BAML is an innovative open-source framework crafted to streamline the creation of robust, production-ready Large Language Model (LLM) agents. Built with lightning-fast Rust, BAML offers consistent performance across various programming languages, including Python, TypeScript, Ruby, and Java. This versatility ensures seamless integration into diverse development environments. The framework stands out by supporting all LLMs, enhancing their capability to produce structured outputs through its unique Schema-Aligned Parsing (SAP) technique. By elevating model accuracy and reliability, BAML empowers developers to deploy advanced language models with ease and efficiency. Whether you're working on complex applications or simple tasks, BAML provides the tools necessary to elevate your AI solutions.

Rig is a versatile and open-source Rust framework designed to streamline the development of applications powered by large language models (LLMs). With Rig, developers can enjoy a consistent API experience across a variety of LLM providers, simplifying integration and boosting productivity. It offers advanced AI workflow abstractions that facilitate the creation of sophisticated systems, ensuring that even complex AI applications are manageable. Rig emphasizes type-safe interactions, providing developers with the confidence to build robust and reliable applications. The framework empowers developers to create a wide range of projects, from basic chatbots to intricate Retrieval-Augmented Generation (RAG) systems and multi-agent setups. Rig's design prioritizes ease of use and efficiency, making it an ideal choice for developers aiming to leverage the full potential of AI in their software solutions.

Rig is a versatile and open-source Rust framework designed to streamline the development of applications powered by large language models (LLMs). With Rig, developers can enjoy a consistent API experience across a variety of LLM providers, simplifying integration and boosting productivity. It offers advanced AI workflow abstractions that facilitate the creation of sophisticated systems, ensuring that even complex AI applications are manageable. Rig emphasizes type-safe interactions, providing developers with the confidence to build robust and reliable applications. The framework empowers developers to create a wide range of projects, from basic chatbots to intricate Retrieval-Augmented Generation (RAG) systems and multi-agent setups. Rig's design prioritizes ease of use and efficiency, making it an ideal choice for developers aiming to leverage the full potential of AI in their software solutions.