The pair for vLLM v0.29.0: rc1's docs pin vllm==0.29.0 and a static scan of
rc1's vllm.* imports against the v0.29.0 tree finds nothing missing, while
our 0.28-based tree needs seven modules v0.29.0 no longer has
(vllm.inputs.preprocess, entrypoints.launcher, openai.cli_args,
openai.engine.protocol, serve.utils.server_utils, layers.batch_invariant,
models.hunyuan_v1).
Ten files conflicted. Upstream's structure is the base everywhere; the
fork's features are re-attached to it:
- deploy_profile / apply_deploy_profile run before rc1's resolve_omni_config
pops deploy_config (async_omni_engine, cli/serve); the deploy-profile
selector and the resolve_model_config_path chain it needs stay in
entrypoints/utils.py; stage_overrides takes rc1's dict type.
- config_factory keeps the lazy diffusion output-type import; the diffusion
registry import in rc1's new config/resolver.py is made lazy for the same
WP6 reason (TTS path must not load diffusion).
- requirements: our core/media split kept; rc1's transformers>=5.13 floor
and kernels==0.16.1 applied in core.txt / media.txt.
- TTS: rc1's split_granularity and bounded seed plus our output_mode=
codec_tokens, _SessionInbox cancel handling and codec DELTA accumulation;
our private _conditioning_cache_salt is superseded by rc1's public
tts_adapters/base.py::conditioning_cache_salt.
- stage_runtime: rc1's single ExitStack G2 path (lock released before READY)
replaces our two-path block, with the four worker_phase names the init
profiler consumes still emitted; _cpu_placed / host admission kept.
Not yet run against vLLM 0.29.0: the tests listed in the W6 record.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
- vllm_omni/edge/step_stats.py: process-local counters enabled by
VLLM_OMNI_STEP_STATS_DIR (scheduler schedule/update_from_output, engine-core
step, chunk hop enqueue->put / put->get / get, orchestrator dispatch), dumped
per process and merged into an attribution table (share of the 80 ms frame).
Hooks: stage_engine_core_proc (instrument after construction, dump at exit),
chunk_transfer_adapter (put/get timing, put->get via the shm lock-file mtime),
orchestrator dispatch loop. Bench: stream_latency_bench.py --step-stats.
- vllm_omni/edge/scheduling.py: playback slack, prefill-throttle decision and
the no-preemption KV admission rule (exact bytes/token from the talker KV
geometry); adapt.derive_overrides now sizes max_num_seqs with it and
auto_profile passes the geometry read from the model config.
- Engine re-reads parallel_stage_init after apply_deploy_profile so the edge
profile's orchestrator default takes effect (was read before the profile).
- benchmarks/tts/cpu_thread_sweep.py: CPU-only 8/16/32-thread sweep (+inductor)
with per-step attribution.
- Tests: tests/core/test_edge_scheduling.py, tests/edge/test_step_stats.py,
tests/benchmarks/test_cpu_thread_sweep.py, profile default test.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
* diffusers is no longer imported by vllm_omni.diffusion.data (annotation only);
vllm_omni.diffusion.io_support (diffusion registry + distributed state) is
imported lazily by config_factory and async_omni_engine, so constructing a
Qwen3-TTS pipeline config / AsyncOmni no longer loads diffusers,
x_transformers or whisper (guarded by tests/config/test_import_guard.py).
* requirements/common.txt = core.txt (AR/speech runtime) + media.txt
(diffusion/video/extra audio); VLLM_OMNI_EDGE_BUILD=1 makes setup.py use
requirements/<device>-edge.txt (core only); `edge` extra adds websockets and
sounddevice for on-device clients.
Measured on this host (CUDA venv): `import vllm` 7.0-7.9 s, `import vllm_omni`
adds ~20 s of which ~17 s is transformers' own import (transformers.utils.import_utils)
pulled in by vllm_omni.patch / vllm_omni.version; that floor is not
vLLM-Omni's and is unchanged. Guard test: no diffusion module loaded on the TTS path.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
