构建自定义Qdrant向量存储MCP服务器
高级
这是一个Building Blocks, AI领域的自动化工作流，包含 44 个节点。主要使用 If, Set, Code, Filter, Switch 等节点，结合人工智能技术实现智能自动化。 构建自定义Qdrant向量存储MCP服务器
前置要求
- •可能需要目标 API 的认证凭证
- •OpenAI API Key
- •Qdrant 服务器连接信息
使用的节点 (44)
工作流预览
可视化展示节点连接关系，支持缩放和平移
导出工作流
复制以下 JSON 配置到 n8n 导入，即可使用此工作流
{
"meta": {
"instanceId": "408f9fb9940c3cb18ffdef0e0150fe342d6e655c3a9fac21f0f644e8bedabcd9",
"templateCredsSetupCompleted": true
},
"nodes": [
{
"id": "49620d3a-d4ec-4017-ade1-ff2ef5473c11",
"name": "便签",
"type": "n8n-nodes-base.stickyNote",
"position": [
-220,
-80
],
"parameters": {
"color": 7,
"width": 680,
"height": 660,
"content": "## 1. Set up an MCP Server Trigger\n[Read more about the MCP Server Trigger](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger)"
},
"typeVersion": 1
},
{
"id": "f0646a81-d328-4f07-a744-60f576b5a51e",
"name": "Insert",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
-40,
380
],
"parameters": {
"name": "insert_review",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $workflow.id }}"
},
"description": "=Call this tool to insert a customer's review into our review database.",
"workflowInputs": {
"value": {
"text": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('text', `The contents of the review`, 'string') }}",
"text2": "null",
"operation": "insert",
"companyIds": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('companyIds', `The company ID is their url address.`, 'string') }}"
},
"schema": [
{
"id": "operation",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "operation",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "text",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "text",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "text2",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "text2",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "companyIds",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "companyIds",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
}
},
"typeVersion": 2.1
},
{
"id": "21e8beac-dbd5-44d7-8472-4edff3f63308",
"name": "Search",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
80,
440
],
"parameters": {
"name": "search_reviews",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $workflow.id }}",
"cachedResultName": "={{ $workflow.id }}"
},
"description": "Call this tool to search our reviews database.",
"workflowInputs": {
"value": {
"text": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('text', `the query or search terms to use`, 'string') }}",
"text2": "null",
"operation": "search",
"companyIds": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('companyIds', `Optional, leave blank to search over all companies otherwise one or more company IDs comma-delimited. The company ID is their url address.`, 'string') }}"
},
"schema": [
{
"id": "operation",
"type": "string",
"display": true,
"required": false,
"displayName": "operation",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "text",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "text",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "text2",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "text2",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "companyIds",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "companyIds",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
}
},
"typeVersion": 2.1
},
{
"id": "ffb100a4-9108-4ccd-a897-e5cd9e752232",
"name": "Recommend",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
280,
240
],
"parameters": {
"name": "recommend_reviews",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $workflow.id }}"
},
"description": "Call this tool to generate a recommendation for a review based on positive and/or negative preferences.",
"workflowInputs": {
"value": {
"text": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('text', `preferences to include.`, 'string') }}",
"text2": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('text2', `preference to avoid.`, 'string') }}",
"operation": "recommend",
"companyIds": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('companyIds', `Optional, leave blank to search across all reviews otherwise one or more company IDs, comma-delimited. The company ID is their url address.`, 'string') }}"
},
"schema": [
{
"id": "operation",
"type": "string",
"display": true,
"required": false,
"displayName": "operation",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "text",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "text",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "text2",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "text2",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "companyIds",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "companyIds",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
}
},
"typeVersion": 2.1
},
{
"id": "d1d53cbc-0a22-409d-9336-d8c98eeaa170",
"name": "Qdrant MCP Server",
"type": "@n8n/n8n-nodes-langchain.mcpTrigger",
"position": [
-40,
60
],
"webhookId": "a1aff1b5-e5c7-4ca2-91eb-017c1fe32dab",
"parameters": {
"path": "a1aff1b5-e5c7-4ca2-91eb-017c1fe32dab"
},
"typeVersion": 1
},
{
"id": "82d747a5-ff5f-44ff-9f68-cc1aa01ba1de",
"name": "When Executed by Another Workflow",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
540,
280
],
"parameters": {
"workflowInputs": {
"values": [
{
"name": "operation"
},
{
"name": "text"
},
{
"name": "text2"
},
{
"name": "companyIds"
}
]
}
},
"typeVersion": 1.1
},
{
"id": "c7a2e948-5cd5-4545-a633-c1157e63edec",
"name": "Operation",
"type": "n8n-nodes-base.switch",
"position": [
760,
240
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "listCompanies",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "fe782b0f-f501-4985-a9d2-f63f4019177f",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.operation }}",
"rightValue": "listCompanies"
}
]
},
"renameOutput": true
},
{
"outputKey": "insert",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "81b134bc-d671-4493-b3ad-8df9be3f49a6",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.operation }}",
"rightValue": "insert"
}
]
},
"renameOutput": true
},
{
"outputKey": "search",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "8d57914f-6587-4fb3-88e0-aa1de6ba56c1",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.operation }}",
"rightValue": "search"
}
]
},
"renameOutput": true
},
{
"outputKey": "compare",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "7c38f238-213a-46ec-aefe-22e0bcb8dffc",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.operation }}",
"rightValue": "compare"
}
]
},
"renameOutput": true
},
{
"outputKey": "recommend",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "2c691501-786a-433f-a185-3a6e0d08d336",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.operation }}",
"rightValue": "recommend"
}
]
},
"renameOutput": true
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "18d805db-376c-4583-963a-db1e5d09aa50",
"name": "便签1",
"type": "n8n-nodes-base.stickyNote",
"position": [
480,
-140
],
"parameters": {
"color": 7,
"width": 580,
"height": 320,
"content": "## 2. Expand Functionality Beyond Vendor Implementation\n[Read more about the Qdrant Node](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.vectorstoreqdrant)\n\nOfficially supported MCP servers are cool but may not always have the features you want. N8N MCP servers give you the freedom to expand and customise to fit your business or product needs and requirements.\n\nFor our Qdrant MCP server, we've added 2 additional capabilities from the Qdrant API; The Group Search and Recommendation API. With these, we can explore many more use-cases for our users.\n"
},
"typeVersion": 1
},
{
"id": "ab8aeea3-0564-4c96-a67c-ff319df3297b",
"name": "Compare",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
220,
380
],
"parameters": {
"name": "compare_reviews",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $workflow.id }}",
"cachedResultName": "={{ $workflow.id }}"
},
"description": "Call this tool to compare search results across 2 or more companies.",
"workflowInputs": {
"value": {
"text": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('text', `the query or search terms to use`, 'string') }}",
"text2": "null",
"operation": "compare",
"companyIds": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('companyIds', `Two or more company IDs, comma-delimited. The company ID is their url address.`, 'string') }}"
},
"schema": [
{
"id": "operation",
"type": "string",
"display": true,
"required": false,
"displayName": "operation",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "text",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "text",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "text2",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "text2",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "companyIds",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "companyIds",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
}
},
"typeVersion": 2.1
},
{
"id": "4f0876cb-dc07-486e-937b-334fa2cb754f",
"name": "便签8",
"type": "n8n-nodes-base.stickyNote",
"position": [
1920,
860
],
"parameters": {
"width": 213.30551928619226,
"height": 332.38559808882246,
"content": "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n### 🚨Configure Your Qdrant Connection\n* Be sure to enter your endpoint address"
},
"typeVersion": 1
},
{
"id": "02031bac-016f-4715-8413-6255cf73e103",
"name": "Recommend API",
"type": "n8n-nodes-base.httpRequest",
"position": [
1980,
900
],
"parameters": {
"url": "=http://qdrant:6333/collections/trustpilot_reviews/points/recommend",
"method": "POST",
"options": {},
"sendBody": true,
"authentication": "predefinedCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "strategy",
"value": "average_vector"
},
{
"name": "limit",
"value": "={{ 3 }}"
},
{
"name": "positive",
"value": "={{ [$json.embeddings[0]] }}"
},
{
"name": "negative",
"value": "={{ [$json.embeddings[1]] }}"
},
{
"name": "filter",
"value": "={{\n$('Operation').first().json.companyIds\n ? {\n \"must\": {\n \"key\": \"metadata.company_id\",\n \"match\": {\n \"any\": $('Operation').first().json.companyIds.split(',')\n }\n }\n }\n : {}\n}}"
},
{
"name": "with_payload",
"value": "={{ true }}"
}
]
},
"nodeCredentialType": "qdrantApi"
},
"credentials": {
"qdrantApi": {
"id": "NyinAS3Pgfik66w5",
"name": "QdrantApi account"
}
},
"typeVersion": 4.2
},
{
"id": "9d058dae-2f24-4e34-bdb6-ba5649a3b431",
"name": "Get 向量嵌入",
"type": "n8n-nodes-base.httpRequest",
"position": [
1580,
900
],
"parameters": {
"url": "https://api.openai.com/v1/embeddings",
"method": "POST",
"options": {},
"sendBody": true,
"authentication": "predefinedCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "input",
"value": "={{ $json.text }}"
},
{
"name": "model",
"value": "text-embedding-3-small"
}
]
},
"nodeCredentialType": "openAiApi"
},
"credentials": {
"openAiApi": {
"id": "8gccIjcuf3gvaoEr",
"name": "OpenAi account"
}
},
"typeVersion": 4.2
},
{
"id": "dfbb9a02-91dd-4dc4-8738-0aff41db2156",
"name": "Preferences to Items",
"type": "n8n-nodes-base.code",
"position": [
1380,
900
],
"parameters": {
"jsCode": "return [\n { text: $input.first().json.text },\n { text: $input.first().json.text2 }\n]"
},
"typeVersion": 2
},
{
"id": "7d6bda64-4f98-43d1-b181-343238f678bb",
"name": "Aggregate 向量嵌入",
"type": "n8n-nodes-base.aggregate",
"position": [
1780,
900
],
"parameters": {
"options": {},
"fieldsToAggregate": {
"fieldToAggregate": [
{
"renameField": true,
"outputFieldName": "embeddings",
"fieldToAggregate": "data[0].embedding"
}
]
}
},
"typeVersion": 1
},
{
"id": "8eacac44-9cfd-4aa0-be7d-534ae630a2d4",
"name": "Get 向量嵌入1",
"type": "n8n-nodes-base.httpRequest",
"position": [
1380,
560
],
"parameters": {
"url": "https://api.openai.com/v1/embeddings",
"method": "POST",
"options": {},
"sendBody": true,
"authentication": "predefinedCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "input",
"value": "={{ $json.text }}"
},
{
"name": "model",
"value": "text-embedding-3-small"
}
]
},
"nodeCredentialType": "openAiApi"
},
"credentials": {
"openAiApi": {
"id": "8gccIjcuf3gvaoEr",
"name": "OpenAi account"
}
},
"typeVersion": 4.2
},
{
"id": "5b23221c-aeb8-4a4f-b33b-75d46ba7a4fd",
"name": "Aggregate 向量嵌入1",
"type": "n8n-nodes-base.aggregate",
"position": [
1580,
560
],
"parameters": {
"options": {},
"fieldsToAggregate": {
"fieldToAggregate": [
{
"renameField": true,
"outputFieldName": "embeddings",
"fieldToAggregate": "data[0].embedding"
}
]
}
},
"typeVersion": 1
},
{
"id": "bbbfaf2f-8294-401f-9f01-efeb58e99f15",
"name": "Group Search API",
"type": "n8n-nodes-base.httpRequest",
"position": [
1780,
560
],
"parameters": {
"url": "http://qdrant:6333/collections/trustpilot_reviews/points/search/groups",
"method": "POST",
"options": {},
"jsonBody": "={{\n{\n \"vector\": $json.embeddings[0],\n \"group_by\": \"metadata.company_id\",\n \"limit\": 10,\n \"group_size\": 3,\n \"with_payload\": true\n}\n}}",
"sendBody": true,
"specifyBody": "json",
"authentication": "predefinedCredentialType",
"nodeCredentialType": "qdrantApi"
},
"credentials": {
"qdrantApi": {
"id": "NyinAS3Pgfik66w5",
"name": "QdrantApi account"
}
},
"typeVersion": 4.2
},
{
"id": "bbed1c97-eebb-47f1-9486-73bade35d290",
"name": "Has Results?",
"type": "n8n-nodes-base.if",
"position": [
2600,
560
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "a83c0c10-74a7-4a52-b6c4-26dc8313023b",
"operator": {
"type": "object",
"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "e995b27a-f331-434c-a828-bc02f978b43c",
"name": "Simplify Group Results",
"type": "n8n-nodes-base.set",
"position": [
2180,
560
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "caf5bf23-087a-496f-8d20-56ab70e303a8",
"name": "category",
"type": "string",
"value": "={{ $json.id }}"
},
{
"id": "db3c2c92-b951-4365-9c19-d5d0f8654a42",
"name": "results",
"type": "array",
"value": "={{\n$json.hits?.map(hit => ({\n content: hit.payload.content,\n metadata: hit.payload.metadata\n}))\n}}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "e0c327a5-ab2e-46ad-9d4b-0fe8cdd1605c",
"name": "Empty Compare Response",
"type": "n8n-nodes-base.set",
"position": [
2820,
660
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "24ab771e-0e19-4bfe-bfee-2fed3a34f7fe",
"name": "response",
"type": "string",
"value": "no results."
}
]
}
},
"typeVersion": 3.4
},
{
"id": "52890718-81b4-4880-9a12-b8456e96ad98",
"name": "聚合 Compare Response",
"type": "n8n-nodes-base.aggregate",
"position": [
2820,
440
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData",
"destinationFieldName": "response"
},
"typeVersion": 1
},
{
"id": "bb87afe4-6910-4c79-9371-d49e77134ac3",
"name": "OpenAI 嵌入",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"position": [
1340,
-40
],
"parameters": {
"options": {}
},
"credentials": {
"openAiApi": {
"id": "8gccIjcuf3gvaoEr",
"name": "OpenAi account"
}
},
"typeVersion": 1.2
},
{
"id": "ba6e426b-9629-445f-b96c-b8b51fcafe3d",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
1460,
-40
],
"parameters": {
"options": {
"metadata": {
"metadataValues": [
{
"name": "company_id",
"value": "={{ $json.companyIds ?? 'unspecified' }}"
}
]
}
},
"jsonData": "={{ $json.text }}",
"jsonMode": "expressionData"
},
"typeVersion": 1
},
{
"id": "de9e7ffa-49e8-40de-acef-fd92216ec10c",
"name": "递归字符文本分割器",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
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"parameters": {
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"chunkSize": 3000
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{
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"content": "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n### 🚨Configure Your Qdrant Connection\n* Be sure to enter your endpoint address"
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"content": "## Try It Out!\n### This n8n demonstrates how to build your own Qdrant MCP server to extend its functionality beyond that of the official implementation.\n\nThis n8n implementation exposes other cool API features from Qdrant such as facet search, grouped search and recommendations APIs. With this, we can build an easily customisable and maintainable Qdrant MCP server for business intelligence.\n\nThis MCP example is based off an official MCP reference implementation which can be found here -https://github.com/qdrant/mcp-server-qdrant/\n\n### How it works\n* A MCP server trigger is used and connected to 5 custom workflow tools. We're using custom workflow tools as there is quite a few nodes required for each task.\n* We use a mix of n8n supported Qdrant nodes for simple operations such as insert documents and similarity search, and HTTP node to hit the Qdrant API directly for Facet search, group search and recommendations.\n* We use \"Edit Field\" and \"Aggregate\" nodes to return suitable responses to the MCP client.\n\n### How to use\n* This Qdrant MCP server allows any compatible MCP client to manage a Qdrant Collection by supporting select and create operations. You will need to have a collection available before you can use this server. Use the Prerequisite manual steps to get started!\n* Connect your MCP client by following the n8n guidelines here - https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger/#integrating-with-claude-desktop\n* Try the following queries in your MCP client:\n * \"Can you help me list the available companies in the collection?\"\n * \"What do customers say about product deliveries from company X?\"\n * \"What do customers of company X and company Y say about product ease of use?\"\n\n### Requirements\n* Qdrant for vector store. This can be an a cloud-hosted instance or one you can self-host internally.\n* MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download\n\n### Customising this workflow\n* Depending on what queries you'll receive, adjust the tool inputs to make it easier for the agent to set the right parameters.\n* Not interested in Reviews? The techniques shared in this template can be used for other types of collections.\n* Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!"
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"jsonBody": "{\n \"vectors\": {\n \"distance\": \"Cosine\",\n \"size\": 1536\n }\n}",
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"content": "## Prerequisite: Setup Qdrant Collection\nIf you don't have an existing Qdrant Collection, you can use this manual flow to get started.\n1. Creates a collection called \"trustpilot_reviews\"\n2. Creates an index to allow for facet search ie. list of values of a the \"company_id\" metadata key."
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"index": 0
}
]
]
}
}
}常见问题
如何使用这个工作流？
复制上方的 JSON 配置代码，在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」，粘贴配置后根据需要修改凭证设置即可。
这个工作流适合什么场景？
高级 - 构建模块, 人工智能
需要付费吗？
本工作流完全免费，您可以直接导入使用。但请注意，工作流中使用的第三方服务（如 OpenAI API）可能需要您自行付费。
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节点数量44
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节点类型17
作者
Jimleuk
@jimleukFreelance consultant based in the UK specialising in AI-powered automations. I work with select clients tackling their most challenging projects. For business enquiries, send me an email at hello@jimle.uk LinkedIn: https://www.linkedin.com/in/jimleuk/ X/Twitter: https://x.com/jimle_uk
外部链接
在 n8n.io 查看 →
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