README.md

metadata

title: Wllama
emoji: 🦙
colorFrom: green
colorTo: pink
sdk: static
pinned: true
short_description: Run GGUF directly on your browser!
license: mit
header: mini
custom_headers:
  cross-origin-embedder-policy: require-corp
  cross-origin-opener-policy: same-origin
  cross-origin-resource-policy: cross-origin

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Running locally / offline

Serve this folder with the COOP/COEP headers the Space uses (required for multithreading + the model cache), then open the printed URL:

python3 serve.py            # http://localhost:8000

What's offline-ready after one-time downloads:

• VAD + TTS: bundled locally (vad/, piper/, voices/, onnx/) — always work offline.
• LLM model (GGUF): download once from the Manage models page; it is cached in the browser.
• ASR (Whisper): use the Voice modules → Install button on the Manage models page. It downloads the whisper model and runs the ONNX runtime from the local asr/ folder, so speech-to-text works fully offline after install.

Voice-to-voice mode

Click 🎙 Voice in the top bar for a full-screen voice interface:

• Hands-free: speak → transcribed (whisper) → answered (LLM) → read aloud (piper TTS).
• A neon audio visualizer reacts to the assistant's speech.
• Only sentences that have already been spoken are shown on screen, so faster text generation stays hidden until it is actually said.
• On a new conversation the LLM invents a random personality for the assistant and speaks its greeting.
• Click any spoken sentence (or any assistant bubble in normal chat) to regenerate that reply.