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chore: introduce write queue for inference_store (#3383)
# What does this PR do? Adds a write worker queue for writes to inference store. This avoids overwhelming request processing with slow inference writes. ## Test Plan Benchmark: ``` cd /docs/source/distributions/k8s-benchmark # start mock server python openai-mock-server.py --port 8000 # start stack server LLAMA_STACK_LOGGING="all=WARNING" uv run --with llama-stack python -m llama_stack.core.server.server docs/source/distributions/k8s-benchmark/stack_run_config.yaml # run benchmark script uv run python3 benchmark.py --duration 120 --concurrent 50 --base-url=http://localhost:8321/v1/openai/v1 --model=vllm-inference/meta-llama/Llama-3.2-3B-Instruct ``` ## RPS from 21 -> 57
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7 changed files with 139 additions and 22 deletions
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@ -78,7 +78,10 @@ async def get_auto_router_impl(
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# TODO: move pass configs to routers instead
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if api == Api.inference and run_config.inference_store:
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inference_store = InferenceStore(run_config.inference_store, policy)
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inference_store = InferenceStore(
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config=run_config.inference_store,
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policy=policy,
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)
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await inference_store.initialize()
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api_to_dep_impl["store"] = inference_store
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@ -90,6 +90,11 @@ class InferenceRouter(Inference):
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async def shutdown(self) -> None:
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logger.debug("InferenceRouter.shutdown")
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if self.store:
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try:
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await self.store.shutdown()
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except Exception as e:
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logger.warning(f"Error during InferenceStore shutdown: {e}")
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async def register_model(
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self,
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