百度向量数据库

Baidu VectorDB is a robust, enterprise-level distributed database service, meticulously developed and fully managed by Baidu Intelligent Cloud. It stands out for its exceptional ability to store, retrieve, and analyze multi-dimensional vector data. At its core, VectorDB operates on Baidu's proprietary "Mochow" vector database kernel, which ensures high performance, availability, and security, alongside remarkable scalability and user-friendliness.

This database service supports a diverse range of index types and similarity calculation methods, catering to various use cases. A standout feature of VectorDB is its capacity to manage an immense vector scale of up to 10 billion, while maintaining impressive query performance, supporting millions of queries per second (QPS) with millisecond-level query latency.

您需要使用 pip install -qU langchain-community 安装 langchain-community 才能使用此集成

本笔记本展示了如何使用与百度向量数据库相关的功能。

要运行，您需要拥有一个数据库实例。。

!pip3 install pymochow

from langchain_community.document_loaders import TextLoader
from langchain_community.embeddings.fake import FakeEmbeddings
from langchain_community.vectorstores import BaiduVectorDB
from langchain_community.vectorstores.baiduvectordb import ConnectionParams
from langchain_text_splitters import CharacterTextSplitter

API 参考：TextLoader | FakeEmbeddings | BaiduVectorDB | ConnectionParams | CharacterTextSplitter

loader = TextLoader("../../how_to/state_of_the_union.txt")
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
docs = text_splitter.split_documents(documents)
embeddings = FakeEmbeddings(size=128)

conn_params = ConnectionParams(
    endpoint="http://192.168.xx.xx:xxxx", account="root", api_key="****"
)

vector_db = BaiduVectorDB.from_documents(
    docs, embeddings, connection_params=conn_params, drop_old=True
)

query = "What did the president say about Ketanji Brown Jackson"
docs = vector_db.similarity_search(query)
docs[0].page_content

vector_db = BaiduVectorDB(embeddings, conn_params)
vector_db.add_texts(["Ankush went to Princeton"])
query = "Where did Ankush go to college?"
docs = vector_db.max_marginal_relevance_search(query)
docs[0].page_content

向量存储概念指南
向量存储操操作指南

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