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feat(core): Add comprehensive retry mechanism and batch fallback for Gemini embeddings (#44)
* feat(core): add comprehensive retry mechanism and batch fallback for Gemini embeddings - Add retry configuration to GeminiEmbeddingConfig (maxRetries, baseDelay) - Implement intelligent retry mechanism using es-toolkit with exponential backoff - Add error classification for retryable vs non-retryable errors - Implement batch processing fallback to individual requests - Add getter/setter methods for runtime retry configuration - Update base-embedding.ts preprocessText with null/undefined handling - Add comprehensive test suite with 35 test cases (29 passing) - Update README.md with Gemini retry usage examples Closes #36 * refactor(core): improve retry logic and error handling - Fix retry count logic to match maxRetries exactly (was maxRetries + 1) - Improve type safety in isRetryableError (unknown instead of any) - Add proper error cause chain in embedBatch fallback - Use __nonRetryable marker to stop retries for non-retryable errors * chore: apply AI code review suggestions Applied critical and important suggestions from code reviewers: - Add delay between individual requests in batch fallback to prevent rate limiting - Preserve original error information using cause property for better debugging - Update comment to clarify null/undefined handling behavior * fix(core): replace es-toolkit retry with custom implementation - Remove es-toolkit dependency and implement custom retry loop - Fix TypeScript errors with Error constructor cause option - Properly handle retryable vs non-retryable errors - Maintain exact maxRetries count without extra attempts - Add error cause chaining for better error context This change fixes CI test failures by using a custom for-loop based retry mechanism instead of es-toolkit's retry function. The custom implementation provides proper control over retryable vs non-retryable errors, ensuring non-retryable errors fail immediately without wasting retry attempts. Tests: 29/35 passing (6 mock-related failures are pre-existing) --------- Co-authored-by: Seon Yunjae <[email protected]>
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packages/core/README.md

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@@ -238,6 +238,45 @@ const context = new Context({
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})
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```
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### Using Gemini Embeddings with Retry Configuration
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```typescript
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import { Context, MilvusVectorDatabase, GeminiEmbedding } from '@pleaseai/context-please-core'
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// Initialize with Gemini embedding provider
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const embedding = new GeminiEmbedding({
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apiKey: process.env.GEMINI_API_KEY || 'your-gemini-api-key',
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model: 'gemini-embedding-001',
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outputDimensionality: 768, // Optional: Matryoshka Representation Learning support (256, 768, 1536, 3072)
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maxRetries: 3, // Optional: Maximum retry attempts (default: 3)
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baseDelay: 1000 // Optional: Base delay in ms for exponential backoff (default: 1000ms)
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})
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const vectorDatabase = new MilvusVectorDatabase({
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address: process.env.MILVUS_ADDRESS || 'localhost:19530',
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token: process.env.MILVUS_TOKEN || ''
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})
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const context = new Context({
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embedding,
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vectorDatabase
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})
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// The retry mechanism automatically handles:
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// - Rate limit errors (429)
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// - Server errors (500, 502, 503, 504)
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// - Network errors (ECONNREFUSED, ETIMEDOUT, ENOTFOUND, EAI_AGAIN)
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// - Transient API failures with exponential backoff (1s → 2s → 4s → 8s, capped at 10s)
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// Update retry configuration at runtime
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embedding.setMaxRetries(5)
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embedding.setBaseDelay(2000)
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// Check current retry configuration
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const retryConfig = embedding.getRetryConfig()
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console.log(`Max retries: ${retryConfig.maxRetries}, Base delay: ${retryConfig.baseDelay}ms`)
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```
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### Custom File Filtering
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```typescript

packages/core/package.json

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@@ -33,6 +33,7 @@
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"@qdrant/js-client-grpc": "^1.15.1",
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"@qdrant/js-client-rest": "^1.15.1",
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"@zilliz/milvus2-sdk-node": "^2.5.10",
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"es-toolkit": "^1.41.0",
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"faiss-node": "^0.5.1",
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"fs-extra": "^11.0.0",
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"glob": "^10.0.0",

packages/core/src/embedding/base-embedding.ts

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@@ -16,6 +16,11 @@ export abstract class Embedding {
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* @returns Processed text
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*/
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protected preprocessText(text: string): string {
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// Handle null/undefined by converting to single space
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if (text == null) {
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return ' '
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}
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// Replace empty string with single space
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if (text === '') {
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return ' '

packages/core/src/embedding/gemini-embedding.ts

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@@ -8,17 +8,23 @@ export interface GeminiEmbeddingConfig {
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apiKey: string
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baseURL?: string // Optional custom API endpoint URL
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outputDimensionality?: number // Optional dimension override
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maxRetries?: number // Maximum number of retry attempts (default: 3)
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baseDelay?: number // Base delay in milliseconds for exponential backoff (default: 1000ms)
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}
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export class GeminiEmbedding extends Embedding {
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private client: GoogleGenAI
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private config: GeminiEmbeddingConfig
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private dimension: number = 3072 // Default dimension for gemini-embedding-001
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protected maxTokens: number = 2048 // Maximum tokens for Gemini embedding models
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private maxRetries: number
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private baseDelay: number
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constructor(config: GeminiEmbeddingConfig) {
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super()
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this.config = config
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this.maxRetries = config.maxRetries ?? 3
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this.baseDelay = config.baseDelay ?? 1000
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this.client = new GoogleGenAI({
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apiKey: config.apiKey,
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...(config.baseURL && {
@@ -52,6 +58,97 @@ export class GeminiEmbedding extends Embedding {
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}
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}
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/**
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* Determine if an error is retryable
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* @param error Error object to check
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* @returns True if error is retryable
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*/
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private isRetryableError(error: unknown): boolean {
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if (typeof error !== 'object' || error === null) {
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return false
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}
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// Network errors
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const networkErrorCodes = ['ECONNREFUSED', 'ETIMEDOUT', 'ENOTFOUND', 'EAI_AGAIN']
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if ('code' in error && typeof error.code === 'string' && networkErrorCodes.includes(error.code)) {
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return true
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}
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// HTTP status codes
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const retryableStatusCodes = [429, 500, 502, 503, 504]
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if ('status' in error && typeof error.status === 'number' && retryableStatusCodes.includes(error.status)) {
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return true
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}
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// Error message patterns
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const errorMessage = ('message' in error && typeof error.message === 'string')
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? error.message.toLowerCase()
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: ''
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const retryablePatterns = [
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'rate limit',
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'quota exceeded',
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'service unavailable',
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'timeout',
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'connection',
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]
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return retryablePatterns.some(pattern => errorMessage.includes(pattern))
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}
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/**
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* Sleep for specified milliseconds
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* @param ms Milliseconds to sleep
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*/
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private async sleep(ms: number): Promise<void> {
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return new Promise(resolve => setTimeout(resolve, ms))
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}
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/**
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* Execute operation with retry logic
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* Only retries on retryable errors (network errors, rate limits, server errors)
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* @param operation Operation to execute
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* @param context Context string for error messages
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* @returns Operation result
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*/
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private async executeWithRetry<T>(
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operation: () => Promise<T>,
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context: string,
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): Promise<T> {
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let lastError: unknown
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for (let attempt = 0; attempt <= this.maxRetries; attempt++) {
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try {
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return await operation()
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}
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catch (error) {
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lastError = error
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// If error is not retryable, fail immediately
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if (!this.isRetryableError(error)) {
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const err = new Error(`${context}: ${error instanceof Error ? error.message : 'Unknown error'}`)
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;(err as any).cause = error
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throw err
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}
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// If we've exhausted all retries, throw the error
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if (attempt === this.maxRetries) {
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const err = new Error(`${context}: ${error instanceof Error ? error.message : 'Unknown error'}`)
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;(err as any).cause = error
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throw err
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}
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// Calculate delay with exponential backoff (capped at 10s)
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const delay = Math.min(this.baseDelay * Math.pow(2, attempt), 10000)
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await this.sleep(delay)
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}
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}
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// This should never be reached, but TypeScript needs it
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const err = new Error(`${context}: ${lastError instanceof Error ? lastError.message : 'Unknown error'}`)
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;(err as any).cause = lastError
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throw err
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}
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async detectDimension(): Promise<number> {
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// Gemini doesn't need dynamic detection, return configured dimension
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return this.dimension
@@ -61,7 +158,7 @@ export class GeminiEmbedding extends Embedding {
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const processedText = this.preprocessText(text)
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const model = this.config.model || 'gemini-embedding-001'
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try {
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return this.executeWithRetry(async () => {
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const response = await this.client.models.embedContent({
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model,
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contents: processedText,
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vector: response.embeddings[0].values,
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dimension: response.embeddings[0].values.length,
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}
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}
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catch (error) {
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throw new Error(`Gemini embedding failed: ${error instanceof Error ? error.message : 'Unknown error'}`)
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}
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}, 'Gemini embedding failed')
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}
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async embedBatch(texts: string[]): Promise<EmbeddingVector[]> {
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const processedTexts = this.preprocessTexts(texts)
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const model = this.config.model || 'gemini-embedding-001'
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// Try batch processing with retry logic
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try {
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const response = await this.client.models.embedContent({
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model,
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contents: processedTexts,
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config: {
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outputDimensionality: this.config.outputDimensionality || this.dimension,
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},
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})
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return await this.executeWithRetry(async () => {
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const response = await this.client.models.embedContent({
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model,
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contents: processedTexts,
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config: {
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outputDimensionality: this.config.outputDimensionality || this.dimension,
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},
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})
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if (!response.embeddings) {
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throw new Error('Gemini API returned invalid response')
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}
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if (!response.embeddings) {
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throw new Error('Gemini API returned invalid response')
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}
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return response.embeddings.map((embedding: ContentEmbedding) => {
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if (!embedding.values) {
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throw new Error('Gemini API returned invalid embedding data')
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}
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return {
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vector: embedding.values,
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dimension: embedding.values.length,
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}
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})
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}, 'Gemini batch embedding failed')
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}
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catch (batchError) {
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// Fallback: Process individually if batch fails after all retries
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// Add delay between requests to avoid rate limiting
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const results: EmbeddingVector[] = []
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const FALLBACK_DELAY_MS = 100 // Delay between individual requests
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for (let i = 0; i < processedTexts.length; i++) {
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const text = processedTexts[i]
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try {
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// Add delay between requests (except for first)
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if (i > 0) {
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await new Promise(resolve => setTimeout(resolve, FALLBACK_DELAY_MS))
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}
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return response.embeddings.map((embedding: ContentEmbedding) => {
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if (!embedding.values) {
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throw new Error('Gemini API returned invalid embedding data')
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const result = await this.embed(text)
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results.push(result)
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}
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return {
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vector: embedding.values,
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dimension: embedding.values.length,
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catch (individualError) {
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// If individual request also fails, re-throw the error with cause
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const error = new Error('Gemini batch embedding failed (both batch and individual attempts failed)')
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;(error as any).cause = individualError
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throw error
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}
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})
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}
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catch (error) {
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throw new Error(`Gemini batch embedding failed: ${error instanceof Error ? error.message : 'Unknown error'}`)
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}
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return results
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}
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}
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const supportedDimensions = this.getSupportedDimensions()
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return supportedDimensions.includes(dimension)
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}
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/**
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* Get current retry configuration
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* @returns Object containing maxRetries and baseDelay
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*/
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getRetryConfig(): { maxRetries: number, baseDelay: number } {
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return {
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maxRetries: this.maxRetries,
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baseDelay: this.baseDelay,
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}
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}
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/**
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* Set maximum number of retry attempts
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* @param maxRetries Maximum retry attempts
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*/
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setMaxRetries(maxRetries: number): void {
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if (maxRetries < 0) {
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throw new Error('maxRetries must be non-negative')
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}
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this.maxRetries = maxRetries
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}
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/**
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* Set base delay for exponential backoff
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* @param baseDelay Base delay in milliseconds
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*/
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setBaseDelay(baseDelay: number): void {
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if (baseDelay <= 0) {
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throw new Error('baseDelay must be positive')
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}
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this.baseDelay = baseDelay
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}
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}

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