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ACE-Step 1.5 music generator
Generate music with ACE-Step 1.5 XL from a musical description and lyrics, and export MP3. No media upload is required. For a first run, keep the supplied description, lyrics, and defaults, then generate: the example requests a two-minute ambient song with English vocals at 72 BPM in E minor. Musical instructions guide generation rather than guaranteeing exact performance. To create your own track, describe genre, instruments, mood, vocal delivery, production, and arrangement in Music description. Enter sung words and optional bracketed section cues in Lyrics, then select the matching vocal language. Keep tempo, key, and meter references consistent across the text and musical controls. The time-signature selector offers source values 2, 3, 4, and 6, with no separate denominator control. Output duration sets the audio length in seconds. Conditioning duration is independent: update both to the same value when changing length. Track count sets the batch size using the same musical conditioning. Seed is shared by audio-code generation and diffusion sampling; -1 randomizes it, while a fixed nonnegative integer lets you reuse a seed with the same settings. Generate audio codes enables the additional language-model stage. Its guidance, temperature, top-p, top-k, and min-p controls apply only when enabled. Disabling it leaves the text-conditioned diffusion path available. Advanced Audio sampling controls set diffusion steps, CFG, sampler, scheduler, and denoising strength. Sampling configuration exposes the source sampling shift, defaulting to 3. Full denoising defaults to 1 because generation starts from an empty audio latent. Negative conditioning is automatically zeroed; there is no editable negative prompt. MP3 quality selects V0 variable-bitrate encoding or fixed 128k or 320k encoding and affects export rather than music generation. The workflow uses the ACE-Step XL base diffusion model, its two Qwen text encoders, and the ACE 1.5 audio VAE. It has no uploaded audio reference, continuation, or audio-editing input.
Poster remake and image edit
Create a new poster from a reference image, apply direct image edits, or generate an image from text using Gemini. For a first run, upload a reference poster, leave Direct prompt mode off, and replace the example Prompt with your new title, supporting text, subject, and desired content. Leave the Reference image stage enabled when using an upload. The default Poster instructions ask Gemini to borrow the reference's style, colors, and typography while changing people's faces, clothing, and poses. They request a large, mainly white artistic title that avoids the face and omit reference watermarks and tiny text. These are creative directions, not guarantees of exact layout, lettering, or identity preservation. Turn Direct prompt mode on to send your brief without Poster instructions. With a reference enabled, describe the edits to apply. For text-only generation, disable the Reference image stage and describe the image you want; Direct prompt mode avoids the default poster instructions that refer to an uploaded picture. Generation instructions still apply in both modes. Auto aspect ratio follows the reference when present. Choose an explicit ratio when you need a particular format, especially without a reference. Resolution defaults to 2K; the source uses Gemini's native upscaler for 2K and 4K. Model selects the Gemini image model for all modes. Use seed -1 for a new random seed each run; a fixed seed requests best-effort consistency, but identical results are not guaranteed. Adjust Poster instructions under advanced controls to change the reusable poster direction. They are prepended to your brief only when Direct prompt mode is off. Generation instructions control the shared foundational direction sent to Gemini. This Pipe returns generated images through its preview output; it does not include the model's separate text response or a workflow file-saving stage. Prompts and enabled reference images are sent to Gemini through a provider-priced API call.
AUTO-SEND FILES PRIVATE/SECURE 🔐: ComfyUI Output Folder >> Encrypt >> Send to GoogleDrive / Dropbox 😎👍 — v1.0.0
Sick of manually downloading your ComfyUI output files from the cloud? Want them to just show up in your GoogleDrive automatically? (or DropBox - Link Below)
Grok image restyling
Upload one image and describe the appearance you want. For a first run, keep the pixel-art instruction, 1K resolution and one result. The prompt is fully editable: specify the desired style and which subjects or details should remain recognizable. Identity preservation is a request to the generative model, not a guarantee. The source contains equivalent style examples. This tool uses one editing branch with one editable prompt rather than running every example simultaneously. Copy any of these source starting instructions into the prompt: - Change the images style into pixel art, maintain identity - Change the images style into 3d animation, maintain identity - Change the images style into claymation, maintain identity - Change the images style into hyper realistic, maintain identity - Change the images style into cross stitch, maintain identity - Change the images style into oil painting with visible brushstrokes, maintain identity - Change the images style into detailed colored pencil, maintain identity - Change the images style into flat vector illustration, maintain identity - Change the images style into reflective metal sculpture, maintain identity - Change the images style into charcoal sketch, maintain identity - Change the images style into lineart, maintain identity - Change the images style into watercolor, maintain identity Choose 1K or 2K resolution and request 1–10 edited images. Model selection exposes the source-supported grok-imagine-image, grok-imagine-image-quality and grok-imagine-image-pro options. Aspect ratio remains automatic for this single-image input; the source permits explicit ratios only with multiple input images. Increasing result count does not create multiple input images. Seed controls whether the provider node re-runs; results remain nondeterministic even with a fixed seed. The default randomizes on each run. Outputs are generated raster still images: animation and sculpture instructions describe appearances, vector instructions do not produce vector files, and cross-stitch instructions do not produce stitch patterns. Pixel art is prompted without enforced grid or palette constraints. Uploaded transparency is not preserved by the selected image-only path.
[LuisaP] Sci-fi/Hard surface
Needs the keyword " structure " ex: a cyberpunk structure , a building structure , a turret structure .
Wan 2.2 four-step frame-to-video
Generate a silent video from a scene and motion prompt, optionally guided by a start image, an end image, or both. For a first run, upload a start image and replace the sleeping-cat prompt with your subject, action, camera movement and style. Upload an end image if you want ending-frame guidance; otherwise disable the End image stage. Both image stages initially remain enabled, so upload an image for each enabled stage or disable it explicitly. Leave the default 640 × 640 dimensions, 81 frames, 16 FPS and sampling settings for the first run, then generate and view the returned video. The default playback lasts approximately 5.1 seconds. The image stages can be disabled independently: start only animates from an opening image, end only provides ending guidance, both guide a transition, and disabling both leaves prompt-driven generation. Images provide guidance rather than a guarantee of an exact transition. Only RGB image outputs are connected; uploaded alpha masks are unused. There is no audio input in this tool. Width and height are pixels in increments of 16. Frame count follows 1, 5, 9 and so on and changes how many frames are generated. Playback FPS changes duration without generating additional frames: duration is frame count divided by FPS. Keep batch size at 1 for a single video; this Pipe has one video output rather than separate outputs per batch item. Advanced settings preserve separate initial and finishing-stage controls. Seed -1 randomizes initial noise; a fixed nonnegative seed repeats the noise choice with the same other settings. The high-noise stage adds noise and runs steps 0–2, then the low-noise stage continues steps 2–4 without adding fresh noise. Both use a total schedule length of 4, CFG 1, Euler, simple scheduling and sampling shift 8. The fixed high/low-noise Lightx2v LoRAs each have model strength 1. If deliberately changing this recipe, coordinate both total step counts and the segment boundaries; changing one field alone can interrupt the handoff. LoRA strengths do not select the standard 20-step sibling recipe. The supplied negative prompt is a Chinese list of unwanted visual defects and content; retain it or edit it for your scene. Output container, codec, CRF and bit depth control video representation and encoding. Leave container and codec on auto and CRF at -1 for the first run. Ten-bit output may be unsupported by some players or downstream nodes.
Wan 2.6 text to video
Generate a video from an English or Chinese scene description using Wan, with optional generated audio and continuous-shot or multi-shot composition. No uploaded image, video, or audio input is exposed in this Pipe. For a first run, replace the example scene description with your subjects, actions, setting, camera movement, and visual style. Keep Wan 2.6, landscape 720p, and the five-second duration. Audio generation and AI prompt enhancement are enabled by default; include desired sound in your description when using generated audio. Review the negative prompt and replace scene-specific exclusions that do not apply. Output size selects resolution and aspect ratio together. Duration is in seconds: Wan 2.6 supports 5, 10, or 15; when selecting Wan 2.5 preview, choose 5 or 10. Shot type selects one continuous shot or multiple shots with cuts, and takes effect only while Enhance prompt is enabled. Disable enhancement to submit your wording without AI expansion. Turn off Generate audio if you do not want automatic audio generation. Seed -1 randomizes each run; enter a fixed seed to control randomization. Watermark requests an AI-generated watermark and is disabled by default. The generated video is returned to Sweet Tea. In the advanced Video output section, leave file type and codec on auto for the first run, or select an explicit container and encoding. Keep the supplied CRF default unless you need to configure encoding quality.
Ideogram V4 image generator
Generate an image through the Ideogram V4 partner API using a written prompt. No source image is required. For a first run, keep the bundled surreal collage-poster prompt, Auto output size, and DEFAULT rendering speed, then run. The execution environment needs access to the partner API. Replace the prompt with plain natural language for a simple idea, or edit the bundled JSON to describe composition, colors, objects, and in-image wording. JSON remains one prompt field; this Pipe does not provide separate per-object editors or a negative prompt. Treat layout and lettering instructions as generation requests rather than guaranteed exact placement or transcription. Choose an explicit output size when you need a particular pixel size and aspect ratio, and keep composition instructions consistent with that shape. Rendering speed offers DEFAULT, TURBO, and QUALITY modes for the provider's speed-versus-quality trade-off. Seed defaults to a new random value each run. The source's Gemini helper is disabled and disconnected. Prompt building is manual in this Pipe; it does not automatically expand ideas into JSON.
Action figure image edit
Create an articulated toy or action-figure style image from an uploaded image. Describe the edit in the positive prompt using "action the [thing]", such as "action the scene"; optionally add exclusions in the negative prompt. Fast mode selects the Lightning LoRA branch with four sampling steps by default; disabling it selects standard sampling. Advanced controls adjust edit strength, LoRA strengths, seed, sampler, scheduler, and each mode's steps and guidance.
Hentai Manga Style Concept
This is a embedding i trained on just hentai images. Therefore you will get a lot of open mouths, ahegao, sweating, saliva etc.. from just using the embedding.
Character Expression Sheet
Create a labeled sheet of 12 expressions from a character image, or render one selected preset or custom expression. Start with a character image and set its longest-side size. Batch mode is on by default and creates angry, anxious, confident, confused, contemptuous, disgusted, fearful, happy, sad, shy, sleepy, and surprised expressions in one sheet. Turn batch mode off to render one selected preset or enter a custom expression instruction. Expression strength and seed are available as advanced controls.
Topaz video upscale
Enhance an uploaded video with Topaz Starlight Precise 2.5 and return one video at FullHD (1080p) or 4K (2160p). For a first run, upload your source video, keep FullHD (1080p), leave Compression level at Low, and leave File type and Codec on auto. Run the Pipe to receive the enhanced video. A source video is required; no sample video is supplied as the upload default. Output resolution selects the Topaz enhancement resolution. Compression level selects Topaz's CQP setting from Low, Mid and High. In Video encoding, you can choose MP4, MKV or WebM and H.264 or AV1 instead of automatic selection. Manual file type and codec combinations must be compatible and supported by the runtime. These output encoding choices are separate from Topaz's compression setting. This Pipe uses Starlight Precise 2.5 with frame interpolation disabled. Other enhancement models, creative-model tuning, target frame rate and slow-motion settings are not offered because their required mode-specific bindings are absent from this configuration. Processing sends the uploaded video to the Topaz partner API, requires runtime authentication, and uses provider-priced processing.
