This workflow creates an intelligent system that enables users to interact with a BigQuery database via a chat interface, generating SQL queries on the fly. When a user asks a question within the embedded chat widget, the workflow fetches the database schema, consolidates table and column information, and employs OpenAI’s GPT-4 model to craft a valid SQL query tailored to the user’s request. The workflow then runs the generated query against BigQuery and returns the results or prompts the user to ask another question if the query fails. This setup is ideal for creating an interactive data assistant, empowering non-technical users to explore large datasets effortlessly through natural language queries.
AI-Powered BigQuery SQL Generator with n8n and Chat Interface
| Node Count | 11 – 20 Nodes |
|---|---|
| Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.outputParserStructured, aggregate, code, googleBigQuery, merge, stickyNote |
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