Orchard is an open-source framework intended for the research community. It provides a platform for training and evaluating AI agents across various task types. The framework’s design aims to simplify the process of working with agentic AI systems. Orchard reduces complexity while supporting strong performance from smaller models. This is achieved by allowing researchers to reuse the same infrastructure across different projects.
The framework’s architecture is designed for scalability. It is intended to support the development of agentic AI systems that can handle complex tasks. The framework’s open-source nature allows for community contributions and further development. This collaborative approach is expected to accelerate research in the field of agentic AI.
Orchard’s primary goal is to provide a consistent and efficient environment for researchers. This allows for focused experimentation and comparison of different agentic AI approaches. The framework’s design emphasizes performance and scalability, enabling the development of robust and reliable agentic AI systems.
Source: https://www.microsoft.com/en-us/research/blog/orchard-an-open-framework-for-scalable-agentic-ai/