structure saas with tools

.venv/lib/python3.10/site-packages/huggingface_hub/utils/_auth.py

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+# Copyright 2023 The HuggingFace Team. 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 an helper to get the token from machine (env variable, secret or config file)."""
+
+import configparser
+import logging
+import os
+import warnings
+from pathlib import Path
+from threading import Lock
+from typing import Dict, Optional
+
+from .. import constants
+from ._runtime import is_colab_enterprise, is_google_colab
+
+
+_IS_GOOGLE_COLAB_CHECKED = False
+_GOOGLE_COLAB_SECRET_LOCK = Lock()
+_GOOGLE_COLAB_SECRET: Optional[str] = None
+
+logger = logging.getLogger(__name__)
+
+
+def get_token() -> Optional[str]:
+    """
+    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.
+
+    Token is retrieved in priority from the `HF_TOKEN` environment variable. Otherwise, we read the token file located
+    in the Hugging Face home folder. Returns None if user is not logged in. To log in, use [`login`] or
+    `huggingface-cli login`.
+
+    Returns:
+        `str` or `None`: The token, `None` if it doesn't exist.
+    """
+    return _get_token_from_google_colab() or _get_token_from_environment() or _get_token_from_file()
+
+
+def _get_token_from_google_colab() -> Optional[str]:
+    """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:
+            # Means the user did not define a `HF_TOKEN` secret => warn
+            warnings.warn(
+                "\nThe secret `HF_TOKEN` does not exist in your Colab secrets."
+                "\nTo authenticate with the Hugging Face Hub, create a token in your settings tab "
+                "(https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session."
+                "\nYou will be able to reuse this secret in all of your notebooks."
+                "\nPlease note that authentication is 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)}'."
+                "\nYou are not authenticated with the Hugging Face Hub in this notebook."
+                "\nIf the error persists, please let us know by opening an issue on GitHub "
+                "(https://github.com/huggingface/huggingface_hub/issues/new)."
+            )
+            _GOOGLE_COLAB_SECRET = None
+
+        _IS_GOOGLE_COLAB_CHECKED = True
+        return _GOOGLE_COLAB_SECRET
+
+
+def _get_token_from_environment() -> Optional[str]:
+    # `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() -> Optional[str]:
+    try:
+        return _clean_token(Path(constants.HF_TOKEN_PATH).read_text())
+    except FileNotFoundError:
+        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.
+    """
+    tokens_path = Path(constants.HF_STORED_TOKENS_PATH)
+    if not tokens_path.exists():
+        stored_tokens = {}
+    config = configparser.ConfigParser()
+    try:
+        config.read(tokens_path)
+        stored_tokens = {token_name: config.get(token_name, "hf_token") for token_name in config.sections()}
+    except configparser.Error as e:
+        logger.error(f"Error parsing stored tokens file: {e}")
+        stored_tokens = {}
+    return stored_tokens
+
+
+def _save_stored_tokens(stored_tokens: Dict[str, str]) -> None:
+    """
+    Saves the given configuration to the stored tokens file.
+
+    Args:
+        stored_tokens (`Dict[str, str]`):
+            The stored tokens to save. Key is the token name and value is the token.
+    """
+    stored_tokens_path = Path(constants.HF_STORED_TOKENS_PATH)
+
+    # Write the stored tokens into an INI file
+    config = configparser.ConfigParser()
+    for token_name in sorted(stored_tokens.keys()):
+        config.add_section(token_name)
+        config.set(token_name, "hf_token", stored_tokens[token_name])
+
+    stored_tokens_path.parent.mkdir(parents=True, exist_ok=True)
+    with stored_tokens_path.open("w") as config_file:
+        config.write(config_file)
+
+
+def _get_token_by_name(token_name: str) -> Optional[str]:
+    """
+    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) -> 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.
+    """
+    tokens_path = Path(constants.HF_STORED_TOKENS_PATH)
+    stored_tokens = get_stored_tokens()
+    stored_tokens[token_name] = token
+    _save_stored_tokens(stored_tokens)
+    logger.info(f"The token `{token_name}` has been saved to {tokens_path}")
+
+
+def _clean_token(token: Optional[str]) -> Optional[str]:
+    """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