RecursiveCharacterTextSplitter in LangChain - Mini Project: Build & Apply

Using RecursiveCharacterTextSplitter in Langchain

📖 Scenario: You are building a text processing tool that breaks a long text into smaller chunks for easier analysis. This is useful when working with large documents in language models.

🎯 Goal: Learn how to use the RecursiveCharacterTextSplitter from Langchain to split a long text into manageable pieces.

📋 What You'll Learn

Create a variable text with a multi-sentence string.

Create a chunk_size variable to set the maximum size of each chunk.

Use RecursiveCharacterTextSplitter with the chunk_size to split the text into chunks.

Store the result in a variable called chunks.

💡 Why This Matters

🌍 Real World

Splitting large documents into smaller parts helps language models process text efficiently without losing context.

💼 Career

Understanding text splitting is useful for building chatbots, search engines, and AI applications that handle large texts.

1

Create the text variable

Create a variable called text and assign it this exact string: "Langchain helps you build applications with language models. It provides tools to manage prompts, chains, and memory. RecursiveCharacterTextSplitter is useful for splitting long texts."

LangChain

# Create the text variable
# Your code here

Need a hint?

Use a string variable named text and assign the exact text given.

2

Set the chunk size

Create a variable called chunk_size and set it to 50 to define the maximum size of each text chunk.

LangChain

text = "Langchain helps you build applications with language models. It provides tools to manage prompts, chains, and memory. RecursiveCharacterTextSplitter is useful for splitting long texts."
# Set the chunk_size variable
# Your code here

Need a hint?

Define chunk_size as an integer with value 50.

3

Split the text using RecursiveCharacterTextSplitter

Import RecursiveCharacterTextSplitter from langchain.text_splitter. Then create an instance called text_splitter with chunk_size=chunk_size. Use text_splitter.split_text(text) to split the text and assign the result to a variable called chunks.

LangChain

text = "Langchain helps you build applications with language models. It provides tools to manage prompts, chains, and memory. RecursiveCharacterTextSplitter is useful for splitting long texts."
chunk_size = 50
# Import RecursiveCharacterTextSplitter and split the text
# Your code here

Need a hint?

Remember to import the class, create an instance with the chunk size, and call split_text on the text.

4

Complete by checking the chunks variable

Add a comment line that says # chunks now contains the split text pieces to indicate completion.

LangChain

from langchain.text_splitter import RecursiveCharacterTextSplitter

text = "Langchain helps you build applications with language models. It provides tools to manage prompts, chains, and memory. RecursiveCharacterTextSplitter is useful for splitting long texts."
chunk_size = 50

text_splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size)
chunks = text_splitter.split_text(text)
# Add a comment to indicate chunks are ready
# Your code here

Need a hint?

Add a comment line exactly as shown to mark the end of the code.