9 Commits
Author SHA1 Message Date
MOVZXandHinata fe3cd9247b build: Reuse the extensions for a Python-only patch series
git am refreshes every file timestamp, so a Python-only patch series
forced a full extension rebuild and ninja saw everything as changed.
Diff csrc/ and the build files between the recorded tree and HEAD, and
rebuild only when a C++/CUDA source moved; otherwise the shipped .so
stays.

Update the expected tree to the 106-patch series
(c9c526755364d44d8d9923d9acc9d6d1a3d58718).

Add ipc: host, SYS_PTRACE, and seccomp=unconfined to the container so
a profiler or debugger can attach.

Raise --block-size from 2048 to 4096 and drop
--safetensors-load-strategy prefetch.

Co-Authored-By: Hinata <hinata@idihore.id>
Signed-off-by: MOVZX <movzx@yahoo.com>
2026-10-17 23:29:02 +00:00
MOVZXandHinata d9ca3bc4f2 feat: Set concurrency and the CUDA graph list from .env
MAX_SEQS and the prefill chunk were fixed in the start profile, so any
change to concurrency needed an edit to the script. Read both from .env,
and validate them before the engine starts. The chunk must be at least
the sequence count, the rule vLLM applies at scheduler.py:309. A
MAX_SEQS whose full context exceeds the 924,993-token pool prints a
note, because that shape preempts and recomputes instead of failing.

The captured graph list was a fixed [1,2,4,8,12,16], which covers a
decode batch of 4 requests and nothing wider. One decode step is K+1 = 4
tokens per request, so the list now follows MAX_SEQS: 1, 2, 4, then
every 4 tokens up to MAX_SEQS x 4. At the shipped 4 it produces the old
list exactly. Above 8 graphs a note prints, since each size costs
capture time and graph VRAM.

Drop --mm-processor-cache-gb. This workload sends each image once, so
the cache never had a hit to keep, and vLLM's own 4 GiB default is the
better base.

Co-Authored-By: Hinata <hinata@idihore.id>
Signed-off-by: MOVZX <movzx@yahoo.com>
2026-10-18 02:04:50 +07:00
MOVZXandHinata fab0eb9fc7 feat: Offload the vision tower to host RAM
The vision tower sat on GPU 0 and 1 all the time, and did work only
when a request carried an image. It now streams from pinned host RAM
and encodes over H2D, which frees 432 MiB on GPU 0 and 1. Stage 1
carries no tower, so GPU 2 and 3 gain nothing, and the KV cache stays
at 924,993 tokens because --kv-cache-memory pins it. The freed memory
is headroom, not capacity. An image request passes: 2223 image tokens
in 11.77 s, with no VRAM growth.

Key the prebuilt ops cache on the compiled inputs, so a Python-only
patch installs from the shipped tarball instead of a 20-40 minute
compile.

Raise --mm-processor-cache-gb to 16. That cache is duplicated for each
API process and engine core process, so 16 GiB costs 32 GiB of host
RAM and no VRAM, and repeated images stop re-processing.

Co-Authored-By: Hinata <hinata@idihore.id>
Signed-off-by: MOVZX <movzx@yahoo.com>
2026-10-18 01:49:04 +07:00
MOVZXandHinata 3a0a5d1510 feat: Set the engine stats interval to 1 s
The stats line carried throughput, KV usage and queue depth, but the
interval was never set. Unset, vLLM waits 10 s (vllm/envs.py:47), so a
quiet run looked idle for ten seconds and a short one printed nothing.

Export VLLM_LOG_STATS_INTERVAL in start.sh with a default of 1, and pass
it through Compose so .env can raise it back to 10. Add the variable to
.env.example, to the start.sh header, and to the Variables table in both
READMEs.

Co-Authored-By: Hinata <hinata@idihore.id>
Signed-off-by: MOVZX <movzx@yahoo.com>
2026-10-16 06:01:27 +00:00
MOVZXandHinata c4d88acb4d feat: Accept any model name in a request
A request that named another model failed with 404 "The model `X` does
not exist.", and the model name changes often here. vLLM already has
the switch: _is_model_supported() accepts every name when
VLLM_SKIP_MODEL_NAME_VALIDATION is set, and _check_model is the only
gate, on the chat, completion, responses, tokenize, pooling and
realtime paths alike.

Turn it on in the serve profile, under the upstream name, so 0 still
restores the strict check. The served name does not change: /v1/models
and the model field of every reply still report MODEL_NAME. No patch is
needed, and Compose bind-mounts start.sh, so a restart applies this.

Co-Authored-By: Hinata <hinata@idihore.id>
Signed-off-by: MOVZX <movzx@yahoo.com>
2026-10-16 05:40:19 +00:00
MOVZXandHinata 1281bf9c03 fix: Load the FP8 KV scales from the shipped file name
The default sidecar pointed at qsa_kv_scales_swift.json, a name no
checkpoint on this box carries. The guard in start.sh then stopped every
start with "scales sidecar missing", and a start without the guard would
run FP8 KV at scale 1.0.

Point the default at qsa_kv_scales.json, the file both checkpoints ship,
and rename the sidecar in the start.sh header, both READMEs, and the
Dockerfile comment. Name SCALES in the guard message.

Co-Authored-By: Hinata <hinata@idihore.id>
Signed-off-by: MOVZX <movzx@yahoo.com>
2026-10-15 18:52:06 +00:00
MOVZXandHinata 5cc9ee2505 chore: Reset vLLM logging interval back to default
Co-Authored-By: Hinata <hinata@idihore.id>
Signed-off-by: MOVZX <movzx@yahoo.com>
2026-10-15 06:37:23 +00:00
MOVZX eb8c302bb3 fix: Adjust start script to avoid crashing on high pressure KV cache
Stress-tested using 4 concurrent requests with 240K tokens each:
```
(APIServer pid=1) INFO 10-15 06:21:25 [loggers.py:315] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3.0 tokens/s, Running: 4 reqs, Waiting: 1 reqs, GPU KV cache usage: 98.8%, Prefix cache hit rate: 0.0%
(APIServer pid=1) INFO 10-15 06:21:26 [loggers.py:315] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 17.0 tokens/s, Running: 4 reqs, Waiting: 1 reqs, GPU KV cache usage: 99.2%, Prefix cache hit rate: 0.0%
(APIServer pid=1) INFO 10-15 06:21:27 [loggers.py:315] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 8.0 tokens/s, Running: 4 reqs, Waiting: 1 reqs, GPU KV cache usage: 99.6%, Prefix cache hit rate: 0.0%
(APIServer pid=1) INFO 10-15 06:21:28 [loggers.py:315] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 20.9 tokens/s, Running: 4 reqs, Waiting: 1 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 0.0%
```
Co-Authored-By: Hinata <hinata@idihore.id>
Signed-off-by: MOVZX <movzx@yahoo.com>
2026-10-15 06:24:25 +00:00
MOVZX 777e910dd0 Initial commit
Signed-off-by: MOVZX <movzx@yahoo.com>
2026-10-15 01:01:52 +07:00