/** * Brand Assets AI Context Routes — Primary Logo guided generation * * Background-queue endpoints that generate a PRIMARY logo after studying the * business profile, brand strategy, and competitor landscape. Mirrors the * aiContextBrand.ts pattern: createJob → 202 { jobId } → setImmediate runs * the work → completeJob with a result the frontend polls. * * POST /primary-logo/generate — fresh generation from current context * POST /primary-logo/regenerate — distinctly different direction, same context * POST /primary-logo/refine — incorporate user feedback ("make it bolder") * GET /status/:jobId — poll job status * * The image itself is produced by the same providers as /image-generations * (generateImageWithOpenAI with Zhipu CogView fallback) and stored as an * ImageGeneration doc with versions[] so the existing review/history UI works. * "Use this logo" is handled by the existing POST /image-generations/save-to-brand-assets/:id. */ import express, { Request, Response } from 'express'; import fs from 'fs'; import path from 'path'; import { body, validationResult } from 'express-validator'; import { authenticate } from '../middleware/auth'; import { requirePermission } from '../middleware/permissions'; import { createJob, updateJobProgress, completeJob, failJob, getJob } from '../services/aiContext/aiJobManager'; import { buildPrimaryLogoPrompt, PrimaryLogoPromptInputs } from '../services/aiContext/primaryLogoPrompts'; import { buildWatermarkPrompt, WatermarkPromptInputs } from '../services/aiContext/watermarkPrompts'; import { buildBackdropPrompt, BackdropPromptInputs } from '../services/aiContext/backdropPrompts'; import multer from 'multer'; import { generateImageWithZhipuCogView, generateImageForProvider } from './imageGenerations'; import { getAIConfig, getImageProviderForModel, IMAGE_PROVIDER_NAMES, type ImageProvider } from '../utils/aiProvider'; import { stripReasoning } from '../utils/stripReasoning'; import { getModels } from '../models'; const router = express.Router(); router.use(authenticate); // ============================================ // HELPERS // ============================================ /** Authorise company access — admin bypasses all checks (mirrors imageGenerations). */ const authorizeCompany = (req: Request, companyId: string): boolean => { return !!companyId && (req.user?.companyIds?.includes(companyId) || req.user?.role === 'admin'); }; /** Hard outer timeout so a hung provider call can't hold the job forever. */ const PROVIDER_TIMEOUT_MS = 240000; function withTimeout(promise: Promise, ms: number, label: string): Promise { let timer: NodeJS.Timeout | undefined; const timeout = new Promise((_, reject) => { timer = setTimeout(() => reject(new Error(`${label} timed out after ${Math.round(ms / 1000)}s`)), ms); }); return Promise.race([promise, timeout]).finally(() => { if (timer) clearTimeout(timer); }); } /** * The ImageGeneration schema caps `originalPrompt` at 3000 chars, but the * composed logo prompt (brand + competitor + guidance) is usually longer. * Truncate the stored field to fit the schema while the FULL prompt is still * sent to the image provider and preserved in `ollamaEnhancedPrompt` (15k cap). */ function truncateForStorage(text: string, limit: number): string { if (text.length <= limit) return text; const marker = '…[truncated for storage; full prompt sent to generator]'; return text.slice(0, Math.max(0, limit - marker.length)) + marker; } /** * Direct OpenAI Images call using gpt-image-2 at HIGH quality. Shared by the * guided Primary Logo and Watermark flows. This bypasses the shared * generateImageWithOpenAI provider, whose per-request timeout (config.AI_TIMEOUT, * ~120s) + retry loop is too short for gpt-image-2 high-quality generation, * which routinely exceeds 120s and would otherwise be aborted on every attempt. * * Single attempt, 300s timeout, no model fallback (we want gpt-image-2 * specifically). The Zhipu CogView fallback in the caller handles total * failure. `logLabel` only affects console logs. */ async function generateBrandImageWithOpenAI(prompt: string, logLabel = 'PrimaryLogo', userId?: string): Promise<{ base64Data: string; revisedPrompt: string; model: string; provider: string; tokenUsage: { inputTokens: number; outputTokens: number; totalTokens: number }; latencyMs: number; }> { const config = await getAIConfig(userId); const openaiKey = config.OPENAI_API_KEY; if (!openaiKey) { throw new Error('OpenAI API key not configured. Set OPENAI_API_KEY in .env or add a key in Super Admin settings.'); } const openaiBaseUrl = (config.OPENAI_API_URL || 'https://api.openai.com/v1/chat/completions') .replace('/chat/completions', '') .replace(/\/$/, ''); const imagesUrl = `${openaiBaseUrl}/images/generations`; const size = '1024x1024'; const model = 'gpt-image-2'; const body = { model, prompt, size, quality: 'high' }; const callStartTime = Date.now(); const controller = new AbortController(); const timeoutId = setTimeout(() => controller.abort(), 300000); // 300s — gpt-image-2 high can be slow console.log(`[${logLabel}] Calling OpenAI Images API: ${imagesUrl} | model=${model} | size=${size} | quality=high (300s timeout)`); try { const response = await fetch(imagesUrl, { method: 'POST', headers: { 'Content-Type': 'application/json', Authorization: `Bearer ${openaiKey}`, }, body: JSON.stringify(body), signal: controller.signal, }); if (!response.ok) { const errorText = await response.text(); throw new Error(`OpenAI Images API error (${response.status}) with ${model}: ${errorText}`); } const data: any = await response.json(); const latencyMs = Date.now() - callStartTime; const usage = data.usage; const tokenUsage = { inputTokens: usage?.input_tokens || usage?.prompt_tokens || 0, outputTokens: usage?.output_tokens || usage?.completion_tokens || 0, totalTokens: (usage?.input_tokens || usage?.prompt_tokens || 0) + (usage?.output_tokens || usage?.completion_tokens || 0), }; // Extract base64. gpt-image-2 via Images API returns { data: [{ b64_json }] }. let base64 = ''; let revisedPrompt = ''; const image = data.data?.[0]; if (image) { base64 = image.b64_json || image.base64_data || image.base64Data || image.data || ''; revisedPrompt = image.revised_prompt || ''; } // Chat-style: { output: [{ content: [{ type: 'image_url', url: 'data:image/...;base64,...' }] }] } if (!base64 && Array.isArray(data.output)) { for (const out of data.output) { for (const c of out.content || []) { if (c.type === 'image_url' && typeof c.url === 'string' && c.url.startsWith('data:image')) { const m = c.url.match(/^data:image\/\w+;base64,(.+)$/); if (m) base64 = m[1]; } } } } // URL response — download and convert. if (!base64 && image?.url) { const urlResp = await fetch(image.url, { signal: AbortSignal.timeout(60000) }); if (urlResp.ok) { base64 = Buffer.from(await urlResp.arrayBuffer()).toString('base64'); } } if (!base64) { throw new Error(`OpenAI returned no image data. Response keys: ${Object.keys(data).join(', ')}`); } console.log(`[${logLabel}] Image generated with ${model} in ${latencyMs}ms | base64 length=${base64.length}`); return { base64Data: base64, revisedPrompt, model, provider: 'openai', tokenUsage, latencyMs }; } finally { clearTimeout(timeoutId); } } // ============================================ // SECONDARY LOGO — image-to-image from the primary logo // ============================================ /** * Variation → { directive, assetType, label }. The directive is folded into the * prompt sent with the reference image; assetType is the BrandAsset type used * when the user clicks "Use this logo". The roadmap's Secondary Logo stage is * considered done when any of these types exists. */ const SECONDARY_LOGO_VARIATIONS: Record = { wordmark: { directive: 'wordmark (text only): render ONLY the brand name in the SAME type style, weight and colour as the ' + 'attached primary logo, with no icon/mark. Keep the typography identical to the reference.', assetType: 'wordmark', label: 'Wordmark', }, horizontal: { directive: 'horizontal lockup: place the icon/mark to the LEFT of the wordmark, aligned on a single baseline, side ' + 'by side. Preserve the exact mark and wordmark from the reference — do not restyle them.', assetType: 'logoHorizontal', label: 'Horizontal lockup', }, stacked: { directive: 'stacked / vertical lockup: place the icon/mark ABOVE the wordmark, both centred as a vertical stack. ' + 'Preserve the exact mark and wordmark from the reference — do not restyle them.', assetType: 'logoVertical', label: 'Stacked / vertical lockup', }, 'icon-only': { directive: 'icon-only mark: show ONLY the symbol/mark from the attached primary logo, centred, with no wordmark. ' + 'Keep the mark identical to the reference.', assetType: 'logoIconOnly', label: 'Icon-only mark', }, }; /** * Logo VARIATION definitions — treatments/layouts derived from the primary logo * (the Logo Variations roadmap stage). Each is generated image-to-image from the * approved primary logo so it stays visually aligned. `assetType` is the * BrandAsset type used when the user saves a variation; the roadmap's Logo * Variations stage is considered done when any of these types exists. */ const LOGO_VARIATION_DEFINITIONS: Record = { logoMarkLight: { directive: 'light mark: render the logo/mark in a single light, light-background-friendly monochrome treatment (e.g. ' + 'white or pale tint on a neutral light backdrop). Preserve the mark shape and proportions from the reference ' + 'exactly — only change the colour treatment.', assetType: 'logoMarkLight', label: 'Light mark', }, logoMarkDark: { directive: 'dark mark: render the logo/mark in a single dark monochrome treatment (e.g. black or deep tint on a neutral ' + 'backdrop) suitable for dark backgrounds. Preserve the mark shape and proportions from the reference exactly ' + '— only change the colour treatment.', assetType: 'logoMarkDark', label: 'Dark mark', }, 'logo-icon': { directive: 'icon-only mark: show ONLY the symbol/mark from the attached primary logo, centred, with no wordmark. ' + 'Keep the mark identical to the reference.', assetType: 'logoIconOnly', label: 'Icon-only mark', }, horizontal: { directive: 'horizontal lockup: place the icon/mark to the LEFT of the wordmark, aligned on a single baseline, side ' + 'by side. Preserve the exact mark and wordmark from the reference — do not restyle them.', assetType: 'logoHorizontal', label: 'Horizontal lockup', }, stacked: { directive: 'stacked / vertical lockup: place the icon/mark ABOVE the wordmark, both centred as a vertical stack. ' + 'Preserve the exact mark and wordmark from the reference — do not restyle them.', assetType: 'logoVertical', label: 'Stacked / vertical lockup', }, }; /** * Brand PATTERN definitions — geometric/abstract/logo-inspired surface patterns * derived image-to-image from the approved primary logo. Each is generated from * the primary logo as a reference image so the pattern stays visually tied to * the brand mark. Saved as BrandAsset type `brandPattern` (which the website & * landing-page generators already consume as a decorative overlay). The roadmap's * Brand Patterns stage is considered done when any `brandPattern` asset exists. */ const BRAND_PATTERN_VARIATIONS: Record = { geometric: { directive: 'geometric pattern: derive a crisp, structured geometric tile from the shapes and silhouette of the ' + 'attached PRIMARY logo. Extract the mark\'s core geometric forms (circles, squares, triangles, lines, ' + 'grids) and repeat them in a clean, rhythmic layout. Precise, architectural, modern.', assetType: 'brandPattern', label: 'Geometric', }, abstract: { directive: 'abstract pattern: create a fluid, expressive abstract motif inspired by the forms, movement and ' + 'character of the attached PRIMARY logo. Loose shapes and gestures echoing the mark, arranged as a ' + 'balanced surface pattern. Artistic and contemporary.', assetType: 'brandPattern', label: 'Abstract', }, 'seamless-tile': { directive: 'seamless tileable pattern: design a pattern that tiles seamlessly edge-to-edge in ALL directions ' + '(top/bottom and left/right must match perfectly with no visible seams), derived from the mark or ' + 'monogram of the attached PRIMARY logo. Repeatable as a background fill. Subtle enough to sit behind ' + 'content while retaining brand recognition.', assetType: 'brandPattern', label: 'Seamless tile', }, 'packaging-motif': { directive: 'packaging motif: a denser, more decorative surface pattern tuned for product packaging, derived from ' + 'the attached PRIMARY logo\'s mark. Richer texture and visual rhythm than a background pattern, with ' + 'layered elements and depth — still unmistakably on-brand.', assetType: 'brandPattern', label: 'Packaging motif', }, 'presentation-backdrop': { directive: 'presentation backdrop: a very subtle, low-contrast pattern suitable as a slide background behind text, ' + 'derived from the attached PRIMARY logo. Mostly empty space, minimal motif, brand colours at reduced ' + 'saturation and low visual weight so it never competes with foreground content.', assetType: 'brandPattern', label: 'Presentation backdrop', }, }; /** * Read the primary logo's image bytes from disk (or decode its base64Data) so * it can be sent as the reference image to /images/edits. Returns null if no * usable image is found. */ async function readPrimaryLogoImage(asset: any): Promise<{ buffer: Buffer; mimeType: string } | null> { try { if (asset.base64Data) { const dataUriMatch = String(asset.base64Data).match(/^data:([^;]+);base64,(.+)$/s); if (dataUriMatch) { return { buffer: Buffer.from(dataUriMatch[2], 'base64'), mimeType: dataUriMatch[1] }; } return { buffer: Buffer.from(String(asset.base64Data), 'base64'), mimeType: 'image/png' }; } if (asset.url && typeof asset.url === 'string') { // url is a web path like /uploads/brand-assets/.png — resolve from cwd. const filePath = asset.url.startsWith('/uploads/brand-assets/') ? path.resolve(process.cwd(), 'uploads', 'brand-assets', path.basename(asset.url)) : path.resolve(process.cwd(), asset.url.replace(/^\//, '')); if (!fs.existsSync(filePath)) { console.warn(`[SecondaryLogo] Primary logo file not found at ${filePath}`); return null; } const buffer = await fs.promises.readFile(filePath); const ext = path.extname(filePath).toLowerCase(); const mimeType = ext === '.jpg' || ext === '.jpeg' ? 'image/jpeg' : ext === '.webp' ? 'image/webp' : ext === '.svg' ? 'image/svg+xml' : 'image/png'; return { buffer, mimeType }; } return null; } catch (e) { console.warn('[SecondaryLogo] Failed to read primary logo image:', (e as Error).message); return null; } } /** * Call OpenAI /images/edits with a reference image (e.g. the primary logo) and * a prompt, using gpt-image-2 at high quality. Single attempt, 300s timeout. * This is the shared image-to-image mechanism that keeps derived brand assets * (secondary logos, logo variations, watermark) visually aligned with the * approved primary logo — the model sees the reference image. No Zhipu * fallback — CogView cannot take a reference image, so a fallback would lose * alignment; callers decide how to handle a failed edit (e.g. fall back to a * from-scratch generation). `logLabel` only affects console logs. */ export async function generateBrandImageEditWithOpenAI( prompt: string, imageBuffer: Buffer, imageMime: string, logLabel = 'ImageEdit', userId?: string ): Promise<{ base64Data: string; revisedPrompt: string; model: string; provider: string; tokenUsage: { inputTokens: number; outputTokens: number; totalTokens: number }; latencyMs: number; }> { const config = await getAIConfig(userId); const openaiKey = config.OPENAI_API_KEY; if (!openaiKey) { throw new Error('OpenAI API key not configured. Set OPENAI_API_KEY in .env or add a key in Super Admin settings.'); } const openaiBaseUrl = (config.OPENAI_API_URL || 'https://api.openai.com/v1/chat/completions') .replace('/chat/completions', '') .replace(/\/$/, ''); const editsUrl = `${openaiBaseUrl}/images/edits`; const model = 'gpt-image-2'; const form = new FormData(); form.append('model', model); form.append('image', new Blob([imageBuffer], { type: imageMime }), 'primary-logo.png'); form.append('prompt', prompt); form.append('size', '1024x1024'); form.append('quality', 'high'); const callStartTime = Date.now(); const controller = new AbortController(); const timeoutId = setTimeout(() => controller.abort(), 300000); // 300s console.log(`[${logLabel}] Calling OpenAI Images Edits: ${editsUrl} | model=${model} | ref mime=${imageMime} (300s timeout)`); try { const response = await fetch(editsUrl, { method: 'POST', headers: { Authorization: `Bearer ${openaiKey}` }, body: form, signal: controller.signal, }); if (!response.ok) { const errorText = await response.text(); throw new Error(`OpenAI Images Edits error (${response.status}) with ${model}: ${errorText}`); } const data: any = await response.json(); const latencyMs = Date.now() - callStartTime; const usage = data.usage; const tokenUsage = { inputTokens: usage?.input_tokens || usage?.prompt_tokens || 0, outputTokens: usage?.output_tokens || usage?.completion_tokens || 0, totalTokens: (usage?.input_tokens || usage?.prompt_tokens || 0) + (usage?.output_tokens || usage?.completion_tokens || 0), }; let base64 = ''; let revisedPrompt = ''; const image = data.data?.[0]; if (image) { base64 = image.b64_json || image.base64_data || image.base64Data || image.data || ''; revisedPrompt = image.revised_prompt || ''; } if (!base64 && Array.isArray(data.output)) { for (const out of data.output) { for (const c of out.content || []) { if (c.type === 'image_url' && typeof c.url === 'string' && c.url.startsWith('data:image')) { const m = c.url.match(/^data:image\/\w+;base64,(.+)$/); if (m) base64 = m[1]; } } } } if (!base64 && image?.url) { const urlResp = await fetch(image.url, { signal: AbortSignal.timeout(60000) }); if (urlResp.ok) { base64 = Buffer.from(await urlResp.arrayBuffer()).toString('base64'); } } if (!base64) { throw new Error(`OpenAI returned no image data. Response keys: ${Object.keys(data).join(', ')}`); } console.log(`[${logLabel}] Reference-image edit generated with ${model} in ${latencyMs}ms | base64 length=${base64.length}`); return { base64Data: base64, revisedPrompt, model, provider: 'openai', tokenUsage, latencyMs }; } finally { clearTimeout(timeoutId); } } // ============================================ // GET /status/:jobId // ============================================ router.get('/status/:jobId', async (req: Request, res: Response) => { const { jobId } = req.params; const job = getJob(jobId); if (!job) { res.status(404).json({ error: 'Job not found' }); return; } res.json({ jobId: job.jobId, status: job.status, progress: job.progress, step: job.step, result: job.result, error: job.error, }); }); // ============================================ // Shared generation handler // ============================================ interface GenerateBody { companyId: string; refineFeedback?: string; regenerateFeedback?: string; previousPrompt?: string; previousConceptSummary?: string; style?: string; aspectRatio?: string; model?: string; // User configuration fields description?: string; requirements?: string; stylePreferences?: string[]; additionalNotes?: string; logoType?: string; } /** * Run the full Primary Logo generation in the background, updating the job as * it goes. Resolves when completeJob/failJob has been called. * * `kind` only affects the progress label and the `source` reported on the job. */ async function runPrimaryLogoGeneration( jobId: string, req: Request, body: GenerateBody, kind: 'generate' | 'regenerate' | 'refine' ): Promise { const { ImageGeneration } = getModels(); const { companyId } = body; updateJobProgress(jobId, 10, 'Analyzing business profile & brand strategy...'); const promptInputs: PrimaryLogoPromptInputs = { companyId, refineFeedback: kind === 'refine' ? body.refineFeedback : undefined, regenerateFeedback: kind === 'regenerate' ? body.regenerateFeedback : undefined, previousPrompt: kind !== 'generate' ? body.previousPrompt : undefined, previousConceptSummary: kind !== 'generate' ? body.previousConceptSummary : undefined, style: body.style || 'Minimalist', aspectRatio: body.aspectRatio || '1:1', // User configuration description: body.description, requirements: body.requirements, stylePreferences: body.stylePreferences, additionalNotes: body.additionalNotes, }; const { systemPrompt: _systemPrompt, userPrompt, conceptSummary } = await buildPrimaryLogoPrompt(promptInputs); updateJobProgress(jobId, 40, 'Analyzing competitor landscape & composing logo prompt...'); // Create / fetch an ImageGeneration doc to accumulate versions. // For generate we create a new doc; for regenerate/refine we append a version // to the existing doc identified by previousPrompt's generation if available, // but simplest correct behaviour: create a new doc per request so each // version is traceable. The frontend keeps the latest imageGenerationId. const generation = new ImageGeneration({ companyId, name: 'Primary Logo', description: 'Primary brand logo (guided flow)', style: promptInputs.style || 'Minimalist', platform: 'Brand', aspectRatio: promptInputs.aspectRatio || '1:1', // Schema caps originalPrompt at 3000 chars; full prompt is sent to the // provider and preserved in ollamaEnhancedPrompt below. originalPrompt: truncateForStorage(userPrompt, 3000), status: 'generating', createdBy: req.user?.id, }); await generation.save(); updateJobProgress(jobId, 55, 'Generating primary logo...'); const size = '1024x1024'; // Determine model and provider from the request body, defaulting to gpt-image-2. const model = body.model || 'gpt-image-2'; const imageProvider: ImageProvider = getImageProviderForModel(model); // Primary logos use gpt-image-2 at high quality via a dedicated direct call // (300s timeout) — the shared provider's 120s per-request timeout aborts // gpt-image-2 high-quality generation, which routinely exceeds 120s. If the // direct OpenAI call fails, fall back to Zhipu CogView. const PRIMARY_MODEL = model; const userId = req.user?._id?.toString(); let imageResult; let providerUsed: string; let modelUsed: string; try { if (imageProvider === 'openai') { // Use the dedicated high-quality call for OpenAI (300s timeout for gpt-image-2) imageResult = await generateBrandImageWithOpenAI(userPrompt, 'PrimaryLogo', userId); } else { // Use the unified provider router for non-OpenAI providers imageResult = await withTimeout( generateImageForProvider(imageProvider, model, userPrompt, size, 'standard', 'vivid'), PROVIDER_TIMEOUT_MS, `Primary logo generation (${IMAGE_PROVIDER_NAMES[imageProvider] || imageProvider})` ); } providerUsed = imageResult.provider; modelUsed = imageResult.model; } catch (primaryErr) { // Only attempt CogView-3 fallback when the primary provider is OpenAI if (imageProvider === 'openai') { console.warn(`[PrimaryLogo] ${PRIMARY_MODEL} unavailable, trying Zhipu CogView fallback:`, (primaryErr as Error).message); updateJobProgress(jobId, 70, 'Primary provider unavailable; trying fallback...'); try { imageResult = await withTimeout( generateImageWithZhipuCogView(userPrompt, size), PROVIDER_TIMEOUT_MS, 'Primary logo generation (fallback)' ); providerUsed = imageResult.provider; modelUsed = imageResult.model; } catch (fallbackErr) { generation.status = 'failed'; await generation.save().catch(() => {}); throw new Error( `Logo generation failed: ${(fallbackErr as Error).message || (primaryErr as Error).message || 'all image providers failed'}` ); } } else { generation.status = 'failed'; await generation.save().catch(() => {}); throw new Error( `Logo generation failed with ${IMAGE_PROVIDER_NAMES[imageProvider] || imageProvider}: ${(primaryErr as Error).message || 'image generation failed'}` ); } } // Push the new version (mirror imageGenerations.ts /generate/:id logic). for (const v of generation.versions) v.isCurrent = false; const versionNumber = generation.versions.length + 1; generation.versions.push({ version: versionNumber, prompt: generation.originalPrompt, enhancedPrompt: stripReasoning(userPrompt), imageUrl: '', base64Data: imageResult.base64Data, generationProvider: providerUsed, generationModel: modelUsed, aspectRatio: generation.aspectRatio, size, quality: 'standard', style: 'vivid', revisedPrompt: imageResult.revisedPrompt, tokenUsage: imageResult.tokenUsage || { inputTokens: 0, outputTokens: 0, totalTokens: 0 }, latencyMs: imageResult.latencyMs || 0, isCurrent: true, } as any); generation.currentVersion = versionNumber; generation.totalVersions = versionNumber; generation.generationProvider = providerUsed; generation.generationModel = modelUsed; if (!generation.ollamaEnhancedPrompt) { generation.ollamaEnhancedPrompt = truncateForStorage(stripReasoning(userPrompt), 15000); } generation.status = 'completed'; await generation.save(); updateJobProgress(jobId, 90, 'Finalizing...'); completeJob( jobId, { imageGenerationId: String(generation._id), brandAssetId: null, // not saved as a BrandAsset until "Use this logo" prompt: userPrompt, conceptSummary, model: modelUsed, provider: providerUsed, versionNumber, }, kind === 'regenerate' ? 'regenerated' : kind === 'refine' ? 'refined' : 'generated' ); } // ============================================ // Route validation helper // ============================================ function validateCompany(req: Request, res: Response): string | null { const errors = validationResult(req); if (!errors.isEmpty()) { res.status(400).json({ errors: errors.array() }); return null; } const companyId = req.body.companyId as string; if (!authorizeCompany(req, companyId)) { res.status(403).json({ error: 'Not authorised for this company' }); return null; } return companyId; } const generateValidations = [ body('companyId').trim().notEmpty().withMessage('Company ID is required'), ]; // ============================================ // POST /primary-logo/generate // ============================================ router.post( '/primary-logo/generate', requirePermission('brand-assets', 'ai-generate'), generateValidations, async (req: Request, res: Response) => { const companyId = validateCompany(req, res); if (!companyId) return; const job = createJob('brand-assets', companyId, 'brand-assets'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runPrimaryLogoGeneration(job.jobId, req, req.body, 'generate'); } catch (err) { console.error('[PrimaryLogo] generate failed:', err); failJob(job.jobId, (err as Error).message || 'Primary logo generation failed'); } }); } ); // ============================================ // POST /primary-logo/regenerate // ============================================ router.post( '/primary-logo/regenerate', requirePermission('brand-assets', 'ai-generate'), [ ...generateValidations, body('regenerateFeedback').trim().notEmpty().withMessage('Regenerate feedback is required'), ], async (req: Request, res: Response) => { const companyId = validateCompany(req, res); if (!companyId) return; const job = createJob('brand-assets', companyId, 'brand-assets'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runPrimaryLogoGeneration(job.jobId, req, req.body, 'regenerate'); } catch (err) { console.error('[PrimaryLogo] regenerate failed:', err); failJob(job.jobId, (err as Error).message || 'Primary logo regeneration failed'); } }); } ); // ============================================ // POST /primary-logo/refine // ============================================ router.post( '/primary-logo/refine', requirePermission('brand-assets', 'ai-generate'), [ ...generateValidations, body('refineFeedback').trim().notEmpty().withMessage('Refine feedback is required'), ], async (req: Request, res: Response) => { const companyId = validateCompany(req, res); if (!companyId) return; const job = createJob('brand-assets', companyId, 'brand-assets'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runPrimaryLogoGeneration(job.jobId, req, req.body, 'refine'); } catch (err) { console.error('[PrimaryLogo] refine failed:', err); failJob(job.jobId, (err as Error).message || 'Primary logo refinement failed'); } }); } ); // ============================================ // SECONDARY LOGO — guided, image-to-image from the primary logo // ============================================ /** * Shared reference-image variation generator. Reads the approved primary logo, * then for each chosen variation sends it to gpt-image-2 /images/edits (image- * to-image) with that variation's prompt, stores one ImageGeneration doc per * variation, and completes the job with a `generations[]` array. Each variation * stays visually aligned with the primary because the model sees the reference * image. Used by both the Secondary Logo and Logo Variations guided flows. */ interface ReferenceVariationConfig { variationMap: Record; /** Build the per-variation prompt from its definition. */ buildPrompt: (def: { directive: string; assetType: string; label: string }) => string; /** ImageGeneration doc name for a given variation label. */ docName: (label: string) => string; /** ImageGeneration doc description for a given variation label. */ docDescription: (label: string) => string; /** Console-log label. */ jobLabel: string; /** Noun used in the "failed at " error message. */ errorNoun: string; } async function runReferenceVariationGeneration( jobId: string, req: Request, body: { companyId: string; primaryLogoAssetId: string; variations: string[]; model?: string; // User configuration description?: string; requirements?: string; stylePreferences?: string[]; additionalNotes?: string; }, config: ReferenceVariationConfig ): Promise { const { ImageGeneration, BrandAsset } = getModels(); const { companyId, primaryLogoAssetId, variations, model: requestedModel, description, requirements, stylePreferences, additionalNotes } = body; // Determine the image generation provider from the model parameter const model = requestedModel || 'gpt-image-2'; const provider: ImageProvider = getImageProviderForModel(model); const isEditCapable = provider === 'openai'; // Only OpenAI supports image edits (/images/edits) if (!Array.isArray(variations) || variations.length === 0) { throw new Error('At least one variation is required.'); } // Validate + de-duplicate variations up front. const uniqueVariations = Array.from(new Set(variations)); for (const v of uniqueVariations) { if (!config.variationMap[v]) { throw new Error(`Unknown variation: ${v}. Expected one of ${Object.keys(config.variationMap).join(', ')}`); } } updateJobProgress(jobId, 5, 'Loading your primary logo…'); const primaryAsset = await (BrandAsset as any).findOne({ _id: primaryLogoAssetId, companyId }); if (!primaryAsset) { throw new Error('Primary logo not found. Save a primary logo first.'); } const primaryImage = await readPrimaryLogoImage(primaryAsset); if (!primaryImage) { throw new Error('Could not load the primary logo image file. Try regenerating the primary logo first.'); } const generations: Array<{ imageGenerationId: string; variation: string; variationLabel: string; assetType: string; }> = []; let lastModel = 'gpt-image-2'; let lastProvider = 'openai'; const size = '1024x1024'; const total = uniqueVariations.length; for (let i = 0; i < total; i++) { const variation = uniqueVariations[i]; const variationDef = config.variationMap[variation]; const baseProgress = Math.round((i / total) * 100); updateJobProgress( jobId, 10 + baseProgress, `Generating ${variationDef.label} (${i + 1}/${total}) from your primary logo…` ); // Build prompt with user configuration let userPrompt = config.buildPrompt(variationDef); // Add user configuration to the prompt const userConfigParts: string[] = []; if (description) { userConfigParts.push(`USER REQUIREMENTS: ${description.trim()}`); } if (requirements) { userConfigParts.push(`SPECIFIC CONSTRAINTS: ${requirements.trim()}`); } if (stylePreferences && stylePreferences.length > 0) { userConfigParts.push(`STYLE DIRECTION: ${stylePreferences.join(', ')}`); } if (additionalNotes) { userConfigParts.push(`ADDITIONAL NOTES: ${additionalNotes.trim()}`); } if (userConfigParts.length > 0) { userPrompt = userConfigParts.join('\n\n') + '\n\n' + userPrompt; } const generation = new ImageGeneration({ companyId, name: config.docName(variationDef.label), description: config.docDescription(variationDef.label), style: 'Minimalist', platform: 'Brand', aspectRatio: '1:1', originalPrompt: truncateForStorage(userPrompt, 3000), status: 'generating', createdBy: req.user?.id, }); await generation.save(); let imageResult; try { if (isEditCapable && primaryImage) { // OpenAI supports image-to-image edits with a reference image imageResult = await generateBrandImageEditWithOpenAI( userPrompt, primaryImage.buffer, primaryImage.mimeType, config.jobLabel ); } else { // Non-OpenAI providers: use text-to-image (no reference image support) imageResult = await generateImageForProvider(provider, model, userPrompt, size, 'standard', 'vivid'); } lastModel = imageResult.model; lastProvider = imageResult.provider; } catch (err) { generation.status = 'failed'; await generation.save().catch(() => {}); throw new Error( `${config.errorNoun} generation failed at ${variationDef.label}: ${(err as Error).message || 'image generation failed'}` ); } for (const v of generation.versions) v.isCurrent = false; const versionNumber = generation.versions.length + 1; generation.versions.push({ version: versionNumber, prompt: generation.originalPrompt, enhancedPrompt: stripReasoning(userPrompt), imageUrl: '', base64Data: imageResult.base64Data, generationProvider: imageResult.provider, generationModel: imageResult.model, aspectRatio: generation.aspectRatio, size, quality: 'standard', style: 'vivid', revisedPrompt: imageResult.revisedPrompt, tokenUsage: imageResult.tokenUsage || { inputTokens: 0, outputTokens: 0, totalTokens: 0 }, latencyMs: imageResult.latencyMs || 0, isCurrent: true, } as any); generation.currentVersion = versionNumber; generation.totalVersions = versionNumber; generation.generationProvider = imageResult.provider; generation.generationModel = imageResult.model; if (!generation.ollamaEnhancedPrompt) { generation.ollamaEnhancedPrompt = truncateForStorage(stripReasoning(userPrompt), 15000); } generation.status = 'completed'; await generation.save(); generations.push({ imageGenerationId: String(generation._id), variation, variationLabel: variationDef.label, assetType: variationDef.assetType, }); } updateJobProgress(jobId, 95, 'Finalizing…'); completeJob( jobId, { generations, model: lastModel, provider: lastProvider, }, 'generated' ); } /** * Secondary Logo flow — wordmark / lockups / icon-only, derived image-to-image * from the approved primary logo. */ async function runSecondaryLogoGeneration( jobId: string, req: Request, body: { companyId: string; primaryLogoAssetId: string; variations: string[] } ): Promise { return runReferenceVariationGeneration(jobId, req, body, { variationMap: SECONDARY_LOGO_VARIATIONS, buildPrompt: (def) => 'You are creating a SECONDARY logo variation based on the attached PRIMARY logo (reference image).\n' + `Variation required: ${def.directive}\n\n` + 'Keep the SAME mark, colours, type style and visual language as the attached primary logo — do NOT ' + 'redesign it or change the brand identity. Only rearrange or extract the elements as the variation ' + 'requires. Clean, neutral background. Output the logo centred with clear space around it. Scalable ' + 'vector-style, strong silhouette, at most 2–3 brand colours.', docName: (label) => `Secondary Logo — ${label}`, docDescription: (label) => `Secondary logo variation (${label}) derived from the primary logo`, jobLabel: 'SecondaryLogo', errorNoun: 'Secondary logo', }); } /** * Logo Variations flow — light/dark/icon-only/lockup treatments, derived * image-to-image from the approved primary logo so every variation stays on-brand. */ async function runLogoVariationsGeneration( jobId: string, req: Request, body: { companyId: string; primaryLogoAssetId: string; variations: string[] } ): Promise { return runReferenceVariationGeneration(jobId, req, body, { variationMap: LOGO_VARIATION_DEFINITIONS, buildPrompt: (def) => 'You are creating a LOGO VARIATION based on the attached PRIMARY logo (reference image).\n' + `Variation required: ${def.directive}\n\n` + 'Keep the SAME mark, colours, type style and visual language as the attached primary logo — do NOT ' + 'redesign it or change the brand identity. Only adapt the colour treatment or layout as the variation ' + 'requires. Clean, neutral background. Output the logo centred with clear space around it. Scalable ' + 'vector-style, strong silhouette, at most 2–3 brand colours.', docName: (label) => `Logo Variation — ${label}`, docDescription: (label) => `Logo variation (${label}) derived from the primary logo`, jobLabel: 'LogoVariation', errorNoun: 'Logo variation', }); } /** * Logo Variants Batch — combines ALL logo variants (secondary logo types + * logo variations) into a single batch generation from the primary logo. * This is the unified flow that runs after the user approves their primary logo, * generating wordmark, horizontal, stacked, icon-only, light mark, and dark mark * all at once. */ const LOGO_VARIANTS_BATCH_DEFINITIONS: Record = { wordmark: { directive: 'wordmark (text only): render ONLY the brand name in the SAME type style, weight and colour as the ' + 'attached primary logo, with no icon/mark. Keep the typography identical to the reference.', assetType: 'wordmark', label: 'Wordmark', }, horizontal: { directive: 'horizontal lockup: place the icon/mark to the LEFT of the wordmark, aligned on a single baseline, side ' + 'by side. Preserve the exact mark and wordmark from the reference — do not restyle them.', assetType: 'logoHorizontal', label: 'Horizontal lockup', }, stacked: { directive: 'stacked / vertical lockup: place the icon/mark ABOVE the wordmark, both centred as a vertical stack. ' + 'Preserve the exact mark and wordmark from the reference — do not restyle them.', assetType: 'logoVertical', label: 'Stacked / vertical lockup', }, 'icon-only': { directive: 'icon-only mark: show ONLY the symbol/mark from the attached primary logo, centred, with no wordmark. ' + 'Keep the mark identical to the reference.', assetType: 'logoIconOnly', label: 'Icon-only mark', }, logoMarkLight: { directive: 'light mark: render the logo/mark in a single light, light-background-friendly monochrome treatment (e.g. ' + 'white or pale tint on a neutral light backdrop). Preserve the mark shape and proportions from the reference ' + 'exactly — only change the colour treatment.', assetType: 'logoMarkLight', label: 'Light mark', }, logoMarkDark: { directive: 'dark mark: render the logo/mark in a single dark monochrome treatment (e.g. black or deep tint on a neutral ' + 'backdrop) suitable for dark backgrounds. Preserve the mark shape and proportions from the reference exactly ' + '— only change the colour treatment.', assetType: 'logoMarkDark', label: 'Dark mark', }, favicon: { directive: 'favicon: create a small, square favicon (1:1 aspect ratio) derived from the primary logo\'s icon/mark. ' + 'Simplify and refine the mark so it remains clear, recognisable and legible at 16×16 px and 32×32 px sizes. ' + 'Remove fine detail, thin strokes and small text — the favicon must be a bold, simplified silhouette of the ' + 'brand mark on a transparent or solid background. Preserve the core shape and colour identity from the reference.', assetType: 'favicon', label: 'Favicon', }, }; async function runLogoVariantsBatchGeneration( jobId: string, req: Request, body: { companyId: string; primaryLogoAssetId: string; variations: string[] } ): Promise { return runReferenceVariationGeneration(jobId, req, body, { variationMap: LOGO_VARIANTS_BATCH_DEFINITIONS, buildPrompt: (def) => 'You are creating a LOGO VARIANT based on the attached PRIMARY logo (reference image).\n' + `Variant required: ${def.directive}\n\n` + 'Keep the SAME mark, colours, type style and visual language as the attached primary logo — do NOT ' + 'redesign it or change the brand identity. Only rearrange, extract, or adapt the elements as the variant ' + 'requires. Clean, neutral background. Output the logo centred with clear space around it. Scalable ' + 'vector-style, strong silhouette, at most 2–3 brand colours.', docName: (label) => `Logo Variant — ${label}`, docDescription: (label) => `Logo variant (${label}) derived from the primary logo`, jobLabel: 'LogoVariantsBatch', errorNoun: 'Logo variant', }); } /** * Brand Patterns flow — geometric / abstract / seamless / packaging / backdrop * patterns derived image-to-image from the approved primary logo so every * pattern stays visually tied to the brand mark. Saved as `brandPattern`. */ async function runBrandPatternGeneration( jobId: string, req: Request, body: { companyId: string; primaryLogoAssetId: string; variations: string[]; model?: string } ): Promise { return runReferenceVariationGeneration(jobId, req, body, { variationMap: BRAND_PATTERN_VARIATIONS, buildPrompt: (def) => 'You are creating a BRAND PATTERN based on the attached PRIMARY logo (reference image).\n' + `Pattern required: ${def.directive}\n\n` + 'Draw the pattern\'s motifs DIRECTLY from the attached primary logo — its mark, shapes, silhouette and ' + 'visual language — do NOT introduce unrelated decoration or redesign the brand identity. Use ONLY the ' + 'brand\'s colours (at most 2–3). The output is a SURFACE PATTERN, not a logo: it must read as a repeating ' + 'or fillable texture, not as a single centred emblem. Seamless/tileable where the variation calls for it. ' + 'Clean edges, professional refinement, no photographic noise or illegible small text.', docName: (label) => `Brand Pattern — ${label}`, docDescription: (label) => `Brand pattern (${label}) derived from the primary logo`, jobLabel: 'BrandPattern', errorNoun: 'Brand pattern', }); } router.post( '/secondary-logo/generate', requirePermission('brand-assets', 'ai-generate'), [ body('companyId').trim().notEmpty().withMessage('Company ID is required'), body('primaryLogoAssetId').trim().notEmpty().withMessage('Primary logo asset ID is required'), body('variations').isArray({ min: 1 }).withMessage('At least one variation is required'), ], async (req: Request, res: Response) => { const errors = validationResult(req); if (!errors.isEmpty()) { res.status(400).json({ errors: errors.array() }); return; } const companyId = req.body.companyId as string; if (!authorizeCompany(req, companyId)) { res.status(403).json({ error: 'Not authorised for this company' }); return; } // Distinct job module so the secondary flow doesn't collide with the // primary-logo flow's useJobResult('brand-assets', companyId) state. const job = createJob('brand-assets-secondary', companyId, 'brand-assets-secondary'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runSecondaryLogoGeneration(job.jobId, req, req.body); } catch (err) { console.error('[SecondaryLogo] generate failed:', err); failJob(job.jobId, (err as Error).message || 'Secondary logo generation failed'); } }); } ); // ============================================ // LOGO VARIANTS BATCH — all logo variants in a single step // ============================================ router.post( '/logo-variants-batch/generate', requirePermission('brand-assets', 'ai-generate'), [ body('companyId').trim().notEmpty().withMessage('Company ID is required'), body('primaryLogoAssetId').trim().notEmpty().withMessage('Primary logo asset ID is required'), body('variations').isArray({ min: 1 }).withMessage('At least one variation is required'), ], async (req: Request, res: Response) => { const errors = validationResult(req); if (!errors.isEmpty()) { res.status(400).json({ errors: errors.array() }); return; } const companyId = req.body.companyId as string; if (!authorizeCompany(req, companyId)) { res.status(403).json({ error: 'Not authorised for this company' }); return; } const job = createJob('brand-assets-variants-batch', companyId, 'brand-assets-variants-batch'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runLogoVariantsBatchGeneration(job.jobId, req, req.body); } catch (err) { console.error('[LogoVariantsBatch] generate failed:', err); failJob(job.jobId, (err as Error).message || 'Logo variants batch generation failed'); } }); } ); // ============================================ // LOGO VARIATIONS — guided, image-to-image from the primary logo // ============================================ router.post( '/logo-variations/generate', requirePermission('brand-assets', 'ai-generate'), [ body('companyId').trim().notEmpty().withMessage('Company ID is required'), body('primaryLogoAssetId').trim().notEmpty().withMessage('Primary logo asset ID is required'), body('variations').isArray({ min: 1 }).withMessage('At least one variation is required'), ], async (req: Request, res: Response) => { const errors = validationResult(req); if (!errors.isEmpty()) { res.status(400).json({ errors: errors.array() }); return; } const companyId = req.body.companyId as string; if (!authorizeCompany(req, companyId)) { res.status(403).json({ error: 'Not authorised for this company' }); return; } // Distinct job module so the variations flow doesn't collide with the // secondary or primary flows' useJobResult state. const job = createJob('brand-assets-variations', companyId, 'brand-assets-variations'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runLogoVariationsGeneration(job.jobId, req, req.body); } catch (err) { console.error('[LogoVariations] generate failed:', err); failJob(job.jobId, (err as Error).message || 'Logo variation generation failed'); } }); } ); // ============================================ // BRAND PATTERNS — guided, image-to-image from the primary logo // ============================================ router.post( '/brand-patterns/generate', requirePermission('brand-assets', 'ai-generate'), [ body('companyId').trim().notEmpty().withMessage('Company ID is required'), body('primaryLogoAssetId').trim().notEmpty().withMessage('Primary logo asset ID is required'), body('variations').isArray({ min: 1 }).withMessage('At least one variation is required'), ], async (req: Request, res: Response) => { const errors = validationResult(req); if (!errors.isEmpty()) { res.status(400).json({ errors: errors.array() }); return; } const companyId = req.body.companyId as string; if (!authorizeCompany(req, companyId)) { res.status(403).json({ error: 'Not authorised for this company' }); return; } // Distinct job module so the patterns flow doesn't collide with the // secondary/variations/watermark flows' useJobResult state. const job = createJob('brand-assets-patterns', companyId, 'brand-assets-patterns'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runBrandPatternGeneration(job.jobId, req, req.body); } catch (err) { console.error('[BrandPattern] generate failed:', err); failJob(job.jobId, (err as Error).message || 'Brand pattern generation failed'); } }); } ); // ============================================ // WATERMARK — guided flow (mirrors the Primary Logo flow) // ============================================ /** * Run the guided Watermark generation in the background. Same shape as * runPrimaryLogoGeneration but uses the watermark prompt builder and saves the * ImageGeneration doc as a watermark. Distinct job module * 'brand-assets-watermark' so it doesn't collide with the primary or secondary * flows' useJobResult state. */ async function runWatermarkGeneration( jobId: string, req: Request, body: { companyId: string; /** Approved primary logo to distil the watermark from (reference image). */ primaryLogoAssetId?: string; refineFeedback?: string; regenerateFeedback?: string; previousPrompt?: string; previousConceptSummary?: string; style?: string; aspectRatio?: string; // User configuration description?: string; requirements?: string; stylePreferences?: string[]; additionalNotes?: string; }, kind: 'generate' | 'regenerate' | 'refine' ): Promise { const { ImageGeneration, BrandAsset } = getModels(); const { companyId } = body; updateJobProgress(jobId, 10, 'Analyzing business profile & brand strategy...'); const promptInputs: WatermarkPromptInputs = { companyId, refineFeedback: kind === 'refine' ? body.refineFeedback : undefined, regenerateFeedback: kind === 'regenerate' ? body.regenerateFeedback : undefined, previousPrompt: kind !== 'generate' ? body.previousPrompt : undefined, previousConceptSummary: kind !== 'generate' ? body.previousConceptSummary : undefined, style: body.style || 'Minimalist', aspectRatio: body.aspectRatio || '1:1', // User configuration description: body.description, requirements: body.requirements, stylePreferences: body.stylePreferences, additionalNotes: body.additionalNotes, }; const { systemPrompt: _systemPrompt, userPrompt, conceptSummary } = await buildWatermarkPrompt(promptInputs); updateJobProgress(jobId, 40, 'Analyzing competitor landscape & composing watermark prompt...'); const generation = new ImageGeneration({ companyId, name: 'Watermark', description: 'Brand watermark (guided flow)', style: promptInputs.style || 'Minimalist', platform: 'Brand', aspectRatio: promptInputs.aspectRatio || '1:1', originalPrompt: truncateForStorage(userPrompt, 3000), status: 'generating', createdBy: req.user?.id, }); await generation.save(); // ── Reference chain: distil the watermark from the approved primary logo ── // When a primary logo is available, send it as the reference image to // /images/edits so the watermark stays visually tied to the brand mark. If the // edit call fails (or no reference is available), fall back to from-scratch // generation, then to Zhipu CogView — the watermark is still produced. let referenceImage: { buffer: Buffer; mimeType: string } | null = null; if (body.primaryLogoAssetId) { try { const primaryAsset = await (BrandAsset as any).findOne({ _id: body.primaryLogoAssetId, companyId }); if (primaryAsset) { referenceImage = await readPrimaryLogoImage(primaryAsset); } } catch (e) { console.warn('[Watermark] Could not load primary logo reference:', (e as Error).message); } } const referenceNote = referenceImage ? 'The attached image is the brand\'s approved PRIMARY logo (reference image). Distil its core mark or ' + 'monogram into the watermark — preserve the mark\'s silhouette and visual identity; do not redesign it.\n\n' : ''; const generationPrompt = referenceNote + userPrompt; updateJobProgress(jobId, 55, referenceImage ? 'Generating watermark from your primary logo…' : 'Generating watermark...'); const size = '1024x1024'; const WATERMARK_MODEL = 'gpt-image-2'; const userId = req.user?._id?.toString(); let imageResult; let provider: string; let model: string; try { if (referenceImage) { // Image-to-image from the primary logo — keeps the watermark on-brand. imageResult = await generateBrandImageEditWithOpenAI( generationPrompt, referenceImage.buffer, referenceImage.mimeType, 'Watermark', userId ); } else { imageResult = await generateBrandImageWithOpenAI(generationPrompt, 'Watermark', userId); } provider = imageResult.provider; model = imageResult.model; } catch (primaryErr) { // If the reference-image edit failed, retry from-scratch before giving up. if (referenceImage) { console.warn('[Watermark] Reference-image edit failed, retrying from-scratch:', (primaryErr as Error).message); updateJobProgress(jobId, 70, 'Reference edit failed; generating from-scratch…'); } else { console.warn(`[Watermark] ${WATERMARK_MODEL} unavailable, trying Zhipu CogView fallback:`, (primaryErr as Error).message); updateJobProgress(jobId, 70, 'Primary provider unavailable; trying fallback...'); } try { imageResult = await generateBrandImageWithOpenAI(userPrompt, 'Watermark', userId); provider = imageResult.provider; model = imageResult.model; } catch (openAiErr) { try { imageResult = await withTimeout( generateImageWithZhipuCogView(userPrompt, size), PROVIDER_TIMEOUT_MS, 'Watermark generation (fallback)' ); provider = imageResult.provider; model = imageResult.model; } catch (fallbackErr) { generation.status = 'failed'; await generation.save().catch(() => {}); throw new Error( `Watermark generation failed: ${(fallbackErr as Error).message || (openAiErr as Error).message || (primaryErr as Error).message || 'all image providers failed'}` ); } } } for (const v of generation.versions) v.isCurrent = false; const versionNumber = generation.versions.length + 1; generation.versions.push({ version: versionNumber, prompt: generation.originalPrompt, enhancedPrompt: stripReasoning(userPrompt), imageUrl: '', base64Data: imageResult.base64Data, generationProvider: provider, generationModel: model, aspectRatio: generation.aspectRatio, size, quality: 'standard', style: 'vivid', revisedPrompt: imageResult.revisedPrompt, tokenUsage: imageResult.tokenUsage || { inputTokens: 0, outputTokens: 0, totalTokens: 0 }, latencyMs: imageResult.latencyMs || 0, isCurrent: true, } as any); generation.currentVersion = versionNumber; generation.totalVersions = versionNumber; generation.generationProvider = provider; generation.generationModel = model; if (!generation.ollamaEnhancedPrompt) { generation.ollamaEnhancedPrompt = truncateForStorage(stripReasoning(userPrompt), 15000); } generation.status = 'completed'; await generation.save(); updateJobProgress(jobId, 90, 'Finalizing...'); completeJob( jobId, { imageGenerationId: String(generation._id), brandAssetId: null, // not saved as a BrandAsset until "Use this watermark" prompt: userPrompt, conceptSummary, model, provider, versionNumber, }, kind === 'regenerate' ? 'regenerated' : kind === 'refine' ? 'refined' : 'generated' ); } router.post( '/watermark/generate', requirePermission('brand-assets', 'ai-generate'), generateValidations, async (req: Request, res: Response) => { const companyId = validateCompany(req, res); if (!companyId) return; const job = createJob('brand-assets-watermark', companyId, 'brand-assets-watermark'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runWatermarkGeneration(job.jobId, req, req.body, 'generate'); } catch (err) { console.error('[Watermark] generate failed:', err); failJob(job.jobId, (err as Error).message || 'Watermark generation failed'); } }); } ); router.post( '/watermark/regenerate', requirePermission('brand-assets', 'ai-generate'), [ ...generateValidations, body('regenerateFeedback').trim().notEmpty().withMessage('Regenerate feedback is required'), ], async (req: Request, res: Response) => { const companyId = validateCompany(req, res); if (!companyId) return; const job = createJob('brand-assets-watermark', companyId, 'brand-assets-watermark'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runWatermarkGeneration(job.jobId, req, req.body, 'regenerate'); } catch (err) { console.error('[Watermark] regenerate failed:', err); failJob(job.jobId, (err as Error).message || 'Watermark regeneration failed'); } }); } ); router.post( '/watermark/refine', requirePermission('brand-assets', 'ai-generate'), [ ...generateValidations, body('refineFeedback').trim().notEmpty().withMessage('Refine feedback is required'), ], async (req: Request, res: Response) => { const companyId = validateCompany(req, res); if (!companyId) return; const job = createJob('brand-assets-watermark', companyId, 'brand-assets-watermark'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runWatermarkGeneration(job.jobId, req, req.body, 'refine'); } catch (err) { console.error('[Watermark] refine failed:', err); failJob(job.jobId, (err as Error).message || 'Watermark refinement failed'); } }); } ); // ============================================ // BACKDROP — branded backdrop with single or multiple logo composition // ============================================ // Multer for handling multiple logo file uploads in backdrop generation const backdropLogoUpload = multer({ storage: multer.memoryStorage(), limits: { fileSize: 10 * 1024 * 1024 }, // 10MB per file fileFilter: (_req: any, file: Express.Multer.File, cb: multer.FileFilterCallback) => { const allowedMimeTypes = ['image/jpeg', 'image/png', 'image/gif', 'image/webp', 'image/svg+xml']; if (allowedMimeTypes.includes(file.mimetype)) { cb(null, true); } else { cb(new Error('Invalid file format. Supported: JPG, PNG, GIF, WebP, SVG')); } }, }); /** * Run backdrop generation — single-logo (image-to-image from primary logo) or * multiple-logos (compositing uploaded logos). The prompt builder handles both * modes; the only difference is how the reference image(s) reach the provider. */ async function runBackdropGeneration( jobId: string, req: Request, body: { companyId: string; mode: 'single-logo' | 'multiple-logos'; /** Approved primary logo to use as reference (single-logo mode). */ primaryLogoAssetId?: string; /** Uploaded logo files (multiple-logos mode) — set by the route handler from multer. */ logoFiles?: Express.Multer.File[]; refineFeedback?: string; regenerateFeedback?: string; previousPrompt?: string; previousConceptSummary?: string; style?: string; aspectRatio?: string; // User configuration description?: string; requirements?: string; stylePreferences?: string[]; additionalNotes?: string; }, kind: 'generate' | 'regenerate' | 'refine' ): Promise { const { ImageGeneration, BrandAsset } = getModels(); const { companyId } = body; updateJobProgress(jobId, 10, 'Analyzing business profile & brand strategy...'); const promptInputs: BackdropPromptInputs = { companyId, mode: body.mode || 'single-logo', refineFeedback: kind === 'refine' ? body.refineFeedback : undefined, regenerateFeedback: kind === 'regenerate' ? body.regenerateFeedback : undefined, previousPrompt: kind !== 'generate' ? body.previousPrompt : undefined, previousConceptSummary: kind !== 'generate' ? body.previousConceptSummary : undefined, style: body.style || 'Abstract', aspectRatio: body.aspectRatio || '16:9', // User configuration description: body.description, requirements: body.requirements, stylePreferences: body.stylePreferences, additionalNotes: body.additionalNotes, }; const { systemPrompt: _systemPrompt, userPrompt, conceptSummary } = await buildBackdropPrompt(promptInputs); updateJobProgress(jobId, 40, 'Analyzing competitor landscape & composing backdrop prompt...'); const generation = new ImageGeneration({ companyId, name: 'Backdrop', description: body.mode === 'multiple-logos' ? 'Branded backdrop (multiple logos)' : 'Branded backdrop (single logo)', style: promptInputs.style || 'Abstract', platform: 'Brand', aspectRatio: promptInputs.aspectRatio || '16:9', originalPrompt: truncateForStorage(userPrompt, 3000), status: 'generating', createdBy: req.user?.id, }); await generation.save(); // ── Reference images ── // Single-logo mode: distil the backdrop from the approved primary logo. // Multiple-logos mode: compose uploaded logos into the backdrop. let referenceImage: { buffer: Buffer; mimeType: string } | null = null; if (body.mode === 'multiple-logos' && body.logoFiles && body.logoFiles.length > 0) { // Multiple-logos mode: use the first uploaded file as the primary reference // (OpenAI /images/edits accepts a single image, so we use the first file). // Future enhancement could composite all files into a reference collage. try { const firstFile = body.logoFiles[0]; referenceImage = { buffer: firstFile.buffer, mimeType: firstFile.mimetype, }; console.log(`[Backdrop] Using uploaded file "${firstFile.originalname}" as reference (${body.logoFiles.length} total files uploaded)`); } catch (e) { console.warn('[Backdrop] Could not read uploaded logo file:', (e as Error).message); } } else if (body.primaryLogoAssetId) { try { const primaryAsset = await (BrandAsset as any).findOne({ _id: body.primaryLogoAssetId, companyId }); if (primaryAsset) { referenceImage = await readPrimaryLogoImage(primaryAsset); } } catch (e) { console.warn('[Backdrop] Could not load primary logo reference:', (e as Error).message); } } const modeNote = body.mode === 'multiple-logos' ? 'The attached image is one of multiple brand logos that need to be composed together in a branded backdrop. Arrange all logos in a balanced, harmonious layout on a branded background. Each logo should remain recognisable but work together as a cohesive visual.\n\n' : referenceImage ? 'The attached image is the brand\'s approved PRIMARY logo. Create a BACKDROP that features or is inspired by this logo. The logo should be the central visual element, arranged in a visually compelling way on a branded background. Preserve the logo\'s identity — do not redesign it.\n\n' : ''; const generationPrompt = modeNote + userPrompt; updateJobProgress(jobId, 55, referenceImage ? 'Generating backdrop from reference logo…' : 'Generating backdrop...'); const size = '1792x1024'; // 16:9 aspect ratio for backdrop const userId = req.user?._id?.toString(); let imageResult; let provider: string; let model: string; try { if (referenceImage) { imageResult = await generateBrandImageEditWithOpenAI( generationPrompt, referenceImage.buffer, referenceImage.mimeType, 'Backdrop', userId ); } else { imageResult = await generateBrandImageWithOpenAI(generationPrompt, 'Backdrop', userId); } provider = imageResult.provider; model = imageResult.model; } catch (primaryErr) { if (referenceImage) { console.warn('[Backdrop] Reference-image edit failed, retrying from-scratch:', (primaryErr as Error).message); updateJobProgress(jobId, 70, 'Reference edit failed; generating from-scratch…'); } else { console.warn('[Backdrop] Primary provider unavailable, trying fallback:', (primaryErr as Error).message); updateJobProgress(jobId, 70, 'Primary provider unavailable; trying fallback...'); } try { imageResult = await generateBrandImageWithOpenAI(userPrompt, 'Backdrop', userId); provider = imageResult.provider; model = imageResult.model; } catch (openAiErr) { try { imageResult = await withTimeout( generateImageWithZhipuCogView(userPrompt, size), PROVIDER_TIMEOUT_MS, 'Backdrop generation (fallback)' ); provider = imageResult.provider; model = imageResult.model; } catch (fallbackErr) { generation.status = 'failed'; await generation.save().catch(() => {}); throw new Error( `Backdrop generation failed: ${(fallbackErr as Error).message || (openAiErr as Error).message || (primaryErr as Error).message || 'all image providers failed'}` ); } } } for (const v of generation.versions) v.isCurrent = false; const versionNumber = generation.versions.length + 1; generation.versions.push({ version: versionNumber, prompt: generation.originalPrompt, enhancedPrompt: stripReasoning(userPrompt), imageUrl: '', base64Data: imageResult.base64Data, generationProvider: provider, generationModel: model, aspectRatio: generation.aspectRatio, size, quality: 'standard', style: 'vivid', revisedPrompt: imageResult.revisedPrompt, tokenUsage: imageResult.tokenUsage || { inputTokens: 0, outputTokens: 0, totalTokens: 0 }, latencyMs: imageResult.latencyMs || 0, isCurrent: true, } as any); generation.currentVersion = versionNumber; generation.totalVersions = versionNumber; generation.generationProvider = provider; generation.generationModel = model; if (!generation.ollamaEnhancedPrompt) { generation.ollamaEnhancedPrompt = truncateForStorage(stripReasoning(userPrompt), 15000); } generation.status = 'completed'; await generation.save(); updateJobProgress(jobId, 90, 'Finalizing...'); completeJob( jobId, { imageGenerationId: String(generation._id), brandAssetId: null, prompt: userPrompt, conceptSummary, model, provider, versionNumber, }, kind === 'regenerate' ? 'regenerated' : kind === 'refine' ? 'refined' : 'generated' ); } // ── Backdrop endpoints ── // POST /backdrop/generate — multipart for multiple-logos, JSON for single-logo router.post( '/backdrop/generate', requirePermission('brand-assets', 'ai-generate'), backdropLogoUpload.array('logoFiles', 5), (req: Request, res: Response, next: Function) => { // If multipart, multer parsed the fields; if JSON, they're already in req.body. // Normalise the mode field from the parsed multipart fields. next(); }, async (req: Request, res: Response) => { const companyId = req.body.companyId; if (!companyId) { res.status(400).json({ error: 'Company ID is required' }); return; } if (!authorizeCompany(req, companyId)) { res.status(403).json({ error: 'Not authorised for this company' }); return; } // Parse stylePreferences if sent as a JSON string (multipartFormData) let stylePreferences: string[] = []; if (req.body.stylePreferences) { if (typeof req.body.stylePreferences === 'string') { try { stylePreferences = JSON.parse(req.body.stylePreferences); } catch { stylePreferences = []; } } else if (Array.isArray(req.body.stylePreferences)) { stylePreferences = req.body.stylePreferences; } } // Attach multer files to body for the handler const body = { ...req.body, companyId, mode: (req.body.mode || 'single-logo') as 'single-logo' | 'multiple-logos', stylePreferences, logoFiles: ((req as any).files || []) as Express.Multer.File[], }; const job = createJob('brand-assets-backdrop', companyId, 'brand-assets-backdrop'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runBackdropGeneration(job.jobId, req, body, 'generate'); } catch (err) { console.error('[Backdrop] generate failed:', err); failJob(job.jobId, (err as Error).message || 'Backdrop generation failed'); } }); } ); router.post( '/backdrop/regenerate', requirePermission('brand-assets', 'ai-generate'), [ ...generateValidations, body('regenerateFeedback').trim().notEmpty().withMessage('Regenerate feedback is required'), ], async (req: Request, res: Response) => { const companyId = validateCompany(req, res); if (!companyId) return; const job = createJob('brand-assets-backdrop', companyId, 'brand-assets-backdrop'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runBackdropGeneration(job.jobId, req, req.body, 'regenerate'); } catch (err) { console.error('[Backdrop] regenerate failed:', err); failJob(job.jobId, (err as Error).message || 'Backdrop regeneration failed'); } }); } ); router.post( '/backdrop/refine', requirePermission('brand-assets', 'ai-generate'), [ ...generateValidations, body('refineFeedback').trim().notEmpty().withMessage('Refine feedback is required'), ], async (req: Request, res: Response) => { const companyId = validateCompany(req, res); if (!companyId) return; const job = createJob('brand-assets-backdrop', companyId, 'brand-assets-backdrop'); res.status(202).json({ jobId: job.jobId, status: 'processing' }); setImmediate(async () => { try { await runBackdropGeneration(job.jobId, req, req.body, 'refine'); } catch (err) { console.error('[Backdrop] refine failed:', err); failJob(job.jobId, (err as Error).message || 'Backdrop refinement failed'); } }); } ); export default router;