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Hi 👋 First off, thanks a ton for your work on this 💚 Really appreciate what you're providing here for the community. ## Description This PR adds a basic language parser for the [Elixir](https://elixir-lang.org/) programming language. The parser code is based upon the approach outlined in https://github.com/langchain-ai/langchain/pull/13318: it's using `tree-sitter` under the hood and aligns with all the other `tree-sitter` based parses added that PR. The `CHUNK_QUERY` I'm using here is probably not the most sophisticated one, but it worked for my application. It's a starting point to provide "core" parsing support for Elixir in LangChain. It enables people to use the language parser out in real world applications which may then lead to further tweaking of the queries. I consider this PR just the ground work. - **Dependencies:** requires `tree-sitter` and `tree-sitter-languages` from the extended dependencies - **Twitter handle:**`@bitcrowd` ## Checklist - [x] **PR title**: "package: description" - [x] **Add tests and docs** - [x] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. <!-- If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17. --> |
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README.md |
🦜✂️ LangChain Text Splitters
Quick Install
pip install langchain-text-splitters
What is it?
LangChain Text Splitters contains utilities for splitting into chunks a wide variety of text documents.
For full documentation see the API reference and the Text Splitters module in the main docs.
📕 Releases & Versioning
langchain-text-splitters
is currently on version 0.0.x
.
Minor version increases will occur for:
- Breaking changes for any public interfaces NOT marked
beta
Patch version increases will occur for:
- Bug fixes
- New features
- Any changes to private interfaces
- Any changes to
beta
features
💁 Contributing
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
For detailed information on how to contribute, see the Contributing Guide.