# Colab Remote

> >

- **Type:** Skill
- **Install:** `agentstack add skill-broomva-skills-colab-remote`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [broomva](https://agentstack.voostack.com/s/broomva)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [broomva](https://github.com/broomva)
- **Source:** https://github.com/broomva/skills/tree/main/skills/compute/colab-remote
- **Website:** https://skills.sh/broomva/skills

## Install

```sh
agentstack add skill-broomva-skills-colab-remote
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Colab Remote — SSH-Operated GPU Training

Operate Google Colab Pro/Pro+ instances as headless GPU backends from the local terminal.

## Architecture

```
Local Mac (Claude Code)
  ├── agent-browser → Chrome → colab.research.google.com
  │   └── Opens notebook, runs colab-ssh setup cell
  ├── SSH tunnel → Colab runtime (via ngrok or cloudflared)
  │   └── Run training, monitor GPU, transfer files
  └── /autoany EGRI loop (local)
      └── Proposes mutations → SSH executes on Colab → evaluates results
```

## Phase 1: Launch Colab Session (Browser Automation)

Use `/agent-browser` to open Colab and set up SSH access.

### Step 1: Open Colab and create notebook

```bash
agent-browser open "https://colab.research.google.com/#create=true"
agent-browser wait --load networkidle
agent-browser snapshot -i
```

If login is required, prompt the user to authenticate manually, then re-snapshot.

### Step 2: Select GPU runtime

Navigate Runtime > Change runtime type, select GPU (T4/V100/A100 depending on plan), and save.

### Step 3: Install colab-ssh and get connection details

Type the SSH setup code into a cell. Two methods supported:

**Method A: ngrok (recommended)**

```python
!pip install colab-ssh --upgrade
from colab_ssh import launch_ssh
launch_ssh("YOUR_NGROK_TOKEN")
```

User must provide ngrok authtoken from https://ngrok.com.

**Method B: cloudflared (no account needed)**

```python
!pip install colab-ssh --upgrade
from colab_ssh import launch_ssh_cloudflared
launch_ssh_cloudflared(password="your-password-here")
```

### Step 4: Extract and save connection details

After the cell runs, snapshot output to extract hostname/port. Save for reuse:

```bash
mkdir -p ~/.colab-remote
cat > ~/.colab-remote/session.env  train.log 2>&1 &"
# Monitor
ssh -p $COLAB_PORT root@$COLAB_HOST "tail -f /content/train.log"
```

### Monitor GPU

```bash
ssh -p $COLAB_PORT root@$COLAB_HOST "nvidia-smi --query-gpu=utilization.gpu,utilization.memory,memory.used,memory.total,temperature.gpu --format=csv"
```

### Install dependencies

```bash
ssh -p $COLAB_PORT root@$COLAB_HOST "pip install torch transformers peft bitsandbytes accelerate datasets"
```

## Phase 3: EGRI Integration (/autoany)

Wire Colab as the execution backend for an EGRI optimization loop. See `references/egri-colab.md` for the full problem-spec template and harness patterns.

### Execution loop (summary)

```
for each trial:
  1. Upload mutated artifact → scp to Colab
  2. Execute on Colab GPU → ssh python train.py
  3. Evaluate results → ssh python evaluate.py
  4. Download metrics → scp results.json
  5. Score locally (immutable evaluator)
  6. Promote or discard based on policy
```

## Phase 4: Session Lifecycle

| Tier | Max runtime | Idle timeout | GPU |
|------|-------------|--------------|-----|
| Free | 12h | 90min | T4, limited |
| Pro | 24h | 90min | T4, V100, priority |
| Pro+ | 24h | 90min | T4, V100, A100 |

### Keep-alive

```bash
ssh -p $COLAB_PORT root@$COLAB_HOST "while true; do sleep 300; echo keepalive; done &"
```

### Reconnect after timeout

1. Check: `ssh -p $COLAB_PORT root@$COLAB_HOST "echo ok" 2>/dev/null && echo "UP" || echo "DOWN"`
2. If dead, re-launch via Phase 1 (browser automation)
3. Resume from last checkpoint

### Google Drive persistence

Mount Drive to persist across sessions:

```bash
ssh -p $COLAB_PORT root@$COLAB_HOST "python -c 'from google.colab import drive; drive.mount(\"/content/drive\")'"
# Checkpoints survive in /content/drive/MyDrive/
```

## Quick Reference

| Task | Command |
|------|---------|
| Check GPU | `ssh -p $COLAB_PORT root@$COLAB_HOST "nvidia-smi"` |
| Upload | `scp -P $COLAB_PORT ./file root@$COLAB_HOST:/content/` |
| Download | `scp -P $COLAB_PORT root@$COLAB_HOST:/content/file ./` |
| Run script | `ssh -p $COLAB_PORT root@$COLAB_HOST "python /content/script.py"` |
| Background job | `ssh -p $COLAB_PORT root@$COLAB_HOST "nohup python train.py > log 2>&1 &"` |
| Tail log | `ssh -p $COLAB_PORT root@$COLAB_HOST "tail -20 /content/log"` |
| Disk space | `ssh -p $COLAB_PORT root@$COLAB_HOST "df -h /content"` |
| Kill job | `ssh -p $COLAB_PORT root@$COLAB_HOST "pkill -f train.py"` |
| Session alive? | `ssh -p $COLAB_PORT root@$COLAB_HOST "echo ok" 2>/dev/null` |

## Prerequisites

- **ngrok account** (free): https://ngrok.com — or `cloudflared`: `brew install cloudflared`
- **Colab Pro/Pro+** for GPU priority and longer runtimes
- **agent-browser** installed and working
- **Google account** signed into Chrome

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [broomva](https://github.com/broomva)
- **Source:** [broomva/skills](https://github.com/broomva/skills)
- **License:** MIT
- **Homepage:** https://skills.sh/broomva/skills

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** yes
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-broomva-skills-colab-remote
- Seller: https://agentstack.voostack.com/s/broomva
- Browse the marketplace: https://agentstack.voostack.com/browse

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