An interactive web-based tutorial for learning Pantheon-CLI, the first fully open-source, infinitely extensible scientific "vibe analysis" framework built on Python.
This tutorial provides a comprehensive, hands-on learning experience for Pantheon-CLI through an interactive web interface. Learn how to use this revolutionary AI-powered scientific analysis tool that combines mixed programming capabilities with PhD-level scientific assistance.
Pantheon-CLI is a groundbreaking command-line tool that redefines how scientists interact with data in the AI era:
- Mixed Programming Environment: Seamlessly combine Python, R, Julia, and natural language in one session
- AI-Powered Scientific Assistant: PhD-level intelligent analysis capabilities for complex research tasks
- Complete Data Privacy: All computation runs locally with no data upload requirements
- Open Source & Extensible: Built on Python with full transparency and unlimited customization
- What is Pantheon-CLI and why it matters
- Core architecture and capabilities
- Getting started guide
- System requirements and prerequisites
- Platform-specific installation guides (Windows, macOS, Linux)
- Model configuration and knowledge base setup
- Verification and troubleshooting
- System commands and navigation
- Dialog-based interactions
- Program command execution (Python, R, Julia, Shell)
- General-purpose and domain-specific tools
- Advanced tool configurations and customization
- Performance optimization techniques
- Social behavior analysis
- Financial and customs data processing
- Single-cell RNA sequencing analysis
- Molecular docking and computational biology
- Mixed Python/R workflows
- Common installation and runtime errors
- Debugging techniques and tools
- Frequently asked questions
# Python code
%import pandas as pd
%data = pd.read_csv('example.csv')
# R code in the same session
>summary(data)
>plot(data$column1, data$column2)
# Julia for high-performance computing
]using Statistics
]mean(data)
# Shell commands
!ls -la
!cat results.txt- Natural language analysis requests
- Automatic method selection and optimization
- Intelligent error diagnosis and fixes
- Context-aware scientific guidance
- Complete offline operation support
- Local large language model execution
- Zero data upload requirements
- Enterprise-grade security compliance
-
Installation
pip install pantheon-cli
-
Verify Installation
pantheon-cli --version
-
Start Learning
- Begin with the Introduction section
- Follow the Installation Guide for detailed setup
- Practice with Basic Commands
- Explore Advanced Features
- Study Real Cases for practical applications
- Frontend: Vue.js 3 with Composition API
- Styling: Tailwind CSS for responsive design
- Terminal Simulation: xterm.js for interactive command-line experience
- Content Management: Markdown-based documentation with YAML navigation
- Internationalization: Support for English and Chinese languages
- Node.js 16+ and npm
- Modern web browser
# Clone and install dependencies
npm install
# Start development server
npm run dev
# Build for production
npm run buildsrc/
├── components/ # Vue components
├── content/ # Tutorial content (en/zh)
├── terminal/ # Terminal examples (en/zh)
├── config/ # Navigation and configuration
├── stores/ # Pinia state management
└── styles/ # Global styles
This tutorial is part of the Pantheon-CLI ecosystem. Contributions are welcome for:
- Content improvements and translations
- Bug fixes and feature enhancements
- New tutorial examples and use cases
- Documentation updates
- Pantheon-CLI GitHub: https://github.com/aristoteleo/pantheon-cli
- Tutorial Issues: Report bugs and request features
- Community: Join discussions and get support
This tutorial is open source and available under the same license as Pantheon-CLI.
Ready to revolutionize your data analysis workflow? Start with the Introduction and discover the power of AI-driven scientific computing!