Grant
8ac455f5f5
After the recent eugr/spark-vllm-docker update, vLLM became stricter about multimodal token budgets: ValueError: Chunked MM input disabled but max_tokens_per_mm_item (2496) is larger than max_num_batched_tokens (2048). Please increase max_num_batched_tokens. Each image input produces 2496 tokens, but vLLM's default --max-num-batched-tokens of 2048 is just under. Same class of bug as the Qwen3.6 Mamba block-size assertion we fixed in 0.6.0:1, surfacing on different models. Fix: bake --max-num-batched-tokens=16384 into every multimodal model entry. Now applied to: - qwen36 (already had it for the Mamba constraint; works for multimodal too since Qwen3.6 has vision) - gemma4 (crashed today on engine init) - qwen3-vl (would crash with the same error if anyone tried it) The pre-flight Test button validates argparse but the 2048<2496 check happens at runtime engine init, so it's not caught by Test — only by actually trying to load. This is exactly the kind of bug v0.7's Test catches the *syntax* of but not the *semantics*; runtime errors like this still surface only on real swap. Known limitation documented in v0.7 release notes.
38 lines
3.2 KiB
Markdown
38 lines
3.2 KiB
Markdown
# Known issues
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## ~~magpie-tts crash loop (Spark 2)~~ — RESOLVED 2026-05-12
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**What Magpie is:** NVIDIA's multilingual text-to-speech (TTS) model, served via the NIM (NVIDIA Inference Microservices) framework — a Riva Speech Server container that converts text into spoken audio. It's the counterpart to Parakeet (which is speech-to-text / STT). When working, it exposes `/v1/audio/speech` on port 9000 and is used by clients like Open WebUI for the "read aloud" feature.
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**Root cause:** The Docker volume `magpie-model-cache` (mounted at `/opt/nim/.cache` in the container) was owned by `root:root` on the host. The container drops to uid 1000 (`riva-server`) and tries to download model manifests into that cache — got `I/O error Permission denied (os error 13)` — exited 1 — restarted infinitely (24,000+ restarts before the fix).
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**Fix:**
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```bash
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ssh <spark-user>@<spark-2-host> 'docker run --rm -v magpie-model-cache:/cache alpine chown -R 1000:1000 /cache && docker restart magpie-tts'
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```
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The trick is the `docker run --rm alpine chown` — it runs as root inside the throwaway container, which is enough to chown the bind-mounted volume on the host, without needing `sudo` on the host itself. After the chown + restart, magpie downloaded its ~3 GB model from NGC into the cache and came up healthy on `:9000`.
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**If it ever recurs** (e.g. after wiping the volume), re-run that one command.
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## Qwen3.6-35B-A3B `--moe_backend=flashinfer_cutlass` may fail on launch
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This flag is Blackwell-specific. If vLLM in the container reports `unrecognized arguments: --moe_backend` or similar, edit `models.yaml` for `qwen36` and drop that flag. The swap UI does NOT auto-fallback in v0.1 — failure surfaces in the log stream.
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## Qwen3.6 Mamba block-size assertion (fixed in v0.6.0:1)
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Qwen3.6 uses a Mamba-attention hybrid that requires `--max-num-batched-tokens >= 2096`. vLLM's default is 2048, which trips `AssertionError: In Mamba cache align mode, block_size (2096) must be <= max_num_batched_tokens (2048)`. Fix: bake `--max-num-batched-tokens=16384` into the bundled qwen36 entry — matches the upstream qwen3.5-35b-a3b-fp8 recipe.
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## Multimodal token budget for vision models (fixed in v0.8.0:1)
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After the eugr/spark-vllm-docker update, vLLM became stricter about multimodal token budgets. Vision-capable models like Gemma 4 31B and Qwen3-VL crash at engine init with `ValueError: Chunked MM input disabled but max_tokens_per_mm_item (2496) is larger than max_num_batched_tokens (2048)`. Fix: bake `--max-num-batched-tokens=16384` into every model that has the `vision` capability. Now applied to qwen3-vl, gemma4, and qwen36 (which was already set for the Mamba issue).
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## Two SSH paths to Spark 1 from the laptop
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`ssh <spark-user>@<spark-1-ip>` does NOT work from the laptop because the NVIDIA Sync ssh_config only has a Host entry for `<spark-1-host>.local`. Always use the `.local` hostname or `<spark-2-ip>`-style entries that ARE matched.
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## Older models in `models.yaml`
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The `qwen3-235b-fp8` and `qwen25-72b` catalog entries are conservative guesses for vLLM flags — they're on disk but were never the focus of this project. First launch of either may fail or be suboptimal; capture working flags here.
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