RAG 流水线
中级
这是一个Engineering, AI领域的自动化工作流,包含 13 个节点。主要使用 FormTrigger, Agent, ChatTrigger, LmChatOllama, EmbeddingsOllama 等节点,结合人工智能技术实现智能自动化。 基于检索增强生成(RAG)的本地聊天机器人
前置要求
- •Qdrant 服务器连接信息
使用的节点 (13)
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
{
"id": "L9nteAq0NLYqIGxH",
"meta": {
"instanceId": "558d88703fb65b2d0e44613bc35916258b0f0bf983c5d4730c00c424b77ca36a",
"templateCredsSetupCompleted": true
},
"name": "RAG 流水线",
"tags": [],
"nodes": [
{
"id": "a00e5b5b-1cc1-4272-9790-8ffde3c92efb",
"name": "表单提交时",
"type": "n8n-nodes-base.formTrigger",
"position": [
0,
0
],
"webhookId": "4e1e20d4-f759-42c8-8439-87b93f43aa7c",
"parameters": {
"options": {},
"formTitle": "Add your file here",
"formFields": {
"values": [
{
"fieldType": "file",
"fieldLabel": "File",
"requiredField": true,
"acceptFileTypes": ".pdf"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "1218186e-a93e-4e05-b47e-a395f28cf5f9",
"name": "Qdrant 向量存储",
"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
"position": [
220,
0
],
"parameters": {
"mode": "insert",
"options": {},
"qdrantCollection": {
"__rl": true,
"mode": "id",
"value": "rag_collection"
}
},
"credentials": {
"qdrantApi": {
"id": "sFfERYppMeBnFNeA",
"name": "Local QdrantApi database"
}
},
"typeVersion": 1.2
},
{
"id": "9c7fb858-b571-4626-b976-d3e1995c464b",
"name": "嵌入 Ollama",
"type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
"position": [
60,
220
],
"parameters": {
"model": "mxbai-embed-large:latest"
},
"credentials": {
"ollamaApi": {
"id": "xHuYe0MDGOs9IpBW",
"name": "Local Ollama service"
}
},
"typeVersion": 1
},
{
"id": "af14443b-ae01-48dc-8552-5ded7a27fce2",
"name": "默认数据加载器",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
360,
220
],
"parameters": {
"options": {},
"dataType": "binary"
},
"typeVersion": 1
},
{
"id": "660380c5-63da-4404-98e6-f9c0ee9aaa90",
"name": "递归字符文本分割器",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
460,
440
],
"parameters": {
"options": {},
"chunkSize": 200,
"chunkOverlap": 50
},
"typeVersion": 1
},
{
"id": "49dbe387-751f-4a2e-8803-290bc2c06ec5",
"name": "便签",
"type": "n8n-nodes-base.stickyNote",
"position": [
-140,
-100
],
"parameters": {
"color": 3,
"width": 840,
"height": 700,
"content": "## 数据摄取"
},
"typeVersion": 1
},
{
"id": "45683271-af59-41d0-9e69-af721d566661",
"name": "当收到聊天消息时",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
940,
-20
],
"webhookId": "5e56a263-3a40-44bd-bc9d-1cfb3bc2a87d",
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "af562588-2e8c-4c0b-b041-d6fc8c0affd0",
"name": "AI 代理",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1220,
-20
],
"parameters": {
"options": {
"systemMessage": "You are a helpful assistant. You have access to a tool to retrieve data from a semantic database to answer questions. Always provide arguments when you execute the tool"
}
},
"typeVersion": 2
},
{
"id": "4d924b4a-fe07-4606-8385-613d6ea14991",
"name": "## 🧠 LLM 总结",
"type": "@n8n/n8n-nodes-langchain.lmChatOllama",
"position": [
1060,
220
],
"parameters": {
"options": {}
},
"credentials": {
"ollamaApi": {
"id": "xHuYe0MDGOs9IpBW",
"name": "Local Ollama service"
}
},
"typeVersion": 1
},
{
"id": "de87b7bb-6fec-4d8f-a77a-25bc3a30a038",
"name": "简单记忆",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
1260,
220
],
"parameters": {},
"typeVersion": 1.3
},
{
"id": "16261539-5218-4df1-8b14-915dd3377167",
"name": "Qdrant 向量存储1",
"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
"position": [
1540,
240
],
"parameters": {
"mode": "retrieve-as-tool",
"options": {},
"toolName": "retriever",
"toolDescription": "Retrieve data from a semantic database to answer questions",
"qdrantCollection": {
"__rl": true,
"mode": "id",
"value": "rag_collection"
}
},
"credentials": {
"qdrantApi": {
"id": "sFfERYppMeBnFNeA",
"name": "Local QdrantApi database"
}
},
"typeVersion": 1.2
},
{
"id": "57d3be1d-73cd-4464-a3f3-7dd4a3157cdf",
"name": "嵌入 Ollama1",
"type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
"position": [
1460,
440
],
"parameters": {
"model": "mxbai-embed-large:latest"
},
"credentials": {
"ollamaApi": {
"id": "xHuYe0MDGOs9IpBW",
"name": "Local Ollama service"
}
},
"typeVersion": 1
},
{
"id": "5919cc58-05f4-42c8-aada-3782a16574d9",
"name": "便签1",
"type": "n8n-nodes-base.stickyNote",
"position": [
740,
-100
],
"parameters": {
"color": 4,
"width": 1200,
"height": 700,
"content": "## RAG 聊天机器人"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "895c0261-fbf5-4bb6-9581-4cea3c4d20bd",
"connections": {
"Simple Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Embeddings Ollama": {
"ai_embedding": [
[
{
"node": "Qdrant Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Ollama Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Embeddings Ollama1": {
"ai_embedding": [
[
{
"node": "Qdrant Vector Store1",
"type": "ai_embedding",
"index": 0
}
]
]
},
"On form submission": {
"main": [
[
{
"node": "Qdrant Vector Store",
"type": "main",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Qdrant Vector Store",
"type": "ai_document",
"index": 0
}
]
]
},
"Qdrant Vector Store1": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Recursive Character Text Splitter": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"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?
中级 - 工程, 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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