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agency

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Basic Information

Agency is a Go library for developers who want to build and experiment with large language models and generative AI in an idiomatic, statically typed way. It is designed to simplify creation of assistants and autonomous agent systems by providing a small, extendable core that separates business logic from concrete implementations. The project targets both simple chat interfaces and more complex workflows such as retrieval-augmented generation and multimodal operations. It offers OpenAI-compatible API bindings and example code to get started quickly. The README emphasizes using Go-native patterns rather than porting Python frameworks, and positions Agency as a foundation for composing operations into processes and for coordinating single or multiple agents.

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490
App URL
https://github.com/neurocult/agency
Github Repository
https://github.com/neurocult/agency/blob/main/README.md

App Details

Features
Pure Go implementation emphasizing speed, light weight, and static typing. Clean architecture that separates business logic from providers and concrete implementations. Simple interfaces that let developers create custom operations and compose them into processes. Interceptors that allow observation of each step in a process. OpenAI API bindings supporting text-to-text, image, and speech operations and compatibility with OpenAI-like APIs. Examples and quick start code for chat, RAGs, and multimodal use cases. Roadmap items include external function calls and expanded provider adapters. The library focuses on extendability and Go-idiomatic design rather than reusing Python idioms.
Use Cases
Agency helps developers prototype and build generative AI features and autonomous agents within a Go ecosystem. By offering a compact core and well-defined interfaces, it reduces boilerplate and makes it easier to swap providers or add new operations without changing business logic. Observability via interceptors aids debugging and monitoring of multi-step processes. The included examples and quick start demonstrate chat loops and RAG scenarios so developers can adapt patterns to their applications. Support for OpenAI-compatible APIs and multimodal operations lowers integration friction. The roadmap indicates ongoing improvements like metadata handling and a more powerful API for autonomous agents, signaling continued utility for both experimentation and production-focused development.

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