使用 RAG 和 Google Gemini API 的 IPL 板球规则问答聊天机器人
高级
这是一个Engineering, Multimodal AI领域的自动化工作流，包含 24 个节点。主要使用 HttpRequest, ManualTrigger, Agent, ChatTrigger, LmChatGoogleGemini 等节点。 基于 RAG 和 Google Gemini API 的 IPL 板球规则问答聊天机器人
前置要求
- •可能需要目标 API 的认证凭证
- •Google Gemini API Key
使用的节点 (24)
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": "CkgF5zRqCL4BS6I5",
"meta": {
"instanceId": "5c50f3d58b333c0490a31213f0ec76116e02346dcdd9088649ba9dd6fbe45ca1",
"templateCredsSetupCompleted": true
},
"name": "使用 RAG 和 Google Gemini API 的 IPL 板球规则问答聊天机器人",
"tags": [],
"nodes": [
{
"id": "4c32f558-efff-4eff-b714-202c7419a96c",
"name": "当收到聊天消息时",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
-1216,
192
],
"webhookId": "4df707a8-70c8-4fab-a970-a97ce7d7594f",
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "352186bb-07d1-4d7d-9f0f-b57e0880fc11",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-1008,
64
],
"parameters": {
"options": {
"systemMessage": "You are a cricket expert. \n\nYou are tasked with answering questions on ipl cricket queries. Information should only be referred to and provided if it is provided explicitly in the data base to you. Your goal is to provide accurate information based on this information.\n\nIf information is not provided to you explicitly or if you can not answer the question using the provided information, say \"Sorry I donot know\""
}
},
"typeVersion": 2.1
},
{
"id": "15f7fbdc-ab77-4007-9a8e-8ddbe881d984",
"name": "简单记忆",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
-784,
336
],
"parameters": {
"contextWindowLength": 20
},
"typeVersion": 1.3
},
{
"id": "dc61d50a-fdd8-4a21-974f-33aa8aab5c0a",
"name": "简单向量存储",
"type": "@n8n/n8n-nodes-langchain.vectorStoreInMemory",
"position": [
-720,
176
],
"parameters": {
"mode": "retrieve-as-tool",
"topK": 10,
"memoryKey": {
"__rl": true,
"mode": "list",
"value": "vector_store_key"
},
"toolDescription": "This is a repository of ipl cricket rules and international cricket rules"
},
"typeVersion": 1.3
},
{
"id": "69f8782c-c5d2-4693-bc00-a2ab58c61e08",
"name": "Google Gemini聊天模型",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
-944,
336
],
"parameters": {
"options": {
"topP": 0.3
}
},
"credentials": {
"googlePalmApi": {
"id": "3f4CCF4BMZnEfG6y",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "33d9a2a4-6f13-4cbe-a3b3-19f3d0b7d6a1",
"name": "嵌入 Google Gemini",
"type": "@n8n/n8n-nodes-langchain.embeddingsGoogleGemini",
"position": [
-608,
320
],
"parameters": {},
"credentials": {
"googlePalmApi": {
"id": "3f4CCF4BMZnEfG6y",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "05bbad6c-877c-4d6d-90e1-6c82d6560ae2",
"name": "简单向量存储1",
"type": "@n8n/n8n-nodes-langchain.vectorStoreInMemory",
"position": [
-896,
-544
],
"parameters": {
"mode": "insert",
"memoryKey": {
"__rl": true,
"mode": "list",
"value": "vector_store_key"
}
},
"typeVersion": 1.3
},
{
"id": "34948452-2e69-40cc-9b86-b78500873aab",
"name": "嵌入 Google Gemini1",
"type": "@n8n/n8n-nodes-langchain.embeddingsGoogleGemini",
"position": [
-896,
-320
],
"parameters": {},
"credentials": {
"googlePalmApi": {
"id": "3f4CCF4BMZnEfG6y",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "d6b2871c-78c6-4785-8913-262eb2364f7d",
"name": "默认数据加载器",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
-720,
-400
],
"parameters": {
"options": {},
"dataType": "binary",
"textSplittingMode": "custom"
},
"typeVersion": 1.1
},
{
"id": "6818e50a-ecc1-40e5-aac9-9d38fc85d3ec",
"name": "递归字符文本分割器",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
-704,
-256
],
"parameters": {
"options": {},
"chunkOverlap": 200
},
"typeVersion": 1
},
{
"id": "48da425a-c41f-4301-b4a7-df00f604ba5b",
"name": "HTTP 请求",
"type": "n8n-nodes-base.httpRequest",
"position": [
-1040,
-448
],
"parameters": {
"url": "https://documents.iplt20.com/bcci/documents/1742707993986_Match_Playing_Conditions.pdf",
"options": {}
},
"typeVersion": 4.2
},
{
"id": "3fc9062b-fdef-421d-a7a3-d348c83cb51c",
"name": "当点击\"执行工作流\"时",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-1232,
-448
],
"parameters": {},
"typeVersion": 1
},
{
"id": "60491e32-d0c1-4e4a-922f-8ce976b481d1",
"name": "便签",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2576,
-48
],
"parameters": {
"color": 6,
"width": 2144,
"height": 624,
"content": "## 步骤 2"
},
"typeVersion": 1
},
{
"id": "1909411f-90b0-4cd5-823a-39f4f918cc5e",
"name": "便签 1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2576,
-624
],
"parameters": {
"width": 2160,
"height": 544,
"content": "## 步骤 1"
},
"typeVersion": 1
},
{
"id": "63e38b73-3e30-47d7-86bb-afa2ad92dc2b",
"name": "便签7",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2576,
-768
],
"parameters": {
"color": 5,
"width": 2160,
"height": 128,
"content": "## 此工作流程包含 2 个主要步骤"
},
"typeVersion": 1
},
{
"id": "f45e2852-88a8-4f70-a124-01f2b06d9a19",
"name": "便签 2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1232,
-544
],
"parameters": {
"color": 3,
"width": 278,
"height": 80,
"content": "## 步骤 1.1"
},
"typeVersion": 1
},
{
"id": "0b72e856-23c6-42c2-860e-8f761f861d95",
"name": "便签 3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-608,
-304
],
"parameters": {
"color": 3,
"width": 166,
"height": 128,
"content": "## 步骤 1.2"
},
"typeVersion": 1
},
{
"id": "96c343b7-3961-49c1-97e0-35b4eee90d78",
"name": "便签 4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1088,
-240
],
"parameters": {
"color": 3,
"width": 150,
"height": 80,
"content": "## 步骤 1.4"
},
"typeVersion": 1
},
{
"id": "f78516ba-4b17-4e48-9450-ba5d7cb123f1",
"name": "便签 5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-592,
-544
],
"parameters": {
"color": 3,
"width": 150,
"height": 80,
"content": "## 步骤 1.5"
},
"typeVersion": 1
},
{
"id": "b97281a4-6b1f-41a1-9a1e-c48be5a6854c",
"name": "便签6",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1248,
96
],
"parameters": {
"color": 4,
"width": 160,
"height": 80,
"content": "## 步骤 2.1"
},
"typeVersion": 1
},
{
"id": "a8de0dce-eaa0-441d-b050-5374741f3b5f",
"name": "便签8",
"type": "n8n-nodes-base.stickyNote",
"position": [
-976,
464
],
"parameters": {
"color": 4,
"width": 160,
"height": 80,
"content": "## 步骤 2.4"
},
"typeVersion": 1
},
{
"id": "1f405862-c83e-4687-b919-3e128bcd2073",
"name": "便签9",
"type": "n8n-nodes-base.stickyNote",
"position": [
-608,
64
],
"parameters": {
"color": 4,
"width": 160,
"height": 80,
"content": "## 步骤 2.3"
},
"typeVersion": 1
},
{
"id": "dfb4cbe2-f6b0-45c4-bda7-d5f33a3b8e5f",
"name": "便签 10",
"type": "n8n-nodes-base.stickyNote",
"position": [
-800,
464
],
"parameters": {
"color": 4,
"width": 160,
"height": 80,
"content": "## 步骤 2.2"
},
"typeVersion": 1
},
{
"id": "c5cfbb0b-2d09-40b8-ba18-5c4028d8a556",
"name": "便签11",
"type": "n8n-nodes-base.stickyNote",
"position": [
-928,
-32
],
"parameters": {
"color": 4,
"width": 160,
"height": 80,
"content": "## 步骤 2.5"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "98c130a5-eef0-4246-8a95-88a29c4e8ce6",
"connections": {
"HTTP Request": {
"main": [
[
{
"node": "Simple Vector Store1",
"type": "main",
"index": 0
}
]
]
},
"Simple Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Simple Vector Store1",
"type": "ai_document",
"index": 0
}
]
]
},
"Simple Vector Store": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Embeddings Google Gemini": {
"ai_embedding": [
[
{
"node": "Simple Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Embeddings Google Gemini1": {
"ai_embedding": [
[
{
"node": "Simple Vector Store1",
"type": "ai_embedding",
"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
}
]
]
},
"When clicking ‘Execute workflow’": {
"main": [
[
{
"node": "HTTP Request",
"type": "main",
"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 - 工程, 多模态 AI
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。
相关工作流推荐
使用Gemini RAG管道构建文档专家聊天机器人
使用Gemini RAG管道构建文档专家聊天机器人
Set
Html
Filter
+16
48 节点Lucas Peyrin
内部知识库
在可视化参考库中探索n8n节点
在可视化参考库中探索n8n节点
If
Ftp
Set
+93
113 节点I versus AI
其他
🤖 使用 RAG、Gemini 和 Supabase 创建文档专家机器人
🤖 使用 RAG、Gemini 和 Supabase 创建文档专家机器人
Set
Html
Filter
+18
54 节点Lucas Peyrin
内部知识库
AI智能助手：与Supabase存储和Google Drive文件对话
AI智能助手：与Supabase存储和Google Drive文件对话
If
Set
Wait
+20
62 节点Mark Shcherbakov
工程
使用RAG（Pinecone和OpenAI）与GitHub OpenAPI规范对话
与GitHub API文档对话：基于RAG的聊天机器人，使用Pinecone和OpenAI
Http Request
Manual Trigger
Agent
+9
17 节点Mihai Farcas
工程
基于 GPT-4、Stripe 和 CRM 集成的 WooCommerce 对话式销售代理
基于 GPT-4、Stripe 和 CRM 集成的 WooCommerce 对话式销售代理
Set
Google Drive
Http Request
+16
27 节点Cong Nguyen
AI 聊天机器人
