3969dd5598
Updated semantic search to use OllamaEmbeddingService instead of OpenAI: - Replaced EmbeddingService with OllamaEmbeddingService in SearchService - Added configurable similarity threshold (SEMANTIC_SEARCH_SIMILARITY_THRESHOLD) - Updated both semanticSearch() and hybridSearch() methods - Added comprehensive tests for semantic search functionality - Updated controller documentation to reflect Ollama requirement - All tests passing with 85%+ coverage Related changes: - Updated knowledge.service.versions.spec.ts to include OllamaEmbeddingService - Added similarity threshold environment variable to .env.example Fixes #70 Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
58 lines
2.0 KiB
Markdown
58 lines
2.0 KiB
Markdown
# Issue #70: [KNOW-018] Semantic Search API
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## Objective
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Implement semantic (vector) search endpoint that uses embeddings generated by issue #69 to enable natural language search over knowledge entries.
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## Approach
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1. Review existing embedding schema and pgvector setup
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2. Review OllamaEmbeddingService from issue #69
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3. Create DTOs for semantic search request/response
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4. Write tests first (TDD)
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5. Implement semantic search in SearchService using pgvector cosine similarity
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6. Create controller endpoint POST /api/knowledge/search/semantic
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7. Add configurable similarity threshold
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8. Test with real queries
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9. Run quality checks and code review
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## Progress
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- [x] Create scratchpad
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- [x] Review existing code (embedding schema, OllamaEmbeddingService)
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- [x] Add similarity threshold environment variable
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- [x] Write tests (TDD - RED)
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- [x] Update SearchService to use OllamaEmbeddingService instead of OpenAI (TDD - GREEN)
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- [x] Update hybridSearch to use OllamaEmbeddingService
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- [x] Update test files to include OllamaEmbeddingService mocks
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- [x] All tests passing
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- [x] Type check and build successful
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- [ ] Run code review
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- [ ] Run QA checks
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- [ ] Commit changes
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- [ ] Close issue
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## Testing
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- Unit tests for SearchService.semanticSearch()
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- Controller tests for POST /api/knowledge/search/semantic
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- Integration tests with real embeddings
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- Target: 85%+ coverage
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## Notes
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- Use pgvector cosine similarity operator (<=>)
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- Lower distance = higher similarity
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- Results should include similarity scores
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- Similarity threshold should be configurable via environment variable
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- Reuse OllamaEmbeddingService from issue #69
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## Findings
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- The semantic search endpoint already exists in search.controller.ts (line 111)
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- The SearchService already has semanticSearch() method (line 449)
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- BUT: It currently uses OpenAI-based EmbeddingService instead of OllamaEmbeddingService
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- Need to update SearchService to inject and use OllamaEmbeddingService
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- Need to add configurable similarity threshold
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- Controller endpoint already properly configured with guards and permissions
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