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assistant/docs/overview.md
Johannes Kresner bba0095bc0 feat: bootstrap vela UI and gateway workspace
Establish the monorepo, tooling, and starter apps so UI and gateway development can begin from a documented, runnable baseline.
2026-04-08 17:49:46 +02:00

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Vela Overview

Objective

Vela is a fully local, voice-first assistant system with:

  • local-first architecture and no mandatory cloud dependencies
  • natural TTS output via Kokoro
  • voice-driven interaction as the primary interface
  • integrations with Home Assistant and SearXNG
  • a lightweight SvelteKit PWA
  • remote LLM inference via Ollama on a NAS

Core Design Principles

Voice-first

  • UI optimized for speaking instead of typing
  • minimal visual clutter
  • real-time feedback through partial transcripts and streaming responses

Local-first

  • no required cloud APIs
  • all services self-hosted
  • browser used for capture and playback only

Tool-driven intelligence

  • the LLM does not directly control external systems
  • all external actions route through explicit tools

Low-latency interaction

  • streaming STT partial results
  • streaming LLM token output
  • streaming TTS audio chunks
  • interruptible responses

Product Scope

Primary Interface

  • browser-based PWA
  • push-to-talk interaction
  • transcript and response display
  • playback of streamed or returned audio

Secondary Screens

  • /history
  • /settings
  • /admin

These screens are lower priority than the main voice loop and should be implemented after the core interaction path is stable.

Repository Layout

  • apps/vela-ui — minimal SvelteKit browser UI
  • apps/vela-gateway — minimal Fastify gateway service
  • docs/ — technical documentation and phased backlog

Use Yarn workspaces from the repository root to manage these packages.

Primary User Flow

User presses mic
→ audio streaming starts
→ transcript appears
→ final transcript sent
→ assistant processes
→ response streams as text and audio
→ user can interrupt anytime

Non-Goals for v1

  • full conversational memory system
  • emotion simulation or personality modeling
  • multi-user identity separation
  • offline LLM on the NanoPi
  • wake word and other future extensions listed in architecture docs

Documentation Map