vertex-ai-search
A modular testing framework for Google Vertex AI Search and Conversation that processes 1600 HTML documents from the Natural Questions dataset through isolated pipeline stages. The system handles data ingestion, cloud storage operations, vector embedding generation, and performance metrics collection with high test coverage across each independently deployable component.
A comprehensive testing framework for Google Vertex AI Search and Conversation that processes 1600 HTML documents from the Natural Questions dataset through a modular pipeline architecture. The system implements pure module isolation with 16 independent components covering data ingestion, cloud operations, vector embeddings, and performance testing with impressive test coverage across all modules.
- ✓Exceptional test coverage across all modules (86-100% range) with detailed coverage reporting
- ✓Innovative pure module isolation architecture where each of 16 modules can be built, tested, and deployed independently with strict <60 files per module constraint
- ✓Production-ready vector search pipeline with specific performance targets (<120ms p95 for ANN queries) and comprehensive monitoring through dedicated metrics collection
- →Add concrete performance benchmarks and comparison metrics in the README to demonstrate the system's effectiveness against baseline search solutions
- →Include example API responses and usage scenarios for the FastAPI endpoints to help developers understand integration patterns