Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

huggingface[patch]: hide client field in HuggingFaceEmbeddings #27522

Merged
merged 2 commits into from
Oct 21, 2024
Merged

huggingface[patch]: hide client field in HuggingFaceEmbeddings #27522

Changes from 1 commit
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
294e6db
huggingface[patch]: hide client field in HuggingFaceEmbeddings
vbarda Oct 21, 2024
67a1cd9
lint + validation
vbarda Oct 21, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
9 changes: 4 additions & 5 deletions libs/partners/huggingface/langchain_huggingface/embeddings/huggingface.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,6 @@ class HuggingFaceEmbeddings(BaseModel, Embeddings):
)
"""

client: Any = None #: :meta private:
model_name: str = DEFAULT_MODEL_NAME
"""Model name to use."""
cache_folder: Optional[str] = None
Expand Down Expand Up @@ -57,7 +56,7 @@ def __init__(self, **kwargs: Any):
"Please install it with `pip install sentence-transformers`."
) from exc

self.client = sentence_transformers.SentenceTransformer(
self._client = sentence_transformers.SentenceTransformer(
self.model_name, cache_folder=self.cache_folder, **self.model_kwargs
)

Expand All @@ -79,11 +78,11 @@ def embed_documents(self, texts: List[str]) -> List[List[float]]:

texts = list(map(lambda x: x.replace("\n", " "), texts))
if self.multi_process:
pool = self.client.start_multi_process_pool()
embeddings = self.client.encode_multi_process(texts, pool)
pool = self._client.start_multi_process_pool()
embeddings = self._client.encode_multi_process(texts, pool)
sentence_transformers.SentenceTransformer.stop_multi_process_pool(pool)
else:
embeddings = self.client.encode(
embeddings = self._client.encode(
texts, show_progress_bar=self.show_progress, **self.encode_kwargs
)

Expand Down
Loading