- miku-stt: switch PyTorch CUDA -> CPU-only (~2.5 GB savings)
- Silero VAD already runs on CPU via ONNX (onnx=True), CUDA PyTorch was waste
- faster-whisper/CTranslate2 uses CUDA directly, no PyTorch GPU needed
- torch+torchaudio layer: 3.3 GB -> 796 MB; total image 9+ GB -> 6.83 GB
- Tested: Silero VAD loads (ONNX), Whisper loads on cuda, server ready
- llama-swap-rocm: add root .dockerignore to fix 31 GB build context
- Dockerfile clones all sources from git, never COPYs from context
- 19 GB of GGUF model files were being transferred on every build
- Now excludes everything (*), near-zero context transfer
- anime-face-detector: add .dockerignore to exclude accumulated outputs
- api/outputs/ (56 accumulated detection files) no longer baked into image
- api/__pycache__/ and images/ also excluded
- .gitignore: remove .dockerignore exclusion so these files are tracked
- Added Evil Miku mode with 4 evil moods (aggressive, cunning, sarcastic, evil_neutral)
- Created evil mode content files (evil_miku_lore.txt, evil_miku_prompt.txt, evil_miku_lyrics.txt)
- Implemented persistent evil mode state across restarts (saves to memory/evil_mode_state.json)
- Fixed API endpoints to use client.loop.create_task() to prevent timeout errors
- Added evil mode toggle in web UI with red theme styling
- Modified mood rotation to handle evil mode
- Configured DarkIdol uncensored model for evil mode text generation
- Reduced system prompt redundancy by removing duplicate content
- Added markdown escape for single asterisks (actions) while preserving bold formatting
- Evil mode now persists username, pfp, and nicknames across restarts without re-applying changes
- Added optional reply message ID field to web UI
- Added radio buttons to control mention/ping behavior in replies
- Updated frontend JavaScript to send reply parameters
- Modified /manual/send and /dm/{user_id}/manual endpoints to support replies
- Fixed async context by moving message fetching inside bot event loop task
- Supports both channel and DM reply functionality
Features:
- Real-time streaming chat interface (ChatGPT-like experience)
- Model selection: Text model (fast) or Vision model (image analysis)
- System prompt toggle: Chat with Miku's personality or raw LLM
- Mood selector: Choose from 14 different emotional states
- Full context integration: Uses complete miku_lore.txt, miku_prompt.txt, and miku_lyrics.txt
- Conversation memory: Maintains chat history throughout session
- Image upload support for vision model
- Horizontal scrolling tabs for responsive design
- Clear chat history functionality
- SSE (Server-Sent Events) for streaming responses
- Keyboard shortcuts (Ctrl+Enter to send)
Technical changes:
- Added POST /chat/stream endpoint in api.py with streaming support
- Updated ChatMessage model with mood, conversation_history, and image_data
- Integrated context_manager for proper Miku personality context
- Added Chat with LLM tab to index.html
- Implemented JavaScript streaming client with EventSource-like handling
- Added CSS for chat messages, typing indicators, and animations
- Made tab navigation horizontally scrollable for narrow viewports
