AInterior

A team project developed for our engineering thesis. The application focuses on helping interior architects to use artificial intelligence models in their work.

Features

• Many Stable Diffusion model versions to choose from
• Available workflows:
  • Text-to-image
  • Image-to-image
  • ControlNet
  • Inpainting
  • Outpainting
  • Canvas
• User accounts system with gallery, to store all created pictures, and administrator panel
• Many features to support architects:
  • Visual Prompting - visual representation of text prompts
  • Advanced parameter selection sheet
  • Easy switching between workflows
  • Prompt writing tutorial

Techstack

• Backend: Python + FastAPI
• Frontend: React + Tailwind CSS
• Database: MongoDB
• Image generation: Stable Diffusion, Hugging Face API, Civit AI API, Comfy UI
• Containerization: Docker

How to deploy

It is recommended to run this application on either native or wsl Ubuntu LTS 24.04.

Hardware requirements

• RAM: 32 GB or more
• GPU: NVIDIA RTX 2080 8GB / NVIDIA RTX 4060 8GB or better
• Storage: 1TB free disk space or more

Preparation

1. Install docker with this instructions https://docs.docker.com/engine/install/ubuntu/ (In case of buildix issue: https://forums.docker.com/t/tips-for-how-to-fix-my-borked-cli-plugins/144327/3)

2. Install NVIDIA Container Toolkit
   a. Add NVIDIA GPG key and repository

    curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | \
    sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
    curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
    sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
    sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
   

   b. Update package list

    sudo apt-get update
   

   c. Install the toolkit

    sudo apt-get install -y nvidia-container-toolkit
   

   d. Configure the runtime

    sudo nvidia-ctk runtime configure --runtime=docker
    sudo systemctl restart docker
    sudo nvidia-ctk runtime configure --runtime=containerd
    sudo systemctl restart containerd
   

3. Generate read only api token on https://huggingface.co/settings/tokens.

4. Generate api token on https://civitai.com/user/account.

5. In main directory create api_keys.env file with following contents:

   HF_TOKEN=<hf_api_token>
   CIVITAI_TOKEN=<civitai_api_token>
   

6. Run sudo ./download_models.shto download all the models (This needs to be run only once)

7. Build & run (Use after making changes to the docker related files or when installing new packages/modules) FIRST RUN WILL TAKE A LONG TIME!!!:

   • Developement mode: docker compose down && docker compose up --build
     or
   • Production mode: docker compose down && docker compose -f docker-compose-production.yml up --build -d

8. Run:

   • Developement mode: docker compose down && docker compose up
     or
   • Production mode:docker compose down && docker compose -f docker-compose-production.yml up -d

How to forward frontend via ssh (For AGH University of Krakow users):

1. ssh -L 80:localhost:80 -J <login_bastion>@bastion.ii.agh.edu.pl <login_pc>@<ip_pc>

How to run tests

1. cd frontend
2. sudo apt install npm
3. npm run test:ui or npm run test