Reconcile Meeting Assistant architecture with Meeting Lab
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# Meeting Knowledge Assistant
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# Meeting Assistant
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## Vision
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Meeting Assistant is the user-facing application for turning recorded meetings
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into reviewed, distributable protocols. It uses Meeting Lab as its reusable
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local processing backend.
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The Meeting Knowledge Assistant (MKA) is an AI-assisted desktop application that records meetings, creates high-quality transcripts and transforms them into structured knowledge.
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## Current MVP Direction
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Unlike traditional meeting assistants, MKA does not aim to replace human interaction during meetings.
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Its goal is to create an accurate, searchable and long-term knowledge base from spoken communication.
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The first product milestone is a desktop GUI that lets a user:
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The project follows an "AI-first" architecture:
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- select an existing audio recording
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- create and edit structured meeting metadata and participants
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- optionally map anonymous `SPEAKER_XX` labels to known participants
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- start the Meeting Lab processing pipeline
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- follow stage-based progress
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- review and edit the generated protocol
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- export the reviewed result
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Audio
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→ Transcription
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→ Speaker Identification
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→ AI Analysis
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→ Structured Knowledge
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→ Search
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The MVP does not include integrated recording. OBS Studio remains a recommended
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reference recorder, but imported audio is not tied to OBS-specific behavior.
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---
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## Core Features
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- Import of existing meeting recordings
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- OBS Studio as the recommended reference recorder
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- High-quality local transcription
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- Speaker diarization
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- Editable working transcripts
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- AI-generated meeting minutes
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- Executive summaries
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- Action items
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- Decision tracking
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- Knowledge extraction
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- Local file-based storage
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- Export to Markdown, PDF and DOCX
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---
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## Recording Workflow
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The MVP does not include its own audio recorder.
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OBS Studio is the recommended reference recorder for online meetings. It can
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capture system audio and microphone audio without joining the meeting as a bot.
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Initial workflow:
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## Processing Pipeline
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```text
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Audio file
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-> FFmpeg preparation (mono, 16 kHz PCM WAV)
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-> whisper.cpp transcription (large-v3-turbo)
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-> optional pyannote.audio Community-1 diarization
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-> direct full-transcript protocol generation
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-> human review and export
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```
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Online Meeting
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Meeting Assistant calls Meeting Lab's reusable Python API
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(`MvpMeetingConfig`, `MvpRunResult` and `run_mvp_meeting(...)`). It does not run
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the Meeting Lab CLI as a subprocess. Fixed five-minute audio chunking is not a
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required part of this workflow.
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↓
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GPU acceleration is supported where available, but CPU execution remains a
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compatibility path. Diarization is optional and produces anonymous speaker
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labels. A label identifies a participant only when the user explicitly
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confirms the mapping; automatic speaker-name inference is not allowed.
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OBS Studio
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## Product Outputs
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↓
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The product direction includes:
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WAV Recording
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- a detailed, contextual protocol for review and continued work
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- a shorter version suitable for participants and distribution
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↓
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The detailed direct-protocol flow is the practical MVP direction. The shorter
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version may be implemented after the initial GUI. Human review remains part of
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the workflow for all generated protocols.
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Meeting Assistant Import
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## Project Boundary
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↓
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Meeting Lab owns reusable audio preparation, transcription, diarization,
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orchestration and protocol-generation logic. Meeting Assistant owns the GUI,
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context and participant editing, explicit speaker mapping, progress display,
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protocol editing and export.
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Transcription
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The code currently contains the initial Meeting Assistant project and domain
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foundation. The GUI has not yet been implemented.
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↓
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Speaker Diarization
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↓
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Analysis and Export
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---
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## Design Goals
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- High transcription quality
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- Modular architecture
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- Offline-first whenever practical
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- Replaceable AI components
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- Vendor independence
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- Long-term maintainability
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---
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## Philosophy
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The transcript is the primary asset.
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Everything else (summaries, reports, action items, knowledge extraction)
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can always be regenerated using better AI models in the future.
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Therefore:
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Audio
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→ Transcript
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is considered immutable.
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AI output is considered reproducible.
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---
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## Planned Architecture
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Recorder
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↓
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Transcription
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↓
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Speaker Identification
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↓
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LLM Processing
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↓
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Knowledge Database
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↓
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Export
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---
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## Current Status
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Project planning.
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No implementation has started yet.
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See [Architecture](docs/architecture.md), [Project Knowledge](PROJECT_KNOWLEDGE.md),
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[Roadmap](ROADMAP.md) and [ADR 0011](docs/adr/0011-use-meeting-lab-mvp-backend.md).
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