展示HN：OxyJen – 一款用于以图形方式执行大语言模型（LLMs）的Java框架
在过去的几个月里，我一直在构建 OxyJen，这是一个用于在 Java 中构建可靠的多步骤 AI 流水线的开源框架。在大多数 Java LLM 项目中，一切仍然只是字符串。你构建一个提示，发出调用，然后解析你的正则表达式，等待返回的“几乎是 JSON”的结果是否有效。这种方式脆弱、不易测试，感觉与 Java 的“契约优先”理念背道而驰。
OxyJen 的方法有所不同。它是一个基于图的编排框架（目前是顺序执行），在这个框架中，LLM 被视为流水线中的原生、可靠节点，而不是神奇的辅助工具。核心思想是为概率性 AI 调用带来确定性的可靠性。系统中的每个元素都是图中的一个节点，LLMNode、LLMChain、LLM API 被用来构建一个简单的 LLM 节点，支持重试/回退、抖动/退避和超时强制（目前支持 OpenAI）。
PromptTemplate、Variable（必需/可选）和 PromptRegistry 被用来构建和存储可重用的提示，避免你重复编写提示。
JSONSchema 和 SchemaGenerator 被用来从 POJOs/Records 构建模式，这将对这些 LLM 的输出提供 JSON 强制。SchemaNode<T> 封装了 SchemaEnforcer 和验证器，以便将 LLM 输出直接映射到类上。Enforcer 还确保你的输出是正确的，并进行最大重试。
目前正在开发 Tool API，以帮助用户在 OxyJen 中构建自定义工具。我现在是一个独立开发者，项目处于非常早期的阶段，因此我非常欢迎任何反馈和贡献（即使是文档中的小改进也会很有价值）。
OxyJen: [https://github.com/11divyansh/OxyJen](https://github.com/11divyansh/OxyJen)
查看原文
For the past few months, I've been building OxyJen, an open-source framework for building reliable, multi-step AI pipelines in Java.
In most Java LLM projects, everything is still just strings. You build a prompt, make a call, and then parse your regex and wait if it works on the "almost-JSON" that comes back. It's brittle, untestable, and feels like the opposite of Java's "contract-first" philosophy.<p>OxyJen's approach is different. It's a graph-based orchestration framework(currently sequential) where LLMs are treated as native, reliable nodes in a pipeline, not as magical helper utilities. The core idea is to bring deterministic reliability to probabilistic AI calls. Everything is a node in a graph based system, LLMNode, LLMChain, LLM api is used to build a simple LLM node for the graph with retry/fallback, jitter/backoff, timeout enforcements(currently supports OpenAI).<p>PromptTemplate, Variable(required/optional) and PromptRegistry is used to build and store reusable prompts which saves you from re writing prompts.<p>JSONSchema and SchemaGenerator is used to build schema from POJOs/Records which will provide Json enforcements on outputs of these LLMs. SchemaNode<T> wraps SchemaEnforcer and validator to map LLM output directly to the classes.
Enforcer also makes sure your output is correct and takes maximum retries.<p>Currently working on the Tool API to help users build their custom tools in Oxyjen.
I'm a solo builder right now and the project is in its very early stage so I would really appreciate any feedback and contributions(even a small improvement in docs would be valuable).<p>OxyJen: <a href="https://github.com/11divyansh/OxyJen" rel="nofollow">https://github.com/11divyansh/OxyJen</a>