AV_IPAdapterPipeline

Documentation

• Class name: AV_IPAdapterPipeline
• Category: Art Venture/IP Adapter
• Output node: False

The AV_IPAdapterPipeline node is designed to load and configure IP adapter and clip vision models for use in art generation pipelines. It facilitates the integration of these models into a unified pipeline, enabling enhanced image processing and manipulation capabilities.

Input types

Required

• ip_adapter_name
  • Specifies the name of the IP adapter model to be loaded. This is crucial for identifying and loading the correct IP adapter model for the pipeline.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• clip_name
  • Determines the name of the clip vision model to be loaded. This is essential for fetching and integrating the appropriate clip vision model into the pipeline.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str

Output types

• p
  • Comfy dtype: IPADAPTER
  • unknown
  • Python dtype: unknown

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

    class AV_IPAdapterPipeline:
        @classmethod
        def INPUT_TYPES(cls):
            return {
                "required": {
                    "ip_adapter_name": (folder_paths.get_filename_list("ipadapter"),),
                    "clip_name": (folder_paths.get_filename_list("clip_vision"),),
                }
            }

        RETURN_TYPES = ("IPADAPTER",)
        RETURN_NAMES = "pipeline"
        CATEGORY = "Art Venture/IP Adapter"
        FUNCTION = "load_ip_adapter"

        def load_ip_adapter(ip_adapter_name, clip_name):
            ip_adapter = loader.load_ipadapter_model(ip_adapter_name)[0]

            clip_path = folder_paths.get_full_path("clip_vision", clip_name)
            clip_vision = comfy.clip_vision.load(clip_path)

            pipeline = {"ipadapter": {"model": ip_adapter}, "clipvision": {"model": clip_vision}}
            return pipeline