LazyLLM

LazyLLM is an open source development framework for building and optimizing multi agent AI applications. It is written in Python and aims to cover the stages of application development in one toolkit: application construction, data preparation, model deployment, model fine tuning and evaluation. The stated goal is to let developers build AI applications at low cost and keep iterating on their quality. The documentation walks through a first hello world program, multi turn dialogue, a web interface and a command line interface. A cookbook, best practice guides, advanced topics, an API reference and tutorials follow, along with a list of supported models and a roadmap. Features documented include an automatic registry mechanism for extending components. Developers can install the minimal dependencies for key features or add extras for particular scenarios with the lazyllm install command, and the project can be set up manually from the GitHub repository, with Docker, or from pip. LazyLLM is aimed at Python developers building agent and retrieval applications, and at teams that want deployment and fine tuning handled in the same framework as application logic. The code is developed in the LazyAGI repository on GitHub. The documentation site lists no pricing. The framework is distributed through pip, Docker and its repository.