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models.py

@@ -176,65 +176,40 @@ def load_controlnets():
 def load_sdxl_pipeline(controlnets):
     """
     Load SDXL pipeline with InstantID support.
-    controlnets MUST be a list: [identitynet, depthnet]
-    Following the working example from examplewithface.py
+    EXACTLY following working example: from_pretrained with controlnet list
     """
     print("Loading SDXL checkpoint with InstantID pipeline...")
-    try:
-        model_path = download_model_with_retry(MODEL_REPO, MODEL_FILES['checkpoint'])
-        
-        # CRITICAL: from_single_file doesn't auto-wrap lists in MultiControlNetModel
-        # We must do it explicitly (unlike from_pretrained which does it automatically)
-        if isinstance(controlnets, list) and len(controlnets) > 1:
-            from diffusers.models.controlnets.multicontrolnet import MultiControlNetModel
-            print(f"  Wrapping {len(controlnets)} ControlNets in MultiControlNetModel...")
-            controlnet_for_pipeline = MultiControlNetModel(controlnets)
-        else:
-            controlnet_for_pipeline = controlnets[0] if isinstance(controlnets, list) else controlnets
-        
-        # Use InstantID-enabled pipeline
-        pipe = StableDiffusionXLInstantIDImg2ImgPipeline.from_single_file(
-            model_path,
-            controlnet=controlnet_for_pipeline,
-            torch_dtype=dtype,
-            use_safetensors=True
-        ).to(device)
-        
-        # Load IP-Adapter weights for InstantID
-        print("Loading IP-Adapter for InstantID...")
-        ip_adapter_path = download_model_with_retry(
-            "InstantX/InstantID",
-            "ip-adapter.bin"
-        )
-        pipe.load_ip_adapter_instantid(ip_adapter_path)
-        print("  [OK] IP-Adapter loaded (scale will be set dynamically)")
-        
-        print("  [OK] InstantID pipeline loaded successfully")
-        return pipe, True
-        
-    except Exception as e:
-        print(f"  [ERROR] Could not load InstantID pipeline: {e}")
-        import traceback
-        traceback.print_exc()
-        
-        # Fallback to standard pipeline
-        print("  [WARNING] Falling back to standard SDXL pipeline (no InstantID)")
-        from diffusers import StableDiffusionXLControlNetImg2ImgPipeline
-        
-        # Wrap in MultiControlNetModel for fallback too
-        if isinstance(controlnets, list) and len(controlnets) > 1:
-            from diffusers.models.controlnets.multicontrolnet import MultiControlNetModel
-            controlnet_for_pipeline = MultiControlNetModel(controlnets)
-        else:
-            controlnet_for_pipeline = controlnets[0] if isinstance(controlnets, list) else controlnets
-        
-        pipe = StableDiffusionXLControlNetImg2ImgPipeline.from_pretrained(
-            "stabilityai/stable-diffusion-xl-base-1.0",
-            controlnet=controlnet_for_pipeline,
-            torch_dtype=dtype,
-            use_safetensors=True
-        ).to(device)
-        return pipe, False
+    
+    # Load VAE (like working example line 128)
+    print("Loading VAE...")
+    vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=dtype)
+    print("  [OK] VAE loaded")
+    
+    # Load pipeline EXACTLY like working example (line 134-137)
+    # Uses from_pretrained, NOT from_single_file!
+    # Passes controlnet list directly, NO MultiControlNetModel wrapper!
+    print("Loading InstantID pipeline from_pretrained (like working example)...")
+    pipe = StableDiffusionXLInstantIDImg2ImgPipeline.from_pretrained(
+        "frankjoshua/albedobaseXL_v21",
+        vae=vae,
+        controlnet=controlnets,  # Pass list directly [identitynet, depthnet]
+        torch_dtype=dtype
+    )
+    pipe = pipe.to(device)
+    print("  [OK] Pipeline loaded with from_pretrained")
+    
+    # Load IP-Adapter weights for InstantID (like working example line 139)
+    print("Loading IP-Adapter for InstantID...")
+    ip_adapter_path = download_model_with_retry(
+        "InstantX/InstantID",
+        "ip-adapter.bin"
+    )
+    pipe.load_ip_adapter_instantid(ip_adapter_path)
+    pipe.set_ip_adapter_scale(0.8)  # Initial scale like working example line 140
+    print("  [OK] IP-Adapter loaded (initial scale 0.8)")
+    
+    print("  [OK] InstantID pipeline loaded successfully (matches working example)")
+    return pipe, True
 
 
 # Global variable to track LORA fusion state (like in working example)