Computer

Agents with computer access can execute code, run shell commands, and read/write files in sandboxed Linux environments. Enable it in your agent's settings under Capabilities > Computer.

Providers

Flapjack supports two sandbox providers. Choose based on your workload:

Tensorlake (default)

Sandbox runs alongside your agent on Tensorlake infrastructure. Named sandboxes persist across tool calls within a conversation.

• Startup: Fast — sandbox runs in the same environment as the agent
• Persistence: Filesystem persists across tool calls within a turn
• Runtime: Python 3.13, Node.js, common tools pre-installed
• Best for: Short tasks, quick scripts, file manipulation

Vercel Sandbox

Firecracker microVM managed by the Flapjack control plane. Each sandbox is an isolated Linux VM with its own filesystem and network.

• Startup: Sub-second with snapshots, ~5s without
• Persistence: Reliable filesystem persistence across tool calls
• Runtime: Amazon Linux 2023, Node.js 24, Python 3.13, sudo access
• Best for: Longer builds, git operations, tasks requiring strong isolation

Configuration

Dashboard

In your agent's settings, enable Computer and select a provider. The mode, scope, and size options depend on the provider.

API

curl -X PUT https://flapjack.chat/api/agents/{agentId}/computer \
  -H "Authorization: Bearer fj_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "enabled": true,
    "provider": "tensorlake",
    "mode": "ephemeral",
    "scope": "thread"
  }'

SDK

When sending messages, you can override computer settings per-message:

await fj.sendMessage(threadId, content, {
  computerOverrides: { enabled: true },
});

Tools

When computer is enabled, your agent gets three tools:

• computer_run — Execute a shell command. Returns stdout, stderr, and exit code.
• computer_write_file — Write content to a file path.
• computer_read_file — Read content from a file path.

The agent decides when to use these based on the conversation. You don't need to invoke them directly.

Lifecycle

• Ephemeral mode: A fresh sandbox is created for each conversation and destroyed when the conversation ends.
• Thread scope: The sandbox persists across messages within the same thread but not across threads.
• Cross-turn persistence: On Tensorlake, named sandboxes can be reconnected across turns. On Vercel, the sandbox ID is stored and the VM is reconnected via the API.