Welcome to the Semantic Chunking Project, a comprehensive research initiative focused on developing and evaluating innovative methods for semantic chunking. Our goal is to enhance understanding and processing of natural language through advanced chunking techniques.
The project is organized into several key components, each designed to facilitate efficient research and development:
- Location:
notebooks/lab_book.ipynb - Purpose: This Jupyter notebook contains detailed records of experiments, including data analysis, algorithm testing, and results evaluation.
- Package:
chroma_research - Example Usage: Refer to
main.pyfor example implementations using our package, demonstrating how to apply our methods to your datasets.
- Location:
/data - Details: All databases and datasets utilized in our research are stored here, ensuring easy access and reproducibility.
- Notes:
notes.md - Contents: Contains references, bibliographic details, and inspiration sources that have guided our research methodology.
- Python Version: 3.11.8
Please ensure that your development environment matches the specified Python version to avoid compatibility issues.
To begin using the Semantic Chunker project, clone the repository and navigate to the respective files detailed above. Installation instructions and additional documentation can be found within each component's respective files.
We encourage contributions and feedback on our project to continuously improve and push the boundaries of semantic chunking research. Feel free to fork the repository, suggest changes, or discuss your ideas with us.