Build a Smart Agent That Learns from Conversations
Workflow Description
An automation that creates an intelligent agent receiving messages through a chat interface, processes them using Gemini's language model, and maintains conversation context in memory to deliver coherent and contextual responses.
How it works
- 1.Receive messages via chat trigger
- 2.Process the message using Gemini language model
- 3.Manage conversation context and memory buffer
- 4.Generate intelligent response through the agent
- 5.Aggregate data and send response to user
Use cases
- Create a chatbot assistant that understands historical conversation context
- Build a smart agent that learns from previous user interactions
- Develop an automated customer support system maintaining conversation continuity
Requirements
- Google account for Gemini access
- Basic understanding of memory management in automation
- Ability to customize agent logic based on business needs
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 (14)
When chat message received
Chat Trigger
Google Gemini Chat Model
Gemini Model
Google Gemini Chat Model1
Gemini Model
Keyword Data Response Formatter
Agent
Keyword Query Extraction & Cleaning Agent
Agent
Extract Main Keyword & 10 related Keyword data
Code
Aggregate Keyword Data
Aggregate
Ahrefs Keyword API Request
HTTP Request
Sticky Note
Sticky Note
Sticky Note1
Sticky Note
Sticky Note2
Sticky Note
Sticky Note3
Sticky Note
Sticky Note4
Sticky Note
Simple Memory
Memory Buffer Window