Travel Planning Agent with Couchbase Vector Search, Gemini 2.0 Flash and OpenAI
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An AI agent for travel planning that leverages Couchbase vector search, Gemini 2.0 Flash, and OpenAI embeddings.
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About This Workflow
Overview
This workflow sets up an AI-powered travel planning agent. It uses Couchbase for vector search to retrieve relevant points of interest, Gemini 2.0 Flash for chat interactions, and OpenAI for generating embeddings. The agent can answer travel-related questions by querying a vector database.
Key Features
- AI-driven travel planning assistant
- Vector search capabilities with Couchbase
- Integration with Google Gemini 2.0 Flash
- OpenAI embeddings for enhanced search
- Support for both retrieving and inserting vectorized data
How To Use
- Configure Credentials: Set up Google API credentials for Gemini and OpenAI API credentials.
- Set up Couchbase: Create a Couchbase cluster (e.g., Couchbase Capella or Couchbase Server) and add database credentials.
- Configure Network: Allow appropriate IP addresses for your n8n instance (e.g.,
0.0.0.0/0for testing). - Create Couchbase Schema: Create a bucket (e.g.,
travel-agent), scope (e.g.,vectors), and collection (e.g.,points-of-interest). - Import Search Index: Navigate to Couchbase Data Tools, import the provided search index JSON.
- Ingest Data: Use the provided CURL command or shell script to send data points to the webhook URL.
- Test the Agent: Send chat messages to the workflow to ask questions about travel points of interest.
Apps Used
Workflow JSON
{
"id": "9bbb93d5-2251-40fc-9bdf-decb8e238d6d",
"name": "Travel Planning Agent with Couchbase Vector Search, Gemini 2.0 Flash and OpenAI",
"nodes": 0,
"category": "AI & Machine Learning",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 9bbb93d5-2251...
About the Author
AI_Workflow_Bot
LLM Specialist
Building complex chains with OpenAI, Claude, and LangChain.
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