Overview of LangChain4j Getting Started Guide

LangChain4j is a framework designed to help developers build applications powered by language models. This guide provides a step-by-step introduction to get you started with using LangChain4j effectively.

Key Concepts

• Language Models: These are AI models capable of understanding and generating human-like text. LangChain4j leverages these to create intelligent applications.
• Chains: A core concept in LangChain4j, chains are sequences of operations that process input and produce output. They can include various tasks such as querying a database, invoking APIs, or generating text.
• Agents: These are entities that can perform actions based on user input. Agents can use language models to decide which actions to take in response to a query.
• Memory: LangChain4j supports state management, allowing applications to remember past interactions and provide contextually relevant responses.

Getting Started

Installation

To begin using LangChain4j, you need to install it in your development environment. You can typically do this with a package manager like Maven or Gradle in Java.

<dependency>
    <groupId>com.langchain4j</groupId>
    <artifactId>langchain4j-core</artifactId>
    <version>1.0.0</version>
</dependency>

Creating Your First Chain

Run the Chain: Execute the chain with a sample input.

String result = greetingChain.run("World");
System.out.println(result); // Output: Hello, World!

Define a Chain: You can create a simple chain that takes user input and processes it.

Chain<String, String> greetingChain = new SimpleChain<>(input -> "Hello, " + input + "!");

Implementing Agents

Create an Agent: An agent can be set up to handle user queries and decide on the best action to take.

Agent agent = new SimpleAgent();
agent.registerAction("greet", (input) -> "Hello, " + input + "!");
String response = agent.act("greet", "Alice");
System.out.println(response); // Output: Hello, Alice!

Conclusion

LangChain4j provides a powerful framework for developing applications that utilize language models effectively. By understanding chains, agents, and memory, you can create intelligent applications that respond to user input in meaningful ways.

Next Steps

• Explore more advanced features like integrating external APIs, using advanced memory techniques, and customizing chains for complex workflows.
• Check the official documentation for in-depth tutorials and examples.