OmniBot

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    <img alt="OpenOmniBot" src="docs/pic/OmniBot.png" width="50%">
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  <a href="README.md"><b>English</b></a> |
  <a href="README.zh-CN.md"><b>简体中文</b></a>
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Your On-Device AI Assistant
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<a href="#use-cases"><b>Demo</b></a>
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<a href="#quick-start"><b>Quick Start</b></a>
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<a href="https://github.com/omnimind-ai/OpenOmniBot/releases"><b>Release</b></a>
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<a href="https://github.com/omnimind-ai/OpenOmniBot/issues"><b>Issues</b></a>
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> OmniBot runs directly on your Android device and combines chat, agent tools, local workspaces, and system integrations in one app.
> 🎉 Our iOS & macOS version: [ViaVera](https://github.com/omnimind-ai/ViaVera)

OmniBot is an on-device AI agent built with native Android Kotlin and Flutter. Instead of stopping at chat, it focuses on the full loop of **understand -> decide -> execute -> reflect**.

<h2 id="core-capabilities">Core Capabilities</h2>

- **Extensible tool ecosystem**: Skills, Alpine environment, browser access, MCP, and Android system-level tools.
- **System-level actions**: Supports scheduled tasks, alarms, calendar creation/query/update, and audio playback control.
- **Personal context**: Query authorized calendars, contacts, notifications, app usage, location, media, documents, SMS and call history without root, and manage calendar events and contacts.
- **Memory system**: Short-term and long-term memory with embedding support.
- **Productivity tools**: Read and write files, browse the workspace, use the browser, and access the terminal.

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  <img src="docs/tutorial/example.png" alt="Example" />
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<details>
<summary id="quick-start"><strong>Quick Start</strong></summary>

### Configure the app

Open the settings page from the left sidebar:

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  <img src="docs/tutorial/two.png" alt="Configure AI capabilities" width="260" />
  <img src="docs/tutorial/three.png" alt="Configure AI providers" width="420" />
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Then open the scenario model settings:

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  <img src="docs/tutorial/four.png" alt="Configure AI models" width="260" />
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Note: `Memory embedding` requires an embedding model. For the best overall experience, the other scenarios should use multimodal or vision-capable models whenever possible.

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