Large Language Models in Modern Applications
Large Language Models (LLMs) play a pivotal role in modern business applications by significantly enhancing natural language understanding and generation capabilities. These LLM models enable more sophisticated interactions, allowing applications to comprehend user inputs, generate contextually relevant responses, and automate complex language-related tasks. Integrating LLMs into Java applications empowers developers to create more intelligent, user-friendly systems, fostering a seamless interaction between software and users. It opens avenues for enhanced language processing, enabling innovative solutions and improved user experiences in diverse domains.
This post will show how the Large Language Model can be customized to leverage the custom REST APIs to empower your AI Assistant.
LangChain for Java
If you are new to this topic, you can refer to the following nice articles to quickly get up to speed with the concepts:
Building a Simple AI-Powered Patient Appointment Scheduling System in Java
Please make sure you have the following tools installed:
- Scaffolding the project with Hilla CLI. (The initial setup is detailed in this dzone post)
- npx @hilla/cli init ai-assistant
-
<dependency>
<groupId>dev.langchain4j</groupId>
<artifactId>langchain4j</artifactId>
<version>${langchain.version}</version>
</dependency>
<dependency>
<groupId>dev.langchain4j</groupId>
<artifactId>langchain4j-open-ai</artifactId>
<version>${langchain.version}</version>
</dependency>
<dependency>
<groupId>dev.langchain4j</groupId>
<artifactId>langchain4j-embeddings-all-minilm-l6-v2</artifactId>
<version>${langchain.version}</version>
</dependency>
</dependencies>
- AssistantService: https://github.com/jobinesh/llm/blob/main/ai-assistant/src/main/java/com/jobinesh/ai/example/service/AssistantService.java
Patient Appointment Scheduling System in Action
Here is how the interaction looks like at runtime:
You can play around with this assistant and see how the prompt can be fines tuned for a better user experience
Source Code
Have fun!
