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+{"id":"7PVU0dnK3csdntrn","meta":{"instanceId":"f50c4225657041a867073dfd116003f9f3659e08e71fb6a5bb5c90807373de2c","templateCredsSetupCompleted":true},"name":"PageIndex RAG - Vectorless PDF Q&A","tags":[],"nodes":[{"id":"cb4bce05-a6d3-40a6-8611-d1b5f9ecde1b","name":"Sticky Note - Summary","type":"n8n-nodes-base.stickyNote","position":[4224,2016],"parameters":{"color":7,"width":608,"height":576,"content":"##  🧠 Workflow Summary\n\n**PageIndex Vectorless RAG Bot**\n\n\nThis workflow builds a vectorless RAG system using [PageIndex](https://pageindex.ai) — no embeddings, no vector database. PageIndex builds a hierarchical tree index (like a Table of Contents) from your PDF, and the LLM reasons over that tree to find precise answers.\n\n\n---\n\n\n**📄 Flow 1 — PDF Upload (Run Once)**\nSend a PDF file to the Telegram bot. It downloads and indexes it on PageIndex cloud.\n\n**💬 Flow 2 — Q&A (Runs Every Time)**\nSend any question to the Telegram bot. It fetches all your indexed docs, passes them to PageIndex LLM reasoning, and returns a cited answer.\n\n\n---\n\n**🔑 Required Credentials**\n- Telegram Bot Token (via @BotFather)\n- PageIndex API Key (via dash.pageindex.ai)\n\n**💡 How PageIndex Works**\nInstead of vector similarity search, PageIndex builds a tree of section summaries. The LLM reads the tree, decides which sections are relevant, retrieves only those, and generates the answer — with page citations included."},"typeVersion":1},{"id":"669aff95-ffe9-499d-97d0-5f9d3a02054f","name":"Sticky Note - Flow 1 Header","type":"n8n-nodes-base.stickyNote","position":[4848,2016],"parameters":{"color":5,"width":856,"height":96,"content":"## 📄 Flow 1 -> PDF Knowledge Upload\nRun this flow by sending a PDF file to the Telegram bot. The PDF is downloaded and indexed on PageIndex cloud. Run once per document."},"typeVersion":1},{"id":"e5526cd9-4df7-48a8-8098-77fb89f4188f","name":"Sticky Note - Receive PDF","type":"n8n-nodes-base.stickyNote","position":[4848,2128],"parameters":{"width":258,"height":472,"content":"### 📎 Receive PDF Document\n**Purpose:** Entry point for PDF upload flow. Listens for incoming Telegram messages that contain a file/document.\n\n**Input:** Telegram message with a PDF attachment\n**Output:** `message.document.file_id` used to download the file\n\n**Note:** Only send PDF files here. Other file types will cause errors downstream."},"typeVersion":1},{"id":"ebbd31aa-c73c-4489-ac06-563ed1107fd4","name":"Sticky Note - Download PDF","type":"n8n-nodes-base.stickyNote","position":[5120,2128],"parameters":{"width":274,"height":472,"content":"### ⬇️ Download PDF File\n**Purpose:** Downloads the PDF binary from Telegram's file storage using the `file_id`.\n\n**Input:** `message.document.file_id` from Telegram Trigger\n**Output:** Binary PDF file data\n\n**Note:** Telegram stores files temporarily. This node fetches the actual file content before it expires."},"typeVersion":1},{"id":"2a06e5cd-e74d-4ab1-a82a-a21b2ac9b1b0","name":"Sticky Note - Index PDF","type":"n8n-nodes-base.stickyNote","position":[5408,2128],"parameters":{"width":290,"height":472,"content":"### ☁️ Index PDF on PageIndex\n**Purpose:** Uploads the PDF to PageIndex cloud. PageIndex builds a hierarchical tree index (TOC) using LLM - no vectors.\n\n**Input:** Binary PDF data\n**Output:** `doc_id` (e.g. `pi-abc123`) assigned to this document\n\n**Note:** Processing takes 10–60s depending on PDF size. The doc is stored permanently."},"typeVersion":1},{"id":"57988369-c99a-4be1-b8c6-a8e80749f56d","name":"Receive PDF Document","type":"n8n-nodes-base.telegramTrigger","position":[4928,2432],"webhookId":"f75f357f-e414-4f95-a956-4df18a9ca6fa","parameters":{"updates":["message"],"additionalFields":{}},"credentials":{"telegramApi":{"id":"YlmcnSgYYsULTVHI","name":"Telegram account"}},"typeVersion":1.2},{"id":"35a146e0-cba2-4e9a-a766-821f5becea38","name":"Download PDF File","type":"n8n-nodes-base.telegram","position":[5216,2432],"webhookId":"56257dbd-8ec0-4248-98f3-c6a1d5a746d5","parameters":{"fileId":"={{ $json.message.document.file_id }}","resource":"file","additionalFields":{}},"credentials":{"telegramApi":{"id":"YlmcnSgYYsULTVHI","name":"Telegram account"}},"typeVersion":1.2},{"id":"140249e8-c6f3-4e70-a6b7-e32dd3023320","name":"Index PDF on PageIndex","type":"n8n-nodes-base.httpRequest","position":[5504,2432],"parameters":{"url":"https://api.pageindex.ai/doc/","method":"POST","options":{},"sendBody":true,"contentType":"multipart-form-data","sendHeaders":true,"bodyParameters":{"parameters":[{"name":"file","parameterType":"formBinaryData","inputDataFieldName":"data"}]},"headerParameters":{"parameters":[{"name":"api_key","value":"YOUR_PAGEINDEX_API_KEY"}]}},"typeVersion":4.2},{"id":"04057de2-5fec-45fb-8824-68a204192fd4","name":"Sticky Note - Flow 2 Header","type":"n8n-nodes-base.stickyNote","position":[4224,2624],"parameters":{"color":4,"width":1466,"height":80,"content":"## 💬 Flow 2 -> Q&A Chat\nRun this flow by sending any text message to the Telegram bot. It fetches all indexed docs, sends the question to PageIndex LLM reasoning, and returns a cited answer to the same user."},"typeVersion":1},{"id":"64697575-d379-4f4d-8d3e-2666019ebd6d","name":"Sticky Note - Receive Question","type":"n8n-nodes-base.stickyNote","position":[4224,2720],"parameters":{"color":6,"width":290,"height":519,"content":"### 💬 Receive User Question\n**Purpose:** Entry point for Q&A flow. Listens for text messages sent to the Telegram bot.\n\n**Input:** Telegram text message from user\n**Output:** `message.text` (the question) and `message.from.id` (for reply routing)\n\n**Note:** Any text message triggers this flow. The answer is always sent back to the same user."},"typeVersion":1},{"id":"622fbf87-1349-4de5-82ba-27fdf02e49d8","name":"Sticky Note - Fetch Docs","type":"n8n-nodes-base.stickyNote","position":[4528,2720],"parameters":{"color":6,"width":258,"height":519,"content":"### 📚 Fetch All Indexed Documents\n**Purpose:** Retrieves the list of all documents already indexed in your PageIndex account.\n\n**Input:** PageIndex API key (header)\n**Output:** Array of document objects including `id`, `name`, `status`, `pageNum`\n\n**Note:** Only documents with `status: completed` are ready for querying."},"typeVersion":1},{"id":"6fb9f267-cb04-4155-82f8-9eae020cefdb","name":"Sticky Note - Extract IDs","type":"n8n-nodes-base.stickyNote","position":[4800,2720],"parameters":{"color":6,"width":258,"height":519,"content":"### 🔑 Extract Document IDs\n**Purpose:** Maps the documents array into a clean array of `doc_id` strings for use in the chat API.\n\n**Input:** `documents` array from PageIndex\n**Output:** `doc_ids` array (e.g. `[\"pi-abc123\", \"pi-def456\"]`)\n\n**Note:** Passing multiple doc_ids allows PageIndex to reason across all your indexed documents at once."},"typeVersion":1},{"id":"534a8b8e-f17c-4042-a2ac-d2ed8706bb4d","name":"Sticky Note - LLM Reasoning","type":"n8n-nodes-base.stickyNote","position":[5072,2720],"parameters":{"color":6,"width":338,"height":519,"content":"### 🧠 LLM Reasoning over Document Tree\n**Purpose:** Core RAG step. Sends the user question + all doc_ids to PageIndex. The LLM reasons over the hierarchical tree index to find and retrieve the most relevant sections.\n\n**Input:** User question + `doc_ids` array\n**Output:** LLM-generated answer with page citations\n\n**Note:** No vector search involved. PageIndex uses tree traversal + LLM reasoning."},"typeVersion":1},{"id":"f4cc58b5-26fd-4096-bef2-785a5f294d90","name":"Sticky Note - Send Answer","type":"n8n-nodes-base.stickyNote","position":[5424,2720],"parameters":{"color":6,"width":274,"height":519,"content":"### 📤 Send Answer to User\n**Purpose:** Delivers the LLM-generated answer back to the user on Telegram.\n\n**Input:** `choices[0].message.content` from PageIndex response\n**Output:** Text message sent to the user's Telegram chat\n\n**Note:** Reply is routed using `message.from.id` so each user gets their own response."},"typeVersion":1},{"id":"369a3577-6c59-4d02-a551-a6cab6308a20","name":"Receive User Question","type":"n8n-nodes-base.telegramTrigger","position":[4320,3040],"webhookId":"f9e85743-0681-4314-997e-302ff57aec75","parameters":{"updates":["message"],"additionalFields":{}},"credentials":{"telegramApi":{"id":"YlmcnSgYYsULTVHI","name":"Telegram account"}},"typeVersion":1.2},{"id":"22cab621-7b73-465f-81e1-8531cb3fcfcc","name":"Fetch All Indexed Documents","type":"n8n-nodes-base.httpRequest","position":[4608,3040],"parameters":{"url":"https://api.pageindex.ai/docs","options":{},"sendHeaders":true,"headerParameters":{"parameters":[{"name":"api_key","value":"YOUR_PAGEINDEX_API_KEY"}]}},"typeVersion":4.4},{"id":"e320a50f-32a7-4bcc-a9c6-d9e09192652d","name":"Extract Document IDs","type":"n8n-nodes-base.set","position":[4880,3040],"parameters":{"options":{},"assignments":{"assignments":[{"id":"59845b9c-a89b-41a0-a038-ec0f8d06bf91","name":"doc_ids","type":"array","value":"={{ $json.documents.map(d => d.id) }}"}]}},"typeVersion":3.4},{"id":"b697c98a-4b45-446b-8a72-0765b411e305","name":"LLM Reasoning over Document Tree","type":"n8n-nodes-base.httpRequest","position":[5200,3040],"parameters":{"url":"https://api.pageindex.ai/chat/completions","method":"POST","options":{},"jsonBody":"={\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"{{ $('Receive User Question').item.json.message.text }}\"\n    }\n  ],\n  \"stream\": false,\n  \"doc_id\": {{ JSON.stringify($json.doc_ids) }},\n  \"temperature\": 0.5,\n  \"enable_citations\": false\n}","sendBody":true,"sendHeaders":true,"specifyBody":"json","headerParameters":{"parameters":[{"name":"api_key","value":"YOUR_PAGEINDEX_API_KEY"},{"name":"Content-Type","value":"application/json"}]}},"typeVersion":4.2},{"id":"9632028b-74b7-46f2-897b-7b22ed91de11","name":"Send Answer to User","type":"n8n-nodes-base.telegram","position":[5504,3040],"webhookId":"cd17bf60-aec0-468f-a0f6-70b4681a662c","parameters":{"text":"={{ $json.choices[0].message.content }}","chatId":"={{ $('Receive User Question').item.json.message.from.id }}","additionalFields":{}},"credentials":{"telegramApi":{"id":"YlmcnSgYYsULTVHI","name":"Telegram account"}},"typeVersion":1.2}],"active":false,"pinData":{},"settings":{"binaryMode":"separate","availableInMCP":false,"executionOrder":"v1"},"versionId":"d98e663c-e64f-4450-af7f-af70ecd02ef0","connections":{"Download PDF File":{"main":[[{"node":"Index PDF on PageIndex","type":"main","index":0}]]},"Extract Document IDs":{"main":[[{"node":"LLM Reasoning over Document Tree","type":"main","index":0}]]},"Receive PDF Document":{"main":[[{"node":"Download PDF File","type":"main","index":0}]]},"Receive User Question":{"main":[[{"node":"Fetch All Indexed Documents","type":"main","index":0}]]},"Index PDF on PageIndex":{"main":[[]]},"Fetch All Indexed Documents":{"main":[[{"node":"Extract Document IDs","type":"main","index":0}]]},"LLM Reasoning over Document Tree":{"main":[[{"node":"Send Answer to User","type":"main","index":0}]]}}}
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