How to beginner · 3 min read

How to split by tokens in LangChain

Q: How to split by tokens in LangChain

Use LangChain's TokenTextSplitter to split text by tokens efficiently. It leverages tokenizers like tiktoken to chunk text based on token count, ensuring prompt size limits are respected.

Quick answer

Use LangChain's TokenTextSplitter to split text by tokens efficiently. It leverages tokenizers like tiktoken to chunk text based on token count, ensuring prompt size limits are respected.

PREREQUISITES

Python 3.8+
pip install langchain tiktoken
OpenAI API key (free tier works) if using OpenAI tokenizer

Setup

Install LangChain and tiktoken for token-based splitting. Set your OpenAI API key as an environment variable for tokenizer compatibility.

bash

pip install langchain tiktoken

Step by step

Use TokenTextSplitter from LangChain to split text by tokens. Specify the tokenizer name and chunk size to control token limits.

python

from langchain.text_splitter import TokenTextSplitter
import os

# Example text
text = """LangChain helps you build applications with LLMs by managing prompts and token limits effectively."""

# Initialize TokenTextSplitter with OpenAI tokenizer
splitter = TokenTextSplitter(
    encoding_name="cl100k_base",  # OpenAI tokenizer for GPT-4o
    chunk_size=10,                # max tokens per chunk
    chunk_overlap=0               # no overlap
)

# Split the text
chunks = splitter.split_text(text)

# Print chunks
for i, chunk in enumerate(chunks, 1):
    print(f"Chunk {i}: {chunk}")

output

Chunk 1: LangChain helps you build applications
Chunk 2: with LLMs by managing prompts and
Chunk 3: token limits effectively.

Common variations

Use different tokenizer encodings like gpt2 or r50k_base depending on your model.
Adjust chunk_size and chunk_overlap for your use case.
For async or streaming, integrate with LangChain's async utilities but token splitting remains synchronous.

Troubleshooting

If you get errors about unknown encoding, verify encoding_name matches a valid tiktoken encoding.
Ensure tiktoken is installed and up to date.
For very large texts, increase chunk_size or split text before token splitting.

✅

Key Takeaways

Use LangChain's TokenTextSplitter with a proper tokenizer to split text by tokens.
Adjust chunk_size and chunk_overlap to control token chunking for prompt limits.
Ensure the tokenizer encoding matches your target model's tokenization scheme.

Verified 2026-04 · gpt-4o

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