Add makima chain mechanism

2026-02-03T22:01:37+00:00

Release in makima repo

2026-02-02T22:52:05+00:00

Also remove all other TTS models

Add Qwen3-TTS streaming endpoint for voice synthesis (#40)

2026-01-28T02:54:17+00:00

* Task completion checkpoint * Task completion checkpoint * Task completion checkpoint * Add Qwen3-TTS research document for live TTS replacement Research findings for replacing Chatterbox TTS with Qwen3-TTS-12Hz-0.6B-Base: - Current TTS: Chatterbox-Turbo-ONNX with batch-only generation, no streaming - Qwen3-TTS: 97ms end-to-end latency, streaming support, 3-second voice cloning - Voice cloning: Requires 3s reference audio + transcript (Makima voice planned) - Integration: Python service with WebSocket bridge (no ONNX export available) - Languages: 10 supported including English and Japanese Document includes: - Current architecture analysis (makima/src/tts.rs) - Qwen3-TTS capabilities and requirements - Feasibility assessment for live/streaming TTS - Audio clip requirements for voice cloning - Preliminary technical approach with architecture diagrams Co-Authored-By: Claude Opus 4.5 * [WIP] Heartbeat checkpoint - 2026-01-27 03:11:15 UTC * Add Qwen3-TTS research documentation Comprehensive research on replacing Chatterbox TTS with Qwen3-TTS-12Hz-0.6B-Base: - Current TTS implementation analysis (Chatterbox-Turbo-ONNX in makima/src/tts.rs) - Qwen3-TTS capabilities: 97ms streaming latency, voice cloning with 3s reference - Cross-lingual support: Japanese voice (Makima/Tomori Kusunoki) speaking English - Python microservice architecture recommendation (FastAPI + WebSocket) - Implementation phases and technical approach - Hardware requirements and dependencies Key findings: - Live/streaming TTS is highly feasible with 97ms latency - Voice cloning fully supported with 0.95 speaker similarity - Recommended: Python microservice with WebSocket streaming Co-Authored-By: Claude Opus 4.5 * Add comprehensive Qwen3-TTS integration specification This specification document defines the complete integration of Qwen3-TTS-12Hz-0.6B-Base as a replacement for the existing Chatterbox-Turbo TTS implementation. The document covers: ## Functional Requirements - WebSocket endpoint /api/v1/speak for streaming TTS - Voice cloning with default Makima voice (Japanese VA speaking English) - Support for custom voice references - Detailed client-to-server and server-to-client message protocols - Integration with Listen page for bidirectional speech ## Non-Functional Requirements - Latency targets: < 200ms first audio byte - Audio quality: 24kHz, mono, PCM16/PCM32f - Hardware requirements: CUDA GPU with 4-8GB VRAM - Scalability: 10 concurrent sessions per GPU ## Architecture Specification - Python TTS microservice with FastAPI/WebSocket - Rust proxy endpoint in makima server - Voice prompt caching mechanism (LRU cache) - Error handling and recovery strategies ## API Contract - Complete WebSocket message format definitions (TypeScript) - Error codes and responses (TTS_UNAVAILABLE, SYNTHESIS_ERROR, etc.) - Session state machine and lifecycle management ## Voice Asset Requirements - Makima voice clip specifications (5-10s WAV, transcript required) - Storage location: models/voices/makima/ - Metadata format for voice management ## Testing Strategy - Unit tests for Python TTS service and Rust proxy - Integration tests for WebSocket flow - Latency benchmarks with performance targets - Test data fixtures for various text lengths Co-Authored-By: Claude Opus 4.5 * Add Qwen3-TTS implementation plan Comprehensive implementation plan for replacing Chatterbox-TTS with Qwen3-TTS streaming TTS service, including: - Task breakdown with estimated hours for each phase - Phase 1: Python TTS microservice (FastAPI, WebSocket) - Phase 2: Rust proxy integration (speak.rs, tts_client.rs) - Detailed file changes and new module structure - Testing plan with unit, integration, and latency benchmarks - Risk assessment with mitigation strategies - Success criteria for each phase Based on specification in docs/specs/qwen3-tts-spec.md Co-Authored-By: Claude Opus 4.5 * Add author and research references to TTS implementation plan Add links to research documentation and author attribution. Co-Authored-By: Claude Opus 4.5 * [WIP] Heartbeat checkpoint - 2026-01-27 03:25:06 UTC * Add Python TTS service project structure (Phase 1.1-1.3) Create the initial makima-tts Python service directory structure with: - pyproject.toml with FastAPI, Qwen-TTS, and torch dependencies - config.py with pydantic-settings TTSConfig class - models.py with Pydantic message models (Start, Speak, Stop, Ready, etc.) This implements tasks P1.1, P1.2, and P1.3 from the Qwen3-TTS implementation plan. Co-Authored-By: Claude Opus 4.5 * Add TTS engine and voice manager for Qwen3-TTS (Phase 1.4-1.5) Implement core TTS functionality: - tts_engine.py: Qwen3-TTS wrapper with streaming audio chunk generation - voice_manager.py: Voice prompt caching with LRU eviction and TTL support Co-Authored-By: Claude Opus 4.5 * [WIP] Heartbeat checkpoint - 2026-01-27 03:30:06 UTC * Add TTS proxy client and message types (Phase 2.1, 2.2, 2.4) - Add tts_client.rs with TtsConfig, TtsCircuitBreaker, TtsError, TtsProxyClient, and TtsConnection structs for WebSocket proxying - Add TTS message types to messages.rs (TtsAudioEncoding, TtsPriority, TtsStartMessage, TtsSpeakMessage, TtsStopMessage, TtsClientMessage, TtsReadyMessage, TtsAudioChunkMessage, TtsCompleteMessage, TtsErrorMessage, TtsStoppedMessage, TtsServerMessage) - Export tts_client module from server mod.rs - tokio-tungstenite already present in Cargo.toml Co-Authored-By: Claude Opus 4.5 * Add TTS WebSocket handler and route (Phase 2.3, 2.5, 2.6) - Create speak.rs WebSocket handler that proxies to Python TTS service - Add TtsState fields (tts_client, tts_config) to AppState - Add with_tts() builder and is_tts_healthy() methods to AppState - Register /api/v1/speak route in the router - Add speak module export in handlers/mod.rs The handler forwards WebSocket messages bidirectionally between the client and the Python TTS microservice with proper error handling. Co-Authored-By: Claude Opus 4.5 * Add Makima voice profile assets for TTS voice cloning Creates the voice assets directory structure with: - manifest.json containing voice configuration (voice_id, speaker, language, reference audio path, and Japanese transcript placeholder) - README.md with instructions for obtaining voice reference audio Co-Authored-By: Claude Opus 4.5 * Add Rust-native Qwen3-TTS integration research document Research findings for integrating Qwen3-TTS-12Hz-0.6B-Base directly into the makima Rust codebase without Python. Key conclusions: - ONNX export is not viable (unsupported architecture) - Candle (HF Rust ML framework) is the recommended approach - Model weights available in safetensors format (2.52GB total) - Three components needed: LM backbone, code predictor, speech tokenizer - Crane project has Qwen3-TTS as highest priority (potential upstream) Co-Authored-By: Claude Opus 4.5 * [WIP] Heartbeat checkpoint - 2026-01-27 11:21:43 UTC * [WIP] Heartbeat checkpoint - 2026-01-27 11:24:19 UTC * [WIP] Heartbeat checkpoint - 2026-01-27 11:26:43 UTC * feat: implement Rust-native Qwen3-TTS using candle framework Replace monolithic tts.rs with modular tts/ directory structure: - tts/mod.rs: TtsEngine trait, TtsEngineFactory, shared types (AudioChunk, TtsError), and utility functions (save_wav, resample, argmax) - tts/chatterbox.rs: existing ONNX-based ChatterboxTTS adapted to implement TtsEngine trait with Mutex-wrapped sessions for Send+Sync - tts/qwen3/mod.rs: Qwen3Tts entry point with HuggingFace model loading - tts/qwen3/config.rs: Qwen3TtsConfig parsing from HF config.json - tts/qwen3/model.rs: 28-layer Qwen3 transformer with RoPE, GQA (16 heads, 8 KV heads), SiLU MLP, RMS norm, and KV cache - tts/qwen3/code_predictor.rs: 5-layer MTP module predicting 16 codebooks - tts/qwen3/speech_tokenizer.rs: ConvNet encoder/decoder with 16-layer RVQ - tts/qwen3/generate.rs: autoregressive generation loop with streaming support Add candle-core, candle-nn, candle-transformers, safetensors to Cargo.toml. Co-Authored-By: Claude Opus 4.5 * feat: integrate TTS engine into speak WebSocket handler - Update speak.rs handler to use TTS engine directly from SharedState instead of returning a stub "not implemented" error - Add TtsEngine (OnceCell lazy-loaded) to AppState in state.rs with get_tts_engine() method for lazy initialization on first connection - Implement full WebSocket protocol: client sends JSON speak/cancel/stop messages, server streams binary PCM audio chunks and audio_end signals - Create voices/makima/manifest.json for Makima voice profile configuration - All files compile successfully with zero errors Co-Authored-By: Claude Opus 4.5 * feat: add /speak TTS page with WebSocket audio playback Add a new /speak frontend page for text-to-speech via WebSocket. The page accepts text input and streams synthesized PCM audio through the Web Audio API. Includes model loading indicator, cancel support, and connection status. Also adds a loading bar to the listen page ControlPanel during WebSocket connection. Co-Authored-By: Claude Opus 4.5 --------- Co-authored-by: Claude Opus 4.5

Add patch checkpointing

2026-01-23T01:03:04+00:00

Update CLI to show log history as well

2026-01-20T17:23:46+00:00

Add interactive TUI browser for tasks, contracts, and files (makima view) (#7)

2026-01-19T13:47:32+00:00

* feat(tui): Implement fuzzy search with real-time filtering and highlighting Adds comprehensive fuzzy search functionality to the TUI browser: ## Fuzzy Matching (fuzzy.rs) - FuzzyMatcher wrapper using SkimMatcherV2 from fuzzy-matcher crate - fuzzy_match() returns score and matched character indices - fuzzy_match_all() supports multi-term search (space-separated) - Recency-aware scoring to boost recent items in results - Unit tests for all matching scenarios ## App State (app.rs) - FilteredItem struct with index, score, and matched_indices - apply_filter() uses fuzzy matching with score-based sorting - match_count() and has_no_matches() helper methods - Results sorted by match score (highest first) ## List View (list_view.rs) - Highlighted matched characters in search results - Yellow bold styling for matched chars - Status icons with color coding ## Search Input (search_input.rs) - Real-time match count display (X/Y matches) - Visual feedback for no matches (red border) - Placeholder text when search is empty - Active search mode indication (yellow border) ## Event Handling (event.rs) - Arrow key navigation while in search mode - Ctrl+K/J for vim-style navigation during search - Delete key support alongside backspace - Ctrl+U to clear search query - Tab toggles preview while searching - Escape clears search and exits search mode Co-Authored-By: Claude Opus 4.5 * Task completion checkpoint * [WIP] Heartbeat checkpoint - 2026-01-19 11:20:34 UTC * Task completion checkpoint * [WIP] Heartbeat checkpoint - 2026-01-19 11:31:19 UTC * Task completion checkpoint * [WIP] Heartbeat checkpoint - 2026-01-19 11:39:07 UTC * fix(tui): Fix module exports and main binary integration - Update mod.rs to properly export app, event, fuzzy, and ui modules - Add run() function for TUI entry point - Fix run_view() to use ViewCommand enum instead of ViewArgs - Fix event handling to use poll_event and handle_key_event Co-Authored-By: Claude Opus 4.5 --------- Co-authored-by: Claude Opus 4.5

Add cleanup to daemon

2026-01-15T03:39:28+00:00

Also fixup for container image

Contract system

2026-01-15T00:21:16+00:00

Initial Control system

2026-01-11T03:01:13+00:00

Add claude opus/sonnet support

2025-12-23T18:24:42+00:00

soryu/Cargo.lock, branch master