Definition
Profiling in the context of RAG and AI Agents is the granular analysis of latency, token consumption, and computational cost across individual pipeline nodes—such as embedding generation, vector search, and LLM inference. It identifies performance bottlenecks where the trade-off between retrieval depth and generation speed becomes inefficient.
Distinguish from 'User Profiling'; here it refers to execution performance and resource instrumentation, not demographic data.
"A digital stopwatch and a receipt printer attached to every station on a factory conveyor belt."
- Tracing(Prerequisite)
- Latency(Component)
- Token Usage Metrics(Component)
- Observability(Parent Concept)
Conceptual Overview
Profiling in the context of RAG and AI Agents is the granular analysis of latency, token consumption, and computational cost across individual pipeline nodes—such as embedding generation, vector search, and LLM inference. It identifies performance bottlenecks where the trade-off between retrieval depth and generation speed becomes inefficient.
Disambiguation
Distinguish from 'User Profiling'; here it refers to execution performance and resource instrumentation, not demographic data.
Visual Analog
A digital stopwatch and a receipt printer attached to every station on a factory conveyor belt.