Segment 61
In this sub-session, the assistant shifted focus from training to deployment of the z-lab DFlash DDTree drafter. The active training run was killed, and after investigating deployment options (finding SGLang's native DFlash linear-only and vLLM's DDTree PR blocked), a temporary standalone OpenAI-compatible DDTree service was deployed on CT200 using the z-lab draft model, verified with smoke tests and health checks. The assistant then researched the feasibility of integrating DDTree into SGLang or vLLM, concluding SGLang is the better target, and created a detailed roadmap (sglang-ddtree-roadmap.md) outlining implementation phases. Additionally, a standalone utility module (sglang_ddtree_utils.py) was implemented with DDTree tree-building, visibility mask construction, tree-walk verification, and debug summary metrics, staged on the eval host's SGLang package.
The Deployment Pivot: From Training to Production with DDTree Speculative Decoding