         comm.send_message(progress_msg)
-        if get_debug():
-            print(f"PROGRESS: Job {job_id_int} - 5% - Initializing analysis job")
+        print(f"PROGRESS: Job {job_id_int} - 5% - Initializing analysis job")
 
     torch.cuda.empty_cache()
     total_tokens = 0
@@ -214,8 +213,7 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id_int=None,
             'message': f'Model {model_path.split("/")[-1]} loaded successfully'
         })
         comm.send_message(progress_msg)
-        if get_debug():
-            print(f"PROGRESS: Job {job_id_int} - 8% - Model loaded successfully")
+        print(f"PROGRESS: Job {job_id_int} - 8% - Model loaded successfully")
 
     # Get system prompt
     print(f"DEBUG: Retrieving system prompt for job {job_id_int}")
@@ -241,8 +239,7 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id_int=None,
                 'message': f'Extracted {total_frames} frames'
             })
             comm.send_message(progress_msg)
-            if get_debug():
-                print(f"PROGRESS: Job {job_id_int} - 10% - Extracted {total_frames} frames")
+            print(f"PROGRESS: Job {job_id_int} - 10% - Extracted {total_frames} frames")
 
         descriptions = []
 
@@ -259,8 +256,7 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id_int=None,
                     'message': f'Processing frame {i+1}/{total_frames} at {ts:.1f}s'
                 })
                 comm.send_message(progress_msg)
-                if get_debug():
-                    print(f"PROGRESS: Job {job_id_int} - {progress_percent}% - Processing frame {i+1}/{total_frames}")
+                print(f"PROGRESS: Job {job_id_int} - {progress_percent}% - Processing frame {i+1}/{total_frames}")
 
             # Check for cancellation
             if job_id_int and check_job_cancelled(job_id_int):
@@ -295,8 +291,7 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id_int=None,
                     'message': f'Completed frame {i+1}/{total_frames} ({progress_percent}%)'
                 })
                 comm.send_message(progress_msg)
-                if get_debug():
-                    print(f"PROGRESS: Job {job_id_int} - {progress_percent}% - Completed frame {i+1}/{total_frames}")
+                print(f"PROGRESS: Job {job_id_int} - {progress_percent}% - Completed frame {i+1}/{total_frames}")
 
         if output_dir:
             import shutil
@@ -313,8 +308,7 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id_int=None,
                 'message': 'Generating video summary'
             })
             comm.send_message(progress_msg)
-            if get_debug():
-                print(f"PROGRESS: Job {job_id_int} - 85% - Generating video summary")
+            print(f"PROGRESS: Job {job_id_int} - 85% - Generating video summary")
 
         # Check for cancellation before summary
         if job_id_int and check_job_cancelled(job_id_int):
@@ -367,8 +361,7 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id_int=None,
                 'message': 'Analysis completed'
             })
             comm.send_message(progress_msg)
-            if get_debug():
-                print(f"PROGRESS: Job {job_id_int} - 100% - Analysis completed")
+            print(f"PROGRESS: Job {job_id_int} - 100% - Analysis completed")
 
         result = f"Frame Descriptions:\n" + "\n".join(descriptions) + f"\n\nSummary:\n{summary}"
         return result, total_tokens
@@ -384,8 +377,7 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id_int=None,
                 'message': 'Starting image analysis'
             })
             comm.send_message(progress_msg)
-            if get_debug():
-                print(f"PROGRESS: Job {job_id_int} - 20% - Starting image analysis")
+            print(f"PROGRESS: Job {job_id_int} - 20% - Starting image analysis")
 
         # Check for cancellation before processing image
         if job_id_int and check_job_cancelled(job_id_int):
@@ -401,8 +393,7 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id_int=None,
                 'message': 'Processing image with AI model'
             })
             comm.send_message(progress_msg)
-            if get_debug():
-                print(f"PROGRESS: Job {job_id_int} - 50% - Processing image with AI model")
+            print(f"PROGRESS: Job {job_id_int} - 50% - Processing image with AI model")
 
         result, tokens = analyze_single_image(media_path, full_prompt, model)
         total_tokens += tokens
@@ -417,8 +408,7 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id_int=None,
                 'message': 'Finalizing analysis results'
             })
             comm.send_message(progress_msg)
-            if get_debug():
-                print(f"PROGRESS: Job {job_id_int} - 90% - Finalizing analysis results")
+            print(f"PROGRESS: Job {job_id_int} - 90% - Finalizing analysis results")
 
         # Send final progress update
         if comm:
@@ -429,8 +419,7 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id_int=None,
                 'message': 'Image analysis completed successfully'
             })
             comm.send_message(progress_msg)
-            if get_debug():
-                print(f"PROGRESS: Job {job_id_int} - 100% - Image analysis completed successfully")
+            print(f"PROGRESS: Job {job_id_int} - 100% - Image analysis completed successfully")
 
         torch.cuda.empty_cache()
         return result, total_tokens
@@ -468,8 +457,7 @@ def worker_process(backend_type: str):
                     interval = data.get('interval', 10)
                     job_id = message.msg_id  # Use message ID for job identification
                     job_id_int = int(message.msg_id.split('_')[1])  # Extract integer job ID
-                    if get_debug():
-                        print(f"PROGRESS: Job {job_id_int} accepted - Starting analysis")
+                    print(f"PROGRESS: Job {job_id_int} accepted - Starting analysis")
                     print(f"DEBUG: Starting analysis of {media_path} with model {model_path} for job {job_id}")
                     result, tokens_used = analyze_media(media_path, prompt, model_path, interval, job_id_int, comm)
                     print(f"DEBUG: Analysis completed for job {message.msg_id}, used {tokens_used} tokens")