AwaDB
AwaDB 是一款用于搜索和存储 LLM 应用程序使用的嵌入向量的 AI 原生数据库。
您需要使用 pip install -qU langchain-community 安装 langchain-community 才能使用此集成
此笔记本展示了如何使用与 AwaDB 相关的功能。
%pip install --upgrade --quiet awadb
from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores import AwaDB
from langchain_text_splitters import CharacterTextSplitter
loader = TextLoader("../../how_to/state_of_the_union.txt")
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=100, chunk_overlap=0)
docs = text_splitter.split_documents(documents)
db = AwaDB.from_documents(docs)
query = "What did the president say about Ketanji Brown Jackson"
docs = db.similarity_search(query)
print(docs[0].page_content)
And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.
带分数的相似性搜索
返回的距离分数在 0-1 之间。0 表示不相似，1 表示最相似
docs = db.similarity_search_with_score(query)
print(docs[0])
(Document(page_content='And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.', metadata={'source': '../../how_to/state_of_the_union.txt'}), 0.561813814013747)
恢复之前创建并添加数据的表格
AwaDB 会自动持久化添加的文档数据。
如果您能够恢复之前创建并添加的表格，您可以像下面这样操作
import awadb
awadb_client = awadb.Client()
ret = awadb_client.Load("langchain_awadb")
if ret:
print("awadb load table success")
else:
print("awadb load table failed")
awadb 加载表格成功