diff --git a/README.md b/README.md
index ce6d52a37..7ff223a2a 100644
--- a/README.md
+++ b/README.md
@@ -242,6 +242,29 @@ What to know before integrating:
See [`examples/realtime_transcription.py`](examples/realtime_transcription.py)
for a runnable end-to-end example.
+## Loading tokenized dataset previews
+
+Install the optional Hugging Face datasets support:
+
+```sh
+pip install "together[datasets]"
+```
+
+Then retrieve the tokenized preview from a fine-tuning job as a `DatasetDict`:
+
+```python
+tokenized = client.fine_tuning.retrieve_tokenized_dataset(
+ "ft-...",
+ return_dataset=True,
+)
+print(tokenized["train"])
+```
+
+The result contains a `train` split and, when the job has evaluation data, a
+`validation` split. Without `return_dataset=True`, the method continues to
+return the presigned download metadata. Preview archives are limited to 10,000
+members, 512 MiB per member, and 1 GiB total after extraction.
+
## Using types
Nested request parameters are [TypedDicts](https://docs.python.org/3/library/typing.html#typing.TypedDict). Responses are [Pydantic models](https://docs.pydantic.dev) which also provide helper methods for things like:
diff --git a/api.md b/api.md
index b0d3675ef..9fa7f41e9 100644
--- a/api.md
+++ b/api.md
@@ -456,7 +456,7 @@ Methods:
- client.fine_tuning.list_metrics(id, \*\*params) -> FineTuningListMetricsResponse
- client.fine_tuning.model_limits(\*\*params) -> FinetuneModelLimits
- client.fine_tuning.preview(\*\*params) -> FineTunePreviewResponse
-- client.fine_tuning.retrieve_tokenized_dataset(id) -> FineTuneTokenizedDatasetRetrieveResponse
+- client.fine_tuning.retrieve_tokenized_dataset(id, return_dataset=False) -> FineTuneTokenizedDatasetRetrieveResponse | DatasetDict
# CodeInterpreter
diff --git a/pyproject.toml b/pyproject.toml
index 0ccfc06f5..43e58a278 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -56,6 +56,10 @@ pyarrow = ["pyarrow>=16.1.0", "pyarrow-stubs>=10.0.1.7"]
cli = ["PyYAML", "questionary>=2.1.1"]
# websockets>=13 is the floor for both websockets.sync.client and websockets.asyncio.client
realtime = ["websockets>=13,<16"]
+datasets = [
+ "datasets>=5.0.1",
+ "zstandard>=0.25.0",
+]
[project.scripts]
together = "together.lib.cli:main"
diff --git a/src/together/lib/tokenized_dataset.py b/src/together/lib/tokenized_dataset.py
new file mode 100644
index 000000000..1ede3ded7
--- /dev/null
+++ b/src/together/lib/tokenized_dataset.py
@@ -0,0 +1,204 @@
+from __future__ import annotations
+
+import shutil
+import tarfile
+import tempfile
+import importlib
+from typing import TYPE_CHECKING, Any
+from pathlib import Path, PurePosixPath
+
+import anyio
+import httpx
+from anyio.to_thread import run_sync
+
+from together._types import NotGiven, not_given
+
+if TYPE_CHECKING:
+ from datasets import DatasetDict # type: ignore[import-untyped] # pyright: ignore[reportMissingTypeStubs]
+else:
+ DatasetDict = Any
+
+_DATASETS_INSTALL_HINT = (
+ "Returning a Hugging Face dataset requires the `datasets` extra. Install it with `pip install together[datasets]`."
+)
+_TRAIN_DATASET_DIR = "train_dataset"
+_EVAL_DATASET_DIR = "eval_dataset"
+_EXPECTED_DATASET_DIRS = {_TRAIN_DATASET_DIR, _EVAL_DATASET_DIR}
+_REDIRECT_STATUS_CODES = {301, 302, 303, 307, 308}
+_MAX_REDIRECTS = 20
+_MAX_ARCHIVE_MEMBERS = 10_000
+_MAX_MEMBER_BYTES = 512 * 1024 * 1024
+_MAX_EXTRACTED_BYTES = 1024 * 1024 * 1024
+
+_DatasetDependencies = tuple[Any, Any, Any]
+
+
+def _require_datasets() -> _DatasetDependencies:
+ try:
+ datasets = importlib.import_module("datasets")
+ zstandard = importlib.import_module("zstandard")
+ except ImportError as exc:
+ raise RuntimeError(_DATASETS_INSTALL_HINT) from exc
+ return datasets.DatasetDict, datasets.load_from_disk, zstandard.ZstdDecompressor
+
+
+def _extract_archive(archive_path: Path, output_dir: Path, decompressor_type: Any) -> None:
+ member_count = 0
+ extracted_bytes = 0
+ with archive_path.open("rb") as compressed:
+ with decompressor_type().stream_reader(compressed) as decompressed:
+ with tarfile.open(fileobj=decompressed, mode="r|") as archive:
+ for member in archive:
+ member_count += 1
+ if member_count > _MAX_ARCHIVE_MEMBERS:
+ raise ValueError("Tokenized dataset archive contains too many members.")
+ if member.size < 0 or member.size > _MAX_MEMBER_BYTES:
+ raise ValueError(f"Tokenized dataset archive member is too large: {member.name!r}")
+ extracted_bytes += member.size
+ if extracted_bytes > _MAX_EXTRACTED_BYTES:
+ raise ValueError("Tokenized dataset archive is too large after extraction.")
+
+ member_path = PurePosixPath(member.name)
+ if (
+ member_path.is_absolute()
+ or "\\" in member.name
+ or ".." in member_path.parts
+ or not member_path.parts
+ or member_path.parts[0] not in _EXPECTED_DATASET_DIRS
+ ):
+ raise ValueError(f"Unexpected tokenized dataset archive member: {member.name!r}")
+
+ destination = output_dir.joinpath(*member_path.parts)
+ if member.isdir():
+ destination.mkdir(parents=True, exist_ok=True)
+ continue
+ if not member.isfile():
+ raise ValueError(f"Unsupported tokenized dataset archive member: {member.name!r}")
+
+ source = archive.extractfile(member)
+ if source is None:
+ raise ValueError(f"Could not read tokenized dataset archive member: {member.name!r}")
+ destination.parent.mkdir(parents=True, exist_ok=True)
+ with source, destination.open("wb") as target:
+ shutil.copyfileobj(source, target)
+
+
+def _load_archive(
+ archive_path: Path,
+ dependencies: _DatasetDependencies | None = None,
+) -> DatasetDict:
+ if dependencies is None:
+ dependencies = _require_datasets()
+ dataset_dict_type, load_from_disk, decompressor_type = dependencies
+ with tempfile.TemporaryDirectory() as temporary_directory:
+ output_dir = Path(temporary_directory)
+ _extract_archive(archive_path, output_dir, decompressor_type)
+
+ train_path = output_dir / _TRAIN_DATASET_DIR
+ if not train_path.is_dir():
+ raise ValueError("Tokenized dataset archive does not contain a train dataset.")
+
+ splits = {"train": load_from_disk(train_path, keep_in_memory=True)}
+ eval_path = output_dir / _EVAL_DATASET_DIR
+ if eval_path.is_dir():
+ splits["validation"] = load_from_disk(eval_path, keep_in_memory=True)
+ return dataset_dict_type(splits)
+
+
+def _validate_download_url(url: str) -> None:
+ parsed_url = httpx.URL(url)
+ if parsed_url.scheme != "https" or not parsed_url.host:
+ raise ValueError("Tokenized dataset download URL must use HTTPS.")
+
+
+def _get_redirect_url(response: httpx.Response) -> str | None:
+ if response.status_code not in _REDIRECT_STATUS_CODES:
+ return None
+ location = response.headers.get("location")
+ if location is None:
+ raise ValueError("Tokenized dataset download redirect is missing a location.")
+ return str(response.url.join(location))
+
+
+def _client_options(
+ timeout: float | httpx.Timeout | None | NotGiven,
+) -> dict[str, Any]:
+ if isinstance(timeout, NotGiven):
+ return {}
+ return {"timeout": timeout}
+
+
+def retrieve_dataset(
+ url: str,
+ *,
+ expected_size: int,
+ timeout: float | httpx.Timeout | None | NotGiven = not_given,
+) -> DatasetDict:
+ dependencies = _require_datasets()
+ _validate_download_url(url)
+ with tempfile.TemporaryDirectory() as temporary_directory:
+ archive_path = Path(temporary_directory) / "tokenized-datasets.tar.zst"
+ with httpx.Client(**_client_options(timeout)) as client:
+ for _ in range(_MAX_REDIRECTS + 1):
+ with client.stream("GET", url) as response:
+ redirect_url = _get_redirect_url(response)
+ if redirect_url is not None:
+ _validate_download_url(redirect_url)
+ url = redirect_url
+ continue
+
+ response.raise_for_status()
+ bytes_written = 0
+ with archive_path.open("wb") as archive:
+ for chunk in response.iter_bytes():
+ if bytes_written + len(chunk) > expected_size:
+ raise ValueError("Downloaded file exceeds the remote file size.")
+ archive.write(chunk)
+ bytes_written += len(chunk)
+ if bytes_written != expected_size:
+ raise ValueError(
+ f"Downloaded file size `{bytes_written}` bytes does not match "
+ f"remote file size `{expected_size}` bytes."
+ )
+ break
+ else:
+ raise ValueError("Tokenized dataset download exceeded the maximum number of redirects.")
+ return _load_archive(archive_path, dependencies)
+
+
+async def async_retrieve_dataset(
+ url: str,
+ *,
+ expected_size: int,
+ timeout: float | httpx.Timeout | None | NotGiven = not_given,
+) -> DatasetDict:
+ _validate_download_url(url)
+ dependencies = await run_sync(_require_datasets)
+ with tempfile.TemporaryDirectory() as temporary_directory:
+ archive_path = Path(temporary_directory) / "tokenized-datasets.tar.zst"
+ async with httpx.AsyncClient(**_client_options(timeout)) as client:
+ for _ in range(_MAX_REDIRECTS + 1):
+ async with client.stream("GET", url) as response:
+ redirect_url = _get_redirect_url(response)
+ if redirect_url is not None:
+ _validate_download_url(redirect_url)
+ url = redirect_url
+ continue
+
+ response.raise_for_status()
+ bytes_written = 0
+ async with await anyio.open_file(archive_path, "wb") as archive:
+ async for chunk in response.aiter_bytes():
+ if bytes_written + len(chunk) > expected_size:
+ raise ValueError("Downloaded file exceeds the remote file size.")
+ await archive.write(chunk)
+ bytes_written += len(chunk)
+ if bytes_written != expected_size:
+ raise ValueError(
+ f"Downloaded file size `{bytes_written}` bytes does not match "
+ f"remote file size `{expected_size}` bytes."
+ )
+ break
+ else:
+ raise ValueError("Tokenized dataset download exceeded the maximum number of redirects.")
+ return await run_sync(_load_archive, archive_path, dependencies)
diff --git a/src/together/resources/fine_tuning.py b/src/together/resources/fine_tuning.py
index bc1c068a2..bedefadcc 100644
--- a/src/together/resources/fine_tuning.py
+++ b/src/together/resources/fine_tuning.py
@@ -2,7 +2,7 @@
from __future__ import annotations
-from typing import Any, Union, Optional, cast
+from typing import TYPE_CHECKING, Any, Union, Optional, cast, overload
from datetime import datetime
from typing_extensions import Literal
@@ -36,6 +36,10 @@
async_to_custom_streamed_response_wrapper,
)
from .._base_client import make_request_options
+from ..lib.tokenized_dataset import (
+ retrieve_dataset as _retrieve_tokenized_dataset,
+ async_retrieve_dataset as _async_retrieve_tokenized_dataset,
+)
from ..lib.types.fine_tuning import FinetuneResponse as FinetuneResponseLib
from ..types.finetune_response import FinetuneResponse
from ..lib.resources.fine_tuning import create_finetune_request
@@ -50,6 +54,11 @@
from ..types.fine_tuning_list_checkpoints_response import FineTuningListCheckpointsResponse
from ..types.fine_tune_tokenized_dataset_retrieve_response import FineTuneTokenizedDatasetRetrieveResponse
+if TYPE_CHECKING:
+ from datasets import DatasetDict # type: ignore[import-untyped] # pyright: ignore[reportMissingTypeStubs]
+else:
+ DatasetDict = Any
+
__all__ = ["FineTuningResource", "AsyncFineTuningResource"]
_WARNING_MESSAGE_INSUFFICIENT_FUNDS = (
@@ -809,17 +818,73 @@ def preview(
cast_to=FineTunePreviewResponse,
)
+ def _retrieve_tokenized_dataset_metadata(
+ self,
+ id: str,
+ *,
+ extra_headers: Headers | None = None,
+ extra_query: Query | None = None,
+ extra_body: Body | None = None,
+ timeout: float | httpx.Timeout | None | NotGiven = not_given,
+ ) -> FineTuneTokenizedDatasetRetrieveResponse:
+ if not id:
+ raise ValueError(f"Expected a non-empty value for `id` but received {id!r}")
+ return self._get(
+ path_template("/fine-tunes/{id}/download-tokenized-dataset", id=id),
+ options=make_request_options(
+ extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
+ ),
+ cast_to=FineTuneTokenizedDatasetRetrieveResponse,
+ )
+
+ @overload
+ def retrieve_tokenized_dataset(
+ self,
+ id: str,
+ *,
+ return_dataset: Literal[False] = False,
+ extra_headers: Headers | None = None,
+ extra_query: Query | None = None,
+ extra_body: Body | None = None,
+ timeout: float | httpx.Timeout | None | NotGiven = not_given,
+ ) -> FineTuneTokenizedDatasetRetrieveResponse: ...
+
+ @overload
def retrieve_tokenized_dataset(
self,
id: str,
*,
+ return_dataset: Literal[True],
+ extra_headers: Headers | None = None,
+ extra_query: Query | None = None,
+ extra_body: Body | None = None,
+ timeout: float | httpx.Timeout | None | NotGiven = not_given,
+ ) -> DatasetDict: ...
+
+ @overload
+ def retrieve_tokenized_dataset(
+ self,
+ id: str,
+ *,
+ return_dataset: bool,
+ extra_headers: Headers | None = None,
+ extra_query: Query | None = None,
+ extra_body: Body | None = None,
+ timeout: float | httpx.Timeout | None | NotGiven = not_given,
+ ) -> FineTuneTokenizedDatasetRetrieveResponse | DatasetDict: ...
+
+ def retrieve_tokenized_dataset(
+ self,
+ id: str,
+ *,
+ return_dataset: bool = False,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = not_given,
- ) -> FineTuneTokenizedDatasetRetrieveResponse:
+ ) -> FineTuneTokenizedDatasetRetrieveResponse | DatasetDict:
"""
Get a presigned URL for the tokenized dataset archive generated for a fine-tune
job.
@@ -827,6 +892,10 @@ def retrieve_tokenized_dataset(
Args:
id: The ID of the fine-tune job whose tokenized dataset should be downloaded.
+ return_dataset: Download and load the archive as a Hugging Face `DatasetDict`. This
+ requires the `datasets` extra. Extraction is limited to 10,000 members,
+ 512 MiB per member, and 1 GiB total.
+
extra_headers: Send extra headers
extra_query: Add additional query parameters to the request
@@ -835,15 +904,21 @@ def retrieve_tokenized_dataset(
timeout: Override the client-level default timeout for this request, in seconds
"""
- if not id:
- raise ValueError(f"Expected a non-empty value for `id` but received {id!r}")
- return self._get(
- path_template("/fine-tunes/{id}/download-tokenized-dataset", id=id),
- options=make_request_options(
- extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
- ),
- cast_to=FineTuneTokenizedDatasetRetrieveResponse,
- )
+ metadata = self._retrieve_tokenized_dataset_metadata(
+ id,
+ extra_headers=extra_headers,
+ extra_query=extra_query,
+ extra_body=extra_body,
+ timeout=timeout,
+ )
+ if return_dataset:
+ download_timeout = self._client.timeout if isinstance(timeout, NotGiven) else timeout
+ return _retrieve_tokenized_dataset(
+ metadata.url,
+ expected_size=metadata.size,
+ timeout=download_timeout,
+ )
+ return metadata
class AsyncFineTuningResource(AsyncAPIResource):
@@ -1594,17 +1669,73 @@ async def preview(
cast_to=FineTunePreviewResponse,
)
+ async def _retrieve_tokenized_dataset_metadata(
+ self,
+ id: str,
+ *,
+ extra_headers: Headers | None = None,
+ extra_query: Query | None = None,
+ extra_body: Body | None = None,
+ timeout: float | httpx.Timeout | None | NotGiven = not_given,
+ ) -> FineTuneTokenizedDatasetRetrieveResponse:
+ if not id:
+ raise ValueError(f"Expected a non-empty value for `id` but received {id!r}")
+ return await self._get(
+ path_template("/fine-tunes/{id}/download-tokenized-dataset", id=id),
+ options=make_request_options(
+ extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
+ ),
+ cast_to=FineTuneTokenizedDatasetRetrieveResponse,
+ )
+
+ @overload
+ async def retrieve_tokenized_dataset(
+ self,
+ id: str,
+ *,
+ return_dataset: Literal[False] = False,
+ extra_headers: Headers | None = None,
+ extra_query: Query | None = None,
+ extra_body: Body | None = None,
+ timeout: float | httpx.Timeout | None | NotGiven = not_given,
+ ) -> FineTuneTokenizedDatasetRetrieveResponse: ...
+
+ @overload
+ async def retrieve_tokenized_dataset(
+ self,
+ id: str,
+ *,
+ return_dataset: Literal[True],
+ extra_headers: Headers | None = None,
+ extra_query: Query | None = None,
+ extra_body: Body | None = None,
+ timeout: float | httpx.Timeout | None | NotGiven = not_given,
+ ) -> DatasetDict: ...
+
+ @overload
async def retrieve_tokenized_dataset(
self,
id: str,
*,
+ return_dataset: bool,
+ extra_headers: Headers | None = None,
+ extra_query: Query | None = None,
+ extra_body: Body | None = None,
+ timeout: float | httpx.Timeout | None | NotGiven = not_given,
+ ) -> FineTuneTokenizedDatasetRetrieveResponse | DatasetDict: ...
+
+ async def retrieve_tokenized_dataset(
+ self,
+ id: str,
+ *,
+ return_dataset: bool = False,
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
# The extra values given here take precedence over values defined on the client or passed to this method.
extra_headers: Headers | None = None,
extra_query: Query | None = None,
extra_body: Body | None = None,
timeout: float | httpx.Timeout | None | NotGiven = not_given,
- ) -> FineTuneTokenizedDatasetRetrieveResponse:
+ ) -> FineTuneTokenizedDatasetRetrieveResponse | DatasetDict:
"""
Get a presigned URL for the tokenized dataset archive generated for a fine-tune
job.
@@ -1612,6 +1743,10 @@ async def retrieve_tokenized_dataset(
Args:
id: The ID of the fine-tune job whose tokenized dataset should be downloaded.
+ return_dataset: Download and load the archive as a Hugging Face `DatasetDict`. This
+ requires the `datasets` extra. Extraction is limited to 10,000 members,
+ 512 MiB per member, and 1 GiB total.
+
extra_headers: Send extra headers
extra_query: Add additional query parameters to the request
@@ -1620,15 +1755,21 @@ async def retrieve_tokenized_dataset(
timeout: Override the client-level default timeout for this request, in seconds
"""
- if not id:
- raise ValueError(f"Expected a non-empty value for `id` but received {id!r}")
- return await self._get(
- path_template("/fine-tunes/{id}/download-tokenized-dataset", id=id),
- options=make_request_options(
- extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
- ),
- cast_to=FineTuneTokenizedDatasetRetrieveResponse,
- )
+ metadata = await self._retrieve_tokenized_dataset_metadata(
+ id,
+ extra_headers=extra_headers,
+ extra_query=extra_query,
+ extra_body=extra_body,
+ timeout=timeout,
+ )
+ if return_dataset:
+ download_timeout = self._client.timeout if isinstance(timeout, NotGiven) else timeout
+ return await _async_retrieve_tokenized_dataset(
+ metadata.url,
+ expected_size=metadata.size,
+ timeout=download_timeout,
+ )
+ return metadata
class FineTuningResourceWithRawResponse:
@@ -1670,7 +1811,7 @@ def __init__(self, fine_tuning: FineTuningResource) -> None:
fine_tuning.preview,
)
self.retrieve_tokenized_dataset = to_raw_response_wrapper(
- fine_tuning.retrieve_tokenized_dataset,
+ fine_tuning._retrieve_tokenized_dataset_metadata,
)
@@ -1713,7 +1854,7 @@ def __init__(self, fine_tuning: AsyncFineTuningResource) -> None:
fine_tuning.preview,
)
self.retrieve_tokenized_dataset = async_to_raw_response_wrapper(
- fine_tuning.retrieve_tokenized_dataset,
+ fine_tuning._retrieve_tokenized_dataset_metadata,
)
@@ -1756,7 +1897,7 @@ def __init__(self, fine_tuning: FineTuningResource) -> None:
fine_tuning.preview,
)
self.retrieve_tokenized_dataset = to_streamed_response_wrapper(
- fine_tuning.retrieve_tokenized_dataset,
+ fine_tuning._retrieve_tokenized_dataset_metadata,
)
@@ -1799,5 +1940,5 @@ def __init__(self, fine_tuning: AsyncFineTuningResource) -> None:
fine_tuning.preview,
)
self.retrieve_tokenized_dataset = async_to_streamed_response_wrapper(
- fine_tuning.retrieve_tokenized_dataset,
+ fine_tuning._retrieve_tokenized_dataset_metadata,
)
diff --git a/tests/unit/test_tokenized_dataset.py b/tests/unit/test_tokenized_dataset.py
new file mode 100644
index 000000000..0c297de4d
--- /dev/null
+++ b/tests/unit/test_tokenized_dataset.py
@@ -0,0 +1,279 @@
+from __future__ import annotations
+
+# pyright: reportMissingTypeStubs=false, reportUnknownMemberType=false
+import io
+import tarfile
+import importlib
+from typing import Any, cast
+from pathlib import Path
+
+import pytest
+import zstandard
+from respx import MockRouter
+from datasets import Dataset, DatasetDict
+
+from together import Together, AsyncTogether
+from together.lib import tokenized_dataset
+
+
+def _write_archive(tmp_path: Path, splits: dict[str, Dataset]) -> Path:
+ source_dir = tmp_path / "source"
+ source_dir.mkdir()
+ for name, dataset in splits.items():
+ dataset.save_to_disk(source_dir / name)
+
+ tar_path = tmp_path / "datasets.tar"
+ with tarfile.open(tar_path, "w") as archive:
+ for name in splits:
+ archive.add(source_dir / name, arcname=name)
+
+ archive_path = tmp_path / "datasets.tar.zst"
+ with tar_path.open("rb") as source, archive_path.open("wb") as target:
+ zstandard.ZstdCompressor().copy_stream(source, target)
+ return archive_path
+
+
+def _write_member_archive(tmp_path: Path, member_name: str) -> Path:
+ tar_path = tmp_path / "member.tar"
+ content = b"unexpected"
+ with tarfile.open(tar_path, "w") as archive:
+ member = tarfile.TarInfo(member_name)
+ member.size = len(content)
+ archive.addfile(member, io.BytesIO(content))
+
+ archive_path = tmp_path / "member.tar.zst"
+ with tar_path.open("rb") as source, archive_path.open("wb") as target:
+ zstandard.ZstdCompressor().copy_stream(source, target)
+ return archive_path
+
+
+def _mock_metadata(respx_mock: MockRouter, url: str, size: int = 100) -> None:
+ respx_mock.get("https://api.example/fine-tunes/ft-test/download-tokenized-dataset").respond(
+ json={
+ "content_type": "application/zstd",
+ "expires_at": "2026-08-19T10:00:00Z",
+ "filename": "tokenized-datasets.tar.zst",
+ "size": size,
+ "url": url,
+ }
+ )
+
+
+@pytest.mark.parametrize("include_validation", [False, True])
+def test_load_archive(tmp_path: Path, include_validation: bool) -> None:
+ splits = {"train_dataset": Dataset.from_dict({"input_ids": [[1, 2], [3, 4]]})}
+ if include_validation:
+ splits["eval_dataset"] = Dataset.from_dict({"input_ids": [[5, 6]]})
+
+ result = tokenized_dataset._load_archive(_write_archive(tmp_path, splits))
+
+ assert isinstance(result, DatasetDict)
+ assert result["train"]["input_ids"] == [[1, 2], [3, 4]]
+ if include_validation:
+ assert result["validation"]["input_ids"] == [[5, 6]]
+ else:
+ assert "validation" not in result
+
+
+@pytest.mark.parametrize(
+ "member_name",
+ ["../outside", r"train_dataset\..\outside", "other_dataset/state.json"],
+)
+def test_load_archive_rejects_unexpected_members(tmp_path: Path, member_name: str) -> None:
+ with pytest.raises(ValueError, match="Unexpected tokenized dataset archive member"):
+ tokenized_dataset._load_archive(_write_member_archive(tmp_path, member_name))
+
+
+def test_load_archive_requires_train_split(tmp_path: Path) -> None:
+ archive_path = _write_archive(
+ tmp_path,
+ {"eval_dataset": Dataset.from_dict({"input_ids": [[5, 6]]})},
+ )
+
+ with pytest.raises(ValueError, match="does not contain a train dataset"):
+ tokenized_dataset._load_archive(archive_path)
+
+
+def test_load_archive_limits_extracted_size(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
+ archive_path = _write_archive(
+ tmp_path,
+ {"train_dataset": Dataset.from_dict({"input_ids": [[1, 2]]})},
+ )
+ monkeypatch.setattr(tokenized_dataset, "_MAX_EXTRACTED_BYTES", 1)
+
+ with pytest.raises(ValueError, match="too large after extraction"):
+ tokenized_dataset._load_archive(archive_path)
+
+
+def test_missing_datasets_extra_raises_runtime_error(monkeypatch: pytest.MonkeyPatch) -> None:
+ import_module = importlib.import_module
+
+ def missing_datasets(name: str):
+ if name == "datasets":
+ raise ImportError("datasets is not installed")
+ return import_module(name)
+
+ monkeypatch.setattr(tokenized_dataset.importlib, "import_module", missing_datasets)
+
+ with pytest.raises(RuntimeError, match=r"pip install together\[datasets\]"):
+ tokenized_dataset._require_datasets()
+
+
+def test_retrieve_requires_https() -> None:
+ with pytest.raises(ValueError, match="must use HTTPS"):
+ tokenized_dataset.retrieve_dataset("http://download.example/archive.tar.zst", expected_size=0)
+
+
+def test_retrieve_rejects_insecure_redirect(respx_mock: MockRouter) -> None:
+ url = "https://download.example/tokenized-datasets.tar.zst"
+ redirect = respx_mock.get(url).respond(
+ status_code=302,
+ headers={"location": "http://insecure.example/tokenized-datasets.tar.zst"},
+ )
+ insecure_download = respx_mock.get("http://insecure.example/tokenized-datasets.tar.zst").respond(content=b"")
+
+ with pytest.raises(ValueError, match="must use HTTPS"):
+ tokenized_dataset.retrieve_dataset(url, expected_size=0)
+
+ assert redirect.called
+ assert not insecure_download.called
+
+
+def test_retrieve_tokenized_dataset_returns_dataset(
+ respx_mock: MockRouter,
+ tmp_path: Path,
+) -> None:
+ url = "https://download.example/tokenized-datasets.tar.zst"
+ archive_path = _write_archive(
+ tmp_path,
+ {"train_dataset": Dataset.from_dict({"input_ids": [[1, 2]]})},
+ )
+ archive_content = archive_path.read_bytes()
+ _mock_metadata(respx_mock, url, len(archive_content))
+ download = respx_mock.get(url).respond(content=archive_content)
+
+ with Together(api_key="test", base_url="https://api.example") as client:
+ result = client.fine_tuning.retrieve_tokenized_dataset("ft-test", return_dataset=True)
+
+ assert result["train"]["input_ids"] == [[1, 2]]
+ assert download.called
+ assert "authorization" not in download.calls.last.request.headers
+
+
+async def test_async_retrieve_tokenized_dataset_returns_dataset(
+ respx_mock: MockRouter,
+ tmp_path: Path,
+) -> None:
+ url = "https://download.example/tokenized-datasets.tar.zst"
+ archive_path = _write_archive(
+ tmp_path,
+ {"train_dataset": Dataset.from_dict({"input_ids": [[1, 2]]})},
+ )
+ archive_content = archive_path.read_bytes()
+ _mock_metadata(respx_mock, url, len(archive_content))
+ download = respx_mock.get(url).respond(content=archive_content)
+
+ async with AsyncTogether(api_key="test", base_url="https://api.example") as client:
+ result = await client.fine_tuning.retrieve_tokenized_dataset("ft-test", return_dataset=True)
+
+ assert result["train"]["input_ids"] == [[1, 2]]
+ assert download.called
+ assert "authorization" not in download.calls.last.request.headers
+
+
+def test_retrieve_tokenized_dataset_returns_metadata_by_default(respx_mock: MockRouter) -> None:
+ url = "https://download.example/tokenized-datasets.tar.zst"
+ _mock_metadata(respx_mock, url)
+ download = respx_mock.get(url).respond(content=b"not requested")
+
+ with Together(api_key="test", base_url="https://api.example") as client:
+ result = client.fine_tuning.retrieve_tokenized_dataset("ft-test")
+
+ assert result.url == url
+ assert not download.called
+
+
+def test_retrieve_validates_download_size(respx_mock: MockRouter) -> None:
+ url = "https://download.example/tokenized-datasets.tar.zst"
+ _mock_metadata(respx_mock, url, size=10)
+ respx_mock.get(url).respond(content=b"short")
+
+ with Together(api_key="test", base_url="https://api.example") as client:
+ with pytest.raises(ValueError, match="does not match remote file size"):
+ client.fine_tuning.retrieve_tokenized_dataset("ft-test", return_dataset=True)
+
+
+def test_retrieve_stops_oversized_download(respx_mock: MockRouter) -> None:
+ url = "https://download.example/tokenized-datasets.tar.zst"
+ _mock_metadata(respx_mock, url, size=2)
+ respx_mock.get(url).respond(content=b"too large")
+
+ with Together(api_key="test", base_url="https://api.example") as client:
+ with pytest.raises(ValueError, match="exceeds the remote file size"):
+ client.fine_tuning.retrieve_tokenized_dataset("ft-test", return_dataset=True)
+
+
+def test_raw_retrieve_preserves_response_wrapper(respx_mock: MockRouter) -> None:
+ url = "https://download.example/tokenized-datasets.tar.zst"
+ _mock_metadata(respx_mock, url)
+ download = respx_mock.get(url).respond(content=b"not requested")
+
+ with Together(api_key="test", base_url="https://api.example") as client:
+ response = client.fine_tuning.with_raw_response.retrieve_tokenized_dataset(
+ "ft-test",
+ )
+
+ assert cast(Any, response.parse()).url == url
+ assert not download.called
+
+
+def test_streaming_retrieve_preserves_response_wrapper(respx_mock: MockRouter) -> None:
+ url = "https://download.example/tokenized-datasets.tar.zst"
+ _mock_metadata(respx_mock, url)
+ download = respx_mock.get(url).respond(content=b"not requested")
+
+ with Together(api_key="test", base_url="https://api.example") as client:
+ with client.fine_tuning.with_streaming_response.retrieve_tokenized_dataset(
+ "ft-test",
+ ) as response:
+ assert cast(Any, response.parse()).url == url
+
+ assert not download.called
+
+
+async def test_async_raw_retrieve_preserves_response_wrapper(respx_mock: MockRouter) -> None:
+ url = "https://download.example/tokenized-datasets.tar.zst"
+ _mock_metadata(respx_mock, url)
+ download = respx_mock.get(url).respond(content=b"not requested")
+
+ async with AsyncTogether(api_key="test", base_url="https://api.example") as client:
+ response = await client.fine_tuning.with_raw_response.retrieve_tokenized_dataset(
+ "ft-test",
+ )
+
+ assert cast(Any, await response.parse()).url == url
+ assert not download.called
+
+
+async def test_async_streaming_retrieve_preserves_response_wrapper(respx_mock: MockRouter) -> None:
+ url = "https://download.example/tokenized-datasets.tar.zst"
+ _mock_metadata(respx_mock, url)
+ download = respx_mock.get(url).respond(content=b"not requested")
+
+ async with AsyncTogether(api_key="test", base_url="https://api.example") as client:
+ async with client.fine_tuning.with_streaming_response.retrieve_tokenized_dataset(
+ "ft-test",
+ ) as response:
+ assert cast(Any, await response.parse()).url == url
+
+ assert not download.called
+
+
+def test_response_wrapper_rejects_return_dataset() -> None:
+ with Together(api_key="test", base_url="https://api.example") as client:
+ retrieve = cast(Any, client.fine_tuning.with_raw_response.retrieve_tokenized_dataset)
+ with pytest.raises(TypeError, match="return_dataset"):
+ retrieve(
+ "ft-test",
+ return_dataset=True,
+ )
diff --git a/uv.lock b/uv.lock
index 30f75b153..fc406a69a 100644
--- a/uv.lock
+++ b/uv.lock
@@ -2,10 +2,16 @@ version = 1
revision = 3
requires-python = ">=3.10"
resolution-markers = [
- "python_full_version >= '3.14' and extra != 'group-8-together-pydantic-v1' and extra == 'group-8-together-pydantic-v2'",
- "python_full_version < '3.14' and extra != 'group-8-together-pydantic-v1' and extra == 'group-8-together-pydantic-v2'",
- "extra == 'group-8-together-pydantic-v1' and extra != 'group-8-together-pydantic-v2'",
- "extra != 'group-8-together-pydantic-v1' and extra != 'group-8-together-pydantic-v2'",
+ "python_full_version >= '3.14' and sys_platform == 'win32'",
+ "python_full_version >= '3.14' and sys_platform == 'emscripten'",
+ "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+ "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform == 'win32'",
+ "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform == 'emscripten'",
+ "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+ "python_full_version == '3.11.*' and sys_platform == 'win32'",
+ "python_full_version == '3.11.*' and sys_platform == 'emscripten'",
+ "python_full_version == '3.11.*' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+ "python_full_version < '3.11'",
]
conflicts = [[
{ package = "together", group = "pydantic-v1" },
@@ -222,6 +228,181 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/e6/ad/3cc14f097111b4de0040c83a525973216457bbeeb63739ef1ed275c1c021/certifi-2026.1.4-py3-none-any.whl", hash = "sha256:9943707519e4add1115f44c2bc244f782c0249876bf51b6599fee1ffbedd685c", size = 152900, upload-time = "2026-01-04T02:42:40.15Z" },
]
+[[package]]
+name = "charset-normalizer"
+version = "3.5.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/e5/3f/143b048436775b0f76ac3eec145c019e8173ccc2885c8f20319b996d5e83/charset_normalizer-3.5.1.tar.gz", hash = "sha256:6117b84ea48435e5356dc737f5121485c30920ba43375fa7b434fd753df0eac3", size = 171764, upload-time = "2026-08-15T08:20:44.807Z" }
+wheels = [
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