I’m confused about how the chunk_size setting works in langchain’s text splitter. I thought it would limit the maximum size of each text chunk, but my testing shows otherwise.
Here’s what I tried:
from langchain.text_splitter import CharacterTextSplitter
max_chars = 8
overlap_chars = 3
text_splitter = CharacterTextSplitter(chunk_size=max_chars, chunk_overlap=overlap_chars)
input_text = 'the quick brown fox jumps over the lazy dog'
result = text_splitter.split_text(input_text)
print(result)
The output is ['the quick brown fox jumps over the lazy dog'] which is way longer than my chunk_size=8 setting.
I get that it didn’t split because there was no separator found, but then what exactly does the chunk_size parameter control? The documentation wasn’t clear on this behavior and I’m trying to understand the actual purpose of this setting.
The chunk_size parameter doesn’t work like you’d think. It’s not a hard limit - it’s more like a target size that the splitter aims for when it finds good places to break.
CharacterTextSplitter has a hierarchy: it tries paragraph breaks first, then newlines, then spaces, and finally individual characters as a last resort. In your case, since there’s no paragraphs or newlines, it’d normally split on spaces. But here’s the thing - even splitting on spaces wouldn’t create chunks over your 8-character limit, so it just keeps everything together.
The splitter cares more about keeping meaningful chunks intact than chopping text at exact character counts. If you need strict limits, try RecursiveCharacterTextSplitter with different separator settings, or write custom logic that forces splits no matter what. Bottom line: chunk_size guides the process but won’t sacrifice text coherence.
Had this exact issue last year building a document processing pipeline. What others aren’t mentioning is that CharacterTextSplitter is actually helping you out.
With chunk_size=8, it won’t just hack your text at exactly 8 characters. It tries to split intelligently. Your sentence “the quick brown fox jumps over the lazy dog” has spaces, but splitting there with an 8-character limit would give you junk like “the quic” and “k brown”.
The splitter sees this coming and thinks “nope, that’ll create garbage” so it keeps everything as one chunk rather than break the meaning.
Learned this the hard way with legal documents. Set chunk_size too small and you get either zero splits or completely mangled fragments. Bump it to something reasonable like 20-30 characters and it’ll start splitting on spaces properly.
For real projects, I start around chunk_size=1000 and tweak from there depending on the content.
yeah, this surprised me too lol. the chunk_size only works after it finds valid separators. since your string doesn’t have any \n\n, it never checks the size limit. add some paragraph breaks and you’ll see it respect the 8 char limit. weird design choice but that’s how langchain works.
Had this exact problem when I started with LangChain! CharacterTextSplitter won’t split anything unless it finds the default separator - “\n\n” (double newline). Your test string is one continuous line with no paragraph breaks, so it treats the whole thing as one chunk no matter what chunk_size you set. Here’s how it works: first it looks for separators to find natural breaking points, then checks if those chunks are too big. Since your example has no double newlines, you get one massive chunk with everything. Toss some “\n\n” into your test text and chunk_size will actually do something. Threw me off at first too since most text tools just enforce hard character limits.