Metadata-Version: 2.4
Name: meeting-helper
Version: 2.5.14
Summary: AI meeting assistant for macOS — auto-record, live transcription, Claude-powered answers
Author: Victor
License: MIT
Keywords: meeting,transcription,deepgram,claude,overlay,macos
Requires-Python: >=3.11
Description-Content-Type: text/markdown
Requires-Dist: click>=8.0
Requires-Dist: anthropic>=0.40.0
Requires-Dist: google-genai>=1.0.0
Requires-Dist: mcp>=1.0.0
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Requires-Dist: numpy>=1.24
Requires-Dist: deepgram-sdk<4.0,>=3.0
Requires-Dist: faster-whisper>=1.0.0
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Requires-Dist: aiohttp>=3.9.0
Requires-Dist: pynput>=1.7.6
Requires-Dist: PySide6>=6.5.0
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Requires-Dist: pyobjc-framework-AVFoundation>=10.0; sys_platform == "darwin"
Requires-Dist: pyobjc-framework-Quartz>=10.0; sys_platform == "darwin"
Requires-Dist: pyobjc-framework-ScreenCaptureKit>=10.0; sys_platform == "darwin"
Requires-Dist: pyobjc-framework-CoreMedia>=10.0; sys_platform == "darwin"
Requires-Dist: pyobjc-framework-libdispatch>=10.0; sys_platform == "darwin"
Requires-Dist: psutil>=5.9
Provides-Extra: dev
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Requires-Dist: pytest-aiohttp; extra == "dev"
Requires-Dist: ruff; extra == "dev"
Requires-Dist: mypy; extra == "dev"

# Meeting Helper

AI meeting assistant for macOS. Automatically detects when a meeting starts, records and transcribes in real-time, and lets you ask Claude questions about what's being discussed — using your codebase and knowledge base as context.

## Features

- **Auto-detection** — starts recording automatically when any app activates your microphone (Zoom, Meet, Teams, etc.)
- **Real-time transcription** — local Whisper (free, no API key needed) or Deepgram Nova-3 streaming
- **Invisible overlay** — native macOS window hidden from screen share via `NSWindow.setSharingType_(0)`
- **Ask Claude** — hotkey or type a question during the meeting; Claude answers using the transcript + your repos + knowledge docs
- **Per-meeting context** — select which repos and knowledge folders to load per meeting, so Claude only gets relevant context
- **Post-meeting** — full transcription + structured summary saved alongside the MP3 recording

## Requirements

- macOS 13+ (Ventura or later)
- Python 3.11+
- Microphone + Screen Recording + Accessibility permissions (prompted on first run)

---

## Installation

### Option A — pipx (recommended)

```bash
# Install pipx if you don't have it
brew install pipx && pipx ensurepath

# Install meeting-helper
pipx install meeting-helper
```

### Option B — from source

```bash
git clone <repo-url> meeting-helper
cd meeting-helper
python3 -m venv .venv
source .venv/bin/activate
pip install -e .
```

---

## First Run Setup

### 1. Download the Whisper model

Whisper is used for local transcription (no API key needed). The model needs to be downloaded once before your first meeting:

```bash
python3 -c "from faster_whisper import WhisperModel; WhisperModel('tiny', device='cpu', compute_type='int8')"
```

This downloads ~75MB to `~/.cache/huggingface/`. It only happens once.

> **Optional — better accuracy:** Use the `small` model (~244MB) instead of `tiny`:
> ```bash
> python3 -c "from faster_whisper import WhisperModel; WhisperModel('small', device='cpu', compute_type='int8')"
> ```
> Then in `meeting-helper setup`, set the Whisper model to `small`.

### 2. Run the setup wizard

```bash
meeting-helper setup
```

You'll be prompted for:

1. **Anthropic API key** — get one at [console.anthropic.com/settings/keys](https://console.anthropic.com/settings/keys)
2. **Deepgram API key** *(optional)* — get one at [console.deepgram.com](https://console.deepgram.com) for lower-latency streaming transcription. Leave blank to use local Whisper.
3. **Recordings directory** — where to save MP3s and transcripts (default: `~/meetings`)
4. **Repos** *(optional)* — paths to your code repos for Claude context
5. **Knowledge folder** *(optional)* — a folder of `.md`/`.txt` files organized by topic

### 3. Grant macOS permissions

On first run, macOS will prompt for:
- **Microphone** — to capture your voice
- **Screen Recording** — to capture system audio (meeting participants' voices)
- **Accessibility** — for global hotkeys (2×Cmd, 2×ESC)

After granting each permission, run `meeting-helper start` again if it stops.

---

## Usage

```bash
meeting-helper start          # start the background daemon
meeting-helper gui            # open the main window
meeting-helper stop           # stop the daemon
meeting-helper status         # show daemon and meeting status
meeting-helper logs           # tail the daemon log
meeting-helper version        # check for updates
meeting-helper fix-recording      # recover Screen Recording without rebooting
meeting-helper diagnose-recording # dump SCK / TCC diagnostics for paste-back
```

### `fix-recording` — when system audio goes silent

On managed/corporate laptops the Screen Recording permission sometimes
silently breaks: the OS still says it's granted, but ScreenCaptureKit
stops producing samples and only mic audio is captured. Reboot is the
only known certain fix. Before rebooting, try:

```bash
meeting-helper fix-recording
```

It (1) restarts the daemon to clear any stale capture session inside our
process, then (2) optionally restarts `tccd` and `coreaudiod` (the macOS
daemons that own permission state + audio routing) — needs your sudo
password — which often un-wedges the OS-side cause without a reboot.

Flags: `--no-sudo` skips the sudo nudge; `--open-settings` opens System
Settings → Privacy & Security → Screen Recording at the end.

Once the daemon is running:

1. **Start a Zoom/Meet/Teams call** → recording starts automatically
2. **Speak** → transcript appears in the overlay and GUI dashboard
3. **Ask Claude** → press `2×Cmd` (hotkey) or type in the "Ask Claude" box in the GUI
4. **End the call** → recording stops, MP3 + live transcript saved

### Hotkeys

| Combo | Action |
|---|---|
| `2× Cmd` | Trigger Claude query (uses last 5 transcript sentences) |
| `2× ESC` | Toggle overlay show/hide |
| `ESC + →` / `ESC + ←` | Scroll response down/up |
| `ESC + ]` / `ESC + [` | Navigate previous/next response |
| `Cmd + ↑` / `Cmd + ↓` | Font size up/down in overlay |

---

## local-todo Integration

If you use [local-todo](https://github.com/) as your task tracker (via its MCP server), meeting-helper can ground its answers and pre-meeting briefs in your real ticket data.

### Setup

In `meeting-helper setup`, you'll be prompted for the local-todo MCP command (default: `npx @local-todo/mcp`). Adjust if your install differs. The daemon spawns this command lazily on first use and keeps it alive for its lifetime.

### Generate Standup Brief

In the GUI dashboard, click **Generate Standup Brief**. The agent pulls your current sprint's active tasks from local-todo and produces a first-person script (3-6 bullets) for you to read at standup. Source ticket cards appear below the script so you can verify before reading.

### Hotkey-grounded answers

When you press `2× Cmd` during a meeting, meeting-helper now searches your local-todo for tickets and docs matching the recent transcript. Matches are passed to Claude as context AND rendered as cards beneath the answer in the overlay and dashboard, so you can see exactly which tickets the answer is grounded in.

If local-todo isn't configured (or the MCP fails), queries fall back to the existing repos/knowledge context — no other behavior changes.

### Live topic tracking (TopicWorker)

While a meeting is active, a background TopicWorker keeps track of what *you* are currently discussing — based on your microphone speech only (system audio is excluded). Every ~5 seconds it:

1. Reads the rolling self-buffer (your last ~25 sentences).
2. Extracts the topic, ticket IDs, a search query, and your most recent declarative statement using your configured AI provider (Claude / Gemini / local Ollama — same one you set in Settings).
3. Pre-fetches matching tickets from local-todo into a warm cache.
4. Broadcasts the result to the overlay and dashboard so you can see what the agent thinks you're working on.

When you press `2× Cmd`, the answer is built using this warm cache instantly — no per-query LLM extraction or local-todo search. Result: faster answers, and the AI gets explicit `## Topic just discussed` and `## What I just said` sections in its prompt that resolve pronouns and vague follow-ups (e.g. "what's the difference now?" after you mentioned a ticket).

### Two-stream audio (mic vs system)

Microphone and system audio (call participants) are now transcribed into separate buffers — `self_buffer` for what you say, `other_buffer` for what others say. The TopicWorker reads only `self_buffer` so the topic is grounded in *your* speech and not contaminated by what others say. The MP3 recording still mixes both for archival.

**Required:** wear headphones during meetings. Without headphones the laptop speaker feeds the mic, the call audio gets attributed to your buffer, and the topic detection becomes unreliable.

---

## Per-Meeting Context

By default, no repos or knowledge docs are loaded into Claude's context — loading everything would dilute accuracy. Instead, use the **Context Selector** in the Dashboard during a meeting:

1. Chips show your configured repos — click to select
2. Tree shows your knowledge base folders — check what's relevant
3. Click **Load Context** — Claude now has access to only what you selected
4. Ask questions — Claude answers using that specific context

---

## Post-Meeting

Open the **Recordings** screen in the GUI to:
- Play back the MP3
- Run full transcription (faster-whisper, timestamped)
- Generate a structured summary with Claude (key points, decisions, action items)

---

## Configuration

Config is saved to `~/.config/meeting-helper/config.json`. Run `meeting-helper setup` to reconfigure.

### Whisper model quality vs speed

| Model | Size | Speed | Accuracy |
|---|---|---|---|
| `tiny` | 75MB | Fastest | Good for real-time |
| `small` | 244MB | Fast | Better accuracy |
| `base` | 142MB | Medium | Balanced |

Default is `tiny` for real-time transcription. Post-meeting transcription always uses `small` for better quality.

---

## Check for Updates

```bash
meeting-helper version
```

Checks PyPI and upgrades automatically via pipx if a newer version is available.

---

## Troubleshooting

**Daemon not detecting meetings**
- Make sure Screen Recording permission is granted in System Settings → Privacy & Security
- Try `meeting-helper logs` to see what's happening

**No transcription appearing**
- If using Deepgram: check your API key with `meeting-helper status`
- If using local Whisper: ensure the model was downloaded (see First Run Setup above)
- Check `meeting-helper logs` for errors

**Overlay not visible**
- Press `2×ESC` to show/hide
- The overlay is intentionally invisible to screen share — check your physical display, not a recording

**Permission denied errors**
- Go to System Settings → Privacy & Security → Microphone / Screen Recording / Accessibility
- Remove and re-add the terminal app or meeting-helper entry

### Testing without real audio

For testing the topic/query flow without a microphone (e.g. you're on a plane, or just want to script a scenario), use:

```
curl -X POST localhost:7891/debug/say -d '{"role":"self","text":"I am working on ENGT-4212 — frontend contract layer."}'
sleep 6  # let TopicWorker debounce + LLM call finish
curl localhost:7891/current_topic | jq
curl -X POST localhost:7891/query -d '{"text":"what does the feature flag do?"}'
```

The `/debug/say` endpoint appends a sentence to `self_buffer` (or `other_buffer` if `"role":"other"`), which is exactly what the transcribers do for real speech. The TopicWorker, broadcasts, and `/query` handler all behave identically to the real-audio path.
