fix(workflow): remove unused MIN_THREADS / CPU_THRESHOLD env vars

src/strands_tools/workflow.py

@@ -7,7 +7,7 @@
 Key Features:
 -------------
 1. Advanced Task Management:
-   • Parallel execution with dynamic thread pooling
+   • Parallel execution with a fixed-size thread pool
    • Priority-based scheduling (1-5 levels)
    • Complex dependency resolution with validation
    • Timeout and resource controls per task
@@ -25,11 +25,8 @@
    • Automatic tool filtering and validation
    • Support for any combination of tools per task
 
-4. Resource Optimization:
-   • Automatic thread pool scaling (2-8 threads)
-   • Rate limiting with exponential backoff
-   • Resource-aware task distribution
-   • CPU usage monitoring and optimization
+4. Rate Limiting:
+   • Exponential backoff on retries
 
 5. Reliability Features:
    • Persistent state storage with real-time monitoring
@@ -130,9 +127,7 @@
 os.makedirs(WORKFLOW_DIR, exist_ok=True)
 
 # Default thread pool settings
-MIN_THREADS = int(os.getenv("STRANDS_WORKFLOW_MIN_THREADS", "2"))
 MAX_THREADS = int(os.getenv("STRANDS_WORKFLOW_MAX_THREADS", "8"))
-CPU_THRESHOLD = int(os.getenv("STRANDS_WORKFLOW_CPU_THRESHOLD", "80"))  # CPU usage threshold for scaling down
 
 # Rate limiting configuration
 _rate_limit_lock = RLock()
@@ -157,10 +152,9 @@ def on_modified(self, event):
 
 
 class TaskExecutor:
-    """Advanced task executor with dynamic scaling and resource monitoring."""
+    """Task executor that runs workflow tasks in a fixed-size thread pool."""
 
-    def __init__(self, min_workers=MIN_THREADS, max_workers=MAX_THREADS):
-        self.min_workers = min_workers
+    def __init__(self, max_workers=MAX_THREADS):
         self.max_workers = max_workers
         self._executor = ThreadPoolExecutor(max_workers=max_workers)
         self.task_queue = Queue()