Fullstack AI Chat Application

Overview

This project is a fullstack AI chat application that integrates a backend powered by Spring AI with the Ollama model and a frontend developed using the Hilla framework. Both the frontend and backend are hosted on the same server, providing a unified and seamless user experience.

Features

• AI-Powered Chat: Uses the Ollama model via Spring AI to deliver intelligent and context-aware chat responses.
• Integrated Frontend and Backend: Built with the Hilla framework, ensuring a cohesive application where both components operate on the same server.
• Responsive Interface: Offers an interactive and modern chat experience within the web application.

Technologies

• Java 17: The application is developed using Java 17.
• Spring AI: Framework for integrating AI models into Java applications.
• Ollama Model: Advanced AI model for generating chat responses.
• Hilla Framework: Combines Vaadin and Spring Boot for a unified fullstack solution.
• Docker Compose: Used for managing and running the Ollama container.

Getting Started

Prerequisites

• JDK 17
• Maven
• Docker and Docker Compose

Installation

1. Clone the Repository:

   git clone https://github.com/abbes-larbaoui/llm-spring-hilla.git
   cd llm-spring-hilla

2. Run the Docker Compose File:

   • Navigate to the directory containing the docker-compose.yml file.
   • Start the Ollama container:

    docker-compose up -d

3. Run the Llama2 Model:

   • Start the Llama2 model within the Ollama container using::

    docker exec -it ollama ollama run llama2

4. Build and Run the Application:

   • Navigate to the project root directory.
   • Install dependencies and build the application with Maven:

    mvn clean install

   • Run the Spring Boot application, which will start both the backend and frontend:

    mvn spring-boot:run

5. Access the Application:

   • Open your web browser and go to http://localhost:8080 to interact with the chat application.

Usage

• Chat Interface: Use the integrated chat interface to interact with the AI model.
• Configuration: Modify AI model parameters and other settings in the src/main/resources/application.yml file.