HuggingFaceEmbeddingProvider.ts•4.01 kB
// HuggingFace Embedding Provider
// Users should implement this provider to use HuggingFace embeddings (API or local)
import { BaseEmbeddingProvider } from '../BaseEmbeddingProvider.js';
import { PROVIDER_CONFIG } from '../../../core/config.js';
/**
* HuggingFace Embedding Provider Implementation
* Supports both API and local inference via Transformers.js
*
* To implement:
* For API: Set HF_TOKEN in environment
* For Local: npm install @xenova/transformers
* Then implement generateEmbeddingsInternal method
*/
export class HuggingFaceEmbeddingProvider extends BaseEmbeddingProvider {
private pipeline: any = null;
protected getProviderType(): string {
return 'huggingface';
}
protected getDefaultModel(): string {
return PROVIDER_CONFIG.HUGGINGFACE_MODEL || 'sentence-transformers/all-MiniLM-L6-v2';
}
protected getDefaultMaxBatchSize(): number {
return PROVIDER_CONFIG.HUGGINGFACE_USE_LOCAL ? 10 : 100;
}
protected isLocalProvider(): boolean {
return PROVIDER_CONFIG.HUGGINGFACE_USE_LOCAL || false;
}
async isAvailable(): Promise<boolean> {
if (PROVIDER_CONFIG.HUGGINGFACE_USE_LOCAL) {
// Check if Transformers.js is available
try {
// Check if Transformers.js module can be resolved
const transformersModule = await import('@xenova/transformers' as string);
return !!transformersModule;
} catch (error) {
console.warn('Transformers.js not installed. Run: npm install @xenova/transformers');
return false;
}
} else {
// Check if HuggingFace API key is configured
if (!PROVIDER_CONFIG.HUGGINGFACE_API_KEY) {
console.warn('HuggingFace API key not configured');
return false;
}
return true;
}
}
async warmUp(): Promise<void> {
if (PROVIDER_CONFIG.HUGGINGFACE_USE_LOCAL) {
console.log(`🔥 Loading HuggingFace model ${this.getModel()} locally...`);
// TODO: Initialize the pipeline
/*
const { pipeline } = await import('@xenova/transformers');
this.pipeline = await pipeline('feature-extraction', this.getModel());
console.log('✅ Model loaded and ready');
*/
}
}
protected async generateEmbeddingsInternal(texts: string[]): Promise<number[][]> {
if (PROVIDER_CONFIG.HUGGINGFACE_USE_LOCAL) {
// TODO: Implement local inference with Transformers.js
/*
if (!this.pipeline) {
await this.warmUp();
}
const embeddings: number[][] = [];
for (const text of texts) {
const output = await this.pipeline(text, {
pooling: 'mean',
normalize: true
});
embeddings.push(Array.from(output.data));
}
return embeddings;
*/
} else {
// TODO: Implement API-based inference
/*
const response = await fetch(
`https://api-inference.huggingface.co/models/${this.getModel()}`,
{
method: 'POST',
headers: {
'Authorization': `Bearer ${PROVIDER_CONFIG.HUGGINGFACE_API_KEY}`,
'Content-Type': 'application/json'
},
body: JSON.stringify({
inputs: texts,
options: {
wait_for_model: true
}
})
}
);
if (!response.ok) {
const error = await response.text();
throw new Error(`HuggingFace error: ${response.status} - ${error}`);
}
const data = await response.json();
return data;
*/
}
throw new Error('HuggingFace provider not implemented. Please implement generateEmbeddingsInternal method.');
}
estimateCost(tokenCount: number): number {
if (PROVIDER_CONFIG.HUGGINGFACE_USE_LOCAL) {
return 0; // Local inference is free
}
// HuggingFace Inference API pricing varies by model
return tokenCount * 0.00006 / 1000; // Approximate
}
}
console.log('✅ HuggingFace embedding provider template loaded');