agency
🕵️♂️ Library designed for developers eager to explore the potential of Large Language Models (LLMs) and other generative AI through a clean, effective, and Go-idiomatic approach.
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Overview
Agency是一个专为Go开发者设计的生成式AI库，致力于通过清洁、有效、符合Go语言习惯的方式探索大语言模型(LLM)的潜力。该库提供纯Go实现，无需依赖Python或JavaScript，支持静态类型检查和高性能执行。Agency的核心理念是支持清洁架构，通过分离业务逻辑和具体实现来构建可维护的AI应用。库提供了完整的OpenAI API绑定，支持文本生成、图像生成、语音合成和语音识别等多种AI功能。开发者可以轻松创建自定义操作并将其组合成复杂的AI流程，同时利用拦截器机制观察和调试每个执行步骤。Agency特别适合构建自主AI代理系统，从简单的聊天界面到复杂的数据分析应用都能胜任。
Deep Analysis
Key Differentiator
vs LangChainGo: Go-native design from scratch (not a Python port) — composable operations, interceptors, and multimodal support with clean Go-idiomatic architecture
⚡ Capabilities
- • Go-idiomatic library for LLM and generative AI applications
- • Clean architecture with operation composition into processes
- • Interceptors for step-by-step process observation
- • OpenAI API bindings (text-to-text, text-to-image, text-to-speech, speech-to-text)
- • Custom operation creation via simple interface
- • External function call support
- • Image-to-text operations
🔗 Integrations
OpenAI API (any OpenAI-compatible API)
✓ Best For
- ✓ Go developers wanting an idiomatic AI framework (not a Python port)
- ✓ Building multimodal AI applications in Go (text, image, speech)
- ✓ Teams preferring clean architecture with composable operations
✗ Not Ideal For
- ✗ Python-first AI teams
- ✗ Projects requiring multiple LLM provider support immediately
- ✗ Full autonomous agent capabilities (still in development)
Languages
Go
Deployment
go get github.com/neurocult/agency
⚠ Known Limitations
- ⚠ Only OpenAI-compatible providers currently (more planned)
- ⚠ No metadata tracking (tokens used, audio duration) yet
- ⚠ Autonomous agent API still in development
- ⚠ Relatively new — smaller community than LangChainGo
Pros
- + 纯Go实现提供卓越性能和类型安全，无需Python或JavaScript依赖
- + 支持清洁架构原则，业务逻辑与实现分离，代码可维护性高
- + 易于扩展的接口设计，可创建自定义操作并组合成复杂AI流程
Cons
- - 相对较新的库，GitHub星数较少(506)，社区规模有限
- - Go生态系统中AI库相对稀缺，可能缺乏一些成熟Python库的高级功能
- - 文档和示例相对有限，学习资源可能不如主流AI库丰富
Use Cases
- • 构建高性能的AI聊天机器人和对话系统
- • 开发复杂的数据分析和处理管道，利用LLM进行智能分析
- • 创建自主AI代理系统，实现多步骤推理和决策流程
Getting Started
1. 安装库：运行 `go get github.com/neurocult/agency` 添加依赖。2. 配置环境：设置 OPENAI_API_KEY 环境变量或创建 .env 文件。3. 创建首个AI助手：使用 openai.New() 创建提供者，配置模型参数，然后通过 SetPrompt() 和 Execute() 方法实现对话功能。