Vector Index Configuration Optimizer

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Optimize vector index configurations by analyzing HNSW and IVF parameters with performance trade-off analysis and memory impact assessment.

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As a Lead AI Engineer, optimize the vector index configuration for our use case.

## Dataset Profile
- Vector count: {{vector_count}}
- Dimensionality: {{dimensions}}
- Query volume: {{qps}}

## Current Configuration
{{current_config}}

## Performance Metrics
- Recall@10: {{recall_at_10}}
- Query latency P99: {{latency_p99}}ms

Evaluate index types and parameters:

**HNSW Analysis**:
- M parameter optimization
- ef_construction tuning
- ef_search calibration

**IVF Analysis**:
- nlist optimization
- nprobe tuning
- Quantization options (PQ, SQ)

Provide:
- Recommended configuration with rationale
- Expected performance improvements
- Memory impact assessment
- Reindexing strategy

Details

Category

Analysis

Use Cases

Index optimizationVector search tuningPerformance tuning

Works Best With

claude-sonnet-4-20250514gpt-4o
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Vector Index Configuration Optimizer | Promptsy