Beta/venv/lib/python3.12/site-packages/huggingface_hub/lfs.py

# Copyright 2019-present, the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Git LFS related type definitions and utilities"""

import io
import re
from collections.abc import Iterable
from dataclasses import dataclass
from math import ceil
from os.path import getsize
from typing import TYPE_CHECKING, BinaryIO, TypedDict
from urllib.parse import unquote

from huggingface_hub import constants

from .utils import (
    build_hf_headers,
    fix_hf_endpoint_in_url,
    hf_raise_for_status,
    http_backoff,
    logging,
    validate_hf_hub_args,
)
from .utils._lfs import SliceFileObj
from .utils.sha import sha256, sha_fileobj


if TYPE_CHECKING:
    from ._commit_api import CommitOperationAdd

logger = logging.get_logger(__name__)

OID_REGEX = re.compile(r"^[0-9a-f]{40}$")

LFS_MULTIPART_UPLOAD_COMMAND = "lfs-multipart-upload"

LFS_HEADERS = {
    "Accept": "application/vnd.git-lfs+json",
    "Content-Type": "application/vnd.git-lfs+json",
}


@dataclass
class UploadInfo:
    """
    Dataclass holding required information to determine whether a blob
    should be uploaded to the hub using the LFS protocol or the regular protocol

    Args:
        sha256 (`bytes`):
            SHA256 hash of the blob
        size (`int`):
            Size in bytes of the blob
        sample (`bytes`):
            First 512 bytes of the blob
    """

    sha256: bytes
    size: int
    sample: bytes

    @classmethod
    def from_path(cls, path: str):
        size = getsize(path)
        with open(path, "rb") as file:
            sample = file.peek(512)[:512]
            sha = sha_fileobj(file)
        return cls(size=size, sha256=sha, sample=sample)

    @classmethod
    def from_bytes(cls, data: bytes):
        sha = sha256(data).digest()
        return cls(size=len(data), sample=data[:512], sha256=sha)

    @classmethod
    def from_fileobj(cls, fileobj: BinaryIO):
        sample = fileobj.read(512)
        fileobj.seek(0, io.SEEK_SET)
        sha = sha_fileobj(fileobj)
        size = fileobj.tell()
        fileobj.seek(0, io.SEEK_SET)
        return cls(size=size, sha256=sha, sample=sample)


@validate_hf_hub_args
def post_lfs_batch_info(
    upload_infos: Iterable[UploadInfo],
    token: str | None,
    repo_type: str,
    repo_id: str,
    revision: str | None = None,
    endpoint: str | None = None,
    headers: dict[str, str] | None = None,
    transfers: list[str] | None = None,
) -> tuple[list[dict], list[dict], str | None]:
    """
    Requests the LFS batch endpoint to retrieve upload instructions

    Learn more: https://github.com/git-lfs/git-lfs/blob/main/docs/api/batch.md

    Args:
        upload_infos (`Iterable` of `UploadInfo`):
            `UploadInfo` for the files that are being uploaded, typically obtained
            from `CommitOperationAdd.upload_info`
        token (`str` or `None`):
            An authentication token (see https://huggingface.co/settings/token).
            Pass `None` to fall back to the local cached token (or no token if unauthenticated).
        repo_type (`str`):
            Type of the repo to upload to: `"model"`, `"dataset"` or `"space"`.
        repo_id (`str`):
            A namespace (user or an organization) and a repo name separated
            by a `/`.
        revision (`str`, *optional*):
            The git revision to upload to.
        endpoint (`str`, *optional*):
            The Hub endpoint to send the request to. Defaults to the value of `HF_ENDPOINT`.
        headers (`dict`, *optional*):
            Additional headers to include in the request
        transfers (`list`, *optional*):
            List of transfer methods to use. Defaults to ["basic", "multipart"].

    Returns:
        `LfsBatchInfo`: 3-tuple:
            - First element is the list of upload instructions from the server
            - Second element is a list of errors, if any
            - Third element is the chosen transfer adapter if provided by the server (e.g. "basic", "multipart", "xet")

    Raises:
        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
            If an argument is invalid or the server response is malformed.
        [`HfHubHTTPError`]
            If the server returned an error.
    """
    endpoint = endpoint if endpoint is not None else constants.ENDPOINT
    url_prefix = ""
    if repo_type in constants.REPO_TYPES_URL_PREFIXES:
        url_prefix = constants.REPO_TYPES_URL_PREFIXES[repo_type]
    batch_url = f"{endpoint}/{url_prefix}{repo_id}.git/info/lfs/objects/batch"
    payload: dict = {
        "operation": "upload",
        "transfers": transfers if transfers is not None else ["basic", "multipart"],
        "objects": [
            {
                "oid": upload.sha256.hex(),
                "size": upload.size,
            }
            for upload in upload_infos
        ],
        "hash_algo": "sha256",
    }
    if revision is not None:
        payload["ref"] = {"name": unquote(revision)}  # revision has been previously 'quoted'

    headers = {
        **LFS_HEADERS,
        **build_hf_headers(token=token),
        **(headers or {}),
    }
    resp = http_backoff("POST", batch_url, headers=headers, json=payload)
    hf_raise_for_status(resp)
    batch_info = resp.json()

    objects = batch_info.get("objects", None)
    if not isinstance(objects, list):
        raise ValueError("Malformed response from server")

    chosen_transfer = batch_info.get("transfer")
    chosen_transfer = chosen_transfer if isinstance(chosen_transfer, str) else None

    return (
        [_validate_batch_actions(obj) for obj in objects if "error" not in obj],
        [_validate_batch_error(obj) for obj in objects if "error" in obj],
        chosen_transfer,
    )


class PayloadPartT(TypedDict):
    partNumber: int
    etag: str


class CompletionPayloadT(TypedDict):
    """Payload that will be sent to the Hub when uploading multi-part."""

    oid: str
    parts: list[PayloadPartT]


def lfs_upload(
    operation: "CommitOperationAdd",
    lfs_batch_action: dict,
    token: str | None = None,
    headers: dict[str, str] | None = None,
    endpoint: str | None = None,
) -> None:
    """
    Handles uploading a given object to the Hub with the LFS protocol.

    Can be a No-op if the content of the file is already present on the hub large file storage.

    Args:
        operation (`CommitOperationAdd`):
            The add operation triggering this upload.
        lfs_batch_action (`dict`):
            Upload instructions from the LFS batch endpoint for this object. See [`~utils.lfs.post_lfs_batch_info`] for
            more details.
        token (`str`, *optional*):
            An authentication token (see https://huggingface.co/settings/token). Used to call the
            optional LFS verify step at the end of the upload. If `None`, falls back to the local
            cached token.
        headers (`dict`, *optional*):
            Headers to include in the request, including authentication and user agent headers.
        endpoint (`str`, *optional*):
            The Hub endpoint to send the request to. Defaults to the value of `HF_ENDPOINT`.

    Raises:
        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
            If `lfs_batch_action` is improperly formatted
        [`HfHubHTTPError`]
            If the upload resulted in an error
    """
    # 0. If LFS file is already present, skip upload
    _validate_batch_actions(lfs_batch_action)
    actions = lfs_batch_action.get("actions")
    if actions is None:
        # The file was already uploaded
        logger.debug(f"Content of file {operation.path_in_repo} is already present upstream - skipping upload")
        return

    # 1. Validate server response (check required keys in dict)
    upload_action = lfs_batch_action["actions"]["upload"]
    _validate_lfs_action(upload_action)
    verify_action = lfs_batch_action["actions"].get("verify")
    if verify_action is not None:
        _validate_lfs_action(verify_action)

    # 2. Upload file (either single part or multi-part)
    header = upload_action.get("header", {})
    chunk_size = header.get("chunk_size")
    upload_url = fix_hf_endpoint_in_url(upload_action["href"], endpoint=endpoint)
    if chunk_size is not None:
        try:
            chunk_size = int(chunk_size)
        except (ValueError, TypeError):
            raise ValueError(
                f"Malformed response from LFS batch endpoint: `chunk_size` should be an integer. Got '{chunk_size}'."
            )
        _upload_multi_part(operation=operation, header=header, chunk_size=chunk_size, upload_url=upload_url)
    else:
        _upload_single_part(operation=operation, upload_url=upload_url)

    # 3. Verify upload went well
    if verify_action is not None:
        _validate_lfs_action(verify_action)
        verify_url = fix_hf_endpoint_in_url(verify_action["href"], endpoint)
        verify_resp = http_backoff(
            "POST",
            verify_url,
            headers=build_hf_headers(token=token, headers=headers),
            json={"oid": operation.upload_info.sha256.hex(), "size": operation.upload_info.size},
        )
        hf_raise_for_status(verify_resp)
    logger.debug(f"{operation.path_in_repo}: Upload successful")


def _validate_lfs_action(lfs_action: dict):
    """validates response from the LFS batch endpoint"""
    if not (
        isinstance(lfs_action.get("href"), str)
        and (lfs_action.get("header") is None or isinstance(lfs_action.get("header"), dict))
    ):
        raise ValueError("lfs_action is improperly formatted")
    return lfs_action


def _validate_batch_actions(lfs_batch_actions: dict):
    """validates response from the LFS batch endpoint"""
    if not (isinstance(lfs_batch_actions.get("oid"), str) and isinstance(lfs_batch_actions.get("size"), int)):
        raise ValueError("lfs_batch_actions is improperly formatted")

    upload_action = lfs_batch_actions.get("actions", {}).get("upload")
    verify_action = lfs_batch_actions.get("actions", {}).get("verify")
    if upload_action is not None:
        _validate_lfs_action(upload_action)
    if verify_action is not None:
        _validate_lfs_action(verify_action)
    return lfs_batch_actions


def _validate_batch_error(lfs_batch_error: dict):
    """validates response from the LFS batch endpoint"""
    if not (isinstance(lfs_batch_error.get("oid"), str) and isinstance(lfs_batch_error.get("size"), int)):
        raise ValueError("lfs_batch_error is improperly formatted")
    error_info = lfs_batch_error.get("error")
    if not (
        isinstance(error_info, dict)
        and isinstance(error_info.get("message"), str)
        and isinstance(error_info.get("code"), int)
    ):
        raise ValueError("lfs_batch_error is improperly formatted")
    return lfs_batch_error


def _upload_single_part(operation: "CommitOperationAdd", upload_url: str) -> None:
    """
    Uploads `fileobj` as a single PUT HTTP request (basic LFS transfer protocol)

    Args:
        upload_url (`str`):
            The URL to PUT the file to.
        fileobj:
            The file-like object holding the data to upload.

    Raises:
        [`HfHubHTTPError`]
            If the upload resulted in an error.
    """
    with operation.as_file(with_tqdm=True) as fileobj:
        # S3 might raise a transient 500 error -> let's retry if that happens
        response = http_backoff("PUT", upload_url, data=fileobj)
        hf_raise_for_status(response)


def _upload_multi_part(operation: "CommitOperationAdd", header: dict, chunk_size: int, upload_url: str) -> None:
    """
    Uploads file using HF multipart LFS transfer protocol.
    """
    # 1. Get upload URLs for each part
    sorted_parts_urls = _get_sorted_parts_urls(header=header, upload_info=operation.upload_info, chunk_size=chunk_size)

    # 2. Upload parts (pure Python)
    response_headers = _upload_parts_iteratively(
        operation=operation, sorted_parts_urls=sorted_parts_urls, chunk_size=chunk_size
    )

    # 3. Send completion request
    # NOTE: `upload_url` is the Hub completion endpoint (not the S3 upload URLs).
    completion_res = http_backoff(
        "POST",
        upload_url,
        json=_get_completion_payload(response_headers, operation.upload_info.sha256.hex()),
        headers=LFS_HEADERS,
    )
    hf_raise_for_status(completion_res)


def _get_sorted_parts_urls(header: dict, upload_info: UploadInfo, chunk_size: int) -> list[str]:
    sorted_part_upload_urls = [
        upload_url
        for _, upload_url in sorted(
            [
                (int(part_num, 10), upload_url)
                for part_num, upload_url in header.items()
                if part_num.isdigit() and len(part_num) > 0
            ],
            key=lambda t: t[0],
        )
    ]
    num_parts = len(sorted_part_upload_urls)
    if num_parts != ceil(upload_info.size / chunk_size):
        raise ValueError("Invalid server response to upload large LFS file")
    return sorted_part_upload_urls


def _get_completion_payload(response_headers: list[dict], oid: str) -> CompletionPayloadT:
    parts: list[PayloadPartT] = []
    for part_number, header in enumerate(response_headers):
        etag = header.get("etag")
        if etag is None or etag == "":
            raise ValueError(f"Invalid etag (`{etag}`) returned for part {part_number + 1}")
        parts.append(
            {
                "partNumber": part_number + 1,
                "etag": etag,
            }
        )
    return {"oid": oid, "parts": parts}


def _upload_parts_iteratively(
    operation: "CommitOperationAdd", sorted_parts_urls: list[str], chunk_size: int
) -> list[dict]:
    headers = []
    with operation.as_file(with_tqdm=True) as fileobj:
        for part_idx, part_upload_url in enumerate(sorted_parts_urls):
            with SliceFileObj(
                fileobj,
                seek_from=chunk_size * part_idx,
                read_limit=chunk_size,
            ) as fileobj_slice:
                # S3 might raise a transient 500 error -> let's retry if that happens
                part_upload_res = http_backoff("PUT", part_upload_url, data=fileobj_slice)
                hf_raise_for_status(part_upload_res)
                headers.append(part_upload_res.headers)
    return headers  # type: ignore