Add Anima-3.8B architecture model.

README.md

@@ -98,6 +98,7 @@ models:
   - lightx2v/Qwen-Image-2512-Lightning
   - lightx2v/Qwen-Image-Edit-2511-Lightning
   - LyliaEngine/Pony_Diffusion_V6_XL
+  - lylogummy/Anima-3.8B
   - MIC-Lab/illustriousXLv0.1_controlnet
   - MIC-Lab/illustriousXLv1.1_controlnet
   - misri/hassakuXLIllustrious_v30

comfy_integration/setup.py

@@ -88,6 +88,14 @@ def initialize_comfyui():
     else:
         print("✅ comfyui-krea2edit extension already exists.")
 
+    # 6. comfyui-anima-3-8B
+    anima_38b_nodes_path = os.path.join(APP_DIR, "custom_nodes", "comfyui-anima-3-8B")
+    if not os.path.exists(anima_38b_nodes_path):
+        os.system(f"git clone https://github.com/GumGum10/comfyui-anima-3-8B.git {anima_38b_nodes_path}")
+        print("✅ comfyui-anima-3-8B extension cloned.")
+    else:
+        print("✅ comfyui-anima-3-8B extension already exists.")
+
     print(f"✅ Current working directory is: {os.getcwd()}")
     
     import comfy.model_management

core/pipelines/sd_image_pipeline.py

@@ -190,6 +190,7 @@ class SdImagePipeline(BasePipeline):
             }
 
             if isinstance(path_or_components, dict):
+                workflow_inputs.update(path_or_components)
                 workflow_inputs.update({
                     'unet_name': path_or_components.get('unet'),
                     'unet_uncond_name': path_or_components.get('unet_uncond'),
@@ -200,6 +201,9 @@ class SdImagePipeline(BasePipeline):
                     'clip3_name': path_or_components.get('clip3'),
                     'clip4_name': path_or_components.get('clip4'),
                     'lora_name': path_or_components.get('lora'),
+                    'qwen35_model': path_or_components.get('qwen35_model'),
+                    'adapter_name': path_or_components.get('adapter_name'),
+                    'adapter_strength': path_or_components.get('adapter_strength', 1.0),
                 })
             else:
                 workflow_inputs['model_name'] = path_or_components

core/pipelines/workflow_recipes/_partials/conditioning/anima-3.8b.yaml

@@ -0,0 +1,83 @@
+nodes:
+  unet_loader:
+    class_type: UNETLoader
+    title: "Load Diffusion Model"
+    params:
+      weight_dtype: "default"
+  clip_loader:
+    class_type: CLIPLoader
+    title: "Load CLIP"
+    params:
+      type: "stable_diffusion"
+      device: "default"
+  qwen35_loader:
+    class_type: AnimaQwen35Loader
+    title: "Load Anima Qwen35"
+  unified_prompt:
+    class_type: AnimaQwen35UnifiedPrompt
+    title: "Anima Qwen35 Unified Prompt"
+    params:
+      adapter_name: "Anima-3.8B-expanded_adapter.safetensors"
+      adapter_strength: 1.0
+  neg_prompt:
+    class_type: CLIPTextEncode
+    title: "CLIP Text Encode (Negative)"
+  vae_loader:
+    class_type: VAELoader
+    title: "Load VAE"
+
+connections:
+  - from: "unet_loader:0"
+    to: "ksampler:model"
+  - from: "unet_loader:0"
+    to: "unified_prompt:model"
+  - from: "clip_loader:0"
+    to: "unified_prompt:native_clip"
+  - from: "qwen35_loader:0"
+    to: "unified_prompt:qwen35_clip"
+  - from: "clip_loader:0"
+    to: "neg_prompt:clip"
+  - from: "unified_prompt:0"
+    to: "ksampler:positive"
+  - from: "neg_prompt:0"
+    to: "ksampler:negative"
+  - from: "vae_loader:0"
+    to: "vae_decode:vae"
+  - from: "vae_loader:0"
+    to: "vae_encode:vae"
+
+dynamic_lora_chains:
+  lora_chain:
+    template: "LoraLoader"
+    output_map:
+      "unet_loader:0": "model"
+      "clip_loader:0": "clip"
+    input_map:
+      "model": "model"
+      "clip": "clip"
+    end_input_map:
+      "model": ["ksampler:model", "unified_prompt:model"]
+      "clip": ["unified_prompt:native_clip", "neg_prompt:clip"]
+
+dynamic_anima_controlnet_lllite_chains:
+  anima_controlnet_lllite_chain:
+    ksampler_node: "ksampler"
+
+dynamic_conditioning_chains:
+  conditioning_chain:
+    ksampler_node: "ksampler"
+    clip_source: "clip_loader:0"
+
+dynamic_pid_chains:
+  pid_chain:
+    ksampler_node: "ksampler"
+
+ui_map:
+  positive_prompt: "unified_prompt:prompt"
+  negative_prompt: "neg_prompt:text"
+  unet_name: "unet_loader:unet_name"
+  clip_name: "clip_loader:clip_name"
+  qwen35_model: "qwen35_loader:qwen35_model"
+  adapter_name: "unified_prompt:adapter_name"
+  adapter_strength: "unified_prompt:adapter_strength"
+  vae_name: "vae_loader:vae_name"

mcp_tools/common.py

@@ -166,8 +166,7 @@ _COMMON_OPTIONAL_INPUTS_SCHEMA = {
         "type": "integer",
         "default": 60,
         "minimum": 1,
-        "maximum": 120,
-        "description": "GPU execution time quota allocation in seconds on HuggingFace ZeroGPU spaces (default: 60, maximum: 120)."
+        "description": "GPU execution time quota allocation in seconds on HuggingFace ZeroGPU spaces (default: 60)."
     },
     "steps": {
         "type": "integer",

mcp_tools/mcp_gradio_integration.py

@@ -116,7 +116,7 @@ def register_high_level_mcp_apis(demo):
 OPTIONAL CONTROL PARAMETERS:
 - seed (int): Random seed (-1 for random, >=0 for deterministic reproducibility). Default: -1.
 - batch_size (int): Number of images generated per batch (1 to 16). Default: 1.
-- zero_gpu_duration (int): GPU quota allocation in seconds on HuggingFace ZeroGPU spaces (default: 60, max: 120).
+- zero_gpu_duration (int): GPU quota allocation in seconds on HuggingFace ZeroGPU spaces (default: 60).
 - negative_prompt (str): Text prompt specifying elements to avoid.
 
 IMPORTANT FORMAT RULES FOR 'chain':

mcp_tools/run.py

@@ -23,7 +23,7 @@ def handle_run(params: dict) -> dict:
     [OPTIONAL CONTROL PARAMETERS]
     - seed (int): Random seed for generation. Default: -1 (random seed). Specify >=0 for deterministic reproducibility.
     - batch_size (int): Number of images generated in a single batch (1 to 16, default: 1).
-    - zero_gpu_duration (int): GPU quota allocation in seconds on HuggingFace ZeroGPU spaces (default: 60, max: 120).
+    - zero_gpu_duration (int): GPU quota allocation in seconds on HuggingFace ZeroGPU spaces (default: 60).
     - negative_prompt (str): Text prompt specifying undesirable elements to avoid.
     - steps (int), cfg (float), sampler (str), scheduler (str): Inference hyperparams (auto-applied from model defaults if omitted).
 

ui/imagegen_ui.py

@@ -164,7 +164,7 @@ def create_ui():
                     components[f'seed_{prefix}'] = gr.Number(label="Seed (-1 for random)", value=-1, precision=0)
                     components[f'batch_size_{prefix}'] = gr.Slider(label="Batch Size", minimum=1, maximum=16, step=1, value=1)
                 with gr.Row():
-                    components[f'zero_gpu_{prefix}'] = gr.Number(label="ZeroGPU Duration (s)", value=60, placeholder="Default: 60s, Max: 120s", info="Optional: Set how long to reserve the GPU. Longer jobs may need more time.")
+                    components[f'zero_gpu_{prefix}'] = gr.Number(label="ZeroGPU Duration (s)", value=60, placeholder="Default: 60s", info="Optional: Set how long to reserve the GPU. Longer jobs may need more time.")
 
             with gr.Column(scale=1):
                 components[f'result_{prefix}'] = gr.Gallery(label="Result", show_label=False, columns=2, object_fit="contain", height=627)

ui/shared/ui_components.py

@@ -114,7 +114,7 @@ def create_base_parameter_ui(prefix, defaults=None):
         components[f'seed_{prefix}'] = gr.Number(label="Seed (-1 for random)", value=-1, precision=0)
         components[f'batch_size_{prefix}'] = gr.Slider(label="Batch Size", minimum=1, maximum=16, step=1, value=1)
     with gr.Row():
-        components[f'zero_gpu_{prefix}'] = gr.Number(label="ZeroGPU Duration (s)", value=60, placeholder="Default: 60s, Max: 120s", info="Optional: Set how long to reserve the GPU.")
+        components[f'zero_gpu_{prefix}'] = gr.Number(label="ZeroGPU Duration (s)", value=60, placeholder="Default: 60s", info="Optional: Set how long to reserve the GPU.")
             
     return components
 

utils/app_utils.py

@@ -649,7 +649,16 @@ def get_model_generation_defaults(model_display_name: str, model_type: str, defa
     if 'Default' in defaults_config:
         final_defaults.update(defaults_config['Default'])
 
-    model_type_key = next((key for key in defaults_config if key.lower().replace(" ", "-").replace(".", "") == model_type.lower()), None)
+    def _norm(s):
+        return str(s).lower().replace(" ", "-").replace(".", "")
+
+    norm_type = _norm(model_type)
+    model_type_key = next((
+        key for key in defaults_config 
+        if key.lower() == model_type.lower() 
+        or _norm(key) == norm_type 
+        or _norm(key) == model_type.lower()
+    ), None)
     if model_type_key:
         model_type_config = defaults_config[model_type_key]
         if '_defaults' in model_type_config:

yaml/constants.yaml

@@ -119,6 +119,14 @@ RESOLUTION_MAP:
     "3:4 (Classic Portrait)": [896, 1152]
     "3:2 (Photography)": [1216, 832]
     "2:3 (Photography Portrait)": [832, 1216]
+  anima-3.8b:
+    "1:1 (Square)": [1024, 1024]
+    "16:9 (Landscape)": [1344, 768]
+    "9:16 (Portrait)": [768, 1344]
+    "4:3 (Classic)": [1152, 896]
+    "3:4 (Classic Portrait)": [896, 1152]
+    "3:2 (Photography)": [1216, 832]
+    "2:3 (Photography Portrait)": [832, 1216]
   anima:
     "1:1 (Square)": [1024, 1024]
     "16:9 (Landscape)": [1344, 768]
@@ -263,6 +271,7 @@ MULTIPLIERS_MAP:
   qwen-image: 1
   longcat-image: 1
   cosmos-predict2: 1
+  anima-3.8b: 1
   anima: 1
   newbie-image: 1
   kandinsky-5: 32

yaml/file_list.yaml

@@ -509,6 +509,11 @@ file:
       source: "hf"
       repo_id: "nvidia/Cosmos-Predict2-14B-Text2Image"
       repository_file_path: "model.pt"
+    # Anima-3.8B
+    - filename: "Anima-3.8B.safetensors"
+      source: "hf"
+      repo_id: "lylogummy/Anima-3.8B"
+      repository_file_path: "difussion_models/Anima-3.8B.safetensors"
     # Anima
     - filename: "anima-turbo-v1.0.safetensors"
       source: "hf"
@@ -888,6 +893,15 @@ file:
       source: "hf"
       repo_id: "Comfy-Org/Lens"
       repository_file_path: "text_encoders/gpt_oss_20b_nvfp4.safetensors"
+    # Anima-3.8B
+    - filename: "qwen35_4b.safetensors"
+      source: "hf"
+      repo_id: "lylogummy/Anima-3.8B"
+      repository_file_path: "text_encoders/qwen35_4b.safetensors"
+    - filename: "Anima-3.8B-expanded_adapter.safetensors"
+      source: "hf"
+      repo_id: "lylogummy/Anima-3.8B"
+      repository_file_path: "text_encoders/Anima-3.8B-expanded_adapter.safetensors"
     # Anima
     - filename: "qwen_3_06b_base.safetensors"
       source: "hf"

yaml/model_architecture_features.yaml

@@ -84,6 +84,14 @@ cosmos-predict2:
   - conditioning
   - vae
 
+anima-3.8b:
+  enabled_chains:
+  - lora
+  - conditioning
+  - anima_controlnet_lllite
+  - vae
+  - pid
+
 anima:
   enabled_chains:
   - lora

yaml/model_architectures.yaml

@@ -13,6 +13,7 @@ architecture_order:
   - "Qwen-Image"
   - "LongCat-Image"
   - "Cosmos-Predict2"
+  - "Anima-3.8B"
   - "Anima"
   - "NewBie-Image"
   - "Kandinsky-5"
@@ -65,6 +66,9 @@ architectures:
   "Cosmos-Predict2":
     model_type: "cosmos-predict2"
     controlnet_key: "Cosmos-Predict2"
+  "Anima-3.8B":
+    model_type: "anima-3.8b"
+    controlnet_key: "Anima"
   "Anima":
     model_type: "anima"
     controlnet_key: "Anima"

yaml/model_defaults.yaml

@@ -152,6 +152,16 @@ Cosmos-Predict2:
     sampler_name: "euler"
     scheduler: "karras"
 
+Anima-3.8B:
+  _defaults:
+    steps: 32
+    cfg: 7.5
+    sampler_name: "res_multistep"
+    scheduler: "beta"
+    positive_prompt: "masterpiece, best quality, high quality, newest, year 2025, year 2024, \nDescription:\n"
+    negative_prompt: "worst quality, low quality, score_1, score_2, score_3, blurry, jpeg artifacts, sepia"
+    filename_prefix: "anima_3_8b"
+
 Anima:
   _defaults:
     steps: 30

yaml/model_list.yaml

@@ -232,6 +232,16 @@ Checkpoint:
           unet: "cosmos_predict2_14B_t2i.pt"
           clip: "oldt5_xxl_fp8_e4m3fn_scaled.safetensors"
           vae: "wan_2.1_vae.safetensors"
+  Anima-3.8B:
+    latent_type: sd3_latent
+    models:
+      - display_name: "lylogummy/Anima-3.8B"
+        components:
+          unet: "Anima-3.8B.safetensors"
+          clip: "qwen_3_06b_base.safetensors"
+          qwen35_model: "qwen35_4b.safetensors"
+          adapter_name: "Anima-3.8B-expanded_adapter.safetensors"
+          vae: "qwen_image_vae.safetensors"
   Anima:
     latent_type: latent
     models:

yaml/pid.yaml

@@ -4,7 +4,7 @@ PiD:
     architectures: ["flux2", "flux2-kv", "ideogram-4", "lens", "ernie-image"]
   - filepath: "pid_1.5_qwenimage_1024_to_4096_4step_int8_convrot.safetensors"
     latent_format: "qwenimage"
-    architectures: ["anima", "qwen-image", "krea-2"]
+    architectures: ["anima", "anima-3.8b", "qwen-image", "krea-2"]
   - filepath: "pid_1.5_flux1_1024_to_4096_4step_int8_convrot.safetensors"
     latent_format: "flux"
     architectures: ["longcat-image", "newbie-image", "z-image", "kandinsky-5", "ovis-image", "omnigen2", "chroma1", "hidream-i1", "flux1", "boogu-image"]