Base
BaseVectorStore ¶
Bases: ABC
Source code in libs/kotaemon/kotaemon/storages/vectorstores/base.py
add
abstractmethod
¶
Add vector embeddings to vector stores
Parameters:
Name | Type | Description | Default |
---|---|---|---|
embeddings
|
list[list[float]] | list[DocumentWithEmbedding]
|
List of embeddings |
required |
metadatas
|
Optional[list[dict]]
|
List of metadata of the embeddings |
None
|
ids
|
Optional[list[str]]
|
List of ids of the embeddings |
None
|
kwargs
|
meant for vectorstore-specific parameters |
required |
Returns:
Type | Description |
---|---|
list[str]
|
List of ids of the embeddings |
Source code in libs/kotaemon/kotaemon/storages/vectorstores/base.py
delete
abstractmethod
¶
Delete vector embeddings from vector stores
Parameters:
Name | Type | Description | Default |
---|---|---|---|
ids
|
list[str]
|
List of ids of the embeddings to be deleted |
required |
kwargs
|
meant for vectorstore-specific parameters |
{}
|
Source code in libs/kotaemon/kotaemon/storages/vectorstores/base.py
query
abstractmethod
¶
Return the top k most similar vector embeddings
Parameters:
Name | Type | Description | Default |
---|---|---|---|
embedding
|
list[float]
|
List of embeddings |
required |
top_k
|
int
|
Number of most similar embeddings to return |
1
|
ids
|
Optional[list[str]]
|
List of ids of the embeddings to be queried |
None
|
Returns:
Type | Description |
---|---|
tuple[list[list[float]], list[float], list[str]]
|
the matched embeddings, the similarity scores, and the ids |
Source code in libs/kotaemon/kotaemon/storages/vectorstores/base.py
LlamaIndexVectorStore ¶
Bases: BaseVectorStore
Mixin for LlamaIndex based vectorstores
Source code in libs/kotaemon/kotaemon/storages/vectorstores/base.py
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|
query ¶
Return the top k most similar vector embeddings
Parameters:
Name | Type | Description | Default |
---|---|---|---|
embedding
|
list[float]
|
List of embeddings |
required |
top_k
|
int
|
Number of most similar embeddings to return |
1
|
ids
|
Optional[list[str]]
|
List of ids of the embeddings to be queried |
None
|
kwargs
|
extra query parameters. Depending on the name, these parameters will be used when constructing the VectorStoreQuery object or when performing querying of the underlying vector store. |
{}
|
Returns:
Type | Description |
---|---|
tuple[list[list[float]], list[float], list[str]]
|
the matched embeddings, the similarity scores, and the ids |