SQL agent with memory
Empower your data analysis with the SQL agent with memory workflow, automating the process of querying databases using natural language. This powerful workflow connects OpenAI's advanced language models with your local SQL databases, allowing you to interact with your data through a conversational interface. Initially, the workflow downloads a chinook.zip example database, extracts it, and saves the chinook.db file locally, making it immediately available for querying. The AI Agent, powered by OpenAI Chat Model and supported by a Window Buffer Memory, interprets your natural language questions, translates them into SQL queries, executes them against your local chinook.db, and provides the results back to you. This is incredibly useful for data analysts, business intelligence professionals, or anyone needing quick insights from their databases without writing complex SQL queries, significantly reducing the time and specialized knowledge required for data exploration. By leveraging the Chat Trigger, users can easily initiate conversations and receive immediate, intelligent responses, streamlining data access and accelerating decision-making.
Workflow JSON
{"id": "AQJ6QnF2yVdCWMnx", "meta": {"instanceId": "fb924c73af8f703905bc09c9ee8076f48c17b596ed05b18c0ff86915ef8a7c4a", "templateCredsSetupCompleted": true}, "name": "SQL agent with memory", "tags": [], "nodes": [{"id": "3544950e-4d8e-46ca-8f56-61c152a5cae3", "name": "Window Buffer Memory", "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow", "position": [1220, 500], "parameters": {"contextWindowLength": 10}, "typeVersion": 1.2}, {"id": "743cc4e7-5f24-4adc-b872-7241ee775bd0", "name": "OpenAI Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [1000, 500], "parameters": {"model": "gpt-4-turbo", "options": {"temperature": 0.3}}, "credentials": {"openAiApi": {"id": "", "name": "[Your openAiApi]"}}, "typeVersion": 1}, {"id": "cc30066c-ad2c-4729-82c1-a6b0f4214dee", "name": "When clicking \"Test workflow\"", "type": "n8n-nodes-base.manualTrigger", "position": [500, -80], "parameters": {}, "typeVersion": 1}, {"id": "0deacd0d-45cb-4738-8da0-9d1251858867", "name": "Get chinook.zip example", "type": "n8n-nodes-base.httpRequest", "position": [700, -80], "parameters": {"url": "https://www.sqlitetutorial.net/wp-content/uploads/2018/03/chinook.zip", "options": {}}, "typeVersion": 4.2}, {"id": "61f34708-f8ed-44a9-8522-6042d28511ae", "name": "Extract zip file", "type": "n8n-nodes-base.compression", "position": [900, -80], "parameters": {}, "typeVersion": 1.1}, {"id": "6a12d9ac-f1b7-4267-8b34-58cdb9d347bb", "name": "Save chinook.db locally", "type": "n8n-nodes-base.readWriteFile", "position": [1100, -80], "parameters": {"options": {}, "fileName": "./chinook.db", "operation": "write", "dataPropertyName": "file_0"}, "typeVersion": 1}, {"id": "701d1325-4186-4185-886a-3738163db603", "name": "Load local chinook.db", "type": "n8n-nodes-base.readWriteFile", "position": [620, 360], "parameters": {"options": {}, "fileSelector": "./chinook.db"}, "typeVersion": 1}, {"id": "d7b3813d-8180-4ff1-87a4-bd54a03043af", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [440, -280.9454545454546], "parameters": {"width": 834.3272727272731, "height": 372.9454545454546, "content": "## Run this part only once\nThis section:\n* downloads the example zip file from https://www.sqlitetutorial.net/sqlite-sample-database/\n* extracts the archive (it contains only a single file)\n* saves the extracted `chinook.db` SQLite database locally\n\nNow you can use chat to \"talk\" to your data!"}, "typeVersion": 1}, {"id": "6bd25563-2c59-44c2-acf9-407bd28a15cf", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [400, 240], "parameters": {"width": 558.5454545454544, "height": 297.89090909090913, "content": "## On every chat message:\n* the local SQLite database is loaded\n* JSON from Chat Trigger is combined with SQLite binary data"}, "typeVersion": 1}, {"id": "2be63956-236e-46f7-b8e4-0f55e2e25a5c", "name": "Combine chat input with the binary", "type": "n8n-nodes-base.set", "position": [820, 360], "parameters": {"mode": "raw", "options": {"includeBinary": true}, "jsonOutput": "={{ $('Chat Trigger').item.json }}\n"}, "typeVersion": 3.3}, {"id": "7f4c9adb-eab4-40d7-ad2e-44f2c0e3e30a", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [980, 120], "parameters": {"width": 471.99692219161466, "height": 511.16641410437836, "content": "### LangChain SQL Agent can make several queries before producing the final answer.\nTry these examples:\n1. \"Please describe the database\". This input usually requires just 1 query + an extra observation to produce a final answer.\n2. \"What are the revenues by genre?\". This input will launch a series of Agent actions, because it needs to make several queries.\n\nThe final answer is stored in the memory and will be recalled on the next input from the user."}, "typeVersion": 1}, {"id": "ac819eb5-13b2-4280-b9d6-06ec1209700e", "name": "AI Agent", "type": "@n8n/n8n-nodes-langchain.agent", "position": [1020, 360], "parameters": {"agent": "sqlAgent", "options": {}, "dataSource": "sqlite"}, "typeVersion": 1.6}, {"id": "5ecaa3eb-e93e-4e41-bbc0-98a8c2b2d463", "name": "Chat Trigger", "type": "@n8n/n8n-nodes-langchain.chatTrigger", "position": [420, 360], "webhookId": "fb565f08-a459-4ff9-8249-1ede58599660", "parameters": {}, "typeVersion": 1}], "active": false, "pinData": {}, "settings": {"executionOrder": "v1"}, "versionId": "fbc06ddd-dbd8-49ee-bbee-2f495d5651a2", "connections": {"Chat Trigger": {"main": [[{"node": "Load local chinook.db", "type": "main", "index": 0}]]}, "Extract zip file": {"main": [[{"node": "Save chinook.db locally", "type": "main", "index": 0}]]}, "OpenAI Chat Model": {"ai_languageModel": [[{"node": "AI Agent", "type": "ai_languageModel", "index": 0}]]}, "Window Buffer Memory": {"ai_memory": [[{"node": "AI Agent", "type": "ai_memory", "index": 0}]]}, "Load local chinook.db": {"main": [[{"node": "Combine chat input with the binary", "type": "main", "index": 0}]]}, "Get chinook.zip example": {"main": [[{"node": "Extract zip file", "type": "main", "index": 0}]]}, "When clicking \"Test workflow\"": {"main": [[{"node": "Get chinook.zip example", "type": "main", "index": 0}]]}, "Combine chat input with the binary": {"main": [[{"node": "AI Agent", "type": "main", "index": 0}]]}}}How to Import This Workflow
- 1Copy the workflow JSON above using the Copy Workflow JSON button.
- 2Open your n8n instance and go to Workflows.
- 3Click Import from JSON and paste the copied workflow.
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