Project AIRI Web AI Realtime Voice Chat Demo

Note

If you don't know what Project AIRI is, here's the introduction:

Project AIRI aimed to build the ultimate virtual AI lives within the cyber spaces, we are currently targeting to re-create Neuro-sama.

Funding? Startup?

Currently, we have several parnership projects with other companies to build similar products, but I (@nekomeowww) primarily self sponsored those most contributed members of both @proj-airi and @moeru-ai, for supporting their work. I'd love have a opportunity to work on this project in long term without worrying the funding. If you are, and indeed got interested in this project, please contact me.

Who are we?

We are a group of currently non-funded talented people made up with computer scientists, experts in multi-modal fields, designers, product managers, and popular open source contributors who loves the goal of where we are heading now.

Demos:

• VAD
• VAD + ASR
• VAD + ASR + LLM Chat
• VAD + ASR + LLM Chat + TTS

Development

pnpm i

pnpm -F @proj-airi/vad-asr-chat dev

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-dev/ml: 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.