Text

Text Embedding

Extract semantic embeddings from documents, transcripts and text content

827K runs

Note: This playground provides simulated output to showcase functionality. No input data is processed or stored on our servers. Use this demo to explore the feature extractor's capabilities before integrating it into your application.

Input

Text Input string

Enter the text you want to process

# model string

The embedding model to use. Default: text-embedding-3-large

# truncate boolean

Whether to truncate long texts. Default: true

# normalize boolean

Whether to normalize the embeddings. Default: true

Output

{
  "embedding": [
    0.024,
    -0.015,
    0.128,
    0.035,
    "..."
  ],
  "dimensions": 1536,
  "model": "text-embedding-3-large",
  "text_chunk": "Sample text content for embedding generation",
  "token_count": 128,
  "truncated": false,
  "normalized": true
}