From 5b6e25a88f015f9436ee5ac953c6f3ba49a4c3b3 Mon Sep 17 00:00:00 2001 From: "open-swe[bot]" Date: Thu, 31 Jul 2025 00:13:51 +0000 Subject: [PATCH] Apply patch [skip ci] --- .../embeddings/huggingface.py | 23 ++++++++----------- 1 file changed, 10 insertions(+), 13 deletions(-) diff --git a/libs/partners/huggingface/langchain_huggingface/embeddings/huggingface.py b/libs/partners/huggingface/langchain_huggingface/embeddings/huggingface.py index ef112b94ae6..618c75c7610 100644 --- a/libs/partners/huggingface/langchain_huggingface/embeddings/huggingface.py +++ b/libs/partners/huggingface/langchain_huggingface/embeddings/huggingface.py @@ -44,23 +44,19 @@ class HuggingFaceEmbeddings(BaseModel, Embeddings): """Model name to use.""" cache_folder: Optional[str] = None """Path to store models. - Can be also set by SENTENCE_TRANSFORMERS_HOME environment variable.""" + Can be also set by TRANSFORMERS_CACHE environment variable.""" model_kwargs: dict[str, Any] = Field(default_factory=dict) - """Keyword arguments to pass to the Sentence Transformer model, such as `device`, - `prompts`, `default_prompt_name`, `revision`, `trust_remote_code`, or `token`. - See also the Sentence Transformer documentation: https://sbert.net/docs/package_reference/SentenceTransformer.html#sentence_transformers.SentenceTransformer""" + """Keyword arguments to pass to the transformer model, such as `device`, + `revision`, `trust_remote_code`, or `token`.""" encode_kwargs: dict[str, Any] = Field(default_factory=dict) - """Keyword arguments to pass when calling the `encode` method for the documents of - the Sentence Transformer model, such as `prompt_name`, `prompt`, `batch_size`, - `precision`, `normalize_embeddings`, and more. - See also the Sentence Transformer documentation: https://sbert.net/docs/package_reference/SentenceTransformer.html#sentence_transformers.SentenceTransformer.encode""" + """Keyword arguments to pass when calling the `encode` method for the documents, + such as `batch_size`, `normalize_embeddings`, and more.""" query_encode_kwargs: dict[str, Any] = Field(default_factory=dict) - """Keyword arguments to pass when calling the `encode` method for the query of - the Sentence Transformer model, such as `prompt_name`, `prompt`, `batch_size`, - `precision`, `normalize_embeddings`, and more. - See also the Sentence Transformer documentation: https://sbert.net/docs/package_reference/SentenceTransformer.html#sentence_transformers.SentenceTransformer.encode""" + """Keyword arguments to pass when calling the `encode` method for the query, + such as `batch_size`, `normalize_embeddings`, and more.""" multi_process: bool = False - """Run encode() on multiple GPUs.""" + """Run encode() on multiple GPUs. Note: This feature is not supported with transformers + and will be ignored with a warning.""" show_progress: bool = False """Whether to show a progress bar.""" @@ -174,3 +170,4 @@ class HuggingFaceEmbeddings(BaseModel, Embeddings): ) return self._embed([text], embed_kwargs)[0] +