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| title: Minion Space | |
| emoji: 💬 | |
| colorFrom: yellow | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 5.32.0 | |
| app_file: app_with_mcp.py | |
| pinned: false | |
| license: mit | |
| short_description: minion running in space | |
| tags: | |
| - mcp-server-track | |
| - agent-demo-track | |
| An example chatbot based on minion framework(https://github.com/femto/minion), can handle arbitray type | |
| of queries, task-aware routing(if don't choose route, it will automatically choose proper route) | |
| ## Demo Videos | |
| 🎥 **[Minion-Space Demo: Solving Game 24 and Listing Files](https://youtu.be/FGjvGHKKxfo)** | |
| Watch this video to see minion-space in action, demonstrating how it can solve mathematical puzzles like the Game of 24 and perform file operations. | |
| 🎥 **[Minion-Space List-Files Demo](https://youtu.be/7neYqi_IQ18)** | |
| This video showcases the list-files functionality of minion-space, demonstrating how it can efficiently browse and manage file systems. | |
| 🎥 **[Plan Writing Long Novel](https://youtu.be/ULPvwcyhsI4)** | |
| This video demonstrates how to plan writing long novels using minion-space, showcasing its capability for creative writing planning and story structure development. | |
| 🎥 **[Plan Trip](https://youtu.be/nFK2PoL1SfE)** | |
| This video demonstrates how to plan trips using minion-space, showcasing its capability for travel planning, itinerary creation, and destination recommendations. | |
| ## Configuration Options | |
| ### API Type Configuration | |
| - **openai**: For OpenAI-compatible APIs (OpenAI, local models, etc.) | |
| - Use standard OpenAI API format | |
| - Set Base URL to your API endpoint | |
| - API Version is optional | |
| - **azure**: For Azure OpenAI Service | |
| - **Required**: Must specify API Version (e.g., "2024-06-01") | |
| - Set Base URL to your Azure endpoint | |
| - Uses Azure-specific authentication | |
| ### Route Selection | |
| - **Auto (empty)**: Automatically selects the most appropriate route based on query type | |
| - **Raw**: Direct LLM output without additional processing | |
| - **Native**: Standard minion processing | |
| - **CoT**: Chain of Thought reasoning for complex problems | |
| - **DCoT**: Dynamic Chain of Thought with adaptive reasoning | |
| - **Plan**: Planning-based approach for multi-step tasks | |
| - **Python**: Code execution environment for computational queries | |
| ### Preset Models | |
| - **gpt-4o**: Latest GPT-4 Omni model for general tasks | |
| - **gpt-4o-mini**: Lightweight version for faster responses | |
| - **gpt-4.1**: Advanced reasoning model | |
| - **o4-mini**: Optimized mini model | |
| - **Custom**: Configure your own API settings | |
| ### Additional Settings | |
| - **Enable Check**: Activates output verification and validation | |
| - **Query Type** (Python route only): Choose between `calculate`, `code_solution`, or `generate` | |
| - **Temperature**: Controls response creativity (0.0-2.0) | |
| - **Max Tokens**: Maximum response length (100-8000) |