d803bfe2b1
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
113 lines
2.5 KiB
TypeScript
113 lines
2.5 KiB
TypeScript
/* tslint:disable */
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/* eslint-disable */
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/**
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* Strategy for pooling token embeddings into a single sentence embedding
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*/
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export enum PoolingStrategy {
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/**
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* Average all token embeddings (most common)
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*/
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Mean = 0,
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/**
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* Use only the [CLS] token embedding
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*/
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Cls = 1,
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/**
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* Take the maximum value across all tokens for each dimension
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*/
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Max = 2,
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/**
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* Mean pooling normalized by sqrt of sequence length
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*/
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MeanSqrtLen = 3,
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/**
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* Use the last token embedding (for decoder models)
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*/
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LastToken = 4,
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}
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export class WasmEmbedder {
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free(): void;
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[Symbol.dispose](): void;
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/**
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* Get maximum sequence length
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*/
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maxLength(): number;
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/**
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* Compute similarity between two texts
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*/
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similarity(text1: string, text2: string): number;
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/**
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* Generate embeddings for multiple texts
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*/
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embedBatch(texts: string[]): Float32Array;
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/**
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* Create embedder with custom configuration
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*/
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static withConfig(model_bytes: Uint8Array, tokenizer_json: string, config: WasmEmbedderConfig): WasmEmbedder;
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/**
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* Create a new embedder from model and tokenizer bytes
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*
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* # Arguments
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* * `model_bytes` - ONNX model file bytes
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* * `tokenizer_json` - Tokenizer JSON configuration
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*/
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constructor(model_bytes: Uint8Array, tokenizer_json: string);
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/**
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* Get the embedding dimension
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*/
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dimension(): number;
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/**
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* Generate embedding for a single text
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*/
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embedOne(text: string): Float32Array;
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}
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export class WasmEmbedderConfig {
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free(): void;
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[Symbol.dispose](): void;
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/**
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* Set pooling strategy (0=Mean, 1=Cls, 2=Max, 3=MeanSqrtLen, 4=LastToken)
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*/
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setPooling(pooling: number): WasmEmbedderConfig;
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/**
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* Set whether to normalize embeddings
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*/
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setNormalize(normalize: boolean): WasmEmbedderConfig;
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/**
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* Set maximum sequence length
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*/
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setMaxLength(max_length: number): WasmEmbedderConfig;
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/**
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* Create a new configuration
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*/
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constructor();
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}
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/**
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* Compute cosine similarity between two embedding vectors (JS-friendly)
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*/
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export function cosineSimilarity(a: Float32Array, b: Float32Array): number;
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/**
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* Initialize panic hook for better error messages in WASM
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*/
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export function init(): void;
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/**
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* L2 normalize an embedding vector (JS-friendly)
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*/
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export function normalizeL2(embedding: Float32Array): Float32Array;
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/**
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* Check if SIMD is available (for performance info)
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* Returns true if compiled with WASM SIMD128 support
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*/
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export function simd_available(): boolean;
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/**
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* Get the library version
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*/
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export function version(): string;
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