@proj-airi/unplugin-fetch

@proj-airi/unplugin-download

Helper plugin for helping installing the remote assets into public dir.

Installation

Pick the package manager of your choice:

ni @proj-airi/lobe-icons -D # from @antfu/ni, can be installed via `npm i -g @antfu/ni`
pnpm i @proj-airi/unplugin-download -D
yarn i @proj-airi/unplugin-download -D
npm i @proj-airi/unplugin-download -D

UnoCSS usage

import { Download } from '@proj-airi/unplugin-download/vite'
import { defineConfig } from 'vite'

export default defineConfig({
  plugins: [
    Download('https://dist.ayaka.moe/live2d-models/hiyori_free_zh.zip', 'hiyori_free_zh.zip', 'assets/live2d/models'),
    Download('https://dist.ayaka.moe/live2d-models/hiyori_pro_zh.zip', 'hiyori_pro_zh.zip', 'assets/live2d/models'),
  ]
})

Other side projects born from Project AIRI

• Awesome AI VTuber: A curated list of AI VTubers and related projects
• unspeech: Universal endpoint proxy server for /audio/transcriptions and /audio/speech, like LiteLLM but for any ASR and TTS
• hfup: tools to help on deploying, bundling to HuggingFace Spaces
• xsai-transformers: Experimental 🤗 Transformers.js provider for xsAI.
• WebAI: Realtime Voice Chat: Full example of implementing ChatGPT's realtime voice from scratch with VAD + STT + LLM + TTS.
• @proj-airi/drizzle-duckdb-wasm: Drizzle ORM driver for DuckDB WASM
• @proj-airi/duckdb-wasm: Easy to use wrapper for @duckdb/duckdb-wasm
• Airi Factorio: Allow Airi to play Factorio
• Factorio RCON API: RESTful API wrapper for Factorio headless server console
• autorio: Factorio automation library
• tstl-plugin-reload-factorio-mod: Reload Factorio mod when developing
• Velin: Use Vue SFC and Markdown to write easy to manage stateful prompts for LLM
• demodel: Easily boost the speed of pulling your models and datasets from various of inference runtimes.
• inventory: Centralized model catalog and default provider configurations backend service
• MCP Launcher: Easy to use MCP builder & launcher for all possible MCP servers, just like Ollama for models!
• 🥺 SAD: Documentation and notes for self-host and browser running LLMs.