langchain-text-splitters
LangChain text splitting utilities
Decision gist · record as of 2026-08-14
Yes. The package is production-stable, actively maintained, has zero known vulnerabilities, and installs with minimal friction. It is a standard component of LangChain-based LLM workflows and is worth installing if you are building applications that need to split documents for language model processing.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; langchain-core must be installed as a runtime dependency.
- Low friction install with a single runtime dependency on langchain-core.
- The package is actively maintained with a recent release and no known vulnerabilities.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions; you may use, modify, and distribute the package freely provided you include the license notice.
last release 2026-04-16 (120 days) · last repo commit 2026-08-14 · 144,195 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 48,406,861 downloads/mo, #590 on PyPI
Alternatives
Verify before relying
pip install langchain-text-splitters
from langchain_text_splitters import CharacterTextSplitter
splitter = CharacterTextSplitter()
chunks = splitter.split_text(your_text)- Whether the package supports splitting formats beyond plain text (e.g., markdown, code, structured documents).
- Performance characteristics and memory usage when processing very large documents.
- Availability and behavior of specific splitting strategies beyond character-based splitting.
- Configurable parameters for chunk size and overlap behavior.
What it is and what it does
LangChain Text Splitters provides utilities for breaking text documents into smaller, manageable chunks—a critical preprocessing step when preparing documents for language model consumption. The package is part of the LangChain ecosystem and integrates with langchain-core to offer a variety of splitting strategies. It handles the common problem of fitting long documents into token limits and context windows of language models by chunking text according to configurable parameters.
The package is production-stable, actively maintained, and widely used in the LangChain community. It supports modern Python versions from 3.10 through 3.14 and has no known security vulnerabilities. Installation is straightforward with minimal dependencies, making it a lightweight addition to any LLM-focused Python project.
Use it for
- Prepare long documents for ingestion into language models by splitting them into chunks.
- Create text segments to preserve context when feeding documents to retrieval-augmented generation pipelines.
- Preprocess diverse document types before embedding them for semantic search or similarity matching.
- Break up large text corpora into uniform chunks for batch processing in NLP workflows.
- Segment documents for question-answering systems that require manageable input sizes.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is production-stable, actively maintained, has zero known vulnerabilities, and installs with minimal friction. It is a standard component of LangChain-based LLM workflows and is worth installing if you are building applications that need to split documents for language model processing.
Install
langchain-text-splitters on PyPI
Before you install
Low friction install with a single runtime dependency on langchain-core. The package is actively maintained with a recent release and no known vulnerabilities.
Requires Python 3.10 or later; langchain-core must be installed as a runtime dependency.
License in practice
MIT license permits commercial and private use with minimal restrictions; you may use, modify, and distribute the package freely provided you include the license notice.
Quickstart
pip install langchain-text-splitters
from langchain_text_splitters import CharacterTextSplitter
splitter = CharacterTextSplitter()
chunks = splitter.split_text(your_text)Verify before relying
- Whether the package supports splitting formats beyond plain text (e.g., markdown, code, structured documents).
- Performance characteristics and memory usage when processing very large documents.
- Availability and behavior of specific splitting strategies beyond character-based splitting.
- Configurable parameters for chunk size and overlap behavior.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0.0,>=3.10.0 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagelangchain-core |
| Maintenance | Actively maintained 120 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 48,406,861 / month, #590 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Software Development :: Libraries :: Python ModulesTopic :: Text Processing |
Evidence: langchain_text_splitters-1.1.2-py3-none-any.whl
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See also langchain-deepseek · langchain-perplexity · langchain-ollama · langchain-unstructured · chonkie-core · memchunk · semantic-text-splitter · langchain-qdrant · langchain · langchain-openai