lion-core 0.6.0

A core package for the Lion framework.

🦁 Lion-Core: Unleash the Power of AI Development

Lion-Core is a lightweight yet powerful Python library designed to serve as a foundational framework for machine learning, artificial intelligence, workflow automation, scientific computing, and advanced data management.

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🌟 Highlights

Feature	Description
🧘‍♂️ Minimal Dependencies	Built with only Pydantic and Pandas, ensuring a lightweight and maintainable codebase
🧩 Extensible Architecture	Modular design adaptable to a wide range of computational needs
⚡ Performance-Focused	Optimized data structures and algorithms for efficient large-scale data processing
🛡️ Type-Safe	Leveraging Pydantic for robust type checking and data validation

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🚀 Features

📊 Advanced Data Structures

• Pile: A flexible container combining the best of lists and dictionaries, offering efficient access and powerful querying capabilities.
• Progression: An ordered sequence container designed for high-performance operations on large datasets.
• Flow: A versatile structure for managing complex workflows and data pipelines.

🧱 Core Components

• Element: A foundational class serving as the building block for creating modular and composable components.
• Node: An extension of Element, designed for creating interconnected components in a graph-like structure.
• Exchange: A system for managing asynchronous communication between components.

🛠️ Utility Systems

• Converter System: A flexible framework for seamless data conversion between various formats.
• Form and Validator System: Dynamic tools for creating and validating complex data structures and workflows.
• Rule System: A powerful mechanism for defining and enforcing business logic and data constraints.

💬 Communication Framework

• Message System: A robust inter-component messaging system, facilitating the development of distributed and microservices-based applications.
• Mail Manager: An advanced system for managing asynchronous communication across different components and processes.

🧠 AI and Machine Learning Tools

• Action System: A framework for defining and executing AI actions and function calls.
• Session Management: Tools for managing conversational contexts and multi-turn interactions in AI systems.

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🏗️ Architecture

Lion-Core's architecture is designed to be both powerful and flexible, allowing developers to build complex AI and machine learning applications with ease. The following diagram illustrates the high-level architecture and key components of the library:

flowchart TB
    subgraph Lion-Core
        direction TB
        Core[Core Components]
        Data[Data Structures]
        Comm[Communication]
        Util[Utility Systems]
        AI[AI and ML Tools]
    end

    subgraph CoreComponents
        direction LR
        Core --> Element
        Core --> Node
        Element --> |extends| Node
    end

    subgraph DataStructures
        direction LR
        Data --> Pile
        Data --> Progression
        Data --> Flow
    end

    subgraph Communication
        direction LR
        Comm --> MessageSystem
        Comm --> MailManager
        Comm --> Exchange
    end

    subgraph UtilitySystems
        direction LR
        Util --> ConverterSystem
        Util --> FormValidator[Form & Validator]
        Util --> RuleSystem
    end

    subgraph AIMLTools
        direction LR
        AI --> ActionSystem
        AI --> SessionManagement
    end

    %% Relationships
    Node -.-> Pile
    Node -.-> Progression
    Node -.-> Flow
    MessageSystem --> MailManager
    MailManager --> Exchange
    FormValidator --> RuleSystem
    ActionSystem --> SessionManagement

    %% Styling
    classDef coreColor fill:#f9d,stroke:#333,stroke-width:2px;
    classDef dataColor fill:#afd,stroke:#333,stroke-width:2px;
    classDef commColor fill:#ddf,stroke:#333,stroke-width:2px;
    classDef utilColor fill:#fda,stroke:#333,stroke-width:2px;
    classDef aiColor fill:#dff,stroke:#333,stroke-width:2px;
    classDef mainColor fill:#f5f5f5,stroke:#333,stroke-width:4px;

    class Core,Element,Node coreColor;
    class Data,Pile,Progression,Flow dataColor;
    class Comm,MessageSystem,MailManager,Exchange commColor;
    class Util,ConverterSystem,FormValidator,RuleSystem utilColor;
    class AI,ActionSystem,SessionManagement aiColor;
    class Lion-Core mainColor;

Each component can be used independently or in combination with others, enabling modular and scalable application development.

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📦 Installation

To install the latest stable version from PyPI:

pip install lion-core

For the latest development version:

pip install git+https://github.com/lion-agi/lion-core.git

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🛠️ Development Setup

Click to expand

1. Clone the repository:

   git clone https://github.com/lion-agi/lion-core.git
   cd lion-core
   

2. Set up a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
   

3. Install dependencies:

   pip install -e .[dev]
   

4. Set up pre-commit hooks:

   pre-commit install
   

5. Run tests:

   pytest --asyncio-mode=auto --maxfail=1 --disable-warnings tests/
   

6. Check code style:

   black --check .
   isort --check-only .
   

7. (Optional) Run pre-commit hooks manually:

   pre-commit run --all-files
   

Note: Pre-commit hooks will run automatically on git commit. If any checks fail, the commit will be aborted. Fix the issues and try committing again.

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📚 Documentation

We are continuously improving our documentation to help you get the most out of Lion-Core. Here's what's available:

Type	Description	Location
📘 Reference Docs	API references and core concepts	API References
💻 Inline Docs	Detailed docstrings for all components	Within source code
📓 Examples & Tutorials	(Coming Soon) Jupyter notebooks	examples/ directory
🌐 Online Docs	(Planned) Comprehensive searchable documentation	TBA

Our reference documentation includes:

• Comprehensive API documentation for all modules
• In-depth explanations of key concepts and data structures
• Usage guidelines and best practices

Stay tuned for updates as we continue to expand our documentation!

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🛣️ Roadmap

As we work towards stable releases, our focus includes:

• Enhancing core abstractions and data structures
• Expanding the converter system for broader compatibility
• Refining workflow automation processes
• Developing additional scientific computing utilities
• Improving documentation and adding comprehensive examples

We're committed to evolving Lion-Core to meet the needs of our community. Your feedback and contributions are crucial in shaping the future of this library.

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🤝 Contributing

We welcome contributions from the community! Whether it's bug fixes, feature additions, or documentation improvements, your input is valuable. Please check our CONTRIBUTING.md for guidelines on how to contribute.

If you're planning to work on a significant change, please open an issue first to discuss your ideas. This helps ensure your time is well spent and that the changes align with the project's direction.

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📄 License

Lion-Core is released under the Apache License 2.0. See the LICENSE file for details.

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📬 Contact & Community

• 🐛 Issues & Feature Requests: GitHub Issues
• 💬 Discussions & Support: Join our Discord Server

We're building a community of developers, researchers, and AI enthusiasts. Join us in shaping the future of AI development!

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Note: Lion-Core is an extraction and refinement of core components from the larger lionagi project. After reaching version 0.1.0, development will continue on Lion-Core while also informing a rewrite of the lionagi library.

Thank you for your interest in Lion-Core. Together, let's unleash the power of AI development! 🦁✨