smartbotic/nodes/sdcpp/sdcpp-model.js

/**
 * @node sdcpp-model
 * @name SD.cpp Model
 * @category sdcpp
 * @version 1.0.0
 * @description List, load or unload models on an sdcpp-restapi server, and read its health
 * @icon layers
 */

const configSchema = {
    type: 'object',
    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. Not needed for the health operation, which the server leaves open',
            dynamicOptions: {
                source: 'credentials',
                filter: { type: ['basic'] }
            }
        },
        operation: {
            type: 'string',
            title: 'Operation',
            enum: ['health', 'list', 'load', 'unload', 'loadUpscaler', 'unloadUpscaler', 'refresh'],
            default: 'health',
            description: 'health reports what is loaded now, list shows what is available on disk, load swaps the main model slot, loadUpscaler fills the separate upscaler slot, refresh rescans the model directories'
        },
        modelName: {
            type: 'string',
            title: 'Model Name',
            description: 'File name of the model to load, relative to its type directory. Required for load and loadUpscaler'
        },
        modelType: {
            type: 'string',
            title: 'Model Type',
            enum: ['', 'checkpoint', 'diffusion'],
            default: '',
            description: 'checkpoint bundles the U-Net, CLIP and VAE together and suits SD1, SD2 and SDXL. diffusion holds only the U-Net or DiT weights and needs its components named separately, which is how Flux, SD3, Qwen, Wan and Z-Image load'
        },
        vae: { type: 'string', title: 'VAE', description: 'Component file name, for a diffusion model' },
        clipL: { type: 'string', title: 'CLIP-L', description: 'Component file name' },
        clipG: { type: 'string', title: 'CLIP-G', description: 'Component file name' },
        t5xxl: { type: 'string', title: 'T5-XXL', description: 'Component file name' },
        llm: { type: 'string', title: 'LLM', description: 'Component file name, used by Z-Image, Qwen, Anima and Flux2' },
        taesd: { type: 'string', title: 'TAESD', description: 'Tiny autoencoder used to render progress previews, not final output' },
        controlnet: { type: 'string', title: 'ControlNet', description: 'Component file name' },
        options: {
            type: 'object',
            title: 'Load Options',
            description: 'Extra load options passed straight through, such as flash_attn, enable_mmap, weight_type, stream_layers or max_vram. See /options/descriptions on the server for the full list'
        },
        listType: {
            type: 'string',
            title: 'List Type',
            enum: ['', 'checkpoint', 'diffusion', 'vae', 'lora', 'clip', 't5', 'embedding',
                'controlnet', 'llm', 'esrgan', 'taesd', 'motion_module', 'adetailer'],
            default: '',
            description: 'For the list operation, restrict the result to one kind of model. Empty lists all of them'
        },
        search: {
            type: 'string',
            title: 'Search',
            description: 'For the list operation, keep only models whose name contains this text'
        },
        timeout: {
            type: 'number',
            title: 'Timeout (ms)',
            description: 'Loading a large model reads many gigabytes from disk and can take minutes, so this defaults high',
            default: 300000
        }
    },
    required: []
};

const inputSchema = {
    type: 'object',
    properties: {
        data: { type: 'any' }
    }
};

const outputSchema = {
    type: 'object',
    properties: {
        operation: { type: 'string' },
        success: { type: 'boolean' },
        modelLoaded: { type: 'boolean', description: 'For health, whether a model occupies the main slot' },
        modelName: { type: 'string' },
        modelType: { type: 'string' },
        architecture: { type: 'string', description: 'Architecture the server detected, which decides the generation defaults' },
        upscalerLoaded: { type: 'boolean' },
        upscalerName: { type: 'string' },
        loadedComponents: { type: 'object', description: 'Which component files are resident' },
        models: { type: 'array', description: 'For list, a flat array of {type, name} entries' },
        modelsByType: { type: 'object', description: 'For list, the raw grouping the server returned' },
        count: { type: 'number', description: 'For list, how many models matched' },
        message: { type: 'string' },
        health: { type: 'object', description: 'For health, the full response including memory and feature flags' }
    }
};

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;
}

function putIfSet(target, key, value) {
    if (value === undefined || value === null || value === '') {
        return;
    }
    target[key] = value;
}

// The list response groups models under one key per kind. Flattening gives a
// single array a Loop node can walk without knowing the key names.
const LIST_GROUPS = {
    checkpoints: 'checkpoint',
    diffusion_models: 'diffusion',
    vae: 'vae',
    loras: 'lora',
    clip: 'clip',
    t5: 't5',
    embeddings: 'embedding',
    controlnets: 'controlnet',
    llm: 'llm',
    esrgan: 'esrgan',
    taesd: 'taesd',
    motion_modules: 'motion_module',
    adetailers: 'adetailer'
};

function flattenModels(listed) {
    const flat = [];
    const groupNames = Object.keys(LIST_GROUPS);

    for (let i = 0; i < groupNames.length; i++) {
        const group = groupNames[i];
        const entries = listed[group];
        if (!Array.isArray(entries)) {
            continue;
        }
        for (let j = 0; j < entries.length; j++) {
            const entry = entries[j];
            // Entries are sometimes plain file names and sometimes objects
            // carrying a name plus size and hash, so handle both rather than
            // assuming one and producing a column of undefined.
            if (entry && typeof entry === 'object') {
                flat.push({
                    type: LIST_GROUPS[group],
                    name: entry.name || entry.filename || '',
                    details: entry
                });
            } else {
                flat.push({ type: LIST_GROUPS[group], name: String(entry), details: null });
            }
        }
    }
    return flat;
}

async function execute(config, input, context) {
    const server = normalizeServer(config.serverUrl);
    const operation = config.operation || 'health';
    const timeout = config.timeout || 300000;

    // /health is the one endpoint the server leaves unauthenticated, which makes
    // it usable as a reachability check before any credential exists.
    if (operation === 'health') {
        const health = call({
            method: 'GET',
            url: server + '/health',
            timeout: timeout,
            what: 'reading server health'
        });

        return {
            operation: operation,
            success: true,
            modelLoaded: health.model_loaded === true,
            modelName: health.model_name || '',
            modelType: health.model_type || '',
            architecture: health.model_architecture || '',
            upscalerLoaded: health.upscaler_loaded === true,
            upscalerName: health.upscaler_name || '',
            loadedComponents: health.loaded_components || {},
            models: [],
            modelsByType: {},
            count: 0,
            message: health.status || '',
            health: health
        };
    }

    if (!config.credentialId) {
        throw new Error('SD.cpp: the ' + operation + ' operation needs a credential. ' +
            'Only health works without one');
    }

    const credential = readCredential(config.credentialId);
    const token = login(server, credential, timeout);
    const authHeaders = { 'Authorization': 'Bearer ' + token };
    const jsonHeaders = {
        'Authorization': 'Bearer ' + token,
        'Content-Type': 'application/json'
    };

    if (operation === 'list') {
        const query = [];
        if (config.listType) {
            query.push('type=' + encodeURIComponent(config.listType));
        }
        if (config.search) {
            query.push('search=' + encodeURIComponent(config.search));
        }

        const listed = call({
            method: 'GET',
            url: server + '/models' + (query.length ? '?' + query.join('&') : ''),
            headers: authHeaders,
            timeout: timeout,
            what: 'listing models'
        });

        const flat = flattenModels(listed);

        return {
            operation: operation,
            success: true,
            modelLoaded: !!listed.loaded_model,
            modelName: listed.loaded_model || '',
            modelType: listed.loaded_model_type || '',
            architecture: '',
            upscalerLoaded: false,
            upscalerName: '',
            loadedComponents: {},
            models: flat,
            modelsByType: listed,
            count: flat.length,
            message: '',
            health: {}
        };
    }

    if (operation === 'refresh') {
        const refreshed = call({
            method: 'POST',
            url: server + '/models/refresh',
            headers: jsonHeaders,
            body: '{}',
            timeout: timeout,
            what: 'rescanning the model directories'
        });

        return {
            operation: operation,
            success: true,
            modelLoaded: false,
            modelName: '',
            modelType: '',
            architecture: '',
            upscalerLoaded: false,
            upscalerName: '',
            loadedComponents: {},
            models: [],
            modelsByType: {},
            count: 0,
            message: refreshed.message || 'model directories rescanned',
            health: {}
        };
    }

    if (operation === 'unload' || operation === 'unloadUpscaler') {
        const path = operation === 'unload' ? '/models/unload' : '/upscaler/unload';
        const unloaded = call({
            method: 'POST',
            url: server + path,
            headers: jsonHeaders,
            body: '{}',
            timeout: timeout,
            what: operation === 'unload' ? 'unloading the model' : 'unloading the upscaler'
        });

        return {
            operation: operation,
            success: true,
            modelLoaded: false,
            modelName: '',
            modelType: '',
            architecture: '',
            upscalerLoaded: false,
            upscalerName: '',
            loadedComponents: {},
            models: [],
            modelsByType: {},
            count: 0,
            message: unloaded.message || 'unloaded',
            health: {}
        };
    }

    const modelName = String(config.modelName || '').trim();
    if (!modelName) {
        throw new Error('SD.cpp: the ' + operation + ' operation needs a model name');
    }

    if (operation === 'loadUpscaler') {
        const body = { model_name: modelName };
        const loaded = call({
            method: 'POST',
            url: server + '/upscaler/load',
            headers: jsonHeaders,
            body: JSON.stringify(body),
            timeout: timeout,
            what: 'loading upscaler ' + modelName
        });

        smartbotic.log.info('SD.cpp: loaded upscaler ' + modelName);

        return {
            operation: operation,
            success: loaded.success !== false,
            modelLoaded: false,
            modelName: modelName,
            modelType: 'esrgan',
            architecture: '',
            upscalerLoaded: true,
            upscalerName: modelName,
            loadedComponents: {},
            models: [],
            modelsByType: {},
            count: 0,
            message: loaded.message || '',
            health: {}
        };
    }

    if (operation !== 'load') {
        throw new Error('SD.cpp: unknown operation "' + operation + '"');
    }

    const body = { model_name: modelName };
    putIfSet(body, 'model_type', config.modelType);
    putIfSet(body, 'vae', config.vae);
    putIfSet(body, 'clip_l', config.clipL);
    putIfSet(body, 'clip_g', config.clipG);
    putIfSet(body, 't5xxl', config.t5xxl);
    putIfSet(body, 'llm', config.llm);
    putIfSet(body, 'taesd', config.taesd);
    putIfSet(body, 'controlnet', config.controlnet);

    if (config.options && typeof config.options === 'object') {
        body.options = config.options;
    }

    // Loading a model unloads whatever was in the slot first, and the server
    // holds a mutex for the duration, so this call blocks until the weights are
    // resident. That is why the timeout defaults to five minutes.
    const loaded = call({
        method: 'POST',
        url: server + '/models/load',
        headers: jsonHeaders,
        body: JSON.stringify(body),
        timeout: timeout,
        what: 'loading model ' + modelName
    });

    smartbotic.log.info('SD.cpp: loaded model ' + modelName +
        (loaded.model_type ? ' as ' + loaded.model_type : ''));

    return {
        operation: operation,
        success: loaded.success !== false,
        modelLoaded: true,
        modelName: loaded.model_name || modelName,
        modelType: loaded.model_type || config.modelType || '',
        architecture: '',
        upscalerLoaded: false,
        upscalerName: '',
        loadedComponents: loaded.loaded_components || {},
        models: [],
        modelsByType: {},
        count: 0,
        message: loaded.message || '',
        health: {}
    };
}

module.exports = { configSchema, inputSchema, outputSchema, execute };