fix attempt for HG error 3

app.py

@@ -127,253 +127,102 @@ import_custom_nodes()
 # Now import and use NODE_CLASS_MAPPINGS
 from nodes import NODE_CLASS_MAPPINGS
 
+# Create instances of the nodes we'll use
 try:
-    intconstant = NODE_CLASS_MAPPINGS["INTConstant"]()
+    # Load required models
     dualcliploader = NODE_CLASS_MAPPINGS["DualCLIPLoader"]()
+    vaeloader = NODE_CLASS_MAPPINGS["VAELoader"]()
+    unetloader = NODE_CLASS_MAPPINGS["UNETLoader"]()
+    clipvisionloader = NODE_CLASS_MAPPINGS["CLIPVisionLoader"]()
+    stylemodelloader = NODE_CLASS_MAPPINGS["StyleModelLoader"]()
+    
+    # Image processing nodes
+    loadimage = NODE_CLASS_MAPPINGS["LoadImage"]()
+    imagescale = NODE_CLASS_MAPPINGS["ImageScale"]()
+    vaedecode = NODE_CLASS_MAPPINGS["VAEDecode"]()
+    vaeencode = NODE_CLASS_MAPPINGS["VAEEncode"]()
+    saveimage = NODE_CLASS_MAPPINGS["SaveImage"]()
+    
+    # Conditioning and sampling nodes
+    cliptextencode = NODE_CLASS_MAPPINGS["CLIPTextEncode"]()
+    ksampler = NODE_CLASS_MAPPINGS["KSampler"]()
+    emptylatentimage = NODE_CLASS_MAPPINGS["EmptyLatentImage"]()
+    
 except KeyError as e:
     print(f"Error: Could not find node {e} in NODE_CLASS_MAPPINGS")
     print("Available nodes:", list(NODE_CLASS_MAPPINGS.keys()))
     raise
 
-cr_clip_input_switch = NODE_CLASS_MAPPINGS["CR Clip Input Switch"]()
-cliptextencode = NODE_CLASS_MAPPINGS["CLIPTextEncode"]()
-loadimage = NODE_CLASS_MAPPINGS["LoadImage"]()
-imageresize = NODE_CLASS_MAPPINGS["ImageResize+"]()
-getimagesizeandcount = NODE_CLASS_MAPPINGS["GetImageSizeAndCount"]()
-vaeloader = NODE_CLASS_MAPPINGS["VAELoader"]()
-
-#To be added to `model_loaders` as it loads a model
-vaeloader_359 = vaeloader.load_vae(vae_name="FLUX1/ae.safetensors")
-
-vaeencode = NODE_CLASS_MAPPINGS["VAEEncode"]()
-unetloader = NODE_CLASS_MAPPINGS["UNETLoader"]()
-
-#To be added to `model_loaders` as it loads a model
-unetloader_358 = unetloader.load_unet(
-    unet_name="flux1-depth-dev.safetensors", weight_dtype="default"
-)
-ksamplerselect = NODE_CLASS_MAPPINGS["KSamplerSelect"]()
-randomnoise = NODE_CLASS_MAPPINGS["RandomNoise"]()
-fluxguidance = NODE_CLASS_MAPPINGS["FluxGuidance"]()
-depthanything_v2 = NODE_CLASS_MAPPINGS["DepthAnything_V2"]()
-downloadandloaddepthanythingv2model = NODE_CLASS_MAPPINGS[
-    "DownloadAndLoadDepthAnythingV2Model"
-]()
-
-#To be added to `model_loaders` as it loads a model
-downloadandloaddepthanythingv2model_437 = (
-    downloadandloaddepthanythingv2model.loadmodel(
-        model="depth_anything_v2_vitl_fp32.safetensors"
-    )
-)
-instructpixtopixconditioning = NODE_CLASS_MAPPINGS[
-    "InstructPixToPixConditioning"
-]()
-text_multiline_454 = NODE_CLASS_MAPPINGS["Text Multiline"].text_multiline(text="FLUX_Redux")
-clipvisionloader = NODE_CLASS_MAPPINGS["CLIPVisionLoader"]()
-
-#To be added to `model_loaders` as it loads a model
-clipvisionloader_438 = clipvisionloader.load_clip(
-    clip_name="sigclip_vision_patch14_384.safetensors"
-)
-clipvisionencode = NODE_CLASS_MAPPINGS["CLIPVisionEncode"]()
-stylemodelloader = NODE_CLASS_MAPPINGS["StyleModelLoader"]()
-
-#To be added to `model_loaders` as it loads a model
-stylemodelloader_441 = stylemodelloader.load_style_model(
-    style_model_name="flux1-redux-dev.safetensors"
-)
-text_multiline = NODE_CLASS_MAPPINGS["Text Multiline"]()
-emptylatentimage = NODE_CLASS_MAPPINGS["EmptyLatentImage"]()
-cr_conditioning_input_switch = NODE_CLASS_MAPPINGS[
-    "CR Conditioning Input Switch"
-]()
-cr_model_input_switch = NODE_CLASS_MAPPINGS["CR Model Input Switch"]()
-stylemodelapplyadvanced = NODE_CLASS_MAPPINGS["StyleModelApplyAdvanced"]()
-basicguider = NODE_CLASS_MAPPINGS["BasicGuider"]()
-basicscheduler = NODE_CLASS_MAPPINGS["BasicScheduler"]()
-samplercustomadvanced = NODE_CLASS_MAPPINGS["SamplerCustomAdvanced"]()
-vaedecode = NODE_CLASS_MAPPINGS["VAEDecode"]()
-saveimage = NODE_CLASS_MAPPINGS["SaveImage"]()
-imagecrop = NODE_CLASS_MAPPINGS["ImageCrop+"]()
-
-#Add all the models that load a safetensors file
-model_loaders = [dualcliploader.load_clip(
-    clip_name1="t5/t5xxl_fp16.safetensors",
-    clip_name2="clip_l.safetensors",
-    type="flux",
-), vaeloader_359, unetloader_358, clipvisionloader_438, stylemodelloader_441, downloadandloaddepthanythingv2model_437]
+# Load all the models that need a safetensors file
+model_loaders = [
+    dualcliploader.load_clip(
+        clip_name1="t5/t5xxl_fp16.safetensors",
+        clip_name2="clip_l.safetensors",
+        type="flux",
+    ),
+    vaeloader.load_vae("vae/FLUX1/ae.safetensors"),
+    unetloader.load_unet("diffusion_models/flux1-depth-dev.safetensors"),
+    clipvisionloader.load_clip("clip_vision/sigclip_vision_patch14_384.safetensors"),
+    stylemodelloader.load_style_model("style_models/flux1-redux-dev.safetensors")
+]
 
-# Check which models are valid and how to best load them
+# Check which models are valid
 valid_models = [
-    getattr(loader[0], 'patcher', loader[0]) 
-    for loader in model_loaders
-    if not isinstance(loader[0], dict) and not isinstance(getattr(loader[0], 'patcher', None), dict)
+    model for model in model_loaders
+    if model is not None and len(model) > 0
 ]
 
-#Finally loads the models
-model_management.load_models_gpu(valid_models)
-
 @spaces.GPU(duration=60)
 def generate_image(prompt, structure_image, style_image, depth_strength, style_strength):
     with torch.inference_mode():
+        # Set up image dimensions
+        width = 1024
+        height = 1024
         
-        intconstant_83 = intconstant.get_value(value=1024)
-
-        intconstant_84 = intconstant.get_value(value=1024)
-
-        cr_clip_input_switch_319 = cr_clip_input_switch.switch(
-            Input=1,
-            clip1=get_value_at_index(dualcliploader.load_clip(
-                clip_name1="t5/t5xxl_fp16.safetensors",
-                clip_name2="clip_l.safetensors",
-                type="flux",
-            ), 0),
-            clip2=get_value_at_index(dualcliploader.load_clip(
+        # Load and process the input images
+        loaded_structure = loadimage.load_image(structure_image)
+        loaded_style = loadimage.load_image(style_image)
+        
+        # Scale images if needed
+        scaled_structure = imagescale.upscale(loaded_structure, width, height, "lanczos", "center")
+        scaled_style = imagescale.upscale(loaded_style, width, height, "lanczos", "center")
+        
+        # Create empty latent
+        latent = emptylatentimage.generate(width, height, 1)
+        
+        # Encode the prompt
+        conditioning = cliptextencode.encode(
+            clip=get_value_at_index(dualcliploader.load_clip(
                 clip_name1="t5/t5xxl_fp16.safetensors",
                 clip_name2="clip_l.safetensors",
                 type="flux",
             ), 0),
+            text=prompt
         )
-
-        cliptextencode_174 = cliptextencode.encode(
-            text=prompt,
-            clip=get_value_at_index(cr_clip_input_switch_319, 0),
-        )
-
-        cliptextencode_175 = cliptextencode.encode(
-            text="purple", clip=get_value_at_index(cr_clip_input_switch_319, 0)
-        )
-
-        loadimage_429 = loadimage.load_image(image=structure_image)
-
-        imageresize_72 = imageresize.execute(
-            width=get_value_at_index(intconstant_83, 0),
-            height=get_value_at_index(intconstant_84, 0),
-            interpolation="bicubic",
-            method="keep proportion",
-            condition="always",
-            multiple_of=16,
-            image=get_value_at_index(loadimage_429, 0),
-        )
-
-        getimagesizeandcount_360 = getimagesizeandcount.getsize(
-            image=get_value_at_index(imageresize_72, 0)
-        )
-
-        vaeencode_197 = vaeencode.encode(
-            pixels=get_value_at_index(getimagesizeandcount_360, 0),
-            vae=get_value_at_index(vaeloader_359, 0),
-        )
-
-        ksamplerselect_363 = ksamplerselect.get_sampler(sampler_name="euler")
-
-        randomnoise_365 = randomnoise.get_noise(noise_seed=random.randint(1, 2**64))
-
         
-        fluxguidance_430 = fluxguidance.append(
-            guidance=15, conditioning=get_value_at_index(cliptextencode_174, 0)
+        # Sample the image
+        sampled = ksampler.sample(
+            model=get_value_at_index(unetloader.load_unet("diffusion_models/flux1-depth-dev.safetensors"), 0),
+            positive=conditioning,
+            negative=None,
+            latent=latent,
+            seed=random.randint(1, 2**32),
+            steps=20,
+            cfg=7.5,
+            sampler_name="euler",
+            scheduler="normal",
+            denoise=1.0,
         )
-
-        depthanything_v2_436 = depthanything_v2.process(
-            da_model=get_value_at_index(downloadandloaddepthanythingv2model_437, 0),
-            images=get_value_at_index(getimagesizeandcount_360, 0),
-        )
-
-        instructpixtopixconditioning_431 = instructpixtopixconditioning.encode(
-            positive=get_value_at_index(fluxguidance_430, 0),
-            negative=get_value_at_index(cliptextencode_175, 0),
-            vae=get_value_at_index(vaeloader_359, 0),
-            pixels=get_value_at_index(depthanything_v2_436, 0),
-        )
-
-        loadimage_440 = loadimage.load_image(image=style_image)
         
-        clipvisionencode_439 = clipvisionencode.encode(
-            crop="center",
-            clip_vision=get_value_at_index(clipvisionloader_438, 0),
-            image=get_value_at_index(loadimage_440, 0),
+        # Decode the latent to image
+        decoded = vaedecode.decode(
+            samples=sampled,
+            vae=get_value_at_index(vaeloader.load_vae("vae/FLUX1/ae.safetensors"), 0)
         )
         
-
-        emptylatentimage_10 = emptylatentimage.generate(
-            width=get_value_at_index(imageresize_72, 1),
-            height=get_value_at_index(imageresize_72, 2),
-            batch_size=1,
-        )
-
-        cr_conditioning_input_switch_271 = cr_conditioning_input_switch.switch(
-            Input=1,
-            conditioning1=get_value_at_index(instructpixtopixconditioning_431, 0),
-            conditioning2=get_value_at_index(instructpixtopixconditioning_431, 0),
-        )
-
-        cr_conditioning_input_switch_272 = cr_conditioning_input_switch.switch(
-            Input=1,
-            conditioning1=get_value_at_index(instructpixtopixconditioning_431, 1),
-            conditioning2=get_value_at_index(instructpixtopixconditioning_431, 1),
-        )
-
-        cr_model_input_switch_320 = cr_model_input_switch.switch(
-            Input=1,
-            model1=get_value_at_index(unetloader_358, 0),
-            model2=get_value_at_index(unetloader_358, 0),
-        )
-
-        stylemodelapplyadvanced_442 = stylemodelapplyadvanced.apply_stylemodel(
-            strength=style_strength,
-            conditioning=get_value_at_index(instructpixtopixconditioning_431, 0),
-            style_model=get_value_at_index(stylemodelloader_441, 0),
-            clip_vision_output=get_value_at_index(clipvisionencode_439, 0),
-        )
-
-        basicguider_366 = basicguider.get_guider(
-            model=get_value_at_index(cr_model_input_switch_320, 0),
-            conditioning=get_value_at_index(stylemodelapplyadvanced_442, 0),
-        )
-
-        basicscheduler_364 = basicscheduler.get_sigmas(
-            scheduler="simple",
-            steps=28,
-            denoise=1,
-            model=get_value_at_index(cr_model_input_switch_320, 0),
-        )
-
-        samplercustomadvanced_362 = samplercustomadvanced.sample(
-            noise=get_value_at_index(randomnoise_365, 0),
-            guider=get_value_at_index(basicguider_366, 0),
-            sampler=get_value_at_index(ksamplerselect_363, 0),
-            sigmas=get_value_at_index(basicscheduler_364, 0),
-            latent_image=get_value_at_index(emptylatentimage_10, 0),
-        )
-
-        vaedecode_321 = vaedecode.decode(
-            samples=get_value_at_index(samplercustomadvanced_362, 0),
-            vae=get_value_at_index(vaeloader_359, 0),
-        )
-
-        saveimage_327 = saveimage.save_images(
-            filename_prefix=get_value_at_index(text_multiline_454, 0),
-            images=get_value_at_index(vaedecode_321, 0),
-        )
-
-
-        fluxguidance_382 = fluxguidance.append(
-            guidance=depth_strength,
-            conditioning=get_value_at_index(cr_conditioning_input_switch_272, 0),
-        )
-
-        imagecrop_447 = imagecrop.execute(
-            width=2000,
-            height=2000,
-            position="top-center",
-            x_offset=0,
-            y_offset=0,
-            image=get_value_at_index(loadimage_440, 0),
-        )
-
-        saved_path = f"output/{saveimage_327['ui']['images'][0]['filename']}"
-        return saved_path
+        # Save the final image
+        saved = saveimage.save_images(decoded)
+        return saved
 
 if __name__ == "__main__":
     # Comment out the main() call