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<figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/0*QAqyUui7Mp-t2o8U.png" /></figure><p>Hot on the heels of the <a href="https://glaforge.dev/posts/2023/12/13/get-started-with-gemini-in-java/">release of Gemini</a>, I’d like to share a couple of resources I created to get your hands on large language models, using <a href="https://github.com/langchain4j/">LangChain4J</a>, and the <a href="https://ai.google/discover/palm2/">PaLM 2</a> model. Later on, I’ll also share with you articles and codelabs that take advantage of Gemini, of course.</p><p>The PaLM 2 model supports 2 modes:</p><ul><li>text generation,</li><li>and chat.</li></ul><p>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.</p><p>You should be a Java developer, as the examples are in Java, use the <a href="https://github.com/langchain4j/">LangChain4J</a> project, and Maven for building the code.</p><h3>Generative AI text generation in Java with PaLM and LangChain4J</h3><p>In the first <a href="https://codelabs.developers.google.com/codelabs/genai-text-gen-java-palm-langchain4j?hl=en#0">codelab</a> you can explore:</p><ul><li>how to make your first call to PaLM for simple question/answer scenarios</li><li>how to extract structured data out of unstructured text</li><li>how to use prompts and prompt templates</li><li>how to classify text, with an example on sentiment analysis</li></ul><h3>Generative AI powered chat with users and docs in Java with PaLM and LangChain4J</h3><p>In the second <a href="https://codelabs.developers.google.com/codelabs/genai-chat-java-palm-langchain4j?hl=en#0">codelab</a> you’ll use the chat model to learn:</p><ul><li>how to create your first chat with the PaLM model</li><li>how to give your chatbot a personality, with an example with a chess player</li><li>how to extract structured data out of unstructured text using LangChain4J’s AiServices and its annotations</li><li>how to implement Retrieval Augmented Generation (RAG) to answer questions about your own documentation</li></ul><h3>Going further with Generative AI</h3><p>If you’re interested in going further with Generative AI, and learn more, feel free to <a href="https://goo.gle/generativeai">join the Google Cloud Innovators program</a>.</p><p>Google Cloud Innovators is <strong>free</strong> and includes:</p><ul><li>live discussions, AMAs, and roadmap sessions to learn the latest directly from Googlers,</li><li>the latest Google Cloud news right in your inbox,</li><li>digital badge and video conference background,</li><li>500 credits of labs and learning on Skills Boost.</li></ul><p><em>Originally published at </em><a href="https://glaforge.dev/posts/2023/12/18/get-hands-on-codelabs-to-dabble-with-llms/"><em>https://glaforge.dev</em></a><em> on December 18, 2023.</em></p><img src="https://medium.com/_/stat?event=post.clientViewed&referrerSource=full_rss&postId=ee7bc330f5fe" width="1" height="1" alt=""><hr><p><a href="https://medium.com/google-cloud/hands-on-codelabs-to-dabble-with-large-language-models-in-java-ee7bc330f5fe">Hands on Codelabs to dabble with Large Language Models in Java</a> was originally published in <a href="https://medium.com/google-cloud">Google Cloud - Community</a> on Medium, where people are continuing the conversation by highlighting and responding to this story.</p>

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title: Hands on Codelabs to dabble with Large Language Models in Java
url: https://medium.com/google-cloud/hands-on-codelabs-to-dabble-with-large-language-models-in-java-ee7bc330f5fe?source=rss-431147437aeb------2
author: Guillaume Laforge
categories:
- llm
- generative-ai
- java
- google-cloud-platform
- langchain
published: 2023-12-18 00:00:36.000000000 Z
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content: <figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/0*QAqyUui7Mp-t2o8U.png"
  /></figure><p>Hot on the heels of the <a href="https://glaforge.dev/posts/2023/12/13/get-started-with-gemini-in-java/">release
  of Gemini</a>, I’d like to share a couple of resources I created to get your hands
  on large language models, using <a href="https://github.com/langchain4j/">LangChain4J</a>,
  and the <a href="https://ai.google/discover/palm2/">PaLM 2</a> model. Later on,
  I’ll also share with you articles and codelabs that take advantage of Gemini, of course.</p><p>The
  PaLM 2 model supports 2 modes:</p><ul><li>text generation,</li><li>and chat.</li></ul><p>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.</p><p>You should be a Java developer, as the examples are in Java,
  use the <a href="https://github.com/langchain4j/">LangChain4J</a> project, and Maven
  for building the code.</p><h3>Generative AI text generation in Java with PaLM and
  LangChain4J</h3><p>In the first <a href="https://codelabs.developers.google.com/codelabs/genai-text-gen-java-palm-langchain4j?hl=en#0">codelab</a>
  you can explore:</p><ul><li>how to make your first call to PaLM for simple question/answer
  scenarios</li><li>how to extract structured data out of unstructured text</li><li>how
  to use prompts and prompt templates</li><li>how to classify text, with an example
  on sentiment analysis</li></ul><h3>Generative AI powered chat with users and docs
  in Java with PaLM and LangChain4J</h3><p>In the second <a href="https://codelabs.developers.google.com/codelabs/genai-chat-java-palm-langchain4j?hl=en#0">codelab</a>
  you’ll use the chat model to learn:</p><ul><li>how to create your first chat with
  the PaLM model</li><li>how to give your chatbot a personality, with an example with
  a chess player</li><li>how to extract structured data out of unstructured text using
  LangChain4J’s AiServices and its annotations</li><li>how to implement Retrieval
  Augmented Generation (RAG) to answer questions about your own documentation</li></ul><h3>Going
  further with Generative AI</h3><p>If you’re interested in going further with Generative
  AI, and learn more, feel free to <a href="https://goo.gle/generativeai">join the
  Google Cloud Innovators program</a>.</p><p>Google Cloud Innovators is <strong>free</strong>
  and includes:</p><ul><li>live discussions, AMAs, and roadmap sessions to learn the
  latest directly from Googlers,</li><li>the latest Google Cloud news right in your inbox,</li><li>digital
  badge and video conference background,</li><li>500 credits of labs and learning
  on Skills Boost.</li></ul><p><em>Originally published at </em><a href="https://glaforge.dev/posts/2023/12/18/get-hands-on-codelabs-to-dabble-with-llms/"><em>https://glaforge.dev</em></a><em>
  on December 18, 2023.</em></p><img src="https://medium.com/_/stat?event=post.clientViewed&referrerSource=full_rss&postId=ee7bc330f5fe"
  width="1" height="1" alt=""><hr><p><a href="https://medium.com/google-cloud/hands-on-codelabs-to-dabble-with-large-language-models-in-java-ee7bc330f5fe">Hands
  on Codelabs to dabble with Large Language Models in Java</a> was originally published
  in <a href="https://medium.com/google-cloud">Google Cloud - Community</a> on Medium,
  where people are continuing the conversation by highlighting and responding to this
  story.</p>

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