diff --git a/NODES.md b/NODES.md deleted file mode 100644 index 2613c27..0000000 --- a/NODES.md +++ /dev/null @@ -1,260 +0,0 @@ -## Nodes List - -### Workflow - -#### TT FLUX Workflow Settings - -Node for configuring Flux workflow generation parameters. - -#### TT FLUX Workflow Settings (Advanced) - -Advanced node for configuring Flux workflow generation parameters with separate CLIP-L and T5XXL prompts. - -#### TT Flux2 Workflow Settings - -Use this node as the single source of truth for FLUX2 workflow parameters. The `WORKFLOW_CONFIG` output is -designed for context-aware nodes that consume a TT_WORKFLOW_CONFIG directly. Individual outputs are available -for connecting to standard ComfyUI nodes. The sigma schedule (`SCHEDULER`) is computed automatically from -the seed and resolution via `get_schedule`. - -#### TT Flux2 Workflow Settings (Advanced) - -Advanced version of TT Flux2 Workflow Settings with `prompt` and `lora_triggers` fields included directly in the -node. Both are stored in the `WORKFLOW_CONFIG` output alongside all other sampling parameters, making this node -sufficient as the sole configuration source for full context-driven FLUX2 pipelines. Individual outputs remain -available for connecting to standard ComfyUI nodes. - -#### TT SDXL Workflow Settings - -Node for configuring SDXL workflow generation parameters. - -#### TT SDXL Workflow Settings (Advanced) - -Advanced SDXL workflow configuration with separate CLIP-L/G prompts and aesthetic scores. - -### Latent - -#### TT Latent Factory - -Select aspect ratio, resolution, and orientation to automatically compute pixel dimensions suited for the chosen -model. FLUX1.D uses 16-channel latents, FLUX2.D uses 128-channel, SDXL uses 4-channel. `clip_multiplier` scales the TARGET -dimensions relative to the image dimensions — useful for multi-resolution CLIP conditioning. Connect `RANDOM_NOISE` -directly to a sampler node for reproducible noise tied to `noise_seed`. - -### Loaders - -#### TT SDXL Models Loader - -All-in-one model loader for SDXL workflows with checkpoint merging support. - -#### TT SDXL Models Loader (Advanced) - -Extended all-in-one model loader for SDXL with checkpoint merging and LoRA support. - -#### TT GGUF Models Loader - -All-in-one loader for GGUF-quantized models. Place your `.gguf` diffusion model files in the `diffusion_models` or `unet` directory, CLIP files in `text_encoders` or `clip` directory. VAE can be any standard ComfyUI-compatible VAE file. - -#### TT GGUF Models Loader (Advanced) - -Extended version of GGUF Models Loader. Supports up to 4 LoRAs loaded simultaneously. Enable `apply_sampling` to apply flux sampling shift patch — useful for improving quality at non-standard resolutions. Advanced parameters are hidden by default and can be revealed via the node's show/hide controls. - -#### TT FLUX Models Loader - -All-in-one model loader for Flux workflows. - -#### TT FLUX Models Loader (Advanced) - -Extended all-in-one model loader for Flux with sampling patches, LoRA support, and advanced settings. - -### Text Encoder - -#### TT CLIP Text Encode FLUX - -Flux text encoder with separate CLIP-L and T5-XXL prompt inputs. - -#### TT CLIP Text Encode FLUX (Context) - -Context-based Flux text encoder that extracts prompts from workflow config. - -#### TT CLIP Text Encode SDXL - -SDXL text encoder with separate CLIP-L and CLIP-G prompt inputs and conditioning parameters. - -#### TT CLIP Text Encode SDXL (Context) - -Context-based SDXL text encoder that extracts prompts and parameters from workflow config. - -#### TT Clip Text Encode Flux2 - -Encodes text prompts specifically for FLUX2 models. Enter your main prompt in `prompt` and any LoRA-specific trigger -words separately in `lora_triggers` — the node combines them internally. Adjust `guidance` to control how strongly -the model follows the prompt (3.5 is a good starting point for FLUX2). - -#### TT Clip Text Encode Flux2 (Context) - -Context-aware version of the FLUX2 text encoder. Instead of individual inputs, it reads `model`, `clip`, and -`workflow_config` (containing `prompt`, `lora_triggers`, and `guidance`) from the passed `context`. The resulting -guider is both returned as an output and stored back into the context under the `guider` key. Raises an error if -any of the required fields are missing from the context. - -### Samplers - -#### TT KSampler - -Standard KSampler for generating images. Accepts all common sampling parameters and returns a denoised latent ready for -VAE decoding. - -#### TT KSampler (Advanced) - -Advanced sampler for multi-stage workflows and fine control. Use start_step/last_step for partial denoising, add_noise -to control noise injection, and denoise for strength control. Useful for img2img, refinement passes, and complex -sampling workflows. - -#### TT KSampler (Context) - -Simplified sampler for context-based workflows. Automatically extracts all sampling parameters from the context object: - -- Model, positive/negative conditioning, and latent from context -- Seed, steps, cfg, sampler_name, and scheduler from workflow_config - -Requires context to contain: model, latent, and workflow_config. Raises error if any required component is missing. - -#### TT KSampler (Two Stages) - -Automated two-stage sampling workflow. First performs a draft pass with partial denoising, then refines the result with -a second pass. Each stage can use different samplers, schedulers, and step counts. Useful for quick previews followed by -quality refinement, or combining different sampling strategies. - -#### TT KSampler (Guided) - -Runs guided diffusion sampling on the input latent. Connect a guider from a text encoder node, sigmas from a -scheduler, and a sampler from a workflow settings node. `random_noise` controls stochasticity — use a seeded -noise node for reproducible results. - -### VAE - -#### TT VAE Decode (Context) - -Simplified decoder for context-based workflows. Automatically extracts VAE and latent from context, decodes to image -space, and stores the result back in context. Handles nested tensors and reshapes output to standard format. Raises -error if VAE or latent is missing from context. - -#### TT VAE Decode (Tiled) - -Decode large latent images by processing them in smaller tiles. Useful for generating high-resolution images that would -otherwise exceed VRAM capacity. The overlap parameter helps reduce visible seams between tiles. Enable circular padding -for seamless texture generation. - -#### TT Vae Encode (Context) - -Encodes pixel-space images into latent representations for diffusion processing. Extracts VAE and image from context, -performs encoding, and stores the result back in context. - -Requires context to contain both `vae` and `image` components. Raises error if either is missing. - -#### TT Vae Encode (Tiled) - -Processes large images in smaller tiles to reduce memory requirements during VAE encoding. Useful for encoding -high-resolution images that would otherwise cause out-of-memory errors. - -Tile size should be set based on available VRAM (smaller tiles = less memory). Overlap prevents visible seams at tile -boundaries - higher overlap produces smoother results but increases processing time. Recommended overlap is 10-15% of -tile size. - -### Postproduction - -#### TT Apply LUT - -Apply professional color grading using LUT files. Place your .cube LUT files in the designated LUT directory. Adjust -strength to blend between original and graded image (1.0 = full LUT, 0.0 = original). Choose colorspace based on your -LUT file's intended working space. - -#### TT Add Film Grain - -Add realistic film grain texture to images for a cinematic aesthetic. Adjust scale for grain size, strength for -intensity, and saturation for color. The toe parameter controls the distribution curve of grain in shadows/highlights. -Use different seeds for varied grain patterns. - -#### TT Quick Image Upscaler - -Quick and simple AI upscaling node using tiled processing for memory efficiency. Select an upscale model from your -upscale_models directory. Adjust tile size based on VRAM - smaller tiles use less memory. Increase overlap to reduce -visible seams between tiles. - -#### TT Image Enhancer - -All-in-one image enhancement node for adjusting brightness, contrast, colors, and applying effects. Use default values ( -brightness: 0.0, contrast/gamma/saturation: 1.0, posterize: 8, solarize: 1.0) for no effect. Adjust individual -parameters as needed - effects are applied sequentially. - -#### TT Postproduction - -Complete post-production pipeline in one node. Toggle each effect on/off with boolean switches. Processing order: LUT → -Film Grain → Upscale. Disable any effect by setting its toggle to False. All effects are optional and can be used -independently or combined. - -#### TT Postproduction (Advanced) - -Complete post-production pipeline with full enhancement controls. Processing order: Image Enhancement → LUT → Film -Grain → Upscale. Toggle each effect on/off independently. Image enhancement includes brightness, contrast, gamma, hue, -saturation, sharpness, posterize, and solarize adjustments. All effects are optional. - -### Image - -#### TT Image Preview / Save - -Dual-purpose node that can preview images in the UI and/or save them to disk with extensive formatting options. - -#### TT Image Preview / Upscale / Save - -All-in-one node that can preview, upscale, and save images in a single step. Upscaling is applied before saving — the upscaled result is both displayed in the UI and written to disk. When `upscale_image` is disabled, the original image is used. When `save_image` is disabled, the image is only previewed in the UI without writing to disk. - -### Context - -#### TT Base Context - -Use this node to package your core workflow components into a single context object that can be passed through your -workflow and modified by other context nodes. - -#### TT Context - -Use this node to create a new context from scratch or modify specific parameters in an existing context. All parameters -are optional - provide only what you need to set or change. - -#### TT FLUX Large Context - -Use this node for Flux workflows when you need fine-grained control over CLIP-L and T5-XXL prompts separately, along -with Flux-specific guidance settings. - -#### TT SDXL Large Context - -Use this node for SDXL workflows when you need separate control over CLIP-L and CLIP-G prompts, aesthetic scores, and -target dimensions for conditioning. - -#### TT Even Larger Context - -Use this node when you need comprehensive control over all workflow parameters including ControlNet and masking. -Supports both SDXL (CLIP-L/G) and Flux (T5-XXL) conditioning simultaneously. - -#### TT Context Set Image - -Stores pixel-space image in context for use by downstream nodes. Overwrites existing image if present. - -#### TT Context Set Latent - -Stores latent representation in context for use by downstream nodes. Overwrites existing latent if present. - -#### TT Context Set Guider - -Sets the `guider` field inside a TT_CONTEXT object. Use this node when you have a guider produced outside the -context pipeline and need to inject it back in for use by subsequent context-aware nodes. - -#### TT Context Passthrough - -Use this node to pass context through your workflow while optionally modifying specific parameters without changing the -rest of the context. - ---- - -_(c) TenserTensor || Apache-2.0 (apache.org/licenses/LICENSE-2.0)_ diff --git a/README.md b/README.md index 0a4f6b5..9d57ed5 100644 --- a/README.md +++ b/README.md @@ -11,8 +11,7 @@ *— Alfred Bester, The Demolished Man* -A collection of custom nodes for ComfyUI that streamline common workflows. The main goal is to reduce visual clutter by -combining frequently used node chains into single, convenient loaders. +A collection of custom nodes for ComfyUI that streamline common workflows. The main goal is to reduce visual clutter by combining frequently used node chains into single, convenient loaders. > [!IMPORTANT] > ⚠️ **Note:** The pack is currently undergoing refactoring and migration to ComfyUI API V3. Some nodes are marked as deprecated and will be removed in a future major release. Please check node descriptions for migration guidance. @@ -56,10 +55,6 @@ comfy node install tenser-tensor/ComfyUI-TenserTensor Restart ComfyUI after installation. -## Nodes List - -[Nodes List](NODES.md) - ## Acknowledgments This project uses GGUF file handling code from [City96](https://github.com/city96).