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..55f6d05 100644 --- a/.github/workflows/linting.yml +++ b/.github/workflows/linting.yml @@ -9,7 +9,7 @@ on: - 'datashare-python/**.py' - 'worker-template/**.py' - 'asr-worker/**.py' - - '.github/workflows/linting.yml' + - 'translation-worker/**.py' # TODO: leverage some caching here jobs: @@ -37,7 +37,7 @@ jobs: - name: Lint test run: ruff check --config qa/ruff.toml worker-template - doc: + asr-worker: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 @@ -45,18 +45,33 @@ jobs: with: args: "--version" # skips test by displaying the version - name: Check formatting - run: ruff format --config qa/ruff.toml --check docs + run: ruff format --config qa/ruff.toml --check asr-worker - name: Lint test - run: ruff check --config qa/ruff.toml docs + run: ruff check --config qa/ruff.toml asr-worker - asr-worker: + translation-worker: 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 translation-worker + - name: Lint test + run: ruff check --config qa/ruff.toml translation-worker + + doc: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - uses: astral-sh/ruff-action@v3 + with: + args: "--version" # skips test by displaying the version + - name: Check formatting + run: ruff format --config qa/ruff.toml --check docs + - name: Lint test + run: ruff check --config qa/ruff.toml docs concurrency: group: ${{ github.workflow }}-${{ github.ref }} diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 29d40a8..9f6bb47 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -71,6 +71,60 @@ jobs: uv sync --frozen --all-extras 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: worker-template + - name: Run tests + run: | + cd asr-worker + uv sync --frozen --all-extras + uv run --frozen python -m pytest --timeout=180 -vvv --cache-clear --show-capture=all -r A + + test-translation-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: worker-template + - name: Run tests + run: | + cd translation-worker + uv sync --frozen --all-extras + uv run --frozen python -m pytest --timeout=180 -vvv --cache-clear --show-capture=all -r A + concurrency: group: ${{ github.workflow }}-${{ github.ref }} cancel-in-progress: true diff --git a/Dockerfile b/Dockerfile index 12a120f..3de02bb 100644 --- a/Dockerfile +++ b/Dockerfile @@ -16,10 +16,11 @@ WORKDIR /app # add task cli ADD datashare-python/ ./datashare-python/ +ADD worker-template/ ./worker-template/ # install python deps -RUN --mount=type=cache,target=~/.cache/uv \ - uv pip install --system datashare-python/ +RUN --mount=type=cache,target=~/.cache/uv uv pip install --system worker-template/ +RUN --mount=type=cache,target=~/.cache/uv uv pip install --system datashare-python/ # copy build-independant files ADD scripts scripts diff --git a/asr-worker/asr_worker/activities.py b/asr-worker/asr_worker/activities.py index 838db38..57fc57b 100644 --- a/asr-worker/asr_worker/activities.py +++ b/asr-worker/asr_worker/activities.py @@ -1,4 +1,5 @@ import torchaudio + from caul.configs.parakeet import ParakeetConfig from caul.model_handlers.helpers import ParakeetModelHandlerResult from caul.tasks.preprocessing.helpers import PreprocessedInput diff --git a/asr-worker/asr_worker/constants.py b/asr-worker/asr_worker/constants.py index e801bfa..7d50773 100644 --- a/asr-worker/asr_worker/constants.py +++ b/asr-worker/asr_worker/constants.py @@ -8,8 +8,4 @@ PARAKEET = "parakeet" -DEFAULT_TEMPORAL_ADDRESS = "temporal:7233" - -RESPONSE_SUCCESS = "success" - -RESPONSE_ERROR = "error" +ASR_WORKFLOW_NAME = "asr-workflow" diff --git a/asr-worker/asr_worker/models.py b/asr-worker/asr_worker/models.py deleted file mode 100644 index f878d3d..0000000 --- a/asr-worker/asr_worker/models.py +++ /dev/null @@ -1,54 +0,0 @@ -from dataclasses import dataclass, field, asdict -from typing import Optional - -from asr_worker.constants import PARAKEET - - -@dataclass -class BatchSize: - """Batch size helper""" - - batch_size: int = 32 - - -@dataclass -class PreprocessingConfig(BatchSize): - """Preprocessing config""" - - -@dataclass -class InferenceConfig(BatchSize): - """Inference config""" - - model_name: str = PARAKEET - - -@dataclass -class ASRPipelineConfig: - """ASR pipeline config""" - - preprocessing: PreprocessingConfig = field(default_factory=PreprocessingConfig) - inference: InferenceConfig = field(default_factory=InferenceConfig) - - def serialize(self): - return { - "preprocessing": asdict(self.preprocessing), - "inference": asdict(self.inference), - } - - -@dataclass -class ASRInputs: - """Inputs to ASR workflow""" - - file_paths: list[str] - pipeline: ASRPipelineConfig - - -@dataclass -class ASRResponse: - """ASR workflow response""" - - status: str - transcriptions: list[dict] = field(default_factory=list) - error: Optional[str] = None diff --git a/asr-worker/asr_worker/objects.py b/asr-worker/asr_worker/objects.py new file mode 100644 index 0000000..3c92080 --- /dev/null +++ b/asr-worker/asr_worker/objects.py @@ -0,0 +1,40 @@ +from pydantic import BaseModel, Field +from datashare_python.objects import WorkerResponse, BasePayload + +from .constants import PARAKEET + + +class BatchSize(BaseModel): + """Batch size helper""" + + batch_size: int = 32 + + +class PreprocessingConfig(BatchSize): + """Preprocessing config""" + + +class InferenceConfig(BatchSize): + """Inference config""" + + model_name: str = PARAKEET + + +class ASRPipelineConfig(BaseModel): + """ASR pipeline config""" + + preprocessing: PreprocessingConfig = Field(default_factory=PreprocessingConfig) + inference: InferenceConfig = Field(default_factory=InferenceConfig) + + +class ASRRequest(BasePayload): + """Inputs to ASR workflow""" + + file_paths: list[str] + pipeline: ASRPipelineConfig + + +class ASRResponse(WorkerResponse): + """ASR workflow response""" + + transcriptions: list[dict] = Field(default_factory=list) diff --git a/asr-worker/asr_worker/worker.py b/asr-worker/asr_worker/worker.py index 2a40864..a729716 100644 --- a/asr-worker/asr_worker/worker.py +++ b/asr-worker/asr_worker/worker.py @@ -2,22 +2,20 @@ import logging import os import socket -from concurrent.futures import ThreadPoolExecutor +from concurrent.futures import ThreadPoolExecutor from temporalio.client import Client from temporalio.worker import Worker - from temporalio import workflow - -from asr_worker.constants import ( +from datashare_python.constants import DEFAULT_TEMPORAL_ADDRESS +from .constants import ( ASR_TASK_QUEUE, ASR_WORKER_NAME, - DEFAULT_TEMPORAL_ADDRESS, ) -from asr_worker.workflow import ASRWorkflow +from .workflow import ASRWorkflow with workflow.unsafe.imports_passed_through(): - from asr_worker.activities import ASRActivities + from .activities import ASRActivities LOGGER = logging.getLogger(__name__) diff --git a/asr-worker/asr_worker/workflow.py b/asr-worker/asr_worker/workflow.py index 55da800..bfa8e0e 100644 --- a/asr-worker/asr_worker/workflow.py +++ b/asr-worker/asr_worker/workflow.py @@ -1,20 +1,20 @@ from asyncio import gather from dataclasses import asdict from datetime import timedelta - from more_itertools import flatten from temporalio import workflow -from asr_worker.constants import _TEN_MINUTES, RESPONSE_ERROR, RESPONSE_SUCCESS -from asr_worker.models import ASRInputs, ASRResponse +from datashare_python.objects import WorkerResponseStatus +from .objects import ASRResponse, ASRRequest +from .constants import _TEN_MINUTES with workflow.unsafe.imports_passed_through(): - from asr_worker.activities import ASRActivities + from .activities import ASRActivities # TODO: Figure out which modules are violating sandbox restrictions # and grant a limited passthrough -@workflow.defn(name="asr.transcription", sandboxed=False) +@workflow.defn(sandboxed=False) class ASRWorkflow: """ASR workflow definition""" @@ -22,10 +22,10 @@ def __init__(self): pass @workflow.run - async def run(self, inputs: ASRInputs) -> ASRResponse: + async def run(self, inputs: ASRRequest) -> ASRResponse: """Run ASR workflow - :param inputs: ASRInputs + :param inputs: ASRRequest :return: ASRResponse """ try: @@ -81,8 +81,8 @@ async def run(self, inputs: ASRInputs) -> ASRResponse: serialized_transcriptions = [] # drop unnecessary fields, serialize - for transcription in flatten(transcriptions): - transcription = asdict(transcription) + for trans in flatten(transcriptions): + transcription = asdict(trans) del transcription["input_ordering"] @@ -93,11 +93,9 @@ async def run(self, inputs: ASRInputs) -> ASRResponse: # TODO: Output formatting; do we want to keep PreprocessedInput metadata # and remap results to it? return ASRResponse( - status=RESPONSE_SUCCESS, transcriptions=serialized_transcriptions + status=WorkerResponseStatus.SUCCESS, + transcriptions=serialized_transcriptions, ) except ValueError as e: workflow.logger.exception(e) - return ASRResponse(status=RESPONSE_ERROR, error=str(e)) - - -WORKFLOWS = [ASRWorkflow] + return ASRResponse(status=WorkerResponseStatus.ERROR, error=str(e)) diff --git a/asr-worker/pyproject.toml b/asr-worker/pyproject.toml index b8c1c5c..8503059 100644 --- a/asr-worker/pyproject.toml +++ b/asr-worker/pyproject.toml @@ -21,6 +21,7 @@ authors = [ readme = "README.md" requires-python = ">=3.11.0, <3.14" dependencies = [ + "datashare-python", "temporalio>=1.22.0", "caul==0.1.5", "pyarrow<21.0.0", @@ -30,6 +31,7 @@ dependencies = [ "numpy==2.3.0", "ml-dtypes>=0.5", "kaldialign>=0.9.3", + "icij-common~=0.7.3", ] [project.entry-points."datashare.workflows"] workflows = "asr_worker.workflows:REGISTRY" @@ -52,16 +54,26 @@ torchaudio = [ torchcodec = [ { index = "pytorch-cpu" } ] +datashare-python = { path = "../datashare-python", editable = true } [tool.uv] package = true override-dependencies = ["kaldialign>=0.9.3"] -[tool.pylint."MESSAGES CONTROL"] -disable = [ - "missing-module-docstring", - "logging-fstring-interpolation", - "broad-exception-caught" +[dependency-groups] +dev = [ + "black>=26.1.0", + "datashare-python~=0.1.3", + "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.pip] diff --git a/asr-worker/tests/e2e/asr/test_transcription.py b/asr-worker/tests/test_transcription.py similarity index 90% rename from asr-worker/tests/e2e/asr/test_transcription.py rename to asr-worker/tests/test_transcription.py index 9fe5baf..9c8cbb8 100644 --- a/asr-worker/tests/e2e/asr/test_transcription.py +++ b/asr-worker/tests/test_transcription.py @@ -2,17 +2,19 @@ import os import traceback +import pytest from temporalio.client import Client, WorkflowFailureError from asr_worker.constants import ASR_TASK_QUEUE from asr_worker.models import ( - ASRInputs, + ASRRequest, ASRPipelineConfig, PreprocessingConfig, ) from asr_worker.workflow import ASRWorkflow +@pytest.mark.integration async def test_worker_transcription() -> None: # Create client connected to server at the given address client: Client = await Client.connect("localhost:7233") @@ -20,7 +22,7 @@ async def test_worker_transcription() -> None: audio_dir = os.environ.get("AUDIO_DIR", "resources/files/asr") audio_path = os.path.join(audio_dir, "asr_test.wav") - inputs: ASRInputs = ASRInputs( + inputs: ASRRequest = ASRRequest( file_paths=[audio_path] * 5, pipeline=ASRPipelineConfig(preprocessing=PreprocessingConfig(batch_size=4)), ) @@ -40,8 +42,7 @@ async def test_worker_transcription() -> None: ] except WorkflowFailureError: - print("Got expected exception: ", traceback.format_exc()) - assert False + pytest.fail(traceback.format_exc()) if __name__ == "__main__": diff --git a/datashare-python/datashare_python/constants.py b/datashare-python/datashare_python/constants.py index 8909092..7712f45 100644 --- a/datashare-python/datashare_python/constants.py +++ b/datashare-python/datashare_python/constants.py @@ -12,3 +12,11 @@ DEFAULT_DS_ADDRESS = "http://localhost:8080" DEFAULT_NAMESPACE = "datashare-default" + +CPU = "cpu" + +CUDA = "cuda" + +MPS = "mps" + +MKL = "mkl" diff --git a/datashare-python/datashare_python/objects.py b/datashare-python/datashare_python/objects.py index df0b9ea..4f74cba 100644 --- a/datashare-python/datashare_python/objects.py +++ b/datashare-python/datashare_python/objects.py @@ -3,7 +3,7 @@ from dataclasses import dataclass from datetime import UTC, datetime from enum import StrEnum, unique -from typing import Any, Literal, Self +from typing import Any, Literal, Self, Optional, TypeVar, Awaitable from temporalio import workflow @@ -23,14 +23,28 @@ logger = logging.getLogger(__name__) +T = TypeVar("T") + + +Predicate = Callable[[T], bool] | Callable[[T], Awaitable[bool]] + + class BaseModel(_BaseModel): model_config = merge_configs(icij_config(), no_enum_values_config()) +class BasePayload(_BaseModel): + model_config = icij_config() + + class DatashareModel(BaseModel): model_config = merge_configs(BaseModel.model_config, lowercamel_case_config()) +class LowerCamelCaseModel(_BaseModel): + model_config = merge_configs(icij_config(), lowercamel_case_config()) + + @unique class TaskState(StrEnum): CREATED = "CREATED" @@ -142,3 +156,16 @@ def from_es(cls, es_doc: dict) -> Self: root_document=sources[DOC_ROOT_ID], tags=sources.get("tags", []), ) + + +# Temporal objects +class WorkerResponse(BasePayload): + """Generic worker response""" + + status: str + error: Optional[str] = None + + +class WorkerResponseStatus(StrEnum): + SUCCESS = "success" + ERROR = "error" diff --git a/datashare-python/datashare_python/utils.py b/datashare-python/datashare_python/utils.py index aa912a2..9f21fc0 100644 --- a/datashare-python/datashare_python/utils.py +++ b/datashare-python/datashare_python/utils.py @@ -6,9 +6,19 @@ from dataclasses import dataclass from functools import partial, wraps from inspect import signature -from typing import ParamSpec, TypeVar +from itertools import islice +from typing import ( + ParamSpec, + TypeVar, + AsyncIterator, + AsyncIterable, + Awaitable, + Generator, + Iterable, +) import nest_asyncio +import torch from icij_common.logging_utils import ( DATE_FMT, STREAM_HANDLER_FMT, @@ -23,6 +33,8 @@ from temporalio.common import SearchAttributeKey from temporalio.exceptions import ApplicationError +from .constants import CPU, MPS, MKL, CUDA +from .objects import Predicate from .types_ import ProgressRateHandler, RawProgressHandler DependencyLabel = str | None @@ -201,6 +213,7 @@ async def wrapper(*args, **kwargs) -> T: # recreate kwargs from pargs new_args, new_kwargs = _unpack_positional_args(args, keyword_only, params) return await activity_fn(*new_args, **new_kwargs, **kwargs) + else: @wraps(activity_fn) @@ -211,9 +224,11 @@ def wrapper(*args, **kwargs) -> T: # Update the decorated function signature to appear as p-args only new_params = [ - p.replace(kind=inspect.Parameter.POSITIONAL_OR_KEYWORD) - if p.kind == inspect.Parameter.KEYWORD_ONLY - else p + ( + p.replace(kind=inspect.Parameter.POSITIONAL_OR_KEYWORD) + if p.kind == inspect.Parameter.KEYWORD_ONLY + else p + ) for p in params ] wrapper.__signature__ = sig.replace(parameters=new_params) @@ -252,6 +267,7 @@ async def wrapper(*args, **kwargs) -> T: raise except Exception as e: raise fatal_error_from_exception(e) from e + else: @wraps(activity_fn) @@ -374,3 +390,83 @@ def _handlers( handler.addFilter(worker_id_filter) handler.setLevel(log_level) return handlers + + +# Temporal utils +async def async_batches( + iterable: AsyncIterable[T], batch_size: int +) -> AsyncIterator[tuple[T]]: + it = aiter(iterable) + if batch_size < 1: + raise ValueError("n must be at least one") + while True: + batch = [] + while len(batch) < batch_size: + try: + batch.append(await anext(it)) + except StopAsyncIteration: + if batch: + yield tuple(batch) + return + yield tuple(batch) + + +def batches( + iterable: Iterable[T], batch_size: int +) -> Generator[tuple[T, ...], None, None]: + if batch_size < 1: + raise ValueError("n must be at least one") + it = iter(iterable) + while batch := tuple(islice(it, batch_size)): + yield batch + + +async def maybe_await(maybe_awaitable: Awaitable[T] | T) -> T: + if inspect.isawaitable(maybe_awaitable): + return await maybe_awaitable + return maybe_awaitable + + +async def once(item: T) -> AsyncIterator[T]: + yield item + + +def before_and_after( + iterable: AsyncIterable[T], predicate: Predicate[T] +) -> tuple[AsyncIterable[T], AsyncIterable[T]]: + transition = asyncio.get_event_loop().create_future() + + async def true_iterator() -> AsyncIterator[T]: + async for elem in iterable: + if await maybe_await(predicate(elem)): + yield elem + else: + transition.set_result(elem) + return + transition.set_exception(StopAsyncIteration) + + async def remainder_iterator() -> AsyncIterator[T]: + try: + yield await transition + except StopAsyncIteration: + return + async for elm in iterable: + yield elm + + return true_iterator(), remainder_iterator() + + +# Torch utils +def find_device(device_name: str = CPU) -> torch._C.device: + """Find a device by name if available + + :param device_name: Device name + :return: torch.Device + """ + if ( + hasattr(torch.backends, device_name) + and getattr(torch.backends, device_name).is_available() + ): + return torch.device(device_name) + + return torch.device(CPU) diff --git a/datashare-python/tests/test_utils.py b/datashare-python/tests/test_utils.py index a4ded97..5cd318c 100644 --- a/datashare-python/tests/test_utils.py +++ b/datashare-python/tests/test_utils.py @@ -1,4 +1,8 @@ -from datashare_python.utils import positional_args_only +from typing import AsyncGenerator, AsyncIterable, AsyncIterator + +from aiostream.stream import chain + +from datashare_python.utils import positional_args_only, before_and_after, once from temporalio import activity @@ -15,3 +19,29 @@ def test_keyword_safe_activity() -> None: raise AssertionError( "couldn't create activity from keyword only function " ) from e + + +async def _num_gen() -> AsyncGenerator[int, None]: + for i in range(10): + yield i // 3 + + +async def test_before_and_after() -> None: + # Given + async def group_by_iterator( + items: AsyncIterable[int], + ) -> AsyncIterator[AsyncIterator[int]]: + while True: + try: + next_item = await anext(aiter(items)) + except StopAsyncIteration: + return + gr, items = before_and_after(items, lambda x, next_i=next_item: x == next_i) + yield chain(once(next_item), gr) + + # When + grouped = [] + async for group in group_by_iterator(_num_gen()): + group = [item async for item in group] # noqa: PLW2901 + grouped.append(group) + assert grouped == [[0, 0, 0], [1, 1, 1], [2, 2, 2], [3]] diff --git a/translation-worker/README.md b/translation-worker/README.md new file mode 100644 index 0000000..44e8f4a --- /dev/null +++ b/translation-worker/README.md @@ -0,0 +1,4 @@ +# Translation worker implementation in Temporal + +Implements a translation worker for `temporalio` based on the `argostranslate` +translation library. \ No newline at end of file diff --git a/translation-worker/pyproject.toml b/translation-worker/pyproject.toml new file mode 100644 index 0000000..9a8c349 --- /dev/null +++ b/translation-worker/pyproject.toml @@ -0,0 +1,72 @@ +[build-system] +requires = ["hatchling", "uv-dynamic-versioning"] +build-backend = "hatchling.build" + +[tool.hatch.version] +source = "uv-dynamic-versioning" + +[tool.hatch.build.targets.wheel] +packages = ["translation_worker"] + +[tool.uv-dynamic-versioning] +fallback-version = "0.0.0" + +[project] +name = "translation-worker" +dynamic = ["version"] +description = "Translation worker implementation in Temporal" +authors = [ + { name = "Clément Doumouro", email = "cdoumouro@icij.org" }, + { name = "Clément Doumouro", email = "clement.doumouro@gmail.com" }, + { name = "Lion Summerbell", email = "lsummerbell@icij.org" } +] +readme = "README.md" +requires-python = ">=3.11.0, <3.14" +dependencies = [ + "datashare-python", + "argostranslate>=1.11.0", + "temporalio>=1.22.0", + "pycountry~=26.2.16", + "icij-common[elasticsearch]~=0.7.3", +] + +[project.entry-points."datashare.workflows"] +workflows = "translation_worker.workflows:WORKFLOWS" + +[project.entry-points."datashare.activities"] +activities = "translation_worker.activities:ACTIVITIES" + +[tool.uv.sources] +torch = [ + { index = "pytorch-cpu" }, +] +datashare-python = { path = "../datashare-python", editable = true } + +[[tool.uv.index]] +name = "pytorch-cpu" +url = "https://download.pytorch.org/whl/cpu" +explicit = true + +[dependency-groups] +dev = [ + "black>=26.1.0", + "datashare-python~=0.1.3", + "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.pytest.ini_options] +asyncio_mode = "auto" +asyncio_default_fixture_loop_scope = "session" +markers = [ + "integration", + "pull", +] diff --git a/translation-worker/tests/test_translation.py b/translation-worker/tests/test_translation.py new file mode 100644 index 0000000..7c1368e --- /dev/null +++ b/translation-worker/tests/test_translation.py @@ -0,0 +1,43 @@ +import pytest +from icij_common.es import ESClient + +from datashare_python.conftest import TEST_PROJECT + +from translation_worker.activities import translate_sentences +from translation_worker.objects import BatchSentence, TranslationConfig + + +@pytest.mark.integration +async def test_translate_docs(config: TranslationConfig) -> None: + # Given + sentences = [ + BatchSentence( + sentence="Arriba!\n", + doc_id="0", + root_document="root", + sentence_index=1, + language="es", + ), + BatchSentence( + sentence="Andale!", + doc_id="0", + root_document="root", + sentence_index=0, + language="es", + ), + BatchSentence( + sentence="Vaya con dios", + doc_id="1", + root_document="root", + sentence_index=0, + language="es", + ), + ] + target_language = "en" + + # When + n_translated = await translate_sentences( + sentences, target_language, project=TEST_PROJECT, es_client=ESClient() + ) + + assert n_translated == 2 diff --git a/translation-worker/translation_worker/__init__.py b/translation-worker/translation_worker/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/translation-worker/translation_worker/activities.py b/translation-worker/translation_worker/activities.py new file mode 100644 index 0000000..a993736 --- /dev/null +++ b/translation-worker/translation_worker/activities.py @@ -0,0 +1,433 @@ +import asyncio +import os +from collections import defaultdict +from collections.abc import AsyncGenerator, Iterable +from functools import partial + +from aiostream.stream import chain + +from datashare_python.objects import Document +from datashare_python.types_ import ProgressRateHandler +from datashare_python.utils import ( + ActivityWithProgress, + activity_defn, + to_raw_progress, + async_batches, + batches, + before_and_after, + once, + find_device, +) +from elasticsearch._async.helpers import async_bulk +from icij_common.es import ( + BOOL, + COUNT, + DOC_LANGUAGE, + HITS, + ID_, + SOURCE, + TERM, + ESClient, + must_not, +) +from temporalio.client import Client + +from .objects import ( + TranslationConfig, + BatchSentence, + AsyncEsDocumentIteratorByLanguage, + SentencesBatch, + TranslationPackage, +) +from .constants import ( + TRANSLATION_BATCHING_ACTIVITY_NAME, + TRANSLATION_TRANSLATE_ACTIVITY_NAME, + TRANSLATION_DOC_SOURCES, +) +from .utils import ( + _get_translation_package, + _translate_as_list, + _has_language, + _language_alpha_codes, +) + + +class CreateTranslationBatches(ActivityWithProgress): + def __init__( + self, + es_client: ESClient, + temporal_client: Client, + event_loop: asyncio.AbstractEventLoop, + ): + super().__init__(temporal_client, event_loop) + self._es_client = es_client + + @activity_defn(name=TRANSLATION_BATCHING_ACTIVITY_NAME) + async def create_translation_batches( + self, project: str, target_language_alpha_code: str, batch_size: int + ) -> list[SentencesBatch]: + return await create_translation_batches( + project=project, + target_language_alpha_code=target_language_alpha_code, + batch_size=batch_size, + es_client=self._es_client, + ) + + +class TranslateDocs(ActivityWithProgress): + def __init__( + self, + es_client: ESClient, + temporal_client: Client, + event_loop: asyncio.AbstractEventLoop, + ): + super().__init__(temporal_client, event_loop) + self._es_client = es_client + + @activity_defn(name=TRANSLATION_TRANSLATE_ACTIVITY_NAME) + def translate_sentences( + self, + sentence_batch: SentencesBatch, + target_language_alpha_code: str, + *, + project: str, + config: TranslationConfig, + progress: ProgressRateHandler | None = None, + ) -> int: + return self._event_loop.run_until_complete( + translate_sentences( + sentence_batch, + target_language_alpha_code=target_language_alpha_code, + project=project, + es_client=self._es_client, + config=config, + progress=progress, + ) + ) + + +async def _process_language_group( + language_docs_iter: AsyncEsDocumentIteratorByLanguage, + batch_size: int, + target_language_alpha_code: str, +) -> AsyncGenerator[SentencesBatch, None]: + source_language_alpha_code = language_docs_iter.language + docs_iter = language_docs_iter.document_iter + translation_package = _get_translation_package( + source_language_alpha_code=source_language_alpha_code, + target_language_alpha_code=target_language_alpha_code, + ) + iter_sentences_partial = partial( + _iter_sentences, docs_iter=docs_iter, translation_package=translation_package + ) + + async for batch in async_batches(iter_sentences_partial, batch_size): + yield batch + + +async def _iter_sentences( + docs_iter: AsyncGenerator[dict, None], + translation_package: TranslationPackage, + source_language: str, +) -> AsyncGenerator[SentencesBatch, None]: + async for doc in docs_iter: + es_doc = Document.from_es(doc) + sentences = translation_package.sentencizer.get_sentences(es_doc.content) + sentences = [ + BatchSentence( + doc_id=es_doc.id, + root_document=es_doc.root_document, + sentence_index=i, + sentence=sentence, + ) + for i, sentence in enumerate(sentences) + ] + + yield SentencesBatch( + language=source_language, + sentences=sentences, + ) + + +async def _collect_language_batches( + language_docs: AsyncEsDocumentIteratorByLanguage, + batch_size: int, + target_language_alpha_code: str, +) -> list[SentencesBatch]: + result = [] + async for batch in _process_language_group( + language_docs, batch_size, target_language_alpha_code + ): + result.append(batch) + + return result + + +async def create_translation_batches( + *, + project: str, + target_language_alpha_code: str, + batch_size: int, + es_client: ESClient | None = None, +) -> list[SentencesBatch]: + """Split texts by sentence and batch them + + :param project: Project name + :param target_language_alpha_code: Target language + :param batch_size: Batch size + :param es_client: ES client + :return: list of SentencesBatches + """ + # Retrieve unprocessed docs. + docs_by_language = _untranslated_by_language( + es_client, project, target_language_alpha_code=target_language_alpha_code + ) + # We could set this to a smarter value + task_batch_size = batch_size * 4 + tasks = [] + + async for language_docs in docs_by_language: + tasks.append( + asyncio.create_task( + _collect_language_batches(language_docs, task_batch_size) + ) + ) + + results = await asyncio.gather(*tasks) + return [batch for group in results for batch in group] + + +async def translate_sentences( + sentences_batch: SentencesBatch, + target_language_alpha_code: str, + *, + project: str, + es_client: ESClient | None = None, + progress: ProgressRateHandler | None = None, # noqa: F821 + config: TranslationConfig | None = None, +) -> int: + """Translate sentence batches and reconstruct translations from original sentence ordering, + inserting them into ES + + :param sentences_batch: Sentences batch + :param target_language_alpha_code: Target language alpha2 code + :param project: Project name + :param es_client: ES client + :param progress: ProgressRateHandler + :param config: TranslationConfig | None + :return: number of documents translated + """ + if config is None: + config = TranslationConfig() + + # TODO: this should not happen + if not isinstance(config, TranslationConfig): + config = TranslationConfig.model_validate(config) + + n_sentences = len(sentences_batch.sentences) + if not n_sentences: + return 0 + + device = find_device(config.device) + + # very silly way that argos passes devices to ctranslate2 + os.environ["ARGOS_DEVICE_TYPE"] = str(device) + seen = 0 + # Convert the progress to a "raw" progress to update the progress incrementally + # rather than setting the progress rate + if progress is not None: + progress = to_raw_progress(progress, max_progress=n_sentences) + # We batch the data ourselves, ideally, we should use an async version of: + # https://huggingface.co/docs/datasets/v3.1.0/en/package_reference/main_classes#datasets.Dataset.from_generator + sentences = sentences_batch.sentences + source_language_alpha_code = sentences_batch.language + # unit here is a sentence + seen = 0 + total = len(sentences) * 2 + + # Translate + all_translations = [] + + translation_tasks = [ + asyncio.create_task( + _translate_batch( + sentence_batch, + source_language_alpha_code, + target_language_alpha_code, + config.max_parallel_batches, + config.beam_size, + config.num_hypotheses, + ) + ) + for sentence_batch in batches(sentences, batch_size=config.batch_size) + ] + + for task in asyncio.as_completed(translation_tasks): + translation_batch = await task + all_translations.extend(translation_batch) + + seen += len(translation_batch) + + if progress is not None: + await progress(int(seen / total)) + + all_translations = await asyncio.gather(*translation_tasks) + all_translations = [ + translation for batch in all_translations for translation in batch + ] + + # Reconstruct documents from sentences + reconstructed_docs = defaultdict(dict) + + for batch_sentence, translation in zip(sentences, all_translations): + key = batch_sentence.doc_id, batch_sentence.root_document + reconstructed_docs[key][batch_sentence.sentence_index] = translation + + # Combine sentences into translations and key with doc_id and root_document for insertion + translations_with_doc_ids_and_root_doc = [] + + for (doc_id, root_document), sentence_idx_mapping in reconstructed_docs.items(): + ordered_translation = "".join( + [translation for (_, translation) in sorted(sentence_idx_mapping.items())] + ) + seen += len(ordered_translation) + + translations_with_doc_ids_and_root_doc.append( + (doc_id, root_document, ordered_translation) + ) + + if progress is not None: + await progress(int(seen / total)) + + await _add_translation( + es_client, + translations_with_doc_ids_and_root_doc, + project, + target_language_alpha_code=target_language_alpha_code, + ) + # Return the number of classified documents + return n_sentences + + +# async +async def _translate_batch( + sentence_batch: tuple[BatchSentence, ...], + source_language_alpha_code: str, + target_language_alpha_code: str, + max_parallel_batches: int, + beam_size: int, + num_hypotheses: int, +) -> list[str]: + async with asyncio.Semaphore(max_parallel_batches): + return await asyncio.to_thread( + _translate_as_list, + sentence_batch, + source_language_alpha_code, + target_language_alpha_code, + beam_size, + num_hypotheses, + ) + + +async def _untranslated_by_language( + es_client: ESClient, project: str, target_language_alpha_code: str +) -> AsyncGenerator[AsyncEsDocumentIteratorByLanguage, None]: + # Get all documents that are not in the target language sorted by language + docs = _get_untranslated( + es_client, project, target_language_alpha_code=target_language_alpha_code + ) + while True: + try: + next_doc = await anext(aiter(docs)) + except StopAsyncIteration: + return + current_language = next_doc[SOURCE][DOC_LANGUAGE] + # Consume the iterator until we find a doc with a different language + language_docs, docs = before_and_after( + docs, partial(_has_language, language=current_language) + ) + # Yield all docs of the same language + grouped_docs = chain(once(next_doc), language_docs) + + source_language_alpha_code = _language_alpha_codes(current_language)[0] + + yield AsyncEsDocumentIteratorByLanguage( + language=source_language_alpha_code, + document_iter=grouped_docs, + ) + + +_SCRIPT_SOURCES = """ +if( !ctx._source.containsKey("content_translated") ) { + ctx._source.content_translated = new HashMap(); +} +ctx._source.content_translated[params.language] = params.translation; +""" + + +async def _add_translation( + es_client: ESClient, + translations: Iterable[tuple[Document, str]], + project: str, + *, + target_language_alpha_code: str, +) -> None: + actions = ( + { + "_op_type": "update", + "_index": project, + "_routing": root_document, + ID_: doc_id, + "script": { + "source": _SCRIPT_SOURCES, + "lang": "painless", + "params": { + "language": target_language_alpha_code, + "translation": translation, + }, + }, + } + for doc_id, root_document, translation in translations + ) + await async_bulk(es_client, actions, raise_on_error=True, refresh="wait_for") + + +def _untranslated_query(target_language_alpha_code: str) -> dict: + query = { + "query": { + BOOL: must_not( + { + "exists": { + "field": f"content_translated.{target_language_alpha_code}" + } + }, + {TERM: {DOC_LANGUAGE: target_language_alpha_code}}, + ) + } + } + return query + + +async def _get_untranslated( + es_client: ESClient, project: str, *, target_language_alpha_code: str +) -> AsyncGenerator[dict, None]: + async for res in es_client.poll_search_pages( + index=project, + body=_untranslated_query(target_language_alpha_code), + _source_includes=TRANSLATION_DOC_SOURCES, + sort=[f"{DOC_LANGUAGE}:asc", "_doc:asc"], + ): + for hit in res[HITS][HITS]: + yield hit + + +async def _count_untranslated( + es_client: ESClient, project: str, *, target_language_alpha_code: str +) -> int: + res = await es_client.count( + index=project, body=_untranslated_query(target_language_alpha_code) + ) + return res[COUNT] + + +ACTIVITIES = [CreateTranslationBatches, TranslateDocs] diff --git a/translation-worker/translation_worker/constants.py b/translation-worker/translation_worker/constants.py new file mode 100644 index 0000000..5334ad0 --- /dev/null +++ b/translation-worker/translation_worker/constants.py @@ -0,0 +1,17 @@ +from icij_common.es import DOC_CONTENT, DOC_ROOT_ID, DOC_LANGUAGE + +TRANSLATION_TASK_NAME = "translation" + +TRANSLATION_WORKER_NAME = "translation-worker" + +TRANSLATION_CPU_TASK_QUEUE = "translation-cpu-tasks" + +TRANSLATION_GPU_TASK_QUEUE = "translation-gpu-tasks" + +TRANSLATION_WORKFLOW_NAME = "translation" + +TRANSLATION_BATCHING_ACTIVITY_NAME = "translation-batches-activity" + +TRANSLATION_TRANSLATE_ACTIVITY_NAME = "translation-translate-activity" + +TRANSLATION_DOC_SOURCES = [DOC_CONTENT, DOC_ROOT_ID, DOC_LANGUAGE] diff --git a/translation-worker/translation_worker/objects.py b/translation-worker/translation_worker/objects.py new file mode 100644 index 0000000..e8eab00 --- /dev/null +++ b/translation-worker/translation_worker/objects.py @@ -0,0 +1,68 @@ +from dataclasses import dataclass +from enum import StrEnum +from typing import AsyncGenerator + +import pycountry +from argostranslate.sbd import ( + StanzaSentencizer, + MiniSBDSentencizer, + SpacySentencizerSmall, +) +from argostranslate.tokenizer import BPETokenizer, SentencePieceTokenizer +from ctranslate2 import Translator +from pydantic import Field, BaseModel + +from datashare_python.constants import CPU +from datashare_python.objects import WorkerResponse, BasePayload, Document +from .constants import ( + TRANSLATION_CPU_TASK_QUEUE, + TRANSLATION_GPU_TASK_QUEUE, + TRANSLATION_TASK_NAME, +) + + +class TaskQueues(StrEnum): + CPU = TRANSLATION_CPU_TASK_QUEUE + GPU = TRANSLATION_GPU_TASK_QUEUE + + +class TranslationConfig(BasePayload): + task: str = Field(default=TRANSLATION_TASK_NAME, frozen=True) + device: str = Field(default=CPU, frozen=True) + batch_size: int = 16 + max_parallel_batches: int = 8 + beam_size: int = 4 + num_hypotheses: int = 1 + + +class TranslationRequest(BasePayload): + texts: list[str] = Field(default_factory=list) + translation_config: TranslationConfig = Field(default_factory=TranslationConfig) + + +class TranslationResponse(WorkerResponse): + num_translations: int = 0 + + +class AsyncEsDocumentIteratorByLanguage(BaseModel): + language: str + document_iter: AsyncGenerator[dict, None] = Field(default_factory=list) + + +class BatchSentence(BaseModel): + doc_id: str + root_document: str + sentence_index: int + sentence: str + + +class SentencesBatch(BaseModel): + language: str + sentences: list[BatchSentence] = Field(default_factory=list) + + +class TranslationPackage(BaseModel): + tokenizer: SentencePieceTokenizer | BPETokenizer + sentencizer: StanzaSentencizer | MiniSBDSentencizer | SpacySentencizerSmall + model: Translator + target_prefix: str = "" diff --git a/translation-worker/translation_worker/utils.py b/translation-worker/translation_worker/utils.py new file mode 100644 index 0000000..4802290 --- /dev/null +++ b/translation-worker/translation_worker/utils.py @@ -0,0 +1,199 @@ +import logging +from typing import Generator + +import argostranslate +import pycountry +from argostranslate.package import Package +from argostranslate.translate import ( + get_installed_languages, + CachedTranslation, + PackageTranslation, +) +from icij_common.es import SOURCE, DOC_LANGUAGE +from spacy import Language + +from .objects import BatchSentence, TranslationPackage + +logger = logging.getLogger(__name__) + + +def _translate_as_list( + sentence_batch: tuple[BatchSentence, ...], + source_language_alpha_code: str, + target_language_alpha_code: str, + beam_size: int, + num_hypotheses: int, +) -> list[str]: + return list( + _translate( + [s.sentence for s in sentence_batch], + source_language_alpha_code, + target_language_alpha_code, + beam_size, + num_hypotheses, + ) + ) + + +def _translate( + sentence_batch: list[str], + source_language_alpha_code: str, + target_language_alpha_code: str, + beam_size: int, + num_hypotheses: int, +) -> Generator[str, None, None]: + translation_package = _get_translation_package( + source_language_alpha_code, target_language_alpha_code + ) + tokenized_sentences = [ + translation_package.tokenizer.encode(sentence) for sentence in sentence_batch + ] + + target_prefix = None + + if translation_package.target_prefix != "": + target_prefix = [[translation_package.target_prefix]] * len(tokenized_sentences) + + for translation in translation_package.translator.translate_batch( + tokenized_sentences, + target_prefix=target_prefix, + replace_unknowns=True, + max_batch_size=None, + batch_type="tokens", + beam_size=beam_size, + num_hypotheses=num_hypotheses, + length_penalty=0.2, + return_scores=True, + ): + decoded_translation = translation_package.tokenizer.decode(translation) + + if translation_package.target_prefix != "" and decoded_translation.startswith( + translation_package.target_prefix + ): + # Remove target prefix + decoded_translation = decoded_translation[ + len(decoded_translation.target_prefix) : + ] + + yield decoded_translation + + +def _has_language(doc: dict, language: str) -> bool: + return doc[SOURCE][DOC_LANGUAGE] == language + + +def _language_alpha_codes(*languages: str) -> list[str]: + alpha_codes = [] + + for language in languages: + alpha2 = pycountry.languages.get(name=language).alpha_2 + alpha_codes.append(alpha2) + + return alpha_codes + + +def _get_argos_package( + source_language_alpha_code: str, + target_language_alpha_code: str, +) -> Package | None: + available_packages = argostranslate.package.get_installed_packages() + return next( + filter( + lambda x: x.from_code == source_language_alpha_code + and x.to_code == target_language_alpha_code, + available_packages, + ) + ) + + +def _get_argos_languages( + *languages_to_find: str, +) -> tuple[Language, ...]: + if not isinstance(languages_to_find, list): + languages_to_find = [languages_to_find] + + languages = [] + available_languages = get_installed_languages() + + for language_to_find in languages_to_find: + language_result = next( + filter(lambda x: x.code == language_to_find, available_languages) + ) + + if language_result is None: + continue + + languages.append(language_result) + + return tuple(languages) + + +def _get_or_download_argos_languages( + source_language_alpha_code: str, + target_language_alpha_code: str, +) -> tuple[Language, ...]: + package = _get_argos_package(source_language_alpha_code, target_language_alpha_code) + + if package is None: + argostranslate.package.update_package_index() + available_packages = argostranslate.package.get_available_packages() + package_to_install = next( + filter( + lambda x: x.from_code == source_language_alpha_code + and x.to_code == target_language_alpha_code, + available_packages, + ) + ) + + if package_to_install is not None: + argostranslate.package.install_from_path(package_to_install.download()) + + _get_argos_package(source_language_alpha_code, target_language_alpha_code) + + return _get_argos_languages(source_language_alpha_code, target_language_alpha_code) + + +def _get_translation_package( + source_language_alpha_code: str, target_language_alpha_code: str +) -> TranslationPackage | None: + # Create batches per language + language_packages = _get_or_download_argos_languages( + source_language_alpha_code, target_language_alpha_code + ) + + if len(language_packages) < 2: + logger.exception( + f"Language model for {source_language_alpha_code} and/or {target_language_alpha_code} not available. " + f"Skipping translation." + ) + return None + + source_language_pkg, target_language_pkg = language_packages + # This is one of the weirder things about argos; it thinks of a translation + # from language to another as a functional mapping and so treats it as an object + argos_translation_package: PackageTranslation | None = ( + source_language_pkg.get_translation(target_language_pkg) + ) + + if argos_translation_package is None: + logger.exception( + f"No translation model exists from {source_language_alpha_code} to " + f"{target_language_alpha_code}. Skipping translation." + ) + return None + + # Another clumsy and non-transparent implementation by Argos; underlying is also + # mistyped for returns (should be PackageTranslation, is marked as ITranslation) + if isinstance(argos_translation_package, CachedTranslation): + argos_translation_package: PackageTranslation = ( + argos_translation_package.underlying + ) + + translation_package = TranslationPackage( + sentencizer=argos_translation_package.sentencizer, + tokenizer=argos_translation_package.pkg.tokenizer, + model=argos_translation_package.translator, + target_prefix=argos_translation_package.pkg.target_prefix, + ) + + return translation_package diff --git a/translation-worker/translation_worker/workflows.py b/translation-worker/translation_worker/workflows.py new file mode 100644 index 0000000..7db0265 --- /dev/null +++ b/translation-worker/translation_worker/workflows.py @@ -0,0 +1,69 @@ +import asyncio +from datetime import timedelta + +from temporalio import workflow + +from datashare_python.objects import WorkerResponse, WorkerResponseStatus + +with workflow.unsafe.imports_passed_through(): + from datashare_python.utils import ( + WorkflowWithProgress, + ) + + from .objects import TranslationRequest, TranslationResponse, TaskQueues + from .activities import CreateTranslationBatches, TranslateDocs + from .constants import TRANSLATION_WORKFLOW_NAME + from .utils import _language_alpha_codes + + +@workflow.defn(name=TRANSLATION_WORKFLOW_NAME) +class TranslationWorkflow(WorkflowWithProgress): + @workflow.run + async def run(self, payload: TranslationRequest) -> TranslationResponse: + target_language_alpha_code = _language_alpha_codes(payload.language)[0] + + try: + translation_batch_args = [ + payload.project, + target_language_alpha_code, + payload.config.translation.batch_size, + ] + # Create translation batches + translation_batches = await workflow.execute_activity( + CreateTranslationBatches.create_translation_batches, + args=translation_batch_args, + task_queue=TaskQueues.CPU, + start_to_close_timeout=timedelta(hours=1), + ) + # Translate + translation_args = [ + ( + b, + target_language_alpha_code, + payload.project, + payload.config.translation, + ) + for b in translation_batches + ] + translations_activities = [ + workflow.execute_activity( + TranslateDocs.translate_sentences, + args=args, + task_queue=TaskQueues.GPU, + start_to_close_timeout=timedelta(hours=1), + ) + for args in translation_args + ] + translations = await asyncio.gather(*translations_activities) + num_translations = sum(translations) + + return TranslationResponse( + status=WorkerResponse.SUCCESS, + num_translations=num_translations, + ) + except ValueError as e: + workflow.logger.exception(e) + return TranslationResponse(status=WorkerResponseStatus.ERROR, error=str(e)) + + +WORKFLOWS = [TranslationWorkflow] diff --git a/translation-worker/uv.lock b/translation-worker/uv.lock new file mode 100644 index 0000000..09b6b02 --- /dev/null +++ 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"worker_template/template/README.md" -"tests" = "worker_template/template/tests" +#"tests" = "worker_template/template/tests" "uv.lock" = "worker_template/template/uv.lock" "worker_template" = "worker_template/template/worker_template" diff --git a/worker-template/tests/test_utils.py b/worker-template/tests/test_utils.py deleted file mode 100644 index f7162e6..0000000 --- a/worker-template/tests/test_utils.py +++ /dev/null @@ -1,30 +0,0 @@ -from collections.abc import AsyncGenerator, AsyncIterable, AsyncIterator - -from aiostream.stream import chain -from worker_template.utils_ import before_and_after, once - - -async def _num_gen() -> AsyncGenerator[int, None]: - for i in range(10): - yield i // 3 - - -async def test_before_and_after() -> None: - # Given - async def group_by_iterator( - items: AsyncIterable[int], - ) -> AsyncIterator[AsyncIterator[int]]: - while True: - try: - next_item = await anext(aiter(items)) - except StopAsyncIteration: - return - gr, items = before_and_after(items, lambda x, next_i=next_item: x == next_i) - yield chain(once(next_item), gr) - - # When - grouped = [] - async for group in group_by_iterator(_num_gen()): - group = [item async for item in group] # noqa: PLW2901 - grouped.append(group) - assert grouped == [[0, 0, 0], [1, 1, 1], [2, 2, 2], [3]] diff --git a/worker-template/worker_template/classify.py b/worker-template/worker_template/classify.py new file mode 100644 index 0000000..079f2d8 --- /dev/null +++ b/worker-template/worker_template/classify.py @@ -0,0 +1,284 @@ +import asyncio +import logging +from collections.abc import AsyncGenerator, Generator, Iterable + +from datashare_python.objects import Document +from datashare_python.types_ import ProgressRateHandler +from datashare_python.utils import ( + ActivityWithProgress, + activity_defn, + to_raw_progress, + to_scaled_progress, +) +from elasticsearch._async.helpers import async_bulk +from icij_common.es import ( + BOOL, + DOC_CONTENT, + DOC_CONTENT_TRANSLATED, + DOC_LANGUAGE, + DOC_ROOT_ID, + HITS, + ID_, + MUST_NOT, + QUERY, + SHOULD, + TERM, + UPDATE, + ESClient, + and_query, + bulk_action, + has_id, +) +from temporalio import activity +from temporalio.client import Client +from transformers import Pipeline, pipeline + +from .objects_ import ClassificationConfig +from .utils_ import batches + + +class CreateClassificationBatches(ActivityWithProgress): + def __init__( + self, + es_client: ESClient, + temporal_client: Client, + event_loop: asyncio.AbstractEventLoop, + ): + super().__init__(temporal_client, event_loop) + self._es_client = es_client + + @activity_defn(name="create-classification-batches") + async def create_classification_batches( + self, project: str, target_language: str, config: ClassificationConfig + ) -> list[list[str]]: + return await create_classification_batches( + project=project, + language=target_language, + config=config, + es_client=self._es_client, + logger=activity.logger, + ) + + +class ClassifyDocs(ActivityWithProgress): + def __init__( + self, + es_client: ESClient, + temporal_client: Client, + event_loop: asyncio.AbstractEventLoop, + ): + super().__init__(temporal_client, event_loop) + self._es_client = es_client + + @activity_defn(name="classify-docs") + async def classify_docs( + self, + docs: list[str], + classified_language: str, + # *, + project: str, + config: ClassificationConfig, + progress: ProgressRateHandler | None = None, + ) -> int: + return await classify_docs( + docs, + classified_language=classified_language, + project=project, + es_client=self._es_client, + config=config, + progress=progress, + ) + + +async def create_classification_batches( + *, + project: str, + language: str, + config: ClassificationConfig, + es_client: ESClient, + progress: ProgressRateHandler | None = None, + logger: logging.Logger, +) -> list[list[str]]: + if not isinstance(config, ClassificationConfig): + config = ClassificationConfig.model_validate(config) + # Retrieve unprocessed docs. + model = config.model + unclassified = _get_unclassified( + es_client, project=project, language=language, model=model + ) + unclassified = [d[ID_] async for d in unclassified] + n_docs = len(unclassified) + if not n_docs: + logger.info("found not unclassified documents !") + return [] + logger.info("found %s unclassified documents !", n_docs) + fetch_unclassified_progress = 0.5 + if progress is not None: + await progress(fetch_unclassified_progress) + effective_batch_size = config.batch_size * config.batches_per_task + if progress is not None: + n_tasks = n_docs // config.batch_size + # We scale the progress to post incremental progress updates from 0 to n_tasks + progress = to_scaled_progress(progress, start=fetch_unclassified_progress) + progress = to_raw_progress(progress, max_progress=n_tasks) + logger.info("creating %s classification tasks...", effective_batch_size) + # We create classification tasks which will be picked up by the workers + clf_batches = [] + for batch in batches(unclassified, effective_batch_size): + clf_batches.append(batch) + if progress is not None: + await progress(len(clf_batches)) + logger.info("created all classification tasks !") + return clf_batches + + +_CLASSIF_DOC_SOURCES = [DOC_CONTENT, DOC_ROOT_ID, DOC_CONTENT_TRANSLATED, DOC_LANGUAGE] + + +async def classify_docs( + docs: list[str], + *, + classified_language: str, + project: str, + config: ClassificationConfig | None = None, + progress: ProgressRateHandler | None = None, + es_client: ESClient, +) -> int: + import torch # noqa: PLC0415 + + if config is None: + config = ClassificationConfig() + # TODO: fix this, we should have a ClassificationConfig hered + if not isinstance(config, ClassificationConfig): + config = ClassificationConfig.model_validate(config) + + n_docs = len(docs) + model = config.model + # Torch/macOS silicon stuff + device = None + if torch.backends.mps.is_available(): + device = torch.device("mps") + # Load the classification pipeline + pipe = pipeline(config.task, model=model, device=device) + model = pipe.model.name_or_path + # Convert the progress to a "raw" progress to update the progress incrementally + # from 0 to n_docs (rather than 0.0 to 1.0) + if progress is not None: + progress = to_raw_progress(progress, max_progress=n_docs) + seen = 0 + # We batch the data ourselves, ideally, we should use an async version of: + # https://huggingface.co/docs/datasets/v3.1.0/en/package_reference/main_classes#datasets.Dataset.from_generator + for batch in batches(docs, batch_size=config.batch_size): + batch_length = len(batch) + batch_docs = [] + async for page in es_client.poll_search_pages( + body={QUERY: has_id(batch)}, + _source_includes=_CLASSIF_DOC_SOURCES, + ): + batch_docs.extend([Document.from_es(doc) for doc in page[HITS][HITS]]) + contents = (_get_language_content(d, classified_language) for d in batch_docs) + batch_docs, contents = zip( + *( + (d, c) + for d, c in zip(batch_docs, contents, strict=False) + if c is not None + ), + strict=False, + ) + batch_docs = tuple(batch_docs) + # Offload CPU bound computation to a thread to avoid blocking the IO loop, + # classification will happen in numpy/python (outside of Python's GIL reach) + labels = await asyncio.to_thread(_classify_as_list, pipe, list(contents)) + # We add the classification results by updating the documents with new tags, + # this could also be done using: https://github.com/ICIJ/datashare-tarentula + await _add_classification_tags( + es_client, zip(batch_docs, labels, strict=False), project, model=model + ) + seen += batch_length + if progress is not None: + await progress(seen) + # Return the number of classified documents + return n_docs + + +def _classify(pipe: Pipeline, texts: list[str]) -> Generator[str, None, None]: + # In practice, we should chunk the text + for res in pipe(texts, padding=True, truncation=True): + yield res["label"] + + +def _classify_as_list(pipe: Pipeline, texts: list[str]) -> list[str]: + return list(_classify(pipe, texts)) + + +def _get_language_content(doc: Document, language: str) -> str | None: + if doc.language == language: + return doc.content + return doc.content_translated.get(language) + + +_SCRIPT_SOURCES = """ +if( !ctx._source.containsKey("tags") ) { + ctx._source.tags = []; +} +if( !ctx._source.tags.contains(params.tag) ) { + ctx._source.tags.add(params.tag); +} +""" + + +async def _add_classification_tags( + es_client: ESClient, + tags: Iterable[tuple[Document, str]], + project: str, + *, + model: str, +) -> None: + actions = ( + bulk_action( + op_type=UPDATE, + index=project, + id_=doc.id, + routing=doc.root_document, + script={ + "source": _SCRIPT_SOURCES, + "lang": "painless", + "params": {"tag": f"classified:{model}:{label}"}, + }, + ) + for doc, label in tags + ) + await async_bulk(es_client, actions, raise_on_error=True, refresh="wait_for") + + +def _unclassified_query(model: str, language: str) -> dict: + queries = ( + # Get documents which aren't tagged yet + {BOOL: {MUST_NOT: {"prefix": {"tags": {"value": f"classified:{model}:"}}}}}, + # And which are either in the model language or are translated in the model + # language + { + BOOL: { + SHOULD: [ + {"exists": {"field": f"{DOC_CONTENT_TRANSLATED}.{language}"}}, + {TERM: {DOC_LANGUAGE: language}}, + ] + } + }, + ) + query = and_query(*queries) + return query + + +async def _get_unclassified( + es_client: ESClient, project: str, *, language: str, model: str, **kwargs +) -> AsyncGenerator[dict, None]: + async for res in es_client.poll_search_pages( + index=project, + body=_unclassified_query(model, language=language), + sort="_doc:asc", + _source=False, + **kwargs, + ): + for hit in res[HITS][HITS]: + yield hit diff --git a/worker-template/worker_template/objects_.py b/worker-template/worker_template/objects_.py index e2ddb12..ccb94d8 100644 --- a/worker-template/worker_template/objects_.py +++ b/worker-template/worker_template/objects_.py @@ -6,13 +6,7 @@ ) from pydantic import BaseModel, Field - -class BasePayload(BaseModel): - model_config = icij_config() - - -class LowerCamelCaseModel(BaseModel): - model_config = merge_configs(icij_config(), lowercamel_case_config()) +from datashare_python.objects import BasePayload class ClassificationConfig(BasePayload): diff --git a/worker-template/worker_template/translate.py b/worker-template/worker_template/translate.py new file mode 100644 index 0000000..6e08a5e --- /dev/null +++ b/worker-template/worker_template/translate.py @@ -0,0 +1,273 @@ +import asyncio +from collections.abc import AsyncGenerator, Generator, Iterable +from functools import partial + +from aiostream.stream import chain +from datashare_python.objects import Document +from datashare_python.types_ import ProgressRateHandler +from datashare_python.utils import ( + ActivityWithProgress, + activity_defn, + to_raw_progress, +) +from elasticsearch._async.helpers import async_bulk +from icij_common.es import ( + BOOL, + COUNT, + DOC_CONTENT, + DOC_LANGUAGE, + DOC_ROOT_ID, + HITS, + ID_, + QUERY, + SOURCE, + TERM, + ESClient, + has_id, + must_not, +) +from temporalio.client import Client +from transformers import Pipeline, pipeline + +from .objects_ import TranslationConfig +from datashare_python.utils import async_batches, batches, before_and_after, once + + +class CreateTranslationBatches(ActivityWithProgress): + def __init__( + self, + es_client: ESClient, + temporal_client: Client, + event_loop: asyncio.AbstractEventLoop, + ): + super().__init__(temporal_client, event_loop) + self._es_client = es_client + + @activity_defn(name="create-translation-batches") + async def create_translation_batches( + self, project: str, target_language: str, batch_size: int + ) -> list[list[str]]: + return await create_translation_batches( + project=project, + target_language=target_language, + batch_size=batch_size, + es_client=self._es_client, + ) + + +class TranslateDocs(ActivityWithProgress): + def __init__( + self, + es_client: ESClient, + temporal_client: Client, + event_loop: asyncio.AbstractEventLoop, + ): + super().__init__(temporal_client, event_loop) + self._es_client = es_client + + @activity_defn(name="translate-docs") + def translate_docs( + self, + docs: list[str], + target_language: str, + *, + project: str, + config: TranslationConfig, + progress: ProgressRateHandler | None = None, + ) -> int: + return self._event_loop.run_until_complete( + translate_docs( + docs, + target_language=target_language, + project=project, + es_client=self._es_client, + config=config, + progress=progress, + ) + ) + + +async def create_translation_batches( + *, + project: str, + target_language: str, + batch_size: int, + es_client: ESClient | None = None, +) -> list[list[str]]: + # Retrieve unprocessed docs. + docs_by_language = _untranslated_by_language( + es_client, project, target_language=target_language + ) + # We could set this to a smarter value + task_batch_size = batch_size * 4 + batches = [] + # Iterate on all documents by language + async for language_docs in docs_by_language: + # Create batches per language + async for batch in async_batches(language_docs, task_batch_size): + doc_ids = [doc[ID_] for doc in batch] + batches.append(doc_ids) + return batches + + +_TRANSLATION_DOC_SOURCES = [DOC_CONTENT, DOC_ROOT_ID, DOC_LANGUAGE] + + +async def translate_docs( + docs: list[str], + target_language: str, + *, + project: str, + es_client: ESClient | None = None, + progress: ProgressRateHandler | None = None, # noqa: F821 + config: TranslationConfig | None = None, +) -> int: + import torch # noqa:PLC0415 + + if config is None: + config = TranslationConfig() + + # TODO: this should not happen + if not isinstance(config, TranslationConfig): + config = TranslationConfig.model_validate(config) + + n_docs = len(docs) + if not n_docs: + return 0 + # Torch/macOS silicon stuff + device = None + if torch.backends.mps.is_available(): + device = torch.device("mps") + seen = 0 + # Convert the progress to a "raw" progress to update the progress incrementally + # rather than setting the progress rate + if progress is not None: + progress = to_raw_progress(progress, max_progress=n_docs) + pipe = None + # We batch the data ourselves, ideally, we should use an async version of: + # https://huggingface.co/docs/datasets/v3.1.0/en/package_reference/main_classes#datasets.Dataset.from_generator + for batch in batches(docs, batch_size=config.batch_size): + batch_docs = [] + async for page in es_client.poll_search_pages( + body={QUERY: has_id(batch)}, + _source_includes=_TRANSLATION_DOC_SOURCES, + ): + batch_docs.extend(Document.from_es(doc) for doc in page[HITS][HITS]) + if pipe is None: + source_language = batch_docs[0].language + kwargs = config.to_pipeline_args( + source_language, target_language=target_language + ) + pipe = pipeline(device=device, **kwargs) + # Load the classification pipeline + contents = [d.content for d in batch_docs] + translations = await asyncio.to_thread(_translate_as_list, pipe, contents) + await _add_translation( + es_client, + zip(batch_docs, translations, strict=False), + project, + target_language=target_language, + ) + seen += len(batch) + if progress is not None: + await progress(seen) + # Return the number of classified documents + return n_docs + + +def _translate_as_list(pipe: Pipeline, texts: list[str]) -> list[str]: + return list(_translate(pipe, texts)) + + +def _translate(pipe: Pipeline, texts: list[str]) -> Generator[str, None, None]: + for res in pipe(texts): + yield res["translation_text"] + + +def _has_language(doc: dict, language: str) -> bool: + return doc[SOURCE][DOC_LANGUAGE] == language + + +async def _untranslated_by_language( + es_client: ESClient, project: str, target_language: str +) -> AsyncGenerator[AsyncGenerator[dict, None], None]: + # Get all documents that are not in the target language sorted by language + docs = _get_untranslated(es_client, project, target_language=target_language) + while True: + try: + next_doc = await anext(aiter(docs)) + except StopAsyncIteration: + return + current_language = next_doc[SOURCE][DOC_LANGUAGE] + # Consume the iterator until we find a doc with a different language + language_docs, docs = before_and_after( + docs, partial(_has_language, language=current_language) + ) + # Yield all docs of the same language + yield chain(once(next_doc), language_docs) + + +_SCRIPT_SOURCES = """ +if( !ctx._source.containsKey("content_translated") ) { + ctx._source.content_translated = new HashMap(); +} +ctx._source.content_translated[params.language] = params.translation; +""" + + +async def _add_translation( + es_client: ESClient, + translations: Iterable[tuple[Document, str]], + project: str, + *, + target_language: str, +) -> None: + actions = ( + { + "_op_type": "update", + "_index": project, + "_routing": doc.root_document, + ID_: doc.id, + "script": { + "source": _SCRIPT_SOURCES, + "lang": "painless", + "params": {"language": target_language, "translation": translation}, + }, + } + for doc, translation in translations + ) + await async_bulk(es_client, actions, raise_on_error=True, refresh="wait_for") + + +def _untranslated_query(target_language: str) -> dict: + query = { + "query": { + BOOL: must_not( + {"exists": {"field": f"content_translated.{target_language}"}}, + {TERM: {DOC_LANGUAGE: target_language}}, + ) + } + } + return query + + +async def _get_untranslated( + es_client: ESClient, project: str, *, target_language: str +) -> AsyncGenerator[dict, None]: + async for res in es_client.poll_search_pages( + index=project, + body=_untranslated_query(target_language), + _source_includes=[DOC_LANGUAGE], + sort=[f"{DOC_LANGUAGE}:asc", "_doc:asc"], + ): + for hit in res[HITS][HITS]: + yield hit + + +async def _count_untranslated( + es_client: ESClient, project: str, *, target_language: str +) -> int: + res = await es_client.count( + index=project, body=_untranslated_query(target_language) + ) + return res[COUNT] diff --git a/worker-template/worker_template/utils_.py b/worker-template/worker_template/utils_.py deleted file mode 100644 index 7c1baaa..0000000 --- a/worker-template/worker_template/utils_.py +++ /dev/null @@ -1,79 +0,0 @@ -import asyncio -import inspect -from collections.abc import ( - AsyncIterable, - AsyncIterator, - Awaitable, - Callable, - Generator, - Iterable, -) -from itertools import islice -from typing import TypeVar - -T = TypeVar("T") - -Predicate = Callable[[T], bool] | Callable[[T], Awaitable[bool]] - - -async def async_batches( - iterable: AsyncIterable[T], batch_size: int -) -> AsyncIterator[tuple[T]]: - it = aiter(iterable) - if batch_size < 1: - raise ValueError("n must be at least one") - while True: - batch = [] - while len(batch) < batch_size: - try: - batch.append(await anext(it)) - except StopAsyncIteration: - if batch: - yield tuple(batch) - return - yield tuple(batch) - - -def batches( - iterable: Iterable[T], batch_size: int -) -> Generator[tuple[T, ...], None, None]: - if batch_size < 1: - raise ValueError("n must be at least one") - it = iter(iterable) - while batch := tuple(islice(it, batch_size)): - yield batch - - -async def maybe_await(maybe_awaitable: Awaitable[T] | T) -> T: - if inspect.isawaitable(maybe_awaitable): - return await maybe_awaitable - return maybe_awaitable - - -async def once(item: T) -> AsyncIterator[T]: - yield item - - -def before_and_after( - iterable: AsyncIterable[T], predicate: Predicate[T] -) -> tuple[AsyncIterable[T], AsyncIterable[T]]: - transition = asyncio.get_event_loop().create_future() - - async def true_iterator() -> AsyncIterator[T]: - async for elem in iterable: - if await maybe_await(predicate(elem)): - yield elem - else: - transition.set_result(elem) - return - transition.set_exception(StopAsyncIteration) - - async def remainder_iterator() -> AsyncIterator[T]: - try: - yield await transition - except StopAsyncIteration: - return - async for elm in iterable: - yield elm - - return true_iterator(), remainder_iterator()