+ +
+
+
+
+
+
+ The official CLI and Python client for the Hugging Face Hub.
+
+ About
+ ·
+ Documentation
+ ·
+ Install
+ ·
+ CLI Guide
+ ·
+ Contributing
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+ 
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+ English | + Deutsch | + Français | + हिंदी | + 한국어 | + 中文 (简体) | + ಕನ್ನಡ +
+ + +## Quick start + +Install the [`hf` CLI](https://huggingface.co/docs/huggingface_hub/en/guides/cli) with the standalone installer: + +```bash +# On macOS and Linux. +curl -LsSf https://hf.co/cli/install.sh | bash +``` + +```powershell +# On Windows. +powershell -ExecutionPolicy ByPass -c "irm https://hf.co/cli/install.ps1 | iex" +``` + +Log in, then start working with the Hub: + +```bash +# Log in (use --token $HF_TOKEN in non-interactive environments) +hf auth login + +# Find models served by Inference Providers +hf models ls --warm + +# Download a model +hf download Qwen/Qwen3-0.6B + +# Upload files to your own repo +hf upload username/my-cool-model ./model.safetensors + +# Sync a local folder to a storage bucket +hf buckets sync ./checkpoints hf://buckets/username/my-bucket + +# Run a job on Hugging Face infrastructure +hf jobs run python:3.12 python -c "print('Hello from the cloud!')" + +# Discover everything else +hf --help +``` + +The Hub uses tokens to authenticate applications (see [docs](https://huggingface.co/docs/hub/security-tokens)). Check out the [CLI guide](https://huggingface.co/docs/huggingface_hub/en/guides/cli) for a tour of the main features. + +## What is `huggingface_hub`? + +The `huggingface_hub` library allows you to interact with the [Hugging Face Hub](https://huggingface.co/), a platform democratizing open-source Machine Learning for creators and collaborators. Discover pre-trained models and datasets for your projects, play with the thousands of machine learning apps hosted on the Hub, or create and share your own models, datasets and demos with the community. Everything ships in one package with two interfaces: the [`hf` CLI](https://huggingface.co/docs/huggingface_hub/en/guides/cli) for your terminal and the `huggingface_hub` library for Python — both designed to work well for humans and AI agents. Use them to: + +- [Download files](https://huggingface.co/docs/huggingface_hub/en/guides/download) from the Hub. +- [Upload files](https://huggingface.co/docs/huggingface_hub/en/guides/upload) to the Hub. +- [Manage your repositories](https://huggingface.co/docs/huggingface_hub/en/guides/repository). +- [Run Inference](https://huggingface.co/docs/huggingface_hub/en/guides/inference) on deployed models. +- [Run Jobs](https://huggingface.co/docs/huggingface_hub/en/guides/jobs) on Hugging Face infrastructure. +- [Search](https://huggingface.co/docs/huggingface_hub/en/guides/search) for models, datasets and Spaces. +- [Share Model Cards](https://huggingface.co/docs/huggingface_hub/en/guides/model-cards) to document your models. +- [Engage with the community](https://huggingface.co/docs/huggingface_hub/en/guides/community) through PRs and comments. +- Do all of the above from the terminal with the [`hf` CLI](https://huggingface.co/docs/huggingface_hub/en/guides/cli). + +## Built for humans and AI agents + +The `hf` CLI is designed for people and coding agents alike: the same commands adapt their output when run by an agent. If you use Claude Code, Codex, Cursor, or another coding agent, install the `hf` CLI Skill — a command reference generated from your installed CLI: + +```bash +# for Codex, Cursor, OpenCode, Pi and other agents that load skills from `.agents/skills` +hf skills add +# includes the above + Claude Code +hf skills add --claude +``` + +Learn more in the [Hugging Face CLI for AI agents guide](https://huggingface.co/docs/hub/agents-cli) and the [announcement blog post](https://huggingface.co/blog/hf-cli-for-agents). + +## Use the Python library + +Install the `huggingface_hub` package with [pip](https://pypi.org/project/huggingface-hub/) (this also installs the `hf` CLI): + +```bash +pip install huggingface_hub +``` + +We recommend using [`uv`](https://docs.astral.sh/uv/) for a fast and reliable install: + +```bash +uv pip install huggingface_hub +``` + +In order to keep the package minimal by default, `huggingface_hub` comes with optional dependencies useful for some use cases. For example, if you want to use the MCP module, run: + +```bash +pip install "huggingface_hub[mcp]" +``` + +To learn more about installation and optional dependencies, check out the [installation guide](https://huggingface.co/docs/huggingface_hub/en/installation). + +### Download files + +Download a single file + +```py +from huggingface_hub import hf_hub_download + +hf_hub_download(repo_id="zai-org/GLM-5.2", filename="config.json") +``` + +Or an entire repository + +```py +from huggingface_hub import snapshot_download + +snapshot_download("sentence-transformers/all-MiniLM-L6-v2") +``` + +Files will be downloaded in a local cache folder. More details in [this guide](https://huggingface.co/docs/huggingface_hub/en/guides/manage-cache). + +### Create a repository + +```py +from huggingface_hub import create_repo + +create_repo(repo_id="super-cool-model") +``` + +### Upload files + +Upload a single file + +```py +from huggingface_hub import upload_file + +upload_file( + path_or_fileobj="/home/lysandre/dummy-test/README.md", + path_in_repo="README.md", + repo_id="lysandre/test-model", +) +``` + +Or an entire folder + +```py +from huggingface_hub import upload_folder + +upload_folder( + folder_path="/path/to/local/space", + repo_id="username/my-cool-space", + repo_type="space", +) +``` + +More details in the [upload guide](https://huggingface.co/docs/huggingface_hub/en/guides/upload). + +## Integrating with the Hub. + +We're partnering with cool open source ML libraries to provide free model hosting and versioning. You can find the existing integrations [here](https://huggingface.co/docs/hub/libraries). + +The advantages are: + +- Free model or dataset hosting for libraries and their users. +- Built-in file versioning, even with very large files, made possible by [Xet](https://huggingface.co/docs/hub/xet/index), the Hub's chunk-deduplicated storage backend. +- In-browser widgets to play with the uploaded models. +- Anyone can upload a new model for your library, they just need to add the corresponding tag for the model to be discoverable. +- Fast downloads! We use Cloudfront (a CDN) to geo-replicate downloads so they're blazing fast from anywhere on the globe. +- Usage stats and more features to come. + +If you would like to integrate your library, feel free to open an issue to begin the discussion. We wrote a [step-by-step guide](https://huggingface.co/docs/hub/adding-a-library) with ❤️ showing how to do this integration. + +## Contributions (feature requests, bugs, etc.) are super welcome 💙💚💛💜🧡❤️ + +Everyone is welcome to contribute, and we value everybody's contribution. Code is not the only way to help the community. +Answering questions, helping others, reaching out and improving the documentations are immensely valuable to the community. +We wrote a [contribution guide](https://github.com/huggingface/huggingface_hub/blob/main/CONTRIBUTING.md) to summarize +how to get started to contribute to this repository. diff --git a/.venv/lib/python3.12/site-packages/huggingface_hub-1.24.0.dist-info/RECORD b/.venv/lib/python3.12/site-packages/huggingface_hub-1.24.0.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..7a6e252a4a8b4b14fe7246495656ee7d2528e8ea --- /dev/null +++ b/.venv/lib/python3.12/site-packages/huggingface_hub-1.24.0.dist-info/RECORD @@ -0,0 +1,376 @@ +../../../bin/hf,sha256=QzqAAPLHTL_yQruKm9ioWfHK-6KEvBiZ5ghwRNb6meQ,203 +../../../bin/huggingface-cli,sha256=RkGTZ1xtx21Q0MKTIVPO5Ru9x--InCCDi-rcTUNolV8,215 +../../../bin/tiny-agents,sha256=QxqPt8N8zZVpaY1prKwqUB5LM_mO4GkdqABKYi0qGNs,213 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true +Tag: py3-none-any + diff --git a/.venv/lib/python3.12/site-packages/huggingface_hub-1.24.0.dist-info/entry_points.txt b/.venv/lib/python3.12/site-packages/huggingface_hub-1.24.0.dist-info/entry_points.txt new file mode 100644 index 0000000000000000000000000000000000000000..62018f2f5622f61920179a20b80488f21dbb1686 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/huggingface_hub-1.24.0.dist-info/entry_points.txt @@ -0,0 +1,7 @@ +[console_scripts] +hf = huggingface_hub.cli.hf:main +huggingface-cli = huggingface_hub.cli.deprecated_cli:main +tiny-agents = huggingface_hub.inference._mcp.cli:app + +[fsspec.specs] +hf = huggingface_hub.HfFileSystem diff --git a/.venv/lib/python3.12/site-packages/huggingface_hub-1.24.0.dist-info/licenses/LICENSE b/.venv/lib/python3.12/site-packages/huggingface_hub-1.24.0.dist-info/licenses/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..261eeb9e9f8b2b4b0d119366dda99c6fd7d35c64 --- /dev/null +++ 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All rights reserved. +# +# 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. +"""Contains a helper to get the token from machine (env variable, secret or config file).""" + +import configparser +import io +import logging +import os +import time +import warnings +from pathlib import Path +from threading import Lock +from typing import TypedDict + +from .. import constants +from ..errors import DeviceCodeError, OAuthErrorCode, OIDCError +from ._fixes import WeakFileLock +from ._oauth_device import refresh_access_token +from ._runtime import is_colab_enterprise, is_google_colab + + +_SECRET_FILE_MODE = 0o600 +_SECRET_DIR_MODE = 0o700 + + +def _write_secret(path: Path, content: str) -> None: + """Write content to file, restricting both the file and its parent directory to owner-only on POSIX systems.""" + path.parent.mkdir(parents=True, exist_ok=True, mode=_SECRET_DIR_MODE) + fd = os.open(str(path), os.O_WRONLY | os.O_CREAT | os.O_TRUNC, _SECRET_FILE_MODE) + with os.fdopen(fd, "w") as f: + f.write(content) + try: + path.chmod(_SECRET_FILE_MODE) + path.parent.chmod(_SECRET_DIR_MODE) + except (OSError, NotImplementedError): + # Windows does not support POSIX modes; chmod() will raise. Best-effort. + pass + + +_IS_GOOGLE_COLAB_CHECKED = False +_GOOGLE_COLAB_SECRET_LOCK = Lock() +_GOOGLE_COLAB_SECRET: str | None = None + +logger = logging.getLogger(__name__) + + +def get_token() -> str | None: + """ + Get token if user is logged in. + + Note: in most cases, you should use [`huggingface_hub.utils.build_hf_headers`] instead. This method is only useful + if you want to retrieve the token for other purposes than sending an HTTP request. + + If `HF_OIDC_RESOURCE` is set (Trusted Publishers, typically in CI), a short-lived token obtained via OIDC token + exchange takes precedence. Otherwise the token is retrieved from the `HF_TOKEN` environment variable, then from the + token file in the Hugging Face home folder. Returns None if user is not logged in. To log in, use [`login`] or + `hf auth login`. + + OAuth tokens obtained with the browser-based login come with a refresh token: when such a token is close to + expiry, it is transparently refreshed and persisted before being returned. + + Note: if `HF_OIDC_RESOURCE` is set but the OIDC token exchange fails, this raises instead of returning `None`, + opting into OIDC is explicit, so a failure surfaces as a clear error rather than a silent fallback. + + Returns: + `str` or `None`: The token, `None` if it doesn't exist. + """ + return ( + _get_token_from_oidc() + or _get_token_from_environment() + or _get_token_from_file_refreshed() + or _get_token_from_google_colab() + ) + + +def _get_token_from_google_colab() -> str | None: + """Get token from Google Colab secrets vault using `google.colab.userdata.get(...)`. + + Token is read from the vault only once per session and then stored in a global variable to avoid re-requesting + access to the vault. + """ + # If it's not a Google Colab or it's Colab Enterprise, fallback to environment variable or token file authentication + if not is_google_colab() or is_colab_enterprise(): + return None + + # `google.colab.userdata` is not thread-safe + # This can lead to a deadlock if multiple threads try to access it at the same time + # (typically when using `snapshot_download`) + # => use a lock + # See https://github.com/huggingface/huggingface_hub/issues/1952 for more details. + with _GOOGLE_COLAB_SECRET_LOCK: + global _GOOGLE_COLAB_SECRET + global _IS_GOOGLE_COLAB_CHECKED + + if _IS_GOOGLE_COLAB_CHECKED: # request access only once + return _GOOGLE_COLAB_SECRET + + try: + from google.colab import userdata # type: ignore + from google.colab.errors import Error as ColabError # type: ignore + except ImportError: + return None + + try: + token = userdata.get("HF_TOKEN") + _GOOGLE_COLAB_SECRET = _clean_token(token) + except userdata.NotebookAccessError: + # Means the user has a secret call `HF_TOKEN` and got a popup "please grand access to HF_TOKEN" and refused it + # => warn user but ignore error => do not re-request access to user + warnings.warn( + "\nAccess to the secret `HF_TOKEN` has not been granted on this notebook." + "\nYou will not be requested again." + "\nPlease restart the session if you want to be prompted again." + ) + _GOOGLE_COLAB_SECRET = None + except userdata.SecretNotFoundError: + # No `HF_TOKEN` secret defined: simply not logged in via the Colab vault. Not worth a + # warning now that `login()` is the primary flow (it would even fire during `login()` + # itself, telling the user to set up a secret while they are busy authenticating). + logger.info( + "The secret `HF_TOKEN` does not exist in your Colab secrets. Run `huggingface_hub.login()` to" + " authenticate (recommended but still optional to access public models or datasets)." + ) + _GOOGLE_COLAB_SECRET = None + except ColabError as e: + # Something happen but we don't know what => recommend to open a GitHub issue + warnings.warn(f"\nError while fetching `HF_TOKEN` secret value from your vault: '{str(e)}'.") + _GOOGLE_COLAB_SECRET = None + + _IS_GOOGLE_COLAB_CHECKED = True + return _GOOGLE_COLAB_SECRET + + +def _get_token_from_environment() -> str | None: + # `HF_TOKEN` has priority (keep `HUGGING_FACE_HUB_TOKEN` for backward compatibility) + return _clean_token(os.environ.get("HF_TOKEN") or os.environ.get("HUGGING_FACE_HUB_TOKEN")) + + +def _get_token_from_file() -> str | None: + try: + return _clean_token(Path(constants.HF_TOKEN_PATH).read_text()) + except FileNotFoundError: + return None + + +class _OidcTokenCache(TypedDict): + resource: str + token: str + expires_at: float # monotonic clock value after which the cached token must be re-exchanged + + +# Cache for the OIDC-exchanged token: re-exchanging on every `get_token()` call would be wasteful, +# and re-exchanging shortly before expiry transparently keeps long-running jobs authenticated. +_OIDC_TOKEN_LOCK = Lock() +_OIDC_TOKEN_CACHE: _OidcTokenCache | None = None +_OIDC_REFRESH_MARGIN = 300 # re-exchange this many seconds before the token actually expires + + +def _get_token_from_oidc() -> str | None: + """Get a short-lived OIDC token in CI (Trusted Publishers). + + Enabled by setting `HF_OIDC_RESOURCE`, which scopes the token to a repo or user. + The ID token is read from `HF_OIDC_ID_TOKEN` if available, or minted from a supported CI provider (e.g. GitHub Actions). + + Returns `None` when OIDC is not enabled. + If enabled, any failure is raised explicitly rather than falling back silently. + + See `huggingface_hub._oidc` and https://huggingface.co/docs/hub/trusted-publishers. + """ + resource = os.environ.get("HF_OIDC_RESOURCE") + if not resource: + return None + + from .._oidc import detect_provider, oidc_login + + global _OIDC_TOKEN_CACHE + with _OIDC_TOKEN_LOCK: + now = time.monotonic() + if ( + _OIDC_TOKEN_CACHE is not None + and _OIDC_TOKEN_CACHE["resource"] == resource + and now < _OIDC_TOKEN_CACHE["expires_at"] + ): + return _OIDC_TOKEN_CACHE["token"] + + # An explicit id token (any provider) takes precedence; otherwise mint from a detected one. + subject_token = os.environ.get("HF_OIDC_ID_TOKEN") or None + if subject_token is None and detect_provider() is None: + raise OIDCError( + "HF_OIDC_RESOURCE is set but no OIDC id token is available: not running in a supported " + "CI provider (github) and HF_OIDC_ID_TOKEN is not set. Set HF_OIDC_ID_TOKEN to the id " + "token minted by your CI provider, or unset HF_OIDC_RESOURCE." + ) + + result = oidc_login(resource=resource, subject_token=subject_token) + token = result["access_token"] + expires_in = int(result.get("expires_in", 3600)) + # A pre-supplied HF_OIDC_ID_TOKEN can't be re-minted, so refreshing early is pointless (the id + # token is likely already expired by then): cache for the full lifetime. Only the auto-minted + # path can refresh, so only it gets the safety margin. + margin = 0 if subject_token is not None else _OIDC_REFRESH_MARGIN + _OIDC_TOKEN_CACHE = { + "resource": resource, + "token": token, + "expires_at": now + max(expires_in - margin, 0), + } + return token + + +class _OAuthRefreshCache(TypedDict): + file_token: str # token as read from HF_TOKEN_PATH (cache key) + resolved_token: str # token to return (refreshed, or identical if no refresh was needed) + recheck_at: float # wall-clock timestamp after which the expiry must be re-evaluated + + +# Cache the refresh decision in-process: `get_token()` is called on every HTTP request and must not +# re-read the stored tokens file (let alone hit the network) each time. +_OAUTH_REFRESH_LOCK = Lock() +_OAUTH_REFRESH_CACHE: _OAuthRefreshCache | None = None +_OAUTH_REFRESH_MARGIN = 24 * 3600 # refresh when less than 1 day of validity remains +_OAUTH_RECHECK_INTERVAL = 300 # re-check interval when there is no metadata or the refresh failed +_OAUTH_REFRESH_WARNED = False # warn at most once per process on refresh failure + + +def _get_token_from_file_refreshed() -> str | None: + """Get the token from `HF_TOKEN_PATH`, transparently refreshing it if close to expiry.""" + token = _get_token_from_file() + if token is None: + return None + return _refresh_oauth_token_if_needed(token) + + +def _refresh_oauth_token_if_needed(token: str) -> str: + """Refresh an OAuth access token if it is close to expiry. Best-effort: never raises. + + OAuth tokens obtained with the browser-based login are stored with a `refresh_token` and an + `expires_at` timestamp (see `_save_token`). When the active token is one of them and about to + expire, exchange the refresh token for a new access token and persist it. Any other token is + returned unchanged. + """ + global _OAUTH_REFRESH_CACHE + with _OAUTH_REFRESH_LOCK: + now = time.time() + cache = _OAUTH_REFRESH_CACHE + if cache is not None and cache["file_token"] == token and now < cache["recheck_at"]: + return cache["resolved_token"] + + token_name, fields = next( + ((name, fields) for name, fields in _read_stored_tokens_full().items() if fields.get("hf_token") == token), + (None, {}), + ) + refresh_token = fields.get("refresh_token") + expires_at = _parse_expires_at(fields) + if token_name is None or refresh_token is None or expires_at is None: + # `token` may have just been replaced by a concurrent refresh (in which case it no + # longer appears in the stored tokens): serve the fresh file token without caching. + current_file_token = _get_token_from_file() + if current_file_token is not None and current_file_token != token: + return current_file_token + # Not a refreshable OAuth token (or its metadata was lost): nothing to do. + _OAUTH_REFRESH_CACHE = { + "file_token": token, + "resolved_token": token, + "recheck_at": now + _OAUTH_RECHECK_INTERVAL, + } + return token + + if expires_at - _OAUTH_REFRESH_MARGIN > now: + _OAUTH_REFRESH_CACHE = { + "file_token": token, + "resolved_token": token, + "recheck_at": expires_at - _OAUTH_REFRESH_MARGIN, + } + return token + + try: + # Cross-process file lock: if the server rotates refresh tokens, two processes + # refreshing concurrently would invalidate each other's refresh token. + with WeakFileLock(constants.HF_STORED_TOKENS_PATH + ".lock", timeout=30): + # Re-read under the lock: another process may have refreshed in the meantime. + fields = _read_stored_tokens_full().get(token_name, {}) + if fields.get("hf_token") != token: + # Another process already refreshed this token: adopt its result. + new_token = fields.get("hf_token") or token + new_expires_at = _parse_expires_at(fields) + else: + response = refresh_access_token(refresh_token) + new_token = response["access_token"] + new_expires_at = int(now) + int(response["expires_in"]) if "expires_in" in response else None + _save_token( + token=new_token, + token_name=token_name, + # The server may rotate the refresh token; keep the old one if it doesn't. + refresh_token=response.get("refresh_token") or refresh_token, + expires_at=new_expires_at, + ) + # Update the active token file, unless another process switched to a different token meanwhile. + if _get_token_from_file() == token: + _write_secret(Path(constants.HF_TOKEN_PATH), new_token) + logger.info(f"Access token `{token_name}` has been refreshed.") + except Exception as e: + if isinstance(e, DeviceCodeError) and e.error_code == OAuthErrorCode.INVALID_GRANT: + # Refresh token expired or revoked: retrying is pointless, a re-login is required. + # Warned unconditionally (the inf recheck guarantees it fires at most once): an + # earlier transient warning must not suppress this actionable message. + logger.warning( + "Your Hugging Face access token has expired and could not be refreshed " + f"(session expired or revoked). Run `hf auth login` to re-authenticate. ({e})" + ) + recheck_at = float("inf") + else: + # Transient failure (offline, server error, ...): retry later. + _warn_refresh_failure_once(f"Could not refresh your Hugging Face access token: {e}. Will retry later.") + recheck_at = now + _OAUTH_RECHECK_INTERVAL + # Return the existing token: if it's truly expired, the API will reject it with a clear error. + _OAUTH_REFRESH_CACHE = {"file_token": token, "resolved_token": token, "recheck_at": recheck_at} + return token + + _OAUTH_REFRESH_CACHE = { + "file_token": new_token, + "resolved_token": new_token, + # The floor guards against a token lifetime shorter than the refresh margin, which + # would otherwise put `recheck_at` in the past and trigger a refresh on every call. + "recheck_at": max( + now + _OAUTH_RECHECK_INTERVAL, + new_expires_at - _OAUTH_REFRESH_MARGIN if new_expires_at else 0, + ), + } + return new_token + + +def _warn_refresh_failure_once(message: str) -> None: + global _OAUTH_REFRESH_WARNED + if not _OAUTH_REFRESH_WARNED: + logger.warning(message) + _OAUTH_REFRESH_WARNED = True + + +def _parse_expires_at(fields: dict[str, str]) -> int | None: + """Parse the `expires_at` field of a stored-tokens section, `None` if missing or corrupt.""" + try: + return int(fields["expires_at"]) + except (KeyError, ValueError): + return None + + +def get_stored_tokens() -> dict[str, str]: + """ + Returns the parsed INI file containing the access tokens. + The file is located at `HF_STORED_TOKENS_PATH`, defaulting to `~/.cache/huggingface/stored_tokens`. + If the file does not exist, an empty dictionary is returned. + + Returns: `dict[str, str]` + Key is the token name and value is the token. + """ + return {token_name: fields.get("hf_token", "") for token_name, fields in _read_stored_tokens_full().items()} + + +def _read_stored_tokens_full() -> dict[str, dict[str, str]]: + """Read all sections of the stored tokens INI file, with all their fields. + + Beside `hf_token`, sections for OAuth tokens also carry `refresh_token` and `expires_at` + (unix timestamp), used by [`get_token`] to transparently refresh them. + """ + tokens_path = Path(constants.HF_STORED_TOKENS_PATH) + if not tokens_path.exists(): + return {} + # interpolation=None: token values are opaque strings, a `%` must not be interpreted. + config = configparser.ConfigParser(interpolation=None) + try: + config.read(tokens_path) + return {token_name: dict(config.items(token_name)) for token_name in config.sections()} + except configparser.Error as e: + logger.error(f"Error parsing stored tokens file: {e}") + return {} + + +def _save_stored_tokens_full(stored_tokens: dict[str, dict[str, str]]) -> None: + """Write all sections and their fields to the stored tokens INI file.""" + config = configparser.ConfigParser(interpolation=None) + for token_name in sorted(stored_tokens.keys()): + config.add_section(token_name) + for key, value in stored_tokens[token_name].items(): + config.set(token_name, key, value) + + buf = io.StringIO() + config.write(buf) + _write_secret(Path(constants.HF_STORED_TOKENS_PATH), buf.getvalue()) + + +def _get_token_by_name(token_name: str) -> str | None: + """ + Get the token by name. + + Args: + token_name (`str`): + The name of the token to get. + + Returns: + `str` or `None`: The token, `None` if it doesn't exist. + + """ + stored_tokens = get_stored_tokens() + if token_name not in stored_tokens: + return None + return _clean_token(stored_tokens[token_name]) + + +def _save_token( + token: str, token_name: str, *, refresh_token: str | None = None, expires_at: int | None = None +) -> None: + """ + Save the given token. + + If the stored tokens file does not exist, it will be created. + Args: + token (`str`): + The token to save. + token_name (`str`): + The name of the token. + refresh_token (`str`, *optional*): + OAuth refresh token used to renew the access token when it expires. + expires_at (`int`, *optional*): + Unix timestamp at which the access token expires. + """ + stored_tokens = _read_stored_tokens_full() + fields = {"hf_token": token} + if refresh_token is not None: + fields["refresh_token"] = refresh_token + if expires_at is not None: + fields["expires_at"] = str(expires_at) + # Replace the whole section: re-logging in under the same name must drop stale metadata. + stored_tokens[token_name] = fields + _save_stored_tokens_full(stored_tokens) + logger.info(f"The token `{token_name}` has been saved to {constants.HF_STORED_TOKENS_PATH}") + + +def _clean_token(token: str | None) -> str | None: + """Clean token by removing trailing and leading spaces and newlines. + + If token is an empty string, return None. + """ + if token is None: + return None + return token.replace("\r", "").replace("\n", "").strip() or None diff --git a/.venv/lib/python3.12/site-packages/huggingface_hub/utils/_cache_assets.py b/.venv/lib/python3.12/site-packages/huggingface_hub/utils/_cache_assets.py new file mode 100644 index 0000000000000000000000000000000000000000..01263873715c56d8331200b47a4608a1b1135ab7 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/huggingface_hub/utils/_cache_assets.py @@ -0,0 +1,133 @@ +# 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. +from pathlib import Path + +from ..constants import HF_ASSETS_CACHE + + +def cached_assets_path( + library_name: str, + namespace: str = "default", + subfolder: str = "default", + *, + assets_dir: str | Path | None = None, +) -> Path: + """Return a folder path to cache arbitrary files. + + `huggingface_hub` provides a canonical folder path to store assets. This is the + recommended way to integrate cache in a downstream library as it will benefit from + the builtins tools to scan and delete the cache properly. + + The distinction is made between files cached from the Hub and assets. Files from the + Hub are cached in a git-aware manner and entirely managed by `huggingface_hub`. See + [related documentation](https://huggingface.co/docs/huggingface_hub/how-to-cache). + All other files that a downstream library caches are considered to be "assets" + (files downloaded from external sources, extracted from a .tar archive, preprocessed + for training,...). + + Once the folder path is generated, it is guaranteed to exist and to be a directory. + The path is based on 3 levels of depth: the library name, a namespace and a + subfolder. Those 3 levels grants flexibility while allowing `huggingface_hub` to + expect folders when scanning/deleting parts of the assets cache. Within a library, + it is expected that all namespaces share the same subset of subfolder names but this + is not a mandatory rule. The downstream library has then full control on which file + structure to adopt within its cache. Namespace and subfolder are optional (would + default to a `"default/"` subfolder) but library name is mandatory as we want every + downstream library to manage its own cache. + + Expected tree: + ```text + assets/ + └── datasets/ + │ ├── SQuAD/ + │ │ ├── downloaded/ + │ │ ├── extracted/ + │ │ └── processed/ + │ ├── Helsinki-NLP--tatoeba_mt/ + │ ├── downloaded/ + │ ├── extracted/ + │ └── processed/ + └── transformers/ + ├── default/ + │ ├── something/ + ├── bert-base-cased/ + │ ├── default/ + │ └── training/ + hub/ + └── models--julien-c--EsperBERTo-small/ + ├── blobs/ + │ ├── (...) + │ ├── (...) + ├── refs/ + │ └── (...) + └── [ 128] snapshots/ + ├── 2439f60ef33a0d46d85da5001d52aeda5b00ce9f/ + │ ├── (...) + └── bbc77c8132af1cc5cf678da3f1ddf2de43606d48/ + └── (...) + ``` + + + Args: + library_name (`str`): + Name of the library that will manage the cache folder. Example: `"dataset"`. + namespace (`str`, *optional*, defaults to "default"): + Namespace to which the data belongs. Example: `"SQuAD"`. + subfolder (`str`, *optional*, defaults to "default"): + Subfolder in which the data will be stored. Example: `extracted`. + assets_dir (`str`, `Path`, *optional*): + Path to the folder where assets are cached. This must not be the same folder + where Hub files are cached. Defaults to `HF_HOME / "assets"` if not provided. + Can also be set with `HF_ASSETS_CACHE` environment variable. + + Returns: + Path to the cache folder (`Path`). + + Example: + ```py + >>> from huggingface_hub import cached_assets_path + + >>> cached_assets_path(library_name="datasets", namespace="SQuAD", subfolder="download") + PosixPath('/home/wauplin/.cache/huggingface/extra/datasets/SQuAD/download') + + >>> cached_assets_path(library_name="datasets", namespace="SQuAD", subfolder="extracted") + PosixPath('/home/wauplin/.cache/huggingface/extra/datasets/SQuAD/extracted') + + >>> cached_assets_path(library_name="datasets", namespace="Helsinki-NLP/tatoeba_mt") + PosixPath('/home/wauplin/.cache/huggingface/extra/datasets/Helsinki-NLP--tatoeba_mt/default') + + >>> cached_assets_path(library_name="datasets", assets_dir="/tmp/tmp123456") + PosixPath('/tmp/tmp123456/datasets/default/default') + ``` + """ + # Resolve assets_dir + if assets_dir is None: + assets_dir = HF_ASSETS_CACHE + assets_dir = Path(assets_dir).expanduser().resolve() + + # Avoid names that could create path issues + for part in (" ", "/", "\\"): + library_name = library_name.replace(part, "--") + namespace = namespace.replace(part, "--") + subfolder = subfolder.replace(part, "--") + + # Path to subfolder is created + path = assets_dir / library_name / namespace / subfolder + try: + path.mkdir(exist_ok=True, parents=True) + except (FileExistsError, NotADirectoryError): + raise ValueError(f"Corrupted assets folder: cannot create directory because of an existing file ({path}).") + + # Return + return path diff --git a/.venv/lib/python3.12/site-packages/huggingface_hub/utils/_cache_manager.py b/.venv/lib/python3.12/site-packages/huggingface_hub/utils/_cache_manager.py new file mode 100644 index 0000000000000000000000000000000000000000..5684cf0d286a21eec8c8f0197572f7d885f5838a --- /dev/null +++ b/.venv/lib/python3.12/site-packages/huggingface_hub/utils/_cache_manager.py @@ -0,0 +1,890 @@ +# Copyright 2022-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. +"""Contains utilities to manage the HF cache directory.""" + +import os +import shutil +from collections import defaultdict +from dataclasses import dataclass +from pathlib import Path +from typing import Literal + +from huggingface_hub.errors import CacheNotFound, CorruptedCacheException + +from ..constants import HF_HUB_CACHE +from . import logging +from ._parsing import format_timesince +from ._terminal import tabulate + + +logger = logging.get_logger(__name__) + +REPO_TYPE_T = Literal["model", "dataset", "space"] + +# List of OS-created helper files that need to be ignored +FILES_TO_IGNORE = [".DS_Store", "Thumbs.db", "desktop.ini"] + + +@dataclass(frozen=True) +class CachedFileInfo: + """Frozen data structure holding information about a single cached file. + + Args: + file_name (`str`): + Name of the file. Example: `config.json`. + file_path (`Path`): + Path of the file in the `snapshots` directory. The file path is a symlink + referring to a blob in the `blobs` folder. + blob_path (`Path`): + Path of the blob file. This is equivalent to `file_path.resolve()`. + size_on_disk (`int`): + Size of the blob file in bytes. + blob_last_accessed (`float`): + Timestamp of the last time the blob file has been accessed (from any + revision). + blob_last_modified (`float`): + Timestamp of the last time the blob file has been modified/created. + + > [!WARNING] + > `blob_last_accessed` and `blob_last_modified` reliability can depend on the OS you + > are using. See [python documentation](https://docs.python.org/3/library/os.html#os.stat_result) + > for more details. + """ + + file_name: str + file_path: Path + blob_path: Path + size_on_disk: int + + blob_last_accessed: float + blob_last_modified: float + + @property + def blob_last_accessed_str(self) -> str: + """ + (property) Timestamp of the last time the blob file has been accessed (from any + revision), returned as a human-readable string. + + Example: "2 weeks ago". + """ + return format_timesince(self.blob_last_accessed) + + @property + def blob_last_modified_str(self) -> str: + """ + (property) Timestamp of the last time the blob file has been modified, returned + as a human-readable string. + + Example: "2 weeks ago". + """ + return format_timesince(self.blob_last_modified) + + @property + def size_on_disk_str(self) -> str: + """ + (property) Size of the blob file as a human-readable string. + + Example: "42.2K". + """ + return _format_size(self.size_on_disk) + + +@dataclass(frozen=True) +class CachedRevisionInfo: + """Frozen data structure holding information about a revision. + + A revision correspond to a folder in the `snapshots` folder and is populated with + the exact tree structure as the repo on the Hub but contains only symlinks. A + revision can be either referenced by 1 or more `refs` or be "detached" (no refs). + + Args: + commit_hash (`str`): + Hash of the revision (unique). + Example: `"9338f7b671827df886678df2bdd7cc7b4f36dffd"`. + snapshot_path (`Path`): + Path to the revision directory in the `snapshots` folder. It contains the + exact tree structure as the repo on the Hub. + files: (`frozenset[CachedFileInfo]`): + Set of [`~CachedFileInfo`] describing all files contained in the snapshot. + refs (`frozenset[str]`): + Set of `refs` pointing to this revision. If the revision has no `refs`, it + is considered detached. + Example: `{"main", "2.4.0"}` or `{"refs/pr/1"}`. + size_on_disk (`int`): + Sum of the blob file sizes that are symlink-ed by the revision. + last_modified (`float`): + Timestamp of the last time the revision has been created/modified. + + > [!WARNING] + > `last_accessed` cannot be determined correctly on a single revision as blob files + > are shared across revisions. + + > [!WARNING] + > `size_on_disk` is not necessarily the sum of all file sizes because of possible + > duplicated files. Besides, only blobs are taken into account, not the (negligible) + > size of folders and symlinks. + """ + + commit_hash: str + snapshot_path: Path + size_on_disk: int + files: frozenset[CachedFileInfo] + refs: frozenset[str] + + last_modified: float + + @property + def last_modified_str(self) -> str: + """ + (property) Timestamp of the last time the revision has been modified, returned + as a human-readable string. + + Example: "2 weeks ago". + """ + return format_timesince(self.last_modified) + + @property + def size_on_disk_str(self) -> str: + """ + (property) Sum of the blob file sizes as a human-readable string. + + Example: "42.2K". + """ + return _format_size(self.size_on_disk) + + @property + def nb_files(self) -> int: + """ + (property) Total number of files in the revision. + """ + return len(self.files) + + +@dataclass(frozen=True) +class CachedRepoInfo: + """Frozen data structure holding information about a cached repository. + + Args: + repo_id (`str`): + Repo id of the repo on the Hub. Example: `"google/fleurs"`. + repo_type (`Literal["dataset", "model", "space"]`): + Type of the cached repo. + repo_path (`Path`): + Local path to the cached repo. + size_on_disk (`int`): + Sum of the blob file sizes in the cached repo. + nb_files (`int`): + Total number of blob files in the cached repo. + revisions (`frozenset[CachedRevisionInfo]`): + Set of [`~CachedRevisionInfo`] describing all revisions cached in the repo. + last_accessed (`float`): + Timestamp of the last time a blob file of the repo has been accessed. + last_modified (`float`): + Timestamp of the last time a blob file of the repo has been modified/created. + + > [!WARNING] + > `size_on_disk` is not necessarily the sum of all revisions sizes because of + > duplicated files. Besides, only blobs are taken into account, not the (negligible) + > size of folders and symlinks. + + > [!WARNING] + > `last_accessed` and `last_modified` reliability can depend on the OS you are using. + > See [python documentation](https://docs.python.org/3/library/os.html#os.stat_result) + > for more details. + """ + + repo_id: str + repo_type: REPO_TYPE_T + repo_path: Path + size_on_disk: int + nb_files: int + revisions: frozenset[CachedRevisionInfo] + + last_accessed: float + last_modified: float + + @property + def last_accessed_str(self) -> str: + """ + (property) Last time a blob file of the repo has been accessed, returned as a + human-readable string. + + Example: "2 weeks ago". + """ + return format_timesince(self.last_accessed) + + @property + def last_modified_str(self) -> str: + """ + (property) Last time a blob file of the repo has been modified, returned as a + human-readable string. + + Example: "2 weeks ago". + """ + return format_timesince(self.last_modified) + + @property + def size_on_disk_str(self) -> str: + """ + (property) Sum of the blob file sizes as a human-readable string. + + Example: "42.2K". + """ + return _format_size(self.size_on_disk) + + @property + def cache_id(self) -> str: + """Canonical `type/id` identifier used across cache tooling.""" + return f"{self.repo_type}/{self.repo_id}" + + @property + def refs(self) -> dict[str, CachedRevisionInfo]: + """ + (property) Mapping between `refs` and revision data structures. + """ + return {ref: revision for revision in self.revisions for ref in revision.refs} + + +@dataclass(frozen=True) +class DeleteCacheStrategy: + """Frozen data structure holding the strategy to delete cached revisions. + + This object is not meant to be instantiated programmatically but to be returned by + [`~utils.HFCacheInfo.delete_revisions`]. See documentation for usage example. + + Args: + expected_freed_size (`float`): + Expected freed size once strategy is executed. + blobs (`frozenset[Path]`): + Set of blob file paths to be deleted. + refs (`frozenset[Path]`): + Set of reference file paths to be deleted. + repos (`frozenset[Path]`): + Set of entire repo paths to be deleted. + snapshots (`frozenset[Path]`): + Set of snapshots to be deleted (directory of symlinks). + """ + + expected_freed_size: int + blobs: frozenset[Path] + refs: frozenset[Path] + repos: frozenset[Path] + snapshots: frozenset[Path] + + @property + def expected_freed_size_str(self) -> str: + """ + (property) Expected size that will be freed as a human-readable string. + + Example: "42.2K". + """ + return _format_size(self.expected_freed_size) + + def execute(self) -> None: + """Execute the defined strategy. + + > [!WARNING] + > If this method is interrupted, the cache might get corrupted. Deletion order is + > implemented so that references and symlinks are deleted before the actual blob + > files. + + > [!WARNING] + > This method is irreversible. If executed, cached files are erased and must be + > downloaded again. + """ + # Deletion order matters. Blobs are deleted in last so that the user can't end + # up in a state where a `ref`` refers to a missing snapshot or a snapshot + # symlink refers to a deleted blob. + + # Delete entire repos + for path in self.repos: + _try_delete_path(path, path_type="repo") + + # Delete snapshot directories + for path in self.snapshots: + _try_delete_path(path, path_type="snapshot") + + # Delete refs files + for path in self.refs: + _try_delete_path(path, path_type="ref") + + # Delete blob files + for path in self.blobs: + _try_delete_path(path, path_type="blob") + + logger.info(f"Cache deletion done. Saved {self.expected_freed_size_str}.") + + +@dataclass(frozen=True) +class CachedIncompleteFileInfo: + """Frozen data structure holding information about a single incomplete download. + + Interrupted downloads leave `
+
')
+
+
+def _config_inited(app, config):
+ # Check for srcset hidpi images
+ for i, size in enumerate(app.config.mathmpl_srcset):
+ if size[-1] == 'x': # "2x" = "2.0"
+ try:
+ float(size[:-1])
+ except ValueError:
+ raise ConfigError(
+ f'Invalid value for mathmpl_srcset parameter: {size!r}. '
+ 'Must be a list of strings with the multiplicative '
+ 'factor followed by an "x". e.g. ["2.0x", "1.5x"]')
+ else:
+ raise ConfigError(
+ f'Invalid value for mathmpl_srcset parameter: {size!r}. '
+ 'Must be a list of strings with the multiplicative '
+ 'factor followed by an "x". e.g. ["2.0x", "1.5x"]')
+
+
+def setup(app):
+ setup.app = app
+ app.add_config_value('mathmpl_fontsize', 10.0, True)
+ app.add_config_value('mathmpl_srcset', [], True)
+ try:
+ app.connect('config-inited', _config_inited) # Sphinx 1.8+
+ except ExtensionError:
+ app.connect('env-updated', lambda app, env: _config_inited(app, None))
+
+ # Add visit/depart methods to HTML-Translator:
+ def visit_latex_math_html(self, node):
+ source = self.document.attributes['source']
+ self.body.append(latex2html(node, source))
+
+ def depart_latex_math_html(self, node):
+ pass
+
+ # Add visit/depart methods to LaTeX-Translator:
+ def visit_latex_math_latex(self, node):
+ inline = isinstance(node.parent, nodes.TextElement)
+ if inline:
+ self.body.append('$%s$' % node['latex'])
+ else:
+ self.body.extend(['\\begin{equation}',
+ node['latex'],
+ '\\end{equation}'])
+
+ def depart_latex_math_latex(self, node):
+ pass
+
+ app.add_node(latex_math,
+ html=(visit_latex_math_html, depart_latex_math_html),
+ latex=(visit_latex_math_latex, depart_latex_math_latex))
+ app.add_role('mathmpl', math_role)
+ app.add_directive('mathmpl', MathDirective)
+ if sphinx.version_info < (1, 8):
+ app.add_role('math', math_role)
+ app.add_directive('math', MathDirective)
+
+ metadata = {'parallel_read_safe': True, 'parallel_write_safe': True}
+ return metadata
diff --git a/.venv/lib/python3.12/site-packages/matplotlib/sphinxext/plot_directive.py b/.venv/lib/python3.12/site-packages/matplotlib/sphinxext/plot_directive.py
new file mode 100644
index 0000000000000000000000000000000000000000..7b46b3145e2b14183844d2c5ecd19d0448bb9535
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/matplotlib/sphinxext/plot_directive.py
@@ -0,0 +1,1010 @@
+"""
+A directive for including a Matplotlib plot in a Sphinx document
+================================================================
+
+This is a Sphinx extension providing a reStructuredText directive
+``.. plot::`` for including a plot in a Sphinx document.
+
+In HTML output, ``.. plot::`` will include a .png file with a link
+to a high-res .png and .pdf. In LaTeX output, it will include a .pdf.
+
+The plot content may be defined in one of three ways:
+
+1. **A path to a source file** as the argument to the directive::
+
+ .. plot:: path/to/plot.py
+
+ When a path to a source file is given, the content of the
+ directive may optionally contain a caption for the plot::
+
+ .. plot:: path/to/plot.py
+
+ The plot caption.
+
+ Additionally, one may specify the name of a function to call (with
+ no arguments) immediately after importing the module::
+
+ .. plot:: path/to/plot.py plot_function1
+
+2. Included as **inline content** to the directive::
+
+ .. plot::
+
+ import matplotlib.pyplot as plt
+ plt.plot([1, 2, 3], [4, 5, 6])
+ plt.title("A plotting example")
+
+3. Using **doctest** syntax::
+
+ .. plot::
+
+ A plotting example:
+ >>> import matplotlib.pyplot as plt
+ >>> plt.plot([1, 2, 3], [4, 5, 6])
+
+Options
+-------
+
+The ``.. plot::`` directive supports the following options:
+
+``:filename-prefix:`` : str
+ The base name (without the extension) of the outputted image and script
+ files. The default is to use the same name as the input script, or the
+ name of the RST document if no script is provided. The filename-prefix for
+ each plot directive must be unique.
+
+``:format:`` : {'python', 'doctest'}
+ The format of the input. If unset, the format is auto-detected.
+
+``:include-source:`` : bool
+ Whether to display the source code. The default can be changed using
+ the ``plot_include_source`` variable in :file:`conf.py` (which itself
+ defaults to False).
+
+``:show-source-link:`` : bool
+ Whether to show a link to the source in HTML. The default can be
+ changed using the ``plot_html_show_source_link`` variable in
+ :file:`conf.py` (which itself defaults to True).
+
+``:context:`` : bool or str
+ If provided, the code will be run in the context of all previous plot
+ directives for which the ``:context:`` option was specified. This only
+ applies to inline code plot directives, not those run from files. If
+ the ``:context: reset`` option is specified, the context is reset
+ for this and future plots, and previous figures are closed prior to
+ running the code. ``:context: close-figs`` keeps the context but closes
+ previous figures before running the code.
+
+``:nofigs:`` : bool
+ If specified, the code block will be run, but no figures will be
+ inserted. This is usually useful with the ``:context:`` option.
+
+``:caption:`` : str
+ If specified, the option's argument will be used as a caption for the
+ figure. This overwrites the caption given in the content, when the plot
+ is generated from a file.
+
+``:code-caption:`` : str
+ If specified, the option's argument will be used as a caption for the
+ code block (when ``:include-source:`` is used). This is added as the
+ ``:caption:`` option to the ``.. code-block::`` directive.
+
+Additionally, this directive supports all the options of the `image directive
+