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https://github.com/deepset-ai/haystack.git
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e447bd728a
* Adding the ability to call the Ray pipeline from concurrent apps with async This is to fix #2968 * Fixes: mype + pylint (`invalid-overridden-method`) * Simplifying - no real need for an `AsyncRayPipeline` anymore * Moving the new `run_async` method to the `RayPipeline` * Cleanup * [EMPTY] Re-trigger CI
99 lines
4.1 KiB
Python
99 lines
4.1 KiB
Python
from pathlib import Path
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import pytest
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import ray
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from haystack.pipelines import RayPipeline
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from ..conftest import SAMPLES_PATH
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@pytest.fixture(autouse=True)
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def shutdown_ray():
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yield
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try:
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import ray
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ray.serve.shutdown()
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ray.shutdown()
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except:
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pass
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@pytest.mark.integration
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@pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
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@pytest.mark.parametrize("serve_detached", [True, False])
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def test_load_pipeline(document_store_with_docs, serve_detached):
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pipeline = RayPipeline.load_from_yaml(
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SAMPLES_PATH / "pipeline" / "ray.simple.haystack-pipeline.yml",
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pipeline_name="ray_query_pipeline",
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ray_args={"num_cpus": 8},
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serve_args={"detached": serve_detached},
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)
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prediction = pipeline.run(
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query="Who lives in Berlin?", params={"ESRetriever": {"top_k": 10}, "Reader": {"top_k": 3}}
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)
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assert pipeline._serve_controller_client._detached == serve_detached
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assert ray.serve.get_deployment(name="ESRetriever").num_replicas == 2
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assert ray.serve.get_deployment(name="Reader").num_replicas == 1
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assert ray.serve.get_deployment(name="ESRetriever").max_concurrent_queries == 17
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assert ray.serve.get_deployment(name="ESRetriever").ray_actor_options["num_cpus"] == 0.5
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assert prediction["query"] == "Who lives in Berlin?"
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assert prediction["answers"][0].answer == "Carla"
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@pytest.mark.integration
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@pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
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def test_load_advanced_pipeline(document_store_with_docs):
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pipeline = RayPipeline.load_from_yaml(
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SAMPLES_PATH / "pipeline" / "ray.advanced.haystack-pipeline.yml",
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pipeline_name="ray_query_pipeline",
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ray_args={"num_cpus": 8},
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serve_args={"detached": True},
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)
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prediction = pipeline.run(
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query="Who lives in Berlin?",
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params={"ESRetriever1": {"top_k": 1}, "ESRetriever2": {"top_k": 2}, "Reader": {"top_k": 3}},
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)
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assert pipeline._serve_controller_client._detached is True
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assert ray.serve.get_deployment(name="ESRetriever1").num_replicas == 2
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assert ray.serve.get_deployment(name="ESRetriever2").num_replicas == 2
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assert ray.serve.get_deployment(name="Reader").num_replicas == 1
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assert ray.serve.get_deployment(name="ESRetriever1").max_concurrent_queries == 17
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assert ray.serve.get_deployment(name="ESRetriever2").max_concurrent_queries == 15
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assert ray.serve.get_deployment(name="ESRetriever1").ray_actor_options["num_cpus"] == 0.25
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assert ray.serve.get_deployment(name="ESRetriever2").ray_actor_options["num_cpus"] == 0.25
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assert prediction["query"] == "Who lives in Berlin?"
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assert prediction["answers"][0].answer == "Carla"
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assert len(prediction["answers"]) > 1
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@pytest.mark.asyncio
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@pytest.mark.integration
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@pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
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async def test_load_advanced_pipeline_async(document_store_with_docs):
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pipeline = RayPipeline.load_from_yaml(
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SAMPLES_PATH / "pipeline" / "ray.advanced.haystack-pipeline.yml",
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pipeline_name="ray_query_pipeline",
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ray_args={"num_cpus": 8},
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serve_args={"detached": True},
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)
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prediction = await pipeline.run_async(
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query="Who lives in Berlin?",
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params={"ESRetriever1": {"top_k": 1}, "ESRetriever2": {"top_k": 2}, "Reader": {"top_k": 3}},
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)
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assert pipeline._serve_controller_client._detached is True
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assert ray.serve.get_deployment(name="ESRetriever1").num_replicas == 2
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assert ray.serve.get_deployment(name="ESRetriever2").num_replicas == 2
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assert ray.serve.get_deployment(name="Reader").num_replicas == 1
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assert ray.serve.get_deployment(name="ESRetriever1").max_concurrent_queries == 17
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assert ray.serve.get_deployment(name="ESRetriever2").max_concurrent_queries == 15
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assert ray.serve.get_deployment(name="ESRetriever1").ray_actor_options["num_cpus"] == 0.25
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assert ray.serve.get_deployment(name="ESRetriever2").ray_actor_options["num_cpus"] == 0.25
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assert prediction["query"] == "Who lives in Berlin?"
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assert prediction["answers"][0].answer == "Carla"
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assert len(prediction["answers"]) > 1
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