Performance Optimization
Performance optimization reduces response latency and increases throughput in LLM applications through techniques including parallel execution, caching, model selection, batch processing, and infrastructure optimization. Key techniques: async/await patterns for parallel operations, semantic caching for repeated queries, streaming responses for progressive results, model downgrading with maintained quality, and edge deployment for reduced latency.
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