AI Travel Planner with Couchbase Vector Search via Webhook

## AI Travel Agent Powered by Couchbase.

### You will need to:
1. Setup your Google API Credentials for the Gemini LLM
2. Setup your OpenAI Credentials for the OpenAI embedding nodes.
3. Create a Couchbase cluster (using [Couchbase Capella]({{ $env.WEBHOOK_URL }} in the cloud, or Couchbase Server)
4. Add [Database credentials]({{ $env.WEBHOOK_URL }} with appropriate permissions for the operations you want to perform
5. Configure [Allowed IP addresses]({{ $env.WEBHOOK_URL }} for your n8n instance. Use `0.0.0.0/0` for easier testing.
6. Create a bucket, scope, and collection. We recommend the following:
   - Bucket: `travel-agent`
   - Scope: `vectors`
   - Collection: `points-of-interest`
7. Navigate to the Data Tools, click the Search tab, and click Import Search Index. Upload the following JSON file found [here]({{ $env.WEBHOOK_URL }}


Once all of that is configured you will need to send the loading webhook with some data points (see example).

This should create vectorized data in  `points-of-interest` collection.

Once you have data points there try to ask the Agent questions about the data points and test the response. Eg. "Where should I go for a romantic getaway?"