Nanobot Configuration and Security

1. The core config mindset

Nanobot is simpler than some larger agent platforms, but the same rule still applies:

separate installation, provider setup, and runtime behavior in your head

Most early problems come from mixing those layers together.

2. What to configure first

In practical order, focus on:

1. Python environment and package install,
2. model credentials or provider connection,
3. local tool access,
4. optional UI or bridge surfaces,
5. containerization only after the local flow works.

That sequence avoids debugging Docker, networking, and agent logic all at once.

3. Security posture

Even lightweight agents are still privileged software once they can:

• read local files,
• call external services,
• execute tools,
• write outputs back into your environment.

So the safe operating posture is still:

• use separate API keys for evaluation,
• prefer non-production data first,
• restrict filesystem and secret exposure,
• only enable extra integrations one at a time.

4. Day-two operations

Once Nanobot works on one machine, the next practical questions are usually:

• should this stay a local developer tool,
• should it run in Docker,
• which tools and integrations are actually necessary,
• who owns the credentials and logs.

The repo's container files make it clear that the maintainers expect real operational use, not only experimentation.

5. Practical advice

For most teams, the safest rollout is:

1. prove the local install,
2. test with low-risk prompts and datasets,
3. document the exact provider and tool settings,
4. move to containers only when the working baseline is stable.