pipeIN (Legacy)

Documentation

• Class name: ttN pipeIN
• Category: 🌏 tinyterra/legacy
• Output node: False

The ttN pipeIN node is designed for initializing and configuring pipelines within the tinyterra ecosystem, specifically tailored for legacy applications. It focuses on setting up the initial parameters required for a pipeline, including models, conditioning, latent space, VAE, CLIP, and seed values, along with optional image inputs.

Input types

Required

• model
  • Specifies the model to be used in the pipeline, serving as the foundational component for subsequent operations.
  • Comfy dtype: MODEL
  • Python dtype: str
• pos
  • Defines positive conditioning inputs to guide the model's generation towards desired attributes or features.
  • Comfy dtype: CONDITIONING
  • Python dtype: str
• neg
  • Specifies negative conditioning inputs to steer the model's generation away from certain attributes or features.
  • Comfy dtype: CONDITIONING
  • Python dtype: str
• latent
  • Determines the latent space dimensions to be explored during generation, affecting the diversity and novelty of outputs.
  • Comfy dtype: LATENT
  • Python dtype: str
• vae
  • Specifies the VAE (Variational Autoencoder) to be used for generating or refining outputs, contributing to the quality and variability of the results.
  • Comfy dtype: VAE
  • Python dtype: str
• clip
  • Defines the CLIP model to be used for semantic understanding and alignment of generated content with textual descriptions.
  • Comfy dtype: CLIP
  • Python dtype: str
• seed
  • Sets the seed value for random number generation, ensuring reproducibility of results.
  • Comfy dtype: INT
  • Python dtype: int

Optional

• image
  • Optional parameter for including an image input to be used in conjunction with other inputs for generation or refinement.
  • Comfy dtype: IMAGE
  • Python dtype: str

Output types

• pipe
  • Comfy dtype: PIPE_LINE
  • Outputs a configured pipeline object ready for further processing or generation within the tinyterra ecosystem.
  • Python dtype: dict

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class ttN_pipe_IN:
    version = '1.1.0'
    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "model": ("MODEL",),
                "pos": ("CONDITIONING",),
                "neg": ("CONDITIONING",),
                "latent": ("LATENT",),
                "vae": ("VAE",),
                "clip": ("CLIP",),
                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
            },"optional": {
                "image": ("IMAGE",),
            },
            "hidden": {"ttNnodeVersion": ttN_pipe_IN.version},
        }

    RETURN_TYPES = ("PIPE_LINE", )
    RETURN_NAMES = ("pipe", )
    FUNCTION = "flush"

    CATEGORY = "🌏 tinyterra/legacy"

    def flush(self, model, pos=0, neg=0, latent=0, vae=0, clip=0, image=0, seed=0):
        pipe = {"model": model,
                "positive": pos,
                "negative": neg,
                "vae": vae,
                "clip": clip,

                "refiner_model": None,
                "refiner_positive": None,
                "refiner_negative": None,
                "refiner_vae": None,
                "refiner_clip": None,

                "samples": latent,
                "images": image,
                "seed": seed,

                "loader_settings": {}
        }
        return (pipe, )