genai-friendly-architecture provides a flexible architecture pattern for building AI-ready systems. With this approach, you can create robust solutions without being tied to any one framework. Start developing today while keeping your options open for the future.
To get started with genai-friendly-architecture, you will need to follow these steps:
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Ensure your computer meets the basic requirements. Please use a Windows, macOS, or Linux system. Make sure you have at least 4GB of RAM and 2GB of free disk space.
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Visit the Releases page to download the latest version of the software.
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Click on the version you wish to download. Each release includes a compiled version you can run.
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After the download finishes, find the file in your Downloads folder.
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Double-click the file to run it. Follow the on-screen instructions to set up the application.
To download and install the software, simply visit this releases page. You will find the latest version clearly listed. Choose the file that matches your operating system and download it.
- Framework Agnostic: Build applications without being locked into any single framework.
- AI Ready: Easily integrate AI capabilities into your systems.
- Future-Proof: Design your architecture with future changes in mind.
- User-Friendly: Built with non-technical users in mind, making it easy to understand and use.
Before running genai-friendly-architecture, make sure you have the following:
- Operating System: Windows 10, macOS Catalina (or newer), or a recent Linux distribution.
- Memory: Minimum of 4GB RAM.
- Storage: At least 2GB of available disk space.
- Python: Recommended version 3.8 or higher.
Once you have installed genai-friendly-architecture, you can start to explore its features:
- Creating Workflows: Follow the simple guides to create workflows for AI models.
- Integrating AI Tools: Utilize built-in options to connect various AI resources, such as Langgraph and temporal orchestration.
- Logging and Monitoring: Keep track of your system’s performance and manage tasks efficiently.
For more in-depth information and tutorials, consult the official documentation available on the GitHub wiki. Here, you will find guides on specific functionalities and advanced usage.
We welcome contributions to improve genai-friendly-architecture. If you have suggestions for new features or improvements, please feel free to fork the repository and create a pull request.
If you encounter any issues or have questions, you can open an issue in the GitHub Issues section. We review and respond to all inquiries promptly.
Join the conversation around AI, orchestration, and architecture patterns by following relevant discussions. This project covers topics such as:
- AI Orchestration
- Machine Learning Operations (MLOps)
- Workflow Management
- Future updates will include enhanced features to support more AI models.
- Additional tutorials on advanced configurations and integrations.
Feel free to explore and contribute to genai-friendly-architecture. We are excited to have you as part of our community!