{"product_id":"n8n-document-q-a-webhook-with-openai-chat-vector-search","title":"n8n Document Q\u0026A Webhook with OpenAI Chat + Vector Search","description":"\u003ch3\u003eAnswer support questions from your PDFs with an n8n Document Q\u0026amp;A Webhook (OpenAI Chat + Vector Search)\u003c\/h3\u003e\n\u003cp\u003eTurn your existing documents into a searchable knowledge base and expose a secure, header-authenticated \u003cstrong\u003ewebhook\u003c\/strong\u003e that answers customer support questions using \u003cstrong\u003eOpenAI chat\u003c\/strong\u003e—with optional retrieval from your uploaded PDF\/CSV\/TXT content.\u003c\/p\u003e\n\n\u003ch3\u003eWhat this workflow does\u003c\/h3\u003e\n\u003cul\u003e\n  \u003cli\u003e\n\u003cstrong\u003eIngest documents\u003c\/strong\u003e: Receives uploaded \u003cstrong\u003ePDF, CSV, or TXT\u003c\/strong\u003e files via an n8n form and replaces the current \u003cem\u003ein-memory\u003c\/em\u003e knowledge base with the new content.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eBuild a vector index\u003c\/strong\u003e: Splits files into chunks, generates \u003cstrong\u003eembeddings\u003c\/strong\u003e with OpenAI, and stores vectors in an \u003cstrong\u003ein-memory vector store\u003c\/strong\u003e.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eSecure Q\u0026amp;A webhook\u003c\/strong\u003e: Handles a \u003cstrong\u003ePOST\u003c\/strong\u003e request on a \u003cstrong\u003eheader-authenticated webhook\u003c\/strong\u003e containing a \u003cstrong\u003euser message\u003c\/strong\u003e and a \u003cstrong\u003esession_id\u003c\/strong\u003e.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eChat-first support agent\u003c\/strong\u003e: Uses an OpenAI-based support agent with a \u003cstrong\u003esystem prompt\u003c\/strong\u003e and \u003cstrong\u003e15-message conversation memory\u003c\/strong\u003e to answer directly when possible.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eRetrieve facts when needed\u003c\/strong\u003e: If the agent requires document grounding, it runs a retrieval agent that searches the in-memory vector store and returns \u003cstrong\u003esourced information only\u003c\/strong\u003e.\u003c\/li\u003e\n  \u003cli\u003e\n\u003cstrong\u003eReturns plain text\u003c\/strong\u003e: Formats the final response as \u003cstrong\u003eplain text\u003c\/strong\u003e and sends it back in the webhook response.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003eUse cases\u003c\/h3\u003e\n\u003cul\u003e\n  \u003cli\u003eEnable SaaS support teams to answer billing, policy, or product questions from internal documentation.\u003c\/li\u003e\n  \u003cli\u003eAutomate knowledge-based responses for onboarding FAQs uploaded as PDFs or text files.\u003c\/li\u003e\n  \u003cli\u003eProvide consistent answers by using a session_id for short, session-based conversation context.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003eTechnical details\u003c\/h3\u003e\n\u003cul\u003e\n  \u003cli\u003eWorkflow category: \u003cstrong\u003en8n automation workflow\u003c\/strong\u003e\n\u003c\/li\u003e\n  \u003cli\u003eKey nodes\/steps: \u003cstrong\u003eset\u003c\/strong\u003e, \u003cstrong\u003ewebhook\u003c\/strong\u003e, \u003cstrong\u003esticky note\u003c\/strong\u003e, \u003cstrong\u003eform trigger\u003c\/strong\u003e, \u003cstrong\u003en8nn8n-nodes-langchainagent\u003c\/strong\u003e (OpenAI support agent + retrieval), and \u003cstrong\u003erespond to webhook\u003c\/strong\u003e.\u003c\/li\u003e\n  \u003cli\u003eIntegrations\/requirements: OpenAI for \u003cstrong\u003eembeddings\u003c\/strong\u003e and \u003cstrong\u003echat model\u003c\/strong\u003e; an \u003cstrong\u003eHTTP Header Auth credential\u003c\/strong\u003e for the webhook.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eSEO tip:\u003c\/strong\u003e Ideal for teams building an “\u003cstrong\u003eOpenAI document Q\u0026amp;A\u003c\/strong\u003e” system inside \u003cstrong\u003en8n\u003c\/strong\u003e with “\u003cstrong\u003evector search\u003c\/strong\u003e” over “\u003cstrong\u003ePDF\/CSV\/TXT\u003c\/strong\u003e”.\u003c\/p\u003e","brand":"N8N Commerce","offers":[{"title":"Default Title","offer_id":45878611148979,"sku":"N8N-18572","price":73.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0749\/6279\/6723\/files\/KsU_zJ6RdrCpcj_nneFwK_D8zMvXEP.png?v=1787389379","url":"https:\/\/buyflowscripts.com\/products\/n8n-document-q-a-webhook-with-openai-chat-vector-search","provider":"N8N Commerce","version":"1.0","type":"link"}