8b6184ecc5
Enterprise Meeting Knowledge Management System with: Backend (FastAPI): - Authentication proxy with JWT (pj-auth-api integration) - MySQL database with 4 tables (users, meetings, conclusions, actions) - Meeting CRUD with system code generation (C-YYYYMMDD-XX, A-YYYYMMDD-XX) - Dify LLM integration for AI summarization - Excel export with openpyxl - 20 unit tests (all passing) Client (Electron): - Login page with company auth - Meeting list with create/delete - Meeting detail with real-time transcription - Editable transcript textarea (single block, easy editing) - AI summarization with conclusions/action items - 5-second segment recording (efficient for long meetings) Sidecar (Python): - faster-whisper medium model with int8 quantization - ONNX Runtime VAD (lightweight, ~20MB vs PyTorch ~2GB) - Chinese punctuation processing - OpenCC for Traditional Chinese conversion - Anti-hallucination parameters - Auto-cleanup of temp audio files OpenSpec: - add-meeting-assistant-mvp (47 tasks, archived) - add-realtime-transcription (29 tasks, archived) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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ADDED Requirements
Requirement: Edge Speech-to-Text
The Electron client SHALL perform speech-to-text conversion locally using faster-whisper int8 model.
Scenario: Successful transcription
- WHEN user records audio during a meeting
- THEN the audio SHALL be transcribed locally without network dependency
Scenario: Transcription on target hardware
- WHEN running on i5 processor with 8GB RAM
- THEN transcription SHALL complete within acceptable latency for real-time display
Requirement: Traditional Chinese Output
The transcription engine SHALL output Traditional Chinese (繁體中文) text.
Scenario: Simplified to Traditional conversion
- WHEN whisper outputs Simplified Chinese characters
- THEN OpenCC SHALL convert output to Traditional Chinese
Scenario: Native Traditional Chinese
- WHEN whisper outputs Traditional Chinese directly
- THEN the text SHALL pass through unchanged
Requirement: Real-time Display
The Electron client SHALL display transcription results in real-time.
Scenario: Streaming transcription
- WHEN user is recording
- THEN transcribed text SHALL appear in the left panel within seconds of speech
Requirement: Python Sidecar
The transcription engine SHALL be packaged as a Python sidecar using PyInstaller.
Scenario: Sidecar startup
- WHEN Electron app launches
- THEN the Python sidecar containing faster-whisper and OpenCC SHALL be available
Scenario: Sidecar communication
- WHEN Electron sends audio data to sidecar
- THEN transcribed text SHALL be returned via IPC