ℹ️ About this Session
Discover how to integrate generative artificial intelligence into your Java applications without expertise in machine learning or Python. This university will introduce you to Large Language Models (LLMs) and prompting techniques. Learn to code in Java with LangChain4J to use Google's Gemini LLM in your projects. We will cover the Retrieval Augmented Generation (RAG) approach and integration with a vector database like Apache Cassandra, to generate responses with your own data. The session will include strategies to minimize errors and hallucinations from LLMs (e.g., FLARE) but will also introduce more advanced multimodal models (LMM). Ideal for Java developers eager to add AI capabilities to their applications and who want to go beyond the simple "hello world" chatbot!
⏲️ Duration : 3 hours
🎓 Level Intermediate
- _10_LanguageModelSayHello.java
- _11_LanguageModel_SayHelloTest.java
- _12_LanguageModel_ModelTuningTest.java
- _13_LanguageModel_ExtractTextTest.java
- _14_ImageModel_GenerateTest.java
- _15_ChatLanguageModel_SayHelloTest.java
- _16_PromptTemplateTest.java
- _21_GemmaChat.java
- _51_EmbeddingModel.java
- _52_CassandraVectorDbTest.java
- _53_CassIOVectorDbTest.java
- _54_CassandraVectorStore.java
- _55_AstraVectorTest.java
- _61_NaiveRag_IngestionTest.java
- _62_NaiveRag_RetrievalTest.java
- _63_AdvancedRag_AugmentWithMetadata.java
- _64_AdvancedRag_QueryRouting.java
- _65_AdvancedRag_QueryCompression.java
- _66_AdvancedRag_QueryReranking.java
- _71_CallFunctionTest.java