Zilliz

This notebook shows how to use functionality related to the Zilliz Cloud managed vector database.

To run, you should have a Zilliz Cloud instance up and running: https://zilliz.com/cloud

from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import CharacterTextSplitter
from langchain.vectorstores import Milvus
from langchain.document_loaders import TextLoader

# replace 
ZILLIZ_CLOUD_HOSTNAME = "" # example: "in01-17f69c292d4a50a.aws-us-west-2.vectordb.zillizcloud.com"
ZILLIZ_CLOUD_PORT = "" #example: "19532"

from langchain.document_loaders import TextLoader
loader = TextLoader('../../../state_of_the_union.txt')
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
docs = text_splitter.split_documents(documents)

embeddings = OpenAIEmbeddings()

vector_db = Milvus.from_documents(
    docs,
    embeddings,
    connection_args={"host": ZILLIZ_CLOUD_HOSTNAME, "port": ZILLIZ_CLOUD_PORT},
)

docs = vector_db.similarity_search(query)

docs[0]