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How to build a mini inference engine step by step with Zero to Sglang

Follow Part II to add forward pass, KV Cache, HTTP serving, paging, and RadixAttention to a mini-sglang.

  • Research
  • Advanced
  • 8 hours
  • From the README
  • Any agent

Who it is forAn engineer who wants to understand inference engine internals by writing one, usually over several weeks alongside the course.

The problemReading a production engine like SGLang first is hard without knowing which parts do what.

The outcomeA self-built mini-sglang with forward pass, KV Cache, concurrent HTTP requests, Paged KV Cache, and RadixAttention, plus an understanding of the real engine's structure.

What you need first

  • Python and basic software engineering habits
  • Familiarity with PyTorch and neural network basics
  • Git installed to clone the repository
  • A GPU for Part 0 deployment and full mini-sglang performance tests (cloud GPU is fine; Part I needs no GPU)

Steps

  1. git clone https://github.com/datawhalechina/zero-to-sglang.git
  2. cd zero-to-sglang
  3. Read course-material/eng/part2/Chapter1_mini-sglang-What-an-Inference-Engine-Looks-Like.md for the architecture overview.
  4. Work through Chapter 3 (forward pass and generation) and Chapter 4 (KV Cache) using their concept files and Code Walkthrough files.
  5. Implement Chapter 5 (HTTP and concurrent requests), then Chapter 7 (Paged KV Cache) and Chapter 8 (RadixAttention), checking each step against the code walkthrough.
  6. Install dependencies as each chapter requires, then compare your result with the reference implementation at https://github.com/sgl-project/mini-sglang. (inferred, check the README)

Prompt for your agent

Use the repo https://github.com/datawhalechina/zero-to-sglang and implement Chapter 4 (KV Cache) of Part II in <target-directory>. Expected output: a generation loop that reuses cached keys and values for a short prompt. Verify that the output tokens match a run without the cache for the same prompt.

Caveat. Chapters 6 (Continuous Batching) and 10 (Speculative Decoding) are still planned, so the build path has gaps that you must fill yourself.

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