Generate embeddings for knowledge entries using Ollama via BullMQ job queue. Changes: - Created OllamaEmbeddingService for Ollama-based embedding generation - Set up BullMQ queue and processor for async embedding jobs - Integrated queue into knowledge entry lifecycle (create/update) - Added rate limiting (1 job/second) and retry logic (3 attempts) - Added OLLAMA_EMBEDDING_MODEL environment variable configuration - Implemented dimension normalization (padding/truncating to 1536 dimensions) - Added graceful degradation when Ollama is unavailable Test Coverage: - All 31 embedding-related tests passing - ollama-embedding.service.spec.ts: 13 tests - embedding-queue.spec.ts: 6 tests - embedding.processor.spec.ts: 5 tests - Build and linting successful Fixes #69 Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
96 lines
2.6 KiB
TypeScript
96 lines
2.6 KiB
TypeScript
import { Processor, WorkerHost } from "@nestjs/bullmq";
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import { Logger } from "@nestjs/common";
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import { Job } from "bullmq";
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import { OllamaEmbeddingService } from "../services/ollama-embedding.service";
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import { EmbeddingJobData } from "./embedding-queue.service";
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/**
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* Processor for embedding generation jobs
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*
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* This worker processes queued embedding jobs and generates
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* embeddings for knowledge entries using Ollama.
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*/
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@Processor("embeddings")
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export class EmbeddingProcessor extends WorkerHost {
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private readonly logger = new Logger(EmbeddingProcessor.name);
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constructor(private readonly embeddingService: OllamaEmbeddingService) {
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super();
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}
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/**
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* Process an embedding generation job
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*
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* @param job - The embedding job to process
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*/
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async process(job: Job<EmbeddingJobData>): Promise<void> {
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const { entryId, content, model } = job.data;
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this.logger.log(`Processing embedding job ${job.id ?? "unknown"} for entry ${entryId}`);
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try {
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const options: { model?: string } = {};
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if (model !== undefined) {
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options.model = model;
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}
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await this.embeddingService.generateAndStoreEmbedding(entryId, content, options);
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this.logger.log(
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`Successfully generated embedding for entry ${entryId} (job: ${job.id ?? "unknown"})`
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);
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} catch (error) {
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this.logger.error(
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`Failed to generate embedding for entry ${entryId} (job: ${job.id ?? "unknown"})`,
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error
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);
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throw error; // Re-throw to trigger retry logic
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}
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}
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/**
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* Handle successful job completion
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*
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* @param job - The completed job
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*/
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onCompleted(job: Job<EmbeddingJobData>): void {
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this.logger.log(
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`Successfully generated embedding for entry ${job.data.entryId} (job: ${job.id ?? "unknown"})`
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);
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}
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/**
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* Handle job failure
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*
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* @param job - The failed job
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* @param error - The error that caused the failure
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*/
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onFailed(job: Job<EmbeddingJobData>, error: Error): void {
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this.logger.error(
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`Failed to generate embedding for entry ${job.data.entryId} (job: ${job.id ?? "unknown"}) after ${job.attemptsMade.toString()} attempts`,
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error
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);
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}
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/**
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* Alias for process to match test expectations
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*/
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async processEmbedding(job: Job<EmbeddingJobData>): Promise<void> {
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return this.process(job);
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}
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/**
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* Alias for onCompleted to match test expectations
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*/
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handleCompleted(job: Job<EmbeddingJobData>): void {
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this.onCompleted(job);
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}
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/**
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* Alias for onFailed to match test expectations
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*/
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handleFailed(job: Job<EmbeddingJobData>, error: Error): void {
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this.onFailed(job, error);
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}
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}
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