检查其他资源

• 我为这个问题添加了一个非常描述性的标题。
• 我在集成搜索中搜索了LangChain文档。
• 我使用GitHub搜索找到了一个类似的问题，但没有找到。
• 我确信这是LangChain中的一个bug,而不是我的代码。
• 通过更新到LangChain的最新稳定版本(或特定集成包)无法解决此bug。

示例代码

from langchain_huggingface import (
    ChatHuggingFace,
    HuggingFacePipeline,
)

chat_llm = ChatHuggingFace(
    llm=HuggingFacePipeline.from_model_id(
        model_id="path/to/your/local/model",  # I downloaded Meta-Llama-3-8B
        task="text-generation",
        device_map="auto",
        model_kwargs={"temperature": 0.0, "local_files_only": True},
    )
)

错误信息和堆栈跟踪(如果适用)

src/resources/predictor.py:55: in load
    self.llm = ChatHuggingFace(
/opt/poetry-cache/virtualenvs/sagacify-example-llm-8EXZSVYp-py3.10/lib/python3.10/site-packages/langchain_huggingface/chat_models/huggingface.py:169: in __init__
    self._resolve_model_id()
/opt/poetry-cache/virtualenvs/sagacify-example-llm-8EXZSVYp-py3.10/lib/python3.10/site-packages/langchain_huggingface/chat_models/huggingface.py:295: in _resolve_model_id
    available_endpoints = list_inference_endpoints("*")
/opt/poetry-cache/virtualenvs/sagacify-example-llm-8EXZSVYp-py3.10/lib/python3.10/site-packages/huggingface_hub/hf_api.py:7081: in list_inference_endpoints
    user = self.whoami(token=token)
/opt/poetry-cache/virtualenvs/sagacify-example-llm-8EXZSVYp-py3.10/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:114: in _inner_fn
    return fn(*args, **kwargs)
/opt/poetry-cache/virtualenvs/sagacify-example-llm-8EXZSVYp-py3.10/lib/python3.10/site-packages/huggingface_hub/hf_api.py:1390: in whoami
    headers=self._build_hf_headers(
/opt/poetry-cache/virtualenvs/sagacify-example-llm-8EXZSVYp-py3.10/lib/python3.10/site-packages/huggingface_hub/hf_api.py:8448: in _build_hf_headers
    return build_hf_headers(
/opt/poetry-cache/virtualenvs/sagacify-example-llm-8EXZSVYp-py3.10/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:114: in _inner_fn
    return fn(*args, **kwargs)
/opt/poetry-cache/virtualenvs/sagacify-example-llm-8EXZSVYp-py3.10/lib/python3.10/site-packages/huggingface_hub/utils/_headers.py:124: in build_hf_headers
    token_to_send = get_token_to_send(token)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

token = True

    def get_token_to_send(token: Optional[Union[bool, str]]) -> Optional[str]:
        """Select the token to send from either `token` or the cache."""
        # Case token is explicitly provided
        if isinstance(token, str):
            return token

        # Case token is explicitly forbidden
        if token is False:
            return None

        # Token is not provided: we get it from local cache
        cached_token = get_token()

        # Case token is explicitly required
        if token is True:
            if cached_token is None:
>               raise LocalTokenNotFoundError(
                    "Token is required (`token=True`), but no token found. You"
                    " need to provide a token or be logged in to Hugging Face with"
                    " `huggingface-cli login` or `huggingface_hub.login`. See"
                    " https://huggingface.co/settings/tokens."
                )
E               huggingface_hub.errors.LocalTokenNotFoundError: Token is required (`token=True`), but no token found. You need to provide a token or be logged in to Hugging Face with `huggingface-cli login` or `huggingface_hub.login`. See https://huggingface.co/settings/tokens.

/opt/poetry-cache/virtualenvs/sagacify-example-llm-8EXZSVYp-py3.10/lib/python3.10/site-packages/huggingface_hub/utils/_headers.py:158: LocalTokenNotFoundError

描述

我正在尝试使用 langchain-huggingface 库示例化一个 ChatHuggingFace 对象，该对象具有 HuggingFacePipelinellm 参数，该参数针对本地下载的模型(在这里，Meta-Llama-3-8B)。
尽管我没有在环境中设置HuggingFace令牌，因为我使用的是本地模型，但我希望示例化能够正常工作。
然而，示例化失败，因为它试图读取令牌以列出我HuggingFace帐户下可用的端点。
经过调查，我认为这行代码应该位于文件 langchain/libs/partners/huggingface/langchain_huggingface/chat_models/huggingface.py 的第456行，而不是第443行。

def _resolve_model_id(self) -> None:
  """Resolve the model_id from the LLM's inference_server_url"""

  from huggingface_hub import list_inference_endpoints  # type: ignore[import]

  available_endpoints = list_inference_endpoints("*")  # Line 443: This line is not at the right place
  if _is_huggingface_hub(self.llm) or (
      hasattr(self.llm, "repo_id") and self.llm.repo_id
  ):
      self.model_id = self.llm.repo_id
      return
  elif _is_huggingface_textgen_inference(self.llm):
      endpoint_url: Optional[str] = self.llm.inference_server_url
  elif _is_huggingface_pipeline(self.llm):
      self.model_id = self.llm.model_id
      return                      # My code lies in this case where it does not use available endpoints
  else:
      endpoint_url = self.llm.endpoint_url
                                  # Line 456: The line should be here instead
  for endpoint in available_endpoints:
      if endpoint.url == endpoint_url:
          self.model_id = endpoint.repository

  if not self.model_id:
      raise ValueError(
          "Failed to resolve model_id:"
          f"Could not find model id for inference server: {endpoint_url}"
          "Make sure that your Hugging Face token has access to the endpoint."
      )

系统信息

huggingface-hub           0.23.2          Client library to download and publish models, datasets and other repos on the huggingface.co hub
langchain                 0.2.1           Building applications with LLMs through composability
langchain-core            0.2.2           Building applications with LLMs through composability
langchain-huggingface     0.0.3           An integration package connecting Hugging Face and LangChain
langchain-text-splitters  0.2.0           LangChain text splitting utilities
sentence-transformers     3.0.0           Multilingual text embeddings
tokenizers                0.19.1
transformers              4.41.2          State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

平台：linux
python:Python 3.10.12