# Documentation - Class name: IPAdapterModelHelper __Inspire - Category: InspirePack/models - Output node: False IPAdapterModelHelper节点旨在促进Inspire包中各种模型的集成和管理，确保兼容性和最佳性能。它负责动态加载模型、错误检查，以及应用IPAdapter配置以增强模型的互操作性和功能。 # Input types ## Required - model - 将要应用IPAdapter配置的主要模型。这个参数对于定义将被IPAdapter增强或修改的基础模型至关重要。 - Comfy dtype: MODEL - Python dtype: str - clip - 指定与主模型一起使用的CLIP模型，以增强性能和兼容性。 - Comfy dtype: CLIP - Python dtype: str - preset - 定义模型设置的预设配置，决定要加载和应用哪些模型和设置。 - Comfy dtype: COMBO[STRING] - Python dtype: str - lora_strength_model - 调整应用于模型的LoRA修改的强度，允许对模型的行为进行微调。 - Comfy dtype: FLOAT - Python dtype: float - lora_strength_clip - 调整应用于CLIP模型的LoRA修改的强度，能够精确控制其与主模型的集成。 - Comfy dtype: FLOAT - Python dtype: float - insightface_provider - 指定InsightFace模型的提供者，该模型用于面部识别和增强任务。 - Comfy dtype: COMBO[STRING] - Python dtype: str - cache_mode - 决定模型的缓存策略，特别影响InsightFace模型的缓存和使用方式。 - Comfy dtype: COMBO[STRING] - Python dtype: str # Output types - IPADAPTER_PIPE - 包含IPAdapter和其他模型的管道配置，准备就绪可以进行处理。 - Comfy dtype: IPADAPTER_PIPE - Python dtype: tuple - IPADAPTER - 加载的IPAdapter模型，准备应用于主模型。 - Comfy dtype: IPADAPTER - Python dtype: object - CLIP_VISION - 加载并配置用于管道内的CLIP视觉模型。 - Comfy dtype: CLIP_VISION - Python dtype: object - INSIGHTFACE - 加载用于面部识别和增强任务的InsightFace模型。 - Comfy dtype: INSIGHTFACE - Python dtype: object - MODEL - 应用了IPAdapter配置的增强模型，准备在管道中进一步使用。 - Comfy dtype: MODEL - Python dtype: object - CLIP - 加载并配置用于管道内文本-图像任务的CLIP模型。 - Comfy dtype: CLIP - Python dtype: object - insightface_cache_key - InsightFace模型的缓存键，用于缓存和检索目的。 - Comfy dtype: STRING - Python dtype: str - clip_vision_cache_key - CLIP视觉模型的缓存键，便于高效缓存和访问。 - Comfy dtype: STRING - Python dtype: str ## Usage tips - Infra type: `CPU` - Common nodes: unknown ## Source code ```python class IPAdapterModelHelper: @classmethod def INPUT_TYPES(s): return { "required": { "model": ("MODEL",), "clip": ("CLIP",), "preset": (list(model_preset.keys()),), "lora_strength_model": ("FLOAT", {"default": 1.0, "min": -20.0, "max": 20.0, "step": 0.01}), "lora_strength_clip": ("FLOAT", {"default": 1.0, "min": -20.0, "max": 20.0, "step": 0.01}), "insightface_provider": (["CPU", "CUDA", "ROCM"], ), "cache_mode": (["insightface only", "clip_vision only", "all", "none"], {"default": "insightface only"}), }, "hidden": {"unique_id": "UNIQUE_ID"} } RETURN_TYPES = ("IPADAPTER_PIPE", "IPADAPTER", "CLIP_VISION", "INSIGHTFACE", "MODEL", "CLIP", "STRING", "STRING") RETURN_NAMES = ("IPADAPTER_PIPE", "IPADAPTER", "CLIP_VISION", "INSIGHTFACE", "MODEL", "CLIP", "insightface_cache_key", "clip_vision_cache_key") FUNCTION = "doit" CATEGORY = "InspirePack/models" def doit(self, model, clip, preset, lora_strength_model, lora_strength_clip, insightface_provider, cache_mode="none", unique_id=None): if 'IPAdapter' not in nodes.NODE_CLASS_MAPPINGS: utils.try_install_custom_node('https://github.com/cubiq/ComfyUI_IPAdapter_plus', "To use 'IPAdapterModelHelper' node, 'ComfyUI IPAdapter Plus' extension is required.") raise Exception(f"[ERROR] To use IPAdapterModelHelper, you need to install 'ComfyUI IPAdapter Plus'") is_sdxl_preset = 'SDXL' in preset is_sdxl_model = isinstance(clip.tokenizer, sdxl_clip.SDXLTokenizer) if is_sdxl_preset != is_sdxl_model: server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 1, "label": "IPADAPTER (fail)"}) server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 2, "label": "CLIP_VISION (fail)"}) server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 3, "label": "INSIGHTFACE (fail)"}) server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 4, "label": "MODEL (fail)"}) server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 5, "label": "CLIP (fail)"}) print(f"[ERROR] IPAdapterModelHelper: You cannot mix SDXL and SD1.5 in the checkpoint and IPAdapter.") raise Exception("[ERROR] You cannot mix SDXL and SD1.5 in the checkpoint and IPAdapter.") ipadapter, clipvision, lora, is_insightface = model_preset[preset] ipadapter, ok1 = lookup_model("ipadapter", ipadapter) clipvision, ok2 = lookup_model("clip_vision", clipvision) lora, ok3 = lookup_model("loras", lora) if ok1 == "OK": ok1 = "IPADAPTER" else: ok1 = f"IPADAPTER ({ok1})" if ok2 == "OK": ok2 = "CLIP_VISION" else: ok2 = f"CLIP_VISION ({ok2})" server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 1, "label": ok1}) server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 2, "label": ok2}) if ok3 == "FAIL": server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 4, "label": "MODEL (fail)"}) server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 5, "label": "CLIP (fail)"}) else: server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 4, "label": "MODEL"}) server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 5, "label": "CLIP"}) if ok1 == "FAIL" or ok2 == "FAIL" or ok3 == "FAIL": raise Exception("ERROR: Failed to load several models in IPAdapterModelHelper.") if ipadapter is not None: ipadapter = nodes.NODE_CLASS_MAPPINGS["IPAdapterModelLoader"]().load_ipadapter_model(ipadapter_file=ipadapter)[0] ccache_key = "" if clipvision is not None: if cache_mode in ["clip_vision only", "all"]: ccache_key = clipvision if ccache_key not in backend_support.cache: backend_support.update_cache(ccache_key, "clipvision", (False, nodes.CLIPVisionLoader().load_clip(clip_name=clipvision)[0])) _, (_, clipvision) = backend_support.cache[ccache_key] else: clipvision = nodes.CLIPVisionLoader().load_clip(clip_name=clipvision)[0] if lora is not None: model, clip = nodes.LoraLoader().load_lora(model=model, clip=clip, lora_name=lora, strength_model=lora_strength_model, strength_clip=lora_strength_clip) def f(x): return nodes.LoraLoader().load_lora(model=x, clip=clip, lora_name=lora, strength_model=lora_strength_model, strength_clip=lora_strength_clip) lora_loader = f else: def f(x): return x lora_loader = f if 'IPAdapterInsightFaceLoader' in nodes.NODE_CLASS_MAPPINGS: insight_face_loader = nodes.NODE_CLASS_MAPPINGS['IPAdapterInsightFaceLoader']().load_insightface else: print("'ComfyUI IPAdapter Plus' extension is either too outdated or not installed.") insight_face_loader = None icache_key = "" if is_insightface: if insight_face_loader is None: raise Exception(f"[ERROR] 'ComfyUI IPAdapter Plus' extension is either too outdated or not installed.") if cache_mode in ["insightface only", "all"]: icache_key = 'insightface-' + insightface_provider if icache_key not in backend_support.cache: backend_support.update_cache(icache_key, "insightface", (False, insight_face_loader(insightface_provider)[0])) _, (_, insightface) = backend_support.cache[icache_key] else: insightface = insight_face_loader(insightface_provider)[0] server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 3, "label": "INSIGHTFACE"}) else: insightface = None server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 3, "label": "INSIGHTFACE (N/A)"}) pipe = ipadapter, model, clipvision, insightface, lora_loader return pipe, ipadapter, clipvision, insightface, model, clip, icache_key, ccache_key ```