About this recipe
A recipe for Ai Agent To Chat With Files In Supabase Storage
Recipe Template
{
"meta": {
"instanceId": "6a2a7715680b8313f7cb4676321c5baa46680adfb913072f089f2766f42e43bd"
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"nodes": [
{
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"name": "Get All files",
"type": "n8n-nodes-base.httpRequest",
"position": [
400,
-100
],
"parameters": {
"url": "=https:\/\/yqtvdcvjboenlblgcivl.supabase.co\/storage\/v1\/object\/list\/private",
"method": "POST",
"options": [],
"jsonBody": "={\n \"prefix\": \"\",\n \"limit\": 100,\n \"offset\": 0,\n \"sortBy\": {\n \"column\": \"name\",\n \"order\": \"asc\"\n }\n}",
"sendBody": true,
"specifyBody": "json",
"authentication": "predefinedCredentialType",
"nodeCredentialType": "supabaseApi"
},
"credentials": {
"supabaseApi": {
"id": "t8AQJzvZvrOMDLec",
"name": "Supabase account My Airtable Gen"
}
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"typeVersion": 4.2
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{
"name": "=file_id",
"value": "={{ $json.id }}"
}
]
}
},
"jsonData": "={{ $('Merge').item.json.data ?? $('Merge').item.json.text }}",
"jsonMode": "expressionData"
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"chunkOverlap": 200
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{
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"model": "text-embedding-3-small",
"options": []
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"name": "OpenAi account"
}
},
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{
"id": "4147409f-8686-418f-b979-04f8c8e7fe42",
"name": "Create File record2",
"type": "n8n-nodes-base.supabase",
"position": [
1540,
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],
"parameters": {
"tableId": "files",
"fieldsUi": {
"fieldValues": [
{
"fieldId": "name",
"fieldValue": "={{ $('Loop Over Items').item.json.name }}"
},
{
"fieldId": "storage_id",
"fieldValue": "={{ $('Loop Over Items').item.json.id }}"
}
]
}
},
"credentials": {
"supabaseApi": {
"id": "t8AQJzvZvrOMDLec",
"name": "Supabase account My Airtable Gen"
}
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{
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"operator": {
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"singleValue": true
},
"leftValue": "={{ \n !$('Aggregate').item.json.data || \n !Array.isArray($('Aggregate').item.json.data) || \n !$('Aggregate').item.json.data.some(item => \n item.storage_id === $('Loop Over Items').item.json.id \n ) \n}}",
"rightValue": ""
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{
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"operator": {
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"rightValue": ".emptyFolderPlaceholder"
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{
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"name": "Get All Files",
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"position": [
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"parameters": {
"tableId": "files",
"operation": "getAll"
},
"credentials": {
"supabaseApi": {
"id": "t8AQJzvZvrOMDLec",
"name": "Supabase account My Airtable Gen"
}
},
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{
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"name": "Download",
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"position": [
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],
"parameters": {
"url": "=https:\/\/yqtvdcvjboenlblgcivl.supabase.co\/storage\/v1\/object\/private\/{{ $json.name }}",
"options": [],
"authentication": "predefinedCredentialType",
"nodeCredentialType": "supabaseApi"
},
"credentials": {
"supabaseApi": {
"id": "t8AQJzvZvrOMDLec",
"name": "Supabase account My Airtable Gen"
}
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{
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"batchSize": "=1"
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"typeVersion": 3
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{
"id": "f9c23b5e-0b40-4886-b54f-59fb46132d3f",
"name": "When clicking \u2018Test workflow\u2019",
"type": "n8n-nodes-base.manualTrigger",
"position": [
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],
"parameters": [],
"typeVersion": 1
},
{
"id": "0a0ec290-2c3d-40ba-8d03-6abf75202e73",
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],
"parameters": {
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"aggregate": "aggregateAllItemData"
},
"typeVersion": 1,
"alwaysOutputData": true
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{
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"name": "When chat message received",
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"position": [
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"webhookId": "3c40d311-7996-4ed4-b2fa-c73bea5f4cf5",
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{
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"id": "zJhr5piyEwVnWtaI",
"name": "OpenAi club"
}
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{
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"name": "Embeddings OpenAI2",
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"position": [
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],
"parameters": {
"model": "text-embedding-3-small",
"options": []
},
"credentials": {
"openAiApi": {
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"name": "Test club key"
}
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{
"id": "a1458799-d379-46de-93e6-a5ba0c665163",
"name": "OpenAI Chat Model2",
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"position": [
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],
"parameters": {
"options": []
},
"credentials": {
"openAiApi": {
"id": "SphXAX7rlwRLkiox",
"name": "Test club key"
}
},
"typeVersion": 1
},
{
"id": "d6eeda2f-c984-406d-a625-726840308413",
"name": "Vector Store Tool1",
"type": "@n8n\/n8n-nodes-langchain.toolVectorStore",
"position": [
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],
"parameters": {
"name": "knowledge_base",
"topK": 8,
"description": "Retrieve data about user request"
},
"typeVersion": 1
},
{
"id": "e1d9a348-7d44-4ad1-adbd-2c9a31e06876",
"name": "Switch",
"type": "n8n-nodes-base.switch",
"position": [
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-100
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "txt",
"conditions": {
"options": {
"version": 1,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{$binary.data?.fileExtension == undefined }}",
"rightValue": "txt"
}
]
},
"renameOutput": true
},
{
"outputKey": "pdf",
"conditions": {
"options": {
"version": 1,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "bf04cbec-dd86-4607-988f-4c96b6fd4b58",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{$binary.data.fileExtension }}",
"rightValue": "pdf"
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},
"options": []
},
"typeVersion": 3.1
},
{
"id": "d38afb92-87ae-4e2a-a712-ec24b1efd105",
"name": "Insert into Supabase Vectorstore",
"type": "@n8n\/n8n-nodes-langchain.vectorStoreSupabase",
"position": [
1700,
-100
],
"parameters": {
"mode": "insert",
"options": {
"queryName": "match_documents"
},
"tableName": {
"__rl": true,
"mode": "list",
"value": "documents",
"cachedResultName": "documents"
}
},
"credentials": {
"supabaseApi": {
"id": "t8AQJzvZvrOMDLec",
"name": "Supabase account My Airtable Gen"
}
},
"typeVersion": 1
},
{
"id": "1a903b2e-cab0-4798-b820-ec08d6a71ddd",
"name": "Merge",
"type": "n8n-nodes-base.merge",
"position": [
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],
"parameters": [],
"typeVersion": 3
},
{
"id": "3afd552e-4995-493e-9cd5-ef496dfe359f",
"name": "AI Agent",
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"position": [
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],
"parameters": {
"options": []
},
"typeVersion": 1.7
},
{
"id": "d9688acc-311b-42fd-afa8-2c0e493be34b",
"name": "Supabase Vector Store",
"type": "@n8n\/n8n-nodes-langchain.vectorStoreSupabase",
"position": [
1020,
-660
],
"parameters": {
"options": {
"metadata": {
"metadataValues": [
{
"name": "file_id",
"value": "300b0128-0955-4058-b0d3-a9aefe728432"
}
]
}
},
"tableName": {
"__rl": true,
"mode": "list",
"value": "documents",
"cachedResultName": "documents"
}
},
"credentials": {
"supabaseApi": {
"id": "t8AQJzvZvrOMDLec",
"name": "Supabase account My Airtable Gen"
}
},
"typeVersion": 1
},
{
"id": "66df007c-0418-4551-950e-32e7d79840bd",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
340,
-220
],
"parameters": {
"height": 89.3775420487804,
"content": "### Replace Storage name, database ID and credentials."
},
"typeVersion": 1
},
{
"id": "b164b520-20dd-44a4-aa3b-647391786b20",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-20,
-220
],
"parameters": {
"height": 80,
"content": "### Replace credentials."
},
"typeVersion": 1
},
{
"id": "8688c219-5af4-4e54-9fd1-91851829445b",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1540,
-220
],
"parameters": {
"height": 80,
"content": "### Replace credentials."
},
"typeVersion": 1
},
{
"id": "45c6ece4-f849-4496-8149-31385f5e36a4",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
840,
-220
],
"parameters": {
"height": 89.3775420487804,
"content": "### Replace Storage name, database ID and credentials."
},
"typeVersion": 1
},
{
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"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
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],
"parameters": {
"height": 80,
"content": "### Replace credentials."
},
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{
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"type": "n8n-nodes-base.stickyNote",
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],
"parameters": {
"height": 80,
"content": "### Replace credentials."
},
"typeVersion": 1
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{
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"name": "Sticky Note9",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"color": 7,
"width": 330.5152611046425,
"height": 239.5888196628349,
"content": "### ... or watch set up video [10 min]\n[](https:\/\/www.youtube.com\/watch?v=glWUkdZe_3w)\n"
},
"typeVersion": 1
},
{
"id": "eba121de-a3f7-4ba5-8396-f7d64e648322",
"name": "Sticky Note7",
"type": "n8n-nodes-base.stickyNote",
"position": [
-820,
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],
"parameters": {
"color": 7,
"width": 636.2128494576581,
"height": 497.1532689930921,
"content": "\n## AI Agent To Chat With Files In Supabase Storage\n**Made by [Mark Shcherbakov](https:\/\/www.linkedin.com\/in\/marklowcoding\/) from community [5minAI](https:\/\/www.skool.com\/5minai-2861)**\n\nManually retrieving and analyzing specific information from large document repositories is time-consuming and inefficient. This workflow automates the process by vectorizing documents and enabling AI-powered interactions, making it easy to query and retrieve context-based information from uploaded files.\n\nThe workflow integrates Supabase with an AI-powered chatbot to process, store, and query text and PDF files. The steps include:\n- Fetching and comparing files to avoid duplicate processing.\n- Handling file downloads and extracting content based on the file type.\n- Converting documents into vectorized data for contextual information retrieval.\n- Storing and querying vectorized data from a Supabase vector store.\n\n"
},
"typeVersion": 1
},
{
"id": "df054036-d6b9-4f53-86cb-85ad96f07d0e",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
-820,
-940
],
"parameters": {
"color": 7,
"width": 280.2462120317618,
"height": 545.9087885077763,
"content": "### Set up steps\n\n1. **Fetch File List from Supabase**:\n - Use Supabase to retrieve the stored file list from a specified bucket.\n - Add logic to manage empty folder placeholders returned by Supabase, avoiding incorrect processing.\n\n2. **Compare and Filter Files**:\n - Aggregate the files retrieved from storage and compare them to the existing list in the Supabase `files` table.\n - Exclude duplicates and skip placeholder files to ensure only unprocessed files are handled.\n\n3. **Handle File Downloads**:\n - Download new files using detailed storage configurations for public\/private access.\n - Adjust the storage settings and GET requests to match your Supabase setup.\n\n4. **File Type Processing**:\n - Use a Switch node to target specific file types (e.g., PDFs or text files).\n - Employ relevant tools to process the content:\n - For PDFs, extract embedded content.\n - For text files, directly process the text data.\n\n5. **Content Chunking**:\n - Break large text data into smaller chunks using the Text Splitter node.\n - Define chunk size (default: 500 tokens) and overlap to retain necessary context across chunks.\n\n6. **Vector Embedding Creation**:\n - Generate vectorized embeddings for the processed content using OpenAI's embedding tools.\n - Ensure metadata, such as file ID, is included for easy data retrieval.\n\n7. **Store Vectorized Data**:\n - Save the vectorized information into a dedicated Supabase vector store.\n - Use the default schema and table provided by Supabase for seamless setup.\n\n8. **AI Chatbot Integration**:\n - Add a chatbot node to handle user input and retrieve relevant document chunks.\n - Use metadata like file ID for targeted queries, especially when multiple documents are involved."
},
"typeVersion": 1
},
{
"id": "450a1e49-4be9-451a-9d05-2860e29c3695",
"name": "Sticky Note8",
"type": "n8n-nodes-base.stickyNote",
"position": [
540,
-1160
],
"parameters": {
"color": 5,
"width": 951.7421645394404,
"height": 809.7437181509877,
"content": "## Scenario 2 - AI agent"
},
"typeVersion": 1
},
{
"id": "c3814c5d-8881-4598-897e-268019bee1bc",
"name": "Sticky Note10",
"type": "n8n-nodes-base.stickyNote",
"position": [
-260,
-280
],
"parameters": {
"color": 5,
"width": 2304.723519246249,
"height": 739.2522526116408,
"content": "## Scenario 1 - Flow for adding new files from Supabase storage"
},
"typeVersion": 1
}
],
"pinData": [],
"connections": {
"If": {
"main": [
[
{
"node": "Download",
"type": "main",
"index": 0
}
],
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Merge": {
"main": [
[
{
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"type": "main",
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}
]
]
},
"Switch": {
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[
{
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}
],
[
{
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"type": "main",
"index": 0
}
]
]
},
"Download": {
"main": [
[
{
"node": "Switch",
"type": "main",
"index": 0
}
]
]
},
"Aggregate": {
"main": [
[
{
"node": "Get All files",
"type": "main",
"index": 0
}
]
]
},
"Get All Files": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
},
"Get All files": {
"main": [
[
{
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"type": "main",
"index": 0
}
]
]
},
"Loop Over Items": {
"main": [
null,
[
{
"node": "If",
"type": "main",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "Insert into Supabase Vectorstore",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Embeddings OpenAI2": {
"ai_embedding": [
[
{
"node": "Supabase Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"OpenAI Chat Model1": {
"ai_languageModel": [
[
{
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"type": "ai_languageModel",
"index": 0
}
]
]
},
"OpenAI Chat Model2": {
"ai_languageModel": [
[
{
"node": "Vector Store Tool1",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Vector Store Tool1": {
"ai_tool": [
[
{
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"type": "ai_tool",
"index": 0
}
]
]
},
"Create File record2": {
"main": [
[
{
"node": "Insert into Supabase Vectorstore",
"type": "main",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Insert into Supabase Vectorstore",
"type": "ai_document",
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}
]
]
},
"Extract Document PDF": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 1
}
]
]
},
"Supabase Vector Store": {
"ai_vectorStore": [
[
{
"node": "Vector Store Tool1",
"type": "ai_vectorStore",
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}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Insert into Supabase Vectorstore": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Recursive Character Text Splitter": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"When clicking \u2018Test workflow\u2019": {
"main": [
[
{
"node": "Get All Files",
"type": "main",
"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!