Refactor batch processing with rich progress tracking and update logging in AIAgent

- Replaced tqdm with rich for enhanced visual progress tracking in batch processing.
- Adjusted logging levels in AIAgent to suppress asyncio debug messages.
- Modified datagen script to reduce number of workers for improved performance.

batch_runner.py

@@ -30,7 +30,8 @@ from datetime import datetime
 from multiprocessing import Pool, Manager, Lock
 import traceback
 
-from tqdm import tqdm
+from rich.progress import Progress, SpinnerColumn, BarColumn, TextColumn, TimeRemainingColumn, MofNCompleteColumn
+from rich.console import Console
 import fire
 
 from run_agent import AIAgent
@@ -643,14 +644,36 @@ class BatchRunner:
             print(f"✅ Created {len(tasks)} batch tasks")
             print(f"🚀 Starting parallel batch processing...\n")
             
-            # Use imap_unordered with tqdm for progress tracking
-            results = list(tqdm(
-                pool.imap_unordered(_process_batch_worker, tasks),
-                total=len(tasks),
-                desc="📦 Batches",
-                unit="batch",
-                ncols=80
-            ))
+            # Use rich Progress for better visual tracking with persistent bottom bar
+            # redirect_stdout/stderr lets rich manage all output so progress bar stays clean
+            results = []
+            console = Console(force_terminal=True)
+            with Progress(
+                SpinnerColumn(),
+                TextColumn("[bold blue]📦 Batches"),
+                BarColumn(bar_width=40),
+                MofNCompleteColumn(),
+                TextColumn("•"),
+                TimeRemainingColumn(),
+                console=console,
+                refresh_per_second=2,
+                transient=False,
+                redirect_stdout=False,
+                redirect_stderr=False,
+            ) as progress:
+                task = progress.add_task("Processing", total=len(tasks))
+                
+                # Temporarily suppress DEBUG logging to avoid bar interference
+                root_logger = logging.getLogger()
+                original_level = root_logger.level
+                root_logger.setLevel(logging.WARNING)
+                
+                try:
+                    for result in pool.imap_unordered(_process_batch_worker, tasks):
+                        results.append(result)
+                        progress.update(task, advance=1)
+                finally:
+                    root_logger.setLevel(original_level)
         
         # Aggregate all batch statistics and update checkpoint
         all_completed_prompts = list(completed_prompts_set)

requirements.txt

@@ -7,3 +7,4 @@ tenacity
 python-dotenv
 fire
 httpx
+rich

run_agent.py

@@ -127,7 +127,8 @@ class AIAgent:
             logging.getLogger('openai._base_client').setLevel(logging.WARNING)
             logging.getLogger('httpx').setLevel(logging.WARNING)
             logging.getLogger('httpcore').setLevel(logging.WARNING)
-            print("🔍 Verbose logging enabled (OpenAI/httpx internal logs suppressed)")
+            logging.getLogger('asyncio').setLevel(logging.WARNING)  # Suppress asyncio debug
+            print("🔍 Verbose logging enabled (OpenAI/httpx/asyncio internal logs suppressed)")
         else:
             # Set logging to INFO level for important messages only
             logging.basicConfig(

run_datagen_images.sh

@@ -17,10 +17,10 @@ python batch_runner.py \
   --model="z-ai/glm-4.7" \
   --base_url="https://openrouter.ai/api/v1" \
   --providers_allowed="gmicloud,siliconflow,atlas-cloud,z-ai,novita" \
-  --num_workers=25 \
+  --num_workers=1 \
   --max_turns=25 \
-  --verbose \
   --ephemeral_system_prompt="When generating an image for the user view the image by using the vision_analyze tool to ensure it is what the user wanted. If it isn't feel free to retry a few times. If none are perfect, choose the best option that is the closest match, and explain its imperfections. If the image generation tool fails, try again a few times. If the vision analyze tool fails, provide the image to the user and explain it is your best effort attempt." \
   2>&1 | tee "$LOG_FILE"
 
 echo "✅ Log saved to: $LOG_FILE"
+#  --verbose \