From dec1868d09516ba3a2cbeaee78a70ac294f288c5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Cle=CC=81ment=20Doumouro?= Date: Fri, 27 Mar 2026 09:29:00 +0100 Subject: [PATCH 1/2] refactor(asr-worker): save transcriptions to artifact filesystem --- asr-worker/asr_worker/activities.py | 201 +- asr-worker/asr_worker/config.py | 16 + asr-worker/asr_worker/constants.py | 13 +- asr-worker/asr_worker/models.py | 79 +- asr-worker/asr_worker/workflow.py | 142 +- asr-worker/pyproject.toml | 29 +- asr-worker/tests/conftest.py | 21 + asr-worker/tests/test_activities.py | 36 + asr-worker/tests/test_workflows.py | 243 ++ asr-worker/uv.lock | 2999 ++++++++++------- .../datashare_python/constants.py | 2 + datashare-python/datashare_python/utils.py | 37 + datashare-python/datashare_python/worker.py | 27 +- datashare-python/uv.lock | 4 +- worker-template/tests/conftest.py | 89 +- worker-template/tests/test_workflows.py | 6 +- worker-template/uv.lock | 4 +- worker-template/worker_template/objects_.py | 7 +- worker-template/worker_template/workflows.py | 8 +- 19 files changed, 2584 insertions(+), 1379 deletions(-) create mode 100644 asr-worker/asr_worker/config.py create mode 100644 asr-worker/tests/conftest.py create mode 100644 asr-worker/tests/test_activities.py create mode 100644 asr-worker/tests/test_workflows.py diff --git a/asr-worker/asr_worker/activities.py b/asr-worker/asr_worker/activities.py index 838db38..6cb6507 100644 --- a/asr-worker/asr_worker/activities.py +++ b/asr-worker/asr_worker/activities.py @@ -1,59 +1,158 @@ -import torchaudio -from caul.configs.parakeet import ParakeetConfig -from caul.model_handlers.helpers import ParakeetModelHandlerResult -from caul.tasks.preprocessing.helpers import PreprocessedInput +import uuid +from pathlib import Path + +from caul.model_handlers.objects import ASRModelHandlerResult +from caul.tasks.preprocessing.objects import PreprocessedInput +from config import ASRWorkerConfig +from datashare_python.types_ import ProgressRateHandler +from datashare_python.utils import ( + ActivityWithProgress, + activity_defn, + debuggable_name, + read_artifact_metadata, + safe_dir, + to_raw_progress, + write_artifact_metadata, +) +from datashare_python.utils import artifacts_dir as get_artifacts_dir +from pydantic import TypeAdapter from temporalio import activity +from .constants import ( + POSTPROCESS_ACTIVITY, + PREPROCESS_ACTIVITY, + RUN_INFERENCE_ACTIVITY, + TRANSCRIPTION_JSON, + TRANSCRIPTION_METADATA_KEY, +) +from .models import Transcription + +_BASE_WEIGHT = 1.0 +_PREPROCESS_WEIGHT = 5 * _BASE_WEIGHT +_INFERENCE_WEIGHT = 10 * _PREPROCESS_WEIGHT + +_LIST_OF_PATH_ADAPTER = TypeAdapter(list[Path]) + -class ASRActivities: +class ASRActivities(ActivityWithProgress): """Contains activity definitions as well as reference to models""" - def __init__(self): - # TODO: Eventually this may include whisper, which will - # then require passing language_map - self.asr_handler = ParakeetConfig(return_tensors=False).handler_from_config() - - # load models - self.asr_handler.startup() - - @activity.defn(name="asr.transcription.preprocess") - async def preprocess(self, inputs: list[str]) -> list[list[PreprocessedInput]]: - """Preprocess transcription inputs - - :param inputs: list of file paths - :return: list of caul.tasks.preprocessing.helpers.PreprocessedInput - """ - return self.asr_handler.preprocessor.process(inputs) - - @activity.defn(name="asr.transcription.infer") - async def infer( - self, inputs: list[PreprocessedInput] - ) -> list[ParakeetModelHandlerResult]: - """Transcribe audio files. - - :param inputs: list of preprocessed inputs - :return: list of inference handler results - """ - # Load tensors - for item in inputs: - tensor, sample_rate = torchaudio.load(item.metadata.preprocessed_file_path) - # normalize - tensor = self.asr_handler.preprocessor.normalize(tensor, sample_rate) - # assign - item.tensor = tensor - - return self.asr_handler.inference_handler.process(inputs) - - @activity.defn(name="asr.transcription.postprocess") - async def postprocess( - self, inputs: list[ParakeetModelHandlerResult] - ) -> list[ParakeetModelHandlerResult]: - """Postprocess and reorder transcriptions - - :param inputs: list of inference handler results - :return: list of parakeet inference handler results - """ - return self.asr_handler.postprocessor.process(inputs) + @activity_defn(name=PREPROCESS_ACTIVITY, progress_weight=_PREPROCESS_WEIGHT) + def preprocess(self, paths: list[Path]) -> list[Path]: + # TODO: this shouldn't be necessary, fix this bug + paths = _LIST_OF_PATH_ADAPTER.validate_python(paths) + worker_config = ASRWorkerConfig() + audio_root = worker_config.audio_root + workdir = worker_config.workdir + # TODO: load from config passed at runtime with caching + preprocessor = self.asr_handler.preprocessor + # TODO: implement a caching strategy here, we could avoid processing files + # which have already been preprocessed + to_process = [str(audio_root / p) for p in paths] + batches = [] + # TODO: handle progress here + for batch in preprocessor.process(str(to_process), output_dir=workdir): + for preprocessed_input in batch: + uuid_name = uuid.uuid4().hex[:20] + segment_dir = safe_dir(uuid_name) + # TODO: find a more debuggable name for this + segment_path = workdir / segment_dir / f"{uuid_name}-preprocessed.json" + segment_path.parent.mkdir(parents=True, exist_ok=True) + preprocessed_input.model_dump_json(segment_path) + batches.append(segment_path.relative_to(workdir)) + return batches + + @activity_defn(name=RUN_INFERENCE_ACTIVITY, progress_weight=_INFERENCE_WEIGHT) + def infer( + self, + preprocessed_inputs: list[Path], + *, + progress: ProgressRateHandler | None = None, + ) -> list[Path]: + preprocessed_inputs = _LIST_OF_PATH_ADAPTER.validate_python(preprocessed_inputs) + worker_config = ASRWorkerConfig() + workdir = worker_config.workdir + # TODO: load from config passed at runtime with caching + inference_runner = self.asr_handler.inference_handler + # TODO: extract this into a function to improve testability + paths = [] + if progress is not None: + progress = to_raw_progress(progress, max_progress=len(preprocessed_inputs)) + abs_paths = [workdir / rel_path for rel_path in preprocessed_inputs] + audios = (PreprocessedInput.model_validate_json(f) for f in abs_paths) + for res_i, (path, asr_res) in enumerate( + zip(preprocessed_inputs, inference_runner.process(audios), strict=True) + ): + filename = f"{debuggable_name(path)}-transcript.json" + transcript_path = workdir / safe_dir(filename) / filename + transcript_path.parent.mkdir(parents=True, exist_ok=True) + transcript_path.write_text(asr_res.model_dump_json()) + paths.add(transcript_path.relative_to(workdir)) + if progress is not None: + self._event_loop.run_until_complete(progress(res_i)) + return paths + + @activity_defn(name=POSTPROCESS_ACTIVITY, progress_weight=_BASE_WEIGHT) + def postprocess( + self, + inference_results: list[Path], + input_paths: list[Path], + project: str, + *, + progress: ProgressRateHandler | None = None, + ) -> None: + inference_results = _LIST_OF_PATH_ADAPTER.validate_python(inference_results) + input_paths = _LIST_OF_PATH_ADAPTER.validate_python(input_paths) + worker_config = ASRWorkerConfig() + artifacts_root = worker_config.artifact_root + # TODO: load from config passed at runtime with caching + post_processor = self.asr_handler.postprocess + if progress is not None: + progress = to_raw_progress(progress, max_progress=len(input_paths)) + with post_processor: + transcriptions = post_processor.process(inference_results) + # Strict is important here ! + for i, (original, asr_result) in enumerate( + zip(input_paths, transcriptions, strict=True) + ): + transcription_path = write_transcription( + asr_result, + original.name, + artifacts_root=artifacts_root, + project=project, + ) + activity.logger.debug("wrote transcription for %s", transcription_path) + if progress is not None: + self._event_loop.run_until_complete(progress(i)) + + +def write_transcription( + asr_result: ASRModelHandlerResult, + transcribed_filename: str, + *, + artifacts_root: Path, + project: str, +) -> Path: + result = Transcription.from_asr_handler_result(asr_result) + artifact_dir = artifacts_root / get_artifacts_dir( + project, filename=transcribed_filename + ) + artifact_dir.mkdir(exist_ok=True, parents=True) + # TODO: if transcriptions are too large we could also serialize them + # as jsonl + transcription_path = artifact_dir / TRANSCRIPTION_JSON + transcription_path.write_text(result.model_dump_json()) + try: + meta = read_artifact_metadata( + artifacts_root, project, filename=transcribed_filename + ) + except FileNotFoundError: + meta = dict() + meta[TRANSCRIPTION_METADATA_KEY] = transcription_path.name + write_artifact_metadata( + meta, artifacts_root, project=project, filename=transcribed_filename + ) + return transcription_path REGISTRY = [ASRActivities.preprocess, ASRActivities.infer, ASRActivities.postprocess] diff --git a/asr-worker/asr_worker/config.py b/asr-worker/asr_worker/config.py new file mode 100644 index 0000000..722b8f9 --- /dev/null +++ b/asr-worker/asr_worker/config.py @@ -0,0 +1,16 @@ +from pathlib import Path +from typing import ClassVar + +import datashare_python +from datashare_python.config import WorkerConfig +from pydantic import Field + +_ALL_LOGGERS = [datashare_python.__name__, __name__, "__main__"] + + +class ASRWorkerConfig(WorkerConfig): + loggers: ClassVar[list[str]] = Field(_ALL_LOGGERS, frozen=True) + + audio_root: Path + artifact_root: Path + workdir: Path diff --git a/asr-worker/asr_worker/constants.py b/asr-worker/asr_worker/constants.py index e801bfa..568cfca 100644 --- a/asr-worker/asr_worker/constants.py +++ b/asr-worker/asr_worker/constants.py @@ -1,8 +1,8 @@ ASR_WORKER_NAME = "asr-worker" -_ONE_MINUTE = 60 +ONE_MINUTE = 60 -_TEN_MINUTES = _ONE_MINUTE * 10 +TEN_MINUTES = ONE_MINUTE * 10 ASR_TASK_QUEUE = "transcription-tasks" @@ -13,3 +13,12 @@ RESPONSE_SUCCESS = "success" RESPONSE_ERROR = "error" + +TRANSCRIPTION_JSON = "transcription.json" +TRANSCRIPTION_METADATA_KEY = "transcription" + +ASR_WORKFLOW = "asr.transcription" +GET_CONFIG_ACTIVITY = "asr.transcription.config" +PREPROCESS_ACTIVITY = "asr.transcription.preprocess" +RUN_INFERENCE_ACTIVITY = "asr.transcription.infer" +POSTPROCESS_ACTIVITY = "asr.transcription.postprocess" diff --git a/asr-worker/asr_worker/models.py b/asr-worker/asr_worker/models.py index f878d3d..842b2a8 100644 --- a/asr-worker/asr_worker/models.py +++ b/asr-worker/asr_worker/models.py @@ -1,54 +1,73 @@ -from dataclasses import dataclass, field, asdict -from typing import Optional +from pathlib import Path +from typing import Self -from asr_worker.constants import PARAKEET +from caul.model_handlers.objects import ASRModelHandlerResult +from datashare_python.objects import DatashareModel +from pydantic import Field +from .constants import PARAKEET -@dataclass -class BatchSize: + +class _WithBatchSize(DatashareModel): """Batch size helper""" batch_size: int = 32 -@dataclass -class PreprocessingConfig(BatchSize): +# TODO: ideally these should be caul objects from which can directly init components +# using from_config +class PreprocessingConfig(DatashareModel): """Preprocessing config""" -@dataclass -class InferenceConfig(BatchSize): +class InferenceConfig(DatashareModel): """Inference config""" model_name: str = PARAKEET -@dataclass -class ASRPipelineConfig: - """ASR pipeline config""" +class ASRPipelineConfig(DatashareModel): + batch_size: int = 32 + preprocessing: PreprocessingConfig = Field(default_factory=PreprocessingConfig) + inference: InferenceConfig = Field(default_factory=InferenceConfig) + + +class ASRInputs(DatashareModel): + project: str + paths: list[Path] + config: ASRPipelineConfig + + +class ASRResponse(DatashareModel): + n_transcribed: int - preprocessing: PreprocessingConfig = field(default_factory=PreprocessingConfig) - inference: InferenceConfig = field(default_factory=InferenceConfig) - def serialize(self): - return { - "preprocessing": asdict(self.preprocessing), - "inference": asdict(self.inference), - } +class Timestamp(DatashareModel): + start_s: float + end_s: float + @classmethod + def from_floats(cls, start_s: float, end_s: float) -> Self: + return Timestamp(start_s=start_s, end_s=end_s) -@dataclass -class ASRInputs: - """Inputs to ASR workflow""" - file_paths: list[str] - pipeline: ASRPipelineConfig +class Transcript(DatashareModel): + text: str + timestamp: Timestamp | None = None + speaker: str | None = None -@dataclass -class ASRResponse: - """ASR workflow response""" +class Transcription(DatashareModel): + transcripts: list[Transcript] = Field(default_factory=list) + # TODO: add validation [0, 1] + confidence: float - status: str - transcriptions: list[dict] = field(default_factory=list) - error: Optional[str] = None + @classmethod + def from_asr_handler_result(cls, asr_handler_result: ASRModelHandlerResult) -> Self: + transcripts = [ + Transcript(text=text, timestamp=Timestamp(start_s=start_s, end_s=end_s)) + for start_s, end_s, text in asr_handler_result.transcription + ] + return Transcription( + confidence=asr_handler_result.score, transcripts=transcripts + ) diff --git a/asr-worker/asr_worker/workflow.py b/asr-worker/asr_worker/workflow.py index 55da800..6052564 100644 --- a/asr-worker/asr_worker/workflow.py +++ b/asr-worker/asr_worker/workflow.py @@ -1,26 +1,30 @@ from asyncio import gather -from dataclasses import asdict from datetime import timedelta +from enum import StrEnum +from itertools import repeat -from more_itertools import flatten +from datashare_python.utils import WorkflowWithProgress +from pydantic import TypeAdapter from temporalio import workflow -from asr_worker.constants import _TEN_MINUTES, RESPONSE_ERROR, RESPONSE_SUCCESS +from asr_worker.constants import ASR_WORKFLOW, TEN_MINUTES from asr_worker.models import ASRInputs, ASRResponse with workflow.unsafe.imports_passed_through(): from asr_worker.activities import ASRActivities +_ASR_INPUTS_TYPE_ADAPTER = TypeAdapter(ASRInputs) -# TODO: Figure out which modules are violating sandbox restrictions -# and grant a limited passthrough -@workflow.defn(name="asr.transcription", sandboxed=False) -class ASRWorkflow: - """ASR workflow definition""" - def __init__(self): - pass +class TaskQueues(StrEnum): + IO = "asr.preprocessing.io" + CPU = "asr.processing.cpu" + INFERENCE_GPU = "asr.inference.gpu" + INFERENCE_CPU = "asr.inference.cpu" + +@workflow.defn(name=ASR_WORKFLOW) # noqa: F821 +class ASRWorkflow(WorkflowWithProgress): @workflow.run async def run(self, inputs: ASRInputs) -> ASRResponse: """Run ASR workflow @@ -28,76 +32,58 @@ async def run(self, inputs: ASRInputs) -> ASRResponse: :param inputs: ASRInputs :return: ASRResponse """ - try: - # Preprocessing - preprocessed_batches = await gather( - *[ - workflow.execute_activity_method( - ASRActivities.preprocess, - inputs.file_paths[ - offset : offset + inputs.pipeline.preprocessing.batch_size - ], - start_to_close_timeout=timedelta(seconds=_TEN_MINUTES), - ) - for offset in range( - 0, - len(inputs.file_paths), - inputs.pipeline.preprocessing.batch_size, - ) - ] + # We can't get the config from the env since it's non-deterministic, + # it has to be an activity + # Preprocessing + logger = workflow.logger + batch_size = inputs.config.batch_size + batched_input_paths = [ + inputs.paths[batch_start : batch_start + batch_size] + for batch_start in range(0, len(inputs.paths), batch_size) + ] + preprocessing_acts = ( + workflow.execute_activity( + ASRActivities.preprocess, + paths, + start_to_close_timeout=timedelta(seconds=TEN_MINUTES), + task_queue=TaskQueues.CPU, ) - - workflow.logger.info("Preprocessing complete") - - # Inference - inference_results = [ - await gather( - *[ - workflow.execute_activity_method( - ASRActivities.infer, - inner_batch, - start_to_close_timeout=timedelta(seconds=_TEN_MINUTES), - ) - for inner_batch in outer_batch - ] - ) - for outer_batch in preprocessed_batches - ] - - workflow.logger.info("Inference complete") - - # Postprocessing - transcriptions = await gather( - *[ - workflow.execute_activity_method( - ASRActivities.postprocess, - flatten(inference_result_batch), - start_to_close_timeout=timedelta(seconds=_TEN_MINUTES), - ) - for inference_result_batch in inference_results - ] + for paths in batched_input_paths + ) + logger.info("preprocessing files...") + preprocessed_batches = await gather(*preprocessing_acts) + logger.info("preprocessing complete !") + # Inference + inference_acts = [ + workflow.execute_activity( + ASRActivities.infer, + b, + # TODO: in practice we should parse the config to find out + task_queue=TaskQueues.INFERENCE_CPU, + start_to_close_timeout=timedelta(seconds=TEN_MINUTES), ) - - serialized_transcriptions = [] - - # drop unnecessary fields, serialize - for transcription in flatten(transcriptions): - transcription = asdict(transcription) - - del transcription["input_ordering"] - - serialized_transcriptions.append(transcription) - - workflow.logger.info("Postprocessing complete") - - # TODO: Output formatting; do we want to keep PreprocessedInput metadata - # and remap results to it? - return ASRResponse( - status=RESPONSE_SUCCESS, transcriptions=serialized_transcriptions + for b in preprocessed_batches + ] + logger.info("running inference...") + inference_results = await gather(*inference_acts) + logger.info("inference complete !") + # Postprocessing + postprocessing_ins = zip( + inference_results, batched_input_paths, repeat(inputs.project), strict=False + ) + postprocessing_acts = [ + workflow.execute_activity( + ASRActivities.postprocess, + args=i, + start_to_close_timeout=timedelta(seconds=TEN_MINUTES), + task_queue=TaskQueues.CPU, ) - except ValueError as e: - workflow.logger.exception(e) - return ASRResponse(status=RESPONSE_ERROR, error=str(e)) + for i in postprocessing_ins + ] + logger.info("running postprocessing...") + await gather(*postprocessing_acts) + logger.info("postprocessing complete !") + return ASRResponse(n_transcribed=len(inputs.paths)) -WORKFLOWS = [ASRWorkflow] +REGISTRY = [ASRWorkflow] diff --git a/asr-worker/pyproject.toml b/asr-worker/pyproject.toml index b8c1c5c..9959326 100644 --- a/asr-worker/pyproject.toml +++ b/asr-worker/pyproject.toml @@ -21,15 +21,16 @@ authors = [ readme = "README.md" requires-python = ">=3.11.0, <3.14" dependencies = [ - "temporalio>=1.22.0", - "caul==0.1.5", + "caul~=0.1.6", + "kaldialign>=0.9.3", + "datashare-python~=0.2", + "ml-dtypes>=0.5", + "numpy==2.3.0", "pyarrow<21.0.0", + "temporalio>=1.22.0", "torchaudio>=2.10.0", "torch>=2.10.0", "torchcodec>=0.9.1", - "numpy==2.3.0", - "ml-dtypes>=0.5", - "kaldialign>=0.9.3", ] [project.entry-points."datashare.workflows"] workflows = "asr_worker.workflows:REGISTRY" @@ -37,6 +38,21 @@ workflows = "asr_worker.workflows:REGISTRY" [project.entry-points."datashare.activities"] activities = "asr_worker.activities:REGISTRY" +[dependency-groups] +dev = [ + "black>=26.1.0", + "nest-asyncio>=1.6.0", + "pre-commit>=4.5.1", + "psutil>=6.1.0", + "pylint~=3.1.0", + "pytest~=8.1", + "pytest-asyncio~=0.24", + "pytest-timeout==2.4.0", + "redis[hiredis]>=5.2.1", + "ruff==0.15.2", + "typing-extensions>=4.15.0", +] + [[tool.uv.index]] name = "pytorch-cpu" url = "https://download.pytorch.org/whl/cpu" @@ -52,6 +68,7 @@ torchaudio = [ torchcodec = [ { index = "pytorch-cpu" } ] +datashare-python = { path = "../datashare-python", editable = true } [tool.uv] package = true @@ -77,4 +94,4 @@ markers = [ log_cli = 1 log_cli_level = "DEBUG" log_file_format = "[%(levelname)s][%(asctime)s.%(msecs)03d][%(name)s]: %(message)s" -log_file_date_format = "%Y-%m-%d %H:%M:%S" \ No newline at end of file +log_file_date_format = "%Y-%m-%d %H:%M:%S" diff --git a/asr-worker/tests/conftest.py b/asr-worker/tests/conftest.py new file mode 100644 index 0000000..45a8aa2 --- /dev/null +++ b/asr-worker/tests/conftest.py @@ -0,0 +1,21 @@ +import os +from pathlib import Path + +import pytest +from asr_worker.config import ASRWorkerConfig +from datashare_python.conftest import ( # noqa: F401 + event_loop, + test_deps, + test_temporal_client_session, + test_worker_config, + worker_lifetime_deps, +) +from icij_common.test_utils import reset_env # noqa: F401 + + +@pytest.fixture +def mocked_worker_config_in_env(reset_env, tmp_path: Path) -> ASRWorkerConfig: # noqa: ANN001, F811 + os.environ["DS_WORKER_AUDIO_ROOT"] = str(tmp_path / "audios") + os.environ["DS_WORKER_ARTIFACT_ROOT"] = str(tmp_path / "artifacts") + os.environ["DS_WORKER_WORKDIR"] = str(tmp_path / "workdir") + return ASRWorkerConfig() diff --git a/asr-worker/tests/test_activities.py b/asr-worker/tests/test_activities.py new file mode 100644 index 0000000..9884df2 --- /dev/null +++ b/asr-worker/tests/test_activities.py @@ -0,0 +1,36 @@ +import json +from pathlib import Path + +from asr_worker.activities import write_transcription +from asr_worker.models import Timestamp, Transcript, Transcription +from caul.model_handlers.objects import ASRModelHandlerResult +from datashare_python.conftest import TEST_PROJECT + + +def test_write_transcription(tmpdir: Path) -> None: + # Given + asr_result = ASRModelHandlerResult(transcription=[(0.0, 1.0, "text")], score=0.5) + transcribed_filename = "0011someid" + artifacts_root = Path(tmpdir) + project = TEST_PROJECT + # When + write_transcription( + asr_result, transcribed_filename, artifacts_root=artifacts_root, project=project + ) + # Then + expected_artifact_dir = artifacts_root / project / "00" / "11" / "0011someid" + assert expected_artifact_dir.exists() + metadata_path = expected_artifact_dir / "metadata.json" + assert metadata_path.exists() + metadata = json.loads(metadata_path.read_text()) + assert metadata["transcription"] == "transcription.json" + transcription_path = expected_artifact_dir / metadata["transcription"] + assert transcription_path.exists() + transcription = Transcription.model_validate_json(transcription_path.read_text()) + expected_transcription = Transcription( + transcripts=[ + Transcript(text="text", timestamp=Timestamp(start_s=0.0, end_s=1.0)) + ], + confidence=0.5, + ) + assert transcription == expected_transcription diff --git a/asr-worker/tests/test_workflows.py b/asr-worker/tests/test_workflows.py new file mode 100644 index 0000000..cb68170 --- /dev/null +++ b/asr-worker/tests/test_workflows.py @@ -0,0 +1,243 @@ +import json +import uuid +from asyncio import AbstractEventLoop +from collections.abc import AsyncGenerator +from pathlib import Path + +import pytest +from asr_worker.activities import write_transcription +from asr_worker.config import ASRWorkerConfig +from asr_worker.constants import ( + POSTPROCESS_ACTIVITY, + PREPROCESS_ACTIVITY, + RUN_INFERENCE_ACTIVITY, +) +from asr_worker.models import ( + ASRInputs, + ASRPipelineConfig, + ASRResponse, + Timestamp, + Transcript, + Transcription, +) +from asr_worker.workflow import ASRWorkflow, TaskQueues +from caul.model_handlers.objects import ASRModelHandlerResult +from caul.tasks.preprocessing.objects import InputMetadata, PreprocessedInput +from datashare_python.types_ import ProgressRateHandler, TemporalClient +from datashare_python.utils import ActivityWithProgress, activity_defn +from datashare_python.worker import datashare_worker +from dist.datashare_python.conftest import TEST_PROJECT +from pydantic import TypeAdapter +from temporalio import activity +from temporalio.worker import Worker + +_LIST_OF_PATH_ADAPTER = TypeAdapter(list[Path]) + +_MODEL_RESULT_0 = ASRModelHandlerResult( + transcription=[(0.0, 2.0, "segment zero")], score=0.5 +) +_MODEL_RESULT_1 = ASRModelHandlerResult( + transcription=[(0.0, 1.0, "segment one")], score=0.5 +) + + +_MODEL_RESULTS = [_MODEL_RESULT_0, _MODEL_RESULT_1] +_TRANSCRIPTIONS = [Transcription.from_asr_handler_result(res) for res in _MODEL_RESULTS] + + +class MockedASRActivities(ActivityWithProgress): + @activity_defn(name=PREPROCESS_ACTIVITY) + def preprocess(self, paths: list[Path]) -> list[Path]: + # TODO: this shouldn't be necessary, fix this bug + paths = _LIST_OF_PATH_ADAPTER.validate_python(paths) + workdir = ASRWorkerConfig().workdir + workdir.mkdir(parents=True, exist_ok=True) + batches = [] + for path_i, path in enumerate(paths): + n_segments = len(path.name) + for part_i in range(n_segments): + seg_path = f"file_{path_i}_part_{part_i}.wav" + metadata = InputMetadata( + duration=1, + input_ordering=path_i, + preprocessed_file_path=str(seg_path), + ) + preprocessed_input = PreprocessedInput(metadata=metadata) + (workdir / seg_path).write_text(preprocessed_input.model_dump_json()) + batches.append(seg_path) + return batches + + @activity_defn(name=RUN_INFERENCE_ACTIVITY) + def infer( + self, + preprocessed_inputs: list[Path], + *, + progress: ProgressRateHandler | None = None, + ) -> list[Path]: # noqa: ANN001, ARG001 + # TODO: this shouldn't be necessary, fix this bug + preprocessed_inputs = _LIST_OF_PATH_ADAPTER.validate_python(preprocessed_inputs) + workdir = ASRWorkerConfig().workdir + paths = [] + preprocessed_inputs = [ + PreprocessedInput.model_validate_json((workdir / p).read_text()) + for p in preprocessed_inputs + ] + for preprocessed_i, i in enumerate(preprocessed_inputs): + res = _MODEL_RESULTS[preprocessed_i % len(_MODEL_RESULTS)] + res = ASRModelHandlerResult( + input_ordering=i.metadata.input_ordering, + transcription=res.transcription, + score=res.score, + ) + filename = f"{uuid.uuid4().hex[:20]}-transcript.json" + (workdir / filename).write_text(res.model_dump_json()) + paths.append(filename) + return paths + + @activity.defn(name=POSTPROCESS_ACTIVITY) + def postprocess( + self, + inference_results: list[Path], + input_paths: list[Path], + project: str, + progress: ProgressRateHandler | None = None, + ) -> None: + # TODO: this shouldn't be necessary, fix this bug + inference_results = _LIST_OF_PATH_ADAPTER.validate_python(inference_results) + input_paths = _LIST_OF_PATH_ADAPTER.validate_python(input_paths) + config = ASRWorkerConfig() + artifact_root = config.artifact_root + workdir = config.workdir + artifact_root.mkdir(parents=True, exist_ok=True) + inference_results = [ + ASRModelHandlerResult.model_validate_json((workdir / f).read_text()) + for f in inference_results + ] + current_res = None + asr_results, transcription, scores = [], [], [] + for res in inference_results: + if res.input_ordering != current_res and current_res is not None: + score = (sum(scores) / len(scores)) if scores else 0 + asr_results.append( + ASRModelHandlerResult( + transcription=sum(transcription, []), score=score + ) + ) + asr_results, transcription, scores = [], [], [] + current_res = res.input_ordering + transcription.append(res.transcription) + scores.append(res.score) + asr_results.append( + ASRModelHandlerResult( + transcription=sum(transcription, []), score=sum(scores) / len(scores) + ) + ) + for original, asr_result in zip(input_paths, asr_results, strict=True): + write_transcription( + asr_result, original.name, artifacts_root=artifact_root, project=project + ) + + +@pytest.fixture +async def io_bound_worker( + test_temporal_client_session: TemporalClient, # noqa: F811 +) -> AsyncGenerator[Worker, None]: + client = test_temporal_client_session + worker = datashare_worker(client, task_queue=TaskQueues.IO, workflows=[ASRWorkflow]) + async with worker: + yield worker + + +@pytest.fixture +async def cpu_bound_worker( + test_temporal_client_session: TemporalClient, + event_loop: AbstractEventLoop, # noqa: F811 +) -> AsyncGenerator[Worker, None]: + client = test_temporal_client_session + activities = MockedASRActivities(client, event_loop) + worker = datashare_worker( + client, + task_queue=TaskQueues.CPU, + activities=[activities.preprocess, activities.postprocess], + ) + async with worker: + yield worker + + +@pytest.fixture +async def cpu_inference_worker( + test_temporal_client_session: TemporalClient, + event_loop: AbstractEventLoop, # noqa: F811 +) -> AsyncGenerator[Worker, None]: + client = test_temporal_client_session + activities = MockedASRActivities(client, event_loop) + worker = datashare_worker( + client, task_queue=TaskQueues.INFERENCE_CPU, activities=[activities.infer] + ) + async with worker: + yield worker + + +_EXPECTED_TRANSCRIPTION_0 = Transcription( + transcripts=[ + Transcript(text="segment zero", timestamp=Timestamp(start_s=0.0, end_s=2.0)), + Transcript(text="segment one", timestamp=Timestamp(start_s=0.0, end_s=1.0)), + Transcript(text="segment zero", timestamp=Timestamp(start_s=0.0, end_s=2.0)), + Transcript(text="segment one", timestamp=Timestamp(start_s=0.0, end_s=1.0)), + ], + confidence=0.5, +) +_EXPECTED_TRANSCRIPTION_1 = Transcription( + transcripts=[ + Transcript(text="segment zero", timestamp=Timestamp(start_s=0.0, end_s=2.0)), + Transcript(text="segment one", timestamp=Timestamp(start_s=0.0, end_s=1.0)), + ], + confidence=0.5, +) + + +async def test_asr_workflow( + test_temporal_client_session: TemporalClient, + cpu_bound_worker: Worker, # noqa: ARG001 + cpu_inference_worker: Worker, # noqa: ARG001 + io_bound_worker: Worker, # noqa: ARG001 + mocked_worker_config_in_env: ASRWorkerConfig, +) -> None: + # Given + worker_config = mocked_worker_config_in_env + client = test_temporal_client_session + path = [Path("aabb"), Path("cc")] + batch_size = 1 + config = ASRPipelineConfig(batch_size=batch_size) + workflow_id = f"asr-{uuid.uuid4().hex}" + project = TEST_PROJECT + inputs = ASRInputs(project=project, paths=path, config=config) + # When + result = await client.execute_workflow( + ASRWorkflow.run, inputs, id=workflow_id, task_queue=TaskQueues.IO + ) + # Then + expected_response = ASRResponse(n_transcribed=2) + assert result == expected_response + artifacts_dir = worker_config.artifact_root + expected_transcription_dirs = [ + artifacts_dir / project / "aa" / "bb" / "aabb", + artifacts_dir / project / "cc" / "cc", + ] + expected_transcriptions = [_EXPECTED_TRANSCRIPTION_0, _EXPECTED_TRANSCRIPTION_1] + for expected_t, d in zip( + expected_transcriptions, expected_transcription_dirs, strict=True + ): + assert d.exists() + assert d.is_dir() + meta_path = d / "metadata.json" + assert meta_path.exists() + meta = json.loads(meta_path.read_text()) + transcription_name = meta.get("transcription") + assert transcription_name is not None + transcription_path = d / transcription_name + assert transcription_path.exists() + transcription = Transcription.model_validate_json( + transcription_path.read_text() + ) + assert transcription == expected_t diff --git a/asr-worker/uv.lock b/asr-worker/uv.lock index 91ef2c6..8cc59a3 100644 --- a/asr-worker/uv.lock +++ b/asr-worker/uv.lock @@ -2,20 +2,32 @@ version = 1 revision = 3 requires-python = ">=3.11.0, <3.14" resolution-markers = [ - "python_full_version >= '3.13' and sys_platform == 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8909092..0efca13 100644 --- a/datashare-python/datashare_python/constants.py +++ b/datashare-python/datashare_python/constants.py @@ -12,3 +12,5 @@ DEFAULT_DS_ADDRESS = "http://localhost:8080" DEFAULT_NAMESPACE = "datashare-default" + +METADATA_JSON = "metadata.json" diff --git a/datashare-python/datashare_python/utils.py b/datashare-python/datashare_python/utils.py index 312267b..fb00fbb 100644 --- a/datashare-python/datashare_python/utils.py +++ b/datashare-python/datashare_python/utils.py @@ -1,11 +1,14 @@ import asyncio import inspect +import json import logging import sys from collections.abc import Callable, Coroutine from dataclasses import dataclass from functools import partial, wraps +from hashlib import sha256 from inspect import signature +from pathlib import Path from typing import ParamSpec, TypeVar import nest_asyncio @@ -23,6 +26,7 @@ from temporalio.common import SearchAttributeKey from temporalio.exceptions import ApplicationError +from .constants import METADATA_JSON from .types_ import ProgressRateHandler, RawProgressHandler DependencyLabel = str | None @@ -370,3 +374,36 @@ def _handlers( handler.addFilter(worker_id_filter) handler.setLevel(log_level) return handlers + + +def safe_dir(filename: str) -> Path: + parts = (p for p in (filename[:2], filename[2:4]) if p) + return Path(*parts) + + +def artifacts_dir(project: str, *, filename: str) -> Path: + return Path(project, safe_dir(filename), filename) + + +def metadata_path(filename: str, *, project: str) -> Path: + metadata_path = artifacts_dir(project, filename=filename) / METADATA_JSON + return metadata_path + + +def read_artifact_metadata(root: Path, project: str, *, filename: str) -> dict: + m_path = root / metadata_path(filename, project=project) + return json.loads(m_path.read_text()) + + +def write_artifact_metadata( + metadata: dict, root: Path, project: str, *, filename: str +) -> None: + m_path = root / artifacts_dir(project, filename=filename) / METADATA_JSON + m_path.parent.mkdir(parents=True, exist_ok=True) + m_path.write_text(json.dumps(metadata)) + + +def debuggable_name(path: Path, component_size_limit: int = 10) -> str: + displayable_file_name = [c[:component_size_limit] for c in path.parts] + uuid = sha256(str(path).encode()).hexdigest()[:20] + return f"{uuid}-{'__'.join(displayable_file_name)}" diff --git a/datashare-python/datashare_python/worker.py b/datashare-python/datashare_python/worker.py index 9a521a8..e6be7c8 100644 --- a/datashare-python/datashare_python/worker.py +++ b/datashare-python/datashare_python/worker.py @@ -37,24 +37,24 @@ def datashare_worker( # Scale horizontally be default for activities, each worker processes one activity # at a time max_concurrent_activities: int = 1, + worker_id: str | None = None, ) -> Worker: if workflows is None: workflows = [] if activities is None: activities = [] - are_async = [a.__temporal_activity_definition.is_async for a in activities] - if all(not a for a in are_async): - activity_executor = ThreadPoolExecutor( - thread_name_prefix=_ACTIVITY_THREAD_NAME_PREFIX - ) - elif all(are_async): - activity_executor = None # Use temporal default - else: - activity_executor = ThreadPoolExecutor( - thread_name_prefix=_ACTIVITY_THREAD_NAME_PREFIX - ) - logger.warning(_SEPARATE_IO_AND_CPU_ACTIVITIES) - + activity_executor = None # Use temporal default + if activities: + are_async = [a.__temporal_activity_definition.is_async for a in activities] + if all(not a for a in are_async): + activity_executor = ThreadPoolExecutor( + thread_name_prefix=_ACTIVITY_THREAD_NAME_PREFIX + ) + else: + activity_executor = ThreadPoolExecutor( + thread_name_prefix=_ACTIVITY_THREAD_NAME_PREFIX + ) + logger.warning(_SEPARATE_IO_AND_CPU_ACTIVITIES) if isinstance(activity_executor, ThreadPoolExecutor) and workflows: logger.warning(_SEPARATE_IO_AND_CPU_WORKERS) @@ -71,4 +71,5 @@ def datashare_worker( # Workflow tasks are assumed to be very lightweight and fast we can reserve # several of them workflow_task_poller_behavior=PollerBehaviorSimpleMaximum(5), + identity=worker_id, ) diff --git a/datashare-python/uv.lock b/datashare-python/uv.lock index 5610748..aee7023 100644 --- a/datashare-python/uv.lock +++ b/datashare-python/uv.lock @@ -304,7 +304,7 @@ wheels = [ [[package]] name = "datashare-python" -version = "0.2.12" +version = "0.2.23" source = { editable = "." } dependencies = [ { name = "aiohttp" }, @@ -365,7 +365,7 @@ dev = [ [[package]] name = "datashare-worker-template" -version = "0.1.2" +version = "0.1.5" source = { editable = "../worker-template" } dependencies = [ { name = "datashare-python" }, diff --git a/worker-template/tests/conftest.py b/worker-template/tests/conftest.py index 1e5ff58..25fdedd 100644 --- a/worker-template/tests/conftest.py +++ b/worker-template/tests/conftest.py @@ -2,7 +2,6 @@ import uuid from asyncio import AbstractEventLoop from collections.abc import AsyncGenerator -from concurrent.futures import ThreadPoolExecutor from typing import Any import pytest @@ -33,9 +32,9 @@ with_dependencies, ) from datashare_python.types_ import ContextManagerFactory +from datashare_python.worker import datashare_worker from icij_common.es import ESClient from temporalio.client import Client as TemporalClient -from temporalio.testing import ActivityEnvironment from temporalio.worker import Worker from worker_template.activities import ( ClassifyDocs, @@ -84,18 +83,19 @@ async def io_worker( test_es_client_session: ESClient, # noqa: F811 test_temporal_client_session: TemporalClient, # noqa: F811 event_loop: asyncio.AbstractEventLoop, # noqa: F811 -) -> AsyncGenerator[None, None]: +) -> AsyncGenerator[Worker, None]: es_client = test_es_client_session temporal_client = test_temporal_client_session worker_id = f"test-io-worker-{uuid.uuid4()}" pong_activity = Pong(temporal_client=temporal_client, event_loop=event_loop) + activities = CreateTranslationBatches( + es_client=es_client, + temporal_client=temporal_client, + event_loop=event_loop, + ) io_activities = [ pong_activity.pong, - CreateTranslationBatches( - es_client=es_client, - temporal_client=temporal_client, - event_loop=event_loop, - ).create_translation_batches, + activities.create_translation_batches, CreateClassificationBatches( es_client=es_client, temporal_client=temporal_client, @@ -103,21 +103,15 @@ async def io_worker( ).create_classification_batches, ] workflows = [PingWorkflow, TranslateAndClassifyWorkflow] - worker = Worker( + worker = datashare_worker( temporal_client, - identity=worker_id, - task_queue=TaskQueues.CPU, - activities=io_activities, + task_queue=TaskQueues.IO, workflows=workflows, + activities=io_activities, + worker_id=worker_id, ) async with worker: - t = None - try: - t = asyncio.create_task(worker.run()) - yield - except Exception: # noqa: BLE001 - if t is not None: - t.cancel() + yield worker @pytest.fixture(scope="session") @@ -125,7 +119,7 @@ async def translation_worker( test_es_client_session: ESClient, # noqa: F811 test_temporal_client_session: TemporalClient, # noqa: F811 event_loop: asyncio.AbstractEventLoop, # noqa: F811 -) -> AsyncGenerator[None, None]: +) -> AsyncGenerator[Worker, None]: es_client = test_es_client_session temporal_client = test_temporal_client_session worker_id = f"test-translation-worker-{uuid.uuid4()}" @@ -136,22 +130,14 @@ async def translation_worker( event_loop=event_loop, ).translate_docs, ] - with ThreadPoolExecutor() as executor: - worker = Worker( - temporal_client, - identity=worker_id, - task_queue=TaskQueues.TRANSLATE_GPU, - activities=translation_activities, - activity_executor=executor, - ) - async with worker: - t = None - try: - t = asyncio.create_task(worker.run()) - yield - except Exception: # noqa: BLE001 - if t is not None: - t.cancel() + worker = datashare_worker( + temporal_client, + worker_id=worker_id, + task_queue=TaskQueues.TRANSLATE_GPU, + activities=translation_activities, + ) + async with worker: + yield worker @pytest.fixture(scope="session") @@ -159,7 +145,7 @@ async def classification_worker( test_es_client_session: ESClient, # noqa: F811 test_temporal_client_session: TemporalClient, # noqa: F811 event_loop: asyncio.AbstractEventLoop, # noqa: F811 -) -> AsyncGenerator[None, None]: +) -> AsyncGenerator[Worker, None]: es_client = test_es_client_session temporal_client = test_temporal_client_session worker_id = f"test-classification-worker-{uuid.uuid4()}" @@ -170,24 +156,11 @@ async def classification_worker( event_loop=event_loop, ).classify_docs, ] - with ThreadPoolExecutor() as executor: - worker = Worker( - temporal_client, - identity=worker_id, - task_queue=TaskQueues.CLASSIFY_GPU, - activities=classification_activities, - activity_executor=executor, - ) - async with worker: - t = None - try: - t = asyncio.create_task(worker.run()) - yield - except Exception: # noqa: BLE001 - if t is not None: - t.cancel() - - -@pytest.fixture(scope="session") -def activity_environment() -> ActivityEnvironment: - return ActivityEnvironment() + worker = datashare_worker( + temporal_client, + worker_id=worker_id, + task_queue=TaskQueues.CLASSIFY_GPU, + activities=classification_activities, + ) + async with worker: + yield worker diff --git a/worker-template/tests/test_workflows.py b/worker-template/tests/test_workflows.py index 2f43aae..379e21d 100644 --- a/worker-template/tests/test_workflows.py +++ b/worker-template/tests/test_workflows.py @@ -35,7 +35,7 @@ async def test_ping_workflow_e2e( PingWorkflow, args, id=wf_id, - task_queue=TaskQueues.CPU, + task_queue=TaskQueues.IO, request_eager_start=True, ) @@ -49,7 +49,7 @@ async def test_ping_e2e( test_task_client: DatashareTaskClient, ) -> None: # Given - task_group = TaskQueues.CPU + task_group = TaskQueues.IO # When ping_task_id = await test_task_client.create_task("ping", dict(), group=task_group) # Then @@ -89,7 +89,7 @@ async def test_translate_and_classify_workflow_e2e( TranslateAndClassifyWorkflow.run, payload, id=wf_id, - task_queue=TaskQueues.CPU, + task_queue=TaskQueues.IO, ) # Then diff --git a/worker-template/uv.lock b/worker-template/uv.lock index 0c1c2b1..f328b0d 100644 --- a/worker-template/uv.lock +++ b/worker-template/uv.lock @@ -316,7 +316,7 @@ wheels = [ [[package]] name = "datashare-python" -version = "0.2.20" +version = "0.2.23" source = { editable = "../datashare-python" } dependencies = [ { name = "aiohttp" }, @@ -363,7 +363,7 @@ dev = [ [[package]] name = "datashare-worker-template" -version = "0.1.3" +version = "0.1.5" source = { editable = "." } dependencies = [ { name = "datashare-python" }, diff --git a/worker-template/worker_template/objects_.py b/worker-template/worker_template/objects_.py index e2ddb12..1abea66 100644 --- a/worker-template/worker_template/objects_.py +++ b/worker-template/worker_template/objects_.py @@ -7,14 +7,13 @@ from pydantic import BaseModel, Field -class BasePayload(BaseModel): - model_config = icij_config() - - class LowerCamelCaseModel(BaseModel): model_config = merge_configs(icij_config(), lowercamel_case_config()) +class BasePayload(LowerCamelCaseModel): ... + + class ClassificationConfig(BasePayload): task: str = Field(default="text-classification", frozen=True) model: str = "distilbert/distilbert-base-uncased-finetuned-sst-2-english" diff --git a/worker-template/worker_template/workflows.py b/worker-template/worker_template/workflows.py index 289195c..f396620 100644 --- a/worker-template/worker_template/workflows.py +++ b/worker-template/worker_template/workflows.py @@ -20,7 +20,7 @@ class TaskQueues(StrEnum): - CPU = "cpu" + IO = "io" TRANSLATE_GPU = "translate-gpu" CLASSIFY_GPU = "classify-gpu" @@ -40,7 +40,7 @@ async def run( translation_batches = await workflow.execute_activity( CreateTranslationBatches.create_translation_batches, args=translation_batch_args, - task_queue=TaskQueues.CPU, + task_queue=TaskQueues.IO, start_to_close_timeout=timedelta(hours=1), ) # Translate @@ -68,7 +68,7 @@ async def run( clf_batches = await workflow.execute_activity( CreateClassificationBatches.create_classification_batches, args=clf_batch_args, - task_queue=TaskQueues.CPU, + task_queue=TaskQueues.IO, start_to_close_timeout=timedelta(days=1), ) # Classify @@ -98,7 +98,7 @@ class PingWorkflow(WorkflowWithProgress): async def run(self, arg: dict) -> str: # noqa: ARG002 return await workflow.execute_activity( Pong.pong, - task_queue=TaskQueues.CPU, + task_queue=TaskQueues.IO, start_to_close_timeout=timedelta(hours=1), ) From 2d206b22c4a7435c95643c59694a38951c60a59f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Cle=CC=81ment=20Doumouro?= Date: Fri, 27 Mar 2026 11:26:05 +0100 Subject: [PATCH 2/2] refactor(asr-worker): save transcriptions to artifact filesystem --- .github/actions/pylint/action.yml | 19 - .github/workflows/linting.yml | 9 +- .github/workflows/tests.yml | 37 +- asr-worker/asr_worker/activities.py | 134 +++-- asr-worker/asr_worker/config.py | 4 +- asr-worker/asr_worker/models.py | 8 +- asr-worker/asr_worker/worker.py | 44 -- .../asr_worker/{workflow.py => workflows.py} | 7 - asr-worker/tests/__init__.py | 5 + asr-worker/tests/conftest.py | 2 +- .../tests/e2e/asr/test_transcription.py | 48 -- .../tests/resources/audios}/asr_test.wav | Bin asr-worker/tests/test_workflows.py | 123 +++- datashare-python/datashare_python/template.py | 2 +- datashare-python/datashare_python/utils.py | 40 +- datashare-python/datashare_python/worker.py | 13 +- datashare-python/pyproject.toml | 2 +- datashare-python/tests/test_utils.py | 49 +- datashare-python/uv.lock | 543 +++++++++++++++++- 19 files changed, 863 insertions(+), 226 deletions(-) delete mode 100644 .github/actions/pylint/action.yml delete mode 100644 asr-worker/asr_worker/worker.py rename asr-worker/asr_worker/{workflow.py => workflows.py} (92%) create mode 100644 asr-worker/tests/__init__.py delete mode 100644 asr-worker/tests/e2e/asr/test_transcription.py rename {resources/files/asr => asr-worker/tests/resources/audios}/asr_test.wav (100%) diff --git a/.github/actions/pylint/action.yml b/.github/actions/pylint/action.yml deleted file mode 100644 index 80283bb..0000000 --- a/.github/actions/pylint/action.yml +++ /dev/null @@ -1,19 +0,0 @@ -inputs: - path: - description: 'Path where linting test will be executed' - required: true - -runs: - using: "composite" - steps: - - name: Install dependencies - shell: bash - run: | - python -m pip install --upgrade pip - pip install pylint==4.0.5 - - name: Run linting test on $ {{ inputs.path }} - shell: bash - run: | - pylint_rc=$(pwd)/qa/pylintrc - cd ${{ inputs.path }} - pylint --fail-under 9.49 --rcfile $pylint_rc --load-plugins=pylint.extensions.bad_builtin -r y -j 0 -f colorized **/*.py diff --git a/.github/workflows/linting.yml b/.github/workflows/linting.yml index 3f0d717..cdfc35d 100644 --- a/.github/workflows/linting.yml +++ b/.github/workflows/linting.yml @@ -53,10 +53,13 @@ jobs: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - - uses: ./.github/actions/pylint - name: "Lint ASR worker" + - uses: astral-sh/ruff-action@v3 with: - path: asr-worker + args: "--version" # skips test by displaying the version + - name: Check formatting + run: ruff format --config qa/ruff.toml --check asr-worker + - name: Lint test + run: ruff check --config qa/ruff.toml asr-worker concurrency: group: ${{ github.workflow }}-${{ github.ref }} diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 29d40a8..ae4c7d2 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -25,12 +25,6 @@ jobs: key: docker-${{ runner.os }}-${{ hashFiles('docker-compose.yml') }} - name: Start test services run: docker compose up -d datashare temporal-post-init elasticsearch - - name: test temporal setup - run: | - curl "https://temporal.download/cli/archive/latest?platform=linux&arch=amd64" --output temporal.tar.gz - tar xzvf temporal.tar.gz - sudo mv temporal /usr/local/bin - temporal operator namespace describe -n datashare-default --address localhost:7233 - name: Install uv uses: astral-sh/setup-uv@v7 with: @@ -41,7 +35,7 @@ jobs: - name: Run tests run: | cd datashare-python - uv sync --frozen --all-extras + uv sync --frozen --all-extras --dev uv run --frozen python -m pytest -vvv --cache-clear --show-capture=all -r A test-worker-template: @@ -68,7 +62,34 @@ jobs: - name: Run tests run: | cd worker-template - uv sync --frozen --all-extras + uv sync --frozen --all-extras --dev + uv run --frozen python -m pytest --timeout=180 -vvv --cache-clear --show-capture=all -r A + + test-asr-worker: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - name: Setup Python project + uses: actions/setup-python@v6 + with: + python-version: ${{ env.PYTHON_VERSION }} + - name: Cache Docker images + uses: ScribeMD/docker-cache@0.5.0 + with: + key: docker-${{ runner.os }}-${{ hashFiles('docker-compose.yml') }} + - name: Start test services + run: docker compose up -d datashare temporal-post-init elasticsearch + - name: Install uv + uses: astral-sh/setup-uv@v7 + with: + version: ${{ env.ASTRAL_VERSION }} + python-version: ${{ env.PYTHON_VERSION }} + enable-cache: true + working-directory: asr-worker + - name: Run tests + run: | + cd asr-worker + uv sync --frozen --all-extras --dev uv run --frozen python -m pytest --timeout=180 -vvv --cache-clear --show-capture=all -r A concurrency: diff --git a/asr-worker/asr_worker/activities.py b/asr-worker/asr_worker/activities.py index 6cb6507..561c68d 100644 --- a/asr-worker/asr_worker/activities.py +++ b/asr-worker/asr_worker/activities.py @@ -1,6 +1,10 @@ import uuid +from collections.abc import Generator +from contextlib import contextmanager from pathlib import Path +from caul.configs import ParakeetConfig +from caul.model_handlers.asr_model_handler import ASRModelHandler from caul.model_handlers.objects import ASRModelHandlerResult from caul.tasks.preprocessing.objects import PreprocessedInput from config import ASRWorkerConfig @@ -34,33 +38,49 @@ _LIST_OF_PATH_ADAPTER = TypeAdapter(list[Path]) +# TODO: update caul to provide context managers rather than load/shutdown +@contextmanager +def _handler(config: ParakeetConfig) -> Generator[ASRModelHandler, None, None]: + asr_handler = config.handler_from_config() + try: + asr_handler.startup() + yield asr_handler + finally: + asr_handler.shutdown() + + class ASRActivities(ActivityWithProgress): - """Contains activity definitions as well as reference to models""" + # TODO: pass this at runtime + _handler_config = ParakeetConfig(return_tensors=False) @activity_defn(name=PREPROCESS_ACTIVITY, progress_weight=_PREPROCESS_WEIGHT) def preprocess(self, paths: list[Path]) -> list[Path]: # TODO: this shouldn't be necessary, fix this bug paths = _LIST_OF_PATH_ADAPTER.validate_python(paths) worker_config = ASRWorkerConfig() - audio_root = worker_config.audio_root + audio_root = worker_config.audios_root workdir = worker_config.workdir # TODO: load from config passed at runtime with caching - preprocessor = self.asr_handler.preprocessor - # TODO: implement a caching strategy here, we could avoid processing files - # which have already been preprocessed - to_process = [str(audio_root / p) for p in paths] - batches = [] - # TODO: handle progress here - for batch in preprocessor.process(str(to_process), output_dir=workdir): - for preprocessed_input in batch: - uuid_name = uuid.uuid4().hex[:20] - segment_dir = safe_dir(uuid_name) - # TODO: find a more debuggable name for this - segment_path = workdir / segment_dir / f"{uuid_name}-preprocessed.json" - segment_path.parent.mkdir(parents=True, exist_ok=True) - preprocessed_input.model_dump_json(segment_path) - batches.append(segment_path.relative_to(workdir)) - return batches + # TODO: avoid loading the full handler we just need preprocessing + with _handler(self._handler_config) as asr_handler: + preprocessor = asr_handler.preprocessor + # TODO: implement a caching strategy here, we could avoid processing files + # which have already been preprocessed + to_process = [str(audio_root / p) for p in paths] + batches = [] + # TODO: handle progress here + for batch in preprocessor.process(str(to_process), output_dir=workdir): + for preprocessed_input in batch: + uuid_name = uuid.uuid4().hex[:20] + segment_dir = safe_dir(uuid_name) + # TODO: find a more debuggable name for this + segment_path = ( + workdir / segment_dir / f"{uuid_name}-preprocessed.json" + ) + segment_path.parent.mkdir(parents=True, exist_ok=True) + preprocessed_input.model_dump_json(segment_path) + batches.append(segment_path.relative_to(workdir)) + return batches @activity_defn(name=RUN_INFERENCE_ACTIVITY, progress_weight=_INFERENCE_WEIGHT) def infer( @@ -73,24 +93,28 @@ def infer( worker_config = ASRWorkerConfig() workdir = worker_config.workdir # TODO: load from config passed at runtime with caching - inference_runner = self.asr_handler.inference_handler - # TODO: extract this into a function to improve testability - paths = [] - if progress is not None: - progress = to_raw_progress(progress, max_progress=len(preprocessed_inputs)) - abs_paths = [workdir / rel_path for rel_path in preprocessed_inputs] - audios = (PreprocessedInput.model_validate_json(f) for f in abs_paths) - for res_i, (path, asr_res) in enumerate( - zip(preprocessed_inputs, inference_runner.process(audios), strict=True) - ): - filename = f"{debuggable_name(path)}-transcript.json" - transcript_path = workdir / safe_dir(filename) / filename - transcript_path.parent.mkdir(parents=True, exist_ok=True) - transcript_path.write_text(asr_res.model_dump_json()) - paths.add(transcript_path.relative_to(workdir)) + # TODO: avoid loading the full handler we just need inference + with _handler(self._handler_config) as asr_handler: + inference_runner = asr_handler.inference_handler + # TODO: extract this into a function to improve testability + paths = [] if progress is not None: - self._event_loop.run_until_complete(progress(res_i)) - return paths + progress = to_raw_progress( + progress, max_progress=len(preprocessed_inputs) + ) + abs_paths = [workdir / rel_path for rel_path in preprocessed_inputs] + audios = (PreprocessedInput.model_validate_json(f) for f in abs_paths) + for res_i, (path, asr_res) in enumerate( + zip(preprocessed_inputs, inference_runner.process(audios), strict=True) + ): + filename = f"{debuggable_name(path)}-transcript.json" + transcript_path = workdir / safe_dir(filename) / filename + transcript_path.parent.mkdir(parents=True, exist_ok=True) + transcript_path.write_text(asr_res.model_dump_json()) + paths.append(transcript_path.relative_to(workdir)) + if progress is not None: + self._event_loop.run_until_complete(progress(res_i)) + return paths @activity_defn(name=POSTPROCESS_ACTIVITY, progress_weight=_BASE_WEIGHT) def postprocess( @@ -104,26 +128,28 @@ def postprocess( inference_results = _LIST_OF_PATH_ADAPTER.validate_python(inference_results) input_paths = _LIST_OF_PATH_ADAPTER.validate_python(input_paths) worker_config = ASRWorkerConfig() - artifacts_root = worker_config.artifact_root + artifacts_root = worker_config.artifacts_root # TODO: load from config passed at runtime with caching - post_processor = self.asr_handler.postprocess - if progress is not None: - progress = to_raw_progress(progress, max_progress=len(input_paths)) - with post_processor: - transcriptions = post_processor.process(inference_results) - # Strict is important here ! - for i, (original, asr_result) in enumerate( - zip(input_paths, transcriptions, strict=True) - ): - transcription_path = write_transcription( - asr_result, - original.name, - artifacts_root=artifacts_root, - project=project, - ) - activity.logger.debug("wrote transcription for %s", transcription_path) - if progress is not None: - self._event_loop.run_until_complete(progress(i)) + # TODO: avoid loading the full handler we just need postprocessing + with _handler(self._handler_config) as asr_handler: + post_processor = asr_handler.postprocessor + if progress is not None: + progress = to_raw_progress(progress, max_progress=len(input_paths)) + with post_processor: + transcriptions = post_processor.process(inference_results) + # Strict is important here ! + for i, (original, asr_result) in enumerate( + zip(input_paths, transcriptions, strict=True) + ): + t_path = write_transcription( + asr_result, + original.name, + artifacts_root=artifacts_root, + project=project, + ) + activity.logger.debug("wrote transcription for %s", t_path) + if progress is not None: + self._event_loop.run_until_complete(progress(i)) def write_transcription( diff --git a/asr-worker/asr_worker/config.py b/asr-worker/asr_worker/config.py index 722b8f9..95cbbb8 100644 --- a/asr-worker/asr_worker/config.py +++ b/asr-worker/asr_worker/config.py @@ -11,6 +11,6 @@ class ASRWorkerConfig(WorkerConfig): loggers: ClassVar[list[str]] = Field(_ALL_LOGGERS, frozen=True) - audio_root: Path - artifact_root: Path + audios_root: Path + artifacts_root: Path workdir: Path diff --git a/asr-worker/asr_worker/models.py b/asr-worker/asr_worker/models.py index 842b2a8..148fb91 100644 --- a/asr-worker/asr_worker/models.py +++ b/asr-worker/asr_worker/models.py @@ -1,3 +1,4 @@ +import math from pathlib import Path from typing import Self @@ -68,6 +69,7 @@ def from_asr_handler_result(cls, asr_handler_result: ASRModelHandlerResult) -> S Transcript(text=text, timestamp=Timestamp(start_s=start_s, end_s=end_s)) for start_s, end_s, text in asr_handler_result.transcription ] - return Transcription( - confidence=asr_handler_result.score, transcripts=transcripts - ) + confidence = asr_handler_result.score + if confidence is not None: + confidence = math.exp(asr_handler_result.score) + return Transcription(confidence=confidence, transcripts=transcripts) diff --git a/asr-worker/asr_worker/worker.py b/asr-worker/asr_worker/worker.py deleted file mode 100644 index 2a40864..0000000 --- a/asr-worker/asr_worker/worker.py +++ /dev/null @@ -1,44 +0,0 @@ -import asyncio -import logging -import os -import socket -from concurrent.futures import ThreadPoolExecutor - -from temporalio.client import Client -from temporalio.worker import Worker - -from temporalio import workflow - -from asr_worker.constants import ( - ASR_TASK_QUEUE, - ASR_WORKER_NAME, - DEFAULT_TEMPORAL_ADDRESS, -) -from asr_worker.workflow import ASRWorkflow - -with workflow.unsafe.imports_passed_through(): - from asr_worker.activities import ASRActivities - -LOGGER = logging.getLogger(__name__) - - -async def run_asr_worker(target_host: str = DEFAULT_TEMPORAL_ADDRESS) -> None: - """ASR worker task""" - LOGGER.info("ASR worker connecting to target_host={%s}", target_host) - client = await Client.connect(target_host=target_host, namespace="default") - identity = f"{ASR_WORKER_NAME}:{os.getpid()}@{socket.gethostname()}" - activities = ASRActivities() - worker = Worker( - client=client, - task_queue=ASR_TASK_QUEUE, - workflows=[ASRWorkflow], - activities=[activities.preprocess, activities.infer, activities.postprocess], - activity_executor=ThreadPoolExecutor(), - identity=identity, - ) - LOGGER.info("Activities loaded. ASR worker starting...") - await worker.run() - - -if __name__ == "__main__": - asyncio.run(run_asr_worker()) diff --git a/asr-worker/asr_worker/workflow.py b/asr-worker/asr_worker/workflows.py similarity index 92% rename from asr-worker/asr_worker/workflow.py rename to asr-worker/asr_worker/workflows.py index 6052564..4cca9cd 100644 --- a/asr-worker/asr_worker/workflow.py +++ b/asr-worker/asr_worker/workflows.py @@ -27,13 +27,6 @@ class TaskQueues(StrEnum): class ASRWorkflow(WorkflowWithProgress): @workflow.run async def run(self, inputs: ASRInputs) -> ASRResponse: - """Run ASR workflow - - :param inputs: ASRInputs - :return: ASRResponse - """ - # We can't get the config from the env since it's non-deterministic, - # it has to be an activity # Preprocessing logger = workflow.logger batch_size = inputs.config.batch_size diff --git a/asr-worker/tests/__init__.py b/asr-worker/tests/__init__.py new file mode 100644 index 0000000..0a70366 --- /dev/null +++ b/asr-worker/tests/__init__.py @@ -0,0 +1,5 @@ +from pathlib import Path + +TEST_PATH = Path(__file__).parent +TEST_RESOURCE_PATH = TEST_PATH / "resources" +AUDIOS_PATH = TEST_RESOURCE_PATH / "audios" diff --git a/asr-worker/tests/conftest.py b/asr-worker/tests/conftest.py index 45a8aa2..d990507 100644 --- a/asr-worker/tests/conftest.py +++ b/asr-worker/tests/conftest.py @@ -14,7 +14,7 @@ @pytest.fixture -def mocked_worker_config_in_env(reset_env, tmp_path: Path) -> ASRWorkerConfig: # noqa: ANN001, F811 +def mocked_worker_config_in_env(reset_env, tmp_path: Path) -> ASRWorkerConfig: # noqa: ANN001, ARG001, F811 os.environ["DS_WORKER_AUDIO_ROOT"] = str(tmp_path / "audios") os.environ["DS_WORKER_ARTIFACT_ROOT"] = str(tmp_path / "artifacts") os.environ["DS_WORKER_WORKDIR"] = str(tmp_path / "workdir") diff --git a/asr-worker/tests/e2e/asr/test_transcription.py b/asr-worker/tests/e2e/asr/test_transcription.py deleted file mode 100644 index 9fe5baf..0000000 --- a/asr-worker/tests/e2e/asr/test_transcription.py +++ /dev/null @@ -1,48 +0,0 @@ -import asyncio -import os -import traceback - -from temporalio.client import Client, WorkflowFailureError - -from asr_worker.constants import ASR_TASK_QUEUE -from asr_worker.models import ( - ASRInputs, - ASRPipelineConfig, - PreprocessingConfig, -) -from asr_worker.workflow import ASRWorkflow - - -async def test_worker_transcription() -> None: - # Create client connected to server at the given address - client: Client = await Client.connect("localhost:7233") - - audio_dir = os.environ.get("AUDIO_DIR", "resources/files/asr") - audio_path = os.path.join(audio_dir, "asr_test.wav") - - inputs: ASRInputs = ASRInputs( - file_paths=[audio_path] * 5, - pipeline=ASRPipelineConfig(preprocessing=PreprocessingConfig(batch_size=4)), - ) - - try: - res = await client.execute_workflow( - ASRWorkflow.run, - inputs, - id="test-001", - task_queue=ASR_TASK_QUEUE, - ) - - for transcription in res.transcriptions: - assert transcription["score"] == -248.3 - assert transcription["transcription"] == [ - [0.08, 2.56, "To embrace the chaos that they fought in this battle."] - ] - - except WorkflowFailureError: - print("Got expected exception: ", traceback.format_exc()) - assert False - - -if __name__ == "__main__": - asyncio.run(test_worker_transcription()) diff --git a/resources/files/asr/asr_test.wav b/asr-worker/tests/resources/audios/asr_test.wav similarity index 100% rename from resources/files/asr/asr_test.wav rename to asr-worker/tests/resources/audios/asr_test.wav diff --git a/asr-worker/tests/test_workflows.py b/asr-worker/tests/test_workflows.py index cb68170..8a44c9d 100644 --- a/asr-worker/tests/test_workflows.py +++ b/asr-worker/tests/test_workflows.py @@ -1,11 +1,13 @@ import json +import math +import shutil import uuid from asyncio import AbstractEventLoop from collections.abc import AsyncGenerator from pathlib import Path import pytest -from asr_worker.activities import write_transcription +from asr_worker.activities import ASRActivities, write_transcription from asr_worker.config import ASRWorkerConfig from asr_worker.constants import ( POSTPROCESS_ACTIVITY, @@ -20,7 +22,7 @@ Transcript, Transcription, ) -from asr_worker.workflow import ASRWorkflow, TaskQueues +from asr_worker.workflows import ASRWorkflow, TaskQueues from caul.model_handlers.objects import ASRModelHandlerResult from caul.tasks.preprocessing.objects import InputMetadata, PreprocessedInput from datashare_python.types_ import ProgressRateHandler, TemporalClient @@ -31,13 +33,15 @@ from temporalio import activity from temporalio.worker import Worker +from . import AUDIOS_PATH + _LIST_OF_PATH_ADAPTER = TypeAdapter(list[Path]) _MODEL_RESULT_0 = ASRModelHandlerResult( - transcription=[(0.0, 2.0, "segment zero")], score=0.5 + transcription=[(0.0, 2.0, "segment zero")], score=math.log(0.5) ) _MODEL_RESULT_1 = ASRModelHandlerResult( - transcription=[(0.0, 1.0, "segment one")], score=0.5 + transcription=[(0.0, 1.0, "segment one")], score=math.log(0.5) ) @@ -72,7 +76,7 @@ def infer( self, preprocessed_inputs: list[Path], *, - progress: ProgressRateHandler | None = None, + progress: ProgressRateHandler | None = None, # noqa: ARG002 ) -> list[Path]: # noqa: ANN001, ARG001 # TODO: this shouldn't be necessary, fix this bug preprocessed_inputs = _LIST_OF_PATH_ADAPTER.validate_python(preprocessed_inputs) @@ -100,13 +104,13 @@ def postprocess( inference_results: list[Path], input_paths: list[Path], project: str, - progress: ProgressRateHandler | None = None, + progress: ProgressRateHandler | None = None, # noqa: ARG002 ) -> None: # TODO: this shouldn't be necessary, fix this bug inference_results = _LIST_OF_PATH_ADAPTER.validate_python(inference_results) input_paths = _LIST_OF_PATH_ADAPTER.validate_python(input_paths) config = ASRWorkerConfig() - artifact_root = config.artifact_root + artifact_root = config.artifacts_root workdir = config.workdir artifact_root.mkdir(parents=True, exist_ok=True) inference_results = [ @@ -149,7 +153,7 @@ async def io_bound_worker( @pytest.fixture -async def cpu_bound_worker( +async def mock_cpu_bound_worker( test_temporal_client_session: TemporalClient, event_loop: AbstractEventLoop, # noqa: F811 ) -> AsyncGenerator[Worker, None]: @@ -165,7 +169,7 @@ async def cpu_bound_worker( @pytest.fixture -async def cpu_inference_worker( +async def mock_cpu_inference_worker( test_temporal_client_session: TemporalClient, event_loop: AbstractEventLoop, # noqa: F811 ) -> AsyncGenerator[Worker, None]: @@ -178,6 +182,36 @@ async def cpu_inference_worker( yield worker +@pytest.fixture +async def cpu_bound_worker( + test_temporal_client_session: TemporalClient, + event_loop: AbstractEventLoop, # noqa: F811 +) -> AsyncGenerator[Worker, None]: + client = test_temporal_client_session + activities = ASRActivities(client, event_loop) + worker = datashare_worker( + client, + task_queue=TaskQueues.CPU, + activities=[activities.preprocess, activities.postprocess], + ) + async with worker: + yield worker + + +@pytest.fixture +async def cpu_inference_worker( + test_temporal_client_session: TemporalClient, + event_loop: AbstractEventLoop, # noqa: F811 +) -> AsyncGenerator[Worker, None]: + client = test_temporal_client_session + activities = ASRActivities(client, event_loop) + worker = datashare_worker( + client, task_queue=TaskQueues.INFERENCE_CPU, activities=[activities.infer] + ) + async with worker: + yield worker + + _EXPECTED_TRANSCRIPTION_0 = Transcription( transcripts=[ Transcript(text="segment zero", timestamp=Timestamp(start_s=0.0, end_s=2.0)), @@ -198,8 +232,8 @@ async def cpu_inference_worker( async def test_asr_workflow( test_temporal_client_session: TemporalClient, - cpu_bound_worker: Worker, # noqa: ARG001 - cpu_inference_worker: Worker, # noqa: ARG001 + mock_cpu_bound_worker: Worker, # noqa: ARG001 + mock_cpu_inference_worker: Worker, # noqa: ARG001 io_bound_worker: Worker, # noqa: ARG001 mocked_worker_config_in_env: ASRWorkerConfig, ) -> None: @@ -219,7 +253,7 @@ async def test_asr_workflow( # Then expected_response = ASRResponse(n_transcribed=2) assert result == expected_response - artifacts_dir = worker_config.artifact_root + artifacts_dir = worker_config.artifacts_root expected_transcription_dirs = [ artifacts_dir / project / "aa" / "bb" / "aabb", artifacts_dir / project / "cc" / "cc", @@ -241,3 +275,68 @@ async def test_asr_workflow( transcription_path.read_text() ) assert transcription == expected_t + + +@pytest.fixture +def with_audios(mocked_worker_config_in_env: ASRWorkerConfig) -> list[Path]: + config = mocked_worker_config_in_env + audios = [f for f in AUDIOS_PATH.iterdir() if f.suffix == ".wav"] + paths = [] + config.audios_root.mkdir(parents=True, exist_ok=True) + for audio in audios: + rel_path = audio.relative_to(AUDIOS_PATH) + shutil.copy(audio, config.audios_root / rel_path) + paths.append(rel_path) + return paths + + +@pytest.mark.e2e +async def test_asr_workflow_e2e( + test_temporal_client_session: TemporalClient, + cpu_bound_worker: Worker, # noqa: ARG001 + cpu_inference_worker: Worker, # noqa: ARG001 + io_bound_worker: Worker, # noqa: ARG001 + mocked_worker_config_in_env: ASRWorkerConfig, # noqa: ARG001 + with_audios: list[Path], +) -> None: + # Given + config = mocked_worker_config_in_env + client = test_temporal_client_session + n_audios = 3 + batch_size = n_audios - 1 + audios = with_audios * n_audios + inputs = ASRInputs( + project=TEST_PROJECT, + paths=audios, + config=ASRPipelineConfig(batch_size=batch_size), + ) + workflow_id = f"asr-{uuid.uuid4().hex}" + + # When + response = await client.execute_workflow( + ASRWorkflow.run, inputs, id=workflow_id, task_queue=TaskQueues.IO + ) + + # Then + assert response.n_transcribed == n_audios + expected_transcription_path = config.artifacts_root / "as" / "r_" / "asr_test" + assert expected_transcription_path.exists() + assert expected_transcription_path.is_dir() + meta_path = expected_transcription_path / "metadata.json" + assert meta_path.exists() + meta = json.loads(meta_path.read_text()) + transcription_name = meta.get("transcription") + assert transcription_name is not None + transcription_path = expected_transcription_path / transcription_name + assert transcription_path.exists() + transcription = Transcription.model_validate_json(transcription_path.read_text()) + expcted_transcription = Transcription( + transcripts=[ + Transcript( + text="To embrace the chaos that they fought in this battle.", + timestamp=Timestamp.from_floats(0.08, 2.56), + ) + ], + confidence=math.log(-248.3), + ) + assert transcription == expcted_transcription diff --git a/datashare-python/datashare_python/template.py b/datashare-python/datashare_python/template.py index 30b4d28..8a50403 100644 --- a/datashare-python/datashare_python/template.py +++ b/datashare-python/datashare_python/template.py @@ -76,7 +76,7 @@ def _update_pyproject_toml( project = pyproject_toml["project"] project["authors"] = [] - project.pop("urls") + project.pop("urls", None) project["dependencies"] = sorted( d for d in project["dependencies"] diff --git a/datashare-python/datashare_python/utils.py b/datashare-python/datashare_python/utils.py index fb00fbb..856949b 100644 --- a/datashare-python/datashare_python/utils.py +++ b/datashare-python/datashare_python/utils.py @@ -151,10 +151,7 @@ async def wrapper(self: ActivityWithProgress, *args: P.args) -> T: client=self._temporal_client, weight=weight ) await handler(0.0) - if supports_progress(activity_fn): - res = await activity_fn(self, *args, progress=handler) - else: - res = await activity_fn(self, *args) + res = await activity_fn(self, *args, progress=handler) await handler(1.0) return res @@ -175,10 +172,7 @@ def wrapper(self: ActivityWithProgress, *args: P.args) -> T: ) event_loop = self._event_loop event_loop.run_until_complete(handler(0.0)) - if supports_progress(activity_fn): - res = activity_fn(self, *args, progress=handler) - else: - res = activity_fn(self, *args) + res = activity_fn(self, *args, progress=handler) event_loop.run_until_complete(handler(1.0)) return res @@ -238,8 +232,28 @@ def with_retriables( retriables: set[type[Exception]] = None, ) -> Callable[[Callable[P, T]], Callable[P, T]]: if retriables is None: - retriables = set() - retriables = tuple(retriables) + + def decorator(activity_fn: Callable[P, T]) -> Callable[P, T]: + if asyncio.iscoroutinefunction(activity_fn): + + @wraps(activity_fn) + async def wrapper(*args, **kwargs) -> T: + try: + return await activity_fn(*args, **kwargs) + except Exception as e: + raise fatal_error_from_exception(e) from e + else: + + @wraps(activity_fn) + def wrapper(*args, **kwargs) -> T: + try: + return activity_fn(*args, **kwargs) + except Exception as e: + raise fatal_error_from_exception(e) from e + + return wrapper + + return decorator def decorator(activity_fn: Callable[P, T]) -> Callable[P, T]: if asyncio.iscoroutinefunction(activity_fn): @@ -277,9 +291,10 @@ def activity_defn( dynamic: bool = False, ) -> Callable[[Callable[P, T]], Callable[P, T]]: def decorator(activity_fn: Callable[P, T]) -> Callable[P, T]: - activity_fn = positional_args_only(activity_fn) activity_fn = with_retriables(retriables)(activity_fn) - activity_fn = with_progress(progress_weight)(activity_fn) + activity_fn = positional_args_only(activity_fn) + if supports_progress(activity_fn): + activity_fn = with_progress(progress_weight)(activity_fn) activity_fn = activity.defn( activity_fn, name=name, @@ -377,6 +392,7 @@ def _handlers( def safe_dir(filename: str) -> Path: + filename = filename.split(".", maxsplit=1)[0] parts = (p for p in (filename[:2], filename[2:4]) if p) return Path(*parts) diff --git a/datashare-python/datashare_python/worker.py b/datashare-python/datashare_python/worker.py index e6be7c8..4c6f9bb 100644 --- a/datashare-python/datashare_python/worker.py +++ b/datashare-python/datashare_python/worker.py @@ -45,16 +45,15 @@ def datashare_worker( activities = [] activity_executor = None # Use temporal default if activities: - are_async = [a.__temporal_activity_definition.is_async for a in activities] - if all(not a for a in are_async): + n_sync = sum( + 1 for a in activities if not a.__temporal_activity_definition.is_async + ) + if n_sync: activity_executor = ThreadPoolExecutor( thread_name_prefix=_ACTIVITY_THREAD_NAME_PREFIX ) - else: - activity_executor = ThreadPoolExecutor( - thread_name_prefix=_ACTIVITY_THREAD_NAME_PREFIX - ) - logger.warning(_SEPARATE_IO_AND_CPU_ACTIVITIES) + if n_sync != len(activities): + logger.warning(_SEPARATE_IO_AND_CPU_ACTIVITIES) if isinstance(activity_executor, ThreadPoolExecutor) and workflows: logger.warning(_SEPARATE_IO_AND_CPU_WORKERS) diff --git a/datashare-python/pyproject.toml b/datashare-python/pyproject.toml index 5e8285a..468b761 100644 --- a/datashare-python/pyproject.toml +++ b/datashare-python/pyproject.toml @@ -18,7 +18,7 @@ dependencies = [ "nest-asyncio~=1.6.0", "temporalio~=1.23.0", "typer~=0.15.4", - "datashare-worker-template~=0.1", + "datashare-worker-template[ml]~=0.1", "tomlkit~=0.14.0", "hatchling~=1.27.0", ] diff --git a/datashare-python/tests/test_utils.py b/datashare-python/tests/test_utils.py index a4ded97..12cb500 100644 --- a/datashare-python/tests/test_utils.py +++ b/datashare-python/tests/test_utils.py @@ -1,5 +1,13 @@ -from datashare_python.utils import positional_args_only -from temporalio import activity +import uuid +from datetime import timedelta + +import pytest +from datashare_python.types_ import TemporalClient +from datashare_python.utils import activity_defn, positional_args_only +from datashare_python.worker import datashare_worker +from temporalio import activity, workflow +from temporalio.client import WorkflowFailureError +from temporalio.exceptions import ApplicationError @positional_args_only @@ -15,3 +23,40 @@ def test_keyword_safe_activity() -> None: raise AssertionError( "couldn't create activity from keyword only function " ) from e + + +@activity_defn(name="non_retriable") +async def non_retriable() -> None: + raise ValueError("non retriable error occurred") + + +@workflow.defn(name="non_retriable_workflow") +class NonRetriableWorkflow: + @workflow.run + async def run(self) -> None: + await workflow.execute_activity( + non_retriable, + task_queue="io", + schedule_to_close_timeout=timedelta(seconds=30), + ) + + +async def test_retriable(test_temporal_client_session: TemporalClient) -> None: + # Given + client = test_temporal_client_session + workflow_id = f"workflow_{uuid.uuid4().hex}" + worker = datashare_worker( + client, + task_queue="io", + workflows=[NonRetriableWorkflow], + activities=[non_retriable], + ) + async with worker: + with pytest.raises(WorkflowFailureError) as ctx: + await client.execute_workflow( + NonRetriableWorkflow.run, id=workflow_id, task_queue="io" + ) + cause = ctx.value.cause.__cause__ + assert isinstance(cause, ApplicationError) + assert cause.message == "non retriable error occurred" + assert cause.non_retryable diff --git 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