reorganize imports in hf utils (#7414)

haystack/utils/hf.py

@@ -14,7 +14,7 @@
 with LazyImport(message="Run 'pip install transformers[torch]'") as torch_import:
  import torch
 
-with LazyImport(message="Run 'pip install transformers'") as transformers_import:
+with LazyImport(message="Run 'pip install huggingface_hub'") as huggingface_hub_import:
  from huggingface_hub import HfApi, InferenceClient, model_info
  from huggingface_hub.utils import RepositoryNotFoundError
 
@@ -120,7 +120,7 @@ def resolve_hf_pipeline_kwargs(
  :param token: The token to use as HTTP bearer authorization for remote files.
  If the token is also specified in the `huggingface_pipeline_kwargs`, this parameter will be ignored.
  """
- transformers_import.check()
+ huggingface_hub_import.check()
 
  token = token.resolve_value() if token else None
  # check if the huggingface_pipeline_kwargs contain the essential parameters
@@ -173,7 +173,7 @@ def check_valid_model(model_id: str, model_type: HFModelType, token: Optional[Se
  :param token: The optional authentication token.
  :raises ValueError: If the model is not found or is not a embedding model.
  """
- transformers_import.check()
+ huggingface_hub_import.check()
 
  api = HfApi()
  try:
@@ -202,7 +202,7 @@ def check_generation_params(kwargs: Optional[Dict[str, Any]], additional_accepte
  :param additional_accepted_params: An optional list of strings representing additional accepted parameters.
  :raises ValueError: If any unknown text generation parameters are provided.
  """
- transformers_import.check()
+ huggingface_hub_import.check()
 
  if kwargs:
  accepted_params = {
@@ -219,10 +219,11 @@ def check_generation_params(kwargs: Optional[Dict[str, Any]], additional_accepte
  )
 
 
-with LazyImport(message="Run 'pip install transformers[torch]'") as torch_and_transformers_import:
+with LazyImport(message="Run 'pip install transformers[torch]'") as transformers_import:
  from transformers import PreTrainedTokenizer, PreTrainedTokenizerFast, StoppingCriteria, TextStreamer
 
- torch_and_transformers_import.check()
+ torch_import.check()
+ transformers_import.check()
 
  class StopWordsCriteria(StoppingCriteria):
  """