November 2025
Intermediate to advanced
430 pages
11h 25m
Italian
book
AI applicata allo sviluppo Java aziendale (Italian Edition)
by Alex Soto Bueno, Markus Eisele, Natale Vinto
Content preview from AI applicata allo sviluppo Java aziendale (Italian Edition)
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Capitolo 8. LangChain4j
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Nel capitolo precedente, dedicato all', abbiamo visto come usare i modelli di intelligenza artificiale come API di modelli di inferenza. Questo metodo va bene per problemi semplici, ma quando si sviluppano soluzioni più complesse che usano molto l'intelligenza artificiale, servono più funzioni di una semplice richiesta/risposta.
In questo capitolo, ti presentiamo LangChain4j, un framework che semplifica l'integrazione delle funzionalità AI/LLM nelle app Java, offrendo funzionalità di alto livello come la memoria o l'aumento dei dati. Vedremo esempi usando Java semplice e la sua integrazione con Quarkus e Spring Boot, così potrai farti un'idea completa del suo utilizzo in vari progetti Java.
In questo capitolo imparerete Langchain4j dalle basi agli scenari avanzati, utilizzando prompt, memoria, aumento dei dati ed elaborazione delle immagini. Riserviamo il RAG per il prossimo capitolo.
Cos'è LangChain4j?
LangChain4j è un'implementazione Java ispirata al popolare framework Python LangChain. Aiuta gli sviluppatori a creare app che si integrano con gli LLMs. LangChain4j offre strumenti e astrazioni per semplificare l'integrazione degli LLMs nelle app basate su Java, abilitando funzionalità come NLP, generazione di testo, domande e risposte e altro ancora.
Come il framework LangChain, LangChain4j offre funzionalità per ...
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