Overview

This node operation inserts a new vector into a specified vector collection within HelixDB, a time-series database. It is useful for applications that require storing vector data, such as embeddings for machine learning, similarity search, or other vector-based data processing. For example, a user can insert a vector representing an image or text embedding along with optional metadata for later retrieval or analysis.

Use Case Examples

1. Inserting an embedding vector into a collection named 'embeddings' with associated metadata describing the vector's context.
2. Storing feature vectors extracted from sensor data for time-series analysis.

Properties

Output

JSON

• json - The response from HelixDB after inserting the vector, typically including details about the inserted vector or operation status.

Dependencies

• Requires HelixDB server running with deployed HelixQL queries and an API key credential for authentication.

Troubleshooting

• Ensure the HelixDB server is running and accessible at the configured port.
• Verify that the specified vector collection exists in HelixDB before inserting vectors.
• Check that the vector data is a valid JSON array of numbers; invalid formats will cause errors.
• If the operation fails, the node returns an error message which can be used to diagnose issues such as authentication failure or query errors.

Links

• HelixDB Documentation - Official documentation for HelixDB including setup, query language, and API usage.