AI Engineering · Phase 2
Master LangChain4j end to end: AI Services, document loaders, splitters, embedding stores, retrievers, memory, and tool-using agents.
A complete LangChain4j introduction for Java developers: core abstractions, the AiServices declarative style, memory, tools and retrieval — plus an honest comparison with Spring AI.
Read tutorialConfigure chat models in LangChain4j: OpenAI, Anthropic Claude, Google Gemini, Mistral and Ollama — with streaming, timeouts, retries and how to swap providers without touching your code.
Read tutorialCompose multi-step LLM workflows in LangChain4j: sequential chains, routing by classification, and building custom chains from AI Services — when to chain and when a single call suffices.
Read tutorialLoad documents into LangChain4j from files, URLs, S3, GitHub and more, and parse PDF, DOCX and HTML with Apache Tika — the ingestion front-end for any RAG pipeline in Java.
Read tutorialChunk documents effectively in LangChain4j: the recursive splitter, chunk size and overlap tuning, splitting code and markdown, and why chunking is the highest-impact decision in RAG.
Read tutorialConfigure embedding models in LangChain4j: hosted models like OpenAI and Cohere, free in-process ONNX models, dimension matching, and choosing an embedding model for RAG.
Read tutorialStore and search vectors in LangChain4j: the in-memory store for tests, PgVector for production, Redis and Elasticsearch, plus metadata filtering and picking the right store.
Read tutorialBuild RAG in LangChain4j with ContentRetriever: attach retrieval to AI Services, transform queries, re-rank results, and assemble an advanced RAG pipeline with the RetrievalAugmentor.
Read tutorialBuild tool-using agents in LangChain4j: the @Tool annotation, how the agent loop works, bounding iterations, safe write tools and the ReAct pattern — with production-ready code.
Read tutorialAdd conversation memory to LangChain4j AI Services: message and token windows, per-user memory with @MemoryId, persistent stores, and why unbounded memory breaks in production.
Read tutorialReturn typed objects from LangChain4j AI Services: POJO and record return types, enums, lists, JSON schema mode and validation — no manual parsing of model responses.
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