# GURU-BEAST-ROG Benchmark Setup

RTX 4090 performance comparison against DESKTOP-0O8A1RL (RTX 5070 Ti baseline: **149.5x realtime**).

---

## Step 1 — Sync repo

The audio-processor lives inside the claudetools repo. Pull latest on main.

```powershell
cd D:\claudetools   # or wherever claudetools is cloned on this machine
git pull
```

If not yet cloned:
```powershell
git clone https://azcomputerguru@git.azcomputerguru.com/azcomputerguru/claudetools.git D:\claudetools
cd D:\claudetools\projects\radio-show\audio-processor
```

---

## Step 2 — Python environment

Requires Python 3.11+. Use `py` launcher on Windows.

ffmpeg/ffprobe must be on PATH — the voice profiler shells out for audio duration. Without it the pipeline crashes on the first diarize call.

```powershell
# Install ffmpeg if not already present
winget install --id=Gyan.FFmpeg -e --accept-source-agreements --accept-package-agreements
# Open a new shell so the new PATH takes effect, then verify
ffprobe -version
```

```powershell
cd D:\claudetools\projects\radio-show\audio-processor

py -m venv .venv
.venv\Scripts\activate

# PyTorch with CUDA 12.8 (matches RTX 4090 driver)
pip install torch==2.11.0+cu128 --index-url https://download.pytorch.org/whl/cu128

# Core deps
pip install faster-whisper==1.2.1 transformers==5.6.2 soundfile==0.13.1
pip install numpy==2.4.4 rich==15.0.0 ollama==0.6.1 pyyaml scikit-learn

# Install project in editable mode
pip install -e . --no-deps
```

Verify GPU is visible:
```powershell
.venv\Scripts\python -c "import torch; print(torch.cuda.get_device_name(0))"
```

---

## Step 3 — Copy voice profiles from DESKTOP-0O8A1RL

Voice profiles are not in git (binary numpy files). Copy from the 5070 Ti machine via Tailscale.
DESKTOP-0O8A1RL Tailscale IP: **100.92.127.64**

```powershell
# From GURU-BEAST-ROG — pulls the voice-profiles directory over Tailscale
robocopy "\\100.92.127.64\claudetools\projects\radio-show\audio-processor\voice-profiles" `
         "D:\claudetools\projects\radio-show\audio-processor\voice-profiles" /E /COPYALL
```

If the network share isn't available, copy manually or use scp:
```powershell
scp -r mike@100.92.127.64:"D:/claudetools/projects/radio-show/audio-processor/voice-profiles" .
```

Expected contents after copy:
```
voice-profiles/
  profiles.json
  mike-swanson/
    composite.npy
    embedding_0000.npy ... embedding_0179.npy   (180 files)
```

---

## Step 4 — Download test episodes from IX server

Tailscale must be running. IX server: **172.16.3.10** (use Python paramiko — raw SSH has key agent interference).

```powershell
.venv\Scripts\python - << 'EOF'
import paramiko, os
client = paramiko.SSHClient()
client.set_missing_host_key_policy(paramiko.AutoAddPolicy())
client.connect('172.16.3.10', username='root', password='Gptf*77ttb!@#!@#',
               look_for_keys=False, allow_agent=False, timeout=30)
sftp = client.open_sftp()

os.makedirs('test-data/episodes', exist_ok=True)

downloads = [
    ('/home/gurushow/public_html/archive/2011/3-12-11 HR 1.mp3',        'test-data/episodes/2011-03-12-hr1.mp3'),
    ('/home/gurushow/public_html/archive/2012/3 - March/3-10-12HR1.mp3','test-data/episodes/2012-03-10-hr1.mp3'),
    ('/home/gurushow/public_html/archive/2012/6 - June/6-9-12-HR1.mp3', 'test-data/episodes/2012-06-09-hr1.mp3'),
    ('/home/gurushow/public_html/archive/2014/06/s6e19.mp3',            'test-data/episodes/2014-s6e19.mp3'),
    ('/home/gurushow/public_html/archive/2016/06/s8e43.mp3',            'test-data/episodes/2016-s8e43.mp3'),
    ('/home/gurushow/public_html/archive/2017/04/s9e30.mp3',            'test-data/episodes/2017-s9e30.mp3'),
]

for remote, local in downloads:
    size_mb = sftp.stat(remote).st_size / 1024 / 1024
    print(f'Downloading {local} ({size_mb:.1f} MB)...', flush=True)
    sftp.get(remote, local)
    print('  done', flush=True)

sftp.close()
client.close()
print('All downloads complete.')
EOF
```

---

## Step 5 — Run benchmark

```powershell
.venv\Scripts\python benchmark.py
```

This diarizes all 6 test episodes, prints per-episode timing, and compares to the 5070 Ti baseline.

---

## Step 6 — Report results

Post the benchmark output in the session log or share back to DESKTOP-0O8A1RL.

The key number to compare: **total realtime factor** (5070 Ti got 149.5x).

Also note any Q&A pair count differences — same episodes should produce same pairs on both machines (results are deterministic given the same voice profiles).