AnalyticDB

AnalyticDB for PostgreSQL is a massively parallel processing (MPP) data warehousing service that is designed to analyze large volumes of data online.

AnalyticDB for PostgreSQL is developed based on the open-source Greenplum Database project and is enhanced with in-depth extensions by Alibaba Cloud. AnalyticDB for PostgreSQL is compatible with the ANSI SQL 2003 syntax and the PostgreSQL and Oracle database ecosystems. AnalyticDB for PostgreSQL also supports row store and column store. AnalyticDB for PostgreSQL processes petabytes of data offline at a high performance level and supports highly concurrent online queries.

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 AnalyticDB 向量数据库相关的功能。要运行此笔记本，您需要拥有一个正在运行的 AnalyticDB 实例：

使用 AnalyticDB Cloud 向量数据库。点击此处快速部署。

from langchain_community.vectorstores import AnalyticDB
from langchain_openai import OpenAIEmbeddings
from langchain_text_splitters import CharacterTextSplitter

API 参考：AnalyticDB | OpenAIEmbeddings | CharacterTextSplitter

拆分文档并通过调用 OpenAI API 获取嵌入向量

from langchain_community.document_loaders import TextLoader

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 = OpenAIEmbeddings()

API 参考：TextLoader

通过设置相关环境变量连接至 AnalyticDB。

export PG_HOST={your_analyticdb_hostname}
export PG_PORT={your_analyticdb_port} # Optional, default is 5432
export PG_DATABASE={your_database} # Optional, default is postgres
export PG_USER={database_username}
export PG_PASSWORD={database_password}

然后将您的嵌入向量和文档存储到 AnalyticDB 中。

import os

connection_string = AnalyticDB.connection_string_from_db_params(
    driver=os.environ.get("PG_DRIVER", "psycopg2cffi"),
    host=os.environ.get("PG_HOST", "localhost"),
    port=int(os.environ.get("PG_PORT", "5432")),
    database=os.environ.get("PG_DATABASE", "postgres"),
    user=os.environ.get("PG_USER", "postgres"),
    password=os.environ.get("PG_PASSWORD", "postgres"),
)

vector_db = AnalyticDB.from_documents(
    docs,
    embeddings,
    connection_string=connection_string,
)

查询和检索数据

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

print(docs[0].page_content)

Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. 

Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. 

One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. 

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.

向量存储概念指南
向量存储操操作指南

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