JavAI Workflow 🦜🔂☕: Build programmatically custom agentic workflows, AI Agents, RAG systems for java

An open-source Java library to build, package, integrate, orchestrate and monitor agentic AI systems for java developers 💡

<details> <summary>☕ Java code</summary>

class MyStatefulBean extends AbstractStatefulBean {
  private List<String> documents;
  // other additional input/output fields that you want to store
}

StreamingChatLanguageModel model = OpenAiStreamingChatModel.builder()
        .apiKey(System.getenv("OPENAI_API_KEY"))
        .modelName(GPT_4_O_MINI)
        .build();

var parserDocsNode = Node.from("Docs", obj -> transformDocsFromUrl(obj, uris));
var retrieveNode = Node.from("Vector DB", obj -> extractRelevantDocumentsFromVectorDB(obj));
var generateAnswerNode = StreamingNode.from("Generate",obj -> generateAnswer(obj), model);

var jAiWorkflow = new DefaultJAiWorkflow<MyStatefulBean>(
        new MyStatefulBean(),
        List.of(Transition.from(parserDocsNode, retrieveNode),
                Transition.from(retrieveNode, Conditional.eval("enoughData", 
                        obj -> obj.isEnoughData() ? generateAnswerNode : parserDocsNode, 
                        List.of(parserDocsNode, generateAnswerNode))),
                Transition.from(generateAnswerNode, WorkflowStateName.END)),
        retrieveNode, // Start node
        true // Run in streaming mode
);

// Chat with your JAiWorkflow
var question = "Summarizes the importance of building AI agentic systems";
Flux<String> response = jAiWorkflow.answerStream(question);

</details>