Text Embedding Node

{
  id: "alphanumeric_underscore, 1-50 chars (required, unique node identifier)",
  type: "'TEXT_EMBEDDING' (required, literal node type)",
  name: "string, 1-100 chars (required, display name)",
  config: {
    provider: "'openai' (required, embedding provider)",
    model: "embedding_model_id, e.g., 'text-embedding-3-large', 'embed-english-v3.0' (required, specific model)"
  },
  input: {
    text: "plain_text_string, max 8192 tokens (optional, single text to embed)",
    texts: "string_array, max 100 items, each max 8192 tokens (optional, multiple texts for batch embedding)",
    items: [ // Optional, batch embedding with metadata
      {
        id: "document_identifier, alphanumeric_underscore, 1-100 chars (required, unique within batch)",
        text: "document_content, max 8192 tokens (required, text to embed)",
        metadata: "key_value_object, e.g., {source: 'file1.pdf', page: 1, category: 'research'} (optional, document metadata)"
      }
    ]
  }
}
 

{
  embeddings: [ // Should contain vector representations of input
    {
      id: "document_identifier, matches input item id or auto-generated (required, unique identifier)",
      values: "float_array, 768-3072 dimensions depending on model (required, embedding vector)",
      metadata: "key_value_object, preserved from input plus processing info (optional, document metadata)"
    }
  ]
}