n8n-workflows/workflows/Store Notion_s Pages as Vector Documents into Supabase with OpenAI.json
2025-05-14 11:58:29 +03:00

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{
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"name": "Store Notion's Pages as Vector Documents into Supabase with OpenAI",
"tags": [],
"nodes": [
{
"id": "495609cd-4ca0-426d-8413-69e771398188",
"name": "Sticky Note",
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"content": "## Store Notion's Pages as Vector Documents into Supabase\n\n**This workflow assumes you have a Supabase project with a table that has a vector column. If you don't have it, follow the instructions here:** [Supabase Vector Columns Guide](https://supabase.com/docs/guides/ai/vector-columns)\n\n## Workflow Description\n\nThis workflow automates the process of storing Notion pages as vector documents in a Supabase database with a vector column. The steps are as follows:\n\n1. **Notion Page Added Trigger**:\n - Monitors a specified Notion database for newly added pages. You can create a specific Notion database where you copy the pages you want to store in Supabase.\n - Node: `Page Added in Notion Database`\n\n2. **Retrieve Page Content**:\n - Fetches all block content from the newly added Notion page.\n - Node: `Get Blocks Content`\n\n3. **Filter Non-Text Content**:\n - Excludes blocks of type \"image\" and \"video\" to focus on textual content.\n - Node: `Filter - Exclude Media Content`\n\n4. **Summarize Content**:\n - Concatenates the Notion blocks content to create a single text for embedding.\n - Node: `Summarize - Concatenate Notion's blocks content`\n\n5. **Store in Supabase**:\n - Stores the processed documents and their embeddings into a Supabase table with a vector column.\n - Node: `Store Documents in Supabase`\n\n6. **Generate Embeddings**:\n - Utilizes OpenAI's API to generate embeddings for the textual content.\n - Node: `Generate Text Embeddings`\n\n\n7. **Create Metadata and Load Content**:\n - Loads the block content and creates associated metadata, such as page ID and block ID.\n - Node: `Load Block Content & Create Metadata`\n\n8. **Split Content into Chunks**:\n - Divides the text into smaller chunks for easier processing and embedding generation.\n - Node: `Token Splitter`\n\n\n\n"
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{
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"name": "Embeddings OpenAI",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
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{
"id": "6d2579b8-376f-44c3-82e8-9dc608efd98b",
"name": "Token Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterTokenSplitter",
"position": [
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],
"parameters": {
"chunkSize": 256,
"chunkOverlap": 30
},
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{
"id": "79b3c147-08ca-4db4-9116-958a868cbfd9",
"name": "Notion - Page Added Trigger",
"type": "n8n-nodes-base.notionTrigger",
"position": [
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520
],
"parameters": {
"simple": false,
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"databaseId": {
"__rl": true,
"mode": "list",
"value": "",
"cachedResultUrl": "",
"cachedResultName": ""
}
},
"typeVersion": 1
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{
"id": "e4a6f524-e3f5-4d02-949a-8523f2d21965",
"name": "Notion - Retrieve Page Content",
"type": "n8n-nodes-base.notion",
"position": [
1400,
520
],
"parameters": {
"blockId": {
"__rl": true,
"mode": "url",
"value": "={{ $json.url }}"
},
"resource": "block",
"operation": "getAll",
"returnAll": true
},
"typeVersion": 2.2
},
{
"id": "bfebc173-8d4b-4f8f-a625-4622949dd545",
"name": "Filter Non-Text Content",
"type": "n8n-nodes-base.filter",
"position": [
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],
"parameters": {
"options": {},
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "e5b605e5-6d05-4bca-8f19-a859e474620f",
"operator": {
"type": "string",
"operation": "notEquals"
},
"leftValue": "={{ $json.type }}",
"rightValue": "image"
},
{
"id": "c7415859-5ffd-4c78-b497-91a3d6303b6f",
"operator": {
"type": "string",
"operation": "notEquals"
},
"leftValue": "={{ $json.type }}",
"rightValue": "video"
}
]
}
},
"typeVersion": 2
},
{
"id": "b04939f9-355a-430b-a069-b11800066313",
"name": "Summarize - Concatenate Notion's blocks content",
"type": "n8n-nodes-base.summarize",
"position": [
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],
"parameters": {
"options": {
"outputFormat": "separateItems"
},
"fieldsToSummarize": {
"values": [
{
"field": "content",
"separateBy": "\n",
"aggregation": "concatenate"
}
]
}
},
"typeVersion": 1
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{
"id": "0e64dbb5-20c1-4b90-b818-a1726aaf5112",
"name": "Create metadata and load content",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
2320,
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],
"parameters": {
"options": {
"metadata": {
"metadataValues": [
{
"name": "pageId",
"value": "={{ $('Notion - Page Added Trigger').item.json.id }}"
},
{
"name": "createdTime",
"value": "={{ $('Notion - Page Added Trigger').item.json.created_time }}"
},
{
"name": "pageTitle",
"value": "={{ $('Notion - Page Added Trigger').item.json.properties.Page.title[0].text.content }}"
}
]
}
},
"jsonData": "={{ $('Summarize - Concatenate Notion's blocks content').item.json.concatenated_content }}",
"jsonMode": "expressionData"
},
"typeVersion": 1
},
{
"id": "187aba6f-eaed-4427-8d40-b9da025fb37d",
"name": "Supabase Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStoreSupabase",
"position": [
2200,
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],
"parameters": {
"mode": "insert",
"options": {},
"tableName": {
"__rl": true,
"mode": "list",
"value": "",
"cachedResultName": ""
}
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "77f6b6f7-d699-4a7e-b3e7-fe8a60bde7ba",
"connections": {
"Token Splitter": {
"ai_textSplitter": [
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{
"node": "Create metadata and load content",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
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{
"node": "Supabase Vector Store",
"type": "ai_embedding",
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}
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},
"Filter Non-Text Content": {
"main": [
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{
"node": "Summarize - Concatenate Notion's blocks content",
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"Notion - Page Added Trigger": {
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"node": "Notion - Retrieve Page Content",
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"Notion - Retrieve Page Content": {
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{
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},
"Create metadata and load content": {
"ai_document": [
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{
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"type": "ai_document",
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},
"Summarize - Concatenate Notion's blocks content": {
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{
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}
}
}