Web AI Examples

Note

This project is part of (and also associate to) the Project AIRI, we aim to build a LLM-driven VTuber like Neuro-sama (subscribe if you didn't!) if you are interested in, please do give it a try on live demo.

We experiment HuggingFace models and Transformers.js APIs here in WebAI examples repository, where it helped to grow our technologies inside of the Project AIRI primary repository. Things like:

• Real-time voice chat
• Real-time visual understanding
• Voice processing
• Video frames processing

were all born from here.

Development

pnpm i

pnpm dev

Other examples about AI / Model inference from Project AIRI

• WebAI Example Realtime Voice Chat: 🎤💬 Full example of implementing ChatGPT's realtime voice from scratch with VAD + STT + LLM + TTS technology stack within almost one file!
• 🤗 candle Examples: Examples of using 🤗 candle for inference AI models in Rust, you could think of it as an alternative and more transformers like library than [Burn Examples (this repository)].
• Burn Examples: Examples of using Burn.dev for inference AI models in Rust, you could think of it as an alternative and more advanced library than [🤗 candle Examples].

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.

%%{ init: { 'flowchart': { 'curve': 'catmullRom' } } }%%

flowchart TD
  subgraph deploy&bundle
    direction LR
    HFUP["hfup"]
    HF[/"HuggingFace Spaces"\]
    HFUP -...- UI -...-> HF
    HFUP -...- whisper-webgpu -...-> HF
    HFUP -...- moonshine-web -...-> HF
  end

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