llama-index vector stores hologres integration
Project description
LlamaIndex Vector_Stores Integration: Hologres
Please refer to the notebook for usage of Hologres as vector store in LlamaIndex.
Example Usage
pip install llama-index
pip install llama-index-vector-stores-hologres
# Connect to existing instance
from llama_index.core import VectorStoreIndex
from llama_index.vector_stores.hologres import HologresVectorStore
vector_store = HologresVectorStore.from_param(
host="***",
port=80,
user="***",
password="***",
database="***",
table_name="***",
embedding_dimension=1536,
pre_delete_table=True,
)
# Create index from existing stored vectors
index = VectorStoreIndex.from_vector_store(vector_store)
query_engine = index.as_query_engine()
response = query_engine.query(
"What did the author study prior to working on AI?"
)
print(response)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for llama_index_vector_stores_hologres-0.1.0.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | c733337abb0f87593d96dbc9a95b57a5ced35b4590b6888a8836f35b1472a52e |
|
MD5 | cb7b8f8c1fb5ff3dc7c7505717566053 |
|
BLAKE2b-256 | d3a85b525ab63ef5fc52d9f89b99121435a207e966bb23e62667aee2f891635a |
Close
Hashes for llama_index_vector_stores_hologres-0.1.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3256f838776031d06c13f1f18e050f15e84d488c999da9fe17269c78eea4283b |
|
MD5 | 8ea866183eaebb15a940c75b8f563d6e |
|
BLAKE2b-256 | 2f7310b70e2d93ca56f262afb1659b01980fa6dcd84b46d9636359525ab36500 |