Hippo(
self,
embedding_function: Embeddings,
table_name: str = 'test',
database_name: str| Name | Type | Description |
|---|---|---|
embedding_function* | Embeddings | Function used to embed the text. |
table_name | str | Default: 'test'Which Hippo table to use. Defaults to "test". |
database_name | str | Default: 'default'Which Hippo database to use. Defaults to "default". |
number_of_shards | int | Default: 1 |
number_of_replicas | int | Default: 1 |
connection_args | Optional[dict[str, any]] | Default: None |
index_params | Optional[dict] | Default: None |
drop_old | Optional[bool] | Default: False |
primary_field* | str | |
text_field* | str | |
vector_field* | str |
Hippo vector store.
You need to install hippo-api and run Hippo.
Please visit our official website for how to run a Hippo instance: https://www.transwarp.cn/starwarp
The connection args used for this class comes in the form of a dict, here are a few of the options: host (str): The host of Hippo instance. Default at "localhost". port (str/int): The port of Hippo instance. Default at 7788. user (str): Use which user to connect to Hippo instance. If user and password are provided, we will add related header in every RPC call. password (str): Required when user is provided. The password corresponding to the user.
Example:
.. code-block:: python
from langchain_community.vectorstores import Hippo from langchain_community.embeddings import OpenAIEmbeddings
embedding = OpenAIEmbeddings()
vector_store = Hippo.from_documents( docs, embedding=embeddings, table_name="langchain_test", connection_args=HIPPO_CONNECTION )
The number of shards for the Hippo table.Defaults to 1.
The number of replicas for the Hippo table.Defaults to 1.
The connection args used for this class comes in the form of a dict.
Which index params to use. Defaults to IVF_FLAT.
Whether to drop the current collection. Defaults to False.
Name of the primary key field. Defaults to "pk".
Name of the text field. Defaults to "text".
Name of the vector field. Defaults to "vector".