Chat with Postgresql Database
Empower your users to interact with your PostgreSQL database using natural language by automating the process of querying and retrieving information. This workflow connects a chat interface, triggered by a new message, to an AI Agent that leverages OpenAI's powerful language model to understand user requests. The AI Agent intelligently utilizes a suite of PostgreSQL tools, including "Get Table Definition," "Execute SQL Query," and "Get DB Schema and Tables List," to dynamically fetch database schema, generate appropriate SQL queries, and execute them against your database. Chat history is maintained using an AI memory buffer, allowing for contextual conversations. This solution is ideal for support teams needing quick data lookups, business analysts exploring data without writing SQL, or developers building interactive data dashboards. It eliminates the need for manual SQL query writing, speeds up data access, and reduces the training burden for non-technical users, saving significant time and resources while improving data accessibility.
Workflow JSON
{"id": "eOUewYsEzJmQixI6", "meta": {"instanceId": "77c4feba8f41570ef06dc76ece9a6ded0f0d44f7f1477a64c2d71a8508c11faa", "templateCredsSetupCompleted": true}, "name": "Chat with Postgresql Database", "tags": [], "nodes": [{"id": "6501a54f-a68c-452d-b353-d7e871ca3780", "name": "When chat message received", "type": "@n8n/n8n-nodes-langchain.chatTrigger", "position": [-300, -80], "webhookId": "cf1de04f-3e38-426c-89f0-3bdb110a5dcf", "parameters": {"options": {}}, "typeVersion": 1.1}, {"id": "cd32221b-2a36-408d-b57e-8115fcd810c9", "name": "AI Agent", "type": "@n8n/n8n-nodes-langchain.agent", "position": [0, -80], "parameters": {"agent": "openAiFunctionsAgent", "options": {"systemMessage": "You are DB assistant. You need to run queries in DB aligned with user requests.\n\nRun custom SQL query to aggregate data and response to user. Make sure every table has schema prefix to it in sql query which you can get from `Get DB Schema and Tables List` tool.\n\nFetch all data to analyse it for response if needed.\n\n## Tools\n\n- Execute SQL query - Executes any sql query generated by AI\n- Get DB Schema and Tables List - Lists all the tables in database with its schema name\n- Get Table Definition - Gets the table definition from db using table name and schema name"}}, "typeVersion": 1.7}, {"id": "8accbeeb-7eaf-4e9e-aabc-de8ab3a0459b", "name": "OpenAI Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [-60, 160], "parameters": {"model": {"__rl": true, "mode": "list", "value": "gpt-4o-mini"}, "options": {}}, "credentials": {"openAiApi": {"id": "", "name": "[Your openAiApi]"}}, "typeVersion": 1.2}, {"id": "11f2013f-a080-4c9e-8773-c90492e2c628", "name": "Get Table Definition", "type": "n8n-nodes-base.postgresTool", "position": [780, 140], "parameters": {"query": "select\n c.column_name,\n c.data_type,\n c.is_nullable,\n c.column_default,\n tc.constraint_type,\n ccu.table_name AS referenced_table,\n ccu.column_name AS referenced_column\nfrom\n information_schema.columns c\nLEFT join\n information_schema.key_column_usage kcu\n ON c.table_name = kcu.table_name\n AND c.column_name = kcu.column_name\nLEFT join\n information_schema.table_constraints tc\n ON kcu.constraint_name = tc.constraint_name\n AND tc.constraint_type = 'FOREIGN KEY'\nLEFT join\n information_schema.constraint_column_usage ccu\n ON tc.constraint_name = ccu.constraint_name\nwhere\n c.table_name = '{{ $fromAI(\"table_name\") }}'\n AND c.table_schema = '{{ $fromAI(\"schema_name\") }}'\norder by\n c.ordinal_position", "options": {}, "operation": "executeQuery", "descriptionType": "manual", "toolDescription": "Get table definition to find all columns and types"}, "credentials": {"postgres": {"id": "", "name": "[Your postgres]"}}, "typeVersion": 2.5}, {"id": "760bc9bc-0057-4088-b3f0-3ee37b3519df", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [-300, -240], "parameters": {"color": 5, "width": 560, "height": 120, "content": "### \ud83d\udc68\u200d\ud83c\udfa4 Setup\n1. Add your **postgresql** and **OpenAI** credentials.\n2. Click **Chat** button and start asking questions to your database.\n3. Activate the workflow and you can make the chat publicly available."}, "typeVersion": 1}, {"id": "0df33341-c859-4a54-b6d9-a99670e8d76d", "name": "Chat History", "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow", "position": [120, 160], "parameters": {}, "typeVersion": 1.3}, {"id": "4938b22e-f187-4ca0-b9f1-60835e823799", "name": "Sticky Note3", "type": "n8n-nodes-base.stickyNote", "position": [360, 300], "parameters": {"color": 7, "width": 562, "height": 156, "content": "\ud83d\udee0\ufe0f Tools Used:\n1. Execute SQL Query: Used to execute any query generated by the agent.\n2. Get DB Schema and Tables List: It returns the list of all the tables with its schema name.\n3. Get Table Definition: It returns table details like column names, foreign keys and more of a particular table in a schema."}, "typeVersion": 1}, {"id": "39780c78-4fbc-403e-a220-aa6a4b06df8c", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [-100, 300], "parameters": {"color": 7, "width": 162, "height": 99, "content": "\ud83d\udc46 You can exchange this with any other chat model of your choice."}, "typeVersion": 1}, {"id": "28a5692c-5003-46cb-9a09-b7867734f446", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [100, 300], "parameters": {"color": 7, "width": 162, "height": 159, "content": "\ud83d\udc46 You can change how many number of messages to keep using `Context Window Length` option. It's 5 by default."}, "typeVersion": 1}, {"id": "c18ced71-6330-4ba0-9c52-1bb5852b3039", "name": "Execute SQL Query", "type": "n8n-nodes-base.postgresTool", "position": [380, 140], "parameters": {"query": "{{ $fromAI(\"sql_query\", \"SQL Query\") }}", "options": {}, "operation": "executeQuery", "descriptionType": "manual", "toolDescription": "Get all the data from Postgres, make sure you append the tables with correct schema. Every table is associated with some schema in the database."}, "credentials": {"postgres": {"id": "", "name": "[Your postgres]"}}, "typeVersion": 2.5}, {"id": "557623c6-e499-48a6-a066-744f64f8b6f3", "name": "Get DB Schema and Tables List", "type": "n8n-nodes-base.postgresTool", "position": [580, 140], "parameters": {"query": "SELECT \n table_schema,\n table_name\nFROM information_schema.tables\nWHERE table_type = 'BASE TABLE'\n AND table_schema NOT IN ('pg_catalog', 'information_schema')\nORDER BY table_schema, table_name;", "options": {}, "operation": "executeQuery", "descriptionType": "manual", "toolDescription": "Get list of all tables with their schema in the database"}, "credentials": {"postgres": {"id": "", "name": "[Your postgres]"}}, "typeVersion": 2.5}], "active": false, "pinData": {}, "settings": {"executionOrder": "v1"}, "versionId": "10c7c74e-b383-4ac7-8cb2-c9a15a2818fe", "connections": {"Chat History": {"ai_memory": [[{"node": "AI Agent", "type": "ai_memory", "index": 0}]]}, "Execute SQL Query": {"ai_tool": [[{"node": "AI Agent", "type": "ai_tool", "index": 0}]]}, "OpenAI Chat Model": {"ai_languageModel": [[{"node": "AI Agent", "type": "ai_languageModel", "index": 0}]]}, "Get Table Definition": {"ai_tool": [[{"node": "AI Agent", "type": "ai_tool", "index": 0}]]}, "When chat message received": {"main": [[{"node": "AI Agent", "type": "main", "index": 0}]]}, "Get DB Schema and Tables List": {"ai_tool": [[{"node": "AI Agent", "type": "ai_tool", "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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