# Hands on Codelabs to dabble with Large Language Models in Java

> Dive into hands-on codelabs for Java developers to build LLM apps with PaLM 2 and LangChain4J, covering text generation, chat, and RAG.

Author: [Guillaume Laforge](https://glaforge.dev/) | Published: 2023-12-18 | Topics: machine-learning, large-language-models, generative-ai, google-cloud, java, gemini | Canonical: https://glaforge.dev/posts/2023/12/18/get-hands-on-codelabs-to-dabble-with-llms/


Hot on the heels of the [release of Gemini](https://glaforge.dev/posts/2023/12/13/get-started-with-gemini-in-java/),
I'd like to share a couple of resources I created to get your hands on large language models,
using [LangChain4J](https://github.com/langchain4j/), and the [PaLM 2](https://ai.google/discover/palm2/) model.
Later on, I'll also share with you articles and codelabs that take advantage of Gemini, of course.

The PaLM 2 model supports 2 modes:

- text generation,
- and chat.

In the 2 codelabs, you'll need to have created an account on Google Cloud, and created a project.
The codelabs will guide you through the steps to setup the environment,
and show you how to use the Google Cloud built-in shell and code editor, to develop in the cloud.

You should be a Java developer, as the examples are in Java, use the [LangChain4J](https://github.com/langchain4j/) project, and Maven for building the code.

### [Generative AI text generation in Java with PaLM and LangChain4J](https://codelabs.developers.google.com/codelabs/genai-text-gen-java-palm-langchain4j?hl=en#0)

In the first [codelab](https://codelabs.developers.google.com/codelabs/genai-text-gen-java-palm-langchain4j?hl=en#0)
you can explore:

- how to make your first call to PaLM for simple question/answer scenarios
- how to extract structured data out of unstructured text
- how to use prompts and prompt templates
- how to classify text, with an example on sentiment analysis

### [Generative AI powered chat with users and docs in Java with PaLM and LangChain4J](https://codelabs.developers.google.com/codelabs/genai-chat-java-palm-langchain4j?hl=en#0)

In the second [codelab](https://codelabs.developers.google.com/codelabs/genai-chat-java-palm-langchain4j?hl=en#0)
you'll use the chat model to learn:

- how to create your first chat with the PaLM model
- how to give your chatbot a personality, with an example with a chess player
- how to extract structured data out of unstructured text using LangChain4J's AiServices and its annotations
- how to implement Retrieval Augmented Generation (RAG) to answer questions about your own documentation

## Going further with Generative AI

If you're interested in going further with Generative AI, and learn more,
feel free to [join the Google Cloud Innovators program](https://goo.gle/generativeai).

Google Cloud Innovators is **free** and includes:

- live discussions, AMAs, and roadmap sessions to learn the latest directly from Googlers,
- the latest Google Cloud news right in your inbox,
- digital badge and video conference background,
- and more.

Go check what the [program offers](https://cloud.google.com/innovators?hl=en)!