{"workflow":{"id":12981,"name":"Turn any website into an AI support chatbot with OpenAI and Pinecone","views":251,"recentViews":1,"totalViews":251,"createdAt":"2026-01-25T09:05:45.730Z","description":"# Complete AI support system using website data (RAG pipeline)\n\nThis template provides a full end-to-end Retrieval-Augmented Generation (RAG) system using n8n. It includes two connected workflows:\n\n1. A data ingestion pipeline that crawls a website and stores its content in a vector database.\n2. A customer support chatbot that retrieves this knowledge and answers user queries in real time.\n\nTogether, these workflows allow you to turn any public website into an intelligent AI-powered support assistant grounded in real business data.\n\n---\n\n## Use cases\n\n- AI customer support chatbot for your website  \n- Internal company knowledge assistant  \n- Product FAQ automation  \n- Helpdesk or IT support bot  \n- AI receptionist for services  \n- Semantic search over company content  \n\n---\n\n## How it works\n\n### Ingestion workflow\n1. Discover all URLs from a website sitemap.\n2. Filter and normalize the URLs.\n3. Fetch each page and extract readable text.\n4. Clean HTML into plain text.\n5. Split text into overlapping chunks.\n6. Generate embeddings using OpenAI.\n7. Store vectors in Pinecone with metadata.\n\n### Chatbot workflow\n1. A user sends a message via chat webhook.\n2. The agent queries Pinecone for relevant knowledge.\n3. Retrieved content is passed to OpenAI.\n4. OpenAI generates a grounded response.\n5. Short-term memory maintains conversation context.\n\n---\n\n## How to use\n\n### Step 1 – Run ingestion\n1. Set your target website URL.\n2. Add Firecrawl, OpenAI, and Pinecone credentials.\n3. Create a Pinecone index.\n4. Execute the ingestion workflow.\n5. Wait until all pages are indexed.\n\n### Step 2 – Run chatbot\n1. Deploy the chatbot workflow.\n2. Set the same Pinecone index and namespace.\n3. Copy the chat webhook URL.\n4. Connect it to a website, chat widget, or WhatsApp bot.\n5. Start chatting with your AI assistant.\n\n---\n\n## Requirements\n\n- Firecrawl account  \n- OpenAI API key  \n- Pinecone account and index  \n- Public website to crawl  \n- Optional: frontend chat interface  \n\n---\n\n## Good to know\n\n- The chatbot never answers from memory for business data.\n- All company knowledge comes from Pinecone.\n- If Pinecone returns nothing, the bot fails safely.\n- HTML cleaning is basic and can be replaced with:\n  - Mozilla Readability  \n  - Jina Reader  \n  - Unstructured  \n- Chunk size and overlap affect retrieval quality.\n- Pinecone can be replaced with:\n  - Qdrant  \n  - Weaviate  \n  - Supabase Vector  \n  - Chroma  \n\n---\n\n## Customising this workflow\n\nYou can extend this system by:\n- Adding PDF or document loaders\n- Scheduling ingestion daily or weekly\n- Connecting CRM or ticketing systems\n- Adding appointment booking tools\n- Switching to local or open-source models\n- Adding multilingual support\n- Storing raw content in a database\n- Adding feedback or logging\n\n---\n\n## What this n8n template demonstrates\n\n- Real-world RAG architecture  \n- Web crawling pipelines  \n- Text chunking strategies  \n- Vector database integration  \n- AI agent orchestration  \n- Memory-controlled conversations  \n- Production-grade AI support systems  \n- End-to-end AI infrastructure with n8n  \n\n---\n\n## Architecture overview\n\nThis template follows a modern AI system design:\n\nWebsite → Ingestion → Embeddings → Pinecone → Retrieval → OpenAI → User\n\nIt separates:\n- Data preparation (offline)\n- Knowledge storage\n- Runtime inference\n\nThis makes the system scalable, maintainable, and safe for production use.\n\n---\n\n## Need a custom setup?\n\nIf you want a similar AI system built for your business (custom data sources, CRM integration, WhatsApp bots, booking systems, dashboards, or private deployments), feel free to reach out at dinakars2003@gmail.com.\n\nI help companies design and deploy production-ready AI workflows.\n\n","workflow":{"id":"78rVOQa5gbWxRnJN","meta":{"instanceId":"ea40b8f0e8331542bdc90e5117ede392a0c9898ee6a6065ec70d324338578de7","templateCredsSetupCompleted":true},"name":"Turn any website into an AI customer support chatbot (OpenAI + Pinecone)","tags":[],"nodes":[{"id":"8ecff878-cb1f-4e9c-98a0-3727269aee97","name":"When clicking ‘Execute workflow’","type":"n8n-nodes-base.manualTrigger","position":[-1904,208],"parameters":{},"typeVersion":1},{"id":"23adecea-f54b-49c7-8ac6-75df99bcc469","name":"Embeddings OpenAI","type":"@n8n/n8n-nodes-langchain.embeddingsOpenAi","position":[592,384],"parameters":{"options":{}},"credentials":{"openAiApi":{"id":"PLmLnnIQ0GklOwGP","name":"n8n free OpenAI API credits"}},"typeVersion":1.2},{"id":"673fa27a-9f5d-4a3c-8807-64c26aaaa576","name":"Map Website URLs","type":"@mendable/n8n-nodes-firecrawl.firecrawl","position":[-1632,208],"parameters":{"url":"<your-website-url>","sitemap":"only","operation":"map","requestOptions":{},"includeSubdomains":true},"credentials":{"firecrawlApi":{"id":"VEArGbZc3LNjRfBE","name":"Codritions Firecrawl account"}},"retryOnFail":true,"typeVersion":1},{"id":"d17427ae-ce8c-4015-af2d-c20a44acc11c","name":"Filter and Normalize URLs","type":"n8n-nodes-base.code","position":[-1296,208],"parameters":{"jsCode":"// input: { success: true, links: [ { url: \"...\" } ] }\n\nconst links = $json.links || [];\nconst seen = new Set();\n\nconst blockedKeywords = [\n  \"/press-blog\",\n  \"/newsletter\",\n  \"/assets-vault\",\n  \"press\",\n  \"gallery\",\n  \"project\",\n  \"newsletter\"\n];\n\nreturn links\n  .filter(link => {\n    let url = link.url;\n    if (!url) return false;\n\n    // ❌ Remove blocked keywords\n    for (const keyword of blockedKeywords) {\n      if (url.includes(keyword)) return false;\n    }\n\n    // ❌ Remove XML files\n    if (url.includes(\".xml\")) return false;\n\n    // 🔄 Normalize trailing slash\n    url = url.endsWith(\"/\") ? url.slice(0, -1) : url;\n\n    // ❌ Remove duplicates\n    if (seen.has(url)) return false;\n    seen.add(url);\n\n    // Save normalized URL back\n    link.url = url;\n    return true;\n  })\n  .map(link => {\n    return {\n      url: link.url\n    };\n  });\n"},"typeVersion":2},{"id":"bd51e7d4-485c-4759-b4f1-63b2d1219c35","name":"Process URLs One by One","type":"n8n-nodes-base.splitInBatches","position":[-960,208],"parameters":{"options":{}},"typeVersion":3},{"id":"37897ec6-0cb2-481a-a7ad-15046192720d","name":"Fetch Page Content","type":"n8n-nodes-base.httpRequest","position":[-624,128],"parameters":{"url":"={{ $json.url }}","options":{"redirect":{"redirect":{"followRedirects":true}}}},"retryOnFail":true,"typeVersion":3,"continueOnFail":true},{"id":"ddca10bf-eaca-47a3-8a8a-64ad2e247bfc","name":"Extract HTML and URL","type":"n8n-nodes-base.set","position":[-368,128],"parameters":{"options":{},"assignments":{"assignments":[{"id":"f84fa14c-2e29-46ef-a914-2267eb52b815","name":"html","type":"string","value":"={{ $json.data ?? $json.html ?? \"\" }}"},{"id":"096f51e1-e470-4fde-8d62-3338ffcc4f6b","name":"url","type":"string","value":"={{ $json.url ?? $('Process URLs One by One').item.json.url }}"}]}},"typeVersion":3.4},{"id":"e5da4265-7bb0-4b01-b6dd-97ede548b7c3","name":"Clean HTML to Text","type":"n8n-nodes-base.code","position":[-176,128],"parameters":{"mode":"runOnceForEachItem","jsCode":"const html = $json.html;\n\n// VERY simple cleaner (replace later with readability)\nconst text = html\n  .replace(/<script[\\s\\S]*?<\\/script>/gi, '')\n  .replace(/<style[\\s\\S]*?<\\/style>/gi, '')\n  .replace(/<[^>]+>/g, ' ')\n  .replace(/\\s+/g, ' ')\n  .trim();\n\nreturn {\n  url: $json.url,\n  project_id: $json.project_id,\n  text\n};\n"},"typeVersion":2},{"id":"f5c3ea61-c855-47e2-9110-3242ca6c0ce3","name":"Check Text Length","type":"n8n-nodes-base.if","position":[48,128],"parameters":{"options":{},"conditions":{"options":{"version":3,"leftValue":"","caseSensitive":true,"typeValidation":"loose"},"combinator":"and","conditions":[{"id":"aa3e5022-2d6d-43f6-bf87-9de112a3345f","operator":{"type":"boolean","operation":"true","singleValue":true},"leftValue":"={{$json.text.length > 50}}","rightValue":""}]},"looseTypeValidation":true},"typeVersion":2.3},{"id":"ba89389e-2dcc-4aa1-8f2a-7746641df62c","name":"Split Text into Chunks","type":"n8n-nodes-base.code","position":[272,112],"parameters":{"jsCode":"const raw = $json.text || \"\";\nconst text = raw.replace(/\\s+/g, \" \").trim(); // clean whitespace\nconst chunkSize = 1000;\nconst overlap = 200;\n\nconst chunks = [];\nlet i = 0;\n\nwhile (i < text.length) {\n  const chunk = text.slice(i, i + chunkSize).trim();\n\n  // Only save useful chunks\n  if (chunk.length > 50) {\n    chunks.push({\n      content: chunk,\n      url: $json.url,\n      project_id: $json.project_id\n    });\n  }\n\n  i += chunkSize - overlap;\n}\n\nreturn chunks;\n"},"typeVersion":2},{"id":"a9947307-f9f7-4280-860f-a9f18c81e530","name":"Store in Vector Database","type":"@n8n/n8n-nodes-langchain.vectorStorePinecone","position":[624,192],"parameters":{"mode":"insert","options":{"pineconeNamespace":"<your-pinecone-namespace-name>"},"pineconeIndex":{"__rl":true,"mode":"list","value":""}},"typeVersion":1.3},{"id":"faeb8ce7-2e62-4782-840c-fde4f70d1be0","name":"Document Loader","type":"@n8n/n8n-nodes-langchain.documentDefaultDataLoader","position":[784,400],"parameters":{"options":{"metadata":{"metadataValues":[{"name":"url","value":"={{ $json.url }}"},{"name":"content","value":"={{ $json.content }}"}]}}},"typeVersion":1.1},{"id":"f13244de-8266-41a1-a918-474ab0021376","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-2720,0],"parameters":{"width":592,"height":688,"content":"## Turn any website into an AI‑powered customer‑support chatbot (Open AI + Pinecone)\n\n### How it works\n1️⃣ **Discover URLs** – Firecrawl reads the sitemap (including sub‑domains) and returns every page URL.  \n2️⃣ **Clean & de‑duplicate** – JavaScript removes unwanted paths (press‑blog, newsletter, assets, .xml), trailing slashes and duplicate links.  \n3️⃣ **Controlled crawling** – the remaining URLs are processed one‑by‑one, fetching the raw HTML.  \n4️⃣ **HTML → plain text** – script/style tags are stripped and the rest of the markup is turned into readable text.  \n5️⃣ **Validate & chunk** – pages shorter than 50 chars are ignored; the rest is split into 1 000‑char chunks with a 200‑char overlap.  \n6️⃣ **Embed & store** – each chunk is turned into an OpenAI embedding and up‑serted into a Pinecone index (namespace = your‑site‑name).  \n7️⃣ **Chat endpoint** – a LangChain agent receives a user message, decides (via the system prompt) whether to call the Pinecone retrieval tool, and replies **only** with information that actually exists in the vector store.\n\n### Setup steps\n1️⃣ Add your **Firecrawl** API key (Credentials → Firecrawl).  \n2️⃣ Add your **OpenAI** API key (Credentials → OpenAI).  \n3️⃣ Create a **Pinecone** index (1536 dimensions for `text‑embedding‑ada‑002`).  \n4️⃣ Put the index name and a namespace into the “Store in Vector Database” node.  \n5️⃣ Replace `<your-website-url>` in the *Map Website URLs* node.  \n6️⃣ Execute the workflow – it will fill the vector store.  \n7️⃣ Deploy the **Chat Trigger** webhook (copy the URL) and embed it in your front‑end.\n\nWhen the index is populated the bot will answer any product, policy or FAQ question without hallucinations.\n"},"typeVersion":1},{"id":"18ac8782-ba5b-41e6-b45c-161b329c1b7f","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[-1696,80],"parameters":{"color":2,"height":304,"content":"URL Discovery – Firecrawl reads the sitemap (including sub‑domains) and returns every page URL.\n"},"typeVersion":1},{"id":"026d9947-3d50-40f3-a6fd-369101cde755","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[-1376,80],"parameters":{"color":2,"width":560,"height":304,"content":"## URL Cleaning & Batching\nJavaScript removes press‑blog, newsletter, assets‑vault, .xml files, trailing slashes and duplicate URLs. \n\nThen SplitInBatches processes the list one‑by‑one.\n"},"typeVersion":1},{"id":"27cd19ce-584d-4f2a-9cf3-af3e6c7644d8","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[-704,48],"parameters":{"color":3,"width":672,"height":240,"content":"Page Fetch & Text Extraction – HTTP request gets the HTML, a Set node normalises fields, and a small JS step strips script/style tags and converts the markup to plain readable text.\n"},"typeVersion":1},{"id":"0d1813dd-26c7-4db4-98b0-07bece863767","name":"When chat message received","type":"@n8n/n8n-nodes-langchain.chatTrigger","position":[-1856,752],"webhookId":"4091fa09-fb9a-4039-9411-7104d213f601","parameters":{"mode":"webhook","public":true,"options":{"allowedOrigins":"*"},"availableInChat":true},"typeVersion":1.1},{"id":"c8283ada-3684-4a1e-b26b-f7c341730c83","name":"Chat Memory","type":"@n8n/n8n-nodes-langchain.memoryBufferWindow","position":[-1504,976],"parameters":{"contextWindowLength":10},"typeVersion":1.3},{"id":"953a61ab-99c4-437d-b180-9656dfc9ccc6","name":"Customer Support Agent","type":"@n8n/n8n-nodes-langchain.agent","position":[-1600,752],"parameters":{"options":{"maxIterations":10,"systemMessage":"=You are **Alicia**, an AI customer support assistant for our company.\n\nToday's date is {{ $now.format('yyyy-MM-dd') }}.\nUse this date as the only reference for relative time.\n\n========================\nPRIMARY RULE\n========================\n\nAll business-related information MUST come from tools.\n\nThis includes:\n- Products\n- Services\n- Company information\n- Website content\n- Policies and FAQs\n- Pricing and availability\n- Contact details\n\nDo NOT answer these from memory or assumptions.\nIf a relevant tool exists, you MUST use it.\n\n========================\nPINECONE USAGE (CRITICAL)\n========================\n\nUse the Pinecone vector store whenever the user asks about:\n- Products or services\n- What the company offers\n- Policies, pricing, FAQs\n- Company or website information\n\nDo NOT use Pinecone for:\n- General greetings\n- Small talk\n- Personal details\n- Appointment scheduling\n\nIf Pinecone returns:\n- No results\n- Empty data\n- Errors\n\nReply:\n\"I could not find that information. Would you like me to create a support ticket for you?\"\n\n========================\nMEMORY USAGE\n========================\n\nMemory may only be used for:\n- Name\n- Email\n- Phone number\n\nAnd only after:\n- A successful booking or confirmed interaction.\n\nNever use memory for:\n- Products\n- Services\n- Company info\n- Availability\n\n========================\nGREETING RULE\n========================\n\nIf the user only says:\n\"Hi\", \"Hello\", or \"Hey\"\n\nReply exactly:\n\"Hi, how can I help you today?\"\n\nNo tools.\nNo extra text.\n\n========================\nRESPONSE RULES\n========================\n\n- Be friendly and conversational.\n- Use short, clear sentences.\n- Never mention internal tools.\n- Never invent information.\n- Never explain your reasoning.\n- Never say \"as an AI\".\n\n========================\nLINK RULE\n========================\n\nIf a link is included:\n- Use Markdown format: [Link text](URL)\n- Never show raw URLs.\n- Links must come from tool output only.\n\n========================\nFAILURE RULE\n========================\n\nIf any required tool fails:\n\nReply exactly:\n\"I could not find that information. Would you like me to create a support ticket for you?\"\n\nNo variations.\nNo extra text.\n\n========================\nEND\n========================\n","returnIntermediateSteps":false}},"typeVersion":3},{"id":"a7128a69-d4f9-43e2-af49-3c6b903a0719","name":"OpenAI Chat Model","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[-1600,1168],"parameters":{"model":{"__rl":true,"mode":"list","value":"gpt-4.1-mini","cachedResultName":"gpt-4.1-mini"},"options":{},"builtInTools":{}},"credentials":{"openAiApi":{"id":"22agvGuZZNbxxru1","name":"OpenAi account"}},"typeVersion":1.3},{"id":"f1b6383c-14c4-4562-b89f-3c50715e5fca","name":"OpenAI Embeddings","type":"@n8n/n8n-nodes-langchain.embeddingsOpenAi","position":[-1328,1152],"parameters":{"options":{}},"credentials":{"openAiApi":{"id":"22agvGuZZNbxxru1","name":"OpenAi account"}},"typeVersion":1.2},{"id":"829e903c-08f8-433f-9650-456e3f267f14","name":"Pinecone Vector Storage","type":"@n8n/n8n-nodes-langchain.vectorStorePinecone","position":[-1376,976],"parameters":{"mode":"retrieve-as-tool","topK":10,"options":{"pineconeNamespace":"<your-pinecone-namespace-name>"},"pineconeIndex":{"__rl":true,"mode":"list","value":""},"toolDescription":"=Use this tool whenever the user asks anything about Blushu, our services, company info, website content, product/service details, policies, FAQs, contact information, pricing, or questions that require knowledge from the company knowledge base. \n"},"typeVersion":1.3},{"id":"4a195c24-4dbe-47d4-8f0d-9bd64630f55a","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[224,-16],"parameters":{"color":4,"width":688,"height":528,"content":"## Chunking & Embedding\n\nIf the cleaned text > 50 chars it is split into 1 000‑char chunks (200‑char overlap). 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