Backend:
- New image_gen.py module with Gemini image generation client
- generate_artwork(): generates PNG from text prompt using Google GenAI
- get_image_gen_config(): loads config from .env (model, API key, safety)
- get_available_models(): returns list of Gemini image models
- Safety settings: harassment, hate_speech, sexually_explicit, dangerous
Configurable via IMAGE_GEN_SAFETY_* env vars (default: BLOCK_ONLY_HIGH)
- New endpoints:
* POST /api/clips/{id}/generate-artwork — generates and saves artwork
* GET /api/image-gen/models — lists available models
* GET /api/image-gen/config — returns safe config (API key masked)
- Default model: gemini-3.1-flash-image-preview
- Fallback API key: LYRIA_API_KEY if IMAGE_GEN_API_KEY not set
- Added google-genai==1.0.0 to requirements.txt
Frontend:
- New ArtworkGenerationModal component for prompt input
- Textarea with placeholder, loading spinner during generation
- Styled consistent with SettingsModal (backdrop blur, rounded, dark)
- SettingsModal expanded with Image Generation section (collapsible)
- Shows current model, API key status, safety filter levels
- Read-only display — values configured via .env
- DetailPanel: 'Generate' button added next to Upload/Change
- Passes onGenerateArtwork prop to App.tsx
- App.tsx: handles artwork generation flow, updates state on success
Architecture KB and Tasks KB updated.
Backend:
- New analysis.py module using librosa for BPM + key detection
- detect_bpm(): librosa.beat.beat_track() returns tempo
- detect_key(): Krumhansl-Schmuckler key profiles on chroma features
- analyze_clip(): combined call returning {bpm, key}
- New dependency: librosa==0.10.2 + soundfile==0.12.1
- Database migrations: bpm (REAL) and key (TEXT) columns added
- New set_analysis() function in database.py
- New endpoint: GET /api/clips/{id}/analysis
- Returns cached analysis if available
- Computes on-demand if missing, caches result
- 400 if clip not ready, 404 if no audio file
Frontend:
- Clip interface extended with bpm?: number | null, key?: string | null
- Gallery: BPM and key badges shown in ribbon and tile views
- BPM badge: lyria-accent background
- Key badge: white/5 background
- DetailPanel: BPM and key shown in metadata grid when available
- App.tsx: handleSelectClip() fetches analysis on-demand when opening
detail panel if not already cached
Docs:
- Architecture KB updated with Audio Analysis section
- Tasks KB: T-028 marked In Progress → will mark Done after commit
Backend:
- Install ffmpeg + numpy in Docker image
- New waveform.py: FFT-based SVG generator with 64 frequency bands
- GET /api/clips/{id}/waveform — generates on demand, caches to /data/waveforms/
- DELETE /api/clips/{id} now cascade-removes waveform SVG
- Warm amber-to-orange HSL gradient (25° to 35° hue)
- Mirrored bars: top full opacity, bottom 60% opacity
Frontend:
- DetailPanel shows waveform image beneath album art (80px height)
- Only shown for clips with status='ready'
Storage: /data/waveforms/ persisted via existing ./data volume mount
The Lyria API returns a candidates[].content.parts[] array where:
- parts[0] = text metadata (e.g. '<instrumental>')
- parts[1] = inlineData with the actual audio payload
Previous code only checked parts[0] for inlineData, which always failed
with 'No audio data in response'. Fixed by iterating all parts to find
the inlineData entry.
Successfully generated first real audio clip (lo-fi hip hop, 30s, 728KB MP3).
Also includes: .env.example, requirements updates, docker-compose fixes,
frontend vite config, logger setup.
rin.kagamine