Скачать или смотреть langchain text splitters chunking for beginners 6 examples

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sure! langchain is a framework for developing applications powered by language models. one of its capabilities is efficiently chunking text into smaller segments, which can be particularly useful for processing long documents or texts in a manageable way. in this tutorial, we’ll go over text splitters in langchain and provide examples to help you understand how to use them effectively.

what are text splitters?

text splitters are tools designed to divide a body of text into smaller, more manageable pieces (or chunks). these chunks can then be processed individually, making it easier to work with large documents, especially for tasks such as summarization, q&a, or even training language models.

types of text splitters

langchain provides several types of text splitters. here are a few commonly used splitters:

1. **character splitter**: splits the text into chunks based on a fixed number of characters.
2. **sentence splitter**: splits the text into chunks based on sentences.
3. **token splitter**: splits the text into chunks based on tokens (words).
4. **whitespace splitter**: splits the text based on whitespace.
5. **chunked splitter**: allows you to specify chunk sizes and overlap.
6. **custom splitters**: you can also create your own splitting logic.

example 1: character splitter

```python
from langchain.text_splitter import charactertextsplitter

text = "this is an example text that we will split into chunks based on character length."
splitter = charactertextsplitter(chunk_size=10) split into chunks of 10 characters

chunks = splitter.split_text(text)
print(chunks)
```

example 2: sentence splitter

```python
from langchain.text_splitter import sentencetextsplitter

text = "this is the first sentence. this is the second sentence. and here is the third."
splitter = sentencetextsplitter()

chunks = splitter.split_text(text)
print(chunks)
```

example 3: token splitter

```python
from langchain.text_splitter import tokentextsplitter

text = "token splitt ...

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