Directly-constructed GenerationRequests marked every schema default as
explicit (normalize_generation_request bound the full serialization when
_fastvideo_explicit_paths was absent), so request_to_sampling_param
overwrote model preset values with schema defaults: FastWan DMD ran
3->50 steps, TurboDiffusion 4->50, stable-audio 100 steps/CFG7 ->
50/CFG1, and 1.3B Wan examples rendered 720x1280x125f with CFG off.
Fix at the root: SamplingConfig fields now default to None = "inherit
the model preset". None leaves are never bound as explicit paths — for
directly-constructed requests (normalize_generation_request) and for
parsed YAML/JSON (parse_config treats explicit null as unset, so
widening the types cannot let nulls stomp presets either). Dicts
emptied by the pruning are dropped too, so None-valued extensions
cannot resurface via the live-attribute read in
explicit_request_updates. The _SCHEMA_DEFAULT_UPDATES tolerance hack is
deleted (an explicitly-set field unsupported by a model's SamplingParam
now always fails loudly), and return_state is skipped in the update
loop since it is already translated to return_continuation_state.
Consumers of raw (pre-resolution) sampling fields are guarded: the
streaming server validates operator-pinned default_request.sampling
before the multi-minute model boot (run_server) and in build_app; its
segment negative_prompt merge preserves an explicit "" clear; the mock
server supplies concrete fallbacks; generate_async resolves the preset
so its advertised total_steps matches the actual run; the ray-serve
gradio demo passes "" to keep its no-negative-prompt default. Stale
schema-default claims in video_api/ServeConfig/openai.md docs updated.
Tests: test_preset_inheritance.py locks the contract (bare request
inherits preset; partial override; explicit value equal to an old
schema default wins; negative_prompt None-inherits/""-clears; parsed
nulls inherit; None-valued extensions are dropped; unsupported explicit
field raises) plus a build_app pin-validation test.
SolitaryThinker