One AI - Name TBD, this is just the shortest name I could think of. Also, user beware, this project is scuffed. Very early WIP.

INSTALLATION:

1. Install and configure dependencies. On Arch Linux, run the following:

   # Install dependencies
   sudo pacman -S ollama go cloudflared docker
   yay -S flutter-bin
   
   # Configure ollama
   ollama pull llama3
   #ollama pull qwen:0.5b # Use this if hosting on older hardware.
   
   # Configure cloudflared
   cloudflared tunnel login
   
   # Configure Docker
   systemctl start docker
   #systemctl enable docker
   
   

2. Run the installation script. This will create, configure, and start the Cloudflare Tunnel via cloudflared and create the initial configuration file for One AI;

3. Start the server via Docker or plain Golang: a) Go to ./backend/src/security-layer/ and run ./init.

   b) Go to ./backend/src/security-layer/container and run go run router.go.

   By default, this will expose 4 ports: the router at port 1111, the API on 1112, Auth/Session Management on 1113, and a static webpage on 1114. The ports and webpage directory are configurable through ~/.config/one-ai/test.json.

CONFIGURATION:

The primary configuration file is located at ~/.config/one-ai/. It is recommended to keep two files, test.json and live.json. This is purely for security purposes.

The following are configurable parameters:
- text_model: Specify the LLM used through Ollama, eg. "llama3".
- response_stream: true or false, to receive communication as it is generated or once it is completed generating.
- domain: The URL to be used to access the router.
- router_port: The port to be exposed to the internet.
- api: The URL to be used to access the One AI API.
- api_port: A port to be only accessible to the localhost.
- auth_port: A port to be only accessible to the localhost.
- webpage_dir: The directory containing a website.
- webpage_port: The port to expose the webpage directory to the internet.

TODO: Urgent:

• Basic Documentation

• Installation/setup script

  • AES-256 Private and Public key handshake via USB.
  • Cloudflare Tunnel setup via cloudflared
  • Daemonize service

• Encryption

  • SHA-1 hash API request/response
  • Encrypt API request
  • Encrypt API response

• Dockerize backend

  • Broke Dockerfile, need to expose additional ports.
  • Dynamically expose ports based on primary configuration file.

• Golang backend, connect to other services/projects

  • Port 8080 -> self-hosted portfolio
  • Port 8081 -> self-hosted AI API
  • Encryption
  • User authentication via JWT

• Refactor

• Testing

• Connect Flutter Web App to server

Later:

• Raspberry Pi nightly package

• Image support via llava

  • Encode images to Base64 in frontend
  • Redirect prompts to appropriate model.
  • Image generation via llava, encode to Base64

• GUI in Flutter

  • Conversations list
  • Conversation view
  • Settings
  • File picker
  • Image picker
  • Camera
  • On-device Speech to Text
  • On-device Text to Speech

router.go:

• Allow for additional fields for the client.
• Add preprocessing based upon filetypes.
• Add support for dynamically changing models.
• Actually make text streaming a toggleable setting.
• Authentication via JWT.
• Get config via CLI argument or environment variable.
• Add --test CLI argument when testing solely on localhost.
• Error handling, testing, & documentation.

authentication.go:

• 32 bit key generation & storage between server and client
• Add testing flag
• Error handling, testing, & documentation.

serveAPI.go:

• Error handling, testing, & documentation.

servePage.go:

• Error handling, testing, & documentation.

Much Later:

• Document support via OmniParser

  • Encode files to Base64 to/from backend.
  • Connect to external services like Google Drive

• Context support

  • Access self-hosted or cloud calendar
  • Access self-hosted or cloud todo
  • Access self-hosted or cloud notes/docs
  • Access self-hosted or cloud photos/videos

• User settings

  • Especially conversation history.
  • Choose default models
  • Connect to external API services

• Convert API from REST to WebSocket architecture.

  • NOTE: This is to allow for the text streaming effect, but also audio, video, and for reducing bandwidth.

• Backend Speech-To-Text and Text-To-Speech

  • NOTE: This is primarily due to the lack of native API's on Windows, MacOS, and Linux.

• Update physical backend server to NixOS.

Way later:

• External hardware integration -> see personal notes

This project has been built, structured, architected, etc. in conjunction with AI, specifically the llama3 and qwen2 models.