ファイル検索RAG用のOpenAI参照を作成
上級
これはAI分野の自動化ワークフローで、19個のノードを含みます。主にSet, Code, Markdown, SplitOut, Aggregateなどのノードを使用、AI技術を活用したスマート自動化を実現。 ファイル検索用RAGのためのOpenAI引用の作成
前提条件
- •ターゲットAPIの認証情報が必要な場合あり
- •OpenAI API Key
カテゴリー
ワークフロープレビュー
ノード接続関係を可視化、ズームとパンをサポート
ワークフローをエクスポート
以下のJSON設定をn8nにインポートして、このワークフローを使用できます
{
"id": "5NAbfX550LJsfz6f",
"meta": {
"instanceId": "00493e38fecfc163cb182114bc2fab90114038eb9aad665a7a752d076920d3d5",
"templateCredsSetupCompleted": true
},
"name": "Make OpenAI Citation for File Retrieval RAG",
"tags": [
{
"id": "urxRtGxxLObZWPvX",
"name": "sample",
"createdAt": "2024-09-13T02:43:13.014Z",
"updatedAt": "2024-09-13T02:43:13.014Z"
},
{
"id": "nMXS3c9l1WqDwWF5",
"name": "assist",
"createdAt": "2024-12-23T16:09:38.737Z",
"updatedAt": "2024-12-23T16:09:38.737Z"
}
],
"nodes": [
{
"id": "b9033511-3421-467a-9bfa-73af01b99c4f",
"name": "集計",
"type": "n8n-nodes-base.aggregate",
"position": [
740,
120
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "a61dd9d3-4faa-4878-a6f3-ba8277279002",
"name": "ウィンドウバッファメモリ",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
980,
-320
],
"parameters": {},
"typeVersion": 1.3
},
{
"id": "2daabca5-37ec-4cad-9157-29926367e1a7",
"name": "付箋4",
"type": "n8n-nodes-base.stickyNote",
"position": [
220,
320
],
"parameters": {
"color": 3,
"width": 840,
"height": 80,
"content": "## Within N8N, there will be a chat button to test"
},
"typeVersion": 1
},
{
"id": "bf4485b1-cd94-41c8-a183-bf1b785f2761",
"name": "付箋",
"type": "n8n-nodes-base.stickyNote",
"position": [
-440,
-520
],
"parameters": {
"color": 5,
"width": 500,
"height": 720,
"content": "## Make OpenAI Citation for File Retrieval RAG\n\n## Use case\n\nIn this example, we will ensure that all texts from the OpenAI assistant search for citations and sources in the vector store files. We can also format the output for Markdown or HTML tags.\n\nThis is necessary because the assistant sometimes generates strange characters, and we can also use dynamic references such as citations 1, 2, 3, for example.\n\n## What this workflow does\n\nIn this workflow, we will use an OpenAI assistant created within their interface, equipped with a vector store containing some files for file retrieval.\n\nThe assistant will perform the file search within the OpenAI infrastructure and will return the content with citations.\n\n- We will make an HTTP request to retrieve all the details we need to format the text output.\n\n## Setup\n\nInsert an OpenAI Key\n\n## How to adjust it to your needs\n\nAt the end of the workflow, we have a block of code that will format the output, and there we can add Markdown tags to create links. Optionally, we can transform the Markdown formatting into HTML.\n\n\nby Davi Saranszky Mesquita\nhttps://www.linkedin.com/in/mesquitadavi/"
},
"typeVersion": 1
},
{
"id": "539a4e40-9745-4a26-aba8-2cc2b0dd6364",
"name": "Create a simple Trigger to have the Chat button within N8N",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"notes": "https://www.npmjs.com/package/@n8n/chat",
"position": [
260,
-520
],
"webhookId": "8ccaa299-6f99-427b-9356-e783893a3d0c",
"parameters": {
"options": {}
},
"notesInFlow": true,
"typeVersion": 1.1
},
{
"id": "aa5b2951-df32-43ac-9939-83b02d818e73",
"name": "OpenAI Assistant with Vector Store",
"type": "@n8n/n8n-nodes-langchain.openAi",
"position": [
580,
-520
],
"parameters": {
"options": {
"preserveOriginalTools": false
},
"resource": "assistant",
"assistantId": {
"__rl": true,
"mode": "list",
"value": "asst_QAfdobVCVCMJz8LmaEC7nlId",
"cachedResultName": "Teste"
}
},
"credentials": {
"openAiApi": {
"id": "UfNrqPCRlD8FD9mk",
"name": "OpenAi Lourival"
}
},
"typeVersion": 1.7
},
{
"id": "1817b673-6cb3-49aa-9f38-a5876eb0e6fa",
"name": "付箋1",
"type": "n8n-nodes-base.stickyNote",
"position": [
560,
-680
],
"parameters": {
"width": 300,
"content": "## Setup\n\n- Configure OpenAI Key\n\n### In this step, we will use an assistant created within the OpenAI platform that contains a vector store a.k.a file retrieval"
},
"typeVersion": 1
},
{
"id": "16429226-e850-4698-b419-fd9805a03fb7",
"name": "Get ALL Thread Content",
"type": "n8n-nodes-base.httpRequest",
"position": [
1260,
-520
],
"parameters": {
"url": "=https://api.openai.com/v1/threads/{{ $json.threadId }}/messages",
"options": {},
"sendHeaders": true,
"authentication": "predefinedCredentialType",
"headerParameters": {
"parameters": [
{
"name": "OpenAI-Beta",
"value": "assistants=v2"
}
]
},
"nodeCredentialType": "openAiApi"
},
"credentials": {
"openAiApi": {
"id": "UfNrqPCRlD8FD9mk",
"name": "OpenAi Lourival"
}
},
"typeVersion": 4.2,
"alwaysOutputData": true
},
{
"id": "e8c88b08-5be2-4f7e-8b17-8cf804b3fe9f",
"name": "付箋2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1160,
-620
],
"parameters": {
"content": "### Retrieving all thread content is necessary because the OpenAI tool does not retrieve all citations upon request."
},
"typeVersion": 1
},
{
"id": "0f51e09f-2782-4e2d-b797-d4d58fcabdaf",
"name": "Split all message iterations from a thread",
"type": "n8n-nodes-base.splitOut",
"position": [
220,
-300
],
"parameters": {
"options": {},
"fieldToSplitOut": "data"
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "4d569993-1ce3-4b32-beaf-382feac25da9",
"name": "Split all content from a single message",
"type": "n8n-nodes-base.splitOut",
"position": [
460,
-300
],
"parameters": {
"options": {},
"fieldToSplitOut": "content"
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "999e1c2b-1927-4483-aac1-6e8903f7ed25",
"name": "Split all citations from a single message",
"type": "n8n-nodes-base.splitOut",
"position": [
700,
-300
],
"parameters": {
"options": {},
"fieldToSplitOut": "text.annotations"
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "98af62f5-adb0-4e07-a146-fc2f13b851ce",
"name": "Retrieve file name from a file ID",
"type": "n8n-nodes-base.httpRequest",
"onError": "continueRegularOutput",
"position": [
220,
120
],
"parameters": {
"url": "=https://api.openai.com/v1/files/{{ $json.file_citation.file_id }}",
"options": {},
"sendQuery": true,
"authentication": "predefinedCredentialType",
"queryParameters": {
"parameters": [
{
"name": "limit",
"value": "1"
}
]
},
"nodeCredentialType": "openAiApi"
},
"credentials": {
"openAiApi": {
"id": "UfNrqPCRlD8FD9mk",
"name": "OpenAi Lourival"
}
},
"typeVersion": 4.2,
"alwaysOutputData": true
},
{
"id": "b11f0d3d-bdc4-4845-b14b-d0b0de214f01",
"name": "Regularize output",
"type": "n8n-nodes-base.set",
"position": [
480,
120
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "2dcaafee-5037-4a97-942a-bcdd02bc2ad9",
"name": "id",
"type": "string",
"value": "={{ $json.id }}"
},
{
"id": "b63f967d-ceea-4aa8-98b9-91f5ab21bfe8",
"name": "filename",
"type": "string",
"value": "={{ $json.filename }}"
},
{
"id": "f611e749-054a-441d-8610-df8ba42de2e1",
"name": "text",
"type": "string",
"value": "={{ $('Split all citations from a single message').item.json.text }}"
}
]
}
},
"typeVersion": 3.4,
"alwaysOutputData": true
},
{
"id": "0e999a0e-76ed-4897-989b-228f075e9bfb",
"name": "付箋3",
"type": "n8n-nodes-base.stickyNote",
"position": [
440,
-60
],
"parameters": {
"width": 200,
"height": 220,
"content": "### A file retrieval request contains a lot of information, and we want only the text that will be substituted and the file name.\n\n- id\n- filename\n- text\n"
},
"typeVersion": 1
},
{
"id": "53c79a6c-7543-435f-b40e-966dff0904d4",
"name": "付箋5",
"type": "n8n-nodes-base.stickyNote",
"position": [
700,
-60
],
"parameters": {
"width": 200,
"height": 220,
"content": "### With the last three splits, we may have many citations and texts to substitute. By doing an aggregation, it will be possible to handle everything as a single request."
},
"typeVersion": 1
},
{
"id": "381fb6d6-64fc-4668-9d3c-98aaa43a45ca",
"name": "付箋6",
"type": "n8n-nodes-base.stickyNote",
"position": [
960,
-60
],
"parameters": {
"height": 220,
"content": "### This simple code will take all the previous files and citations and alter the original text, formatting the output. In this way, we can use Markdown tags to create links, or if you prefer, we can add an HTML transformation node."
},
"typeVersion": 1
},
{
"id": "d0cbb943-57ab-4850-8370-1625610a852a",
"name": "Optional Markdown to HTML",
"type": "n8n-nodes-base.markdown",
"disabled": true,
"position": [
1220,
120
],
"parameters": {
"html": "={{ $json.output }}",
"options": {},
"destinationKey": "output"
},
"typeVersion": 1
},
{
"id": "589e2418-5dec-47d0-ba08-420d84f09da7",
"name": "Finnaly format the output",
"type": "n8n-nodes-base.code",
"position": [
980,
120
],
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "let saida = $('OpenAI Assistant with Vector Store').item.json.output;\n\nfor (let i of $input.item.json.data) {\n saida = saida.replaceAll(i.text, \" _(\"+ i.filename+\")_ \");\n}\n\n$input.item.json.output = saida;\nreturn $input.item;"
},
"typeVersion": 2
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "0e621a5a-d99d-4db3-9ae4-ea98c31467e9",
"connections": {
"Aggregate": {
"main": [
[
{
"node": "589e2418-5dec-47d0-ba08-420d84f09da7",
"type": "main",
"index": 0
}
]
]
},
"b11f0d3d-bdc4-4845-b14b-d0b0de214f01": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
},
"Window Buffer Memory": {
"ai_memory": [
[
{
"node": "aa5b2951-df32-43ac-9939-83b02d818e73",
"type": "ai_memory",
"index": 0
}
]
]
},
"16429226-e850-4698-b419-fd9805a03fb7": {
"main": [
[
{
"node": "0f51e09f-2782-4e2d-b797-d4d58fcabdaf",
"type": "main",
"index": 0
}
]
]
},
"589e2418-5dec-47d0-ba08-420d84f09da7": {
"main": [
[
{
"node": "d0cbb943-57ab-4850-8370-1625610a852a",
"type": "main",
"index": 0
}
]
]
},
"98af62f5-adb0-4e07-a146-fc2f13b851ce": {
"main": [
[
{
"node": "b11f0d3d-bdc4-4845-b14b-d0b0de214f01",
"type": "main",
"index": 0
}
]
]
},
"aa5b2951-df32-43ac-9939-83b02d818e73": {
"main": [
[
{
"node": "16429226-e850-4698-b419-fd9805a03fb7",
"type": "main",
"index": 0
}
]
]
},
"4d569993-1ce3-4b32-beaf-382feac25da9": {
"main": [
[
{
"node": "999e1c2b-1927-4483-aac1-6e8903f7ed25",
"type": "main",
"index": 0
}
]
]
},
"999e1c2b-1927-4483-aac1-6e8903f7ed25": {
"main": [
[
{
"node": "98af62f5-adb0-4e07-a146-fc2f13b851ce",
"type": "main",
"index": 0
}
]
]
},
"0f51e09f-2782-4e2d-b797-d4d58fcabdaf": {
"main": [
[
{
"node": "4d569993-1ce3-4b32-beaf-382feac25da9",
"type": "main",
"index": 0
}
]
]
},
"539a4e40-9745-4a26-aba8-2cc2b0dd6364": {
"main": [
[
{
"node": "aa5b2951-df32-43ac-9939-83b02d818e73",
"type": "main",
"index": 0
}
]
]
}
}
}よくある質問
このワークフローの使い方は？
上記のJSON設定コードをコピーし、n8nインスタンスで新しいワークフローを作成して「JSONからインポート」を選択、設定を貼り付けて認証情報を必要に応じて変更してください。
このワークフローはどんな場面に適していますか？
上級 - 人工知能
有料ですか？
このワークフローは完全無料です。ただし、ワークフローで使用するサードパーティサービス（OpenAI APIなど）は別途料金が発生する場合があります。
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