Make all debug and progress messages conditional on --debug flag

vidai/worker_analysis.py

@@ -30,7 +30,7 @@ import time
 import uuid
 from .comm import SocketCommunicator, Message
 from .models import get_model
-from .config import get_system_prompt_content, get_comm_type, get_backend_worker_port
+from .config import get_system_prompt_content, get_comm_type, get_backend_worker_port, get_debug
 
 # Set PyTorch CUDA memory management
 os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'expandable_segments:True'
@@ -186,7 +186,8 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id=None, comm
             'message': 'Initializing analysis job'
         })
         comm.send_message(progress_msg)
-        print(f"PROGRESS: Job {job_id} - 5% - Initializing analysis job")
+        if get_debug():
+            print(f"PROGRESS: Job {job_id} - 5% - Initializing analysis job")
 
     torch.cuda.empty_cache()
     total_tokens = 0
@@ -205,7 +206,8 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id=None, comm
             'message': f'Model {model_path.split("/")[-1]} loaded successfully'
         })
         comm.send_message(progress_msg)
-        print(f"PROGRESS: Job {job_id} - 8% - Model loaded successfully")
+        if get_debug():
+            print(f"PROGRESS: Job {job_id} - 8% - Model loaded successfully")
 
     # Get system prompt
     print(f"DEBUG: Retrieving system prompt for job {job_id}")
@@ -231,7 +233,8 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id=None, comm
                 'message': f'Extracted {total_frames} frames'
             })
             comm.send_message(progress_msg)
-            print(f"PROGRESS: Job {job_id} - 10% - Extracted {total_frames} frames")
+            if get_debug():
+                print(f"PROGRESS: Job {job_id} - 10% - Extracted {total_frames} frames")
 
         descriptions = []
 
@@ -248,7 +251,8 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id=None, comm
                     'message': f'Processing frame {i+1}/{total_frames} at {ts:.1f}s'
                 })
                 comm.send_message(progress_msg)
-                print(f"PROGRESS: Job {job_id} - {progress_percent}% - Processing frame {i+1}/{total_frames}")
+                if get_debug():
+                    print(f"PROGRESS: Job {job_id} - {progress_percent}% - Processing frame {i+1}/{total_frames}")
 
             # Check for cancellation
             if job_id and check_job_cancelled(job_id):
@@ -283,7 +287,8 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id=None, comm
                     'message': f'Completed frame {i+1}/{total_frames} ({progress_percent}%)'
                 })
                 comm.send_message(progress_msg)
-                print(f"PROGRESS: Job {job_id} - {progress_percent}% - Completed frame {i+1}/{total_frames}")
+                if get_debug():
+                    print(f"PROGRESS: Job {job_id} - {progress_percent}% - Completed frame {i+1}/{total_frames}")
 
         if output_dir:
             import shutil
@@ -300,7 +305,8 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id=None, comm
                 'message': 'Generating video summary'
             })
             comm.send_message(progress_msg)
-            print(f"PROGRESS: Job {job_id} - 85% - Generating video summary")
+            if get_debug():
+                print(f"PROGRESS: Job {job_id} - 85% - Generating video summary")
 
         # Check for cancellation before summary
         if job_id and check_job_cancelled(job_id):
@@ -339,7 +345,8 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id=None, comm
                 'message': 'Analysis completed'
             })
             comm.send_message(progress_msg)
-            print(f"PROGRESS: Job {job_id} - 100% - Analysis completed")
+            if get_debug():
+                print(f"PROGRESS: Job {job_id} - 100% - Analysis completed")
 
         result = f"Frame Descriptions:\n" + "\n".join(descriptions) + f"\n\nSummary:\n{summary}"
         return result, total_tokens
@@ -355,7 +362,8 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id=None, comm
                 'message': 'Starting image analysis'
             })
             comm.send_message(progress_msg)
-            print(f"PROGRESS: Job {job_id} - 20% - Starting image analysis")
+            if get_debug():
+                print(f"PROGRESS: Job {job_id} - 20% - Starting image analysis")
 
         # Check for cancellation before processing image
         if job_id and check_job_cancelled(job_id):
@@ -371,7 +379,8 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id=None, comm
                 'message': 'Processing image with AI model'
             })
             comm.send_message(progress_msg)
-            print(f"PROGRESS: Job {job_id} - 50% - Processing image with AI model")
+            if get_debug():
+                print(f"PROGRESS: Job {job_id} - 50% - Processing image with AI model")
 
         result, tokens = analyze_single_image(media_path, full_prompt, model)
         total_tokens += tokens
@@ -386,7 +395,8 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id=None, comm
                 'message': 'Finalizing analysis results'
             })
             comm.send_message(progress_msg)
-            print(f"PROGRESS: Job {job_id} - 90% - Finalizing analysis results")
+            if get_debug():
+                print(f"PROGRESS: Job {job_id} - 90% - Finalizing analysis results")
 
         # Send final progress update
         if comm:
@@ -397,7 +407,8 @@ def analyze_media(media_path, prompt, model_path, interval=10, job_id=None, comm
                 'message': 'Image analysis completed successfully'
             })
             comm.send_message(progress_msg)
-            print(f"PROGRESS: Job {job_id} - 100% - Image analysis completed successfully")
+            if get_debug():
+                print(f"PROGRESS: Job {job_id} - 100% - Image analysis completed successfully")
 
         torch.cuda.empty_cache()
         return result, total_tokens
@@ -434,7 +445,8 @@ def worker_process(backend_type: str):
                     model_path = data.get('model_path', 'Qwen/Qwen2.5-VL-7B-Instruct')
                     interval = data.get('interval', 10)
                     job_id = message.msg_id  # Use message ID for job identification
-                    print(f"PROGRESS: Job {message.msg_id} accepted - Starting analysis")
+                    if get_debug():
+                        print(f"PROGRESS: Job {message.msg_id} 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, comm)
                     print(f"DEBUG: Analysis completed for job {message.msg_id}, used {tokens_used} tokens")