[BUG] Remove token param #10921 (#11022)

Signed-off-by: Flavia Beo <flavia.beo@ibm.com>

vllm/transformers_utils/config.py

 import enum
 import json
+import os
 from pathlib import Path
 from typing import Any, Dict, Optional, Type, Union
 
@@ -41,6 +42,7 @@ else:
     from transformers import AutoConfig
 
 MISTRAL_CONFIG_NAME = "params.json"
+HF_TOKEN = os.getenv('HF_TOKEN', None)
 
 logger = init_logger(__name__)
 
@@ -77,8 +79,8 @@ class ConfigFormat(str, enum.Enum):
     MISTRAL = "mistral"
 
 
-def file_or_path_exists(model: Union[str, Path], config_name, revision,
-                        token) -> bool:
+def file_or_path_exists(model: Union[str, Path], config_name: str,
+                        revision: Optional[str]) -> bool:
     if Path(model).exists():
         return (Path(model) / config_name).is_file()
 
@@ -93,7 +95,10 @@ def file_or_path_exists(model: Union[str, Path], config_name, revision,
     # NB: file_exists will only check for the existence of the config file on
     # hf_hub. This will fail in offline mode.
     try:
-        return file_exists(model, config_name, revision=revision, token=token)
+        return file_exists(model,
+                           config_name,
+                           revision=revision,
+                           token=HF_TOKEN)
     except huggingface_hub.errors.OfflineModeIsEnabled:
         # Don't raise in offline mode, all we know is that we don't have this
         # file cached.
@@ -161,7 +166,6 @@ def get_config(
     revision: Optional[str] = None,
     code_revision: Optional[str] = None,
     config_format: ConfigFormat = ConfigFormat.AUTO,
-    token: Optional[str] = None,
     **kwargs,
 ) -> PretrainedConfig:
     # Separate model folder from file path for GGUF models
@@ -173,19 +177,20 @@ def get_config(
 
     if config_format == ConfigFormat.AUTO:
         if is_gguf or file_or_path_exists(
-                model, HF_CONFIG_NAME, revision=revision, token=token):
+                model, HF_CONFIG_NAME, revision=revision):
             config_format = ConfigFormat.HF
-        elif file_or_path_exists(model,
-                                 MISTRAL_CONFIG_NAME,
-                                 revision=revision,
-                                 token=token):
+        elif file_or_path_exists(model, MISTRAL_CONFIG_NAME,
+                                 revision=revision):
             config_format = ConfigFormat.MISTRAL
         else:
             # If we're in offline mode and found no valid config format, then
             # raise an offline mode error to indicate to the user that they
             # don't have files cached and may need to go online.
             # This is conveniently triggered by calling file_exists().
-            file_exists(model, HF_CONFIG_NAME, revision=revision, token=token)
+            file_exists(model,
+                        HF_CONFIG_NAME,
+                        revision=revision,
+                        token=HF_TOKEN)
 
             raise ValueError(f"No supported config format found in {model}")
 
@@ -194,7 +199,7 @@ def get_config(
             model,
             revision=revision,
             code_revision=code_revision,
-            token=token,
+            token=HF_TOKEN,
             **kwargs,
         )
 
@@ -206,7 +211,7 @@ def get_config(
                 model,
                 revision=revision,
                 code_revision=code_revision,
-                token=token,
+                token=HF_TOKEN,
                 **kwargs,
             )
         else:
@@ -216,7 +221,7 @@ def get_config(
                     trust_remote_code=trust_remote_code,
                     revision=revision,
                     code_revision=code_revision,
-                    token=token,
+                    token=HF_TOKEN,
                     **kwargs,
                 )
             except ValueError as e:
@@ -234,7 +239,7 @@ def get_config(
                     raise e
 
     elif config_format == ConfigFormat.MISTRAL:
-        config = load_params_config(model, revision, token=token, **kwargs)
+        config = load_params_config(model, revision, token=HF_TOKEN, **kwargs)
     else:
         raise ValueError(f"Unsupported config format: {config_format}")
 
@@ -256,8 +261,7 @@ def get_config(
 
 def get_hf_file_to_dict(file_name: str,
                         model: Union[str, Path],
-                        revision: Optional[str] = 'main',
-                        token: Optional[str] = None):
+                        revision: Optional[str] = 'main'):
     """
     Downloads a file from the Hugging Face Hub and returns 
     its contents as a dictionary.
@@ -266,7 +270,6 @@ def get_hf_file_to_dict(file_name: str,
     - file_name (str): The name of the file to download.
     - model (str): The name of the model on the Hugging Face Hub.
     - revision (str): The specific version of the model. 
-    - token (str): The Hugging Face authentication token.
 
     Returns:
     - config_dict (dict): A dictionary containing 
@@ -276,8 +279,7 @@ def get_hf_file_to_dict(file_name: str,
 
     if file_or_path_exists(model=model,
                            config_name=file_name,
-                           revision=revision,
-                           token=token):
+                           revision=revision):
 
         if not file_path.is_file():
             try:
@@ -296,9 +298,7 @@ def get_hf_file_to_dict(file_name: str,
     return None
 
 
-def get_pooling_config(model: str,
-                       revision: Optional[str] = 'main',
-                       token: Optional[str] = None):
+def get_pooling_config(model: str, revision: Optional[str] = 'main'):
     """
     This function gets the pooling and normalize 
     config from the model - only applies to 
@@ -315,8 +315,7 @@ def get_pooling_config(model: str,
     """
 
     modules_file_name = "modules.json"
-    modules_dict = get_hf_file_to_dict(modules_file_name, model, revision,
-                                       token)
+    modules_dict = get_hf_file_to_dict(modules_file_name, model, revision)
 
     if modules_dict is None:
         return None
@@ -332,8 +331,7 @@ def get_pooling_config(model: str,
     if pooling:
 
         pooling_file_name = "{}/config.json".format(pooling["path"])
-        pooling_dict = get_hf_file_to_dict(pooling_file_name, model, revision,
-                                           token)
+        pooling_dict = get_hf_file_to_dict(pooling_file_name, model, revision)
         pooling_type_name = next(
             (item for item, val in pooling_dict.items() if val is True), None)
 
@@ -368,8 +366,8 @@ def get_pooling_config_name(pooling_name: str) -> Union[str, None]:
 
 
 def get_sentence_transformer_tokenizer_config(model: str,
-                                              revision: Optional[str] = 'main',
-                                              token: Optional[str] = None):
+                                              revision: Optional[str] = 'main'
+                                              ):
     """
     Returns the tokenization configuration dictionary for a 
     given Sentence Transformer BERT model.
@@ -379,7 +377,6 @@ def get_sentence_transformer_tokenizer_config(model: str,
     BERT model.
     - revision (str, optional): The revision of the m
     odel to use. Defaults to 'main'.
-    - token (str): A Hugging Face access token.
 
     Returns:
     - dict: A dictionary containing the configuration parameters 
@@ -394,7 +391,7 @@ def get_sentence_transformer_tokenizer_config(model: str,
             "sentence_xlm-roberta_config.json",
             "sentence_xlnet_config.json",
     ]:
-        encoder_dict = get_hf_file_to_dict(config_name, model, revision, token)
+        encoder_dict = get_hf_file_to_dict(config_name, model, revision)
         if encoder_dict:
             break
 
@@ -474,16 +471,14 @@ def maybe_register_config_serialize_by_value() -> None:
             exc_info=e)
 
 
-def load_params_config(model: Union[str, Path],
-                       revision: Optional[str],
-                       token: Optional[str] = None,
+def load_params_config(model: Union[str, Path], revision: Optional[str],
                        **kwargs) -> PretrainedConfig:
     # This function loads a params.json config which
     # should be used when loading models in mistral format
 
     config_file_name = "params.json"
 
-    config_dict = get_hf_file_to_dict(config_file_name, model, revision, token)
+    config_dict = get_hf_file_to_dict(config_file_name, model, revision)
     assert isinstance(config_dict, dict)
 
     config_mapping = {