Supabase (Postgres)
Supabase 是一個開源的 Firebase 替代方案。
Supabase
建構於PostgreSQL
之上,提供強大的 SQL 查詢功能,並能夠與現有的工具和框架建立簡單的介面。
PostgreSQL,又稱
Postgres
,是一個免費且開源的關聯式資料庫管理系統 (RDBMS),強調可擴展性和符合 SQL 標準。
這個筆記本展示了如何使用 Supabase
和 pgvector
作為您的向量資料庫 (VectorStore)。
您需要安裝 langchain-community
,使用 pip install -qU langchain-community
才能使用此整合。
要運行這個筆記本,請確保:
- 已啟用
pgvector
擴展 - 您已安裝
supabase-py
套件 - 您已在資料庫中建立一個
match_documents
函數 - 在您的
public
schema 中有一個與下方類似的documents
資料表。
以下函數確定餘弦相似度,但您可以根據您的需求進行調整。
-- Enable the pgvector extension to work with embedding vectors
create extension if not exists vector;
-- Create a table to store your documents
create table
documents (
id uuid primary key,
content text, -- corresponds to Document.pageContent
metadata jsonb, -- corresponds to Document.metadata
embedding vector (1536) -- 1536 works for OpenAI embeddings, change if needed
);
-- Create a function to search for documents
create function match_documents (
query_embedding vector (1536),
filter jsonb default '{}'
) returns table (
id uuid,
content text,
metadata jsonb,
similarity float
) language plpgsql as $$
#variable_conflict use_column
begin
return query
select
id,
content,
metadata,
1 - (documents.embedding <=> query_embedding) as similarity
from documents
where metadata @> filter
order by documents.embedding <=> query_embedding;
end;
$$;
# with pip
%pip install --upgrade --quiet supabase
# with conda
# !conda install -c conda-forge supabase
我們想要使用 OpenAIEmbeddings
,因此必須取得 OpenAI API 金鑰。
import getpass
import os
if "OPENAI_API_KEY" not in os.environ:
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")
if "SUPABASE_URL" not in os.environ:
os.environ["SUPABASE_URL"] = getpass.getpass("Supabase URL:")
if "SUPABASE_SERVICE_KEY" not in os.environ:
os.environ["SUPABASE_SERVICE_KEY"] = getpass.getpass("Supabase Service Key:")
# If you're storing your Supabase and OpenAI API keys in a .env file, you can load them with dotenv
from dotenv import load_dotenv
load_dotenv()
首先,我們將建立一個 Supabase 客戶端並實例化一個 OpenAI embeddings 類別。
import os
from langchain_community.vectorstores import SupabaseVectorStore
from langchain_openai import OpenAIEmbeddings
from supabase.client import Client, create_client
supabase_url = os.environ.get("SUPABASE_URL")
supabase_key = os.environ.get("SUPABASE_SERVICE_KEY")
supabase: Client = create_client(supabase_url, supabase_key)
embeddings = OpenAIEmbeddings()
API 參考資料:SupabaseVectorStore | OpenAIEmbeddings
接下來,我們將載入和解析一些資料用於我們的向量資料庫(如果您已經在資料庫中儲存了帶有嵌入的文件,請跳過)。
from langchain_community.document_loaders import TextLoader
from langchain_text_splitters import 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)
API 參考資料:TextLoader | CharacterTextSplitter
將以上文件插入到資料庫中。將會自動為每個文件產生嵌入。您可以根據擁有的文件數量調整 chunk_size。 預設值為 500,但降低它可能是必要的。
vector_store = SupabaseVectorStore.from_documents(
docs,
embeddings,
client=supabase,
table_name="documents",
query_name="match_documents",
chunk_size=500,
)
或者,如果您已經在資料庫中擁有帶有嵌入的文件,只需直接實例化一個新的 SupabaseVectorStore
vector_store = SupabaseVectorStore(
embedding=embeddings,
client=supabase,
table_name="documents",
query_name="match_documents",
)
最後,透過執行相似度搜尋來進行測試。
query = "What did the president say about Ketanji Brown Jackson"
matched_docs = vector_store.similarity_search(query)
print(matched_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.
帶分數的相似度搜尋
返回的距離分數是餘弦距離。因此,分數越低越好。
matched_docs = vector_store.similarity_search_with_relevance_scores(query)
matched_docs[0]
(Document(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. \n\nTonight, 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. \n\nOne of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n\nAnd 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': '../../../state_of_the_union.txt'}),
0.802509746274066)
檢索器選項
本節介紹如何使用 SupabaseVectorStore 作為檢索器的不同選項。
最大邊際相關性搜尋 (Maximal Marginal Relevance Searches)
除了在檢索器物件中使用相似度搜尋外,您還可以使用 mmr
。
retriever = vector_store.as_retriever(search_type="mmr")
matched_docs = retriever.invoke(query)
for i, d in enumerate(matched_docs):
print(f"\n## Document {i}\n")
print(d.page_content)
## Document 0
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.
## Document 1
One was stationed at bases and breathing in toxic smoke from “burn pits” that incinerated wastes of war—medical and hazard material, jet fuel, and more.
When they came home, many of the world’s fittest and best trained warriors were never the same.
Headaches. Numbness. Dizziness.
A cancer that would put them in a flag-draped coffin.
I know.
One of those soldiers was my son Major Beau Biden.
We don’t know for sure if a burn pit was the cause of his brain cancer, or the diseases of so many of our troops.
But I’m committed to finding out everything we can.
Committed to military families like Danielle Robinson from Ohio.
The widow of Sergeant First Class Heath Robinson.
He was born a soldier. Army National Guard. Combat medic in Kosovo and Iraq.
Stationed near Baghdad, just yards from burn pits the size of football fields.
Heath’s widow Danielle is here with us tonight. They loved going to Ohio State football games. He loved building Legos with their daughter.
## Document 2
And I’m taking robust action to make sure the pain of our sanctions is targeted at Russia’s economy. And I will use every tool at our disposal to protect American businesses and consumers.
Tonight, I can announce that the United States has worked with 30 other countries to release 60 Million barrels of oil from reserves around the world.
America will lead that effort, releasing 30 Million barrels from our own Strategic Petroleum Reserve. And we stand ready to do more if necessary, unified with our allies.
These steps will help blunt gas prices here at home. And I know the news about what’s happening can seem alarming.
But I want you to know that we are going to be okay.
When the history of this era is written Putin’s war on Ukraine will have left Russia weaker and the rest of the world stronger.
While it shouldn’t have taken something so terrible for people around the world to see what’s at stake now everyone sees it clearly.
## Document 3
We can’t change how divided we’ve been. But we can change how we move forward—on COVID-19 and other issues we must face together.
I recently visited the New York City Police Department days after the funerals of Officer Wilbert Mora and his partner, Officer Jason Rivera.
They were responding to a 9-1-1 call when a man shot and killed them with a stolen gun.
Officer Mora was 27 years old.
Officer Rivera was 22.
Both Dominican Americans who’d grown up on the same streets they later chose to patrol as police officers.
I spoke with their families and told them that we are forever in debt for their sacrifice, and we will carry on their mission to restore the trust and safety every community deserves.
I’ve worked on these issues a long time.
I know what works: Investing in crime prevention and community police officers who’ll walk the beat, who’ll know the neighborhood, and who can restore trust and safety.