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Deploy nanobot on Sealos

A self-hosted AI agent with a browser workspace, persistent conversations, tools, memory, and scheduled tasks.

AI
Launch a private nanobot AI workspace with one-click deployment.Keep models, prompts, and workflow data in your own Sealos environment.Scale GPU or CPU resources as your AI workload grows.Use an open-source template without managing Kubernetes YAML.
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Why deploy on Sealos

Sealos makes deploying any app effortless, secure, and production-ready. From one-click launch to ongoing operations, we handle the heavy lifting so you can focus on what matters.

One-Click Deploy
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Compute
Networking
Storage
Security
Observability
Your Application is Live

One-Click Deployment

Deploy any app template in seconds. No compose setup, manual configure, and go live.

Managed Kubernetes Reliability

Built on Sealos Managed Kubernetes for high availability, auto-scaling, and self-healing by default.

Automatic HTTPS & Security

Every deployment includes a secure domain with automatic SSL. We handle certificates and text protection for you.

Persistent Storage

Attach persistent volumes with ease. Your data stays safe, durable, and always accessible.

Scale when needed

Adjust resources as your app grows, no downtime required.

You Get the Whole Stack

Sealos provisions and connects every resource your application needs. Everything is ready to use.

One-click, fully provisionedSecure by defaultProduction ready

App Service

Your application is running and ready to serve requests.

Public HTTPS URL

Secure, global endpoint to access your application.

Database

Managed database instance for your application.

Persistent Volume

Durable storage for uploads and application data.

Environment Variables

Configuration and secrets injected securely into your app.

Logs & Metrics

Centralized logs and basic metrics are enabled.

README

README.md

Deploy and Host nanobot on Sealos

nanobot is a self-hosted AI agent with a browser workspace, tools, memory, and scheduled tasks. This template deploys the nanobot gateway and its bundled WebUI with persistent storage on Sealos Cloud.

nanobot website

About Hosting nanobot

The gateway serves the WebUI and authenticated WebSocket connections together on port 8765. A single instance stores its configuration, conversations, memory, generated files, and automation state on a 1Gi persistent volume.

The template initializes the configuration once, prepares the tokenizer cache before startup, and preserves settings edited in the WebUI across restarts. Browser access uses the password you set in the deployment form. File tools start with workspace restrictions enabled.

Common Use Cases

  • Personal AI workspace: Keep separate conversations for research, writing, and project tasks.
  • File assistance: Ask the agent to create, inspect, and edit files in its persistent workspace.
  • Repeatable tasks: Use built-in tools, skills, and scheduled automations for recurring work.
  • Chat integrations: Connect supported chat channels with your own platform credentials.

Dependencies for nanobot Hosting

The template includes the Python runtime, bundled WebUI, built-in tools, and persistent storage. Provide an API key, an OpenAI-compatible API base URL, and an exact model ID from the same provider.

Deployment Dependencies

Implementation Details

ComponentConfiguration
Releasenanobot v0.3.0
RuntimeOne gateway with the bundled WebUI, running as UID 1000
Storage1Gi at /home/nanobot/.nanobot
Configuration/home/nanobot/.nanobot/config.json, initialized on first start
Model providerOpenAI-compatible endpoint selected by the deployment inputs
Public entryHTTPS WebUI with WebSocket support on port 8765
Health endpointContainer-local port 18790
Validated low-load limitsGateway: 200m CPU / 256Mi memory; initialization: 100m CPU / 128Mi memory

The image ghcr.io/yangchuansheng/sealos-template-init:nanobot-v0.3.0 is built from the unmodified upstream v0.3.0 Dockerfile and source. The selected upstream deployment stores data in local files; this template provisions the corresponding persistent volume. Keep one replica for this shared local-state runtime.

Why Deploy nanobot on Sealos?

Sealos provides Kubernetes scheduling, persistent storage, HTTPS routing, and pay-as-you-go resources for the gateway. After deployment, use the Canvas AI dialog or resource cards to adjust resources and inspect logs.

Deployment Guide

  1. Open the nanobot template and click Deploy Now.
  2. Enter your provider's API key, API base URL, and model ID. Include the provider's version path in the URL, such as https://api.openai.com/v1.
  3. Fill in the required web_token (WebUI login password) with your own strong password, and save it privately before deploying.
  4. Wait for deployment to complete, typically 2-3 minutes. The Canvas shows the gateway and its persistent storage after deployment.
  5. Open the application's public URL, enter your web_token value in Password, and click Connect. This shared-password flow opens the WebUI directly.
  6. Start a New topic and send a short message to verify your model. Ask the agent to create and read a small file to verify its workspace tools.

Configuration

Use Settings → Models to manage model settings and Settings → Channels for chat integrations. Configuration changes are stored on the persistent volume; follow any restart notice shown by the WebUI. Deployment provider values remain available through OPENAI_API_KEY, OPENAI_API_BASE, and NANOBOT_MODEL.

The browser remembers its access password locally. Enter the same deployment password when connecting from a new browser or after clearing browser storage. Its current value is available as NANOBOT_WEB_TOKEN in the gateway resource card. The gateway uses a shared access password, with each trusted user able to operate the same agent workspace.

Remote installation of optional Python packages starts disabled. The default image includes WhatsApp support; other channels may require an image rebuild with the upstream NANOBOT_CHANNELS build argument before enabling them.

Troubleshooting

  • Password rejected: Copy the current NANOBOT_WEB_TOKEN value from the gateway resource card and enter it without extra whitespace.
  • Model request fails: Confirm the API key, base URL, and exact model ID belong to the same provider, then check its available quota.
  • Gateway is starting: Inspect the initialization and gateway logs. The first run prepares the tokenizer cache before serving requests.
  • More demanding workloads: Increase CPU, memory, or persistent storage from the Canvas resource card as conversations, attachments, and tool workloads grow.

License

This Sealos template follows the templates repository license. nanobot is licensed under the MIT License.

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