LangChain4j

Headlines · 3

1. 17h
   Comparing Four Ways to Connect qwen-plus in a Spring Boot App

   A Juejin AI tutorial implements the same “你是谁？” prompt with qwen-plus through DashScope’s official Java SDK, direct HTTP, Spring AI with Spring AI Alibaba, and LangChain4j. The author recommends using the official SDK to verify credentials, model configuration, and connectivity before moving to Spring AI for business development, while presenting HTTP as a protocol-inspection option and LangChain4j as the shortest but community-dependent implementation.

   掘金 · 人工智能 · 🔥 3
2. 2d
   An 11-Case Golden Set for Measuring RAG Retrieval Quality

   A smart document assistant developer built an offline RAG evaluation using 11 fixed questions, scoring whether an essential answer phrase appears within the top retrieved chunks and its reciprocal rank. The default parent-child chunking, hybrid retrieval, and reranker top-5 configuration achieved recall@1 of 0.455, recall@3 of 0.818, recall@5 of 1.000, and MRR of 0.652; flat chunking produced lower results, while reranker top-2 reduced recall@3 and MRR. Disabling keyword retrieval produced the same aggregate metrics as the default configuration.

   掘金 · 人工智能 · 🔥 0
3. 6d
   A Beginner’s Guide to Spring AI Application Development

   A Juejin article presents a beginner-oriented introduction to AI application development for backend developers familiar with Spring Boot. It explains architecture, RAG, Tool Calling, MCP, Spring AI Advisors, memory, vector retrieval and Agent/ReAct concepts, alongside runnable code and five implementation pitfalls. The article also compares Alibaba Cloud Bailian and DashScope and discusses how models can be accessed through cloud services, self-hosted deployments, platforms, clients and code.

   掘金 · 人工智能 · 🔥 0

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