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