{"workflow":{"id":12175,"name":"Generate photo-based construction cost estimates with GPT-4 Vision and DDC CWICR","views":75,"recentViews":0,"totalViews":75,"createdAt":"2025-12-26T12:50:21.978Z","description":"\nUpload a **construction photo** via web form โ†’ get a detailed **cost estimate** with work breakdown, resource costs, and professional HTML report. Powered by **GPT-4 Vision** and the open-source **DDC CWICR** database (55,000+ work items).\n\n## Who's it for\n\n- **Site managers** who need quick estimates from mobile photos\n- **Renovation contractors** evaluating project scope from initial site visit\n- **Real estate inspectors** estimating repair costs\n- **Construction consultants** providing rapid ballpark figures\n- **DIY enthusiasts** planning home improvement budgets\n\n## What it does\n\n1. **Collects** photo + region/language via n8n Form\n2. **Analyzes** photo with GPT-4 Vision (room type, elements, dimensions)\n3. **Decomposes** visible elements into construction work items\n4. **Searches** DDC CWICR vector database for matching rates\n5. **Generates** professional HTML report with cost breakdown\n\n**Supports 9 regions:** ๐Ÿ‡ฉ๐Ÿ‡ช Berlin ยท ๐Ÿ‡ฌ๐Ÿ‡ง Toronto ยท ๐Ÿ‡ท๐Ÿ‡บ St. Petersburg ยท ๐Ÿ‡ช๐Ÿ‡ธ Barcelona ยท ๐Ÿ‡ซ๐Ÿ‡ท Paris ยท ๐Ÿ‡ง๐Ÿ‡ท Sรฃo Paulo ยท ๐Ÿ‡จ๐Ÿ‡ณ Shanghai ยท ๐Ÿ‡ฆ๐Ÿ‡ช Dubai ยท ๐Ÿ‡ฎ๐Ÿ‡ณ Mumbai\n\n## How it works\n\n```\nโ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”\nโ”‚ Web Form โ”‚ โ†’ โ”‚ STAGE 1 โ”‚ โ†’ โ”‚ STAGE 4 โ”‚ โ†’ โ”‚ Loop Works โ”‚\nโ”‚ Photo+Lang โ”‚ โ”‚ GPT-4 Vision โ”‚ โ”‚ Decompose โ”‚ โ”‚ per item โ”‚\nโ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜\n โ†“ โ†“ โ†“\n โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”\n โ”‚ Identify room, elements, fixtures, dimensions โ”‚\n โ”‚ โ†’ Break down into 15-40 construction work items โ”‚\n โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜\n โ†“\nโ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”\nโ”‚ HTML Report โ”‚ โ† โ”‚ STAGE 7.5 โ”‚ โ† โ”‚ STAGE 5 โ”‚ โ† โ”‚ Qdrant โ”‚\nโ”‚ Response โ”‚ โ”‚ Aggregate โ”‚ โ”‚ Parse+Score โ”‚ โ”‚ Vector DB โ”‚\nโ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜\n```\n\n**Pipeline stages:**\n\n| Stage | Node | Description |\n|-------|------|-------------|\n| 1 | GPT-4 Vision | Analyzes photo: room type, elements, materials, dimensions |\n| 4 | GPT-4 Decompose | Breaks elements into work items with quantities |\n| 5 | Vector Search + Score | Finds matching rates in DDC CWICR, quality scoring |\n| 7.5 | Aggregate & Validate | Sums costs, groups by phase, validates results |\n| 9 | HTML Report | Generates professional estimate document |\n\n## Prerequisites\n\n| Component | Requirement |\n|-----------|-------------|\n| **n8n** | v1.30+ with Form Trigger support |\n| **OpenAI API** | GPT-4 Vision + Embeddings access |\n| **Qdrant** | Vector DB with DDC CWICR collections |\n| **DDC CWICR Data** | [github.com/datadrivenconstruction/DDC-CWICR](https://github.com/datadrivenconstruction/OpenConstructionEstimate-DDC-CWICR) |\n\n## Setup\n\n### 1. n8n Credentials (Settings โ†’ Credentials)\n- **OpenAI API** โ€” required (GPT-4 Vision + text-embedding-3-large)\n- **Qdrant API** โ€” your Qdrant instance connection\n\n### 2. Qdrant Collections\nLoad DDC CWICR embeddings for your target regions:\n```\nDE_BERLIN_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR\nENG_TORONTO_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR\nRU_STPETERSBURG_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR\nES_BARCELONA_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR\nFR_PARIS_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR\nPT_SAOPAULO_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR\nZH_SHANGHAI_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR\nAR_DUBAI_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR\nHI_MUMBAI_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR\n```\n\n### 3. Activate Workflow\n1. Import JSON into n8n\n2. Link OpenAI + Qdrant credentials to respective nodes\n3. Activate workflow\n4. Access form at: `https://your-n8n/form/photo-estimate-pro-v3`\n\n## Features\n\n| Feature | Description |\n|---------|-------------|\n| ๐Ÿ“ธ **Photo Analysis** | GPT-4 Vision identifies room type, elements, fixtures |\n| ๐Ÿ“ **Dimension Estimation** | Uses reference objects (doors, tiles) for sizing |\n| ๐Ÿ”ง **Work Decomposition** | Breaks down to 15-40 specific work items |\n| ๐ŸŽฏ **Quality Scoring** | Rates match quality (high/medium/low/not_found) |\n| ๐Ÿ“Š **Phase Grouping** | PREPARATION โ†’ MAIN โ†’ FINISHING โ†’ MEP |\n| ๐Ÿ’ฐ **Cost Breakdown** | Labor, materials, machines per item |\n| โœ… **Validation** | Warns if <50% rates found or missing demolition |\n| ๐ŸŒ **9 Languages** | Full localization + regional pricing |\n\n## Form Fields\n\n| Field | Type | Options |\n|-------|------|---------|\n| ๐Ÿ“ท Upload Photo | File | .jpg, .png, .webp |\n| ๐ŸŒ Region & Language | Dropdown | 9 regions with currencies |\n| ๐Ÿ—๏ธ Work Type | Dropdown | New / Renovation / Repair / Auto |\n| ๐Ÿ“ Description | Textarea | Optional context |\n\n## Example Output\n\n**Input:** Bathroom photo (renovation) \n**Region:** ๐Ÿ‡ฉ๐Ÿ‡ช German - Berlin (EUR โ‚ฌ)\n\n**Generated Work Items:**\n```\nPREPARATION (3 items)\nโ”œโ”€โ”€ Demolition of wall tiles โ€” 12 mยฒ โ€” โ‚ฌ180\nโ”œโ”€โ”€ Demolition of floor tiles โ€” 4.5 mยฒ โ€” โ‚ฌ95\nโ””โ”€โ”€ Disposal of construction waste โ€” 0.8 mยณ โ€” โ‚ฌ120\n\nMAIN (8 items)\nโ”œโ”€โ”€ Floor waterproofing โ€” 4.5 mยฒ โ€” โ‚ฌ225\nโ”œโ”€โ”€ Wall waterproofing wet zone โ€” 8 mยฒ โ€” โ‚ฌ280\nโ”œโ”€โ”€ Floor screed โ€” 4.5 mยฒ โ€” โ‚ฌ135\nโ”œโ”€โ”€ Wall tiling โ€” 22 mยฒ โ€” โ‚ฌ880\nโ”œโ”€โ”€ Floor tiling โ€” 4.5 mยฒ โ€” โ‚ฌ225\nโ”œโ”€โ”€ Toilet installation โ€” 1 pcs โ€” โ‚ฌ320\nโ”œโ”€โ”€ Sink installation โ€” 1 pcs โ€” โ‚ฌ185\nโ””โ”€โ”€ Shower cabin installation โ€” 1 pcs โ€” โ‚ฌ450\n\nFINISHING (3 items)\nโ”œโ”€โ”€ Ceiling painting โ€” 4.5 mยฒ โ€” โ‚ฌ68\nโ”œโ”€โ”€ Grouting โ€” 26.5 mยฒ โ€” โ‚ฌ133\nโ””โ”€โ”€ Silicone sealing โ€” 8 m โ€” โ‚ฌ48\n\nMEP (4 items)\nโ”œโ”€โ”€ Socket installation โ€” 2 pcs โ€” โ‚ฌ90\nโ”œโ”€โ”€ Light point installation โ€” 2 pcs โ€” โ‚ฌ120\nโ”œโ”€โ”€ Mixer/faucet installation โ€” 2 pcs โ€” โ‚ฌ160\nโ””โ”€โ”€ Ventilation installation โ€” 1 pcs โ€” โ‚ฌ85\n\nโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€\nTOTAL: โ‚ฌ3,799.00\nLabor: โ‚ฌ1,520 ยท Materials: โ‚ฌ1,900 ยท Machines: โ‚ฌ379\nQuality: 78% high match ยท 18 work items\n```\n\n## Quality Scoring System\n\n| Score | Level | Meaning |\n|-------|-------|---------|\n| 60-100 | ๐ŸŸข High | Exact match with resources |\n| 40-59 | ๐ŸŸก Medium | Good match, minor differences |\n| 20-39 | ๐ŸŸ  Low | Partial match, review needed |\n| 0-19 | ๐Ÿ”ด Not Found | No suitable rate found |\n\n**Scoring factors:**\n- Has price in database (+30)\n- Has resources breakdown (+25)\n- Unit matches expected (+20)\n- Material keywords match (+15)\n- Work type keywords match (+10)\n- Vector similarity >0.5 (+10)\n\n## Notes & Tips\n\n- **Best photo angles:** Capture full room, include reference objects (doors, sockets)\n- **Renovation mode:** AI automatically adds demolition works\n- **Validation warnings:** Check if <50% rates found โ€” may need manual additions\n- **Rate accuracy:** Depends on DDC CWICR coverage for your region\n- **Extend:** Chain with PDF generation, email delivery, or CRM integration\n\n## Categories\n\n`AI` ยท `Data Extraction` ยท `Document Ops` ยท `Files & Storage`\n\n## Tags\n\n`photo-analysis`, `gpt-4-vision`, `construction`, `cost-estimation`, `qdrant`, `vector-search`, `form-trigger`, `html-report`, `multilingual`\n\n---\n\n## Author\n\n**DataDrivenConstruction.io** \n[https://DataDrivenConstruction.io](https://DataDrivenConstruction.io) \n[info@datadrivenconstruction.io](mailto:info@datadrivenconstruction.io)\n\n## Consulting & Training\n\nWe help construction, engineering, and technology firms implement:\n- AI-powered visual estimation systems\n- CAD/BIM data processing pipelines\n- Vector database integration for construction data\n- Multilingual cost database solutions\n\n**Contact us** to test with your data or adapt to your project requirements.\n\n## Resources\n\n- **DDC CWICR Database:** [GitHub](https://github.com/datadrivenconstruction/OpenConstructionEstimate-DDC-CWICR)\n- **Qdrant Documentation:** [qdrant.tech/documentation](https://qdrant.tech/documentation/)\n- **n8n Form Trigger:** [docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.formtrigger](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.formtrigger/)\n\n---\n\nโญ **Star us on GitHub!** [github.com/datadrivenconstruction/DDC-CWICR](https://github.com/datadrivenconstruction/OpenConstructionEstimate-DDC-CWICR)","workflow":{"id":"OvYK6agG8RmwF6Gq","meta":{"instanceId":"faa70e11b7175129a74fd834d3451fdc1862589b16d68ded03f91ca7b1ecca12"},"name":"Photo Cost Estimate Pro v2.0","tags":[],"nodes":[{"id":"0f4cbe14-7ba4-46c5-81d2-6b1d4482efcc","name":"Photo Upload Form","type":"n8n-nodes-base.formTrigger","position":[29104,400],"webhookId":"photo-estimate-pro-v3","parameters":{"options":{},"formTitle":"๐Ÿ“ธ Photo Cost Estimate Pro v2","formFields":{"values":[{"fieldType":"file","fieldLabel":"๐Ÿ“ท Upload Photo","multipleFiles":false,"requiredField":true,"acceptFileTypes":".jpg,.jpeg,.png,.webp"},{"fieldType":"dropdown","fieldLabel":"๐ŸŒ Region & Language","fieldOptions":{"values":[{"option":"๐Ÿ‡ฉ๐Ÿ‡ช German - Berlin (EUR โ‚ฌ)"},{"option":"๐Ÿ‡ฌ๐Ÿ‡ง English - Toronto (CAD $)"},{"option":"๐Ÿ‡ท๐Ÿ‡บ Russian - St. Petersburg (RUB โ‚ฝ)"},{"option":"๐Ÿ‡ช๐Ÿ‡ธ Spanish - Barcelona (EUR โ‚ฌ)"},{"option":"๐Ÿ‡ซ๐Ÿ‡ท French - Paris (EUR โ‚ฌ)"},{"option":"๐Ÿ‡ง๐Ÿ‡ท Portuguese - Sรฃo Paulo (BRL R$)"},{"option":"๐Ÿ‡จ๐Ÿ‡ณ Chinese - Shanghai (CNY ยฅ)"},{"option":"๐Ÿ‡ฆ๐Ÿ‡ช Arabic - Dubai (AED ุฏ.ุฅ)"},{"option":"๐Ÿ‡ฎ๐Ÿ‡ณ Hindi - Mumbai (INR โ‚น)"}]},"requiredField":true},{"fieldType":"dropdown","fieldLabel":"๐Ÿ—๏ธ Work Type","fieldOptions":{"values":[{"option":"๐Ÿ”จ New Construction"},{"option":"๐Ÿ”„ Renovation / Remodel"},{"option":"๐Ÿ”ง Repair"},{"option":"โ“ Auto-detect"}]},"requiredField":true},{"fieldType":"textarea","fieldLabel":"๐Ÿ“ Description (optional)","placeholder":"Describe what's in the photo, specify dimensions, or add context..."}]},"responseMode":"lastNode","formDescription":"Upload a construction photo for automatic cost estimation.\nIMPROVED: Multi-stage AI decomposition for accurate work identification.\nPrices based on DDC CWICR regional databases (9 languages)."},"typeVersion":2.2},{"id":"fae54f1a-9225-48c1-a755-83dca9f15033","name":"Extract Input","type":"n8n-nodes-base.code","position":[29328,400],"parameters":{"jsCode":"// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// EXTRACT INPUT FROM FORM - 9 LANGUAGES + WORK TYPE\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n\nconst input = $input.first();\nconst formData = input.json || {};\n\nconst regionField = formData['๐ŸŒ Region & Language'] || formData['Region & Language'] || '';\nconst workTypeField = formData['๐Ÿ—๏ธ Work Type'] || formData['Work Type'] || 'Auto-detect';\n\n// 9 languages mapping\nconst langMap = {\n 'German': 'DE',\n 'English': 'EN',\n 'Russian': 'RU',\n 'Spanish': 'ES',\n 'French': 'FR',\n 'Portuguese': 'PT',\n 'Chinese': 'ZH',\n 'Arabic': 'AR',\n 'Hindi': 'HI'\n};\n\nlet languageCode = 'EN';\nfor (const [lang, code] of Object.entries(langMap)) {\n if (regionField.includes(lang)) {\n languageCode = code;\n break;\n }\n}\n\n// Work type detection\nlet workType = 'auto';\nif (workTypeField.includes('New')) workType = 'new_construction';\nelse if (workTypeField.includes('Renovation')) workType = 'renovation';\nelse if (workTypeField.includes('Repair')) workType = 'repair';\n\nconst userDescription = formData['๐Ÿ“ Description (optional)'] || formData['Description (optional)'] || '';\n\nlet photoBase64 = '';\nlet photoMimeType = 'image/jpeg';\n\nif (input.binary) {\n for (const key of Object.keys(input.binary)) {\n const bin = input.binary[key];\n if (bin.mimeType && bin.mimeType.startsWith('image/')) {\n photoBase64 = bin.data;\n photoMimeType = bin.mimeType;\n break;\n }\n }\n}\n\nreturn {\n json: {\n language_code: languageCode,\n photo_base64: photoBase64,\n photo_mime_type: photoMimeType,\n has_photo: photoBase64.length > 100,\n user_description: userDescription,\n selected_region: regionField,\n work_type: workType\n }\n};"},"typeVersion":2},{"id":"d5b99499-be6d-4da7-a381-94cdf5e9f7d4","name":"Configure Language","type":"n8n-nodes-base.code","position":[29552,400],"parameters":{"jsCode":"// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// LANGUAGE & VECTOR DB CONFIGURATION - 9 LANGUAGES\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n\nconst input = $input.first().json;\nconst languageCode = (input.language_code || 'EN').toUpperCase();\n\nconst languageConfig = {\n 'DE': {\n city: 'Berlin',\n vectorDb: 'DE_BERLIN_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR',\n language: 'German',\n languageNative: 'Deutsch',\n currency: 'EUR',\n currencySymbol: 'โ‚ฌ',\n locale: 'de-DE',\n systemPromptLang: 'Antworte auf Deutsch.',\n searchLang: 'German'\n },\n 'EN': {\n city: 'Toronto',\n vectorDb: 'ENG_TORONTO_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR',\n language: 'English',\n languageNative: 'English',\n currency: 'CAD',\n currencySymbol: '$',\n locale: 'en-CA',\n systemPromptLang: 'Respond in English.',\n searchLang: 'English'\n },\n 'RU': {\n city: 'St. Petersburg',\n vectorDb: 'RU_STPETERSBURG_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR',\n language: 'Russian',\n languageNative: 'ะ ัƒััะบะธะน',\n currency: 'RUB',\n currencySymbol: 'โ‚ฝ',\n locale: 'ru-RU',\n systemPromptLang: 'ะžั‚ะฒะตั‡ะฐะน ะฝะฐ ั€ัƒััะบะพะผ ัะทั‹ะบะต.',\n searchLang: 'Russian'\n },\n 'FR': {\n city: 'Paris',\n vectorDb: 'FR_PARIS_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR',\n language: 'French',\n languageNative: 'Franรงais',\n currency: 'EUR',\n currencySymbol: 'โ‚ฌ',\n locale: 'fr-FR',\n systemPromptLang: 'Rรฉpondez en franรงais.',\n searchLang: 'French'\n },\n 'ES': {\n city: 'Barcelona',\n vectorDb: 'ES_BARCELONA_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR',\n language: 'Spanish',\n languageNative: 'Espaรฑol',\n currency: 'EUR',\n currencySymbol: 'โ‚ฌ',\n locale: 'es-ES',\n systemPromptLang: 'Responde en espaรฑol.',\n searchLang: 'Spanish'\n },\n 'PT': {\n city: 'Sรฃo Paulo',\n vectorDb: 'PT_SAOPAULO_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR',\n language: 'Portuguese',\n languageNative: 'Portuguรชs',\n currency: 'BRL',\n currencySymbol: 'R$',\n locale: 'pt-BR',\n systemPromptLang: 'Responda em portuguรชs.',\n searchLang: 'Portuguese'\n },\n 'ZH': {\n city: 'Shanghai',\n vectorDb: 'ZH_SHANGHAI_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR',\n language: 'Chinese',\n languageNative: 'ไธญๆ–‡',\n currency: 'CNY',\n currencySymbol: 'ยฅ',\n locale: 'zh-CN',\n systemPromptLang: '่ฏท็”จไธญๆ–‡ๅ›ž็ญ”ใ€‚',\n searchLang: 'Chinese'\n },\n 'AR': {\n city: 'Dubai',\n vectorDb: 'AR_DUBAI_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR',\n language: 'Arabic',\n languageNative: 'ุงู„ุนุฑุจูŠุฉ',\n currency: 'AED',\n currencySymbol: 'ุฏ.ุฅ',\n locale: 'ar-AE',\n systemPromptLang: 'ุฃุฌุจ ุจุงู„ู„ุบุฉ ุงู„ุนุฑุจูŠุฉ.',\n searchLang: 'Arabic'\n },\n 'HI': {\n city: 'Mumbai',\n vectorDb: 'HI_MUMBAI_workitems_costs_resources_EMBEDDINGS_3072_DDC_CWICR',\n language: 'Hindi',\n languageNative: 'เคนเคฟเคจเฅเคฆเฅ€',\n currency: 'INR',\n currencySymbol: 'โ‚น',\n locale: 'hi-IN',\n systemPromptLang: 'เคนเคฟเค‚เคฆเฅ€ เคฎเฅ‡เค‚ เคœเคตเคพเคฌ เคฆเฅ‡เค‚เฅค',\n searchLang: 'Hindi'\n }\n};\n\nconst config = languageConfig[languageCode] || languageConfig['EN'];\n\nreturn {\n json: {\n ...input,\n language_code: languageCode,\n language_config: config,\n qdrant_collection: config.vectorDb,\n city: config.city,\n language: config.language,\n language_native: config.languageNative,\n currency: config.currency,\n currency_symbol: config.currencySymbol,\n locale: config.locale,\n system_prompt_lang: config.systemPromptLang,\n search_lang: config.searchLang,\n pricing_level: config.city\n }\n};"},"typeVersion":2},{"id":"2ad831a9-2893-4a0c-992e-337eb4a4bc36","name":"Has Photo?","type":"n8n-nodes-base.if","position":[29776,400],"parameters":{"options":{},"conditions":{"options":{"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"operator":{"type":"boolean","operation":"equals"},"leftValue":"={{ $json.has_photo }}","rightValue":true}]}},"typeVersion":2},{"id":"97d8463c-6e3b-4b16-b44f-6147d7b17f91","name":"Error No Photo","type":"n8n-nodes-base.code","position":[29984,560],"parameters":{"jsCode":"return {\n json: {\n success: false,\n error: true,\n message: 'โŒ No photo provided',\n html_content: '

โŒ Error

No photo was uploaded. Please go back and upload a construction photo.

'\n }\n};"},"typeVersion":2},{"id":"b9545c52-79e0-447f-bb2c-fe81fc38a6bf","name":"STAGE 1 Vision Prompt","type":"n8n-nodes-base.set","position":[29984,384],"parameters":{"options":{},"assignments":{"assignments":[{"id":"prompt","name":"chatInput","type":"string","value":"=You are an expert construction surveyor. {{ $json.system_prompt_lang }}\n\n## STAGE 1: IDENTIFY ELEMENTS FROM PHOTO\n\nAnalyze this construction photo and identify ALL visible elements.\n\n### IDENTIFICATION RULES:\n1. **Identify ROOM TYPE** first (bathroom, kitchen, bedroom, living room, hallway, exterior, facade, roof, basement, utility)\n2. **List ALL visible construction elements** with their materials\n3. **Estimate dimensions** using reference objects:\n - Standard door: 2.0m height, 0.9m width\n - Standard window: 1.2m ร— 1.4m\n - Ceiling height: typically 2.5-2.7m\n - Brick: 25cm ร— 12cm ร— 6.5cm\n - Tile: 30cm ร— 30cm or 60cm ร— 60cm\n - Socket/switch: 8cm ร— 8cm\n\n{{ $json.user_description ? 'User note: ' + $json.user_description : '' }}\n\nReturn ONLY valid JSON (no markdown, no code blocks):\n{\n \"room_type\": \"bathroom|kitchen|bedroom|living_room|hallway|exterior|facade|roof|basement|utility|other\",\n \"room_description\": \"Brief description of what you see\",\n \"estimated_dimensions\": {\n \"floor_area_m2\": 0,\n \"wall_area_m2\": 0,\n \"ceiling_height_m\": 2.5,\n \"perimeter_m\": 0\n },\n \"elements\": [\n {\n \"element_type\": \"wall|floor|ceiling|window|door|fixture|furniture|mep\",\n \"element_name\": \"Descriptive name\",\n \"material\": \"concrete|brick|drywall|tile|wood|glass|metal|plastic\",\n \"surface_finish\": \"painted|tiled|plastered|wallpaper|raw|laminate\",\n \"quantity\": 1,\n \"unit\": \"mยฒ|m|pcs\",\n \"estimated_size\": \"e.g. 3.5 mยฒ or 2.1 m\",\n \"condition\": \"new|good|worn|damaged\",\n \"notes\": \"Any additional observations\"\n }\n ],\n \"fixtures\": [\n {\n \"fixture_type\": \"toilet|sink|bathtub|shower|faucet|radiator|socket|switch|light|vent\",\n \"quantity\": 1,\n \"notes\": \"Description\"\n }\n ],\n \"work_type_detected\": \"new_construction|renovation|repair\",\n \"confidence\": \"high|medium|low\"\n}"}]}},"typeVersion":3.4},{"id":"0fb1af6a-fa06-44e6-9181-2f0c3073f1f6","name":"STAGE 1 Analyze Photo","type":"@n8n/n8n-nodes-langchain.chainLlm","position":[30208,384],"parameters":{"messages":{"messageValues":[{"message":"={{ $json.chatInput }}"}]}},"typeVersion":1.4},{"id":"7a62ea97-a203-4ce0-b693-90d385aa542c","name":"GPT-4 Vision","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[30208,592],"parameters":{"model":{"__rl":true,"mode":"list","value":"chatgpt-4o-latest","cachedResultName":"chatgpt-4o-latest"},"options":{"maxTokens":4000,"temperature":0.2}},"credentials":{"openAiApi":{"id":"credential-id","name":"OpenAi account WS"}},"typeVersion":1.2},{"id":"f4168e15-aa61-4878-a583-79df493e8104","name":"Parse STAGE 1","type":"n8n-nodes-base.code","position":[30480,384],"parameters":{"jsCode":"// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// PARSE STAGE 1 VISION RESPONSE\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n\nconst aiResponse = $input.first().json;\nconst configData = $('Configure Language').first().json;\n\nlet parsed = {\n room_type: 'unknown',\n room_description: 'Analysis failed',\n elements: [],\n fixtures: [],\n estimated_dimensions: { floor_area_m2: 10, wall_area_m2: 30, ceiling_height_m: 2.5, perimeter_m: 12 }\n};\n\ntry {\n const content = aiResponse.text || aiResponse.content || aiResponse.response || '';\n let jsonStr = content;\n \n const jsonMatch = content.match(/```json\\s*([\\s\\S]*?)\\s*```/);\n if (jsonMatch) {\n jsonStr = jsonMatch[1];\n } else {\n const codeMatch = content.match(/```\\s*([\\s\\S]*?)\\s*```/);\n if (codeMatch) {\n jsonStr = codeMatch[1];\n } else {\n const objMatch = content.match(/\\{[\\s\\S]*\\}/);\n if (objMatch) {\n jsonStr = objMatch[0];\n }\n }\n }\n \n parsed = JSON.parse(jsonStr);\n} catch (error) {\n console.error('Parse error:', error.message);\n}\n\nreturn {\n json: {\n ...configData,\n stage1_result: parsed,\n room_type: parsed.room_type || 'unknown',\n room_description: parsed.room_description || 'Photo analysis',\n elements: parsed.elements || [],\n fixtures: parsed.fixtures || [],\n dimensions: parsed.estimated_dimensions || {},\n work_type_detected: parsed.work_type_detected || configData.work_type || 'renovation',\n confidence: parsed.confidence || 'medium'\n }\n};"},"typeVersion":2},{"id":"c733ceb2-3357-42b1-b585-0cf2f8d3f2d1","name":"STAGE 4 Decompose Prompt","type":"n8n-nodes-base.set","position":[30656,384],"parameters":{"options":{},"assignments":{"assignments":[{"id":"prompt2","name":"chatInput","type":"string","value":"={{ $json.system_prompt_lang }}\n\n## STAGE 4: DECOMPOSE ELEMENTS TO CONSTRUCTION WORKS\n\nYou are a construction cost estimator. Based on the photo analysis, decompose each element into specific construction work items.\n\n### PHOTO ANALYSIS RESULTS:\n- Room Type: {{ $json.room_type }}\n- Description: {{ $json.room_description }}\n- Work Type: {{ $json.work_type_detected }}\n- Dimensions: Floor {{ $json.dimensions.floor_area_m2 || 10 }} mยฒ, Walls {{ $json.dimensions.wall_area_m2 || 30 }} mยฒ\n\n### ELEMENTS DETECTED:\n{{ JSON.stringify($json.elements, null, 2) }}\n\n### FIXTURES DETECTED:\n{{ JSON.stringify($json.fixtures, null, 2) }}\n\nโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n## CATEGORY โ†’ WORK ITEMS MAPPING (USE THIS!)\nโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n\n### BATHROOM:\n1. Demolition of old finishes (mยฒ) - if renovation\n2. Waterproofing floor (mยฒ)\n3. Waterproofing walls wet zone (mยฒ)\n4. Floor screed (mยฒ)\n5. Wall tiling (mยฒ)\n6. Floor tiling (mยฒ)\n7. Ceiling finishing (mยฒ)\n8. Toilet installation (pcs)\n9. Sink/washbasin installation (pcs)\n10. Bathtub installation (pcs) - if present\n11. Shower cabin installation (pcs) - if present\n12. Faucet/mixer installation (pcs)\n13. Towel rail installation (pcs)\n14. Mirror installation (pcs)\n15. Ventilation installation (pcs)\n16. Electrical: sockets, switches, lighting (pcs)\n17. Plumbing pipes (m)\n18. Door installation (pcs)\n\n### KITCHEN:\n1. Demolition of old finishes (mยฒ) - if renovation\n2. Wall preparation/plastering (mยฒ)\n3. Wall tiling (backsplash area) (mยฒ)\n4. Floor finishing (mยฒ)\n5. Ceiling finishing (mยฒ)\n6. Kitchen cabinets installation (m)\n7. Countertop installation (m)\n8. Sink installation (pcs)\n9. Faucet installation (pcs)\n10. Appliance connections (pcs)\n11. Electrical: sockets, switches (pcs)\n12. Lighting installation (pcs)\n13. Ventilation hood installation (pcs)\n14. Plumbing pipes (m)\n\n### LIVING ROOM / BEDROOM:\n1. Demolition of old finishes (mยฒ) - if renovation\n2. Wall preparation (mยฒ)\n3. Wall painting OR wallpaper (mยฒ)\n4. Floor preparation/screed (mยฒ)\n5. Floor covering - laminate/parquet/carpet (mยฒ)\n6. Baseboard/skirting installation (m)\n7. Ceiling finishing - paint/stretch/drywall (mยฒ)\n8. Electrical: sockets, switches (pcs)\n9. Lighting installation (pcs)\n10. Window sill finishing (m)\n11. Door installation (pcs)\n12. Radiator installation (pcs) - if visible\n\n### FLOOR WORKS:\n1. Old floor demolition (mยฒ) - if renovation\n2. Floor leveling/screed (mยฒ)\n3. Insulation (mยฒ) - if ground floor\n4. Underfloor heating (mยฒ) - if applicable\n5. Primer/preparation (mยฒ)\n6. Floor covering (mยฒ)\n7. Baseboard installation (m)\n\n### WALL WORKS:\n- Drywall: Metal framing (mยฒ) โ†’ Insulation (mยฒ) โ†’ Boarding (mยฒ) โ†’ Jointing (mยฒ) โ†’ Painting (mยฒ)\n- Masonry: Brickwork (mยฒ) โ†’ Plastering (mยฒ) โ†’ Painting (mยฒ)\n- Tiling: Wall preparation (mยฒ) โ†’ Tiling (mยฒ) โ†’ Grouting (mยฒ)\n\n### WINDOW WORKS:\n1. Old window demolition (pcs) - if renovation\n2. Window frame installation (pcs)\n3. Glazing (mยฒ)\n4. Internal sill (m)\n5. External sill (m)\n6. Sealing/foam (m)\n7. Trim/architrave (m)\n8. Painting/finishing (m)\n\n### DOOR WORKS:\n1. Old door demolition (pcs) - if renovation\n2. Door frame installation (pcs)\n3. Door leaf hanging (pcs)\n4. Hardware installation (pcs)\n5. Trim/architrave (m)\n6. Painting/finishing (mยฒ)\n\n### ELECTRICAL WORKS:\n1. Cable routing (m)\n2. Socket installation (pcs)\n3. Switch installation (pcs)\n4. Junction box (pcs)\n5. Lighting point (pcs)\n6. Panel/breaker installation (pcs)\n\n### PLUMBING WORKS:\n1. Pipe installation - supply (m)\n2. Pipe installation - drain (m)\n3. Valve installation (pcs)\n4. Connection to fixture (pcs)\n5. Pressure testing (pcs)\n\nโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n## CRITICAL RULES:\nโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n\n1. **NEVER return empty work_items** - minimum 3 works per element\n2. **Include PREPARATION works** - demolition, priming, leveling\n3. **Include FINISHING works** - painting, sealing, cleaning\n4. **Match units correctly**: areasโ†’mยฒ, lengthsโ†’m, itemsโ†’pcs\n5. **For RENOVATION**: always include demolition/removal works first\n6. **Scale quantities** from dimensions provided\n7. **search_query must be in {{ $json.search_lang }}** for vector database\n\nโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n\nReturn ONLY valid JSON:\n{\n \"work_items\": [\n {\n \"work_sequence\": 1,\n \"work_category\": \"PREPARATION|MAIN|FINISHING|MEP\",\n \"work_name\": \"Work name in {{ $json.language }}\",\n \"search_query\": \"Search terms in {{ $json.search_lang }} for DDC CWICR database - be specific!\",\n \"quantity\": 12.5,\n \"unit\": \"mยฒ|m|pcs\",\n \"calculation_basis\": \"floor_area ร— 1.0 = 12.5 mยฒ\",\n \"source_element\": \"Which element this work is for\",\n \"is_demolition\": false\n }\n ],\n \"total_works_count\": 15,\n \"phases\": [\"PREPARATION\", \"MAIN\", \"FINISHING\", \"MEP\"]\n}"}]}},"typeVersion":3.4},{"id":"b7550960-96b9-400a-82cd-57fcae2813ec","name":"STAGE 4 Decompose LLM","type":"@n8n/n8n-nodes-langchain.chainLlm","position":[30880,384],"parameters":{"messages":{"messageValues":[{"message":"={{ $json.chatInput }}"}]}},"typeVersion":1.4},{"id":"b973f4c7-7800-48ac-bd3f-f6a7f1e4d278","name":"GPT-4 Decompose","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[30880,592],"parameters":{"model":{"__rl":true,"mode":"list","value":"chatgpt-4o-latest","cachedResultName":"chatgpt-4o-latest"},"options":{"maxTokens":8000,"temperature":0.3}},"credentials":{"openAiApi":{"id":"credential-id","name":"OpenAi account WS"}},"typeVersion":1.2},{"id":"ae0ff40d-08ce-4c80-8cdc-69d7a343b1a7","name":"Parse STAGE 4","type":"n8n-nodes-base.code","position":[31168,384],"parameters":{"jsCode":"// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// PARSE STAGE 4 DECOMPOSITION RESPONSE\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n\nconst aiResponse = $input.first().json;\nconst configData = $('Parse STAGE 1').first().json;\n\nlet parsed = { work_items: [] };\n\ntry {\n const content = aiResponse.text || aiResponse.content || aiResponse.response || '';\n let jsonStr = content;\n \n const jsonMatch = content.match(/```json\\s*([\\s\\S]*?)\\s*```/);\n if (jsonMatch) {\n jsonStr = jsonMatch[1];\n } else {\n const objMatch = content.match(/\\{[\\s\\S]*\\}/);\n if (objMatch) {\n jsonStr = objMatch[0];\n }\n }\n \n parsed = JSON.parse(jsonStr);\n} catch (error) {\n console.error('STAGE 4 Parse error:', error.message);\n}\n\n// Validate and enrich work items\nconst workItems = (parsed.work_items || []).map((work, idx) => {\n // Ensure search_query exists and is meaningful\n let searchQuery = work.search_query || work.work_name || '';\n \n // Add language-specific terms if needed\n if (searchQuery.length < 5) {\n searchQuery = work.work_name + ' ' + (work.source_element || '');\n }\n \n return {\n work_id: `W${String(idx + 1).padStart(3, '0')}`,\n work_sequence: work.work_sequence || idx + 1,\n work_category: work.work_category || 'MAIN',\n work_name: work.work_name || 'Unnamed work',\n search_query: searchQuery.trim(),\n project_quantity: parseFloat(work.quantity) || 1,\n unit: work.unit || 'mยฒ',\n calculation_basis: work.calculation_basis || '',\n source_element: work.source_element || '',\n is_demolition: work.is_demolition || false\n };\n});\n\n// Sort by sequence\nworkItems.sort((a, b) => a.work_sequence - b.work_sequence);\n\nreturn {\n json: {\n ...configData,\n work_items: workItems,\n works_count: workItems.length,\n phases: parsed.phases || ['PREPARATION', 'MAIN', 'FINISHING', 'MEP'],\n stage4_success: workItems.length >= 3\n }\n};"},"typeVersion":2},{"id":"70e62b94-292e-4f2e-b3bc-ca607618d772","name":"Prepare Works","type":"n8n-nodes-base.code","position":[31344,384],"parameters":{"jsCode":"// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// PREPARE WORKS FOR LOOP\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n\nconst data = $input.first().json;\nconst works = data.work_items || [];\n\nconst staticData = $getWorkflowStaticData('global');\nstaticData.photo_config = {\n language_code: data.language_code,\n language: data.language,\n currency: data.currency,\n currency_symbol: data.currency_symbol,\n locale: data.locale,\n city: data.city,\n qdrant_collection: data.qdrant_collection,\n room_type: data.room_type,\n room_description: data.room_description,\n dimensions: data.dimensions,\n work_type_detected: data.work_type_detected,\n phases: data.phases,\n elements: data.elements,\n fixtures: data.fixtures\n};\nstaticData.work_results = [];\n\nif (works.length === 0) {\n return [{ json: { _no_works: true, message: 'No work items generated' } }];\n}\n\nreturn works.map((work) => ({\n json: {\n ...work,\n expected_unit: work.unit,\n type_name: work.work_name,\n category: work.work_category,\n assigned_phase: work.work_category,\n qdrant_collection: data.qdrant_collection,\n language: data.language,\n currency: data.currency,\n currency_symbol: data.currency_symbol,\n locale: data.locale\n }\n}));"},"typeVersion":2},{"id":"10b9b98b-f782-499f-9c12-e254af13bd0a","name":"Loop Works","type":"n8n-nodes-base.splitInBatches","position":[31536,384],"parameters":{"options":{"reset":false}},"typeVersion":3},{"id":"79f735d7-6de7-4a05-88e7-12d08b2fd6df","name":"Store Work Data","type":"n8n-nodes-base.code","position":[32016,592],"parameters":{"jsCode":"// Store current work item for Vector Search\nconst work = $input.first().json;\nconst staticData = $getWorkflowStaticData('global');\nstaticData.currentWork = work;\nreturn { json: work };"},"typeVersion":2},{"id":"60873726-0ece-4e69-91dc-73c77ad796b2","name":"Wait","type":"n8n-nodes-base.wait","position":[32160,592],"webhookId":"wait-photo-v3","parameters":{"amount":0.3},"typeVersion":1.1},{"id":"c5e35231-575a-4d53-95c4-ef2875363906","name":"Restore Work Data","type":"n8n-nodes-base.code","position":[32304,592],"parameters":{"jsCode":"// Restore work data from staticData after Wait\nconst staticData = $getWorkflowStaticData('global');\nconst work = staticData.currentWork || {};\nreturn { json: work };"},"typeVersion":2},{"id":"595e380e-4b57-4063-a594-fb89e010f81f","name":"Vector Search","type":"@n8n/n8n-nodes-langchain.vectorStoreQdrant","position":[32464,592],"parameters":{"mode":"load","topK":5,"prompt":"={{ $json.search_query || $json.work_name }}","options":{"contentPayloadKey":"content"},"qdrantCollection":{"__rl":true,"mode":"id","value":"={{ $json.qdrant_collection }}"}},"credentials":{"qdrantApi":{"id":"credential-id","name":"QdrantApi account 2"}},"typeVersion":1.1},{"id":"782d04ee-61c6-40a0-85bf-c5554533f3b5","name":"Embeddings","type":"@n8n/n8n-nodes-langchain.embeddingsOpenAi","position":[32448,752],"parameters":{"model":"text-embedding-3-large","options":{"dimensions":3072}},"credentials":{"openAiApi":{"id":"credential-id","name":"OpenAi account WS"}},"typeVersion":1.2},{"id":"e527cbd6-8841-4425-902a-ee4a28706c2f","name":"STAGE 5 Parse & Score","type":"n8n-nodes-base.code","position":[32720,592],"parameters":{"jsCode":"// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// STAGE 5: PARSE & VALIDATE VECTOR SEARCH RESULTS\n// FIXED: Correct document/pageContent extraction\n// Quality scoring v2.0 + Resource extraction\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n\nconst searchResults = $input.all();\nconst staticData = $getWorkflowStaticData('global');\nconst workData = staticData.currentWork || {};\n\n// MACHINE/LABOR PATTERNS (9 languages)\nconst MACHINE_PATTERNS = ['masch', 'maschinenstunde', 'gerรคt', 'machine', 'mach-h', 'equipment', 'heure machine', 'engin', 'mรกquina', 'equipo', 'equipamento', 'ะผะฐัˆะธะฝ', 'ะผะฐัˆ-ั‡', 'ะผะฐัˆ.ั‡', 'ะผะฐัˆ.-ั‡', 'ะผะตั…ะฐะฝะธะทะผ', 'ๆœบๅ™จ', 'ๆœบๆขฐ', '่ฎพๅค‡', 'ๅฐ็ญ', 'ุขู„ุฉ', 'ู…ุนุฏุฉ', 'เคฎเคถเฅ€เคจ', 'เคฏเค‚เคคเฅเคฐ'];\nconst LABOR_PATTERNS = ['std', 'stunde', 'arbeiter', 'hour', 'man-hour', 'labor', 'worker', 'heure', 'ouvrier', 'hora', 'obrero', 'operรกrio', 'ั‡-ั‡', 'ั‡ะตะป-ั‡', 'ั‡ะตะปะพะฒะตะบะพ-ั‡ะฐั', 'ั‚ั€ัƒะด', 'ั€ะฐะฑะพั‡ะธะน', 'ั€ะฐะทั€ัะด', ' ั‡', 'ๅทฅๆ—ถ', 'ไบบๅทฅ', 'ๅทฅไบบ', 'ุณุงุนุฉ', 'ุนุงู…ู„', 'เค˜เค‚เคŸเคพ', 'เคถเฅเคฐเคฎ', 'เคฎเคœเคฆเฅ‚เคฐ'];\n\nfunction detectResourceType(unit, name, code) {\n const combined = ((unit || '') + ' ' + (name || '') + ' ' + (code || '')).toLowerCase();\n if (MACHINE_PATTERNS.some(p => combined.includes(p.toLowerCase()))) return 'machine';\n if (LABOR_PATTERNS.some(p => combined.includes(p.toLowerCase()))) return 'labor';\n return 'material';\n}\n\nfunction normalizeUnit(unit) {\n if (!unit) return '';\n const u = unit.toLowerCase().trim();\n const unitGroups = {\n 'm2': ['mยฒ', 'm2', 'qm', 'ะบะฒะผ', 'ะบะฒ.ะผ', 'ะบะฒ. ะผ', 'sq.m', 'sqm', 'ๅนณๆ–น็ฑณ'],\n 'm3': ['mยณ', 'm3', 'cbm', 'ะบัƒะฑ.ะผ', 'ะบัƒะฑ. ะผ', 'cu.m', '็ซ‹ๆ–น็ฑณ'],\n 'm': ['m', 'ะผ', 'lm', 'lfm', 'ะฟ.ะผ', 'ะฟ. ะผ', 'lin.m', '็ฑณ'],\n 'stk': ['stk', 'stรผck', 'st', 'ัˆั‚', 'ัˆั‚.', 'pcs', 'ea', 'each', 'unit', 'ไธช', 'ไปถ'],\n '100m2': ['100 mยฒ', '100mยฒ', '100 m2', '100m2', '100 qm', '100 ะบะฒ.ะผ']\n };\n for (const [normalized, variants] of Object.entries(unitGroups)) {\n if (variants.some(v => u === v || u.includes(v))) return normalized;\n }\n return u;\n}\n\n// MATERIAL KEYWORDS for matching\nconst MATERIAL_KEYWORDS = [\n 'aluminum', 'aluminium', 'alu', 'ะฐะปัŽะผะธะฝ',\n 'wood', 'holz', 'ะดะตั€ะตะฒ', 'ะดั€ะตะฒะตั', 'ๆœจ',\n 'plastic', 'pvc', 'kunststoff', 'ะฟะปะฐัั‚ะธะบ', 'ะฟะฒั…',\n 'steel', 'stahl', 'ัั‚ะฐะป', 'ะผะตั‚ะฐะปะป', '้’ข',\n 'concrete', 'beton', 'ะฑะตั‚ะพะฝ', 'ๆททๅ‡ๅœŸ',\n 'glass', 'glas', 'ัั‚ะตะบะป', '็Žป็’ƒ',\n 'brick', 'ziegel', 'ะบะธั€ะฟะธั‡', '็ –',\n 'tile', 'fliese', 'ะฟะปะธั‚ะบ', 'ะบะฐั„ะตะปัŒ', '็“ท็ –',\n 'ceramic', 'keramik', 'ะบะตั€ะฐะผะธะบ', '้™ถ็“ท',\n 'gypsum', 'gips', 'ะณะธะฟั', '็Ÿณ่†',\n 'drywall', 'ะณะธะฟัะพะบะฐั€ั‚ะพะฝ', 'ะณะบะป',\n 'paint', 'farbe', 'ะบั€ะฐัะบ', 'ๆฒนๆผ†',\n 'wallpaper', 'tapete', 'ะพะฑะพ', 'ๅฃ็บธ',\n 'laminate', 'laminat', 'ะปะฐะผะธะฝะฐั‚',\n 'parquet', 'parkett', 'ะฟะฐั€ะบะตั‚'\n];\n\n// WORK TYPE KEYWORDS for matching\nconst WORK_TYPE_KEYWORDS = [\n 'installation', 'montage', 'ัƒัั‚ะฐะฝะพะฒะบ', 'ะผะพะฝั‚ะฐะถ', 'ๅฎ‰่ฃ…',\n 'demolition', 'abbruch', 'ะดะตะผะพะฝั‚ะฐะถ', 'ัะฝะพั', 'ั€ะฐะทะฑะพั€', 'ๆ‹†้™ค',\n 'preparation', 'vorbereitung', 'ะฟะพะดะณะพั‚ะพะฒ', 'ๅ‡†ๅค‡',\n 'sealing', 'abdichtung', 'ะณะตั€ะผะตั‚ะธะท', 'ะณะธะดั€ะพะธะทะพะป', 'ๅฏ†ๅฐ',\n 'insulation', 'dรคmmung', 'ะธะทะพะปัั†', 'ัƒั‚ะตะฟะป', 'ไฟๆธฉ',\n 'finishing', 'ะพั‚ะดะตะปะบ', 'finish', '่ฃ…ไฟฎ',\n 'excavation', 'aushub', 'ะฒั‹ะตะผะบ', 'ะบะพะฟะฐะฝ', 'ๅผ€ๆŒ–',\n 'concrete', 'beton', 'ะฑะตั‚ะพะฝะธั€', 'ๆททๅ‡ๅœŸ',\n 'reinforcement', 'bewehrung', 'ะฐั€ะผะธั€', '้’ข็ญ‹',\n 'plastering', 'putz', 'ัˆั‚ัƒะบะฐั‚ัƒั€', 'ๆŠน็ฐ',\n 'painting', 'malen', 'anstrich', 'ะพะบั€ะฐัะบ', 'ะฟะพะบั€ะฐัะบ', 'ๆฒนๆผ†',\n 'tiling', 'fliesen', 'ะพะฑะปะธั†ะพะฒ', 'ัƒะบะปะฐะดะบ ะฟะปะธั‚ะบ', '่ดด็ –',\n 'flooring', 'boden', 'ะฝะฐะฟะพะปัŒะฝ', 'ะฟะพะป', 'ๅœฐๆฟ',\n 'roofing', 'dach', 'ะบั€ะพะฒะป', 'ๅฑ‹้ข',\n 'plumbing', 'sanitรคr', 'ัะฐะฝั‚ะตั…ะฝ', '็ฎก้“',\n 'electrical', 'elektro', 'ัะปะตะบั‚ั€', '็”ตๆฐ”'\n];\n\n// NOT FOUND FALLBACK\nif (!searchResults || searchResults.length === 0) {\n return [{\n json: {\n ...workData,\n rate_code: 'NOT_FOUND',\n rate_name: '[Not Found] ' + (workData.work_name || 'Unknown'),\n rate_unit: workData.expected_unit || 'mยฒ',\n unit_cost: 0,\n total_cost: 0,\n estimated_labor_hours: 0,\n quality_level: 'not_found',\n quality_score: 0,\n quality_reason: 'No search results',\n resources_all: [],\n cost_breakdown: { workers: 0, machines: 0, materials: 0 }\n }\n }];\n}\n\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// FIX: CORRECT EXTRACTION OF document.pageContent\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\nconst parsedResults = searchResults.map((item) => {\n const data = item.json || {};\n \n // FIX: Handle nested document structure from Vector Search\n const doc = data.document || {};\n const content = String(doc.pageContent || doc.content || data.pageContent || data.content || '');\n const metadata = doc.metadata || data.metadata || {};\n const score = data.score || 0;\n \n // โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n // EXTRACT TOTAL COST from \"Total cost: 3127.16 EUR\"\n // โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n let totalCost = 0;\n const costPatterns = [\n /Total\\s*cost:\\s*([\\d.,]+)\\s*(?:EUR|USD|RUB|CAD|CNY|AED|INR|BRL)/i,\n /Resources?\\s*cost:\\s*([\\d.,]+)/i,\n /(?:Gesamt|ะ˜ะขะžะ“ะž|ะ’ัะตะณะพ|ะกั‚ะพะธะผะพัั‚ัŒ)[^\\d]*([\\d.,]+)/i,\n /(?:EUR|USD|RUB|CAD|\\$|โ‚ฌ|โ‚ฝ)\\s*([\\d.,]+)/i\n ];\n for (const pattern of costPatterns) {\n const match = content.match(pattern);\n if (match) {\n totalCost = parseFloat(match[1].replace(/,/g, '.').replace(/\\s/g, '')) || 0;\n if (totalCost > 0) break;\n }\n }\n \n // โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n // EXTRACT CODE, NAME, UNIT from content if not in metadata\n // โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n let rateCode = metadata.rsts || metadata.code || '';\n let rateName = metadata.names || metadata.name || '';\n let rateUnit = metadata.unit || '';\n \n // Fallback: extract from content\n if (!rateCode) {\n const codeMatch = content.match(/CODE:\\s*([A-Zะ-ะฏa-zะฐ-ั0-9_-]+)/i);\n if (codeMatch) rateCode = codeMatch[1];\n }\n if (!rateName) {\n const nameMatch = content.match(/NAME:\\s*(.+?)(?:\\n|UNIT:|CATEGORY:)/i);\n if (nameMatch) rateName = nameMatch[1].trim();\n }\n if (!rateUnit) {\n const unitMatch = content.match(/UNIT:\\s*(.+?)(?:\\n|CATEGORY:)/i);\n if (unitMatch) rateUnit = unitMatch[1].trim();\n }\n \n // โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n // EXTRACT LABOR HOURS\n // โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n let laborHours = 0;\n const laborMatch = content.match(/(?:ั€ะฐะทั€ัะด|worker|arbeiter|labor)[^โ€”\\n]*โ€”\\s*([\\d.,]+)\\s*(?:ั‡|ั‡ะฐั|std|hour|h)/i);\n if (laborMatch) {\n laborHours = parseFloat(laborMatch[1].replace(',', '.')) || 0;\n }\n \n // โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n // EXTRACT RESOURCES from RESOURCES: section\n // โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n const resources = [];\n const resourcesSection = content.match(/RESOURCES:\\s*([\\s\\S]*?)(?:$|MACHINES:|SCOPE|CLASSIFICATION:)/i);\n if (resourcesSection) {\n const resourcesText = resourcesSection[1];\n const resourceLines = resourcesText.split('\\n').filter(line => line.trim().startsWith('-'));\n \n for (const line of resourceLines) {\n const resMatch = line.match(/^-\\s*([A-Zะ-ะฏa-zะฐ-ั0-9_-]+)\\s*[โ€”โ€“-]\\s*(.+?)\\s*[โ€”โ€“-]\\s*([\\d.,]+)\\s*(.+?)$/i);\n if (resMatch) {\n const resCode = resMatch[1].trim();\n const resName = resMatch[2].trim();\n const resQty = parseFloat(resMatch[3].replace(',', '.')) || 0;\n const resUnit = resMatch[4].trim();\n const resType = detectResourceType(resUnit, resName, resCode);\n \n resources.push({\n resource_code: resCode,\n resource_name: resName,\n resource_quantity: resQty,\n resource_unit: resUnit,\n resource_cost: 0,\n resource_type: resType\n });\n }\n }\n }\n \n return {\n rate_code: rateCode,\n rate_name: rateName,\n rate_unit: rateUnit,\n total_cost_position: totalCost,\n worker_labor_hours: laborHours,\n hierarchy: metadata.hierarchy || '',\n resources: resources,\n resources_count: resources.length,\n vector_score: score,\n content_preview: content.substring(0, 300)\n };\n});\n\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// QUALITY SCORING v2.0\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\nconst expectedUnit = normalizeUnit(workData.expected_unit || workData.unit || '');\nconst searchQuery = (workData.search_query || workData.work_name || '').toLowerCase();\nconst workName = (workData.work_name || '').toLowerCase();\n\nconst scoredResults = parsedResults.map(result => {\n let score = 0;\n const factors = [];\n const resultUnit = normalizeUnit(result.rate_unit);\n const rateName = (result.rate_name || '').toLowerCase();\n const rateContent = (result.content_preview || '').toLowerCase();\n const combined = rateName + ' ' + rateContent;\n \n if (result.total_cost_position > 0) { \n score += 30; \n factors.push('has_price:' + result.total_cost_position.toFixed(0)); \n }\n \n if (result.resources_count > 0) { \n score += Math.min(25, result.resources_count * 5); \n factors.push('resources:' + result.resources_count); \n }\n \n if (resultUnit && expectedUnit) {\n if (resultUnit === expectedUnit) { \n score += 20; \n factors.push('unit_exact'); \n } else if (resultUnit.includes(expectedUnit) || expectedUnit.includes(resultUnit)) { \n score += 10; \n factors.push('unit_partial'); \n }\n }\n \n const materialMatches = MATERIAL_KEYWORDS.filter(kw => \n (workName.includes(kw) || searchQuery.includes(kw)) && combined.includes(kw)\n );\n if (materialMatches.length > 0) {\n score += 15;\n factors.push('material:' + materialMatches[0]);\n }\n \n const workTypeMatches = WORK_TYPE_KEYWORDS.filter(kw => \n (workName.includes(kw) || searchQuery.includes(kw)) && combined.includes(kw)\n );\n if (workTypeMatches.length > 0) {\n score += 10;\n factors.push('work_type:' + workTypeMatches[0]);\n }\n \n const queryWords = searchQuery.split(/\\s+/).filter(w => w.length > 3);\n const matchedWords = queryWords.filter(w => rateName.includes(w) || rateContent.includes(w));\n if (matchedWords.length > 0) { \n score += Math.min(15, matchedWords.length * 5); \n factors.push('words:' + matchedWords.length); \n }\n \n if (result.vector_score > 0.5) {\n score += 10;\n factors.push('vscore:' + result.vector_score.toFixed(2));\n } else if (result.vector_score > 0.4) {\n score += 5;\n factors.push('vscore:' + result.vector_score.toFixed(2));\n }\n \n const hasLabor = result.resources.some(r => r.resource_type === 'labor');\n const hasMaterial = result.resources.some(r => r.resource_type === 'material');\n if (hasLabor && hasMaterial) {\n score += 5;\n factors.push('complete_rate');\n }\n \n return { ...result, quality_score: score, quality_factors: factors };\n});\n\nconst sorted = scoredResults.sort((a, b) => b.quality_score - a.quality_score);\nconst best = sorted[0] || { quality_score: 0, quality_factors: [], resources: [] };\n\nlet qualityLevel = 'not_found';\nconst s = best.quality_score;\nif (s >= 60) { qualityLevel = 'high'; }\nelse if (s >= 40) { qualityLevel = 'medium'; }\nelse if (s >= 20) { qualityLevel = 'low'; }\n\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// CALCULATE COSTS\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\nconst projectQuantity = workData.project_quantity || 0;\nconst unitCost = best.total_cost_position || 0;\n\nlet unitDivisor = 1;\nconst rateUnit = (best.rate_unit || '').toLowerCase();\nif (rateUnit.includes('100')) unitDivisor = 100;\nelse if (rateUnit.includes('10 ')) unitDivisor = 10;\n\nconst quantityInRateUnits = projectQuantity / unitDivisor;\nconst totalCost = quantityInRateUnits * unitCost;\nconst estimatedLaborHours = (best.worker_labor_hours || 0) * quantityInRateUnits;\n\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// SCALE & CATEGORIZE RESOURCES\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\nlet laborCost = 0, machineCost = 0, materialCost = 0;\nconst scaledResources = (best.resources || []).map(r => {\n const scaledQty = (r.resource_quantity || 0) * quantityInRateUnits;\n const scaledCost = (r.resource_cost || 0) * quantityInRateUnits;\n \n if (r.resource_type === 'labor') laborCost += scaledCost;\n else if (r.resource_type === 'machine') machineCost += scaledCost;\n else materialCost += scaledCost;\n \n return { ...r, scaled_quantity: scaledQty, scaled_cost: scaledCost };\n});\n\nif (laborCost === 0 && materialCost === 0 && totalCost > 0) {\n laborCost = totalCost * 0.35;\n materialCost = totalCost * 0.55;\n machineCost = totalCost * 0.10;\n}\n\nreturn [{\n json: {\n work_id: workData.work_id,\n work_sequence: workData.work_sequence,\n work_category: workData.work_category,\n work_name: workData.work_name,\n source_element: workData.source_element,\n calculation_basis: workData.calculation_basis,\n is_demolition: workData.is_demolition,\n rate_code: best.rate_code || 'NOT_FOUND',\n rate_name: best.rate_name || workData.work_name || 'Not found',\n rate_unit: best.rate_unit || workData.expected_unit,\n project_quantity: projectQuantity,\n project_unit: workData.unit || workData.expected_unit,\n quantity_in_rate_units: quantityInRateUnits,\n calculated_quantity: quantityInRateUnits,\n unit_divisor: unitDivisor,\n unit_cost: unitCost,\n total_cost: totalCost,\n estimated_labor_hours: estimatedLaborHours,\n quality_level: qualityLevel,\n quality_score: s,\n quality_reason: 'Score ' + s + '/100: ' + best.quality_factors.join(', '),\n currency: workData.currency,\n currency_symbol: workData.currency_symbol,\n locale: workData.locale,\n type_name: workData.type_name,\n category: workData.category,\n assigned_phase: workData.assigned_phase,\n resources_all: scaledResources,\n cost_breakdown: {\n workers: laborCost,\n machines: machineCost,\n materials: materialCost\n },\n calculation_details: {\n method: 'photo_analysis',\n calculation_basis: workData.calculation_basis,\n raw_value: projectQuantity,\n unit_divisor: unitDivisor,\n formula_display: (workData.unit || 'Qty') + ' = ' + projectQuantity\n },\n search_debug: {\n query_used: workData.search_query,\n results_count: searchResults.length,\n best_match_score: s,\n best_vector_score: best.vector_score || 0,\n best_rate_found: best.rate_name || 'none'\n }\n }\n}];"},"typeVersion":2},{"id":"577e8350-ff19-4b73-a53f-80605484a493","name":"Accumulate","type":"n8n-nodes-base.code","position":[32864,592],"parameters":{"jsCode":"// ACCUMULATE RESULTS\nconst staticData = $getWorkflowStaticData('global');\nconst work = $input.first().json;\nif (!staticData.work_results) staticData.work_results = [];\nstaticData.work_results.push(work);\nreturn { json: work };"},"typeVersion":2},{"id":"9b8dd6f9-e36b-4fc0-bac8-5a0857890e32","name":"STAGE 7.5 Aggregate & Validate","type":"n8n-nodes-base.code","position":[31824,352],"parameters":{"jsCode":"// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// STAGE 7.5: AGGREGATE & VALIDATE RESULTS\n// Build by_phase structure with validation\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n\nconst staticData = $getWorkflowStaticData('global');\nconst config = staticData.photo_config || {};\nconst works = staticData.work_results || [];\n\n// Calculate totals\nlet grandTotal = 0, grandHours = 0;\nlet grandLaborCost = 0, grandMaterialCost = 0, grandMachineCost = 0;\nlet qHigh = 0, qMedium = 0, qLow = 0, qNotFound = 0;\n\nworks.forEach(w => {\n grandTotal += w.total_cost || 0;\n grandHours += w.estimated_labor_hours || 0;\n \n const cb = w.cost_breakdown || {};\n grandLaborCost += cb.workers || 0;\n grandMaterialCost += cb.materials || 0;\n grandMachineCost += cb.machines || 0;\n \n if (w.quality_level === 'high') qHigh++;\n else if (w.quality_level === 'medium') qMedium++;\n else if (w.quality_level === 'low') qLow++;\n else qNotFound++;\n});\n\n// Sort by sequence\nworks.sort((a, b) => (a.work_sequence || 0) - (b.work_sequence || 0));\n\n// Group by category (PREPARATION, MAIN, FINISHING, MEP)\nconst categories = {};\nworks.forEach(w => {\n const cat = w.work_category || 'MAIN';\n if (!categories[cat]) {\n categories[cat] = {\n works: [],\n total_cost: 0,\n labor_hours: 0\n };\n }\n categories[cat].works.push(w);\n categories[cat].total_cost += w.total_cost || 0;\n categories[cat].labor_hours += w.estimated_labor_hours || 0;\n});\n\n// Build by_phase structure\nconst phaseOrder = ['PREPARATION', 'MAIN', 'FINISHING', 'MEP'];\nconst byPhase = phaseOrder\n .filter(phase => categories[phase])\n .map((phase, idx) => {\n const cat = categories[phase];\n const phaseName = {\n 'PREPARATION': config.language_code === 'RU' ? 'ะŸะพะดะณะพั‚ะพะฒะธั‚ะตะปัŒะฝั‹ะต ั€ะฐะฑะพั‚ั‹' : \n config.language_code === 'DE' ? 'Vorbereitungsarbeiten' : 'Preparation Works',\n 'MAIN': config.language_code === 'RU' ? 'ะžัะฝะพะฒะฝั‹ะต ั€ะฐะฑะพั‚ั‹' : \n config.language_code === 'DE' ? 'Hauptarbeiten' : 'Main Works',\n 'FINISHING': config.language_code === 'RU' ? 'ะžั‚ะดะตะปะพั‡ะฝั‹ะต ั€ะฐะฑะพั‚ั‹' : \n config.language_code === 'DE' ? 'Ausbauarbeiten' : 'Finishing Works',\n 'MEP': config.language_code === 'RU' ? 'ะ˜ะฝะถะตะฝะตั€ะฝั‹ะต ัะธัั‚ะตะผั‹' : \n config.language_code === 'DE' ? 'Haustechnik' : 'MEP Systems'\n }[phase] || phase;\n \n return {\n phase_name: phaseName,\n phase_code: phase,\n phase_total_cost: cat.total_cost,\n phase_labor_hours: cat.labor_hours,\n types: [{\n type_name: config.room_description || 'Photo Analysis',\n category: config.room_type || 'General',\n element_count: cat.works.length,\n type_total_cost: cat.total_cost,\n type_total_labor_hours: cat.labor_hours,\n works: cat.works\n }]\n };\n });\n\n// VALIDATION CHECKS\nconst validationIssues = [];\n\nif (works.length < 3) {\n validationIssues.push('โš ๏ธ Less than 3 work items generated');\n}\n\nconst foundPercent = works.length > 0 ? Math.round((qHigh + qMedium + qLow) / works.length * 100) : 0;\nif (foundPercent < 50) {\n validationIssues.push('โš ๏ธ Less than 50% rates found - manual review needed');\n}\n\nconst zeroCostCount = works.filter(w => w.total_cost === 0).length;\nif (zeroCostCount > works.length * 0.3) {\n validationIssues.push('โš ๏ธ Many items with zero cost - database coverage issue');\n}\n\nif (config.work_type_detected === 'renovation') {\n const hasDemolition = works.some(w => w.is_demolition || \n (w.work_name || '').toLowerCase().match(/ะดะตะผะพะฝั‚ะฐะถ|ัะฝะพั|ั€ะฐะทะฑะพั€|demolition|abbruch|removal/));\n if (!hasDemolition) {\n validationIssues.push('๐Ÿ’ก Renovation detected but no demolition works - consider adding');\n }\n}\n\nconst photoConfig = staticData.photo_config;\nstaticData.work_results = [];\nstaticData.photo_config = null;\n\nreturn {\n json: {\n by_phase: byPhase,\n cost_summary: {\n grand_total_cost: grandTotal,\n grand_labor_hours: grandHours,\n grand_resource_cost: grandLaborCost,\n grand_material_cost: grandMaterialCost,\n grand_machine_cost: grandMachineCost\n },\n photo_analysis: {\n description: photoConfig?.room_description || 'Photo Analysis',\n room_type: photoConfig?.room_type || 'unknown',\n location_type: photoConfig?.room_type || 'interior',\n room_size: (photoConfig?.dimensions?.floor_area_m2 || 'N/A') + ' mยฒ',\n work_phase: photoConfig?.work_type_detected || 'general',\n materials: photoConfig?.elements?.map(e => e.material).filter(Boolean) || [],\n elements_count: photoConfig?.elements?.length || 0,\n fixtures_count: photoConfig?.fixtures?.length || 0\n },\n language_code: photoConfig?.language_code || 'EN',\n currency: photoConfig?.currency || 'EUR',\n currency_symbol: photoConfig?.currency_symbol || 'โ‚ฌ',\n locale: photoConfig?.locale || 'en-US',\n city: photoConfig?.city || 'Toronto',\n language: photoConfig?.language || 'English',\n pricing_level: photoConfig?.city || 'Toronto',\n quality_stats: {\n total: works.length,\n high: qHigh,\n medium: qMedium,\n low: qLow,\n not_found: qNotFound,\n found_percent: foundPercent\n },\n validation: {\n issues: validationIssues,\n issues_count: validationIssues.length,\n passed: validationIssues.length === 0\n }\n }\n};"},"typeVersion":2},{"id":"d3fe33db-d2a6-4217-a976-10aeab400af9","name":"STAGE 9 HTML Report","type":"n8n-nodes-base.code","position":[32240,352],"parameters":{"jsCode":"// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// STAGE 9: PROFESSIONAL HTML REPORT - 9 LANGUAGES\n// Photo Cost Estimate Pro v2 - with validation section\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n\nconst input = $input.first().json;\n\nconst langCode = (input.language_code || 'EN').toUpperCase();\nconst currency = input.currency || 'EUR';\nconst currencySymbol = input.currency_symbol || 'โ‚ฌ';\nconst locale = input.locale || 'en-US';\nconst pricingLevel = input.pricing_level || input.city || 'Unknown';\nconst photoAnalysis = input.photo_analysis || {};\nconst validation = input.validation || {};\nconst projectName = photoAnalysis.description || 'Photo Cost Estimate';\n\nconst RATES_LINK = 'https://openconstructionestimate.com/all-estimates/?utm=OCE';\n\n// TRANSLATIONS - 9 LANGUAGES\nconst translations = {\n 'DE': { doc_title: 'KOSTENVORANSCHLAG', project: 'Projekt', pricing_level: 'Preisniveau', date: 'Datum', col_pos: 'Pos.', col_code: 'Kennziffer', col_description: 'Bezeichnung', col_calc: 'Berechnung', col_unit: 'Einheit', col_qty: 'Menge', col_price: 'EP', col_total: 'GP', col_labor: 'Std.', col_quality: 'Q', subtotal: 'Zwischensumme', grand_total: 'GESAMTSUMME', labor_cost: 'Lohnkosten', material_cost: 'Materialkosten', labor_days: 'Arbeitstage', found_rates: 'Gefunden', manual_check: 'prรผfen', kpi_total: 'Gesamtkosten', kpi_hours: 'Arbeitsstunden', kpi_days: 'Arbeitstage', chart_cost_structure: 'Kostenstruktur', chart_by_phase: 'Nach Phase', chart_labor: 'Lohn', chart_material: 'Material', chart_machines: 'Maschinen', chart_timeline: 'Zeitplan', chart_hierarchy: 'Kostenhierarchie', collapse_all: 'Alles einklappen', expand_all: 'Alles ausklappen', res_labor: 'Lohn', res_material: 'Mat.', res_machine: 'Masch.', photo_analysis: 'Fotoanalyse', location: 'Raumtyp', room_size: 'RaumgrรถรŸe', work_phase: 'Arbeitstyp', materials: 'Materialien', validation: 'Validierung', validation_passed: 'Alle Prรผfungen bestanden', validation_issues: 'Hinweise' },\n 'EN': { doc_title: 'COST ESTIMATE', project: 'Project', pricing_level: 'Pricing Level', date: 'Date', col_pos: 'Pos.', col_code: 'Code', col_description: 'Description', col_calc: 'Calculation', col_unit: 'Unit', col_qty: 'Qty', col_price: 'UP', col_total: 'Total', col_labor: 'Hrs', col_quality: 'Q', subtotal: 'Subtotal', grand_total: 'GRAND TOTAL', labor_cost: 'Labor Cost', material_cost: 'Material Cost', labor_days: 'Work Days', found_rates: 'Found', manual_check: 'check', kpi_total: 'Total Cost', kpi_hours: 'Work Hours', kpi_days: 'Work Days', chart_cost_structure: 'Cost Structure', chart_by_phase: 'By Phase', chart_labor: 'Labor', chart_material: 'Material', chart_machines: 'Machines', chart_timeline: 'Timeline', chart_hierarchy: 'Cost Hierarchy', collapse_all: 'Collapse All', expand_all: 'Expand All', res_labor: 'Labor', res_material: 'Mat.', res_machine: 'Mach.', photo_analysis: 'Photo Analysis', location: 'Room Type', room_size: 'Room Size', work_phase: 'Work Type', materials: 'Materials', validation: 'Validation', validation_passed: 'All checks passed', validation_issues: 'Issues' },\n 'RU': { doc_title: 'ะกะœะ•ะขะ', project: 'ะŸั€ะพะตะบั‚', pricing_level: 'ะฃั€ะพะฒะตะฝัŒ ั†ะตะฝ', date: 'ะ”ะฐั‚ะฐ', col_pos: 'N', col_code: 'ะจะธั„ั€', col_description: 'ะะฐะธะผะตะฝะพะฒะฐะฝะธะต', col_calc: 'ะ ะฐัั‡ั‘ั‚', col_unit: 'ะ•ะด.', col_qty: 'ะšะพะป-ะฒะพ', col_price: 'ะฆะตะฝะฐ', col_total: 'ะกัƒะผะผะฐ', col_labor: 'ะง/ั‡', col_quality: 'ะš', subtotal: 'ะ˜ั‚ะพะณะพ', grand_total: 'ะ’ะกะ•ะ“ะž', labor_cost: 'ะขั€ัƒะด', material_cost: 'ะœะฐั‚ะตั€ะธะฐะปั‹', labor_days: 'ะ”ะฝะตะน', found_rates: 'ะะฐะนะดะตะฝะพ', manual_check: 'ะฟั€ะพะฒะตั€ะธั‚ัŒ', kpi_total: 'ะžะฑั‰ะฐั ัั‚ะพะธะผะพัั‚ัŒ', kpi_hours: 'ะงะฐัั‹', kpi_days: 'ะ”ะฝะธ', chart_cost_structure: 'ะกั‚ั€ัƒะบั‚ัƒั€ะฐ ะทะฐั‚ั€ะฐั‚', chart_by_phase: 'ะŸะพ ัั‚ะฐะฟะฐะผ', chart_labor: 'ะขั€ัƒะด', chart_material: 'ะœะฐั‚ะตั€ะธะฐะปั‹', chart_machines: 'ะœะฐัˆะธะฝั‹', chart_timeline: 'ะ“ั€ะฐั„ะธะบ', chart_hierarchy: 'ะ˜ะตั€ะฐั€ั…ะธั ะทะฐั‚ั€ะฐั‚', collapse_all: 'ะกะฒะตั€ะฝัƒั‚ัŒ ะฒัั‘', expand_all: 'ะ ะฐะทะฒะตั€ะฝัƒั‚ัŒ ะฒัั‘', res_labor: 'ะขั€ัƒะด', res_material: 'ะœะฐั‚.', res_machine: 'ะœะฐัˆ.', photo_analysis: 'ะะฝะฐะปะธะท ั„ะพั‚ะพ', location: 'ะขะธะฟ ะฟะพะผะตั‰ะตะฝะธั', room_size: 'ะŸะปะพั‰ะฐะดัŒ', work_phase: 'ะขะธะฟ ั€ะฐะฑะพั‚', materials: 'ะœะฐั‚ะตั€ะธะฐะปั‹', validation: 'ะŸั€ะพะฒะตั€ะบะฐ', validation_passed: 'ะ’ัะต ะฟั€ะพะฒะตั€ะบะธ ะฟั€ะพะนะดะตะฝั‹', validation_issues: 'ะ—ะฐะผะตั‡ะฐะฝะธั' },\n 'FR': { doc_title: 'DEVIS ESTIMATIF', project: 'Projet', pricing_level: 'Niveau de prix', date: 'Date', col_pos: 'Pos.', col_code: 'Code', col_description: 'Dรฉsignation', col_calc: 'Calcul', col_unit: 'Unitรฉ', col_qty: 'Qtรฉ', col_price: 'PU', col_total: 'Total', col_labor: 'Hrs', col_quality: 'Q', subtotal: 'Sous-total', grand_total: 'TOTAL Gร‰Nร‰RAL', labor_cost: 'Main-d-oeuvre', material_cost: 'Matรฉriaux', labor_days: 'Jours', found_rates: 'Trouvรฉs', manual_check: 'vรฉrifier', kpi_total: 'Coรปt Total', kpi_hours: 'Heures', kpi_days: 'Jours', chart_cost_structure: 'Structure des coรปts', chart_by_phase: 'Par phase', chart_labor: 'Main-d-oeuvre', chart_material: 'Matรฉriaux', chart_machines: 'Machines', chart_timeline: 'Planning', chart_hierarchy: 'Hiรฉrarchie', collapse_all: 'Tout rรฉduire', expand_all: 'Tout dรฉvelopper', res_labor: 'M.O.', res_material: 'Mat.', res_machine: 'Mach.', photo_analysis: 'Analyse photo', location: 'Type de piรจce', room_size: 'Surface', work_phase: 'Type de travaux', materials: 'Matรฉriaux', validation: 'Validation', validation_passed: 'Toutes les vรฉrifications passรฉes', validation_issues: 'Remarques' },\n 'ES': { doc_title: 'PRESUPUESTO', project: 'Proyecto', pricing_level: 'Nivel de precios', date: 'Fecha', col_pos: 'Pos.', col_code: 'Cรณdigo', col_description: 'Descripciรณn', col_calc: 'Cรกlculo', col_unit: 'Unidad', col_qty: 'Cant.', col_price: 'P.U.', col_total: 'Total', col_labor: 'Hrs', col_quality: 'Q', subtotal: 'Subtotal', grand_total: 'TOTAL GENERAL', labor_cost: 'Mano obra', material_cost: 'Materiales', labor_days: 'Dรญas', found_rates: 'Encontrados', manual_check: 'verificar', kpi_total: 'Coste Total', kpi_hours: 'Horas', kpi_days: 'Dรญas', chart_cost_structure: 'Estructura de costes', chart_by_phase: 'Por fase', chart_labor: 'Mano obra', chart_material: 'Material', chart_machines: 'Mรกquinas', chart_timeline: 'Cronograma', chart_hierarchy: 'Jerarquรญa', collapse_all: 'Contraer todo', expand_all: 'Expandir todo', res_labor: 'M.O.', res_material: 'Mat.', res_machine: 'Mรกq.', photo_analysis: 'Anรกlisis foto', location: 'Tipo de espacio', room_size: 'Superficie', work_phase: 'Tipo de obra', materials: 'Materiales', validation: 'Validaciรณn', validation_passed: 'Todas las verificaciones pasaron', validation_issues: 'Observaciones' },\n 'PT': { doc_title: 'ORร‡AMENTO', project: 'Projeto', pricing_level: 'Nรญvel de preรงos', date: 'Data', col_pos: 'Pos.', col_code: 'Cรณdigo', col_description: 'Descriรงรฃo', col_calc: 'Cรกlculo', col_unit: 'Unidade', col_qty: 'Qtd.', col_price: 'P.U.', col_total: 'Total', col_labor: 'Hrs', col_quality: 'Q', subtotal: 'Subtotal', grand_total: 'TOTAL GERAL', labor_cost: 'Mรฃo obra', material_cost: 'Materiais', labor_days: 'Dias', found_rates: 'Encontrados', manual_check: 'verificar', kpi_total: 'Custo Total', kpi_hours: 'Horas', kpi_days: 'Dias', chart_cost_structure: 'Estrutura de custos', chart_by_phase: 'Por fase', chart_labor: 'Mรฃo obra', chart_material: 'Material', chart_machines: 'Mรกquinas', chart_timeline: 'Cronograma', chart_hierarchy: 'Hierarquia', collapse_all: 'Recolher tudo', expand_all: 'Expandir tudo', res_labor: 'M.O.', res_material: 'Mat.', res_machine: 'Mรกq.', photo_analysis: 'Anรกlise foto', location: 'Tipo de espaรงo', room_size: 'รrea', work_phase: 'Tipo de obra', materials: 'Materiais', validation: 'Validaรงรฃo', validation_passed: 'Todas as verificaรงรตes passaram', validation_issues: 'Observaรงรตes' },\n 'ZH': { doc_title: 'ๅทฅ็จ‹้ข„็ฎ—', project: '้กน็›ฎ', pricing_level: 'ไปทๆ ผๆฐดๅนณ', date: 'ๆ—ฅๆœŸ', col_pos: 'ๅบๅท', col_code: '็ผ–็ ', col_description: 'ๅ็งฐ', col_calc: '่ฎก็ฎ—', col_unit: 'ๅ•ไฝ', col_qty: 'ๆ•ฐ้‡', col_price: 'ๅ•ไปท', col_total: 'ๅˆ่ฎก', col_labor: 'ๅทฅๆ—ถ', col_quality: '่ดจ', subtotal: 'ๅฐ่ฎก', grand_total: 'ๆ€ป่ฎก', labor_cost: 'ไบบๅทฅ่ดน', material_cost: 'ๆๆ–™่ดน', labor_days: 'ๅทฅไฝœๆ—ฅ', found_rates: 'ๅทฒๆ‰พๅˆฐ', manual_check: 'ๆ ธๆŸฅ', kpi_total: 'ๆ€ปๆˆๆœฌ', kpi_hours: 'ๅทฅๆ—ถ', kpi_days: 'ๅทฅไฝœๆ—ฅ', chart_cost_structure: 'ๆˆๆœฌ็ป“ๆž„', chart_by_phase: 'ๆŒ‰้˜ถๆฎต', chart_labor: 'ไบบๅทฅ', chart_material: 'ๆๆ–™', chart_machines: 'ๆœบๆขฐ', chart_timeline: '่ฟ›ๅบฆ', chart_hierarchy: 'ๅฑ‚ๆฌก', collapse_all: 'ๅ…จ้ƒจๆŠ˜ๅ ', expand_all: 'ๅ…จ้ƒจๅฑ•ๅผ€', res_labor: 'ไบบๅทฅ', res_material: 'ๆๆ–™', res_machine: 'ๆœบๆขฐ', photo_analysis: '็…ง็‰‡ๅˆ†ๆž', location: 'ๆˆฟ้—ด็ฑปๅž‹', room_size: '้ข็งฏ', work_phase: 'ๆ–ฝๅทฅ็ฑปๅž‹', materials: 'ๆๆ–™', validation: '้ชŒ่ฏ', validation_passed: 'ๆ‰€ๆœ‰ๆฃ€ๆŸฅ้€š่ฟ‡', validation_issues: '้—ฎ้ข˜' },\n 'AR': { doc_title: 'ุชู‚ุฏูŠุฑ ุงู„ุชูƒู„ูุฉ', project: 'ุงู„ู…ุดุฑูˆุน', pricing_level: 'ู…ุณุชูˆู‰ ุงู„ุฃุณุนุงุฑ', date: 'ุงู„ุชุงุฑูŠุฎ', col_pos: 'ุฑู‚ู…', col_code: 'ุงู„ุฑู…ุฒ', col_description: 'ุงู„ูˆุตู', col_calc: 'ุงู„ุญุณุงุจ', col_unit: 'ุงู„ูˆุญุฏุฉ', col_qty: 'ุงู„ูƒู…ูŠุฉ', col_price: 'ุณุนุฑ ุงู„ูˆุญุฏุฉ', col_total: 'ุงู„ู…ุฌู…ูˆุน', col_labor: 'ุณุงุนุงุช', col_quality: 'ุฌ', subtotal: 'ุงู„ู…ุฌู…ูˆุน ุงู„ูุฑุนูŠ', grand_total: 'ุงู„ู…ุฌู…ูˆุน ุงู„ูƒู„ูŠ', labor_cost: 'ุชูƒู„ูุฉ ุงู„ุนู…ุงู„ุฉ', material_cost: 'ุชูƒู„ูุฉ ุงู„ู…ูˆุงุฏ', labor_days: 'ุฃูŠุงู… ุงู„ุนู…ู„', found_rates: 'ุชู… ุงู„ุนุซูˆุฑ', manual_check: 'ุชุญู‚ู‚', kpi_total: 'ุงู„ุชูƒู„ูุฉ ุงู„ุฅุฌู…ุงู„ูŠุฉ', kpi_hours: 'ุณุงุนุงุช ุงู„ุนู…ู„', kpi_days: 'ุฃูŠุงู… ุงู„ุนู…ู„', chart_cost_structure: 'ู‡ูŠูƒู„ ุงู„ุชูƒู„ูุฉ', chart_by_phase: 'ุญุณุจ ุงู„ู…ุฑุญู„ุฉ', chart_labor: 'ุงู„ุนู…ุงู„ุฉ', chart_material: 'ุงู„ู…ูˆุงุฏ', chart_machines: 'ุงู„ู…ุนุฏุงุช', chart_timeline: 'ุงู„ุฌุฏูˆู„ ุงู„ุฒู…ู†ูŠ', chart_hierarchy: 'ุชุณู„ุณู„ ุงู„ุชูƒุงู„ูŠู', collapse_all: 'ุทูŠ ุงู„ูƒู„', expand_all: 'ุชูˆุณูŠุน ุงู„ูƒู„', res_labor: 'ุนู…ุงู„ุฉ', res_material: 'ู…ูˆุงุฏ', res_machine: 'ู…ุนุฏุงุช', photo_analysis: 'ุชุญู„ูŠู„ ุงู„ุตูˆุฑุฉ', location: 'ู†ูˆุน ุงู„ุบุฑูุฉ', room_size: 'ุงู„ู…ุณุงุญุฉ', work_phase: 'ู†ูˆุน ุงู„ุนู…ู„', materials: 'ุงู„ู…ูˆุงุฏ', validation: 'ุงู„ุชุญู‚ู‚', validation_passed: 'ุฌู…ูŠุน ุงู„ูุญูˆุตุงุช ู†ุงุฌุญุฉ', validation_issues: 'ู…ู„ุงุญุธุงุช' },\n 'HI': { doc_title: 'เคฒเคพเค—เคค เค…เคจเฅเคฎเคพเคจ', project: 'เคชเคฐเคฟเคฏเฅ‹เคœเคจเคพ', pricing_level: 'เคฎเฅ‚เคฒเฅเคฏ เคธเฅเคคเคฐ', date: 'เคคเคพเคฐเฅ€เค–', col_pos: 'เค•เฅเคฐเคฎ', col_code: 'เค•เฅ‹เคก', col_description: 'เคตเคฟเคตเคฐเคฃ', col_calc: 'เค—เคฃเคจเคพ', col_unit: 'เค‡เค•เคพเคˆ', col_qty: 'เคฎเคพเคคเฅเคฐเคพ', col_price: 'เคฆเคฐ', col_total: 'เค•เฅเคฒ', col_labor: 'เค˜เค‚เคŸเฅ‡', col_quality: 'เค—เฅ', subtotal: 'เค‰เคช-เคฏเฅ‹เค—', grand_total: 'เค•เฅเคฒ เคฏเฅ‹เค—', labor_cost: 'เคถเฅเคฐเคฎ เคฒเคพเค—เคค', material_cost: 'เคธเคพเคฎเค—เฅเคฐเฅ€ เคฒเคพเค—เคค', labor_days: 'เค•เคพเคฐเฅเคฏ เคฆเคฟเคตเคธ', found_rates: 'เคฎเคฟเคฒเคพ', manual_check: 'เคœเคพเคเคšเฅ‡เค‚', kpi_total: 'เค•เฅเคฒ เคฒเคพเค—เคค', kpi_hours: 'เค•เคพเคฐเฅเคฏ เค˜เค‚เคŸเฅ‡', kpi_days: 'เค•เคพเคฐเฅเคฏ เคฆเคฟเคตเคธ', chart_cost_structure: 'เคฒเคพเค—เคค เคธเค‚เคฐเคšเคจเคพ', chart_by_phase: 'เคšเคฐเคฃ เค…เคจเฅเคธเคพเคฐ', chart_labor: 'เคถเฅเคฐเคฎ', chart_material: 'เคธเคพเคฎเค—เฅเคฐเฅ€', chart_machines: 'เคฎเคถเฅ€เคจเฅ‡เค‚', chart_timeline: 'เคธเคฎเคฏเคฐเฅ‡เค–เคพ', chart_hierarchy: 'เคชเคฆเคพเคจเฅเค•เฅเคฐเคฎ', collapse_all: 'เคธเคญเฅ€ เคธเค‚เค•เฅเคทเคฟเคชเฅเคค เค•เคฐเฅ‡เค‚', expand_all: 'เคธเคญเฅ€ เคตเคฟเคธเฅเคคเฅƒเคค เค•เคฐเฅ‡เค‚', res_labor: 'เคถเฅเคฐเคฎ', res_material: 'เคธเคพเคฎเค—เฅเคฐเฅ€', res_machine: 'เคฎเคถเฅ€เคจ', photo_analysis: 'เคซเฅ‹เคŸเฅ‹ เคตเคฟเคถเฅเคฒเฅ‡เคทเคฃ', location: 'เค•เคฎเคฐเฅ‡ เค•เคพ เคชเฅเคฐเค•เคพเคฐ', room_size: 'เค•เฅเคทเฅ‡เคคเฅเคฐเคซเคฒ', work_phase: 'เค•เคพเคฐเฅเคฏ เคชเฅเคฐเค•เคพเคฐ', materials: 'เคธเคพเคฎเค—เฅเคฐเฅ€', validation: 'เคธเคคเฅเคฏเคพเคชเคจ', validation_passed: 'เคธเคญเฅ€ เคœเคพเคเคš เคชเคพเคธ', validation_issues: 'เคฎเฅเคฆเฅเคฆเฅ‡' }\n};\nconst t = translations[langCode] || translations['EN'];\n\n// HELPERS\nfunction formatCurrency(value) {\n if (value === null || value === undefined || isNaN(value)) return 'โ€”';\n try { return new Intl.NumberFormat(locale, { style: 'currency', currency: currency, minimumFractionDigits: 2, maximumFractionDigits: 2 }).format(value); }\n catch (e) { return currencySymbol + value.toFixed(2); }\n}\nfunction formatNumber(value, decimals) {\n if (decimals === undefined) decimals = 3;\n if (value === null || value === undefined || isNaN(value)) return 'โ€”';\n try { return new Intl.NumberFormat(locale, { minimumFractionDigits: decimals, maximumFractionDigits: decimals }).format(value); }\n catch (e) { return value.toFixed(decimals); }\n}\nfunction formatDateTime() {\n try { return new Intl.DateTimeFormat(locale, { year: 'numeric', month: '2-digit', day: '2-digit', hour: '2-digit', minute: '2-digit' }).format(new Date()); }\n catch (e) { return new Date().toISOString().split('T')[0]; }\n}\nfunction escapeHtml(text) {\n if (!text) return '';\n return String(text).replace(/&/g, '&').replace(//g, '>').replace(/\"/g, '"');\n}\n\n// DATA\nconst phases = input.by_phase || [];\nconst costSummary = input.cost_summary || {};\nconst qualityStats = input.quality_stats || {};\nconst grandTotal = costSummary.grand_total_cost || 0;\nconst grandLaborHours = costSummary.grand_labor_hours || 0;\nconst grandResourceCost = costSummary.grand_resource_cost || 0;\nconst grandMaterialCost = costSummary.grand_material_cost || 0;\nconst grandMachineCost = costSummary.grand_machine_cost || 0;\n\nconst totalWorks = qualityStats.total || 0;\nconst qualityHigh = qualityStats.high || 0;\nconst qualityMedium = qualityStats.medium || 0;\nconst qualityLow = qualityStats.low || 0;\nconst qualityNotFound = qualityStats.not_found || 0;\nconst foundRates = qualityHigh + qualityMedium + qualityLow;\nconst foundPercent = qualityStats.found_percent || 0;\n\nconst laborDays = Math.ceil(grandLaborHours / 8);\nconst laborPercent = grandTotal > 0 ? Math.round(grandResourceCost / grandTotal * 100) : 35;\nconst materialPercent = grandTotal > 0 ? Math.round(grandMaterialCost / grandTotal * 100) : 55;\nconst machinesPercent = grandTotal > 0 ? Math.round(grandMachineCost / grandTotal * 100) : 10;\n\nconst dateTimeStr = formatDateTime();\n\nconst phaseChartData = phases.map(function(phase) { return { name: phase.phase_name || 'Phase', cost: phase.phase_total_cost || 0, hours: phase.phase_labor_hours || 0 }; });\n\n// HTML GENERATION\nvar html = `\n\n\n\n${t.doc_title} - ${escapeHtml(projectName)}\n\n\n\n
\n`;\n\n// HEADER\nhtml += '
' + t.doc_title + ' v2
' + escapeHtml(projectName) + '
' + t.pricing_level + ': ' + pricingLevel + ' | ' + dateTimeStr + '
GitHub\"DDC\"
\\n';\n\n// PHOTO INFO\nhtml += '
๐Ÿ“ท ' + t.photo_analysis + '
' + t.location + ': ' + escapeHtml(photoAnalysis.room_type || 'N/A') + '' + t.room_size + ': ' + escapeHtml(photoAnalysis.room_size || 'N/A') + '' + t.work_phase + ': ' + escapeHtml(photoAnalysis.work_phase || 'N/A') + 'Elements: ' + (photoAnalysis.elements_count || 0) + 'Fixtures: ' + (photoAnalysis.fixtures_count || 0) + '';\nif (photoAnalysis.materials && photoAnalysis.materials.length > 0) {\n html += '' + t.materials + ': ' + escapeHtml(photoAnalysis.materials.slice(0, 5).join(', ')) + '';\n}\nhtml += '
\\n';\n\n// VALIDATION BAR\nif (validation.passed) {\n html += '
โœ…' + t.validation_passed + '
\\n';\n} else if (validation.issues && validation.issues.length > 0) {\n html += '
โš ๏ธ' + t.validation_issues + ':';\n validation.issues.forEach(function(issue) {\n html += '' + escapeHtml(issue) + '';\n });\n html += '
\\n';\n}\n\n// CHARTS SECTION\nhtml += '
๐Ÿ’ฐ
' + formatCurrency(grandTotal) + '
' + t.kpi_total + '
โฑ๏ธ
' + formatNumber(grandLaborHours, 0) + ' h
' + t.kpi_hours + '
๐Ÿ“…
' + laborDays + '
' + t.kpi_days + '
' + t.chart_cost_structure + '
' + t.chart_labor + '' + formatCurrency(grandResourceCost) + ' (' + laborPercent + '%)
' + t.chart_material + '' + formatCurrency(grandMaterialCost) + ' (' + materialPercent + '%)
' + t.chart_machines + '' + formatCurrency(grandMachineCost) + ' (' + machinesPercent + '%)
';\n\n// Phase chart\nvar phaseHtml = '';\nfor (var i = 0; i < phaseChartData.length; i++) {\n var p = phaseChartData[i];\n var pct = grandTotal > 0 ? Math.round(p.cost / grandTotal * 100) : 0;\n phaseHtml += '
' + escapeHtml(p.name) + '' + formatCurrency(p.cost) + '
';\n}\n\n// Timeline chart\nvar timelineHtml = '';\nfor (var i = 0; i < phaseChartData.length; i++) {\n var p = phaseChartData[i];\n var phaseDays = Math.ceil(p.hours / 8);\n var widthPct = laborDays > 0 ? Math.min(phaseDays / laborDays * 100, 100) : 100;\n timelineHtml += '
' + escapeHtml(p.name) + '
' + phaseDays + 'd
';\n}\n\nhtml += '
' + t.chart_by_phase + '
' + phaseHtml + '
' + t.chart_timeline + '
' + timelineHtml + '
';\n\n// Treemap\nvar treemapHtml = '';\nfor (var i = 0; i < phaseChartData.length; i++) {\n var p = phaseChartData[i];\n var pct = grandTotal > 0 ? Math.round(p.cost / grandTotal * 100) : 0;\n treemapHtml += '
' + escapeHtml(p.name) + '
' + formatCurrency(p.cost) + '
' + pct + '%
';\n}\nhtml += '
' + t.chart_hierarchy + '
' + treemapHtml + '
\\n';\n\n// TABLE CONTROLS\nhtml += '
\\n';\n\n// QUALITY BAR\nhtml += '
' + t.found_rates + ':' + foundPercent + '%(' + foundRates + '/' + totalWorks + ')
' + qualityHigh + '
' + qualityMedium + '
' + qualityLow + '
' + qualityNotFound + '
';\nif (qualityNotFound > 0) {\n html += '
โš  ' + qualityNotFound + ' ' + t.manual_check + '
';\n}\nhtml += '
\\n';\n\n// TABLE\nhtml += '';\n\n// DATA ROWS\nvar globalWorkIndex = 0;\nfor (var phaseIdx = 0; phaseIdx < phases.length; phaseIdx++) {\n var phase = phases[phaseIdx];\n var phaseNum = phaseIdx + 1;\n var phasePercent = grandTotal > 0 ? ((phase.phase_total_cost || 0) / grandTotal * 100).toFixed(0) : '0';\n \n html += '';\n\n var types = phase.types || [];\n for (var typeIdx = 0; typeIdx < types.length; typeIdx++) {\n var type = types[typeIdx];\n var typeNum = typeIdx + 1;\n var typeName = type.type_name || 'Unknown Type';\n var elementCount = type.element_count || 1;\n var category = type.category || '';\n \n html += '';\n\n var works = type.works || [];\n for (var workIdx = 0; workIdx < works.length; workIdx++) {\n var work = works[workIdx];\n var workNum = workIdx + 1;\n globalWorkIndex++;\n var level = work.quality_level || 'not_found';\n var dotClass = 'dot-notfound';\n if (level === 'high') dotClass = 'dot-high';\n else if (level === 'medium') dotClass = 'dot-medium';\n else if (level === 'low') dotClass = 'dot-low';\n \n var rateCode = work.rate_code || '';\n var codeLink = (rateCode && rateCode !== 'NOT_FOUND') ? '' + escapeHtml(rateCode) + '' : 'โ€”';\n \n var calcDetails = work.calculation_details || {};\n var calcDisplay = '' + escapeHtml(work.calculation_basis || work.source_element || '') + '';\n if (calcDetails.formula_display) {\n calcDisplay += '' + escapeHtml(calcDetails.formula_display) + '';\n }\n \n var workRowClass = 'work';\n if (work.is_demolition) workRowClass += ' work-demolition';\n \n html += '';\n\n var resources = work.resources_all || [];\n for (var resIdx = 0; resIdx < resources.length; resIdx++) {\n var res = resources[resIdx];\n var isLast = resIdx === resources.length - 1;\n var prefix = isLast ? 'โ””' : 'โ”œ';\n var resType = res.resource_type || 'material';\n var tagLabels = { labor: t.res_labor, material: t.res_material, machine: t.res_machine };\n var tagLabel = tagLabels[resType] || t.res_material;\n var tagClass = 'res-tag res-tag-' + resType;\n \n html += '';\n }\n }\n }\n \n html += '';\n}\n\n// GRAND TOTAL\nhtml += '';\nhtml += '';\nhtml += '
' + t.col_pos + '' + t.col_code + '' + t.col_description + '' + t.col_calc + '' + t.col_unit + '' + t.col_qty + '' + t.col_price + '' + t.col_total + '' + t.col_labor + '' + t.col_quality + '
' + phaseNum + 'โ–ผ ' + escapeHtml(phase.phase_name || 'Phase') + '' + formatCurrency(phase.phase_total_cost || 0) + '' + formatNumber(phase.phase_labor_hours || 0, 1) + '' + phasePercent + '%
' + phaseNum + '.' + typeNum + 'โ–ฝ ' + escapeHtml(typeName) + ' (ร—' + elementCount + ')' + escapeHtml(category) + '' + formatCurrency(type.type_total_cost || 0) + '' + formatNumber(type.type_total_labor_hours || 0, 1) + '
' + phaseNum + '.' + typeNum + '.' + workNum + '' + codeLink + 'โ–ฟ ' + (work.is_demolition ? '๐Ÿ”จ ' : '') + escapeHtml(work.rate_name || work.work_name || 'Work') + '' + calcDisplay + '' + escapeHtml(work.rate_unit || work.project_unit || 'โ€”') + '' + formatNumber(work.calculated_quantity || work.quantity_in_rate_units || work.project_quantity || 0, 4) + '' + formatCurrency(work.unit_cost || 0) + '' + formatCurrency(work.total_cost || 0) + '' + formatNumber(work.estimated_labor_hours || 0, 1) + '
' + escapeHtml(res.resource_code || '') + '' + tagLabel + '' + prefix + ' ' + escapeHtml(res.resource_name || 'Resource') + '' + escapeHtml(res.resource_unit || '') + '' + formatNumber(res.scaled_quantity || res.resource_quantity || 0, 4) + '' + formatCurrency(res.price_per_unit || 0) + '' + formatCurrency(res.scaled_cost || res.resource_cost || 0) + '
' + t.subtotal + ' ' + phaseNum + '' + formatCurrency(phase.phase_total_cost || 0) + '' + formatNumber(phase.phase_labor_hours || 0, 1) + '' + phasePercent + '%
' + t.grand_total + '' + formatCurrency(grandTotal) + '' + formatNumber(grandLaborHours, 1) + '100%
' + t.labor_cost + ': ' + formatCurrency(grandResourceCost) + ' (' + laborPercent + '%)' + t.material_cost + ': ' + formatCurrency(grandMaterialCost) + '' + laborDays + ' ' + t.labor_days + '
\\n';\n\n// FOOTER\nhtml += '
OPEN CONSTRUCTION ESTIMATE v2
Professional cost estimation powered by DDC CWICR database | Multi-stage AI decomposition
openconstructionestimate.comGitHubdatadrivenconstruction.io
DDC CWICR โ€” Construction Work Items, Costs & Resources Database | Generated: ' + dateTimeStr + '
\\n';\n\nhtml += '
\\n';\n\n// SCRIPT\nhtml += `\n`;\n\nhtml += '\\n';\n\nreturn {\n json: {\n success: true,\n html_content: html,\n summary: {\n total_cost: grandTotal,\n total_cost_formatted: formatCurrency(grandTotal),\n labor_hours: grandLaborHours,\n labor_days: laborDays,\n works_count: totalWorks,\n found_percent: foundPercent,\n pricing_city: pricingLevel,\n currency: currency\n },\n photo_analysis: photoAnalysis,\n quality_stats: qualityStats,\n validation: validation,\n message: 'โœ… ' + t.doc_title + ' v2! ' + totalWorks + ' works โ†’ ' + formatCurrency(grandTotal) + ' (' + pricingLevel + ')'\n }\n};"},"typeVersion":2},{"id":"286a9e9b-d24d-49b1-aaf1-eaeea6fb079a","name":"Final HTML Output","type":"n8n-nodes-base.code","position":[32448,352],"parameters":{"jsCode":"// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n// FINAL HTML OUTPUT - Returns HTML directly to Form\n// โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•\n\nconst input = $input.first().json;\nconst htmlContent = input.html_content || '

Error

No content generated

';\n\n// Form Trigger with responseMode: lastNode will return this\nreturn {\n json: {\n success: true,\n message: input.message || 'Estimate complete!',\n summary: input.summary || {},\n validation: input.validation || {}\n },\n binary: {\n data: {\n data: Buffer.from(htmlContent, 'utf-8').toString('base64'),\n mimeType: 'text/html',\n fileName: 'PhotoEstimate_v2.html'\n }\n }\n};"},"typeVersion":2},{"id":"b32c35fe-7284-4c29-818b-c8fed8b42ee5","name":"Validation Note","type":"n8n-nodes-base.stickyNote","position":[31696,48],"parameters":{"color":5,"width":260,"height":464,"content":"## โœ… STAGE 7.5: Validation\n\n**Checks performed:**\n1. Minimum 3 work items\n2. Found rate % > 50%\n3. Zero cost items < 30%\n4. Renovation has demolition\n\nGroups works by category:\n- PREPARATION\n- MAIN\n- FINISHING\n- MEP"},"typeVersion":1},{"id":"fec19cc3-f61f-48bd-86a2-d919d0b36b3f","name":"Pipeline Overview","type":"n8n-nodes-base.stickyNote","position":[28688,640],"parameters":{"color":7,"width":328,"height":240,"content":"## ๐Ÿ“Š Pipeline Overview\n\n| Stage | Description |\n|-------|-------------|\n| 1 | Vision analyzes photo |\n| 4 | Decompose to works |\n| 5 | Vector search pricing |\n| 5.2 | Parse & Score results |\n| 7 | Calculate costs |\n| 7.5 | Validate works |\n| 9 | Generate HTML report |"},"typeVersion":1},{"id":"3623a3d0-55cd-4741-bf4e-58b49c7e2bc2","name":"Block 1 Note","type":"n8n-nodes-base.stickyNote","position":[29040,48],"parameters":{"color":5,"width":1080,"height":824,"content":"## Block 1: Photo Upload & Config\n\nThis block:\n- Receives photo from web form\n- Extracts language/region settings\n- Configures Vector DB collection\n- Validates photo presence\n\n**Supported formats:** JPG, PNG, WebP"},"typeVersion":1},{"id":"a8f67a11-ec59-401c-bf06-429aec72f28a","name":"Block 2 Note","type":"n8n-nodes-base.stickyNote","position":[30144,48],"parameters":{"color":6,"width":464,"height":820,"content":"## Block 2: STAGE 1 - Vision Analysis\n\n### ๐Ÿค– AI Photo Analysis\n\nGPT-4 Vision analyzes photo:\n- Detects room type (bathroom, kitchen, etc.)\n- Identifies construction elements\n- Estimates dimensions from references\n- Lists fixtures and materials\n\n**Output:** Structured JSON with elements"},"typeVersion":1},{"id":"fb2c4ced-db96-4bd2-9032-22ccd960fec4","name":"Block 3 Note","type":"n8n-nodes-base.stickyNote","position":[30624,48],"parameters":{"color":6,"width":656,"height":816,"content":"## Block 3: STAGE 4 - Work Decomposition\n\n### ๐Ÿค– AI Decomposition\n\nDecomposes elements into construction works:\n- BATHROOM โ†’ waterproofing, tiling, plumbing\n- KITCHEN โ†’ cabinets, countertops, backsplash\n- FLOOR โ†’ screed, covering, baseboard\n- WALL โ†’ prep, finish, paint\n- MEP โ†’ electrical, plumbing\n\n**Rules:**\n- Minimum 3 works per element\n- Include PREP + MAIN + FINISHING\n- For renovation: add demolition first"},"typeVersion":1},{"id":"9db962cb-16a4-4368-961d-f00fb59edca9","name":"Block 4 Note","type":"n8n-nodes-base.stickyNote","position":[31296,48],"parameters":{"color":5,"width":380,"height":816,"content":"## Block 4: STAGE 5 - Pricing Loop\n\nProcesses each work item:\n\n1. **Vector Search** - Find rates in Qdrant\n2. **Parse Results** - Extract costs & resources\n3. **Quality Scoring** - Rate match quality\n4. **Calculate** - Qty ร— Unit Price\n\n**Database:** DDC CWICR\n700,000+ construction rates"},"typeVersion":1},{"id":"d34124bf-ae65-49e3-b801-4d80f553964d","name":"Vector Search Note","type":"n8n-nodes-base.stickyNote","position":[32768,48],"parameters":{"width":276,"height":176,"content":"### ๐Ÿ” Vector Search\n\nSearches DDC CWICR database:\n- 3072-dim embeddings\n- Top 5 matches per query\n- Multilingual support"},"typeVersion":1},{"id":"581a9ed1-67e0-4677-be4a-921a38abc68e","name":"Parse Score Note","type":"n8n-nodes-base.stickyNote","position":[31696,528],"parameters":{"color":4,"width":1356,"height":336,"content":"### โšก STAGE 5.2 Parse & Score\n\n**FIXED:** Correct document extraction\n\nExtracts from Qdrant results:\n- Total cost from content\n- Rate code, name, unit\n- Resources (labor/material/machine)\n"},"typeVersion":1},{"id":"77b90b95-27a5-4703-90d7-7cc6364d559f","name":"Block 6 Note","type":"n8n-nodes-base.stickyNote","position":[31968,48],"parameters":{"color":5,"width":776,"height":460,"content":"## Block 6: Report Generation\n\n### ๐Ÿ“Š STAGE 9 HTML Report\n**Features:**\n- Professional design\n- Quality indicators (โ— โ—‹)\n- Calculation formulas\n- Clickable rate links\n- Cost structure charts\n- Phase timeline\n- Treemap visualization\n- 9 language support\n\n**Output:** HTML + XLS files"},"typeVersion":1},{"id":"d260439b-2562-4319-b022-cc7954dacb71","name":"AI Models Note","type":"n8n-nodes-base.stickyNote","position":[28688,48],"parameters":{"width":328,"height":232,"content":"## ๐Ÿง  AI Models Used\n\n**GPT-4 Vision** โ€” Photo analysis\n**GPT-4** โ€” Work decomposition\n\nCan be replaced with:\n- Anthropic Claude 3.5\n- Google Gemini Pro\n- OpenRouter models"},"typeVersion":1},{"id":"6ddf3397-f636-42cd-aac2-ade61036c5e4","name":"Qdrant Setup Note","type":"n8n-nodes-base.stickyNote","position":[32768,256],"parameters":{"width":272,"height":248,"content":"### ๐Ÿ“ฅ Vector Database Setup\n\nTo enable search:\n1. Install Qdrant (local or VPS)\n2. Add Qdrant credentials\n3. Upload DDC CWICR dataset\n4. Select collection for your language\n\nCollections available on [GitHub](https://github.com/datadrivenconstruction)"},"typeVersion":1},{"id":"60030e9d-0323-425b-a99f-973e6ec0e077","name":"Info1","type":"n8n-nodes-base.stickyNote","position":[29040,-112],"parameters":{"width":560,"height":144,"content":"# ๐Ÿ“ธ Photo Cost Estimate Pro v2\n\n## Multi-stage AI decomposition pipeline\n\n"},"typeVersion":1},{"id":"809715a7-2395-4fe1-a987-7e8df7c0cdb8","name":"AI Models Note1","type":"n8n-nodes-base.stickyNote","position":[28688,304],"parameters":{"width":328,"height":312,"content":"### Pipeline:\n1. ๐Ÿ“ท GPT-4 Vision โ†’ Elements\n2. ๐Ÿ”„ STAGE 4: Decompose โ†’ Works \n3. ๐Ÿ” Vector Search DDC CWICR\n4. โœ… Validation Stage\n5. ๐Ÿ“Š HTML Report\n\n### Regions (9):\n๐Ÿ‡ฉ๐Ÿ‡ช Berlin | ๐Ÿ‡ฌ๐Ÿ‡ง Toronto | ๐Ÿ‡ท๐Ÿ‡บ St. Petersburg\n๐Ÿ‡ช๐Ÿ‡ธ Barcelona | ๐Ÿ‡ซ๐Ÿ‡ท Paris | ๐Ÿ‡ง๐Ÿ‡ท Sรฃo Paulo\n๐Ÿ‡จ๐Ÿ‡ณ Shanghai | ๐Ÿ‡ฆ๐Ÿ‡ช Dubai | ๐Ÿ‡ฎ๐Ÿ‡ณ Mumbai\n\nโญ **Star our repository** on [GitHub](https://github.com/datadrivenconstruction/OpenConstructionEstimate-DDC-CWICR)"},"typeVersion":1},{"id":"b4e01f61-6023-4851-b7ae-7d555c5059de","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[32368,-112],"parameters":{"width":356,"height":132,"content":"โญ **If you find our tools helpful**, please consider **starring our repository** on [GitHub](https://github.com/datadrivenconstruction/OpenConstructionEstimate-DDC-CWICR). \n\nYour support helps us improve and continue developing open solutions for the community!\n"},"typeVersion":1}],"active":false,"pinData":{},"settings":{"executionOrder":"v1"},"versionId":"56ea10a3-8e5f-4545-95b5-d107d41cad75","connections":{"Wait":{"main":[[{"node":"Restore Work Data","type":"main","index":0}]]},"Accumulate":{"main":[[{"node":"Loop Works","type":"main","index":0}]]},"Embeddings":{"ai_embedding":[[{"node":"Vector Search","type":"ai_embedding","index":0}]]},"Has Photo?":{"main":[[{"node":"STAGE 1 Vision Prompt","type":"main","index":0}],[{"node":"Error No Photo","type":"main","index":0}]]},"Loop Works":{"main":[[{"node":"STAGE 7.5 Aggregate & Validate","type":"main","index":0}],[{"node":"Store Work Data","type":"main","index":0}]]},"GPT-4 Vision":{"ai_languageModel":[[{"node":"STAGE 1 Analyze Photo","type":"ai_languageModel","index":0}]]},"Extract Input":{"main":[[{"node":"Configure Language","type":"main","index":0}]]},"Parse STAGE 1":{"main":[[{"node":"STAGE 4 Decompose Prompt","type":"main","index":0}]]},"Parse STAGE 4":{"main":[[{"node":"Prepare Works","type":"main","index":0}]]},"Prepare Works":{"main":[[{"node":"Loop Works","type":"main","index":0}]]},"Vector Search":{"main":[[{"node":"STAGE 5 Parse & Score","type":"main","index":0}]]},"GPT-4 Decompose":{"ai_languageModel":[[{"node":"STAGE 4 Decompose LLM","type":"ai_languageModel","index":0}]]},"Store Work Data":{"main":[[{"node":"Wait","type":"main","index":0}]]},"Photo Upload Form":{"main":[[{"node":"Extract Input","type":"main","index":0}]]},"Restore Work Data":{"main":[[{"node":"Vector Search","type":"main","index":0}]]},"Configure Language":{"main":[[{"node":"Has Photo?","type":"main","index":0}]]},"STAGE 9 HTML Report":{"main":[[{"node":"Final HTML Output","type":"main","index":0}]]},"STAGE 1 Analyze Photo":{"main":[[{"node":"Parse STAGE 1","type":"main","index":0}]]},"STAGE 1 Vision Prompt":{"main":[[{"node":"STAGE 1 Analyze Photo","type":"main","index":0}]]},"STAGE 4 Decompose LLM":{"main":[[{"node":"Parse STAGE 4","type":"main","index":0}]]},"STAGE 5 Parse & Score":{"main":[[{"node":"Accumulate","type":"main","index":0}]]},"STAGE 4 Decompose Prompt":{"main":[[{"node":"STAGE 4 Decompose LLM","type":"main","index":0}]]},"STAGE 7.5 Aggregate & Validate":{"main":[[{"node":"STAGE 9 HTML Report","type":"main","index":0}]]}}},"lastUpdatedBy":1,"workflowInfo":{"nodeCount":39,"nodeTypes":{"n8n-nodes-base.if":{"count":1},"n8n-nodes-base.set":{"count":2},"n8n-nodes-base.code":{"count":13},"n8n-nodes-base.wait":{"count":1},"n8n-nodes-base.stickyNote":{"count":14},"n8n-nodes-base.formTrigger":{"count":1},"n8n-nodes-base.splitInBatches":{"count":1},"@n8n/n8n-nodes-langchain.chainLlm":{"count":2},"@n8n/n8n-nodes-langchain.lmChatOpenAi":{"count":2},"@n8n/n8n-nodes-langchain.embeddingsOpenAi":{"count":1},"@n8n/n8n-nodes-langchain.vectorStoreQdrant":{"count":1}}},"status":"published","readyToDemo":null,"user":{"name":"Artem Boiko","username":"datadrivenconstruction","bio":"Founder DataDrivenConstruction.io | AEC Tech Consultant & Automation Expert | Bridging Software and Construction","verified":true,"links":["https://datadrivenconstruction.io/"],"avatar":"https://gravatar.com/avatar/96a88b84c9f49338945054d2393a04a29e434a2b60a8937de78e6ef9a6305b5f?r=pg&d=retro&size=200"},"nodes":[{"id":20,"icon":"fa:map-signs","name":"n8n-nodes-base.if","codex":{"data":{"alias":["Router","Filter","Condition","Logic","Boolean","Branch"],"details":"The IF node can be used to implement binary conditional logic in your workflow. 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