126 lines
4.9 KiB
Markdown
126 lines
4.9 KiB
Markdown
# Meeting Assistant
|
|
|
|
Meeting Assistant is the user-facing application for turning recorded meetings
|
|
into reviewed, distributable protocols. It uses Meeting Lab as its reusable
|
|
local processing backend.
|
|
|
|
## Current MVP Direction
|
|
|
|
The first product milestone is a desktop GUI that lets a user:
|
|
|
|
- select an existing WAV, FLAC, or M4A recording
|
|
- create and edit structured meeting metadata and relevant people, including whether
|
|
they were present or only mentioned
|
|
- optionally map anonymous `SPEAKER_XX` labels to known participants
|
|
- start the Meeting Lab processing pipeline
|
|
- follow stage-based progress
|
|
- review and edit the generated protocol
|
|
- export the reviewed result
|
|
|
|
The MVP does not include integrated recording. OBS Studio remains a recommended
|
|
reference recorder, but imported audio is not tied to OBS-specific behavior.
|
|
|
|
## Processing Pipeline
|
|
|
|
```text
|
|
Audio file
|
|
-> FFmpeg preparation (mono, 16 kHz PCM WAV; normalization optional)
|
|
-> whisper.cpp transcription (large-v3-turbo)
|
|
-> optional pyannote.audio Community-1 diarization
|
|
-> direct full-transcript protocol generation
|
|
-> human review and export
|
|
```
|
|
|
|
Meeting Assistant calls Meeting Lab's reusable Python API
|
|
(`MvpMeetingConfig`, `MvpRunResult` and `run_mvp_meeting(...)`). It does not run
|
|
the Meeting Lab CLI as a subprocess. Fixed five-minute audio chunking is not a
|
|
required part of this workflow.
|
|
|
|
GPU acceleration is supported where available, but CPU execution remains a
|
|
compatibility path. Diarization is optional and produces anonymous speaker
|
|
labels. A label identifies a participant only when the user explicitly
|
|
confirms the mapping; automatic speaker-name inference is not allowed.
|
|
|
|
## Product Outputs
|
|
|
|
The product direction includes:
|
|
|
|
- a detailed, contextual protocol for review and continued work
|
|
- a shorter version suitable for participants and distribution
|
|
|
|
The detailed direct-protocol flow is the practical MVP direction. The shorter
|
|
version may be implemented after the initial GUI. Human review remains part of
|
|
the workflow for all generated protocols.
|
|
|
|
## Project Boundary
|
|
|
|
Meeting Lab owns reusable audio preparation, transcription, diarization,
|
|
orchestration and protocol-generation logic. Meeting Assistant owns the GUI,
|
|
context and participant editing, explicit speaker mapping, progress display,
|
|
protocol editing and export.
|
|
|
|
Audio normalization is enabled by default and can be disabled in the processing
|
|
options. This controls loudness normalization only: Meeting Lab still prepares
|
|
every WAV, FLAC or M4A source as canonical audio before transcription.
|
|
|
|
## Run the Streamlit MVP
|
|
|
|
The development setup expects `meeting-assistant` and `meeting-lab` to be
|
|
sibling repositories. Meeting Lab currently imports its API through the
|
|
`src.meeting_lab` package path, so its repository root must be supplied on
|
|
`PYTHONPATH`. Meeting Assistant does not modify `sys.path` at runtime.
|
|
|
|
Create a virtual environment and install Meeting Assistant, including
|
|
Streamlit:
|
|
|
|
```bash
|
|
python3 -m venv .venv
|
|
.venv/bin/pip install -e '.[dev]'
|
|
.venv/bin/pip install -e ../meeting-lab
|
|
```
|
|
|
|
Configure at least the local whisper.cpp model. All supported values are shown
|
|
in `.env.example`; export them in the shell because the application does not
|
|
load `.env` files implicitly:
|
|
|
|
```bash
|
|
export MKA_WHISPER_MODEL=/path/to/ggml-large-v3-turbo.bin
|
|
export MKA_WHISPER_EXECUTABLE=whisper-cli
|
|
export MKA_FFMPEG_EXECUTABLE=ffmpeg
|
|
export MKA_PROTOCOL_MODEL=qwen3.8:27B
|
|
```
|
|
|
|
Optional machine-specific settings include:
|
|
|
|
- `MKA_DATA_ROOT` (default: `data/meetings`)
|
|
- `MKA_OLLAMA_ENDPOINT` (default: `http://127.0.0.1:11434`)
|
|
- `MKA_WHISPER_THREADS` (default: `auto`)
|
|
- `MKA_FFMPEG_EXECUTABLE` (default: `ffmpeg` found on `PATH`)
|
|
- `MKA_DIARIZATION_MODE` (`auto`, `cpu`, or `gpu`; default: `auto`)
|
|
- `MKA_DIARIZATION_RUNTIME` (`native` or `container`; default: `native`)
|
|
- `MKA_DIARIZATION_CONTAINER_IMAGE` (required for container diarization)
|
|
|
|
From the Meeting Assistant repository, start the UI with:
|
|
|
|
```bash
|
|
PYTHONPATH=src:../meeting-lab .venv/bin/streamlit run src/mka/ui/streamlit_app.py
|
|
```
|
|
|
|
Streamlit opens `http://localhost:8501` by default. Installing the sibling
|
|
Meeting Lab project supplies its runtime requirements such as PyYAML and
|
|
Requests. Optional diarization dependencies are needed only when diarization
|
|
is enabled.
|
|
|
|
Uploaded source files are stored under
|
|
`data/meetings/<meeting-id>/uploads/`. Meeting Lab run artifacts are stored
|
|
under `data/meetings/<meeting-id>/runs/`. The reviewed protocol is saved as
|
|
`protocol_edited.md` inside its run directory; the generated `protocol.md`
|
|
remains unchanged.
|
|
|
|
The upload remains in its original format and is passed unchanged to Meeting Lab.
|
|
Meeting Lab creates the canonical mono 16 kHz signed PCM16 WAV run artifact used by
|
|
transcription; Meeting Assistant does not duplicate audio conversion.
|
|
|
|
See [Architecture](docs/architecture.md), [Project Knowledge](PROJECT_KNOWLEDGE.md),
|
|
[Roadmap](ROADMAP.md) and [ADR 0011](docs/adr/0011-use-meeting-lab-mvp-backend.md).
|