diff --git a/workers/translation-worker/pyproject.toml b/workers/translation-worker/pyproject.toml
index 7f8c9750..d482957e 100644
--- a/workers/translation-worker/pyproject.toml
+++ b/workers/translation-worker/pyproject.toml
@@ -32,11 +32,18 @@ worker_config_cls = "translation_worker.config:WORKER_CONFIG_CLS"
 inference = ['datashare-translation-worker[c2translate]']
 c2translate = [
   "argostranslate==1.11.0",
+  "datashare-translation-worker[sat]",
 ]
 torch = [
   "torch==2.11.0",
   "transformers==5.12.1",
   "accelerate==1.14.0",
+  "datashare-translation-worker[sat]",
+]
+# Sentence splitting for languages without sentence punctuation (Thai), runs on the
+# torch installed by the c2translate (through argostranslate) or torch extras
+sat = [
+  "wtpsplit==2.2.2",
 ]
 
 [tool.uv.sources]
diff --git a/workers/translation-worker/tests/test_activities.py b/workers/translation-worker/tests/test_activities.py
index 393ae796..4977beb9 100644
--- a/workers/translation-worker/tests/test_activities.py
+++ b/workers/translation-worker/tests/test_activities.py
@@ -30,6 +30,7 @@
 from translation_worker.config import TranslationWorkerConfig
 from translation_worker.objects import (
     ArgosTranslatorConfig,
+    DefaultSentenceSplitterConfig,
     TranslationModel,
     untranslated_query,
 )
@@ -71,11 +72,12 @@ async def poll_search_pages(
 
 class MockSentenceSplitter(SentenceSplitter):
     def __init__(self, splits: list[list[str]]):
+        super().__init__(DefaultSentenceSplitterConfig())
         self._splits = iter(splits)
 
     def load(self, language: Language) -> Self: ...
 
-    def split_sentences(self, text: str) -> list[str]:  # noqa: ARG002
+    def _split_sentences(self, text: str) -> list[str]:  # noqa: ARG002
         return next(self._splits)
 
     @classmethod
diff --git a/workers/translation-worker/tests/test_objects.py b/workers/translation-worker/tests/test_objects.py
index 57d63c23..ea055daa 100644
--- a/workers/translation-worker/tests/test_objects.py
+++ b/workers/translation-worker/tests/test_objects.py
@@ -2,17 +2,24 @@
 
 import pytest
 from datashare_python.conftest import TEST_PROJECT
+from datashare_python.objects import DatashareLanguage, Language
 from translation_worker.objects import (
     ArgosSentenceSplitterConfig,
     ArgosSentencizer,
     ArgosTranslatorConfig,
+    BaseTranslatorConfig,
+    DefaultSentenceSplitterConfig,
     DocId,
     DocumentSearchQuery,
+    HunyuanMtTranslatorConfig,
+    RulesSentenceSplitterConfig,
+    SaTSentenceSplitterConfig,
+    SentenceSplitterConfig,
     TranslationArgs,
     TranslationConfig,
 )
 
-from .conftest import DS_ENGLISH
+from .conftest import DS_CHINESE, DS_ENGLISH
 
 
 def test_config_deser() -> None:
@@ -31,6 +38,114 @@ def test_config_deser() -> None:
     assert deser == expected
 
 
+def test_config_deser_defaults() -> None:
+    # When
+    deser = TranslationConfig.model_validate({})
+    # Then
+    assert deser.sentence_splitter == RulesSentenceSplitterConfig()
+    assert deser.language_sentence_splitters == {"th": SaTSentenceSplitterConfig()}
+
+
+def test_config_deser_language_sentence_splitters() -> None:
+    # Given
+    config = {
+        "languageSentenceSplitters": {
+            "km": {"model": "SAT", "modelRef": "sat-12l-sm"},
+            "GERMAN": {"model": "ARGOS"},
+        }
+    }
+    # When
+    deser = TranslationConfig.model_validate(config)
+    # Then
+    expected = {
+        "km": SaTSentenceSplitterConfig(model_ref="sat-12l-sm"),
+        "GERMAN": ArgosSentenceSplitterConfig(),
+    }
+    assert deser.language_sentence_splitters == expected
+    assert TranslationConfig.model_validate(deser.model_dump()) == deser
+
+
+@pytest.mark.parametrize(
+    ("overrides", "language", "expected"),
+    [
+        (None, DatashareLanguage("THAI"), SaTSentenceSplitterConfig()),
+        (None, "th", SaTSentenceSplitterConfig()),
+        (None, DS_ENGLISH, RulesSentenceSplitterConfig()),
+        (None, DS_CHINESE, RulesSentenceSplitterConfig()),
+        (
+            {"zh": DefaultSentenceSplitterConfig()},
+            DS_CHINESE,
+            DefaultSentenceSplitterConfig(),
+        ),
+        (
+            {"zh": DefaultSentenceSplitterConfig()},
+            "zh-Hant",
+            DefaultSentenceSplitterConfig(),
+        ),
+        (
+            {"ENGLISH": SaTSentenceSplitterConfig()},
+            "en-US",
+            SaTSentenceSplitterConfig(),
+        ),
+        ({}, DatashareLanguage("THAI"), RulesSentenceSplitterConfig()),
+    ],
+)
+def test_config_sentence_splitter_for(
+    overrides: dict | None, language: Language, expected: SentenceSplitterConfig
+) -> None:
+    # Given
+    config = TranslationConfig()
+    if overrides is not None:
+        config = TranslationConfig(language_sentence_splitters=overrides)
+    # When
+    splitter_config = config.sentence_splitter_for(language)
+    # Then
+    assert splitter_config.model_copy(update={"max_length": None}) == expected
+
+
+@pytest.mark.parametrize(
+    ("splitter", "translator", "expected_max_length"),
+    [
+        (RulesSentenceSplitterConfig(), ArgosTranslatorConfig(), 1024),
+        (RulesSentenceSplitterConfig(), HunyuanMtTranslatorConfig(), 1024),
+        (
+            RulesSentenceSplitterConfig(),
+            HunyuanMtTranslatorConfig(max_new_tokens=512),
+            256,
+        ),
+        # explicit lengths take precedence
+        (
+            RulesSentenceSplitterConfig(max_length=100),
+            HunyuanMtTranslatorConfig(max_new_tokens=512),
+            100,
+        ),
+    ],
+)
+def test_config_sentence_splitter_for_max_length(
+    splitter: SentenceSplitterConfig,
+    translator: BaseTranslatorConfig,
+    expected_max_length: int,
+) -> None:
+    # Given
+    config = TranslationConfig(sentence_splitter=splitter, translator=translator)
+    # When
+    splitter_config = config.sentence_splitter_for(DS_CHINESE)
+    # Then
+    assert splitter_config.max_length == expected_max_length
+
+
+def test_config_sentence_splitter_for_language_max_length() -> None:
+    # Given
+    config = TranslationConfig(
+        language_sentence_splitters={"zh": SaTSentenceSplitterConfig()},
+        translator=HunyuanMtTranslatorConfig(max_new_tokens=300),
+    )
+    # When
+    splitter_config = config.sentence_splitter_for(DS_CHINESE)
+    # Then
+    assert splitter_config == SaTSentenceSplitterConfig(max_length=150)
+
+
 _NO_ES_TRANSLATED_CONTENT = {
     "bool": {
         "must_not": [
diff --git a/workers/translation-worker/tests/test_sentence_splitters.py b/workers/translation-worker/tests/test_sentence_splitters.py
new file mode 100644
index 00000000..83635b7c
--- /dev/null
+++ b/workers/translation-worker/tests/test_sentence_splitters.py
@@ -0,0 +1,219 @@
+# ruff: noqa: RUF001
+import sys
+from unittest.mock import MagicMock, patch
+
+import pytest
+from translation_worker.objects import (
+    DEFAULT_SAT_MODEL_REF,
+    DefaultSentenceSplitterConfig,
+    RulesSentenceSplitterConfig,
+    SaTSentenceSplitterConfig,
+    TorchDevice,
+)
+from translation_worker.processors import cap_length
+from translation_worker.sentence_splitters import (
+    DefaultSentenceSplitter,
+    RulesSentenceSplitter,
+    SaTSentenceSplitter,
+)
+
+from tests.conftest import DS_ENGLISH
+
+
+@pytest.mark.parametrize(
+    ("text", "expected"),
+    [
+        ("", []),
+        ("No terminator here", ["No terminator here"]),
+        (
+            "Hello world. How are you? I'm fine!",
+            ["Hello world.", "How are you?", "I'm fine!"],
+        ),
+        # CJK terminators don't need a following space
+        ("你好。今天天气很好！你呢？", ["你好。", "今天天气很好！", "你呢？"]),
+        ("他说：“走吧。”然后离开了。", ["他说：“走吧。”", "然后离开了。"]),
+        ("東京に行きました。楽しかった。", ["東京に行きました。", "楽しかった。"]),
+        # closing quotes stay with their sentence
+        ('He said "go." Then he left.', ['He said "go."', "Then he left."]),
+        # decimals, urls
+        (
+            "It costs 3.5 dollars. See example.com now.",
+            ["It costs 3.5 dollars.", "See example.com now."],
+        ),  # noqa: E501
+        # non-latin terminators
+        ("यह एक वाक्य है। यह दूसरा है।", ["यह एक वाक्य है।", "यह दूसरा है।"]),
+        ("یہ پہلا جملہ ہے۔ یہ دوسرا ہے۔", ["یہ پہلا جملہ ہے۔", "یہ دوسرا ہے۔"]),
+        ("ပထမစာကြောင်း။ ဒုတိယစာကြောင်း။", ["ပထမစာကြောင်း။", "ဒုတိယစာကြောင်း။"]),
+        ("ប្រយោគទីមួយ។ ប្រយោគទីពីរ។", ["ប្រយោគទីមួយ។", "ប្រយោគទីពីរ។"]),
+        ("བཀྲ་ཤིས་བདེ་ལེགས། ཐུགས་རྗེ་ཆེ།", ["བཀྲ་ཤིས་བདེ་ལེགས།", "ཐུགས་རྗེ་ཆེ།"]),
+        ("هل أنت بخير؟ نعم.", ["هل أنت بخير؟", "نعم."]),
+        # words ending with a letter after a combining mark
+        ("ते आले आहेत. ते गेले.", ["ते आले आहेत.", "ते गेले."]),
+    ],
+)
+def test_rules_splitter_split_sentences(text: str, expected: list[str]) -> None:
+    # Given
+    splitter = RulesSentenceSplitter(RulesSentenceSplitterConfig())
+    # When
+    sentences = splitter.split_sentences(text)
+    # Then
+    assert sentences == expected
+
+
+@pytest.mark.parametrize(
+    ("text", "expected"),
+    [
+        # known abbreviations
+        ("Dr. Ehud Ur spoke. He left.", ["Dr. Ehud Ur spoke.", "He left."]),
+        (
+            "Prof. Kim und Hr. Weber kamen. Dann gingen sie.",
+            ["Prof. Kim und Hr. Weber kamen.", "Dann gingen sie."],
+        ),  # noqa: E501
+        (
+            "Он пришёл, ул. Ленина. Потом ушёл.",
+            ["Он пришёл, ул. Ленина.", "Потом ушёл."],
+        ),  # noqa: E501
+        # initials
+        (
+            "John F. Kennedy spoke. Then he left.",
+            ["John F. Kennedy spoke.", "Then he left."],
+        ),  # noqa: E501
+        # short dotted abbreviations
+        (
+            "Die Studie, d.h. Die Kontrolle, lief. Dann endete sie.",
+            ["Die Studie, d.h. Die Kontrolle, lief.", "Dann endete sie."],
+        ),  # noqa: E501
+        ("The U.S. Army came. It left.", ["The U.S. Army came.", "It left."]),
+        (
+            "Он вернулся, т.е. Иван вернулся. Потом ушёл.",
+            ["Он вернулся, т.е. Иван вернулся.", "Потом ушёл."],
+        ),  # noqa: E501
+        # lowercase continuation
+        (
+            "Studie, z.B. die Kontrolle. Dann nichts.",
+            ["Studie, z.B. die Kontrolle.", "Dann nichts."],
+        ),  # noqa: E501
+        ("Wait... what happened? Nothing.", ["Wait... what happened?", "Nothing."]),
+        ('"Really?" she asked. Yes.', ['"Really?" she asked.', "Yes."]),
+        # words commonly ending sentences shouldn't be treated as abbreviations
+        ("They said no. Then they left.", ["They said no.", "Then they left."]),
+    ],
+)
+def test_rules_splitter_should_not_split_on_abbreviations(
+    text: str, expected: list[str]
+) -> None:
+    # Given
+    splitter = RulesSentenceSplitter(RulesSentenceSplitterConfig())
+    # When
+    sentences = splitter.split_sentences(text)
+    # Then
+    assert sentences == expected
+
+
+@pytest.mark.parametrize(
+    ("sentences", "max_length", "expected"),
+    [
+        (["a" * 20], None, ["a" * 20]),
+        # short
+        (["short one", "two"], 9, ["short one", "two"]),
+        # prefers clause punctuation over whitespace
+        (["aaa bbb, ccc ddd eee"], 14, ["aaa bbb,", "ccc ddd eee"]),
+        (["一二三四五，六七八九十。"], 8, ["一二三四五，", "六七八九十。"]),
+        # falls back to whitespace
+        (["aaa bbb ccc ddd"], 10, ["aaa bbb", "ccc ddd"]),
+        # ignores breaks in the first half of the window
+        (["a, bbbbbbbbbbbb"], 8, ["a, bbbbb", "bbbbbbb"]),
+        # hard cuts to text without breaks
+        (["一二三四五六七八九十"], 4, ["一二三四", "五六七八", "九十"]),
+    ],
+)
+def test_cap_length(
+    sentences: list[str], max_length: int | None, expected: list[str]
+) -> None:
+    # When
+    capped = cap_length(sentences, max_length)
+    # Then
+    assert capped == expected
+    if max_length is not None:
+        assert all(len(s) <= max_length for s in capped)
+
+
+def test_splitter_caps_sentence_length() -> None:
+    # Given
+    config = DefaultSentenceSplitterConfig(max_length=10)
+    splitter = DefaultSentenceSplitter(config)
+    # When
+    sentences = splitter.split_sentences("一二三四五六七八九十一二三")
+    # Then
+    assert sentences == ["一二三四五六七八九十", "一二三"]
+
+
+def test_sat_splitter_split_sentences_batch_caps_sentence_length() -> None:
+    # Given
+    splitter = SaTSentenceSplitter(SaTSentenceSplitterConfig(max_length=4))
+    splitter._sat = MagicMock()
+    splitter._sat.split.return_value = iter([["一二三四五六"], ["七"]])
+    # When
+    sentences = splitter.split_sentences_batch(["一二三四五六", "七"])
+    # Then
+    assert sentences == [["一二三四", "五六"], ["七"]]
+
+
+def _dummy_sat_modules(*, cuda_available: bool) -> tuple[dict, MagicMock]:
+    torch = MagicMock()
+    torch.cuda.is_available.return_value = cuda_available
+    wtpsplit = MagicMock()
+    return {"torch": torch, "wtpsplit": wtpsplit}, wtpsplit
+
+
+@pytest.mark.parametrize(
+    ("device", "cuda_available", "expected_on_gpu"),
+    [
+        (None, True, True),
+        (None, False, False),
+        (TorchDevice.CPU, True, False),
+        (TorchDevice.GPU, True, True),
+    ],
+)
+def test_sat_splitter_load(
+    device: TorchDevice | None,
+    cuda_available: bool,  # noqa: FBT001
+    expected_on_gpu: bool,  # noqa: FBT001
+) -> None:
+    # Given
+    config = SaTSentenceSplitterConfig(device=device)
+    splitter = SaTSentenceSplitter(config)
+    modules, wtpsplit = _dummy_sat_modules(cuda_available=cuda_available)
+    # When
+    with patch.dict(sys.modules, modules):
+        splitter.load(DS_ENGLISH)
+    # Then
+    wtpsplit.SaT.assert_called_once_with(DEFAULT_SAT_MODEL_REF)
+    sat = wtpsplit.SaT.return_value
+    if expected_on_gpu:
+        sat.half.return_value.to.assert_called_once_with(TorchDevice.GPU)
+    else:
+        sat.half.assert_not_called()
+
+
+def test_sat_splitter_split_sentences_strips_and_drops_empty() -> None:
+    # Given
+    splitter = SaTSentenceSplitter(SaTSentenceSplitterConfig())
+    splitter._sat = MagicMock()
+    splitter._sat.split.return_value = ["ประโยคแรก ", " ", "ประโยคที่สอง"]
+    # When
+    sentences = splitter.split_sentences("ประโยคแรก ประโยคที่สอง")
+    # Then
+    assert sentences == ["ประโยคแรก", "ประโยคที่สอง"]
+
+
+def test_sat_splitter_split_sentences_batch() -> None:
+    # Given
+    splitter = SaTSentenceSplitter(SaTSentenceSplitterConfig())
+    splitter._sat = MagicMock()
+    splitter._sat.split.return_value = iter([["a. ", "b."], ["c."]])
+    # When
+    sentences = splitter.split_sentences_batch(["a. b.", "c."])
+    # Then
+    splitter._sat.split.assert_called_once_with(["a. b.", "c."])
+    assert sentences == [["a.", "b."], ["c."]]
diff --git a/workers/translation-worker/translation_worker/__init__.py b/workers/translation-worker/translation_worker/__init__.py
index b3e15aff..2fe5b364 100644
--- a/workers/translation-worker/translation_worker/__init__.py
+++ b/workers/translation-worker/translation_worker/__init__.py
@@ -2,8 +2,15 @@
 
 with workflow.unsafe.imports_passed_through():
     try:
-        from .sentence_splitters import ArgosSentenceSplitter, DefaultSentenceSplitter
+        from .sentence_splitters import (
+            ArgosSentenceSplitter,
+            DefaultSentenceSplitter,
+            RulesSentenceSplitter,
+            SaTSentenceSplitter,
+        )
     except ImportError:
         ArgosSentenceSplitter = None
         DefaultSentenceSplitter = None
+        RulesSentenceSplitter = None
+        SaTSentenceSplitter = None
     from .translators import ArgosTranslator, HunyuanMtTranslator  # noqa: F401
diff --git a/workers/translation-worker/translation_worker/activities.py b/workers/translation-worker/translation_worker/activities.py
index c014db9b..e8cb9238 100644
--- a/workers/translation-worker/translation_worker/activities.py
+++ b/workers/translation-worker/translation_worker/activities.py
@@ -108,10 +108,11 @@ async def translate_docs(
         translator_key = config_cache_key(config.translator)
         translator_cache = lifespan_translator_cache()
         # SBD, then load the splitter
+        splitter_config = config.sentence_splitter_for(source)
         splitter_factory = partial(
-            _load_splitter_from_config, config=config.sentence_splitter, language=source
+            _load_splitter_from_config, config=splitter_config, language=source
         )
-        splitter_key = config_cache_key(config.sentence_splitter)
+        splitter_key = config_cache_key(splitter_config)
         splitter_cache = lifespan_sentence_splitter_cache()
         with translator_cache.get_or_cache_resource(
             translator_key, translator_factory
diff --git a/workers/translation-worker/translation_worker/objects.py b/workers/translation-worker/translation_worker/objects.py
index df863093..fe2dc9f3 100644
--- a/workers/translation-worker/translation_worker/objects.py
+++ b/workers/translation-worker/translation_worker/objects.py
@@ -1,7 +1,14 @@
 from enum import StrEnum
-from typing import TYPE_CHECKING, Any, ClassVar
-
-from datashare_python.objects import DatashareModel, Language, TaskArgs
+from typing import TYPE_CHECKING, Annotated, Any, ClassVar
+
+import langcodes
+from datashare_python.objects import (
+    DatashareLanguage,
+    DatashareModel,
+    IETFLanguage,
+    Language,
+    TaskArgs,
+)
 from icij_common.es import (
     DOC_CONTENT_TRANSLATED,
     QUERY,
@@ -29,6 +36,8 @@ class TorchDevice(StrEnum):
 class SentenceSplitterModel(StrEnum):
     ARGOS = "ARGOS"
     DEFAULT = "DEFAULT"
+    RULES = "RULES"
+    SAT = "SAT"
 
 
 class TranslationModel(StrEnum):
@@ -73,10 +82,16 @@ def untranslated_query(target: Language) -> dict:
 class _BaseProcessorConfig(DatashareModel, RegistrableConfig): ...
 
 
+DEFAULT_MAX_SENTENCE_LENGTH = 1024
+
+
 class SentenceSplitterConfig(_BaseProcessorConfig):
     registry_key: ClassVar[str] = Field(frozen=True, default="model")
     model: ClassVar[SentenceSplitterModel]
 
+    # max number of characters per sentence
+    max_length: int | None = Field(default=None, gt=0)
+
 
 class DefaultSentenceSplitterConfig(SentenceSplitterConfig):
     model: ClassVar[SentenceSplitterModel] = Field(
@@ -92,10 +107,33 @@ class ArgosSentenceSplitterConfig(SentenceSplitterConfig):
     sentencizer: ArgosSentencizer = ArgosSentencizer.MINI_SBD
 
 
+class RulesSentenceSplitterConfig(SentenceSplitterConfig):
+    model: ClassVar[SentenceSplitterModel] = Field(
+        frozen=True, default=SentenceSplitterModel.RULES
+    )
+
+
+DEFAULT_SAT_MODEL_REF = "sat-3l-sm"
+
+
+class SaTSentenceSplitterConfig(SentenceSplitterConfig):
+    model: ClassVar[SentenceSplitterModel] = Field(
+        frozen=True, default=SentenceSplitterModel.SAT
+    )
+
+    model_ref: str = DEFAULT_SAT_MODEL_REF
+    device: TorchDevice | None = None
+
+
 class BaseTranslatorConfig(_BaseProcessorConfig):
     registry_key: ClassVar[str] = Field(frozen=True, default="model")
     model: ClassVar[TranslationModel]
 
+    @property
+    def max_sentence_length(self) -> int:
+        """Max number of source characters per sentence"""
+        return DEFAULT_MAX_SENTENCE_LENGTH
+
 
 _SentenceSplitterConfig = tagged_union(
     SentenceSplitterConfig.__subclasses__(), lambda t: t.model.default
@@ -130,6 +168,11 @@ class HunyuanMtTranslatorConfig(BaseTranslatorConfig):
     torch_dtype: str = "float32"
     device_map: str = "auto"
 
+    @property
+    def max_sentence_length(self) -> int:
+        # keep a 2x margin so that translations aren't truncated
+        return max(1, self.max_new_tokens // 2)
+
 
 TranslatorConfig = tagged_union(
     BaseTranslatorConfig.__subclasses__(), lambda t: t.model.default
@@ -137,20 +180,62 @@ class HunyuanMtTranslatorConfig(BaseTranslatorConfig):
 translator_discriminator = make_enum_discriminator("model", TranslationModel)
 
 
+def language_subtag(language: Language) -> str:
+    """Normalize a Datashare or IETF language to its IETF language subtag.
+
+    :param language: Datashare language name (``THAI``) or IETF tag (``th``)
+    :return: the language subtag, e.g. ``th``
+    """
+    if isinstance(language, DatashareLanguage):
+        return langcodes.get(language.alpha3).language
+    return langcodes.get(language).language
+
+
+def _default_language_sentence_splitters() -> dict[Language, SentenceSplitterConfig]:
+    # thai doesn't mark sentence ends with punctuation, needs special splitter
+    return {IETFLanguage("th"): SaTSentenceSplitterConfig()}
+
+
 class TranslationConfig(DatashareModel):
     sentence_splitter: _SentenceSplitterConfig = Field(
         discriminator=Discriminator(splitter_discriminator),
-        default_factory=DefaultSentenceSplitterConfig,
+        default_factory=RulesSentenceSplitterConfig,
     )
+    # per-source language overrides
+    language_sentence_splitters: dict[
+        Language,
+        Annotated[_SentenceSplitterConfig, Discriminator(splitter_discriminator)],
+    ] = Field(default_factory=_default_language_sentence_splitters)
     translator: TranslatorConfig = Field(
         discriminator=Discriminator(translator_discriminator),
         default_factory=ArgosTranslatorConfig,
     )
 
-    def to_sentence_splitter(self) -> "SentenceSplitter":
+    def sentence_splitter_for(self, language: Language) -> SentenceSplitterConfig:
+        """Get the sentence splitter config of a source language.
+
+        :param language: the source language
+        :return: the language's splitter config, or else the default one, with its
+            ``max_length`` derived from the translator config when not set
+        """
+        subtag = language_subtag(language)
+        config = next(
+            (
+                config
+                for lang, config in self.language_sentence_splitters.items()
+                if language_subtag(lang) == subtag
+            ),
+            self.sentence_splitter,
+        )
+        if config.max_length is None:
+            max_length = self.translator.max_sentence_length
+            config = config.model_copy(update={"max_length": max_length})
+        return config
+
+    def to_sentence_splitter(self, language: Language) -> "SentenceSplitter":
         from .processors import SentenceSplitter  # noqa: PLC0415
 
-        return SentenceSplitter.from_config(self.sentence_splitter)
+        return SentenceSplitter.from_config(self.sentence_splitter_for(language))
 
     def to_translator(self) -> "Translator":
         from .processors import Translator  # noqa: PLC0415
diff --git a/workers/translation-worker/translation_worker/processors.py b/workers/translation-worker/translation_worker/processors.py
index 478c7a46..8f7cc656 100644
--- a/workers/translation-worker/translation_worker/processors.py
+++ b/workers/translation-worker/translation_worker/processors.py
@@ -1,4 +1,5 @@
 import logging
+import re
 import sys
 from abc import abstractmethod
 from collections.abc import Iterable
@@ -11,17 +12,69 @@
 
 if TYPE_CHECKING:
     from .config import BaseTranslatorConfig
-    from .objects import Language
+    from .objects import Language, SentenceSplitterConfig
 
 logger = logging.getLogger(__name__)
 
 
+_CLAUSE_BREAK = re.compile(r"[,;:，；：、]+")
+_WHITESPACE = re.compile(r"\s+")
+
+
+def cap_length(sentences: list[str], max_length: int | None) -> list[str]:
+    """Cut sentences longer than ``max_length`` characters into chunks.
+
+    Chunks end at last punctuation or whitespace. Sentences without either
+    are split at exactly ``max_length`` characters as a fallback.
+
+    :param sentences: split sentences
+    :param max_length: maximum number of characters per sentence or ``None`` for no cap
+    :return: sentences no longer than ``max_length`` characters
+    """
+    if max_length is None:
+        return sentences
+    return [chunk for s in sentences for chunk in _cap_sentence_length(s, max_length)]
+
+
+def _cap_sentence_length(sentence: str, max_length: int) -> Iterable[str]:
+    while len(sentence) > max_length:
+        cut = _break_position(sentence, max_length)
+        chunk, sentence = sentence[:cut].strip(), sentence[cut:].strip()
+        if chunk:
+            yield chunk
+    if sentence:
+        yield sentence
+
+
+def _break_position(sentence: str, max_length: int) -> int:
+    min_cut = max_length // 2
+    for pattern in (_CLAUSE_BREAK, _WHITESPACE):
+        breaks = list(pattern.finditer(sentence, min_cut, max_length))
+        if breaks:
+            return breaks[-1].end()
+    return max_length
+
+
 class SentenceSplitter(RegistrableFromConfig):
-    @abstractmethod
-    def split_sentences(self, text: str) -> list[str]: ...  # noqa: F821
+    def __init__(self, config: "SentenceSplitterConfig"):
+        self._config = config
+
+    @final
+    def split_sentences(self, text: str) -> list[str]:
+        return cap_length(self._split_sentences(text), self._config.max_length)
 
+    @final
     def split_sentences_batch(self, batch: list[str]) -> list[list[str]]:
-        return [self.split_sentences(t) for t in batch]
+        return [
+            cap_length(sentences, self._config.max_length)
+            for sentences in self._split_sentences_batch(batch)
+        ]
+
+    @abstractmethod
+    def _split_sentences(self, text: str) -> list[str]: ...
+
+    def _split_sentences_batch(self, batch: list[str]) -> list[list[str]]:
+        return [self._split_sentences(t) for t in batch]
 
     @final
     @contextmanager
diff --git a/workers/translation-worker/translation_worker/sentence_splitters.py b/workers/translation-worker/translation_worker/sentence_splitters.py
index 06469445..1a969b8d 100644
--- a/workers/translation-worker/translation_worker/sentence_splitters.py
+++ b/workers/translation-worker/translation_worker/sentence_splitters.py
@@ -1,4 +1,5 @@
 import gc
+import re
 from typing import Self
 
 from datashare_python.objects import DatashareLanguage
@@ -8,30 +9,85 @@
     ArgosSentenceSplitterConfig,
     DefaultSentenceSplitterConfig,
     Language,
+    RulesSentenceSplitterConfig,
+    SaTSentenceSplitterConfig,
     SentenceSplitterModel,
+    TorchDevice,
 )
 from .processors import SentenceSplitter
 
+_CLOSING = "\"'”’」』）)»›\u200b"
+_TERMINATOR = re.compile(rf"[。！？]+[{_CLOSING}]*|[.!?…។။།༎।॥۔؟|]+[{_CLOSING}]*(?=\s)")
+_CASED_TERMINATORS = ".!?…"
+_NEXT_CHAR = re.compile(r"\s*(\S)")
+_PREVIOUS_TOKEN = re.compile(r"\w+(?:\.\w+)*$")
+_MAX_ABBREVIATION_LEN = 16
+_DOTTED_ABBREVIATION = re.compile(r"(?:\w{1,2}\.)+\w{1,2}")
+_ABBREVIATIONS = frozenset(
+    abbreviation
+    for abbreviations in (
+        # en
+        "mr mrs ms dr prof sr jr st mt vs fig nr vol approx dept inc ltd corp gen gov"
+        " rep lt col capt sgt rev hon",
+        # de
+        "hr frl bzw ggf vgl evtl ca mio mrd tel str abs bd jh jhd",
+        # fr, es, pt, it, nl
+        "mme mlle mgr sra srta dra ud uds av avda pág núm sig sigg dott ing avv dhr"
+        " mevr bijv blz",
+        # pl, cs, tr, id, ms, tl
+        "np tzw tj ul al inż godz św např tzv doç bkz sdr bpk jl hlm gng bb",
+        # ru, uk, kk, mn
+        "г гг др им ул стр см рис англ тыс млн млрд руб ст ім вул тис грн",
+    )
+    for abbreviation in abbreviations.split()
+)
+
+
+def _is_abbreviation(text: str, end: int) -> bool:
+    start = max(0, end - _MAX_ABBREVIATION_LEN)
+    token = _PREVIOUS_TOKEN.search(text, start, end)
+    if token is None:
+        return False
+    token = token.group()
+    if len(token) == 1 and token.isupper():
+        return True
+    return (
+        _DOTTED_ABBREVIATION.fullmatch(token) is not None
+        or token.casefold() in _ABBREVIATIONS
+    )
+
+
+def _is_sentence_end(text: str, terminator: re.Match) -> bool:
+    if terminator.group()[0] not in _CASED_TERMINATORS:
+        return True
+    next_char = _NEXT_CHAR.match(text, terminator.end())
+    if next_char is not None and next_char.group(1).islower():
+        return False
+    if terminator.group()[0] == ".":
+        return not _is_abbreviation(text, terminator.start())
+    return True
+
+
+def _clean(sentences: list[str]) -> list[str]:
+    return [s for s in (s.strip() for s in sentences) if s]
+
 
 @SentenceSplitter.register(SentenceSplitterModel.DEFAULT)
 class DefaultSentenceSplitter(SentenceSplitter):
-    def __init__(self, config: DefaultSentenceSplitterConfig):
-        self._config = config
-
     def load(self, language: "Language") -> Self: ...
 
     @classmethod
     def _from_config(cls, config: DefaultSentenceSplitterConfig) -> Self:
         return cls(config)
 
-    def split_sentences(self, text: str) -> list[str]:
+    def _split_sentences(self, text: str) -> list[str]:
         return [text]
 
 
 @SentenceSplitter.register(SentenceSplitterModel.ARGOS)
 class ArgosSentenceSplitter(SentenceSplitter):
     def __init__(self, config: ArgosSentenceSplitterConfig):
-        self._config = config
+        super().__init__(config)
         self._inner = None
 
     def load(self, language: Language) -> Self:
@@ -54,9 +110,72 @@ def __exit__(self, exc_type, exc_val, exc_tb):  # noqa: ANN001
         del self._inner
         gc.collect()
 
-    def split_sentences(self, text: str) -> list[str]:
+    def _split_sentences(self, text: str) -> list[str]:
         return self._inner.split_sentences(text)
 
     @classmethod
     def _from_config(cls, config: ArgosSentenceSplitterConfig) -> Self:
         return cls(config)
+
+
+@SentenceSplitter.register(SentenceSplitterModel.RULES)
+class RulesSentenceSplitter(SentenceSplitter):
+    """Whitespace and punctuation splitter. Languages that don't rely on punctuation
+    (e.g. Thai) should use a different approach.
+    """
+
+    def load(self, language: Language) -> Self:  # noqa: ARG002
+        return self
+
+    @classmethod
+    def _from_config(cls, config: RulesSentenceSplitterConfig) -> Self:
+        return cls(config)
+
+    def _split_sentences(self, text: str) -> list[str]:
+        sentences, start = [], 0
+        for terminator in _TERMINATOR.finditer(text):
+            if _is_sentence_end(text, terminator):
+                sentences.append(text[start : terminator.end()])
+                start = terminator.end()
+        sentences.append(text[start:])
+        return _clean(sentences)
+
+
+@SentenceSplitter.register(SentenceSplitterModel.SAT)
+class SaTSentenceSplitter(SentenceSplitter):
+    """Segment any Text (SaT) splitter"""
+
+    def __init__(self, config: SaTSentenceSplitterConfig):
+        super().__init__(config)
+        self._sat = None
+
+    def load(self, language: Language) -> Self:  # noqa: ARG002
+        import torch  # noqa: PLC0415
+        from wtpsplit import SaT  # noqa: PLC0415
+
+        sat = SaT(self._config.model_ref)
+        device = self._config.device
+        if device is None:
+            device = TorchDevice.GPU if torch.cuda.is_available() else TorchDevice.CPU
+        if device is TorchDevice.GPU:
+            sat.half().to(device)
+        self._sat = sat
+        return self
+
+    @classmethod
+    def _from_config(cls, config: SaTSentenceSplitterConfig) -> Self:
+        return cls(config)
+
+    def _split_sentences(self, text: str) -> list[str]:
+        return _clean(self._sat.split(text))
+
+    def _split_sentences_batch(self, batch: list[str]) -> list[list[str]]:
+        return [_clean(sentences) for sentences in self._sat.split(batch)]
+
+    def __exit__(self, exc_type, exc_val, exc_tb):  # noqa: ANN001
+        import torch  # noqa: PLC0415
+
+        self._sat = None
+        if torch.cuda.is_available():
+            torch.cuda.empty_cache()
+        gc.collect()
diff --git a/workers/translation-worker/uv.dist.lock b/workers/translation-worker/uv.dist.lock
index a3019b8e..e099d770 100644
--- a/workers/translation-worker/uv.dist.lock
+++ b/workers/translation-worker/uv.dist.lock
@@ -1,6 +1,14 @@
 version = 1
 revision = 3
 requires-python = ">=3.11.0, <3.13"
+resolution-markers = [
+    "python_full_version >= '3.12' and sys_platform == 'win32'",
+    "python_full_version >= '3.12' and sys_platform == 'emscripten'",
+    "python_full_version >= '3.12' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version < '3.12' and sys_platform == 'win32'",
+    "python_full_version < '3.12' and sys_platform == 'emscripten'",
+    "python_full_version < '3.12' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+]
 
 [[package]]
 name = "about-time"
@@ -409,37 +417,37 @@ wheels = [
 
 [package.optional-dependencies]
 cublas = [
-    { name = "nvidia-cublas", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cublas" },
 ]
 cudart = [
-    { name = "nvidia-cuda-runtime", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cuda-runtime" },
 ]
 cufft = [
-    { name = "nvidia-cufft", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cufft" },
 ]
 cufile = [
-    { name = "nvidia-cufile", marker = "sys_platform == 'linux'" },
+    { name = "nvidia-cufile" },
 ]
 cupti = [
-    { name = "nvidia-cuda-cupti", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cuda-cupti" },
 ]
 curand = [
-    { name = "nvidia-curand", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-curand" },
 ]
 cusolver = [
-    { name = "nvidia-cusolver", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cusolver" },
 ]
 cusparse = [
-    { name = "nvidia-cusparse", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cusparse" },
 ]
 nvjitlink = [
-    { name = "nvidia-nvjitlink", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-nvjitlink" },
 ]
 nvrtc = [
-    { name = "nvidia-cuda-nvrtc", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cuda-nvrtc" },
 ]
 nvtx = [
-    { name = "nvidia-nvtx", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-nvtx" },
 ]
 
 [[package]]
@@ -502,14 +510,20 @@ dependencies = [
 [package.optional-dependencies]
 c2translate = [
     { name = "argostranslate" },
+    { name = "wtpsplit" },
 ]
 inference = [
     { name = "argostranslate" },
+    { name = "wtpsplit" },
+]
+sat = [
+    { name = "wtpsplit" },
 ]
 torch = [
     { name = "accelerate" },
     { name = "torch" },
     { name = "transformers" },
+    { name = "wtpsplit" },
 ]
 
 [package.dev-dependencies]
@@ -535,8 +549,12 @@ requires-dist = [
     { name = "pydantic-extra-types", extras = ["pycountry"], specifier = "==2.11.1" },
     { name = "torch", marker = "extra == 'torch'", specifier = "==2.11.0" },
     { name = "transformers", marker = "extra == 'torch'", specifier = "==5.12.1" },
+    { name = "wtpsplit", marker = "extra == 'c2translate'", specifier = "==2.2.2" },
+    { name = "wtpsplit", marker = "extra == 'inference'", specifier = "==2.2.2" },
+    { name = "wtpsplit", marker = "extra == 'sat'", specifier = "==2.2.2" },
+    { name = "wtpsplit", marker = "extra == 'torch'", specifier = "==2.2.2" },
 ]
-provides-extras = ["c2translate", "inference", "torch"]
+provides-extras = ["c2translate", "inference", "sat", "torch"]
 
 [package.metadata.requires-dev]
 dev = [
@@ -560,6 +578,12 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/33/6b/e0547afaf41bf2c42e52430072fa5658766e3d65bd4b03a563d1b6336f57/distlib-0.4.0-py2.py3-none-any.whl", hash = "sha256:9659f7d87e46584a30b5780e43ac7a2143098441670ff0a49d5f9034c54a6c16", size = 469047, upload-time = "2025-07-17T16:51:58.613Z" },
 ]
 
+[[package]]
+name = "docopt"
+version = "0.6.2"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/a2/55/8f8cab2afd404cf578136ef2cc5dfb50baa1761b68c9da1fb1e4eed343c9/docopt-0.6.2.tar.gz", hash = "sha256:49b3a825280bd66b3aa83585ef59c4a8c82f2c8a522dbe754a8bc8d08c85c491", size = 25901, upload-time = "2014-06-16T11:18:57.406Z" }
+
 [[package]]
 name = "elasticsearch"
 version = "7.17.13"
@@ -998,6 +1022,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d2/47/7b13b62127a6e1460e1bc3fabf3aab0cf281f73cad81d5972b3aef40c0ff/minisbd-0.9.5-py3-none-any.whl", hash = "sha256:a573a3bb62349a5a7f22f6e12c8305814dbe6765d83bcb034c6f780d1e69d1df", size = 41125, upload-time = "2026-03-03T18:15:10.972Z" },
 ]
 
+[[package]]
+name = "mosestokenizer"
+version = "1.2.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "docopt" },
+    { name = "openfile" },
+    { name = "toolwrapper" },
+    { name = "uctools" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/8d/84/4f3c1b5b8d796a07e3816cd41f7b1491e2291db4ade5f17b850116fd80e5/mosestokenizer-1.2.1.tar.gz", hash = "sha256:438b3e35a221f7930c408e97e3f38af6d0cec74b991eb9edb00a44e3510e836d", size = 37120, upload-time = "2021-10-22T14:15:07.205Z" }
+
 [[package]]
 name = "mpmath"
 version = "1.3.0"
@@ -1076,6 +1112,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/13/bf/028179259aebc18fd4ba5cae2601d1d47517427a537ab44336446431a215/murmurhash-1.0.15-cp312-cp312-win_arm64.whl", hash = "sha256:4a70ca4ae19e600d9be3da64d00710e79dde388a4d162f22078d64844d0ebdda", size = 23338, upload-time = "2025-11-14T09:50:22.359Z" },
 ]
 
+[[package]]
+name = "narwhals"
+version = "2.27.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/bf/21/f64d6b2dbea7bf3f8c38cdc786dcc6ef012ca3d173ad208c782c9a7bedf6/narwhals-2.27.1.tar.gz", hash = "sha256:aed93076a3ea42d9c32c88e4eb5ea422a21937011cbe1f480f9572a523c82094", size = 735013, upload-time = "2026-10-10T06:52:18.113Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/d1/89/5d4c86da1130d9059681e5b6cd7645df5c10279a6a079c5c37dcb2cc6f3f/narwhals-2.27.1-py3-none-any.whl", hash = "sha256:d057df13f5852b8e157596e82eb5e955fad267425df5e420e0ee9863da483b31", size = 483211, upload-time = "2026-10-10T06:52:16.32Z" },
+]
+
 [[package]]
 name = "nest-asyncio"
 version = "1.6.0"
@@ -1324,6 +1369,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/38/fa/e5c43397632a399f542663ed3e3e37763ee203ba845b10b266cd2ede8925/onnxruntime-1.25.1-cp312-cp312-win_arm64.whl", hash = "sha256:b6c7aa5cae606d5c90a392679fac074b60f80025a2e83e1e90fdf882bd2a97f0", size = 12634433, upload-time = "2026-04-27T22:00:25.918Z" },
 ]
 
+[[package]]
+name = "openfile"
+version = "0.0.7"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/16/46/6c8b936e55ace50a6d9ea722dd4b11a4996d58cff41690636a0d6f6f6718/openfile-0.0.7.tar.gz", hash = "sha256:ea4e8f19112049f578ec161b12f70c1113144988c0a488ab173a138b50f37479", size = 2199, upload-time = "2018-09-26T13:16:48.207Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/93/e6/805db6867faacb488b44ba8e0829ef4de151dd0499f3c5da5f4ad11698a7/openfile-0.0.7-py3-none-any.whl", hash = "sha256:d21b69dba1306c9dd397a44fd8f4fa8a83812f1d935c409085e8a25c411d16ec", size = 2355, upload-time = "2018-09-26T13:17:13.226Z" },
+]
+
 [[package]]
 name = "packaging"
 version = "26.0"
@@ -1333,6 +1387,36 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl", hash = "sha256:b36f1fef9334a5588b4166f8bcd26a14e521f2b55e6b9de3aaa80d3ff7a37529", size = 74366, upload-time = "2026-01-21T20:50:37.788Z" },
 ]
 
+[[package]]
+name = "pandas"
+version = "3.0.6"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+    { name = "python-dateutil" },
+    { name = "tzdata", marker = "sys_platform == 'emscripten' or sys_platform == 'win32'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/e2/17/d7b106e05bfa642e8694451e7d3d759c6a241c5386a5d962e4f66c047e06/pandas-3.0.6.tar.gz", hash = "sha256:66b07ef7315a31bfe1089cd3d71a7de781c9dca986762d0b4fe7c0ef17465d10", size = 4667686, upload-time = "2026-09-17T23:23:18.345Z" }
+wheels = [
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 version = "1.0.0"
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+[[package]]
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+version = "2.2.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "huggingface-hub" },
+    { name = "mosestokenizer" },
+    { name = "numpy" },
+    { name = "pandas" },
+    { name = "scikit-learn" },
+    { name = "skops" },
+    { name = "tqdm" },
+    { name = "transformers" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/09/c6/58219e9f36219f115e499d57f2e5073e565a3b4e5290e203355bf5ba1909/wtpsplit-2.2.2.tar.gz", hash = "sha256:398e26b9c12b780d250e72766331c194b68c48a6f77feb2470c872801e850fc3", size = 140746, upload-time = "2026-09-25T15:41:31.09Z" }
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+
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 name = "yarl"
 version = "1.23.0"
diff --git a/workers/translation-worker/uv.lock b/workers/translation-worker/uv.lock
index ceab7a8e..62a59e13 100644
--- a/workers/translation-worker/uv.lock
+++ b/workers/translation-worker/uv.lock
@@ -1,6 +1,14 @@
 version = 1
 revision = 3
 requires-python = ">=3.11.0, <3.13"
+resolution-markers = [
+    "python_full_version >= '3.12' and sys_platform == 'win32'",
+    "python_full_version >= '3.12' and sys_platform == 'emscripten'",
+    "python_full_version >= '3.12' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version < '3.12' and sys_platform == 'win32'",
+    "python_full_version < '3.12' and sys_platform == 'emscripten'",
+    "python_full_version < '3.12' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+]
 
 [[package]]
 name = "about-time"
@@ -409,37 +417,37 @@ wheels = [
 
 [package.optional-dependencies]
 cublas = [
-    { name = "nvidia-cublas", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cublas" },
 ]
 cudart = [
-    { name = "nvidia-cuda-runtime", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cuda-runtime" },
 ]
 cufft = [
-    { name = "nvidia-cufft", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cufft" },
 ]
 cufile = [
-    { name = "nvidia-cufile", marker = "sys_platform == 'linux'" },
+    { name = "nvidia-cufile" },
 ]
 cupti = [
-    { name = "nvidia-cuda-cupti", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cuda-cupti" },
 ]
 curand = [
-    { name = "nvidia-curand", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-curand" },
 ]
 cusolver = [
-    { name = "nvidia-cusolver", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cusolver" },
 ]
 cusparse = [
-    { name = "nvidia-cusparse", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cusparse" },
 ]
 nvjitlink = [
-    { name = "nvidia-nvjitlink", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-nvjitlink" },
 ]
 nvrtc = [
-    { name = "nvidia-cuda-nvrtc", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cuda-nvrtc" },
 ]
 nvtx = [
-    { name = "nvidia-nvtx", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-nvtx" },
 ]
 
 [[package]]
@@ -530,14 +538,20 @@ dependencies = [
 [package.optional-dependencies]
 c2translate = [
     { name = "argostranslate" },
+    { name = "wtpsplit" },
 ]
 inference = [
     { name = "argostranslate" },
+    { name = "wtpsplit" },
+]
+sat = [
+    { name = "wtpsplit" },
 ]
 torch = [
     { name = "accelerate" },
     { name = "torch" },
     { name = "transformers" },
+    { name = "wtpsplit" },
 ]
 
 [package.dev-dependencies]
@@ -563,8 +577,12 @@ requires-dist = [
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     { name = "torch", marker = "extra == 'torch'", specifier = "==2.11.0" },
     { name = "transformers", marker = "extra == 'torch'", specifier = "==5.12.1" },
+    { name = "wtpsplit", marker = "extra == 'c2translate'", specifier = "==2.2.2" },
+    { name = "wtpsplit", marker = "extra == 'inference'", specifier = "==2.2.2" },
+    { name = "wtpsplit", marker = "extra == 'sat'", specifier = "==2.2.2" },
+    { name = "wtpsplit", marker = "extra == 'torch'", specifier = "==2.2.2" },
 ]
-provides-extras = ["c2translate", "inference", "torch"]
+provides-extras = ["c2translate", "inference", "sat", "torch"]
 
 [package.metadata.requires-dev]
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+[[package]]
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+version = "0.6.2"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/a2/55/8f8cab2afd404cf578136ef2cc5dfb50baa1761b68c9da1fb1e4eed343c9/docopt-0.6.2.tar.gz", hash = "sha256:49b3a825280bd66b3aa83585ef59c4a8c82f2c8a522dbe754a8bc8d08c85c491", size = 25901, upload-time = "2014-06-16T11:18:57.406Z" }
+
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 name = "elasticsearch"
 version = "7.17.13"
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 ]
 
+[[package]]
+name = "mosestokenizer"
+version = "1.2.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "docopt" },
+    { name = "openfile" },
+    { name = "toolwrapper" },
+    { name = "uctools" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/8d/84/4f3c1b5b8d796a07e3816cd41f7b1491e2291db4ade5f17b850116fd80e5/mosestokenizer-1.2.1.tar.gz", hash = "sha256:438b3e35a221f7930c408e97e3f38af6d0cec74b991eb9edb00a44e3510e836d", size = 37120, upload-time = "2021-10-22T14:15:07.205Z" }
+
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 version = "1.3.0"
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 ]
 
+[[package]]
+name = "narwhals"
+version = "2.27.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/bf/21/f64d6b2dbea7bf3f8c38cdc786dcc6ef012ca3d173ad208c782c9a7bedf6/narwhals-2.27.1.tar.gz", hash = "sha256:aed93076a3ea42d9c32c88e4eb5ea422a21937011cbe1f480f9572a523c82094", size = 735013, upload-time = "2026-10-10T06:52:18.113Z" }
+wheels = [
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+]
+
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 name = "nest-asyncio"
 version = "1.6.0"
@@ -1352,6 +1397,15 @@ wheels = [
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 ]
 
+[[package]]
+name = "openfile"
+version = "0.0.7"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/16/46/6c8b936e55ace50a6d9ea722dd4b11a4996d58cff41690636a0d6f6f6718/openfile-0.0.7.tar.gz", hash = "sha256:ea4e8f19112049f578ec161b12f70c1113144988c0a488ab173a138b50f37479", size = 2199, upload-time = "2018-09-26T13:16:48.207Z" }
+wheels = [
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+]
+
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 name = "packaging"
 version = "26.0"
@@ -1361,6 +1415,36 @@ wheels = [
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 ]
 
+[[package]]
+name = "pandas"
+version = "3.0.6"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+    { name = "python-dateutil" },
+    { name = "tzdata", marker = "sys_platform == 'emscripten' or sys_platform == 'win32'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/e2/17/d7b106e05bfa642e8694451e7d3d759c6a241c5386a5d962e4f66c047e06/pandas-3.0.6.tar.gz", hash = "sha256:66b07ef7315a31bfe1089cd3d71a7de781c9dca986762d0b4fe7c0ef17465d10", size = 4667686, upload-time = "2026-09-17T23:23:18.345Z" }
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