Overlap and chunk boundaries in LangChain - Mini Project: Build & Apply

Overlap and Chunk Boundaries in Langchain Text Splitting

📖 Scenario: You are building a text processing tool that breaks a long document into smaller pieces called chunks. These chunks help in searching and analyzing text efficiently. Sometimes, chunks overlap to keep context between pieces.

🎯 Goal: Create a Langchain text splitter that divides a long text into chunks of 50 characters with an overlap of 10 characters. You will set up the text, configure the splitter, split the text, and then finalize the chunk output.

📋 What You'll Learn

Create a variable text with the exact string: 'Langchain helps you build applications with language models easily.'

Create a CharacterTextSplitter with chunk_size=50 and chunk_overlap=10

Use the splitter's split_text method on text to get chunks

Print the list of chunks stored in chunks

💡 Why This Matters

🌍 Real World

Breaking large documents into smaller chunks with overlaps helps maintain context in search engines, chatbots, and language model applications.

💼 Career

Understanding text chunking and overlap is important for building efficient natural language processing pipelines and improving user experience in AI applications.

1

Set up the text variable

Create a variable called text and assign it the string exactly: 'Langchain helps you build applications with language models easily.'

LangChain

# Create the text variable
# Your code here

Need a hint?

Use single or double quotes to assign the exact string to text.

2

Configure the CharacterTextSplitter

Import CharacterTextSplitter from langchain.text_splitter and create a variable called splitter that is a CharacterTextSplitter with chunk_size=50 and chunk_overlap=10.

LangChain

text = 'Langchain helps you build applications with language models easily.'
# Import CharacterTextSplitter and create splitter with chunk_size=50 and chunk_overlap=10
# Your code here

Need a hint?

Use the exact class name and parameters as shown.

3

Split the text into chunks

Use the split_text method of splitter on the variable text and assign the result to a variable called chunks.

LangChain

from langchain.text_splitter import CharacterTextSplitter

text = 'Langchain helps you build applications with language models easily.'
splitter = CharacterTextSplitter(chunk_size=50, chunk_overlap=10)
# Split the text into chunks using splitter.split_text
# Your code here

Need a hint?

Call split_text on splitter with text as argument.

4

Output the chunks variable

Add a line that assigns the variable output to the value of chunks. This will represent the final chunked text output.

LangChain

from langchain.text_splitter import CharacterTextSplitter

text = 'Langchain helps you build applications with language models easily.'
splitter = CharacterTextSplitter(chunk_size=50, chunk_overlap=10)
chunks = splitter.split_text(text)
# Assign output to chunks
# Your code here

Need a hint?

Simply assign output to chunks.