41 lines
1.1 KiB
Python
41 lines
1.1 KiB
Python
# __basic_example_begin__
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from ray import serve
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from ray.serve.config import AutoscalingConfig, AutoscalingPolicy
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from ray.serve.schema import CeleryAdapterConfig, TaskProcessorConfig
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from ray.serve.task_consumer import task_consumer, task_handler
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processor_config = TaskProcessorConfig(
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queue_name="my_queue",
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adapter_config=CeleryAdapterConfig(
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broker_url="redis://localhost:6379/0",
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backend_url="redis://localhost:6379/1",
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),
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)
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@serve.deployment(
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max_ongoing_requests=5,
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autoscaling_config=AutoscalingConfig(
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min_replicas=1,
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max_replicas=10,
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target_ongoing_requests=2,
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policy=AutoscalingPolicy(
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policy_function="ray.serve.async_inference_autoscaling_policy:AsyncInferenceAutoscalingPolicy",
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policy_kwargs={
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"broker_url": "redis://localhost:6379/0",
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"queue_name": "my_queue",
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},
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),
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),
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)
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@task_consumer(task_processor_config=processor_config)
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class MyConsumer:
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@task_handler(name="process")
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def process(self, data):
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return f"processed: {data}"
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app = MyConsumer.bind()
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serve.run(app)
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# __basic_example_end__
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