> ## Documentation Index
> Fetch the complete documentation index at: https://docs.chonkie.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview

> Explore cutting-edge chunking capabilities with Chonkie's experimental features

# Experimental Features

Welcome to Chonkie's experimental features! This section contains advanced, cutting-edge functionality that's currently in development and testing phases.

<Warning>
  **Experimental Notice**: Features in this section are experimental and may change significantly between versions. They are provided for early testing and feedback. Use with caution in production environments.
</Warning>

## What's Experimental?

Experimental features in Chonkie represent:

* **Advanced algorithms** that are still being refined
* **New chunking strategies** that may not be fully optimized
* **Innovative approaches** to text processing that need real-world validation
* **Features with evolving APIs** that may change based on user feedback
* **CLI improvements** allowing for directory processing and pipeline execution from the terminal

## Getting Started

To use experimental features, import them from the `chonkie.experimental` module:

```python theme={"system"}
from chonkie.experimental import CodeChunker

# Create an experimental chunker
chunker = CodeChunker(language="python", chunk_size=2048)
```

## Providing Feedback

Your feedback is crucial for graduating experimental features to stable status. If you encounter issues or have suggestions:

1. **Open an issue** on our [GitHub repository](https://github.com/chonkie-inc/chonkie)
2. **Join our Discord** to discuss with the community
3. **Share your use cases** to help us understand real-world applications

## Migration to Stable

When experimental features become stable, they will:

* Move to the main Chonkie namespace
* Receive API stability guarantees
* Include comprehensive documentation and examples
* Be covered by semantic versioning promises

<Note>
  We recommend using experimental features in development and testing environments first, and carefully evaluating their performance before production use.
</Note>