AI Agent for Context-Aware Conversations with Database Data
Workflow Description
An AI agent receives queries via webhook, retrieves relevant data from PostgreSQL, processes them with OpenAI, and delivers intelligent responses. It maintains conversation memory for coherent multi-turn interactions and logs all exchanges.
How it works
- 1.Receive incoming query via webhook and preserve context
- 2.Query PostgreSQL to fetch relevant structured data
- 3.Process query with OpenAI using retrieved data and respond
- 4.Update conversation memory and maintain interaction history
Use cases
- Intelligent customer assistant that answers based on your company data
- Natural language search engine for your database with AI understanding
- Automated support system that remembers conversation context
Requirements
- OpenAI API key and an active PostgreSQL database with queryable data
- Webhook endpoint accessible for incoming requests from your applications
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
Details
How to Use
- 1.Click "Download Template"
- 2.Open your n8n dashboard
- 3.Go to Workflows > Import from File
- 4.Select downloaded file and configure credentials
Nodes Used (30)
Postgres Chat Memory
Memory Postgres Chat
OpenAI Chat Model
OpenAI
Set fields
Set
Sticky Note
Sticky Note
Webhook - ChatInput
Webhook
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Respond to Webhook
Webhook
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Sticky Note
Call Search Console Tool
Tool Workflow
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Sticky Note
Tool calling
Execute Workflow Trigger
Switch
Switch
Set fields - Consruct API CALL
Set
Sticky Note8
Sticky Note
Set fields - Create searchConsoleDataArray
Set
Set fields - Create searchConsoleDataArray 2
Set
Search Console - Get Custom Insights
HTTP Request
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Sticky Note
## Search Console - Get List of Properties
HTTP Request
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Array aggregation - response to AI Agent
Aggregate
Array aggregation - response to AI Agent1
Aggregate
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AI Agent
Agent