Telegram RAG pdf
Answer questions about your PDF documents directly within Telegram using this powerful RAG (Retrieval Augmented Generation) workflow. This automation connects Telegram, Pinecone, and OpenAI to create an intelligent chatbot experience. When a user sends a PDF file to your Telegram bot, the workflow automatically downloads the document, splits its content into manageable chunks, generates embeddings using OpenAI, and stores these embeddings in a Pinecone vector database. If a user sends a text message, the workflow queries the Pinecone database using OpenAI embeddings, retrieves relevant document sections, and then uses Groq's chat model to formulate a concise answer, which is then sent back to the user via Telegram. This is ideal for businesses providing instant support for product manuals, educational institutions offering quick answers from course materials, or individuals wanting to quickly extract information from their personal document archives without manual searching. By automating the document ingestion and Q&A process, this workflow significantly reduces the time and effort required to find information, enhances user experience by providing immediate responses, and eliminates the need for human intervention in routine information retrieval tasks.
Workflow JSON
{"id": "5Ycrm1MuK8htwd96", "meta": {"instanceId": "e5595d8cd58f3a24b5a8cf05dd852846c05423873db868a2b7d01a778210c45a", "templateCredsSetupCompleted": true}, "name": "Telegram RAG pdf", "tags": [], "nodes": [{"id": "9fbce801-8c42-43a4-bc70-d93042d68b2c", "name": "Telegram Trigger", "type": "n8n-nodes-base.telegramTrigger", "position": [-220, 240], "webhookId": "b178f034-9997-4832-9bb4-a43c3015506e", "parameters": {"updates": ["message"], "additionalFields": {}}, "credentials": {"telegramApi": {"id": "", "name": "[Your telegramApi]"}}, "typeVersion": 1.1}, {"id": "1bfc1fbd-86b1-4a8a-9301-fe54497f5acd", "name": "Embeddings OpenAI", "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi", "position": [720, 460], "parameters": {"options": {}}, "credentials": {"openAiApi": {"id": "", "name": "[Your openAiApi]"}}, "typeVersion": 1}, {"id": "d5ad7851-ed40-4b3a-b0d5-aeaf04362f1c", "name": "Default Data Loader", "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader", "position": [860, 460], "parameters": {"options": {}, "dataType": "binary"}, "typeVersion": 1}, {"id": "fed803d0-49a2-4b82-8f20-a02a10caa027", "name": "Recursive Character Text Splitter", "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter", "position": [940, 680], "parameters": {"options": {}, "chunkSize": 3000, "chunkOverlap": 200}, "typeVersion": 1}, {"id": "ab60f36f-fada-4812-8dbd-441ad372cb80", "name": "Stop and Error", "type": "n8n-nodes-base.stopAndError", "position": [220, 840], "parameters": {"errorMessage": "An error occurred"}, "typeVersion": 1}, {"id": "c87f1db3-7cc9-4063-9895-4b4d68ea53a1", "name": "Question and Answer Chain", "type": "@n8n/n8n-nodes-langchain.chainRetrievalQa", "position": [-280, 500], "parameters": {"text": "={{ $json.message.text }}\nSearch the database with the retriever for information for the answer", "promptType": "define"}, "typeVersion": 1.3}, {"id": "c9bc4c80-8e57-48bc-a405-131ed7348c1d", "name": "Vector Store Retriever", "type": "@n8n/n8n-nodes-langchain.retrieverVectorStore", "position": [-240, 680], "parameters": {}, "typeVersion": 1}, {"id": "0217056f-2b71-4308-adf1-19dcd4d2cc11", "name": "Pinecone Vector Store1", "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone", "position": [-280, 860], "parameters": {"options": {}, "pineconeIndex": {"__rl": true, "mode": "list", "value": "telegram", "cachedResultName": "telegram"}}, "credentials": {"pineconeApi": {"id": "", "name": "[Your pineconeApi]"}}, "typeVersion": 1}, {"id": "693f9026-f47f-48dc-8e5d-e8b832a37235", "name": "Groq Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatGroq", "position": [-380, 660], "parameters": {"model": "llama-3.1-70b-versatile", "options": {}}, "credentials": {"groqApi": {"id": "", "name": "[Your groqApi]"}}, "typeVersion": 1}, {"id": "c7acf014-138f-4be7-b569-c309bb10e50d", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [500, 73.04879287725316], "parameters": {"color": 7, "width": 1139.5159692915001, "height": 873.6068151028411, "content": "# Load data into database\nFetch file from **Telegram**, split it into chunks and insert into **Pinecone** index, a message from **Telegram** will be sent just to let the user know that the process finished"}, "typeVersion": 1}, {"id": "dd3b9d8b-5771-4a09-8c1b-794cb8737d5d", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [-878.769, 400], "parameters": {"color": 7, "width": 1344.7918019808176, "height": 806.8716167324012, "content": "# Chat with Database\n\n1. **Receive** the incoming chat message.\n2. **Retrieve** relevant chunks from the _vector store_.\n3. **Pass** these chunks to the model.\n\nThe model will use the retrieved information to **formulate a precise response**.\n"}, "typeVersion": 1}, {"id": "9aaf575a-5e40-407c-951c-10b1d16e5d3c", "name": "Check If is a document", "type": "n8n-nodes-base.if", "position": [220, 240], "parameters": {"options": {}, "conditions": {"options": {"leftValue": "", "caseSensitive": true, "typeValidation": "strict"}, "combinator": "and", "conditions": [{"id": "8839993b-9fe7-4e1e-a1cc-fe5de6b0bb62", "operator": {"type": "object", "operation": "exists", "singleValue": true}, "leftValue": "={{ $json.message.document }}", "rightValue": ""}]}}, "typeVersion": 2}, {"id": "c1edb6bf-ba95-4a5f-9626-add673274086", "name": "Change to application/pdf", "type": "n8n-nodes-base.code", "position": [700, 220], "parameters": {"jsCode": "// Fun\u00e7\u00e3o para modificar os metadados do arquivo bin\u00e1rio\nfunction modifyBinaryMetadata(items) {\n for (const item of items) {\n if (item.binary && item.binary.data) {\n // Modifica o tipo MIME\n item.binary.data.mimeType = 'application/pdf';\n \n // Garante que o nome do arquivo termine com .pdf\n if (!item.binary.data.fileName.toLowerCase().endsWith('.pdf')) {\n item.binary.data.fileName += '.pdf';\n }\n \n // Atualiza o contentType no fileType (se existir)\n if (item.binary.data.fileType) {\n item.binary.data.fileType.contentType = 'application/pdf';\n }\n }\n }\n return items;\n}\n\n// Aplica a modifica\u00e7\u00e3o e retorna os itens atualizados\nreturn modifyBinaryMetadata($input.all());"}, "typeVersion": 2}, {"id": "ea4d4e74-8954-47f0-a3a0-662d47ea2298", "name": "Telegram get File", "type": "n8n-nodes-base.telegram", "position": [520, 220], "parameters": {"fileId": "={{ $json.message.document.file_id }}", "resource": "file"}, "credentials": {"telegramApi": {"id": "", "name": "[Your telegramApi]"}}, "typeVersion": 1.2}, {"id": "cf548bee-d5d5-4f1a-a059-932ea163e155", "name": "Embeddings", "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi", "position": [-100, 1080], "parameters": {"options": {}}, "credentials": {"openAiApi": {"id": "", "name": "[Your openAiApi]"}}, "typeVersion": 1}, {"id": "e3bd4759-80cc-42bb-ba53-f9e88e9ba916", "name": "Telegram Response", "type": "n8n-nodes-base.telegram", "onError": "continueErrorOutput", "position": [160, 560], "parameters": {"text": "={{ $json.response.text }}", "chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}", "additionalFields": {"appendAttribution": false}}, "credentials": {"telegramApi": {"id": "", "name": "[Your telegramApi]"}}, "typeVersion": 1.2}, {"id": "e478df48-9e6d-4a84-89be-beb569914ae3", "name": "Telegram Response about Database", "type": "n8n-nodes-base.telegram", "onError": "continueErrorOutput", "position": [1400, 220], "parameters": {"text": "={{ $json.metadata.pdf.totalPages }} pages saved on Pinecone", "chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}", "additionalFields": {"appendAttribution": false}}, "credentials": {"telegramApi": {"id": "", "name": "[Your telegramApi]"}}, "typeVersion": 1.2}, {"id": "5be7a321-1be6-4173-83de-3d569666718d", "name": "Stop and Error1", "type": "n8n-nodes-base.stopAndError", "position": [1400, 580], "parameters": {"errorMessage": "An error occurred."}, "typeVersion": 1}, {"id": "aae26861-f34d-4b59-bd99-3662fbd6676c", "name": "Pinecone Vector Store", "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone", "position": [880, 220], "parameters": {"mode": "insert", "options": {}, "pineconeIndex": {"__rl": true, "mode": "list", "value": "telegram", "cachedResultName": "telegram"}}, "credentials": {"pineconeApi": {"id": "", "name": "[Your pineconeApi]"}}, "typeVersion": 1}, {"id": "312fb807-4225-4630-ab32-aa12fe07c127", "name": "Limit to 1", "type": "n8n-nodes-base.limit", "position": [1220, 220], "parameters": {}, "typeVersion": 1}], "active": true, "pinData": {}, "settings": {"timezone": "America/Sao_Paulo", "callerPolicy": "workflowsFromSameOwner", "executionOrder": "v1", "saveManualExecutions": true}, "versionId": "03612d23-6630-4ec6-8738-1dae593c8d23", "connections": {"Embeddings": {"ai_embedding": [[{"node": "Pinecone Vector Store1", "type": "ai_embedding", "index": 0}]]}, "Limit to 1": {"main": [[{"node": "Telegram Response about Database", "type": "main", "index": 0}]]}, "Groq Chat Model": {"ai_languageModel": [[{"node": "Question and Answer Chain", "type": "ai_languageModel", "index": 0}]]}, "Telegram Trigger": {"main": [[{"node": "Check If is a document", "type": "main", "index": 0}]]}, "Embeddings OpenAI": {"ai_embedding": [[{"node": "Pinecone Vector Store", "type": "ai_embedding", "index": 0}]]}, "Telegram Response": {"main": [[], [{"node": "Stop and Error", "type": "main", "index": 0}]]}, "Telegram get File": {"main": [[{"node": "Change to application/pdf", "type": "main", "index": 0}]]}, "Default Data Loader": {"ai_document": [[{"node": "Pinecone Vector Store", "type": "ai_document", "index": 0}]]}, "Pinecone Vector Store": {"main": [[{"node": "Limit to 1", "type": "main", "index": 0}]]}, "Check If is a document": {"main": [[{"node": "Telegram get File", "type": "main", "index": 0}], [{"node": "Question and Answer Chain", "type": "main", "index": 0}]]}, "Pinecone Vector Store1": {"ai_vectorStore": [[{"node": "Vector Store Retriever", "type": "ai_vectorStore", "index": 0}]]}, "Vector Store Retriever": {"ai_retriever": [[{"node": "Question and Answer Chain", "type": "ai_retriever", "index": 0}]]}, "Change to application/pdf": {"main": [[{"node": "Pinecone Vector Store", "type": "main", "index": 0}]]}, "Question and Answer Chain": {"main": [[{"node": "Telegram Response", "type": "main", "index": 0}]]}, "Telegram Response about Database": {"main": [[], [{"node": "Stop and Error1", "type": "main", "index": 0}]]}, "Recursive Character Text Splitter": {"ai_textSplitter": [[{"node": "Default Data Loader", "type": "ai_textSplitter", "index": 0}]]}}}How to Import This Workflow
- 1Copy the workflow JSON above using the Copy Workflow JSON button.
- 2Open your n8n instance and go to Workflows.
- 3Click Import from JSON and paste the copied workflow.
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