README / AetherOps-HF-Hub-Build-Spec.md
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Build Aether Voice Studio Docker Space
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AetherOps Hugging Face Docker Space — Build Spec

Objective

Build a polished Hugging Face Docker Space for the AetherOps organization that acts as:

  1. a public-facing product showcase
  2. a docs-style explainer for Aether Voice Studio
  3. a credibility layer for the Aether ecosystem
  4. a controlled demo surface for voice workflows
  5. a launchpad into AetherOps, Aether Voice Studio, and future public docs

This is not intended to replace production infrastructure.


Product Positioning

The Space should feel like:

  • a premium technical landing page
  • a product docs entrypoint
  • a live architecture showcase
  • a curated interactive demo, not a toy

The tone should communicate:

  • serious infrastructure
  • creator utility
  • enterprise utility
  • model routing clarity
  • composable voice tooling

Platform Constraints

Docker Space requirements

The Space must be implemented as a Hugging Face Docker Space using:

  • sdk: docker in README YAML
  • a standard Dockerfile
  • a single externally exposed app port via app_port

If multiple internal services are needed, they must be proxied behind the single external app port.

Do not use Docker Compose as the deployment contract for Hugging Face Space runtime.


Primary Goal

Deliver a highly polished front-end app that explains and showcases:

  • Aether Voice Studio
  • Voice routes and model matrix
  • ASR / TTS / Dialogue / Voice Design flows
  • future Sound Design lane
  • LLM routing
  • internal architecture at a high level
  • product screenshots / diagrams / cards
  • selected live demo interactions if safe and lightweight

Recommended Technical Stack

Preferred:

  • Next.js or Vite + React frontend
  • FastAPI backend for lightweight API/demo endpoints
  • Nginx reverse proxy only if needed for clean single-port routing

Alternative:

  • pure frontend app with static + client-side demo interactions if no backend is necessary

Do not build a heavyweight all-in-one inference stack inside the Space for v1.


Information Architecture

Main sections

  1. Hero
  2. Product Overview
  3. Aether Voice Studio
  4. Route / Model Matrix
  5. Demo Workflows
  6. Creator Workflows
  7. Enterprise / VoiceOps Workflows
  8. Docs Entry
  9. Architecture
  10. FAQ
  11. CTA / Links

Page Layout

1. Hero

Content:

  • product title
  • short positioning statement
  • 2-3 primary CTA buttons
  • subtle animated visual or waveform motif
  • one-line trust statement

Primary CTAs:

  • View Voice Studio
  • Explore Docs
  • View Architecture

2. Product Overview

Cards for:

  • ASR Live
  • ASR File
  • TTS Live
  • TTS File
  • TTS Studio
  • VoiceOps
  • LLM Routing
  • Sound Design (coming soon)

Each card should have:

  • short explanation
  • intended user
  • route target summary
  • status badge (live / in build / planned)

3. Aether Voice Studio

Large section explaining:

  • why TTS Live is separate from TTS Studio
  • voice cloning
  • voice design
  • batch narration
  • dialogue generation
  • reusable voice assets

Use diagrams or cards.

4. Route / Model Matrix

Present the canonical routing system:

  • moss_realtime
  • moss_tts
  • moss_ttsd
  • moss_voice_generator
  • moss_soundeffect
  • chatterbox fallback

Display:

  • use case
  • route
  • output type
  • UI surface

5. Demo Workflows

Show example workflows:

  • Live voice agent response
  • Clone a reference voice
  • Design a custom character voice
  • Batch narration export
  • Dialogue scene generation
  • Future sound effects

If a backend demo is included, keep it small and stable.

6. Creator Workflows

Emphasize:

  • docuseries narration
  • faceless YouTube content
  • dialogue scenes
  • voice design presets
  • future ambience and transition sounds

7. Enterprise / VoiceOps Workflows

Emphasize:

  • telephony
  • branded voice agents
  • support routing
  • dispatch and field service voices
  • enterprise voice infrastructure

8. Docs Entry

This should look like a docs portal. Include:

  • Overview
  • Quick Start
  • Architecture
  • Voice Routes
  • Voice Registry
  • TTS Studio
  • LLM Routing
  • API Reference
  • Troubleshooting

9. Architecture

Show:

  • Voice Studio frontend
  • routing layer
  • route targets
  • provider-aware LLM config
  • model registry / voice registry
  • output artifacts

10. FAQ

Keep concise. Include:

  • Why multiple MOSS routes?
  • Why separate TTS Live from Studio?
  • What is voice design?
  • What is a voice registry?
  • What is the role of Chatterbox?
  • Is Sound Design included?

11. CTA / Links

Buttons to:

  • AetherOps
  • docs
  • future public API
  • internal app screenshots
  • contact / partner form later

Navigation

Top nav:

  • Overview
  • Studio
  • Routes
  • Demos
  • Docs
  • Architecture
  • FAQ

Optional secondary links:

  • GitHub
  • Hugging Face org
  • API docs

Visual Design Direction

Style goals:

  • dark, premium, technical
  • high-contrast but clean
  • soft gradients
  • waveform / voice / routing motifs
  • “serious studio” look, not toy AI landing page

Use:

  • large cards
  • clean spacing
  • strong section boundaries
  • subtle motion
  • architecture diagrams
  • demo output panels

Demo Scope for v1

Allowed:

  • static screenshots
  • route matrix interaction
  • expandable workflow cards
  • example voice design prompt gallery
  • selected sample audio players if pre-generated
  • lightweight metadata-driven demo UI

Avoid for v1:

  • full realtime inference in the Space
  • heavy model hosting
  • anything that depends on long cold starts
  • telephony integration
  • complex secrets-dependent internal routing

Suggested v1 Deliverables

Required

  • Docker Space app builds and runs on single app port
  • polished landing page
  • route/model matrix section
  • docs-style navigation section
  • screenshots or diagrams from Aether Voice Studio
  • creator and enterprise workflow sections
  • FAQ section
  • CTA/footer

Nice to have

  • small demo API endpoint
  • small JSON-driven voice preset gallery
  • pre-generated audio preview cards
  • architecture diagram tab

Hugging Face Space Repo Files

Minimum structure:

  • README.md
  • Dockerfile
  • .dockerignore
  • app/
  • app/frontend/
  • app/backend/
  • app/public/
  • app/data/
  • app/data/voice_seed_library.json
  • app/data/route_model_matrix.json

If frontend-only:

  • simplify accordingly

README YAML

Use Hugging Face Space metadata in the README YAML block.

Recommended fields:

  • title
  • emoji
  • colorFrom
  • colorTo
  • sdk: docker
  • app_port
  • short_description
  • pinned
  • header
  • fullWidth
  • suggested_hardware
  • models
  • tags

Runtime / Secrets

The Space should be designed so it can run without production secrets for v1.

If environment variables are needed:

  • use Hugging Face Space Settings variables/secrets
  • keep secrets server-side only
  • avoid any browser-visible secret flow

Persistence

Do not assume persistent app state for v1. Use:

  • repo assets
  • generated static content
  • environment variables
  • optional external APIs later

Do not design v1 around runtime disk persistence.


Build / Runtime Requirements

  • must run as a proper Docker Space app
  • respect single public port model
  • avoid permission issues by using UID 1000-compatible ownership in image build
  • no GPU requirement for v1 Space

Non-goals

  • no full production inference cluster inside Hugging Face Space
  • no Docker Compose-based deployment target
  • no full telephony backend in Space
  • no user secrets vault in v1
  • no multi-tenant auth flows in v1

Success Criteria

The finished Space should:

  1. look premium and intentional
  2. explain Aether Voice Studio clearly
  3. demonstrate model/route sophistication
  4. support partner/investor/customer credibility
  5. be easy to extend later into a richer public product surface

Add a small Data Contracts section with downloadable or viewable JSON snippets:

voice registry shape

route/model matrix

seed voice library

provider config shape

That quietly signals: “this thing is machine-readable and automation-native.” That matters for your brand.