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Add Gemma4 31B model-specific serving support on top of the shared examples/llm_server harness.
This extracts the existing runner flow into a small Gemma4_31BEngine/LLMSession adapter, keeps main.cpp as a thin runner wrapper, and adds a C++ JSONL worker plus Python OpenAI-compatible launcher. The generic server remains model-agnostic; Gemma-specific behavior stays in examples/models/gemma4_31b, including chat-template options, BOS handling, channel cleanup, and Gemma tool-call parsing.
Also wire the worker into the existing Gemma CUDA/MLX CMake presets and Makefile targets, document the serving harness usage, and add validation coverage: hermetic launcher tests, an opt-in on-device BOS/template regression test, and a CUDA no-bleed integration proof for interleaved multi-session execution.
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