Build Generative AI App Jetpack Compose, Langchain4j &Ollama

Master Building Generative AI Apps with Jetpack Compose, Langchain4j, and Ollama (Local LLM) entirely in Kotlin.

Created byChetan Gupta

Last updated 7/2024

English

English [Auto],

What you'll learn

Develop AI powered application using Jetpack Compose
Integrate Langchain4j Application in Java or Kotlin System
Complete project based approach - End to End AI Application entirely in Kotlin
On device LLM running using Ollama
Build 6 AI application using Jetpack Compose, Langchain4j and Ollama using Kotlin
Use LangChain components to build complex text generation App
Build your own chat-with-a-PDF or chat-with-article application
How to use LangChain4j + Ollama to Build LLM-Powered Applications.
How to use Chroma-db with JVM based environment for Langchain4j
Creating Chains in Langchain4j and AI Service in Langchain4j

Course content

6 sections • 33 lectures • 1h 20m total length

Introduction : What to Expect? Kotlin, Compose, Langchain4j, Ollama!2:21
In this video, we'll outline what to expect from this course, focusing on our tech stack: Langchain4j for pipelines that interact with LLM, Ollama serves out LLM, Jetpack Compose for UI development, and Kotlin as the primary Programming Language. These tools combine to empower you to build advanced, AI-driven applications efficiently and effectively.
Prerequisite: Obtain Ollama and IntelliJ IDE – Essential Setup for Success0:27
Prerequisite: Obtain Ollama and IntelliJ IDE – While not covered in this course, you can install them by learning from YouTube tutorials. Ensure you have these tools ready to maximize your learning experience and effectively follow along with the course content focused on building AI-powered apps with Kotlin and Jetpack Compose.
Suggested Video for installing Ollama & IntelliJ0:10
Let's Begin with Hello: Building a Jetpack Compose Hello World Application1:42
In this lecture, we will build a 'Greeting' application using Jetpack Compose Desktop in Kotlin. We will learn to create a scaffold and implement the necessary components to 'Greet AI' in your application.
Setting Up Ollama Bindings with Langchain4j in Kotlin2:15
Learn to configure Ollama bindings with Langchain4j for Compose Desktop. This lecture guides you through setting up essential integrations, enabling seamless interaction between Ollama's and Langchain4j's within the Jetpack Compose environment in Kotlin
Integrating Langchain4j with Jetpack Compose Desktop: Bringing It All Together1:21
In this lecture, we will be merging powerful AI capabilities with modern UI design. Learn how to wire Langchain4j's AI model with Jetpack Compose Desktop in Kotlin, completing the greeting application

Exploring ChatMessages in Langchain4j1:20
In this lecture on exploring ChatMessages in Langchain4j, we delve into handling different message types such as chatMessage, systemMessage, and AI message. Learn how to effectively manage and manipulate text messages within your applications
Creating UI for Rephaser AI using Jetpack Compose Part 12:27
In this section, we'll construct the scaffold structure for the Rephaser AI using essential components like Box, Column, and TextFields in Jetpack Compose. Learn how to organize and integrate these elements effectively to create a functional user interface
Creating UI for Rephaser AI using Jetpack Compose Part 22:51
In this section, we'll expand on building the Rephaser AI by implementing click listeners and refining the user interface to the prototype stage.
Wiring AI Model with Rephaser UI - Chat Model + Prompt Template in Langchain4j2:22
In this lecture, we delve into integrating an AI model with the Rephaser UI, focusing on system messages, prompt templates, and wiring them seamlessly using Jetpack Compose. Learn how to handle system messages effectively within the UI structure, ensuring smooth communication and interaction flow for an enhanced user experience.
Enhanced Integration : Streaming Chat and Text Response Handling2:06
In this lecture, we advance the integration of the AI model with the Rephaser UI by focusing on streaming chat models and handling responses from streaming text inputs. Explore efficient methods to manage real-time interactions, ensuring seamless integration of dynamic AI capabilities into the user interface for responsive and engaging user experiences.

Unlost AI Jetpack Compose Desktop : Part 1 - Creating User List3:43
In this session, we initiate the creation of the Unlost AI user interface with a focus on setting up the foundational scaffold. Utilizing Jetpack Compose components, including Box, Column, and TextFields, we establish a structured layout that forms the basis for implementing AI-driven features aimed at enhancing user interaction and functionality.
Unlost AI Jetpack Compose Desktop: Part 2 – Chat History with Lazy Column3:38
In this lecture, we continue creating the UI for Unlost AI, focusing on developing a chat history interface using Lazy Column. Explore how to design an intuitive chat UI that displays interactions between the AI and user, optimizing performance with Lazy Column for seamless scrolling and content management.
Unlost AI Jetpack Compose Desktop: Part 3 – Adding ViewModel and Logic for Chat6:58
In this session, we focus on creating the UI for Unlost AI, emphasizing Part 3's crucial steps: setting up ViewModel, integrating stateflows, and implementing logic to manage user settings and message history in the chat interface. Discover how these components work together to enhance the functionality and responsiveness of the Unlost AI application.
Unlost AI Langchain4j : Part 1 - Adding Chat Model & Chat Memory Introduction2:26
In this session, we initiate the Unlost AI development with Part 1 focused on integrating Langchain4j. We begin by wiring the chat model, introducing chat memory functionalities essential for enhancing user interaction and data retention.
Unlost AI Langchain4j : Part 2 - Adding Chat Memory & Streaming Chat Model5:41
In this lecture, we advance the Unlost AI with Langchain4j, focusing on integrating chat memory functionality and transitioning to a streaming chat model. Explore how to effectively manage user interactions through persistent chat memory and enhance real-time communication using a dynamic streaming model, all integrated seamlessly for an optimized user experience.
Unlost AI Langchain4j: Part 3 - Persistent Chat Memory with MapDB4:39
In this session, explore advanced features of Unlost AI with Langchain4j, focusing on integrating persistent chat memory using MapDB. Learn to implement MapDB, create CRUD operations, and store chat memory persistently.
Unlost AI Langchain4j: Part 4 - Memory IDs for Chat Memory2:39
Explore advanced enhancements for Unlost AI using Langchain4j: Implement memory IDs for persistent chat memory, integrate loading states for seamless AI response handling, and incorporate random users for demo purposes.
Unlost AI Langchain4j: Part 5 - Adding User ids as Memory ID1:46
In this segment of Unlost AI with Langchain4j, we enhance the application by replacing hardcoded user identifiers with dynamic user IDs as memory IDs. Explore how to manage profile switching seamlessly, ensuring efficient data association and retrieval for a personalized user experience

Introduction to Chains: Conversational Chains and Text Adventure AI0:26
In this lecture, delve into Langchain's foundational elements, focusing on conversational chains. Discover how these chains drive interactive experiences in Text Adventure AI, enabling dynamic storytelling and responsive interactions based on user inputs and contextual cues
Text Adventure AI Jetpack Compose Desktop : Setting up scaffold2:17
Prepare for Text Adventure AI on Jetpack Compose Desktop by establishing a foundational scaffold. Learn how to structure your project effectively using Jetpack Compose, ensuring a robust framework for developing dynamic, text-based adventure games enhanced with AI capabilities.
Text Adventure AI with Langchain4j: Conversational Chains3:30
In this lecture on Text Adventure AI with Langchain4j, we focus on integrating AI by adding conversational chains. Explore how to incorporate system messages and implement chat memory, enhancing user interaction and creating dynamic storytelling experiences in your text-based adventure game.
Fixing Text Adventure AI Bug: System Message Update0:47
In this lecture on Text Adventure AI with Langchain4j, we address a bug by updating the system message handling, thereby resolving the issue preventing the game from starting.

Introduction to Langchain4j Conversational AI and ResumeQnA Application1:44
Introduction to Conversational-Retrieval-Chains, Embedding Models, Embedding Stores, Document Parsing, and Loading in this lecture. Learn to build ResumeQnA.ai, an AI application that summarizes resumes and retrieves candidate information through interactive queries, leveraging advanced conversational AI techniques for efficient data retrieval and user interaction
ResumeQnA UI: Jetpack Compose Desktop - Setting Up Scaffold1:48
In this lecture, we focus on setting up the user interface for ResumeQnA using Jetpack Compose Desktop. We'll configure a chat-like UI structure similar to our previous applications.
ResumeQnA Langchain4j : Conversational Retrieval Chain & Document Parsing4:49
In this lecture on ResumeQnA with Langchain4j, we integrate a conversational retrieval chain, Apache Tika document parser, and an in-memory embedding model store.
ResumeQnA Langchain4j: Document Ingestion & App Demo1:15
In this lecture on ResumeQnA with Langchain4j, we'll set up the document ingestion flow and demonstrate the app by querying content from resumes.
Installing Docker for Testcontainer0:16
ResumeQnA Langchain4j : Integrating Chroma DB for Persistent Embedding Store2:44
In this lecture on ResumeQnA with Langchain4j, we integrate Chroma DB to establish a persistent embedding store. Explore how this enhancement ensures efficient storage and retrieval of candidate embedding data.

Langchain4j : Introduction to AI Service and RAG App0:55
In this lecture, we will explore Langchain4j's approach to chain implementation and AI Service Components, the application introduction of RAG Medium Articles. Build a simple Retrieval-Augmented Generation (RAG) app that summarizes Medium articles and supports Q&A functionalities, highlighting practical AI integration and its benefits in content retrieval and interaction.
RAG Medium Jetpack Compose Desktop : Setting up scaffold2:19
In this session, we focus on setting up the scaffold for RAG Medium using Jetpack Compose Desktop. Learn to create a chat-like UI similar to previous applications, enhancing user interaction and experience in navigating and interacting with Retrieval-Augmented Generation (RAG) capabilities for Medium articles.
RAG Medium Langchain4j : AI Service with simple chat and streaming2:48
Explore integrating RAG AI services with Langchain4j, showcasing practical examples of chat interactions and real-time streaming. Learn how to implement and optimize AI-driven content retrieval and dynamic communication, demonstrating the capabilities of Retrieval-Augmented Generation in enhancing user engagement and information access.
RAG Medium Langchain4j : Jsoup for Website Parsing3:43
Learn to integrate Jsoup with RAG Medium Langchain4j to parse website content for Q&A capabilities. Discover how this integration enhances the app's ability to retrieve and process information from external sources, making it a versatile tool for interactive content summarization and query answering.

Requirements

Understand Kotlin Programming Language
Beginner level experience with Jetpack Compose

Description

Discover the power of building AI-powered applications entirely in Kotlin with our comprehensive course on Jetpack Compose, Langchain4j, and Ollama (Local LLM).

Whether you're a seasoned developer or a newcomer, this course equips you with the skills to harness these cutting-edge technologies and stay relevant in this AI driven industry.

Throughout the course, we focus on practical hands-on learning, guiding you through the creation of six distinct applications leveraging Langchain4j:

Hello World AI: Create an AI that greets users dynamically.
Rephaser AI: Transform sentences into various tones for easy clipboard use.
Unlost AI: Develop an AI to help users remember where they've placed their belongings.
Text Adventure AI: Construct interactive storytelling experiences using AI.
ResumeQnA AI: Utilize AI to summarize resumes and retrieve candidate information interactively.
RAG Medium Articles AI: Build a Retrieval-Augmented Generation (RAG) AI for summarizing and querying public Medium articles.

You'll gain proficiency in Jetpack Compose for designing modern, responsive UIs and harness Langchain4j and Ollama for AI model management and natural language processing tasks. Learn essential Kotlin programming techniques to seamlessly integrate these technologies and optimize performance on local platforms.

Join us to unlock the potential of Kotlin-based AI app development with practical skills and real-world applications in demand today.

Who this course is for:

Kotlin Developers Looking to Upskill : Developers proficient in Kotlin who want to expand their skills into AI and app development with new tools and frameworks.
Mobile App Developers : Experienced developers looking to enhance their skill set by incorporating generative AI into their Kotlin-based mobile applications.
AI Enthusiasts and Hobbyists : Individuals passionate about artificial intelligence who want to experiment with building AI-powered applications with Kotlin Programming Language
Software Engineers Exploring AI Integration : Engineers with a background in software development who are interested in applying generative AI to enhance existing applications.

Build Generative AI App Jetpack Compose, Langchain4j &Ollama

What you'll learn

Explore related topics

Course content

Hello World AI: Kickstarting Your Jetpack Compose Desktop Project6 lectures • 8min

Rephaser AI : Convert a Sentence into Multiple Tones for Clipboard use5 lectures • 11min

Unlost AI : Your Memory AI Companion for Remembering Item Locations8 lectures • 32min

Text Adventure AI: Create Interactive Stories with AI4 lectures • 7min

ResumeQnA AI: Summarizing Resume and Retrieving Candidate Info through Interact6 lectures • 13min

Simple Retrieval-Augmented Generation (RAG) Medium Articles AI4 lectures • 10min

Requirements

Description

Who this course is for: