localAIUI

This project is a web-based application that allows users to interact with locally installed Ollama models and also use LangChain to interface with Ollama llms. The application consists of a frontend built with Vue.js and a backend built with Flask. The backend interacts with AI models and provides responses to user queries.

Prerequisites

• Docker Desktop
• Ollama installed locally
• LLM models available in Ollama

Setup

Step 1: Clone the Repository

git clone <repository-url>
cd <repository-directory>

Step 2: Build and Run the Application with Docker Compose

docker-compose up --build

This command will build and start the following services:

• ollama: The backend service for handling AI queries.
• frontend: The frontend service for the web application.

Step 3: Access the Application

Open your web browser and navigate to http://localhost:3000 to access the Ollama AI Assistant.

Usage

1. Select an AI model from the dropdown menu.
2. Choose the query type (LangChain or Direct LLM).
3. Type your message in the input box and press Send.
4. The AI response will be displayed in the chat window.

Dockerfile and Docker Compose

The project includes Dockerfiles for both the frontend and backend services, as well as a docker-compose.yml file to orchestrate the services.

Frontend Dockerfile

The frontend/Dockerfile builds the Vue.js application and serves it using Nginx.

Backend Dockerfile

The ollama/Dockerfile sets up the Flask application and installs the necessary dependencies.

Docker Compose

The docker-compose.yml file defines the services and their configurations, including ports, volumes, and environment variables.

License

This project is licensed under the MIT License. See the LICENSE file for more details.