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    Spring Ai For Beginners : Build Genai Llm Apps In Easy Steps

    Posted By: ELK1nG
    Spring Ai For Beginners : Build Genai Llm Apps In Easy Steps

    Spring Ai For Beginners : Build Genai Llm Apps In Easy Steps
    Published 11/2024
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 1.68 GB | Duration: 3h 22m

    A Step-by-Step Guide to Master Spring AI

    What you'll learn

    Learn what Spring AI is how it simplifies using LLMs in our applications

    Use OpenAI LLMS in a Spring Boot application

    Use Open Source LLMS like Mistral,Gemma in a Spring Boot application

    Run Open Source LLMs on your local machine using OLLAMA

    Use PromptTemplates to reuse and build dynamic prompts

    Learn why and how to maintain Chat History

    Learn what embeddings are and use the Embeddings Model to find text Similarity

    Understand what a Vector Store is and use it to store and retrieve Embeddings

    Understand the process of Retrieval Augmented Generation(RAG)

    Implement (RAG) to use our own data with LLMs in simple steps

    Analyze images using Multi Modal Models

    Build multiple LLM APPs using ThymeLeaf and Spring AI

    Master Function Calling and Text Moderations

    All in simple steps

    Requirements

    Knowledge of Spring Boot and Java

    OpenAI Account to work with OpenAI LLMs

    Description

    Welcome to Spring AI for Beginners!This course is designed to provide a gentle, step-by-step introduction to Spring AI, guiding youfrom the basics to more advanced concepts. Whether you're a complete novice or have someexperience with AI, this course will help you understand and leverage the power of Spring AI forbuilding AI-powered applications.Course Goals:- Gradual Learning: Learn Spring AI gradually from basic to advanced topics with clear andconcise instructions.- Comprehensive Understanding: Understand why Spring AI is a powerful tool for building AIapplications and how it simplifies the integration of language models into your projects.- Hands-On Experience: Gain practical experience with essential Spring AI features such asprompt templates, chains, agents, document loaders, output parsers, and model classes.What You Will Learn:- Introduction to Spring AI: Get started with the basics of Spring AI and understand its coreconcepts.- Building Blocks of Spring AI: Learn about prompt templates, chains, agents, document loaders,output parsers, and model classes.- Creating AI Applications: See how these features come together to create a smart and flexible- Practical Coding: Write and run code examples to get a hands-on sense of how Spring AIdevelopment looks like.Course Structure:- Concise Chapters: Each chapter focuses on a specific topic in Spring AI programming,ensuring you gain a deep understanding of each concept.- Interactive Learning: Code along with the examples provided to reinforce your learning and buildyour skills.By the end of this course, you will:Learn what Spring AI is how it simplifies  using LLMs in our applicationsUse OpenAI LLMs in a Spring Boot applicationUse Open Source LLMs like Mistral,Gemma in a Spring Boot applicationRun Open Source LLMs on your local machine using OLLAMAUse PromptTemplates to reuse and build dynamic prompts Learn why and how to maintain Chat HistoryLearn what embeddings are and use the Embeddings Model to find text SimilarityUnderstand what a Vector Store is and use it to store and retrieve EmbeddingsUnderstand the process of Retrieval Augmented Generation(RAG) Implement  (RAG) to use our own data with LLMs in simple stepsAnalyze images using Multi Modal ModelsBuild multiple LLM APPs using Thymeleaf and Spring AIAll in simple steps

    Overview

    Section 1: Introduction

    Lecture 1 Introduction

    Lecture 2 Private Course Feedback Link

    Lecture 3 Download Completed Projects

    Lecture 4 Download Prompts Document

    Section 2: The Fundamentals

    Lecture 5 What is GenAI

    Lecture 6 What is OpenAI

    Lecture 7 Other LLMs

    Lecture 8 What is Spring AI

    Lecture 9 Spring AI Documentation

    Section 3: Software Setup

    Lecture 10 Setup OpenAI Account

    Lecture 11 Setup API Key

    Lecture 12 OpenAI Playground in action

    Lecture 13 Driving models behaviour with options

    Lecture 14 Setup Open Source LLMs

    Section 4: Spring AI in Action

    Lecture 15 Setup Project

    Lecture 16 Generic vs Specific Classes

    Lecture 17 Spring AI in action

    Lecture 18 Do LLMs have memory?

    Lecture 19 Advisors

    Lecture 20 Configure Memory for Chat

    Lecture 21 Configure ChatOptions

    Lecture 22 Use Open Source Models Locally

    Section 5: Prompt Templates

    Lecture 23 Introduction

    Lecture 24 Create a Travel Guide App

    Lecture 25 Create a Cuisine Helper

    Lecture 26 Improve the prompt

    Section 6: Embeddings

    Lecture 27 Introduction

    Lecture 28 Using the Embeddings Model

    Lecture 29 Similarity Finder

    Section 7: Vector Stores

    Lecture 30 Introduction

    Lecture 31 Update Project

    Lecture 32 Code Walk Through

    Lecture 33 TokenTextSplitter

    Lecture 34 Setup ChromaDB

    Lecture 35 Load Data in to Vector Store

    Lecture 36 Implement Job Search Helper

    Lecture 37 More Search Options

    Section 8: RAG - Working With Documents

    Lecture 38 What is RAG

    Lecture 39 UseCase and Code Walkthrough

    Lecture 40 Implement RAG Part 1

    Lecture 41 Implement RAG Part 2

    Lecture 42 Test

    Section 9: Image Processing

    Lecture 43 Introduction

    Lecture 44 Generate a Image

    Lecture 45 Image Analysis Introduction

    Lecture 46 Create Image Analyzer App Part 1

    Lecture 47 Create Image Analyzer App Part 2

    Lecture 48 Test

    Lecture 49 Few More Usecases

    Lecture 50 Create a Diet Helper App

    Section 10: Audio

    Lecture 51 Introduction

    Lecture 52 Speech To Text

    Lecture 53 Set more options

    Lecture 54 Text To Speech

    Section 11: Function Calling

    Lecture 55 Introduction

    Lecture 56 Create the function

    Lecture 57 Configure the bean

    Lecture 58 Create Service Method

    Lecture 59 Test

    Section 12: Moderations

    Lecture 60 Introduction

    Lecture 61 Moderate Text

    Java Developers who want to use Spring AI to build GenAI LLM applications,Any student who has completed my Spring Boot Courses