TextEmbedder class

Performs embedding extraction on text.

Signature:

  export 
  
 declare 
  
 class 
  
 TextEmbedder 
  
 extends 
  
 TaskRunner 
  
 

Extends: TaskRunner

Methods

Method Modifiers Description
static Utility function to compute cosine similarity[1] between two Embedding objects.[1]: https://en.wikipedia.org/wiki/Cosine_similarity
static Initializes the Wasm runtime and creates a new text embedder based on the provided model asset buffer.
static Initializes the Wasm runtime and creates a new text embedder based on the path to the model asset.
static Initializes the Wasm runtime and creates a new text embedder from the provided options.
Performs embeding extraction on the provided text and waits synchronously for the response.
Sets new options for the text embedder.Calling setOptions() with a subset of options only affects those options. You can reset an option back to its default value by explicitly setting it to undefined .

TextEmbedder.cosineSimilarity()

Utility function to compute cosine similarity[1] between two Embedding objects.

[1]: https://en.wikipedia.org/wiki/Cosine_similarity

Signature:

  static 
  
 cosineSimilarity 
 ( 
 u 
 : 
  
 Embedding 
 , 
  
 v 
 : 
  
 Embedding 
 ) 
 : 
  
 number 
 ; 
 

Parameters

Parameter Type Description
u
Embedding
v
Embedding

Returns:

number

Exceptions

if the embeddings are of different types(float vs. quantized), have different sizes, or have an L2-norm of 0.

TextEmbedder.createFromModelBuffer()

Initializes the Wasm runtime and creates a new text embedder based on the provided model asset buffer.

Signature:

  static 
  
 createFromModelBuffer 
 ( 
 wasmFileset 
 : 
  
 WasmFileset 
 , 
  
 modelAssetBuffer 
 : 
  
 Uint8Array 
 ) 
 : 
  
 Promise<TextEmbedder> 
 ; 
 

Parameters

Parameter Type Description
wasmFileset
WasmFileset A configuration object that provides the location of the Wasm binary and its loader.
modelAssetBuffer
Uint8Array A binary representation of the TFLite model.

Returns:

Promise< TextEmbedder >

TextEmbedder.createFromModelPath()

Initializes the Wasm runtime and creates a new text embedder based on the path to the model asset.

Signature:

  static 
  
 createFromModelPath 
 ( 
 wasmFileset 
 : 
  
 WasmFileset 
 , 
  
 modelAssetPath 
 : 
  
 string 
 ) 
 : 
  
 Promise<TextEmbedder> 
 ; 
 

Parameters

Parameter Type Description
wasmFileset
WasmFileset A configuration object that provides the location of the Wasm binary and its loader.
modelAssetPath
string The path to the TFLite model.

Returns:

Promise< TextEmbedder >

TextEmbedder.createFromOptions()

Initializes the Wasm runtime and creates a new text embedder from the provided options.

Signature:

  static 
  
 createFromOptions 
 ( 
 wasmFileset 
 : 
  
 WasmFileset 
 , 
  
 textEmbedderOptions 
 : 
  
 TextEmbedderOptions 
 ) 
 : 
  
 Promise<TextEmbedder> 
 ; 
 

Parameters

Parameter Type Description
wasmFileset
WasmFileset A configuration object that provides the location of the Wasm binary and its loader.
textEmbedderOptions
TextEmbedderOptions The options for the text embedder. Note that either a path to the TFLite model or the model itself needs to be provided (via baseOptions ).

Returns:

Promise< TextEmbedder >

TextEmbedder.embed()

Performs embeding extraction on the provided text and waits synchronously for the response.

Signature:

  embed 
 ( 
 text 
 : 
  
 string 
 ) 
 : 
  
 TextEmbedderResult 
 ; 
 

Parameters

Parameter Type Description
text
string The text to process. The embedding resuls of the text

Returns:

TextEmbedderResult

TextEmbedder.setOptions()

Sets new options for the text embedder.

Calling setOptions() with a subset of options only affects those options. You can reset an option back to its default value by explicitly setting it to undefined .

Signature:

  setOptions 
 ( 
 options 
 : 
  
 TextEmbedderOptions 
 ) 
 : 
  
 Promise<void> 
 ; 
 

Parameters

Parameter Type Description
options
TextEmbedderOptions The options for the text embedder.

Returns:

Promise<void>

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