lllm

A light-weight framework for building llm agentic systems with additional supports for program synthesis and neural-symbolic research.

LLLM is a lightweight framework for developing advanced agentic systems. Allows users to build a complex agentic system with <100 LoC. Prioritizing minimalism, modularity, and reliability, it is specifically suitable for complex and frontier agentic systems beyond daily chat. While these fields require deep architectural customization and highly diverse demands, developers and researchers often face the burden of managing low-level complexities such as exception handling, output parsing, and API error management. LLLM bridges this gap by offering necessary abstractions that balance high-level encapsulation with the simplicity required for flexible experimentation. It also tries to make the code plain, compact, easy-to-understand, with less unnecessary indirection, thus easy for customization for different projects' needs, to allow researchers and developers to focus on the core research questions. See https://lllm.one for detailed documentation.

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