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CodeSignal

LangChain Chat Essentials in Java

via CodeSignal

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Overview

Embark on a journey into conversational AI with LangChain in Java. This course equips you with the skills to build sophisticated chat applications, starting with basic message exchanges and advancing to complex conversation management. Discover how to tailor AI responses, laying a strong foundation for innovative natural language processing endeavors.

Syllabus

  • Unit 1: Introduction to Java and Large Language Models
    • Customize AI Prompts with LangChain
    • Fixing a Prompting Bug
    • Building a Complete LangChain4j Script for OpenAI Communication
    • Converting a LangChain4j Chatbot from OpenAI to Anthropic Claude
  • Unit 2: Customizing Model Parameters in Java
    • Selecting the GPT-4o-Mini Model
    • Controlling AI Response Length with maxTokens Parameter
    • Adding Temperature Parameter to Control AI Response Creativity
    • Implementing Nucleus Sampling with the topP Parameter
    • Reducing Repetition with OpenAI's Frequency Penalty Parameter
    • Implementing Presence Penalty for Diverse AI Responses
  • Unit 3: Structuring AI Conversations in Java with System and User Messages
    • Accessing UserMessage Properties in LangChain
    • Creating SystemMessage Objects in LangChain
    • Fixing Message Handling in LangChain Chat Models
    • Using UserMessage Objects
    • Transforming AI Responses with SystemMessage
    • Adding Constraints to a Math Assistant System Prompt
  • Unit 4: Managing Conversation History with Java for AI Models
    • Creating a Travel Assistant Conversation with LangChain
    • Building a Multi-Turn Conversation with Message History
    • Building a Reusable Conversation Function for a Travel Assistant
    • Implementing a Conversation Reset Function in LangChain4j
    • Implementing Multiple Conversation Management with HashMap in Java

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