Скачать или смотреть Understanding the Langchain Text Splitter Behavior: A Breakdown of RecursiveCharacterTextSplitter

Dive into the behavior of the `Langchain` `RecursiveCharacterTextSplitter`. Learn how it processes text and why it generates unexpected chunk sizes.
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This video is based on the question https://stackoverflow.com/q/76633711/ asked by the user 'GreenEye' ( https://stackoverflow.com/u/2072837/ ) and on the answer https://stackoverflow.com/a/76633770/ provided by the user 'Xiaomin Wu' ( https://stackoverflow.com/u/16637552/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Understanding the Langchain Text Splitter Behavior

When working with natural language processing in Python, you might encounter scenarios where you need to split text into manageable chunks. For this purpose, the Langchain library provides a tool called RecursiveCharacterTextSplitter. However, some users might find the output unexpected. Let's explore a real-world problem that highlights this behavior and break it down for clarity.

The Problem: Unexpected Output from the Text Splitter

You might have experimented with the code below using the RecursiveCharacterTextSplitter:

[[See Video to Reveal this Text or Code Snippet]]

Output

Running the code yields the following output:

[[See Video to Reveal this Text or Code Snippet]]

At first glance, you might expect a more granular output, specifically:

[[See Video to Reveal this Text or Code Snippet]]

However, the text splitter produced two chunks of size 7 and 5, splitting only at one of the newline characters. Let's dissect this behavior.

The Solution: Understanding split_text

The way RecursiveCharacterTextSplitter operates is key to comprehending the output. Here’s how the split_text function is defined:

[[See Video to Reveal this Text or Code Snippet]]

Explanation of the Code

Separator Determination:

The function first determines the appropriate separator from its internal list. In this case, it finds the newline character (\n) present in the input string.

Initial Splitting:

The text is initially split using the identified separator. Therefore, the input test becomes a list: ['a', 'bcefg', 'hij', 'k'].

Chunking Logic:

The function then examines each segment. If a segment's length is less than the defined chunk_size (which is 10), it is added to the _good_splits list.

If _good_splits contains entries, and a subsequent segment exceeds the chunk_size, the entries in _good_splits are merged and added to the final output.

The function recursively calls itself to process longer segments, which may further split them based on the defined logic.

The Key Takeaway

In your scenario, because the cumulative length of 'a\nbcefg' is less than the chunk_size, they are merged into one chunk. The remaining sections are dealt with similarly, resulting in the unexpected final output.

Conclusion

The Langchain RecursiveCharacterTextSplitter uses a fairly complex blending of splitting and merging logic that can surprise new users. Understanding the flow of the split_text function can help you better manage text chunking in your own applications. Experimenting with different settings for chunk_size and chunk_overlap, as well as adjusting the separators, can lead to more predictable results.

Remember, when working with libraries like Langchain, a deep dive into the documentation and source code can provide clarity to confusing behaviors. Happy coding!