Problems / RAG and retrieval, medium
Agentic RAG rewrites each question with a small model before retrieval. The rewriter has 8 slots at 80 questions a second.
Free to open. Runs in your browser, no sign-up.
Success ≥ 99%, time to first token p99 ≤ 2.5 s.
80 requests a second for 30 seconds: 100% request (reads).
What each component does in this design, and what calls it. The simulator mimics each one from these settings.
| Component | Its job here | Settings |
|---|---|---|
| Load balancerLoad balancer | Traffic enters here.Calls AI app.Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header. | – |
| AI appApp service | Load balancer forwards to it.Calls Query rewriter, Hybrid search, Model.Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s. | 3 replicas × 500 slots · timeout 30 s |
| Query rewriterQuery rewriter | AI app calls it.Rewriting a vague question into a precise search query often improves retrieval more than a bigger model does. | 8 slots |
| Hybrid searchHybrid search | AI app calls it.Hybrid search combines keyword matching (BM25) with vector similarity. | 400 slots · 2 steps |
| ModelLLM endpoint | AI app calls it.Latency has two parts: time to the first token, then a steady stream of tokens per second. | 400 streams |
Try it first. Open one hint at a time if you get stuck.
The rewriter runs on every question.
Slots needed = rate × rewrite time.
Give the query rewriter more capacity (or skip it for clear questions).