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Magic 8 Ball

This project is an AI-powered Magic 8 Ball web application. The backend is built using FastAPI and the frontend is built using React. The application utilizes a language model, specifically Phi-3-mini-4k-instruct from Ollama, to generate Magic 8 Ball-style responses.

Features

  • Ask the AI-powered Magic 8 Ball any question, and it responds with short, cryptic answers.
  • Uses Ollama's Phi3 model to generate responses.
  • Simple UI to input questions and receive AI-generated responses in real-time.

Architecture

  • Frontend: Built using React and styled with Tailwind CSS.
  • Backend: Built using FastAPI, handles API request and communicates with the AI model.
  • AI Model: The model is served locally using Ollama, and integrated with the backend for generating responses.

Local Setup

Docker Setup

Ensure Docker and Docker Compose are installed on your machine.

Steps

  1. Build the Containers:

    To build both the backend and frontend services along with Ollama, use the following command:

    docker-compose build

  2. Start the Containers:

    To run both the backend and frontend services along with Ollama, use the following command:

    docker-compose up

Start Ollama

  1. Start Ollama Server: 
    ollama serve
  2. Run model: If you don't have the model in local it will automatically first pull the model and then run it. 
    ollama run phi3

Start Backend:

  1. Clone the repository:

    git clone https://github.com/yourusername/Magic8-Ball.git
cd Magic8-Ball/backend

  2. Create a virtual environment and install dependencies:

    python -m venv venv
source venv/bin/activate  # On Windows use: venv\Scripts\activate
pip install -r requirements.txt

  3. Run the FastAPI server:

    cd .\src\
uvicorn app.main:app --reload

  4. Test the API: Open your browser and go to http://127.0.0.1:8000/docs to view the automatically generated API documentation.

Start Frontend:

  1. Navigate to Frontend:

    cd Magic8-Ball/frontend

  2. Create a virtual environment and install dependencies:

    npm i

  3. Run the Frontend:

    npm run dev