Fix syntax error: close unterminated docstring in _load_models

src/ace_step_engine.py

@@ -92,7 +92,7 @@ class ACEStepEngine:
             raise
 
     def _load_models(self):
-        """Initialize s_dir = get_checkpoints_dir(self.config.get("checkpoint_dir")
+        """Initialize and load ACE-Step models."""
         try:
             if not ACE_STEP_AVAILABLE:
                 raise RuntimeError("ACE-Step 1.5 not available")
@@ -101,15 +101,18 @@ class ACEStepEngine:
             dit_model_path = self.config.get("dit_model_path", "acestep-v15-turbo")
             lm_model_path = self.config.get("lm_model_path", "acestep-5Hz-lm-1.7B")
             
+            # Get checkpoints directory using helper function
+            checkpoints_dir = get_checkpoints_dir(checkpoint_dir)
+            
             # Get project root
             project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
             
-            logger.info(f"Instr(checkpoints_dir / dit_model_path) handler with model: {dit_model_path}")
+            logger.info(f"Initializing DiT handler with model: {dit_model_path}")
             
             # Initialize DiT handler (handles main diffusion model, VAE, text encoder)
             status_dit, success_dit = self.dit_handler.initialize_service(
                 project_root=project_root,
-                config_path=dit_model_path,
+                config_path=str(checkpoints_dir / dit_model_path),
                 device="auto",
                 use_flash_attention=False,
                 compile_model=False,
@@ -119,13 +122,13 @@ class ACEStepEngine:
             if not success_dit:
                 raise RuntimeError(f"Failed to initialize DiT: {status_dit}")
             
-            logger.info(f" DiT initialized: {status_dit}")
-            str(checkpoints_dir)
+            logger.info(f"✓ DiT initialized: {status_dit}")
+            
             # Initialize LLM handler (handles 5Hz Language Model)
             logger.info(f"Initializing LLM handler with model: {lm_model_path}")
             
             status_llm, success_llm = self.llm_handler.initialize(
-                checkpoint_dir=checkpoint_dir,
+                checkpoint_dir=str(checkpoints_dir),
                 lm_model_path=lm_model_path,
                 backend="pt",  # Use PyTorch backend for compatibility
                 device="auto",