vezir 0.1.2

Internal scribe service that wraps meetscribe for team-scale meeting capture, transcription, summarization, and speaker labeling

vezir

Self-hosted scribe service for team-scale meeting capture. Vezir wraps meetscribe and turns it into a multi-user, Tailscale-hosted service: a designated scribe records a meeting on their laptop, the audio uploads to a central GPU-equipped box, and the team gets back a diarized transcript, AI summary, and PDF — with speaker labels resolved to GitHub handles via a shared web UI.

Status

Alpha (0.1.2). Designed for small teams that want to keep meeting audio inside their own infrastructure: one Tailscale tailnet + one GPU-equipped box. Currently dogfooded by the Blink team. Linux clients fully supported, macOS thin client deferred.

Architecture

[Scribe laptop]                       [GPU server]
  vezir scribe / gui / upload ──▶     vezir serve (FastAPI)
   (wraps meet record)                  │
                                        ├── sqlite job queue
                                        │
                                        ▼
                                      worker
                                        │ shells out via HOME-shim
                                        ▼
                                      meet transcribe (unmodified)
                                      meet label --auto
                                      meet sync     ──▶ private git repo
                                        │
                                        ▼
                                      web UI (labeling, dashboard)
                                       ◀── scribe browser

Meetscribe is invoked as an unmodified subprocess. Vezir owns its own job queue, voiceprint database, team roster, and browser auth.

Repo layout

vezir/
  vezir/                    # python package
    cli.py                  # serve, scribe, upload, token issue
    config.py               # paths, env
    server/                 # FastAPI app, queue, worker, meet_runner
    client/                 # vezir scribe (wraps meet record + uploads)
    web/                    # templates + static
  data/
    team.json.example
  infra/
    systemd/vezir.service
  tests/

Runtime data lives outside the repo at ~/vezir-data/.

Install profiles

Role	Install command	Footprint
Scribe client only (record + upload, GUI optional)	pip install --user vezir (or pip install --user 'vezir[gui]' if you also want apt install python3-tk)	~30 MB
Server (FastAPI + worker + dashboard + labeling UI)	pip install --user 'vezir[server]'	~3 GB (pulls meetscribe-offline = whisperx + torch + pyannote)

The split is enforced by pyproject.toml's [project.optional-dependencies]: the base install uses meetscribe-record (capture only). The [server] extra adds meetscribe-offline for the heavy transcription/diarization/summarization pipeline.

Quick start (server, on a GPU box reachable over Tailscale)

git clone https://github.com/pretyflaco/vezir.git
cd vezir
pip install --user -e '.[server]'

# Seed voiceprints from existing meetscribe profile DB
mkdir -p ~/vezir-data
vezir voiceprints seed --from ~/.config/meet/speaker_profiles.json

# Sync target — sandbox repo for development.
# vezir's worker invokes `meet sync --force --meeting-type sandbox-<HHMMSSZ>-<rand>`
# which bypasses meetscribe's schedule and team-presence gates and
# guarantees a unique per-session folder. Every successful job lands in
# meetings/<date>_sandbox-<HHMMSSZ>-<rand>/ on the configured repo
# (e.g. meetings/2026-04-25_sandbox-194051Z-VZJJ3P/).
cat > ~/vezir-data/sync_config.json <<'EOF'
{
  "repo_url": "https://github.com/pretyflaco/vezir-meetings.git",
  "meetings": [],
  "team_members": [],
  "min_team_members": 0
}
EOF

# Initialize team roster (used by labeling UI autocomplete)
cp data/team.json.example ~/vezir-data/team.json
$EDITOR ~/vezir-data/team.json

# Issue a token for yourself
vezir token issue --github kasita

# Start the service
vezir serve

# Or, to skip git sync (artifacts stay only in ~/vezir-data/sessions/<id>/)
VEZIR_SKIP_SYNC=1 vezir serve

Sync target governance

This is intentionally pointed at a private dev sandbox repo (pretyflaco/vezir-meetings) during the pilot. Two reasons:

• production meeting-archive repos (e.g. blinkbitcoin/blink-wip) get schedule + team-presence gating from meetscribe; vezir uses --force to override that, which is appropriate for a dev sandbox but not for production
• vezir may rewrite history or recreate the repo while the pipeline is being shaken down

To graduate to production: change repo_url in ~/vezir-data/sync_config.json, drop --force (planned: env var VEZIR_SYNC_FORCE=0), and let meetscribe's existing schedule/team-gate decide what to push.

Quick start (scribe client)

# Install vezir + meetscribe-record (lightweight; ~30 MB).
pip install --user vezir

# Optional: GUI widget (Tkinter); on Debian/Ubuntu:
sudo apt install python3-tk

# Configure (one-time): server URL = Tailscale name of your vezir server.
# If MagicDNS is unavailable, use the server's Tailscale IP instead.
export VEZIR_URL=http://your-vezir-server:8000
export VEZIR_TOKEN=<token-issued-on-server>

# CLI scribe
vezir scribe --title "what this meeting is about"
# Talk; Ctrl+C when done.
# By default, the recorded WAV is compressed to OGG/Opus before upload.
# Use --no-compress to upload the raw WAV instead.

# Or GUI scribe (always-on-top widget)
vezir gui

# Or upload an existing recording (WAV/OGG)
vezir upload ./previous-meeting.wav --title "previous meeting"

# Compress an existing WAV before uploading it
vezir upload ./previous-meeting.wav --compress --title "previous meeting"

When the recording is uploaded, vezir prints a dashboard URL. Open it in your browser; the GUI's "Open dashboard" button does this for you. The URL flows through /login?token=... so the browser is signed in via HttpOnly cookie before it lands on the session page; subsequent access from the same browser does not require re-passing the token.

Live client recordings remain on the scribe machine under ~/meet-recordings/ by default. vezir status is a server-side/local diagnostic command; on a thin client it inspects that machine's local ~/vezir-data and does not query the remote server.

Standalone uploads currently accept .wav and .ogg, matching what the server-side meetscribe pipeline consumes from session folders. Use vezir upload --compress file.wav to compress a WAV to OGG/Opus before uploading. Other formats such as .mp3, .m4a, and .webm should be transcoded to WAV/OGG first until server-side transcoding is added.

The client reports upload progress, retries from byte 0 after transient connection failures, and sends the expected audio byte count so the server can reject incomplete uploads instead of processing partial meetings.

Environment variables

Variable	Default	Effect
VEZIR_DATA	~/vezir-data	All runtime state — sessions, voiceprints, queue, tokens, sync_config
VEZIR_HOST	0.0.0.0	Bind address for vezir serve
VEZIR_PORT	8000	Port for vezir serve
VEZIR_URL	http://localhost:8000	Server URL for vezir scribe clients
VEZIR_TOKEN	—	Bearer token for vezir scribe clients
VEZIR_LOG_LEVEL	INFO	Logging level
VEZIR_MEET_BIN	$(which meet)	Path to meetscribe meet binary
VEZIR_SKIP_SYNC	unset	Set to 1 to skip the meet sync step entirely
VEZIR_DELETE_AUDIO	unset	Set to 1 to delete audio after artifacts are produced (storage policy). Default OFF during pilot.
VEZIR_SYNC_MEETING_TYPE	sandbox	Subfolder name (under meetings/) used by meet sync --force. Will be removed once vezir respects schedules.
VEZIR_MAX_UPLOAD_BYTES	2147483648	Maximum accepted upload size (default 2 GiB). Oversized uploads return HTTP 413.

Runtime directories are created private (0700) and sensitive runtime files are written private (0600). The systemd unit also sets UMask=0077 so artifacts created by subprocesses inherit private defaults.

License

MIT — see LICENSE.