/** * @node sdcpp-img2img * @name SD.cpp Image to Image * @category sdcpp * @version 1.0.0 * @description Queue an image generation that starts from an existing image * @icon images */ // The credential this node wants, named so it can be found. It is stored as a // plain basic credential - that is what decides how it is encrypted - and this // only says which basic credential is the SD.cpp one. Anything that accepts a // basic credential still accepts this, and this node still accepts a plain // basic credential, because the shape is identical. const credentialTypes = [ { id: 'sdcpp', label: 'SD.cpp Server', baseType: 'basic', description: 'The username and password you sign in to sdcpp-restapi with. The node exchanges them for a token before every call', usernameLabel: 'Username', passwordLabel: 'Password' } ]; const configSchema = { type: 'object', // Generated from the server's own reference at /options/generation - see // scripts/gen-sdcpp-generation-options.py. Every field the endpoint accepts // has a setting here, grouped the way the server groups them. uiGroups: [ { "title": "Server", "fields": [ "serverUrl", "credentialId" ] }, { "title": "Core", "fields": [ "prompt", "negativePrompt", "width", "height", "steps", "cfgScale", "seed", "sampler", "scheduler", "batchCount" ] }, { "title": "Cache Acceleration", "fields": [ "cacheMode", "easycacheThreshold", "easycacheStart", "easycacheEnd", "spectrumW", "spectrumM", "spectrumLam", "spectrumWindowSize", "spectrumFlexWindow", "spectrumWarmupSteps", "spectrumStopPercent" ] }, { "title": "ControlNet", "fields": [ "controlImageBase64", "controlStrength" ] }, { "title": "Prompt Expansion", "fields": [ "expandPrompt" ] }, { "title": "Guidance", "fields": [ "distilledGuidance", "eta", "shiftedTimestep", "flowShift", "clipSkip" ] }, { "title": "Image Input (img2img / image-edit)", "fields": [ "initImageBase64", "maskImageBase64", "strength", "imgCfgScale", "ipAdapterImageBase64", "ipAdapterStrength" ] }, { "title": "Skip Layer Guidance (SLG)", "fields": [ "slgScale", "skipLayers", "slgStart", "slgEnd", "customSigmas" ] }, { "title": "Upscale After Generation", "fields": [ "upscale", "upscaleRepeats", "upscaleAutoUnload" ] }, { "title": "VAE Tiling (per-generation)", "fields": [ "vaeTiling", "vaeTileSizeX", "vaeTileSizeY", "vaeTileOverlap" ] }, { "title": "Job", "fields": [ "title", "extraOptions", "timeout" ] } ], prefill: { "label": "Take the architecture defaults", "description": "Fill these in from the preset for whichever model the server has loaded - the same values it would use if these were left empty", "node": "sdcpp-architecture", "needs": [ "serverUrl", "credentialId" ], "map": { "defaults.width": "width", "defaults.height": "height", "defaults.steps": "steps", "defaults.cfgScale": "cfgScale", "defaults.sampler": "sampler", "defaults.scheduler": "scheduler", "defaults.cacheMode": "cacheMode", "defaults.distilledGuidance": "distilledGuidance", "defaults.flowShift": "flowShift", "defaults.negativePrompt": "negativePrompt" } }, properties: { serverUrl: { type: 'string', title: 'Server URL', description: 'Base address of the sdcpp-restapi server', default: 'http://localhost:8077' }, credentialId: { type: 'string', title: 'Credential', description: 'A basic credential holding the sdcpp-restapi username and password', dynamicOptions: { source: 'credentials', filter: { type: ['sdcpp', 'basic'] } } }, batchCount: { title: "Batch Count", description: "Number of independent images to produce in this single job. Each image gets a different seed (`seed`, `seed+1`, …). Total VRAM doesn't grow with batch_count - sd.cpp serializes. Recommended: 1 for interactive, higher when you want a grid of variations from one prompt. Leave empty for the architecture default.", type: "number" }, cacheMode: { title: "Cache Mode", description: "DiT-model intermediate caching strategy. Skips redundant computation across consecutive sampler steps when the model's intermediate state hasn't changed enough to matter. `easycache` is the simplest; `spectrum` is the newest, generally best for Flux/SD3/Z-Image. Recommended: spectrum for Flux/SD3/Z-Image when generation is too slow. Off for SD1.5/SDXL (UNet is too small for caching to win). Leave empty for the architecture default.", type: "string", enum: ["", "off", "easycache", "ucache", "dbcache", "taylorseer", "cache_dit", "spectrum"], enumLabels: ["(architecture default, which may switch it on)", "Off - no caching, whatever the architecture prefers", "EasyCache - single threshold, simple", "UCache", "DBCache", "TaylorSeer", "Cache-DiT", "Spectrum - frequency-domain analysis (best quality/speed tradeoff)"], default: "" }, cfgScale: { title: "CFG Scale", description: "Classifier-Free Guidance scale. Strength of pushing the cond toward the prompt vs the uncond. Higher = follows prompt more aggressively but can over-saturate. Set to 1.0 to disable CFG (skips the uncond pass - twice as fast). Recommended: SD1.5: 7. SDXL: 4-8. Flux Dev: 1 (CFG bypassed in flow models). Z-Image: 1. Schnell/Turbo: 1. Leave empty for the architecture default.", type: "number" }, clipSkip: { title: "CLIP Skip", description: "Skip the last N layers of CLIP when encoding the prompt. -1 = use the model's recommended default. 2 is the classic anime-model setting. Recommended: -1 (auto). Set to 2 for anime/cartoon SD1.5 fine-tunes. Leave empty for the architecture default.", type: "number" }, controlImageBase64: { title: "ControlNet Image (base64)", description: "Base64-encoded pre-processed control image. Must match the ControlNet model loaded - Canny edges for canny model, depth map for depth model, etc. sd.cpp does not pre-process; you do that client-side. Recommended: Required when using ControlNet. Leave empty for the architecture default.", type: "string" }, controlStrength: { title: "ControlNet Strength", description: "How much the ControlNet influences the diffusion process (0.0-1.0). Lower = looser following, higher = tighter following at cost of overall coherence. Recommended: 0.6-0.9 for most uses. Lower for creative prompts where control should be a hint, not a constraint. Leave empty for the architecture default.", type: "number" }, customSigmas: { title: "Custom Sigma Schedule", description: "Replace the scheduler's noise sigma sequence with a hand-tuned one. Bypasses `scheduler`. Empty array = use the chosen scheduler. Recommended: Empty unless you're hand-tuning per-step noise levels - niche. Leave empty for the architecture default.", type: "array", items: {"type": "number"} }, distilledGuidance: { title: "Distilled Guidance", description: "Distilled-CFG scale for models that bake the CFG behavior into the diffusion model itself (Flux). Replaces the runtime CFG split. Recommended: Flux Dev: 3.5 (sd.cpp default). Other architectures: ignored. Leave empty for the architecture default.", type: "number" }, easycacheEnd: { title: "EasyCache End (% of steps)", description: "Fraction of steps after which EasyCache turns off (last few steps fully recomputed for sharpness). Recommended: 0.95. Leave empty for the architecture default.", type: "number" }, easycacheStart: { title: "EasyCache Start (% of steps)", description: "Fraction of steps before EasyCache becomes active. Small to skip the early high-noise steps where caching hurts. Recommended: 0.15. Leave empty for the architecture default.", type: "number" }, easycacheThreshold: { title: "EasyCache Threshold", description: "Reuse threshold for EasyCache. Higher = more aggressive reuse (faster but more quality loss). Range typically 0.05-0.4. Recommended: 0.2 starting point. Tune up for more speed, down for more quality. Leave empty for the architecture default.", type: "number" }, eta: { title: "Eta", description: "Stochasticity parameter for DDIM-family samplers. 0 = deterministic, 1 = max stochasticity (matches DDPM noise schedule). Most other samplers ignore this. Recommended: 0 (deterministic, reproducible). Raise only with DDIM-trailing for some variation. Leave empty for the architecture default.", type: "number" }, expandPrompt: { title: "Expand Prompt Template", description: "If true, parse `prompt` for a1111-style dynamic-prompts syntax (`{a|b|c}`, `{N$$a|b|c}`) and create one queue item per variation. The response then carries `group_id` + `variation_count` + `job_ids[]` instead of a single `job_id`. Hard cap: 200 variations per request. Recommended: Enable when your prompt actually contains `{…}` syntax. Leave empty for the architecture default.", type: "boolean" }, flowShift: { title: "Flow Shift", description: "Per-generation flow-matching shift parameter for Flux / SD3 / Z-Image models. Higher values shift sampling toward larger noise levels longer. Per-call override; the load-time `flow_shift` is the default if this isn't set. Recommended: Flux Dev: 1.0. Z-Image: 3.0. SD3 Medium: 3.0. Leave empty for the architecture default.", type: "number" }, height: { title: "Height (px)", description: "Output image height in pixels. Same divisibility constraint as `width`. Recommended: Match training resolution. For non-square: total pixel count close to native is more important than aspect ratio. Leave empty for the architecture default.", type: "number" }, imgCfgScale: { title: "Image CFG Scale", description: "Image-CFG for instruct-pix2pix-style models. -1 = same as `cfg_scale`. Different from `cfg_scale`: balances text-prompt influence against image-prompt influence. Recommended: -1 unless using an instruct-pix2pix variant. Leave empty for the architecture default.", type: "number" }, initImageBase64: { title: "Init Image (base64)", description: "Base64-encoded source image for img2img / image-edit. Required for /img2img. Recommended: Required for img2img. Leave empty for the architecture default.", type: "string" }, maskImageBase64: { title: "Mask Image (base64)", description: "Base64-encoded inpainting mask. White areas are repainted, black areas preserved. Recommended: Optional. Empty mask = standard img2img (no inpainting). Leave empty for the architecture default.", type: "string" }, negativePrompt: { title: "Negative Prompt", description: "What to push the model away from. Has effect only when `cfg_scale > 1` (CFG is what compares cond vs uncond). Ignored on architectures that don't use CFG (most flow-matching models default to `cfg_scale = 1`). Recommended: Optional. Empty is a fine default for Flux / SD3 / Z-Image. Leave empty for the architecture default.", type: "string", format: "textarea" }, prompt: { title: "Prompt", description: "Text prompt fed to the model's text encoder (CLIP / T5 / LLM). Supports inline `` tags - these are auto-extracted into the LoRA list before being sent to the encoder. Supports a1111-style dynamic-prompts (`{a|b|c}`) when `expand_prompt: true` is set. Recommended: Required. Leave empty for the architecture default.", type: "string", format: "textarea" }, sampler: { title: "Sampler", description: "Sampling algorithm. Different samplers can produce different images at the same seed; quality and speed differ too. Recommended: euler_a (general), dpmpp2m (SD1.5/SDXL), euler (Flux/SD3/Z-Image), lcm (LCM models). Leave empty for the architecture default.", type: "string", enum: ["", "euler", "euler_a", "heun", "dpm2", "dpm++2s_a", "dpm++2m", "dpm++2mv2", "ipndm", "ipndm_v", "lcm", "ddim_trailing", "tcd", "res_multistep", "res_2s", "er_sde", "euler_cfg_pp", "euler_a_cfg_pp", "euler_ge", "dpm++2m_sde", "dpm++2m_sde_bt", "lms"], enumLabels: ["(architecture default)", "Euler - simple, fast, deterministic", "Euler ancestral - adds noise each step (less reproducible, more variet", "Heun - 2nd-order, slower, sometimes higher quality", "DPM2 - 2nd-order, balanced", "DPM++ 2S ancestral - popular for SDXL", "DPM++ 2M - fast, good quality", "DPM++ 2M v2 - improved schedule", "IPNDM", "IPNDM-V", "LCM - for LCM-finetuned models (4-8 step generation)", "DDIM trailing - required for some fine-tunes", "TCD - for TCD-finetuned models", "RES multistep - flow-model variant", "RES 2S", "ER SDE - SDE sampler", "Euler CFG++ - improved CFG variant of Euler", "Euler ancestral CFG++ - ancestral variant of Euler CFG++", "Euler GE - graph-effective Euler variant", "DPM++ 2M SDE (leejet PR #1742)", "DPM++ 2M SDE with Brownian-tree noise (leejet PR #1743)", "LMS - linear multi-step (leejet PR #1843)"], default: "" }, scheduler: { title: "Scheduler", description: "Determines the noise schedule (the timesteps the sampler walks through). Pairs with the sampler - some combinations (e.g. karras+dpmpp2m) are well-tested, others may be off. Recommended: discrete or karras for SD1.5/SDXL; simple for Flux/SD3; smoothstep for Z-Image. Leave empty for the architecture default.", type: "string", enum: ["", "discrete", "karras", "exponential", "ays", "gits", "sgm_uniform", "simple", "smoothstep", "kl_optimal", "lcm", "bong_tangent", "ltx2", "logit_normal", "flux", "flux2", "beta", "normal"], enumLabels: ["(architecture default)", "Discrete - standard sd.cpp default", "Karras - improves sample quality, especially at low step counts", "Exponential - decays sigma exponentially", "AYS - align-your-steps", "GITS - Golden-Interval Tabular Sampling", "SGM uniform - matches SGM training-time noise schedule", "Simple - basic linear", "Smoothstep - smoothly interpolated schedule", "KL-optimal - minimizes discretization error", "LCM - for LCM-finetuned models", "Bong tangent", "LTX 2 - LTX-Video 2 schedule", "Logit-normal", "Flux - Flux-family model schedule (leejet PR #1723)", "Flux 2 - Flux 2 model schedule (leejet PR #1722)", "Beta - configurable via extra_sample_args beta_alpha=/beta_beta= (leej", "Normal - alias for discrete (leejet PR #1724)"], default: "" }, seed: { title: "Seed", description: "RNG seed for the initial noise tensor (and stochastic samplers). -1 = pick a random one each generation. Same seed + same prompt + same model = same image. Recommended: -1 for variety. Pin a specific number for A/B comparing prompt or sampler changes. Leave empty for the architecture default.", type: "number" }, shiftedTimestep: { title: "Shifted Timestep", description: "Start the sampling schedule from a non-final timestep (used by NitroFusion and similar fast-sampling fine-tunes). 0 = standard schedule. 250-500 = NitroFusion's range. Recommended: 0 unless you're explicitly running a NitroFusion-style fine-tune. Leave empty for the architecture default.", type: "number" }, skipLayers: { title: "SLG Skip Layers", description: "Which transformer layers to skip during the SLG unconditional pass. SD3.5 Medium uses [7, 8, 9]. Recommended: [7,8,9] for SD3.5 Medium. Other models: leave default, ignored when slg_scale=0. Leave empty for the architecture default.", type: "array", items: {"type": "number"} }, slgEnd: { title: "SLG End (% of steps)", description: "Fraction of the sampler schedule at which SLG turns off. Recommended: 0.2 (early-cycle only - late-cycle SLG hurts quality). Leave empty for the architecture default.", type: "number" }, slgScale: { title: "SLG Scale", description: "Skip Layer Guidance scale. Selectively zeros out a few diffusion layers when computing the unconditional pass - improves anatomy / coherence on SD3.5-medium and similar. 0 = disabled. Recommended: 0 for most models. 2.5 for SD3.5 Medium with the recommended skip layers. Leave empty for the architecture default.", type: "number" }, slgStart: { title: "SLG Start (% of steps)", description: "Fraction of the sampler schedule (0.0-1.0) at which SLG kicks in. Recommended: 0.01 (almost from the start). Leave empty for the architecture default.", type: "number" }, spectrumFlexWindow: { title: "Spectrum Cache: flex window", description: "Spectrum-cache flexibility window (0.0-1.0). Recommended: 0.5. Leave empty for the architecture default.", type: "number" }, spectrumLam: { title: "Spectrum Cache: λ", description: "Spectrum-cache regularization λ. Recommended: 0.5. Leave empty for the architecture default.", type: "number" }, spectrumM: { title: "Spectrum Cache: m", description: "Spectrum-cache moving-average length. Recommended: 5. Leave empty for the architecture default.", type: "number" }, spectrumStopPercent: { title: "Spectrum Cache: stop percent", description: "Fraction of steps after which spectrum cache disengages (last steps recomputed). Recommended: 0.8. Leave empty for the architecture default.", type: "number" }, spectrumW: { title: "Spectrum Cache: w", description: "Spectrum-cache `w` weight (frequency cutoff). Higher = retains more spectrum, less speedup. Recommended: 0.5 default. See sd.cpp PR #1322 for tuning. Leave empty for the architecture default.", type: "number" }, spectrumWarmupSteps: { title: "Spectrum Cache: warmup steps", description: "Steps at the start of sampling before spectrum cache becomes active. Recommended: 2. Leave empty for the architecture default.", type: "number" }, spectrumWindowSize: { title: "Spectrum Cache: window size", description: "Spectrum-cache analysis window size in steps. Recommended: 3. Leave empty for the architecture default.", type: "number" }, steps: { title: "Sampling Steps", description: "Number of denoising steps the sampler runs. More steps = closer to the model's converged output, with diminishing returns. Distilled models (Flux Schnell, SDXL Turbo, Z-Image Turbo) need only 4-8. Recommended: 20-30 for SD1.5/SDXL, 20 for Flux Dev, 4-8 for *-Turbo or Schnell variants. Leave empty for the architecture default.", type: "number" }, strength: { title: "Denoising Strength", description: "How much of the init image's noise to keep (0.0 = identical to init, 1.0 = ignore init entirely). Controls how aggressively img2img diverges from the input. Recommended: 0.5-0.75 for natural-looking edits. 0.9+ for radical reinterpretation. Leave empty for the architecture default.", type: "number" }, upscale: { title: "Upscale After Generate", description: "Run the loaded ESRGAN upscaler on the output image after generation. Requires an upscaler to be loaded via POST /upscaler/load. Recommended: On for one-shot 'generate then upscale' workflows. Leave empty for the architecture default.", type: "boolean" }, upscaleAutoUnload: { title: "Auto-unload Upscaler", description: "Free upscaler VRAM right after the upscale step. Useful when you generated with `upscale: true` and want VRAM back for other work. Recommended: On. Leave empty for the architecture default.", type: "boolean" }, upscaleRepeats: { title: "Upscale Repeats", description: "Number of post-generation auto-upscale passes (each with the upscaler's native factor - 4× ESRGAN × 2 passes = 16×). DISTINCT from the `/upscale` endpoint's own `repeats` field, which controls passes inside a single upscale job. `upscale_repeats` only chains additional /upscale calls after txt2img / img2img finish. Recommended: 1. Two passes amplify artifacts, but produces large outputs from small inputs. Leave empty for the architecture default.", type: "number" }, vaeTileOverlap: { title: "VAE Tile Overlap", description: "Overlap fraction between VAE tiles for seam blending. Recommended: 0.5. Leave empty for the architecture default.", type: "number" }, vaeTileSizeX: { title: "VAE Tile Width", description: "Width of VAE tiles when tiling is on. 0 = use load-time default. Recommended: 0. Leave empty for the architecture default.", type: "number" }, vaeTileSizeY: { title: "VAE Tile Height", description: "Height of VAE tiles. 0 = use load-time default. Recommended: 0. Leave empty for the architecture default.", type: "number" }, vaeTiling: { title: "VAE Tiling", description: "Per-generation override of the model-load `vae_tiling`. Process VAE encode/decode in tiles to reduce peak VRAM. Recommended: Enable for ≥2048 px outputs. Otherwise leave to the load-time default. Leave empty for the architecture default.", type: "boolean" }, width: { title: "Width (px)", description: "Output image width in pixels. Must be divisible by the model's patch size (typically 8 or 16). Architectures have native resolutions they were trained at - going far off them can degrade quality. Recommended: Match the architecture's training resolution: SD1.5=512, SDXL=1024, Flux/SD3/Z-Image=1024, Wan video=832. Leave empty for the architecture default.", type: "number" }, ipAdapterImageBase64: { title: "IP-Adapter Image (base64)", description: "A reference image whose style and subject guide the result, as base64. Needs an IP-Adapter loaded alongside the model - see the Load Model node. Recommended: Take it from a Download or Fetch Output node rather than pasting one in. Leave empty for the architecture default.", type: "string" }, ipAdapterStrength: { title: "IP-Adapter Strength", description: "How strongly the reference image guides the result. Recommended: 1.0 is the upstream default. Lower it when the reference is overwhelming the prompt. Leave empty for the architecture default.", type: "number" }, title: { type: "string", title: "Job Title", description: "Optional label stored with the job, useful for finding it again in the queue" }, extraOptions: { type: "object", title: "Extra Options", description: "Any other generation field passed straight through. Everything the server documents already has a setting above, so this is only needed for a field a newer server has gained" }, timeout: { type: "number", title: "Timeout (ms)", description: "Applies to queueing the job, not to the render. The call returns as soon as the job is accepted", default: 30000 } }, required: ['credentialId'] }; const inputSchema = { type: 'object', properties: { data: { type: 'any' } } }; const outputSchema = { type: 'object', properties: { jobId: { type: 'string', description: 'Id of the queued job, to pass to SD.cpp Wait For Job' }, status: { type: 'string', description: 'Queue status when the job was accepted, normally pending' }, position: { type: 'number', description: 'Place in the queue' }, request: { type: 'object', description: 'The body actually sent, useful for seeing which defaults were left to the server' } } }; function normalizeServer(url) { const value = String(url || '').trim(); if (!value) { throw new Error('SD.cpp: a server URL is required, such as http://localhost:8077'); } return value.replace(/\/+$/, ''); } function readCredential(credentialId) { const auth = smartbotic.credentials.get(credentialId); if (!auth || auth.success !== true) { throw new Error('SD.cpp: could not read the credential: ' + ((auth && auth.error) || 'unknown error')); } const value = auth.headerValue || ''; if (value.indexOf('Basic ') !== 0) { throw new Error('SD.cpp: the credential must be a basic one, holding the sdcpp-restapi ' + 'username and password'); } const decoded = smartbotic.utils.base64Decode(value.substring(6)); const separator = decoded.indexOf(':'); if (separator < 1) { throw new Error('SD.cpp: the credential is malformed, expected a username and a password'); } return { username: decoded.substring(0, separator), password: decoded.substring(separator + 1) }; } function call(options) { const response = smartbotic.http.request(options); let body = response.data; if (typeof body === 'string' && body.length > 0) { try { body = JSON.parse(body); } catch (e) { const snippet = body.substring(0, 200).replace(/\s+/g, ' '); throw new Error('SD.cpp: ' + options.what + ' returned HTTP ' + response.status + ' with a body that is not JSON: ' + snippet); } } if (response.status < 200 || response.status >= 300) { const detail = (body && (body.message || body.error)) || ('HTTP ' + response.status); throw new Error('SD.cpp: ' + options.what + ' failed: ' + detail); } return body || {}; } function login(server, credential, timeout) { const session = call({ method: 'POST', url: server + '/auth/login', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ username: credential.username, password: credential.password }), timeout: timeout, what: 'signing in' }); if (!session.token) { throw new Error('SD.cpp: the server accepted the login but returned no token'); } return session.token; } // /health is unauthenticated, and it is the only way to find out what is // already loaded without asking for a token first. function readHealth(server, timeout) { return call({ method: 'GET', url: server + '/health', timeout: timeout, what: 'reading server health' }); } function putIfSet(target, key, value) { if (value === undefined || value === null || value === '') { return; } target[key] = value; } // Every generation field the server documents, and the setting it comes // from. Generated alongside the schema above so the two cannot drift. const GENERATION_OPTIONS = [ { setting: "batchCount", server: "batch_count" }, { setting: "cacheMode", server: "cache_mode" }, { setting: "cfgScale", server: "cfg_scale" }, { setting: "clipSkip", server: "clip_skip" }, { setting: "controlImageBase64", server: "control_image_base64" }, { setting: "controlStrength", server: "control_strength" }, { setting: "customSigmas", server: "custom_sigmas" }, { setting: "distilledGuidance", server: "distilled_guidance" }, { setting: "easycacheEnd", server: "easycache_end" }, { setting: "easycacheStart", server: "easycache_start" }, { setting: "easycacheThreshold", server: "easycache_threshold" }, { setting: "eta", server: "eta" }, { setting: "expandPrompt", server: "expand_prompt" }, { setting: "flowShift", server: "flow_shift" }, { setting: "height", server: "height" }, { setting: "imgCfgScale", server: "img_cfg_scale" }, { setting: "initImageBase64", server: "init_image_base64" }, { setting: "maskImageBase64", server: "mask_image_base64" }, { setting: "negativePrompt", server: "negative_prompt" }, { setting: "prompt", server: "prompt" }, { setting: "sampler", server: "sampler" }, { setting: "scheduler", server: "scheduler" }, { setting: "seed", server: "seed" }, { setting: "shiftedTimestep", server: "shifted_timestep" }, { setting: "skipLayers", server: "skip_layers" }, { setting: "slgEnd", server: "slg_end" }, { setting: "slgScale", server: "slg_scale" }, { setting: "slgStart", server: "slg_start" }, { setting: "spectrumFlexWindow", server: "spectrum_flex_window" }, { setting: "spectrumLam", server: "spectrum_lam" }, { setting: "spectrumM", server: "spectrum_m" }, { setting: "spectrumStopPercent", server: "spectrum_stop_percent" }, { setting: "spectrumW", server: "spectrum_w" }, { setting: "spectrumWarmupSteps", server: "spectrum_warmup_steps" }, { setting: "spectrumWindowSize", server: "spectrum_window_size" }, { setting: "steps", server: "steps" }, { setting: "strength", server: "strength" }, { setting: "upscale", server: "upscale" }, { setting: "upscaleAutoUnload", server: "upscale_auto_unload" }, { setting: "upscaleRepeats", server: "upscale_repeats" }, { setting: "vaeTileOverlap", server: "vae_tile_overlap" }, { setting: "vaeTileSizeX", server: "vae_tile_size_x" }, { setting: "vaeTileSizeY", server: "vae_tile_size_y" }, { setting: "vaeTiling", server: "vae_tiling" }, { setting: "width", server: "width" }, { setting: "ipAdapterImageBase64", server: "ip_adapter_image_base64" }, { setting: "ipAdapterStrength", server: "ip_adapter_strength" } ]; // What the server accepts for each choice, as it described them when this // file was generated. See scripts/gen-sdcpp-generation-options.py. const KNOWN_CHOICES = { "cacheMode": ["easycache", "spectrum"], "sampler": ["ddim_trailing", "dpm++2m", "dpm++2m_sde", "dpm++2m_sde_bt", "dpm++2mv2", "dpm++2s_a", "dpm2", "er_sde", "euler", "euler_a", "euler_a_cfg_pp", "euler_cfg_pp", "euler_ge", "heun", "ipndm", "ipndm_v", "lcm", "lms", "res_2s", "res_multistep", "tcd"], "scheduler": ["ays", "beta", "bong_tangent", "discrete", "exponential", "flux", "flux2", "gits", "karras", "kl_optimal", "lcm", "logit_normal", "ltx2", "normal", "sgm_uniform", "simple", "smoothstep"] }; async function execute(config, input, context) { const server = normalizeServer(config.serverUrl); const timeout = config.timeout || 30000; const credential = readCredential(config.credentialId); const token = login(server, credential, timeout); const body = {}; // Built from the table above rather than field by field, so a setting the // server documents cannot be quietly missing from the request. A setting // left empty is left out of the body entirely: the server fills an absent // field from the loaded model's architecture preset, and sending an empty // box as 0 would override that preset with nonsense. The test is emptiness, // never truthiness - seed 0 and clip_skip 0 are legitimate values. for (let i = 0; i < GENERATION_OPTIONS.length; i++) { const option = GENERATION_OPTIONS[i]; const value = config[option.setting]; if (Array.isArray(value)) { // A list setting is usually filled with one entry holding an // expression for a whole list from an earlier node, which arrives // as a list inside a list. Left alone, the inner list is sent as a // single item and the server sees one nonsense value instead of // several - the same way a batch of two images once became one file // named "a.png,b.png". let flat = []; for (let j = 0; j < value.length; j++) { if (Array.isArray(value[j])) { flat = flat.concat(value[j]); } else if (value[j] !== undefined && value[j] !== null && value[j] !== '') { flat.push(value[j]); } } if (flat.length > 0) { body[option.server] = flat; } } else if (option.server === 'cache_mode' && value === 'off') { // The server reads an absent cache_mode as "use the architecture's // preference" and an empty one as "off". A dropdown cannot express // both with the same empty string, so "off" is sent as the explicit // empty the server wants - which is the only way to stop a preset // that switches caching on. body.cache_mode = ''; } else { putIfSet(body, option.server, value); } } putIfSet(body, 'title', config.title); if (!body.prompt) { throw new Error('SD.cpp: img2img needs a prompt'); } if (!body.init_image_base64) { throw new Error('SD.cpp: img2img needs an init image'); } // Anything else the API accepts, passed through, so a new server field does // not need a node change to be reachable. const extra = config.extraOptions; if (extra && typeof extra === 'object') { const keys = Object.keys(extra); for (let i = 0; i < keys.length; i++) { putIfSet(body, keys[i], extra[keys[i]]); } } const queued = call({ method: 'POST', url: server + '/img2img', headers: { 'Content-Type': 'application/json', 'Authorization': 'Bearer ' + token }, body: JSON.stringify(body), timeout: timeout, what: 'queueing the img2img job' }); if (!queued.job_id) { throw new Error('SD.cpp: the job was accepted but no job id came back'); } smartbotic.log.info('SD.cpp: queued img2img job ' + queued.job_id); return { jobId: queued.job_id, status: queued.status || 'pending', position: queued.position !== undefined ? queued.position : -1, request: body }; } module.exports = { configSchema, inputSchema, outputSchema, execute };