About this recipe
A recipe for Telegram Chat With Pdf
Recipe Template
{
"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": ""
}
},
"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": ""
}
},
"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,
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],
"parameters": {
"options": [],
"chunkSize": 3000,
"chunkOverlap": 200
},
"typeVersion": 1
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{
"id": "ab60f36f-fada-4812-8dbd-441ad372cb80",
"name": "Stop and Error",
"type": "n8n-nodes-base.stopAndError",
"position": [
220,
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],
"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": ""
}
},
"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": ""
}
},
"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": ""
}
},
"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": ""
}
},
"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": ""
}
},
"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": ""
}
},
"typeVersion": 1.2
},
{
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"name": "Stop and Error1",
"type": "n8n-nodes-base.stopAndError",
"position": [
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],
"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": ""
}
},
"typeVersion": 1
},
{
"id": "312fb807-4225-4630-ab32-aa12fe07c127",
"name": "Limit to 1",
"type": "n8n-nodes-base.limit",
"position": [
1220,
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],
"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 Use an n8n Template
1
Create a New Workflow
Click "New Workflow" in your n8n dashboard to get started.
2
Copy & Paste Template
First, copy this template:
Click here to copy the JSON
.
Then, in n8n, click the three dots (···) → "Import from file" and paste the JSON code.
3
Customize the Nodes
Go through each node in the workflow to update inputs like spreadsheet IDs, email addresses, or message content. Adjust field mappings to match your data.
4
Grant Access
For nodes that connect to external apps (like Google Sheets or Slack), you'll need to grant access. Connect your accounts using OAuth or an API key and save the credentials in the node.
5
Test It
Run the workflow by clicking "Execute Node" for each step or "Run Once" for the whole thing. Check the right sidebar to inspect data and debug any errors (they'll show up in red).
6
Activate Workflow
Once everything works as expected, click the "Activate" toggle to turn your workflow on. You're all set!