diff --git a/generation_models/__init__.py b/generation_models/__init__.py
index 9ae66fcf..f4ccece1 100644
--- a/generation_models/__init__.py
+++ b/generation_models/__init__.py
@@ -1,9 +1,12 @@
 from .niche_stable_diffusion import NicheStableDiffusion
 from .niche_stable_diffusion_xl import NicheStableDiffusionXL
 from .niche_go_journey import NicheGoJourney
+from .niche_sticker_maker import NicheStickerMaker
+
 
 __all__ = [
     "NicheStableDiffusion",
     "NicheStableDiffusionXL",
     "NicheGoJourney",
+    "NicheStickerMaker",
 ]
diff --git a/generation_models/configs/model_config.yaml b/generation_models/configs/model_config.yaml
index 98ab7919..7107f2c5 100644
--- a/generation_models/configs/model_config.yaml
+++ b/generation_models/configs/model_config.yaml
@@ -37,6 +37,11 @@ GoJourney:
   params:
     supporting_pipelines: 
       - "gojourney"
+StickerMaker:
+  target: generation_models.NicheStickerMaker
+  params:
+    supporting_pipelines: 
+      - "txt2img"
 Gemma7b:
   target: ""
   repo_id: "google/gemma-7b-it"
diff --git a/generation_models/niche_go_journey.py b/generation_models/niche_go_journey.py
index 5cd3fc5d..7a816094 100644
--- a/generation_models/niche_go_journey.py
+++ b/generation_models/niche_go_journey.py
@@ -18,6 +18,7 @@ def load_model(self, *args, **kwargs):
     def __call__(self, *args, **kwargs):
         return self.inference_function(*args, **kwargs)
 
+
     def load_imagine(self, *args, **kwargs):
         imagine_endpoint = "https://api.midjourneyapi.xyz/mj/v2/imagine"
         fetch_endpoint = "https://api.midjourneyapi.xyz/mj/v2/fetch"
diff --git a/generation_models/niche_stable_diffusion.py b/generation_models/niche_stable_diffusion.py
index b1b2a521..86703b46 100644
--- a/generation_models/niche_stable_diffusion.py
+++ b/generation_models/niche_stable_diffusion.py
@@ -120,3 +120,23 @@ def process_conditional_image(self, **kwargs) -> Image.Image:
         resolution = kwargs.get("resolution", 512)
         conditional_image = resize_for_condition_image(conditional_image, resolution)
         return conditional_image
+
+if __name__ == "__main__":
+    params = {
+        "checkpoint_file": "checkpoints/RealisticVision.safetensors",
+    "download_url": "https://civitai.com/api/download/models/130072?type=Model&format=SafeTensor&size=pruned&fp=fp16",
+    "scheduler": "dpm++2m",
+    "supporting_pipelines": ['txt2img']
+    }
+    pipe = NicheStableDiffusion(
+        **params
+    )
+
+    input_dict = {
+        "pipeline_type": "txt2img",
+        "prompt": "a cat",
+        "num_inference_steps": 25,
+    }
+
+    image = pipe(**input_dict)
+    image.save("debug.webp")
\ No newline at end of file
diff --git a/generation_models/niche_stable_diffusion_xl.py b/generation_models/niche_stable_diffusion_xl.py
index 02152806..f9a42c88 100644
--- a/generation_models/niche_stable_diffusion_xl.py
+++ b/generation_models/niche_stable_diffusion_xl.py
@@ -71,3 +71,5 @@ def process_conditional_image(self, **kwargs) -> Image.Image:
         resolution = kwargs.get("resolution", 768)
         conditional_image = resize_for_condition_image(conditional_image, resolution)
         return conditional_image
+
+
diff --git a/generation_models/niche_sticker_maker.py b/generation_models/niche_sticker_maker.py
new file mode 100644
index 00000000..4ac11407
--- /dev/null
+++ b/generation_models/niche_sticker_maker.py
@@ -0,0 +1,68 @@
+from .base_model import BaseModel
+from generation_models.utils_api_comfyui import *
+import uuid
+from PIL import Image
+import io
+import base64
+
+
+server_address = "82.67.70.191:40892"
+client_id = "13c08530-8911-4e38-8489-7cded8eddd9d"
+
+class NicheStickerMaker(BaseModel):
+    def __init__(self, *args, **kwargs):
+        self.server_address, self.client_id = kwargs.get("server_address"), kwargs.get("client_id")
+
+        self.inference_function = self.load_model(*args, **kwargs)
+
+    def __call__(self, *args, **kwargs):
+        return self.inference_function(*args, **kwargs)
+
+
+    def load_model(self, *args, **kwargs):
+        imagine_inference_function = self.load_image(*args, **kwargs)
+        return imagine_inference_function
+    
+    def load_image(self, *args, **kwargs):
+        # workflow = load_workflow("generation_models/sticker_maker.json")
+
+        def inference_function(*args, **kwargs):
+            with open("generation_models/workflow-json/sticker_maker.json", "r") as file:
+                workflow_json = file.read()
+  
+
+            workflow = json.loads(workflow_json)
+            workflow["2"]["inputs"]["positive"] = kwargs["prompt"]
+            workflow["4"]["inputs"]["seed"] = kwargs["seed"]
+
+
+            ws = websocket.WebSocket()
+            ws.connect("ws://{}/ws?clientId={}".format(server_address, client_id))
+
+            images = get_images(ws, workflow)
+            imgs = []
+            for node_id in images:
+                for image_data in images[node_id]:
+                    image = Image.open(io.BytesIO(image_data))
+                    imgs.append(image)
+
+            return imgs[0]
+
+        return inference_function
+
+if __name__=="__main__":
+    params = {
+    "supporting_pipelines": ['txt2img']
+    }
+    pipe = NicheStickerMaker(
+        **params
+    )
+
+    input_dict = {
+        "pipeline_type": "txt2img",
+        "prompt": "a cat",
+    }
+
+    image = pipe(**input_dict)
+    image.save("debug.webp")
+
diff --git a/generation_models/utils_api_comfyui.py b/generation_models/utils_api_comfyui.py
new file mode 100644
index 00000000..7f94dc7e
--- /dev/null
+++ b/generation_models/utils_api_comfyui.py
@@ -0,0 +1,94 @@
+import websocket #NOTE: websocket-client (https://github.com/websocket-client/websocket-client)
+import uuid
+import json
+import urllib.request
+import urllib.parse
+
+server_address = "82.67.70.191:40892"
+client_id = "13c08530-8911-4e38-8489-7cded8eddd9d"
+
+def queue_prompt(prompt):
+    p = {"prompt": prompt, "client_id": client_id}
+    data = json.dumps(p).encode('utf-8')
+    req =  urllib.request.Request("http://{}/prompt".format(server_address), data=data)
+    return json.loads(urllib.request.urlopen(req).read())
+
+def get_image(filename, subfolder, folder_type):
+    data = {"filename": filename, "subfolder": subfolder, "type": folder_type}
+    url_values = urllib.parse.urlencode(data)
+    with urllib.request.urlopen("http://{}/view?{}".format(server_address, url_values)) as response:
+        return response.read()
+
+def get_history(prompt_id):
+    with urllib.request.urlopen("http://{}/history/{}".format(server_address, prompt_id)) as response:
+        return json.loads(response.read())
+
+def load_workflow(workflow_path):
+    try:
+        with open(workflow_path, 'r') as file:
+            workflow = json.load(file)
+            return workflow
+    except FileNotFoundError:
+        print(f"The file {workflow_path} was not found.")
+        return None
+    except json.JSONDecodeError:
+        print(f"The file {workflow_path} contains invalid JSON.")
+        return None
+
+def get_images(ws, prompt):
+    prompt_id = queue_prompt(prompt)['prompt_id']
+    output_images = {}
+    while True:
+        out = ws.recv()
+
+        if isinstance(out, str):
+
+            message = json.loads(out)
+            if message['type'] == 'executing':
+                data = message['data']
+                if data['node'] is None and data['prompt_id'] == prompt_id:
+                    break #Execution is done
+        else:
+            continue #previews are binary data
+
+    history = get_history(prompt_id)[prompt_id]
+    for o in history['outputs']:
+        for node_id in history['outputs']:
+            node_output = history['outputs'][node_id]
+            if 'images' in node_output:
+                images_output = []
+                for image in node_output['images']:
+                    image_data = get_image(image['filename'], image['subfolder'], image['type'])
+                    images_output.append(image_data)
+            output_images[node_id] = images_output
+
+    return output_images
+if __name__ == "__main__":
+
+    with open("generation_models/workflow-json/sticker_maker.json", "r") as file:
+        workflow_json = file.read()
+  
+
+    workflow = json.loads(workflow_json)
+    #set the text prompt for our positive CLIPTextEncode
+    workflow["2"]["inputs"]["positive"] = "a dog"
+    workflow["4"]["inputs"]["seed"] = 7
+
+    ws = websocket.WebSocket()
+    ws.connect("ws://{}/ws?clientId={}".format(server_address, client_id))
+
+    print(ws)
+    images = get_images(ws, workflow)
+
+
+    #Commented out code to display the output images:
+    i=0
+    for node_id in images:
+        for image_data in images[node_id]:
+            i+=1
+            from PIL import Image
+            import io
+            image = Image.open(io.BytesIO(image_data))
+            # image.show()
+            print("out")
+            image.save(f"Output{i}.webp")
diff --git a/generation_models/workflow-json/face_to_many.json b/generation_models/workflow-json/face_to_many.json
new file mode 100644
index 00000000..dc0762cd
--- /dev/null
+++ b/generation_models/workflow-json/face_to_many.json
@@ -0,0 +1,437 @@
+{
+  "2": {
+    "inputs": {
+      "ckpt_name": "albedobaseXL_v13.safetensors",
+      "vae_name": "Baked VAE",
+      "clip_skip": -1,
+      "lora_name": "None",
+      "lora_model_strength": 1,
+      "lora_clip_strength": 1,
+      "positive": "3D Render Style, 3DRenderAF, person",
+      "negative": "photo, photography, nsfw, nude, ugly, broken, watermark",
+      "token_normalization": "none",
+      "weight_interpretation": "comfy",
+      "empty_latent_width": 1024,
+      "empty_latent_height": 1024,
+      "batch_size": 1,
+      "lora_stack": [
+        "3",
+        0
+      ],
+      "cnet_stack": [
+        "28",
+        0
+      ]
+    },
+    "class_type": "Efficient Loader",
+    "_meta": {
+      "title": "Efficient Loader"
+    }
+  },
+  "3": {
+    "inputs": {
+      "input_mode": "simple",
+      "lora_count": 3,
+      "lora_name_1": "artificialguybr/3DRedmond-3DRenderStyle-3DRenderAF.safetensors",
+      "lora_wt_1": 1,
+      "model_str_1": 1,
+      "clip_str_1": 1,
+      "lora_name_2": "None",
+      "lora_wt_2": 1,
+      "model_str_2": 1,
+      "clip_str_2": 1,
+      "lora_name_3": "None",
+      "lora_wt_3": 1,
+      "model_str_3": 1,
+      "clip_str_3": 1,
+      "lora_name_4": "None",
+      "lora_wt_4": 1,
+      "model_str_4": 1,
+      "clip_str_4": 1,
+      "lora_name_5": "None",
+      "lora_wt_5": 1,
+      "model_str_5": 1,
+      "clip_str_5": 1,
+      "lora_name_6": "None",
+      "lora_wt_6": 1,
+      "model_str_6": 1,
+      "clip_str_6": 1,
+      "lora_name_7": "None",
+      "lora_wt_7": 1,
+      "model_str_7": 1,
+      "clip_str_7": 1,
+      "lora_name_8": "None",
+      "lora_wt_8": 1,
+      "model_str_8": 1,
+      "clip_str_8": 1,
+      "lora_name_9": "None",
+      "lora_wt_9": 1,
+      "model_str_9": 1,
+      "clip_str_9": 1,
+      "lora_name_10": "None",
+      "lora_wt_10": 1,
+      "model_str_10": 1,
+      "clip_str_10": 1,
+      "lora_name_11": "None",
+      "lora_wt_11": 1,
+      "model_str_11": 1,
+      "clip_str_11": 1,
+      "lora_name_12": "None",
+      "lora_wt_12": 1,
+      "model_str_12": 1,
+      "clip_str_12": 1,
+      "lora_name_13": "None",
+      "lora_wt_13": 1,
+      "model_str_13": 1,
+      "clip_str_13": 1,
+      "lora_name_14": "None",
+      "lora_wt_14": 1,
+      "model_str_14": 1,
+      "clip_str_14": 1,
+      "lora_name_15": "None",
+      "lora_wt_15": 1,
+      "model_str_15": 1,
+      "clip_str_15": 1,
+      "lora_name_16": "None",
+      "lora_wt_16": 1,
+      "model_str_16": 1,
+      "clip_str_16": 1,
+      "lora_name_17": "None",
+      "lora_wt_17": 1,
+      "model_str_17": 1,
+      "clip_str_17": 1,
+      "lora_name_18": "None",
+      "lora_wt_18": 1,
+      "model_str_18": 1,
+      "clip_str_18": 1,
+      "lora_name_19": "None",
+      "lora_wt_19": 1,
+      "model_str_19": 1,
+      "clip_str_19": 1,
+      "lora_name_20": "None",
+      "lora_wt_20": 1,
+      "model_str_20": 1,
+      "clip_str_20": 1,
+      "lora_name_21": "None",
+      "lora_wt_21": 1,
+      "model_str_21": 1,
+      "clip_str_21": 1,
+      "lora_name_22": "None",
+      "lora_wt_22": 1,
+      "model_str_22": 1,
+      "clip_str_22": 1,
+      "lora_name_23": "None",
+      "lora_wt_23": 1,
+      "model_str_23": 1,
+      "clip_str_23": 1,
+      "lora_name_24": "None",
+      "lora_wt_24": 1,
+      "model_str_24": 1,
+      "clip_str_24": 1,
+      "lora_name_25": "None",
+      "lora_wt_25": 1,
+      "model_str_25": 1,
+      "clip_str_25": 1,
+      "lora_name_26": "None",
+      "lora_wt_26": 1,
+      "model_str_26": 1,
+      "clip_str_26": 1,
+      "lora_name_27": "None",
+      "lora_wt_27": 1,
+      "model_str_27": 1,
+      "clip_str_27": 1,
+      "lora_name_28": "None",
+      "lora_wt_28": 1,
+      "model_str_28": 1,
+      "clip_str_28": 1,
+      "lora_name_29": "None",
+      "lora_wt_29": 1,
+      "model_str_29": 1,
+      "clip_str_29": 1,
+      "lora_name_30": "None",
+      "lora_wt_30": 1,
+      "model_str_30": 1,
+      "clip_str_30": 1,
+      "lora_name_31": "None",
+      "lora_wt_31": 1,
+      "model_str_31": 1,
+      "clip_str_31": 1,
+      "lora_name_32": "None",
+      "lora_wt_32": 1,
+      "model_str_32": 1,
+      "clip_str_32": 1,
+      "lora_name_33": "None",
+      "lora_wt_33": 1,
+      "model_str_33": 1,
+      "clip_str_33": 1,
+      "lora_name_34": "None",
+      "lora_wt_34": 1,
+      "model_str_34": 1,
+      "clip_str_34": 1,
+      "lora_name_35": "None",
+      "lora_wt_35": 1,
+      "model_str_35": 1,
+      "clip_str_35": 1,
+      "lora_name_36": "None",
+      "lora_wt_36": 1,
+      "model_str_36": 1,
+      "clip_str_36": 1,
+      "lora_name_37": "None",
+      "lora_wt_37": 1,
+      "model_str_37": 1,
+      "clip_str_37": 1,
+      "lora_name_38": "None",
+      "lora_wt_38": 1,
+      "model_str_38": 1,
+      "clip_str_38": 1,
+      "lora_name_39": "None",
+      "lora_wt_39": 1,
+      "model_str_39": 1,
+      "clip_str_39": 1,
+      "lora_name_40": "None",
+      "lora_wt_40": 1,
+      "model_str_40": 1,
+      "clip_str_40": 1,
+      "lora_name_41": "None",
+      "lora_wt_41": 1,
+      "model_str_41": 1,
+      "clip_str_41": 1,
+      "lora_name_42": "None",
+      "lora_wt_42": 1,
+      "model_str_42": 1,
+      "clip_str_42": 1,
+      "lora_name_43": "None",
+      "lora_wt_43": 1,
+      "model_str_43": 1,
+      "clip_str_43": 1,
+      "lora_name_44": "None",
+      "lora_wt_44": 1,
+      "model_str_44": 1,
+      "clip_str_44": 1,
+      "lora_name_45": "None",
+      "lora_wt_45": 1,
+      "model_str_45": 1,
+      "clip_str_45": 1,
+      "lora_name_46": "None",
+      "lora_wt_46": 1,
+      "model_str_46": 1,
+      "clip_str_46": 1,
+      "lora_name_47": "None",
+      "lora_wt_47": 1,
+      "model_str_47": 1,
+      "clip_str_47": 1,
+      "lora_name_48": "None",
+      "lora_wt_48": 1,
+      "model_str_48": 1,
+      "clip_str_48": 1,
+      "lora_name_49": "None",
+      "lora_wt_49": 1,
+      "model_str_49": 1,
+      "clip_str_49": 1
+    },
+    "class_type": "LoRA Stacker",
+    "_meta": {
+      "title": "LoRA Stacker"
+    }
+  },
+  "4": {
+    "inputs": {
+      "seed": 1051763972092850,
+      "steps": 17,
+      "cfg": 7,
+      "sampler_name": "dpmpp_2m_sde_gpu",
+      "scheduler": "karras",
+      "denoise": 0.65,
+      "preview_method": "none",
+      "vae_decode": "true",
+      "model": [
+        "41",
+        0
+      ],
+      "positive": [
+        "41",
+        1
+      ],
+      "negative": [
+        "41",
+        2
+      ],
+      "latent_image": [
+        "51",
+        0
+      ],
+      "optional_vae": [
+        "2",
+        4
+      ]
+    },
+    "class_type": "KSampler (Efficient)",
+    "_meta": {
+      "title": "KSampler (Efficient)"
+    }
+  },
+  "5": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "4",
+        5
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "Save Image"
+    }
+  },
+  "22": {
+    "inputs": {
+      "image": "Screenshot 2024-02-26 at 16.13.24.png",
+      "upload": "image"
+    },
+    "class_type": "LoadImage",
+    "_meta": {
+      "title": "Load Image"
+    }
+  },
+  "24": {
+    "inputs": {
+      "control_net_name": "depth-zoe-xl-v1.0-controlnet.safetensors"
+    },
+    "class_type": "ControlNetLoader",
+    "_meta": {
+      "title": "Load ControlNet Model"
+    }
+  },
+  "28": {
+    "inputs": {
+      "strength": 0.8,
+      "start_percent": 0,
+      "end_percent": 1,
+      "control_net": [
+        "24",
+        0
+      ],
+      "image": [
+        "49",
+        0
+      ]
+    },
+    "class_type": "Control Net Stacker",
+    "_meta": {
+      "title": "Control Net Stacker"
+    }
+  },
+  "35": {
+    "inputs": {
+      "instantid_file": "instantid-ip-adapter.bin"
+    },
+    "class_type": "InstantIDModelLoader",
+    "_meta": {
+      "title": "Load InstantID Model"
+    }
+  },
+  "36": {
+    "inputs": {
+      "provider": "CUDA"
+    },
+    "class_type": "InstantIDFaceAnalysis",
+    "_meta": {
+      "title": "InstantID Face Analysis"
+    }
+  },
+  "40": {
+    "inputs": {
+      "control_net_name": "instantid-controlnet.safetensors"
+    },
+    "class_type": "ControlNetLoader",
+    "_meta": {
+      "title": "Load ControlNet Model"
+    }
+  },
+  "41": {
+    "inputs": {
+      "weight": 1,
+      "start_at": 0,
+      "end_at": 1,
+      "instantid": [
+        "35",
+        0
+      ],
+      "insightface": [
+        "36",
+        0
+      ],
+      "control_net": [
+        "40",
+        0
+      ],
+      "image": [
+        "67",
+        0
+      ],
+      "model": [
+        "2",
+        0
+      ],
+      "positive": [
+        "2",
+        1
+      ],
+      "negative": [
+        "2",
+        2
+      ]
+    },
+    "class_type": "ApplyInstantID",
+    "_meta": {
+      "title": "Apply InstantID"
+    }
+  },
+  "49": {
+    "inputs": {
+      "preprocessor": "MiDaS-DepthMapPreprocessor",
+      "resolution": 512,
+      "image": [
+        "67",
+        0
+      ]
+    },
+    "class_type": "AIO_Preprocessor",
+    "_meta": {
+      "title": "AIO Aux Preprocessor"
+    }
+  },
+  "51": {
+    "inputs": {
+      "pixels": [
+        "67",
+        0
+      ],
+      "vae": [
+        "2",
+        4
+      ]
+    },
+    "class_type": "VAEEncode",
+    "_meta": {
+      "title": "VAE Encode"
+    }
+  },
+  "67": {
+    "inputs": {
+      "width": 1024,
+      "height": 1024,
+      "interpolation": "nearest",
+      "keep_proportion": true,
+      "condition": "always",
+      "image": [
+        "22",
+        0
+      ]
+    },
+    "class_type": "ImageResize+",
+    "_meta": {
+      "title": "🔧 Image Resize"
+    }
+  }
+}
\ No newline at end of file
diff --git a/generation_models/workflow-json/sticker_maker.json b/generation_models/workflow-json/sticker_maker.json
new file mode 100644
index 00000000..e8bb0be5
--- /dev/null
+++ b/generation_models/workflow-json/sticker_maker.json
@@ -0,0 +1,455 @@
+{
+  "2": {
+    "inputs": {
+      "ckpt_name": "albedobaseXL_v13.safetensors",
+      "vae_name": "Baked VAE",
+      "clip_skip": -1,
+      "lora_name": "None",
+      "lora_model_strength": 1,
+      "lora_clip_strength": 1,
+      "positive": "Sticker, cute cat, svg, solid color background",
+      "negative": "nsfw, nude, ugly, broken, photo, photography",
+      "token_normalization": "none",
+      "weight_interpretation": "comfy",
+      "empty_latent_width": 1024,
+      "empty_latent_height": 1024,
+      "batch_size": 1,
+      "lora_stack": [
+        "3",
+        0
+      ]
+    },
+    "class_type": "Efficient Loader",
+    "_meta": {
+      "title": "Efficient Loader"
+    }
+  },
+  "3": {
+    "inputs": {
+      "input_mode": "simple",
+      "lora_count": 3,
+      "lora_name_1": "StickersRedmond.safetensors",
+      "lora_wt_1": 1,
+      "model_str_1": 1,
+      "clip_str_1": 1,
+      "lora_name_2": "None",
+      "lora_wt_2": 1,
+      "model_str_2": 1,
+      "clip_str_2": 1,
+      "lora_name_3": "None",
+      "lora_wt_3": 1,
+      "model_str_3": 1,
+      "clip_str_3": 1,
+      "lora_name_4": "None",
+      "lora_wt_4": 1,
+      "model_str_4": 1,
+      "clip_str_4": 1,
+      "lora_name_5": "None",
+      "lora_wt_5": 1,
+      "model_str_5": 1,
+      "clip_str_5": 1,
+      "lora_name_6": "None",
+      "lora_wt_6": 1,
+      "model_str_6": 1,
+      "clip_str_6": 1,
+      "lora_name_7": "None",
+      "lora_wt_7": 1,
+      "model_str_7": 1,
+      "clip_str_7": 1,
+      "lora_name_8": "None",
+      "lora_wt_8": 1,
+      "model_str_8": 1,
+      "clip_str_8": 1,
+      "lora_name_9": "None",
+      "lora_wt_9": 1,
+      "model_str_9": 1,
+      "clip_str_9": 1,
+      "lora_name_10": "None",
+      "lora_wt_10": 1,
+      "model_str_10": 1,
+      "clip_str_10": 1,
+      "lora_name_11": "None",
+      "lora_wt_11": 1,
+      "model_str_11": 1,
+      "clip_str_11": 1,
+      "lora_name_12": "None",
+      "lora_wt_12": 1,
+      "model_str_12": 1,
+      "clip_str_12": 1,
+      "lora_name_13": "None",
+      "lora_wt_13": 1,
+      "model_str_13": 1,
+      "clip_str_13": 1,
+      "lora_name_14": "None",
+      "lora_wt_14": 1,
+      "model_str_14": 1,
+      "clip_str_14": 1,
+      "lora_name_15": "None",
+      "lora_wt_15": 1,
+      "model_str_15": 1,
+      "clip_str_15": 1,
+      "lora_name_16": "None",
+      "lora_wt_16": 1,
+      "model_str_16": 1,
+      "clip_str_16": 1,
+      "lora_name_17": "None",
+      "lora_wt_17": 1,
+      "model_str_17": 1,
+      "clip_str_17": 1,
+      "lora_name_18": "None",
+      "lora_wt_18": 1,
+      "model_str_18": 1,
+      "clip_str_18": 1,
+      "lora_name_19": "None",
+      "lora_wt_19": 1,
+      "model_str_19": 1,
+      "clip_str_19": 1,
+      "lora_name_20": "None",
+      "lora_wt_20": 1,
+      "model_str_20": 1,
+      "clip_str_20": 1,
+      "lora_name_21": "None",
+      "lora_wt_21": 1,
+      "model_str_21": 1,
+      "clip_str_21": 1,
+      "lora_name_22": "None",
+      "lora_wt_22": 1,
+      "model_str_22": 1,
+      "clip_str_22": 1,
+      "lora_name_23": "None",
+      "lora_wt_23": 1,
+      "model_str_23": 1,
+      "clip_str_23": 1,
+      "lora_name_24": "None",
+      "lora_wt_24": 1,
+      "model_str_24": 1,
+      "clip_str_24": 1,
+      "lora_name_25": "None",
+      "lora_wt_25": 1,
+      "model_str_25": 1,
+      "clip_str_25": 1,
+      "lora_name_26": "None",
+      "lora_wt_26": 1,
+      "model_str_26": 1,
+      "clip_str_26": 1,
+      "lora_name_27": "None",
+      "lora_wt_27": 1,
+      "model_str_27": 1,
+      "clip_str_27": 1,
+      "lora_name_28": "None",
+      "lora_wt_28": 1,
+      "model_str_28": 1,
+      "clip_str_28": 1,
+      "lora_name_29": "None",
+      "lora_wt_29": 1,
+      "model_str_29": 1,
+      "clip_str_29": 1,
+      "lora_name_30": "None",
+      "lora_wt_30": 1,
+      "model_str_30": 1,
+      "clip_str_30": 1,
+      "lora_name_31": "None",
+      "lora_wt_31": 1,
+      "model_str_31": 1,
+      "clip_str_31": 1,
+      "lora_name_32": "None",
+      "lora_wt_32": 1,
+      "model_str_32": 1,
+      "clip_str_32": 1,
+      "lora_name_33": "None",
+      "lora_wt_33": 1,
+      "model_str_33": 1,
+      "clip_str_33": 1,
+      "lora_name_34": "None",
+      "lora_wt_34": 1,
+      "model_str_34": 1,
+      "clip_str_34": 1,
+      "lora_name_35": "None",
+      "lora_wt_35": 1,
+      "model_str_35": 1,
+      "clip_str_35": 1,
+      "lora_name_36": "None",
+      "lora_wt_36": 1,
+      "model_str_36": 1,
+      "clip_str_36": 1,
+      "lora_name_37": "None",
+      "lora_wt_37": 1,
+      "model_str_37": 1,
+      "clip_str_37": 1,
+      "lora_name_38": "None",
+      "lora_wt_38": 1,
+      "model_str_38": 1,
+      "clip_str_38": 1,
+      "lora_name_39": "None",
+      "lora_wt_39": 1,
+      "model_str_39": 1,
+      "clip_str_39": 1,
+      "lora_name_40": "None",
+      "lora_wt_40": 1,
+      "model_str_40": 1,
+      "clip_str_40": 1,
+      "lora_name_41": "None",
+      "lora_wt_41": 1,
+      "model_str_41": 1,
+      "clip_str_41": 1,
+      "lora_name_42": "None",
+      "lora_wt_42": 1,
+      "model_str_42": 1,
+      "clip_str_42": 1,
+      "lora_name_43": "None",
+      "lora_wt_43": 1,
+      "model_str_43": 1,
+      "clip_str_43": 1,
+      "lora_name_44": "None",
+      "lora_wt_44": 1,
+      "model_str_44": 1,
+      "clip_str_44": 1,
+      "lora_name_45": "None",
+      "lora_wt_45": 1,
+      "model_str_45": 1,
+      "clip_str_45": 1,
+      "lora_name_46": "None",
+      "lora_wt_46": 1,
+      "model_str_46": 1,
+      "clip_str_46": 1,
+      "lora_name_47": "None",
+      "lora_wt_47": 1,
+      "model_str_47": 1,
+      "clip_str_47": 1,
+      "lora_name_48": "None",
+      "lora_wt_48": 1,
+      "model_str_48": 1,
+      "clip_str_48": 1,
+      "lora_name_49": "None",
+      "lora_wt_49": 1,
+      "model_str_49": 1,
+      "clip_str_49": 1
+    },
+    "class_type": "LoRA Stacker",
+    "_meta": {
+      "title": "LoRA Stacker"
+    }
+  },
+  "4": {
+    "inputs": {
+      "seed": 940769864734814,
+      "steps": 20,
+      "cfg": 7,
+      "sampler_name": "dpmpp_2m_sde",
+      "scheduler": "karras",
+      "denoise": 1,
+      "preview_method": "auto",
+      "vae_decode": "true",
+      "model": [
+        "2",
+        0
+      ],
+      "positive": [
+        "2",
+        1
+      ],
+      "negative": [
+        "2",
+        2
+      ],
+      "latent_image": [
+        "2",
+        3
+      ],
+      "optional_vae": [
+        "2",
+        4
+      ]
+    },
+    "class_type": "KSampler (Efficient)",
+    "_meta": {
+      "title": "KSampler (Efficient)"
+    }
+  },
+  "5": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "4",
+        5
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "Save Image"
+    }
+  },
+  "8": {
+    "inputs": {},
+    "class_type": "BRIA_RMBG_ModelLoader_Zho",
+    "_meta": {
+      "title": "🧹BRIA_RMBG Model Loader"
+    }
+  },
+  "9": {
+    "inputs": {
+      "rmbgmodel": [
+        "8",
+        0
+      ],
+      "image": [
+        "4",
+        5
+      ]
+    },
+    "class_type": "BRIA_RMBG_Zho",
+    "_meta": {
+      "title": "🧹BRIA RMBG"
+    }
+  },
+  "10": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "9",
+        0
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "Save Image"
+    }
+  },
+  "11": {
+    "inputs": {
+      "upscale_by": 2,
+      "seed": 456216621533243,
+      "steps": 10,
+      "cfg": 8,
+      "sampler_name": "euler",
+      "scheduler": "normal",
+      "denoise": 0.2,
+      "mode_type": "Linear",
+      "tile_width": 512,
+      "tile_height": 512,
+      "mask_blur": 8,
+      "tile_padding": 32,
+      "seam_fix_mode": "None",
+      "seam_fix_denoise": 1,
+      "seam_fix_width": 64,
+      "seam_fix_mask_blur": 8,
+      "seam_fix_padding": 16,
+      "force_uniform_tiles": true,
+      "tiled_decode": false,
+      "image": [
+        "4",
+        5
+      ],
+      "model": [
+        "12",
+        0
+      ],
+      "positive": [
+        "13",
+        0
+      ],
+      "negative": [
+        "14",
+        0
+      ],
+      "vae": [
+        "12",
+        2
+      ],
+      "upscale_model": [
+        "15",
+        0
+      ]
+    },
+    "class_type": "UltimateSDUpscale",
+    "_meta": {
+      "title": "Ultimate SD Upscale"
+    }
+  },
+  "12": {
+    "inputs": {
+      "ckpt_name": "dreamshaper_8.safetensors"
+    },
+    "class_type": "CheckpointLoaderSimple",
+    "_meta": {
+      "title": "Load Checkpoint"
+    }
+  },
+  "13": {
+    "inputs": {
+      "text": "svg sticker",
+      "clip": [
+        "12",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Prompt)"
+    }
+  },
+  "14": {
+    "inputs": {
+      "text": "nsfw",
+      "clip": [
+        "12",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Prompt)"
+    }
+  },
+  "15": {
+    "inputs": {
+      "model_name": "4x-AnimeSharp.pth"
+    },
+    "class_type": "UpscaleModelLoader",
+    "_meta": {
+      "title": "Load Upscale Model"
+    }
+  },
+  "16": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "11",
+        0
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "Save Image"
+    }
+  },
+  "17": {
+    "inputs": {
+      "rmbgmodel": [
+        "8",
+        0
+      ],
+      "image": [
+        "11",
+        0
+      ]
+    },
+    "class_type": "BRIA_RMBG_Zho",
+    "_meta": {
+      "title": "🧹BRIA RMBG"
+    }
+  },
+  "18": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "17",
+        0
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "Save Image"
+    }
+  }
+}
diff --git a/services/rewarding/app.py b/services/rewarding/app.py
index 6140c4c0..a4a56e51 100644
--- a/services/rewarding/app.py
+++ b/services/rewarding/app.py
@@ -136,7 +136,7 @@ async def __call__(self, reward_request: RewardRequest):
     args = get_args()
     model_deployment = serve.deployment(
         ModelDeployment,
-        name="model_deployment",
+        name="model_deployment-reward",
         num_replicas=args.num_replicas,
         ray_actor_options={"num_gpus": args.num_gpus},
     )
@@ -144,12 +144,13 @@ async def __call__(self, reward_request: RewardRequest):
         model_deployment.bind(
             MODEL_CONFIG[args.model_name],
         ),
-        name="model_deployment",
+        name="model_deployment-reward",
     )
-    model_handle = serve.get_deployment_handle("model_deployment", "model_deployment")
+    model_handle = serve.get_deployment_handle("model_deployment-reward", "model_deployment-reward")
     app = RewardApp(model_handle, args)
     uvicorn.run(
         app.app,
         host="0.0.0.0",
         port=args.port,
-    )
\ No newline at end of file
+    )
+    
\ No newline at end of file