Overview

This node provides embeddings generation using the BAAI/bge-m3 model via the DeepInfra API. It is useful for transforming text data into vector embeddings for applications like semantic search, recommendation systems, or natural language processing tasks. Users can input text or arrays of text to receive corresponding embeddings.

Use Case Examples

1. Generating vector embeddings for documents to enable semantic search.
2. Creating embeddings for queries to find similar content in a dataset.

Properties

Output

JSON

• response
  • embedDocuments - Function to generate embeddings for document inputs, returning an array of embeddings.
  • embedQuery - Function to generate embeddings for query inputs, returning an embedding or array of embeddings.

Dependencies

• Requires access to the DeepInfra API endpoint at https://api.deepinfra.com/v1/openai/embeddings

Troubleshooting

• Ensure the API key is correctly provided and valid to avoid authentication errors.
• Check network connectivity to the DeepInfra API endpoint to prevent request failures.
• Verify the input data format is either a string or an array of strings to avoid processing errors.

Links

• DeepInfra BAAI/bge-m3 Model Documentation - Official documentation for the embedding model used by this node.