Building a Conversational AI Agent with Google Gemini API and n8n
I’m excited to share a powerful workflow I recently built using n8n, a visual workflow automation tool to connect chat messages with the Google Gemini API. The goal? To create an AI-powered conversational agent that responds to incoming chat messages using Google’s latest Gemini Chat Model. Here’s how I did it!
🚀 What I Built
This workflow listens for incoming chat messages and passes them to the Google Gemini Chat Model via an AI Agent node. The Gemini API processes the message and returns a contextual, intelligent response just like a chatbot!
🧠 Workflow Overview
Here's what each part does:
🔔 When chat message received
This trigger node activates the workflow as soon as a new chat message is received from any supported platform or webhook.
🤖 AI Agent (Conversational Agent)
This node handles the conversational logic. It’s configured to pass input to an AI model, maintain memory (optionally), and route tools (optional) as needed.
🌐 Google Gemini Chat Model
This is the brain of the conversation. By connecting the AI Agent node to Google Gemini, we leverage Google’s powerful language model to generate natural and relevant responses.
🔧 Key Features
🔧 Key Features
- Real-time Responses: Your app or chatbot gets a reply instantly whenever a user sends a message.
- Customizable Memory and Tools: You can enhance the AI with memory (context history) and tools (e.g., external APIs or logic).
- Low-code/No-code Integration: With n8n, no complex server setup is needed. You drag, drop, and configure.
🔐 Authentication & API Access
To use Google Gemini’s API, you’ll need:
- A Google Cloud account
- Access to the Gemini API
- An API key or OAuth credentials configured in n8n’s HTTP Request or Gemini integration node
Make sure you enable the Gemini Chat Model and give it the right scopes.
💡 Use Cases
- AI customer service chatbots
- Intelligent help desk assistants
- Virtual agents for websites or internal apps
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