Files
wifi-densepose/vendor/ruvector/examples/edge-full/pkg/rvlite/rvlite.d.ts

557 lines
18 KiB
TypeScript

/* tslint:disable */
/* eslint-disable */
export class BaseLoRA {
free(): void;
[Symbol.dispose](): void;
distillFrom(micro: MicroLoRA, blend_factor: number): void;
applyGradients(): void;
constructor(config: LoraConfig);
stats(): any;
forward(input: Float32Array): Float32Array;
}
export class Embedder {
free(): void;
[Symbol.dispose](): void;
/**
* Get embedding dimensions
*/
dimensions(): number;
/**
* Compute similarity between two texts
*/
similarity(text_a: string, text_b: string): number;
/**
* Batch embed multiple texts
* Takes JsValue array of strings, returns JsValue array of Float32Arrays
*/
embed_batch(texts: any): any;
/**
* Create embedder with custom config
*/
static with_config(config: EmbeddingConfig): Embedder;
/**
* Compute cosine similarity between two embeddings (JS arrays)
*/
static cosine_similarity(a: Float32Array, b: Float32Array): number;
/**
* Create a new embedder with default config
*/
constructor();
/**
* Generate embeddings for a single text
* Uses hash-based projection for lightweight WASM operation
* Returns Float32Array for direct JS consumption
*/
embed(text: string): Float32Array;
}
export class EmbeddingConfig {
free(): void;
[Symbol.dispose](): void;
/**
* Create config for larger models
*/
static with_dimensions(dimensions: number): EmbeddingConfig;
constructor();
/**
* Create config for all-MiniLM-L6-v2 (default)
*/
static minilm(): EmbeddingConfig;
/**
* Model dimensions (384 for all-MiniLM-L6-v2)
*/
dimensions: number;
/**
* Normalize output vectors
*/
normalize: boolean;
/**
* Max sequence length
*/
max_length: number;
}
export class LoraConfig {
free(): void;
[Symbol.dispose](): void;
/**
* Create custom LoRA configuration
*/
constructor(hidden_dim: number, rank: number, alpha: number, learning_rate: number);
/**
* Create BaseLoRA configuration (background training)
*/
static base(hidden_dim: number): LoraConfig;
/**
* Create MicroLoRA configuration (per-request, <100μs)
*/
static micro(hidden_dim: number): LoraConfig;
/**
* Export as JSON
*/
toJSON(): any;
/**
* Validate configuration
*/
validate(): void;
/**
* LoRA rank (1-2 for micro, 4-16 for base)
*/
readonly rank: number;
/**
* Alpha scaling factor
*/
readonly alpha: number;
/**
* Learning rate for adaptation
*/
readonly learning_rate: number;
/**
* Hidden dimension
*/
readonly hidden_dim: number;
}
export class MicroLoRA {
free(): void;
[Symbol.dispose](): void;
exportWeights(): any;
applyGradients(): void;
accumulateGradient(input: Float32Array, feedback: number): void;
constructor(config: LoraConfig);
reset(): void;
stats(): any;
forward(input: Float32Array): Float32Array;
}
export class RvLite {
free(): void;
[Symbol.dispose](): void;
/**
* Get configuration
*/
get_config(): any;
/**
* Get version string
*/
get_version(): string;
/**
* Get enabled features
*/
get_features(): any;
/**
* Insert a vector with a specific ID
*/
insert_with_id(id: string, vector: Float32Array, metadata?: any | null): void;
/**
* Search with metadata filter
*/
search_with_filter(query_vector: Float32Array, k: number, filter: any): any;
/**
* Get a vector by ID
*/
get(id: string): any;
/**
* Get the number of vectors in the database
*/
len(): number;
/**
* Create a new RvLite database
*/
constructor(config: RvLiteConfig);
/**
* Execute SQL query (not yet implemented)
*/
sql(_query: string): Promise<any>;
/**
* Execute Cypher query (not yet implemented)
*/
cypher(_query: string): Promise<any>;
/**
* Delete a vector by ID
*/
delete(id: string): boolean;
/**
* Insert a vector with optional metadata
* Returns the vector ID
*/
insert(vector: Float32Array, metadata?: any | null): string;
/**
* Search for similar vectors
* Returns a JavaScript array of search results
*/
search(query_vector: Float32Array, k: number): any;
/**
* Execute SPARQL query (not yet implemented)
*/
sparql(_query: string): Promise<any>;
/**
* Create with default configuration (384 dimensions, cosine similarity)
*/
static default(): RvLite;
/**
* Check if database is empty
*/
is_empty(): boolean;
/**
* Check if database is ready
*/
is_ready(): boolean;
}
export class RvLiteConfig {
free(): void;
[Symbol.dispose](): void;
/**
* Set distance metric (euclidean, cosine, dotproduct, manhattan)
*/
with_distance_metric(metric: string): RvLiteConfig;
constructor(dimensions: number);
}
export class TrmConfig {
free(): void;
[Symbol.dispose](): void;
/**
* Enable/disable attention variant
*/
withAttention(use_attention: boolean): TrmConfig;
/**
* Set default K iterations
*/
withDefaultK(k: number): TrmConfig;
/**
* Enable/disable early stopping
*/
withEarlyStopping(enabled: boolean): TrmConfig;
/**
* Set latent iterations per K step
*/
withLatentIterations(n: number): TrmConfig;
/**
* Set confidence threshold
*/
withConfidenceThreshold(threshold: number): TrmConfig;
/**
* Create a new TRM configuration
*/
constructor(embedding_dim: number, hidden_dim: number, max_k: number);
/**
* Create configuration optimized for speed
*/
static fast(embedding_dim: number): TrmConfig;
/**
* Create configuration optimized for quality
*/
static quality(embedding_dim: number): TrmConfig;
/**
* Export configuration as JSON
*/
toJSON(): any;
/**
* Create balanced configuration (recommended)
*/
static balanced(embedding_dim: number): TrmConfig;
/**
* Validate configuration
*/
validate(): void;
/**
* Import configuration from JSON
*/
static fromJSON(value: any): TrmConfig;
/**
* Embedding dimension (input/output size)
*/
readonly embedding_dim: number;
/**
* Hidden dimension for latent state
*/
readonly hidden_dim: number;
/**
* Maximum K iterations
*/
readonly max_k: number;
/**
* Default K iterations
*/
readonly default_k: number;
/**
* Latent updates per K iteration
*/
readonly latent_iterations: number;
/**
* Use attention variant (more expressive, slower)
*/
readonly use_attention: boolean;
/**
* Number of attention heads
*/
readonly num_heads: number;
/**
* Confidence threshold for early stopping
*/
readonly confidence_threshold: number;
/**
* Enable early stopping
*/
readonly early_stopping: boolean;
/**
* Minimum iterations before early stopping
*/
readonly min_iterations: number;
/**
* Convergence threshold for plateau detection
*/
readonly convergence_threshold: number;
/**
* Residual scale for answer refinement
*/
readonly residual_scale: number;
}
export class TrmEngine {
free(): void;
[Symbol.dispose](): void;
getConfig(): any;
reasonWithK(question: Float32Array, answer: Float32Array, k: number): TrmResult;
constructor(config: TrmConfig);
reset(): void;
stats(): any;
reason(question: Float32Array, answer: Float32Array): TrmResult;
}
export class TrmResult {
private constructor();
free(): void;
[Symbol.dispose](): void;
getAnswer(): Float32Array;
toJSON(): any;
readonly confidence: number;
readonly iterations_used: number;
readonly early_stopped: boolean;
readonly latency_ms: number;
}
/**
* Quick benchmark for embeddings
*/
export function benchmark_embeddings(iterations: number): any;
/**
* Quick benchmark function
*/
export function benchmark_trm(iterations: number, hidden_dim: number): any;
/**
* Compute cosine similarity
*/
export function cosineSimilarity(a: Float32Array, b: Float32Array): number;
/**
* Dot product
*/
export function dotProduct(a: Float32Array, b: Float32Array): number;
/**
* Get feature info
*/
export function features(): any;
export function init(): void;
/**
* Compute L2 distance
*/
export function l2Distance(a: Float32Array, b: Float32Array): number;
/**
* Linear interpolation
*/
export function lerp(a: Float32Array, b: Float32Array, t: number): Float32Array;
/**
* Mean pooling for token embeddings
*/
export function meanPooling(embeddings: any, attention_mask?: Float32Array | null): Float32Array;
/**
* Normalize a vector to unit length
*/
export function normalizeVector(vec: Float32Array): Float32Array;
/**
* Create a random vector
*/
export function randomVector(dim: number, seed?: number | null): Float32Array;
/**
* Softmax function
*/
export function softmax(vec: Float32Array): Float32Array;
/**
* Get version string
*/
export function version(): string;
/**
* Create a zero vector
*/
export function zeros(dim: number): Float32Array;
export type InitInput = RequestInfo | URL | Response | BufferSource | WebAssembly.Module;
export interface InitOutput {
readonly memory: WebAssembly.Memory;
readonly __wbg_baselora_free: (a: number, b: number) => void;
readonly __wbg_embedder_free: (a: number, b: number) => void;
readonly __wbg_embeddingconfig_free: (a: number, b: number) => void;
readonly __wbg_get_embeddingconfig_dimensions: (a: number) => number;
readonly __wbg_get_embeddingconfig_max_length: (a: number) => number;
readonly __wbg_get_embeddingconfig_normalize: (a: number) => number;
readonly __wbg_get_loraconfig_alpha: (a: number) => number;
readonly __wbg_get_loraconfig_hidden_dim: (a: number) => number;
readonly __wbg_get_loraconfig_learning_rate: (a: number) => number;
readonly __wbg_get_trmconfig_confidence_threshold: (a: number) => number;
readonly __wbg_get_trmconfig_convergence_threshold: (a: number) => number;
readonly __wbg_get_trmconfig_early_stopping: (a: number) => number;
readonly __wbg_get_trmconfig_latent_iterations: (a: number) => number;
readonly __wbg_get_trmconfig_max_k: (a: number) => number;
readonly __wbg_get_trmconfig_min_iterations: (a: number) => number;
readonly __wbg_get_trmconfig_num_heads: (a: number) => number;
readonly __wbg_get_trmconfig_residual_scale: (a: number) => number;
readonly __wbg_get_trmconfig_use_attention: (a: number) => number;
readonly __wbg_get_trmresult_confidence: (a: number) => number;
readonly __wbg_get_trmresult_early_stopped: (a: number) => number;
readonly __wbg_get_trmresult_iterations_used: (a: number) => number;
readonly __wbg_get_trmresult_latency_ms: (a: number) => number;
readonly __wbg_loraconfig_free: (a: number, b: number) => void;
readonly __wbg_microlora_free: (a: number, b: number) => void;
readonly __wbg_rvlite_free: (a: number, b: number) => void;
readonly __wbg_rvliteconfig_free: (a: number, b: number) => void;
readonly __wbg_set_embeddingconfig_dimensions: (a: number, b: number) => void;
readonly __wbg_set_embeddingconfig_max_length: (a: number, b: number) => void;
readonly __wbg_set_embeddingconfig_normalize: (a: number, b: number) => void;
readonly __wbg_trmconfig_free: (a: number, b: number) => void;
readonly __wbg_trmengine_free: (a: number, b: number) => void;
readonly __wbg_trmresult_free: (a: number, b: number) => void;
readonly baselora_applyGradients: (a: number) => void;
readonly baselora_distillFrom: (a: number, b: number, c: number, d: number) => void;
readonly baselora_forward: (a: number, b: number, c: number, d: number) => void;
readonly baselora_new: (a: number, b: number) => void;
readonly baselora_stats: (a: number) => number;
readonly benchmark_embeddings: (a: number) => number;
readonly benchmark_trm: (a: number, b: number) => number;
readonly cosineSimilarity: (a: number, b: number, c: number, d: number, e: number) => void;
readonly dotProduct: (a: number, b: number, c: number, d: number, e: number) => void;
readonly embedder_cosine_similarity: (a: number, b: number) => number;
readonly embedder_dimensions: (a: number) => number;
readonly embedder_embed: (a: number, b: number, c: number) => number;
readonly embedder_embed_batch: (a: number, b: number, c: number) => void;
readonly embedder_new: () => number;
readonly embedder_similarity: (a: number, b: number, c: number, d: number, e: number) => number;
readonly embedder_with_config: (a: number) => number;
readonly embeddingconfig_minilm: () => number;
readonly embeddingconfig_with_dimensions: (a: number) => number;
readonly features: () => number;
readonly init: () => void;
readonly l2Distance: (a: number, b: number, c: number, d: number, e: number) => void;
readonly lerp: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
readonly loraconfig_base: (a: number) => number;
readonly loraconfig_micro: (a: number) => number;
readonly loraconfig_new: (a: number, b: number, c: number, d: number) => number;
readonly loraconfig_toJSON: (a: number) => number;
readonly loraconfig_validate: (a: number, b: number) => void;
readonly meanPooling: (a: number, b: number, c: number, d: number) => void;
readonly microlora_accumulateGradient: (a: number, b: number, c: number, d: number, e: number) => void;
readonly microlora_applyGradients: (a: number) => void;
readonly microlora_exportWeights: (a: number) => number;
readonly microlora_forward: (a: number, b: number, c: number, d: number) => void;
readonly microlora_new: (a: number, b: number) => void;
readonly microlora_reset: (a: number) => void;
readonly microlora_stats: (a: number) => number;
readonly normalizeVector: (a: number, b: number, c: number) => void;
readonly randomVector: (a: number, b: number, c: number) => void;
readonly rvlite_cypher: (a: number, b: number, c: number) => number;
readonly rvlite_default: (a: number) => void;
readonly rvlite_delete: (a: number, b: number, c: number, d: number) => void;
readonly rvlite_get: (a: number, b: number, c: number, d: number) => void;
readonly rvlite_get_config: (a: number, b: number) => void;
readonly rvlite_get_features: (a: number, b: number) => void;
readonly rvlite_get_version: (a: number, b: number) => void;
readonly rvlite_insert: (a: number, b: number, c: number, d: number, e: number) => void;
readonly rvlite_insert_with_id: (a: number, b: number, c: number, d: number, e: number, f: number, g: number) => void;
readonly rvlite_is_empty: (a: number, b: number) => void;
readonly rvlite_is_ready: (a: number) => number;
readonly rvlite_len: (a: number, b: number) => void;
readonly rvlite_new: (a: number, b: number) => void;
readonly rvlite_search: (a: number, b: number, c: number, d: number, e: number) => void;
readonly rvlite_search_with_filter: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
readonly rvlite_sparql: (a: number, b: number, c: number) => number;
readonly rvlite_sql: (a: number, b: number, c: number) => number;
readonly rvliteconfig_new: (a: number) => number;
readonly rvliteconfig_with_distance_metric: (a: number, b: number, c: number) => number;
readonly softmax: (a: number, b: number, c: number) => void;
readonly trmconfig_balanced: (a: number) => number;
readonly trmconfig_fast: (a: number) => number;
readonly trmconfig_fromJSON: (a: number, b: number) => void;
readonly trmconfig_new: (a: number, b: number, c: number) => number;
readonly trmconfig_quality: (a: number) => number;
readonly trmconfig_toJSON: (a: number) => number;
readonly trmconfig_validate: (a: number, b: number) => void;
readonly trmconfig_withAttention: (a: number, b: number) => number;
readonly trmconfig_withConfidenceThreshold: (a: number, b: number) => number;
readonly trmconfig_withDefaultK: (a: number, b: number) => number;
readonly trmconfig_withEarlyStopping: (a: number, b: number) => number;
readonly trmconfig_withLatentIterations: (a: number, b: number) => number;
readonly trmengine_getConfig: (a: number) => number;
readonly trmengine_new: (a: number, b: number) => void;
readonly trmengine_reason: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
readonly trmengine_reasonWithK: (a: number, b: number, c: number, d: number, e: number, f: number, g: number) => void;
readonly trmengine_reset: (a: number) => void;
readonly trmengine_stats: (a: number) => number;
readonly trmresult_getAnswer: (a: number, b: number) => void;
readonly trmresult_toJSON: (a: number) => number;
readonly version: (a: number) => void;
readonly zeros: (a: number, b: number) => void;
readonly embeddingconfig_new: () => number;
readonly __wbg_get_trmconfig_embedding_dim: (a: number) => number;
readonly __wbg_get_loraconfig_rank: (a: number) => number;
readonly __wbg_get_trmconfig_hidden_dim: (a: number) => number;
readonly __wbg_get_trmconfig_default_k: (a: number) => number;
readonly __wasm_bindgen_func_elem_690: (a: number, b: number, c: number) => void;
readonly __wasm_bindgen_func_elem_684: (a: number, b: number) => void;
readonly __wasm_bindgen_func_elem_1412: (a: number, b: number, c: number, d: number) => void;
readonly __wbindgen_export: (a: number, b: number) => number;
readonly __wbindgen_export2: (a: number, b: number, c: number, d: number) => number;
readonly __wbindgen_export3: (a: number) => void;
readonly __wbindgen_export4: (a: number, b: number, c: number) => void;
readonly __wbindgen_add_to_stack_pointer: (a: number) => number;
readonly __wbindgen_start: () => void;
}
export type SyncInitInput = BufferSource | WebAssembly.Module;
/**
* Instantiates the given `module`, which can either be bytes or
* a precompiled `WebAssembly.Module`.
*
* @param {{ module: SyncInitInput }} module - Passing `SyncInitInput` directly is deprecated.
*
* @returns {InitOutput}
*/
export function initSync(module: { module: SyncInitInput } | SyncInitInput): InitOutput;
/**
* If `module_or_path` is {RequestInfo} or {URL}, makes a request and
* for everything else, calls `WebAssembly.instantiate` directly.
*
* @param {{ module_or_path: InitInput | Promise<InitInput> }} module_or_path - Passing `InitInput` directly is deprecated.
*
* @returns {Promise<InitOutput>}
*/
export default function __wbg_init (module_or_path?: { module_or_path: InitInput | Promise<InitInput> } | InitInput | Promise<InitInput>): Promise<InitOutput>;