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docs: fix kwargs docstring (#25010)

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Bagatur
2024-08-02 19:54:54 -07:00
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parent 57747892ce
commit e81ddb32a6
61 changed files with 143 additions and 143 deletions
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14
libs/community/langchain_community/vectorstores/deeplake.py
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@@ -385,7 +385,7 @@ class DeepLake(VectorStore):
model was trained. The search is performed using the Deep Memory model.
If False, the distance metric is set to "COS" or whatever distance
metric user specifies.
**kwargs: Additional keyword arguments.
kwargs: Additional keyword arguments.
Returns:
List of Documents by the specified distance metric,
@@ -505,7 +505,7 @@ class DeepLake(VectorStore):
Args:
k (int): Number of Documents to return. Defaults to 4.
query (str): Text to look up similar documents.
**kwargs: Additional keyword arguments include:
kwargs: Additional keyword arguments include:
embedding (Callable): Embedding function to use. Defaults to None.
distance_metric (str): 'L2' for Euclidean, 'L1' for Nuclear, 'max'
for L-infinity, 'cos' for cosine, 'dot' for dot product.
@@ -567,7 +567,7 @@ class DeepLake(VectorStore):
embedding (Union[List[float], np.ndarray]):
Embedding to find similar docs.
k (int): Number of Documents to return. Defaults to 4.
**kwargs: Additional keyword arguments including:
kwargs: Additional keyword arguments including:
filter (Union[Dict, Callable], optional):
Additional filter before embedding search.
- ``Dict`` - Key-value search on tensors of htype json. True
@@ -636,7 +636,7 @@ class DeepLake(VectorStore):
Args:
query (str): Query text to search for.
k (int): Number of results to return. Defaults to 4.
**kwargs: Additional keyword arguments. Some of these arguments are:
kwargs: Additional keyword arguments. Some of these arguments are:
distance_metric: `L2` for Euclidean, `L1` for Nuclear, `max` L-infinity
distance, `cos` for cosine similarity, 'dot' for dot product.
Defaults to `L2`.
@@ -728,7 +728,7 @@ class DeepLake(VectorStore):
which the model was trained. The search is performed using the Deep
Memory model. If False, the distance metric is set to "COS" or
whatever distance metric user specifies.
**kwargs: Additional keyword arguments.
kwargs: Additional keyword arguments.
Returns:
List[Documents] - A list of documents.
@@ -795,7 +795,7 @@ class DeepLake(VectorStore):
which the model was trained. The search is performed using the Deep
Memory model. If False, the distance metric is set to "COS" or
whatever distance metric user specifies.
**kwargs: Additional keyword arguments
kwargs: Additional keyword arguments
Returns:
List of Documents selected by maximal marginal relevance.
@@ -866,7 +866,7 @@ class DeepLake(VectorStore):
Note, in other places, it is called embedding_function.
metadatas (Optional[List[dict]]): List of metadatas. Defaults to None.
ids (Optional[List[str]]): List of document IDs. Defaults to None.
**kwargs: Additional keyword arguments.
kwargs: Additional keyword arguments.
Returns:
DeepLake: Deep Lake dataset.