156 lines
5.0 KiB
Markdown
156 lines
5.0 KiB
Markdown
One AI - Name TBD, this is just the shortest name I could think of.
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Also, user beware, this project is scuffed. Very early WIP.
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INSTALLATION:
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1. Install and configure dependencies. On Arch Linux, run the following:
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```
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# Install dependencies
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sudo pacman -S ollama go cloudflared docker
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yay -S flutter-bin
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# Configure ollama
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ollama pull llama3
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#ollama pull qwen:0.5b # Use this if hosting on older hardware.
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# Configure cloudflared
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cloudflared tunnel login
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# Configure Docker
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systemctl start docker
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#systemctl enable docker
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```
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2. Run the installation script. This will create, configure, and start the
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Cloudflare Tunnel via cloudflared and create the initial configuration
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file for One AI;
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3. Start the server via Docker or plain Golang:
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a) Go to ./backend/src/security-layer/ and run `./init`.
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b) Go to ./backend/src/security-layer/container and run `go run router.go`.
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By default, this will expose 4 ports: the router at port 1111, the API on
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1112, Auth/Session Management on 1113, and a static webpage on 1114. The
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ports and webpage directory are configurable through
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`~/.config/one-ai/test.json`.
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CONFIGURATION:
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The primary configuration file is located at `~/.config/one-ai/`. It is
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recommended to keep two files, `test.json` and `live.json`. This is purely
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for security purposes.
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The following are configurable parameters:
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- `text_model`: Specify the LLM used through Ollama, eg. "llama3".
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- `response_stream`: `true` or `false`, to receive communication as it is
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generated or once it is completed generating.
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- `domain`: The URL to be used to access the router.
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- `router_port`: The port to be exposed to the internet.
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- `api`: The URL to be used to access the One AI API.
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- `api_port`: A port to be only accessible to the localhost.
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- `auth_port`: A port to be only accessible to the localhost.
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- `webpage_dir`: The directory containing a website.
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- `webpage_port`: The port to expose the webpage directory to the internet.
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TODO:
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- [x] Basic Documentation
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- [x] Installation/setup script
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- [ ] AES-256 Private and Public key handshake via USB.
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- [x] Cloudflare Tunnel setup via cloudflared
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- [ ] Daemonize service
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- [x] Encryption
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- [x] SHA-1 hash API request/response
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- [x] Encrypt API request
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- [x] Encrypt API response
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- [x] Dockerize backend
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- [x] Broke Dockerfile, need to expose additional ports.
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- [ ] Dynamically expose ports based on primary configuration file.
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- [ ] Golang backend, connect to other services/projects
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- [x] Port 8080 -> self-hosted portfolio
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- [x] Port 8081 -> self-hosted AI API
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- [x] Encryption
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- [ ] User authentication via JWT
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- [ ] Refactor
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- [ ] Testing
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- [ ] Connect Flutter Web App to server
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Later:
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- [ ] Raspberry Pi nightly package
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- [ ] Image support via llava
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- [x] Encode images to Base64 in frontend
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- [ ] Redirect prompts to appropriate model.
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- [ ] Image generation via llava, encode to Base64
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- [ ] GUI in Flutter
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- [x] Conversations list
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- [x] Conversation view
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- [ ] Settings
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- [x] File picker
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- [x] Image picker
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- [x] Camera
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- [x] On-device Speech to Text
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- [x] On-device Text to Speech
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router.go:
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- [ ] Allow for additional fields for the client.
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- [ ] Add preprocessing based upon filetypes.
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- [ ] Add support for dynamically changing models.
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- [ ] Actually make text streaming a toggleable setting.
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- [ ] Authentication via JWT.
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- [ ] Get config via CLI argument or environment variable.
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- [ ] Add --test CLI argument when testing solely on localhost.
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- [ ] Error handling, testing, & documentation.
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authentication.go:
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- [ ] 32 bit key generation & storage between server and client
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- [ ] Add testing flag
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- [ ] Error handling, testing, & documentation.
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serveAPI.go:
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- [ ] Error handling, testing, & documentation.
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servePage.go:
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- [ ] Error handling, testing, & documentation.
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Much Later:
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- [ ] Document support via OmniParser
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- [ ] Encode files to Base64 to/from backend.
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- [ ] Connect to external services like Google Drive
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- [ ] Context support
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- [ ] Access self-hosted or cloud calendar
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- [ ] Access self-hosted or cloud todo
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- [ ] Access self-hosted or cloud notes/docs
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- [ ] Access self-hosted or cloud photos/videos
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- [ ] User settings
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- [ ] Especially conversation history.
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- [ ] Choose default models
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- [ ] Connect to external API services
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- [ ] Convert API from REST to WebSocket architecture.
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- NOTE: This is to allow for the text streaming effect,
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but also audio, video, and for reducing bandwidth.
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- [ ] Backend Speech-To-Text and Text-To-Speech
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- NOTE: This is primarily due to the lack of native
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API's on Windows, MacOS, and Linux.
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- [ ] Update physical backend server to NixOS.
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Way later:
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- [ ] External hardware integration -> see personal notes
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This project has been built, structured, architected, etc. in conjunction
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with AI, specifically the llama3 and qwen2 models.
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