vh
b8f0f4c568
The char-rp seat shipped with no tool-call parser at all, so every
tools-bearing request was rejected outright:
400 "auto" tool choice requires --enable-auto-tool-choice and
--tool-call-parser to be set
MeroMero-v2 is Gemma-4, which emits its own native
`<|tool_call>call:name{...}<tool_call|>` syntax rather than the
qwen3_coder XML the Qwen-family seats use. vLLM 0.24 ships a matching
`gemma4` parser whose TOOL_CALL_START/END, CHANNEL_START/END and escape
token constants line up with this tokenizer's etc/eoc/escape tokens
exactly.
Three flags, and they are a set:
- --tool-call-parser gemma4 + --enable-auto-tool-choice: the fix proper.
- --reasoning-parser gemma4: without it the post-tool-response turn
leaks a literal `<|channel>thought\n<channel|>` prefix into content
(upstream vllm #45834 — the chat template leaves the prompt inside an
open channel block).
- --default-chat-template-kwargs '{"enable_thinking": false}': MANDATORY
companion to the reasoning parser. The parser reads enable_thinking
from chat_template_kwargs and defaults it to True
(vllm/parser/gemma4.py:439); True makes is_reasoning_end() return
False at a new turn, pre-initialising the engine to REASONING, which
routes ALL plain RP prose into reasoning_content and returns a null
content — breaking every char-rp consumer. This template already
defaults enable_thinking to false (chat_template.jinja:350), so
passing it explicitly renders a byte-identical prompt (verified across
plain / tools / post-tool-response / system-prompt shapes). It changes
generation not at all; it only corrects the parser state machine.
Verified green on the live seat after deploy: tool call streaming and
non-streaming, tool-result round-trip (leak gone), plain prose in
content with reasoning null, vision unchanged.
95 lines
3.8 KiB
YAML
95 lines
3.8 KiB
YAML
# meromero-charrp — G4-MeroMero-v2-31B NVFP4A16 char-rp PROSE seat (non-thinking, MULTIMODAL)
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# on ana-ml2 GPU0. Replaces the retired Magidonia GGUF seat (char-rp-gguf / llama-charrp).
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#
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# Gemma-4 dense but with SLIDING-WINDOW attention -> KV-efficient, serves the full native 256K
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# at ~2x concurrency. Vision enabled: preprocessor_config.json was materialized from
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# processor_config.json's image_processor section (Gemma4ImageProcessor); audio is
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# config-declared but weightless (no audio tensors) so it serves image + text.
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#
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# Co-located on GPU0 with vllm-aeon-gen (gen). util 0.52 leaves ~5GB GPU0 headroom
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# (0.55 left only ~1.8GB). Tunables in .env.
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name: meromero-charrp
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services:
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vllm-meromero-rp:
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image: ${MEROMERO_IMAGE:-vllm/vllm-openai:latest}
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container_name: ${MEROMERO_CONTAINER:-vllm-meromero-rp}
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restart: unless-stopped
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ipc: host
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ports:
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- "${MEROMERO_PORT:-8016}:8000"
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volumes:
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- /tank/aimodels:/tank/aimodels
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environment:
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- PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
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- VLLM_API_KEY=${API_KEY:-}
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command:
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- ${MEROMERO_MODEL:-/tank/aimodels/meromero-v2-nvfp4-work/G4-MeroMero-v2-31B-NVFP4A16}
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- --quantization
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- compressed-tensors
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- --served-model-name
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- char-rp
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# Tool-calling: Gemma-4 emits its OWN native syntax
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# (<|tool_call>call:name{...}<tool_call|>), NOT the qwen3_coder XML the
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# other seats use. vLLM 0.24 ships a matching `gemma4` parser whose token
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# constants line up with this tokenizer's etc/eoc/escape tokens exactly.
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# Without these two flags any tools-bearing request 400s outright.
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- --tool-call-parser
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- gemma4
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- --enable-auto-tool-choice
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# The gemma4 REASONING parser is what absorbs the <|channel>...<channel|>
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# thought markers; without it they leak into `content` verbatim on the
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# post-tool-response turn (upstream vllm #45834 — the chat template leaves
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# the prompt inside an open channel block).
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- --reasoning-parser
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- gemma4
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# MANDATORY companion to the reasoning parser on this seat. The parser
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# reads enable_thinking from chat_template_kwargs and DEFAULTS IT TO TRUE
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# (vllm/parser/gemma4.py:439). True makes is_reasoning_end() return False
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# at a new turn, which pre-initialises the engine to REASONING -> ALL plain
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# RP prose lands in reasoning_content with a NULL content, breaking every
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# char-rp consumer. This template already defaults enable_thinking to false
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# (chat_template.jinja:350), so passing it explicitly renders a BYTE-
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# IDENTICAL prompt (verified across plain/tools/post-tool/system shapes) --
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# it only corrects the parser's state machine. Do not remove.
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- --default-chat-template-kwargs
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- '{"enable_thinking": false}'
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- --max-model-len
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- "${MEROMERO_MAX_MODEL_LEN:-262144}"
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- --max-num-seqs
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- "${MEROMERO_MAX_NUM_SEQS:-32}"
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- --gpu-memory-utilization
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- "${MEROMERO_GPU_MEM_UTIL:-0.52}"
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- --kv-cache-dtype
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- fp8
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- --trust-remote-code
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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device_ids:
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- "${MEROMERO_GPU_ID:-0}"
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capabilities:
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- gpu
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 600s
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networks:
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- tnet
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labels:
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- homepage.group=AI - Inference
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- homepage.name=char-rp (MeroMero-v2 NVFP4, multimodal)
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- homepage.icon=mdi-drama-masks
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- homepage.description=G4-MeroMero-v2-31B NVFP4A16 non-thinking prose seat, vision-enabled, 256K (ana-ml2 GPU0)
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- homepage.href=http://10.250.50.54:${MEROMERO_PORT:-8016}/docs
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networks:
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tnet:
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name: traefik-net
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external: true
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