6大核心模块(Modules)
示例(Examples)
NLTK

LangChain

NLTK文本分割器#

我们不仅可以根据“ ”进行分割,还可以使用NLTK根据分词器进行分割。

  • 文本如何分割:由NLTK进行

  • 如何测量块大小:通过传递的长度函数进行测量(默认为字符数)

# This is a long document we can split up.
with open('../../../state_of_the_union.txt') as f:
    state_of_the_union = f.read()
 
from langchain.text_splitter import NLTKTextSplitter
text_splitter = NLTKTextSplitter(chunk_size=1000)
 
texts = text_splitter.split_text(state_of_the_union)
print(texts[0])
 
Madam Speaker, Madam Vice President, our First Lady and Second Gentleman.
 
Members of Congress and the Cabinet.
 
Justices of the Supreme Court.
 
My fellow Americans.
 
Last year COVID-19 kept us apart.
 
This year we are finally together again.
 
Tonight, we meet as Democrats Republicans and Independents.
 
But most importantly as Americans.
 
With a duty to one another to the American people to the Constitution.
 
And with an unwavering resolve that freedom will always triumph over tyranny.
 
Six days ago, Russia’s Vladimir Putin sought to shake the foundations of the free world thinking he could make it bend to his menacing ways.
 
But he badly miscalculated.
 
He thought he could roll into Ukraine and the world would roll over.
 
Instead he met a wall of strength he never imagined.
 
He met the Ukrainian people.
 
From President Zelenskyy to every Ukrainian, their fearlessness, their courage, their determination, inspires the world.
 
Groups of citizens blocking tanks with their bodies.