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Yoruichi Shihouin (Bleach) TI Embedding by Corneo
This is a textual inversion embedding for Yoruichi Shihouin from Bleach. Use corneoyoruichi to activate.
Recraft creative upscale
Upload an image to produce a Recraft creative upscale result. For your first run, choose a source image no larger than 5 MB, with width and height each no greater than 2048 pixels, then run the Pipe. The resulting image appears in Sweet Tea's output viewer; this workflow does not permanently save it through a SaveImage node. The image is sent to Recraft for a provider-priced upscale operation. This Pipe offers no prompt, scale factor, tuning controls or alternate modes. Uploaded transparency is not preserved because only the loader's RGB image output is connected.
Yor Forger - Thorn Princess version - TI Embedding by Corneo
This is a textual inversion embedding for Yor Forger / Yor Briar from Spy x Family in her Thorn Princess assassin outfit.
pony_negative for PianoMix
Even if you don't specify all the troublesome prompts, you can get a certain result by specifying one negative prompt.
Lens Text to Image
Create one image or a batch from a text prompt using the fixed Lens model, Lens text encoder, and Flux 2 VAE. No uploaded image is required. For a first run, describe your subject, composition, lighting, and style in Positive prompt, or use the supplied flower example. Leave Negative prompt empty unless you have specific exclusions. Keep the square, 2-megapixel output and supplied sampling defaults: 20 steps, CFG 5, Euler, and the simple schedule. Seed -1 chooses fresh starting noise on each run; use a nonnegative seed to select a fixed starting noise pattern. Increase Image count to generate multiple images together. Aspect ratio and Target megapixels jointly determine the output dimensions. Dimensions are aligned to multiples of eight and shared by the latent canvas and model sampling setup. Megapixels is an approximate pixel budget rather than a fixed width or height. Larger sizes and batches require more memory. CFG controls prompt guidance, including the influence of negative conditioning. Advanced controls select the sampling algorithm, distribute noise levels across the requested steps, and adjust CFG normalization and resolution-dependent sampling shifts. Pre-CFG normalization applies normalization before CFG combination without clamping and can amplify predictions; the default post-CFG mode only attenuates them. Base shift and Maximum shift work together with the selected output dimensions. Leave Add noise enabled and Denoise at 1 for ordinary text-to-image generation. Lower Denoise uses a shortened noise schedule on an empty latent canvas; it does not preserve or transform an existing image. Disabling Add noise removes the seeded starting-noise initialization, so the seed no longer controls that initialization. All generated images are returned through one batch image output using Sweet Tea's output transport. The workflow does not permanently save images through the original SaveImage node. The model stack and dimension plumbing are fixed; this Pipe does not accept an input image.
Wan 2.6 Reference-to-video
Generate one video featuring two referenced characters using Wan 2.6. Upload one reference video for each character. Both uploads are required and feed the same generation stage. Describe your scene and motion in the scene prompt, using character1 and character2 to identify the corresponding uploaded characters. English and Chinese prompts are supported. You can describe desired dialogue and sound, but exact delivery is not guaranteed. For a first run, replace the example battle prompt with your scene and keep the default 720p landscape size and 5-second duration. Choose multi for multiple shots with cuts or single for one continuous shot, and write matching shot instructions in your prompt. Available durations are 5 and 10 seconds; keep the requested actions and shots practical for the chosen duration. Use the negative prompt for unwanted elements, or leave it empty. Output size selects resolution and aspect ratio together. AI watermark requests the provider's watermark. Seed -1 randomizes each run; a fixed seed controls generation randomization. Advanced video output settings select the file container and codec; leave both on auto for the first run. The result is returned to Sweet Tea as one video. This tool exposes no FPS control. Generation sends the references and prompt to the Wan provider and uses a paid provider call.
Reskin a sprite and remove its background
Reimagine a sprite using an object description and a style reference, then remove the generated background. Upload both required images: the sprite whose composition and outline should guide the result, and an image showing the desired visual style. Replace the example object description with what you want to render, such as “copper gas lamp.” Gemini receives the sprite as image 1 and the style reference as image 2. For a first run, keep the supplied model, square aspect ratio, 1K resolution and random seed (-1). The default prompt requests the sprite's composition and outline, applies your object description and the reference style, and asks for a black background. Recraft background removal always processes the generated image before the result is returned. Outline preservation is a request to the model, not a guarantee of exact geometry or pixel alignment. Uploaded transparency is not carried through the reference-image paths. Choose either supplied Gemini model to change the generation model. Aspect ratio offers auto and the listed fixed ratios; auto follows the input image's aspect ratio, while another ratio can change framing. Resolution offers 1K, 2K and 4K; 2K and 4K use Gemini's native upscaler. Use -1 for a new random seed each run, or a fixed seed to request repeatability. Identical results are not guaranteed. For custom instructions, edit the advanced composition and style prompt fragments. The prompt joins composition instructions, object description and style instructions in that order without an added separator; preserve spaces or punctuation at their boundaries. The system instructions control Gemini's interpretation of the request. Editing these instructions does not bypass background removal; this interface has no removal bypass.
Topaz Bloom 2 image enhancement
Enhance an uploaded image with the workflow's fixed Topaz Bloom 2 preset and preview the enhanced result. For a first run, upload your source image and run the Pipe. The image upload is required and is the only editable control. The source configuration uses an empty prompt; its accompanying guidance says this lets the model create a prompt automatically. Prompt, seed, model selection and enhancement settings are fixed in this Pipe. No alternate modes or optional stages are exposed. Uploaded transparency is not preserved. Output scale and repeatable results are not established by the supplied source evidence. The selected output is an image preview; the original save node's PNG encoding settings do not apply to this output.
Create images from two references
Generate or edit an image with Gemini using two reference images and a written instruction. Upload both references, then explain which subjects, details or style to take from each. Both uploads are required and are sent together as context for one image request, rather than processed into separate outputs. For a first run, upload character and clothing references, describe how to combine them in a casual fashion pose, and keep the supplied 1:1 aspect ratio and 1K resolution. The references have no fixed character or clothing roles; you can request other compositions or edits. Choose an explicit aspect ratio for the output shape. Auto asks Gemini to match the input image proportions; an explicit ratio avoids ambiguity when the references differ. Resolution selects 1K, 2K or 4K; 2K and 4K use Gemini's native upscaler. The model selector offers Gemini 3 Pro Image Preview and Nano Banana 2 (Gemini 3.1 Flash Image). System instructions set foundational behavior; the supplied instructions prioritize interpreting the prompt visually and producing an image. Keep IMAGE for image-only responses, or select IMAGE+TEXT to request accompanying text from Gemini. This Pipe returns only generated images, so accompanying text is not delivered. Use seed -1 for a new random seed each run. Fixed seeds request best-effort consistency, not identical results. Reference details are interpreted by the model, so exact identity or garment reproduction is not guaranteed. Uploaded alpha masks are not connected, so reference transparency is not preserved. This workflow sends the prompt and reference images to Gemini through a paid provider request. Generated images are returned to Sweet Tea through an output transport that does not permanently save them through the workflow.
Gemini image editing with document context
Create an image from a required reference image and written instructions using Gemini, with optional text or PDF context. The generated image is delivered as the Pipe result. For a first run, upload a reference image, replace the example prompt with the changes you want, and describe which details to retain. Leave Aspect ratio on auto to follow the reference image's proportions, leave both document stages disabled, and run the Pipe. Choose an explicit aspect ratio to request different output proportions. To add document context, place a .txt or .pdf file in ComfyUI/input, enter its filename in the relevant document field, and enable that stage. These fields select existing files rather than uploading documents, and their empty defaults must be filled before enabling them. Either stage can be used independently; enable both with distinct files to supply two documents. Explain in your prompt how Gemini should use their contents. Seed -1 randomizes each run. A fixed seed requests best-effort consistency; identical results are not guaranteed. Generation instructions govern Gemini's interpretation of the prompt. Retain the directive to produce an image when editing them. Response format supports IMAGE and IMAGE+TEXT, but accompanying text is not delivered by this Pipe. This workflow requires a reference image even though Gemini supports other generation modes. Uploaded transparency is not preserved through the connected RGB image path. Image creation uses the Gemini provider and sends the reference image, instructions and enabled document context to that provider; provider billing applies.
Wan 2.1 video outpainting
Expand an uploaded video's canvas with generated surroundings using Wan 2.1 VACE, and export an H.264 MP4 with source audio when available. For a first run, upload a continuous scene and enter an outpainting prompt describing both the existing scene and the surroundings to add. Keep both aspect-ratio controls on Horizontal and retain the other defaults. If you change the canvas shape, set Aspect ratio and Continuation aspect ratio to the same choice: their generated batches must have matching dimensions. Both stages use the fixed I2V720p/HQ resolution preset. The input is resampled to 24 frames per second. Initial source size and Continuation source size set the original content's size in megapixels before padding to the target canvas. Smaller source frames can leave more space for generated surroundings; use matching sizes across stages for consistent framing. Each stage has its own mask-feathering and VACE control-strength settings. Control strength adjusts guidance from the padded source frames and masks. The workflow generates an initial 81-frame batch followed by three fixed continuation iterations. Each continuation requests 81 generated frames, carries the previous generated batch's last frame as a reference, and advances the source slice by 81 frames. The continuation source slices request up to frame index 405, approximately 16.9 seconds at 24 FPS. Supply enough continuous footage to cover those requests. This tool does not adapt its iteration count to the uploaded clip's length. The source's value labeled Length in Seconds controls loop arithmetic rather than exact playback duration and is not an editable duration control. Continuation slices request more conditioning frames than each generated batch; the supplied evidence does not establish precisely how excess conditioning frames are handled. Both stages share the prompt, negative prompt, seed, and CausVid LoRA. Seed -1 randomizes each run; a fixed seed reuses the shared noise seed. Initial and continuation sampling controls are independent. The supplied recipe uses CausVid strength 1, three Euler steps, normal scheduling, CFG 1, and denoise 1 in both stages. Keep these defaults for the first run; changes to LoRA strength affect both stages. Compression controls H.264 CRF: lower values retain more detail and generally create larger files. Trim to audio is enabled by default and can shorten the encoded video to the source audio's length. Disable it to retain generated frames beyond shorter audio. Playback remains fixed at 24 FPS. Outpainting synthesizes content and can alter the original region or show transitions between batches. Scene cuts can conflict with the previous-frame continuation reference. That reference remains part of the workflow and has no supported disable switch.
ACE-Step music remix
Remix an uploaded music track with ACE-Step using style tags and lyrics, then export the result as MP3. For a first run, upload the audio excerpt you want to remix, replace the example style tags and lyrics with your intended direction, and keep the sampling defaults, including remix strength 0.3. Describe genre, instruments, mood, tempo and vocal character with comma-separated tags. Enter intended sung words with section labels and line breaks. Lyrics and tags guide generation; they do not guarantee exact words or performance. Remix strength ranges from 0 to 1: lower values retain more source structure, while higher values permit larger changes. Lyrics strength adjusts lyric conditioning, and CFG controls overall text guidance. The uploaded audio supplies the starting latent and temporal extent. Prepare your excerpt before uploading: this tool has no trimming, independent duration control or separate text-to-music mode. Negative conditioning is zeroed internally, with no editable negative prompt. Use seed -1 for random variations or a fixed nonnegative seed to compare settings. Steps, sampler and scheduler control denoising. Advanced latent tonemap multiplier and sampling shift controls change internal guidance and model sampling; retain their source defaults of 1 and 5 for a first run. Sampling shift is not an audio timing offset. MP3 quality offers V0 variable bitrate, 128k and 320k. This controls file encoding rather than the generated composition. For multilingual lyrics, the supplied source guidance calls for manual romanization and language markers such as [zh], [ja] or [ko]; automatic transliteration is absent. The workflow requires ace_step_v1_3.5b.safetensors in the ComfyUI checkpoints model directory. The supplied model source is https://huggingface.co/Comfy-Org/ACE-Step_ComfyUI_repackaged/resolve/main/all_in_one/ace_step_v1_3.5b.safetensors?download=true. The supplied dependency catalog has not resolved this checkpoint.
Hoshimachi Suisei 星街すいせい / Hololive
sui1, 1girl, solo, side ponytail, hoshimachi suisei, fingerless gloves, single thighhigh, jewelry, thigh strap, bracelet, buttons, plaid dress, blue choker, blue belt, plaid skirt, mini crown, grey skirt, blue ascot,...
Flux 2 Dev with optional image references
Generate new images from text with Flux 2 Dev, optionally conditioned by one or two reference images. First run: enter a positive prompt and keep the default 1024 × 1024 output, batch size 1, 20 steps and guidance 4. Leave both Use reference stages bypassed; no image uploads are needed in this mode. Run to receive the generated image batch. Seed -1 requests fresh randomization on each run; use a fixed seed to compare settings. For reference conditioning, upload Reference image 1 or Reference image 2 and enable its matching Use reference stage. Either reference works independently, and both can contribute to one generation. Explain in the prompt how the references should inform the result. Each enabled reference is resized to approximately one megapixel before encoding. Advanced reference resolution and interpolation controls affect reference preparation, not output dimensions. References condition a new generation; they are not initial images for denoising. This graph has no negative-prompt or denoise control and does not provide a finished-image upscaling mode. Set output Width and Height in pixels, in multiples of 16. Whenever you change either, also change the corresponding Scheduler width or Scheduler height under advanced Sampling to match. These are separate controls, not automatically linked. Batch size sets the number of generated images. Advanced controls also expose guidance, sampling steps and the sampling algorithm. Requires flux2_dev_fp8mixed.safetensors, mistral_3_small_flux2_fp8.safetensors and flux2-vae.safetensors. Supplied dependency evidence identifies the VAE artifact at https://civitai.com/models/2173342?modelVersionId=2447823 but does not resolve the diffusion-model or text-encoder sources.
