Returns
Epsilla vector store.
Return type
Epsilla
classmethod from_texts(texts: List[str], embedding: Embeddings, metadatas: Optional[List[dict]] = None, client: Any = None, db_path: Optional[str] = '/tmp/langchain-epsilla', db_name: Optional[str] = 'langchain_store', collection_name: Optional[str] = 'langchain_collection', drop_old: Optional[bool] = False, **kwargs: Any) → Epsilla[source]¶
Create an Epsilla vectorstore from raw documents.
Parameters
texts (List[str]) – List of text data to be inserted.
embeddings (Embeddings) – Embedding function.
client (pyepsilla.vectordb.Client) – Epsilla client to connect to.
metadatas (Optional[List[dict]]) – Metadata for each text.
Defaults to None.
db_path (Optional[str]) – The path where the database will be persisted.
Defaults to “/tmp/langchain-epsilla”.
db_name (Optional[str]) – Give a name to the loaded database.
Defaults to “langchain_store”.
collection_name (Optional[str]) – Which collection to use.
Defaults to “langchain_collection”.
If provided, default collection name will be set as well.
drop_old (Optional[bool]) – Whether to drop the previous collection
and create a new one. Defaults to False.
Returns
Epsilla vector store.
Return type
Epsilla
get(collection_name: str = '', response_fields: Optional[List[str]] = None) → List[dict][source]¶
Get the collection.
Parameters
collection_name (Optional[str]) – The name of the collection
to retrieve data from.
If not provided, the default collection will be used.