abstractmodels 0.1.0
Foundational data models for the AbstractFramework ecosystem
Requires Python: >=3.8
Keywords: abstractframework, models, data-models, schemas, types

# AbstractModels

**Foundational data models for the AbstractFramework ecosystem**

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## Overview

AbstractModels is a lightweight, dependency-free Python package that provides shared data structures and type definitions for the AbstractFramework ecosystem. By centralizing model definitions, it:

- **Eliminates circular dependencies** between framework packages
- **Ensures consistency** of data structures across components
- **Simplifies maintenance** with a single source of truth
- **Enables clean architecture** with clear separation of concerns

## Purpose

In a multi-package framework like AbstractFramework (which includes AbstractCode, AbstractFlow, AbstractRuntime, etc.), components often need to share common data structures. Without a central model repository, this leads to:

- Circular import dependencies
- Duplicate model definitions
- Version drift and inconsistencies
- Complex dependency graphs

AbstractModels solves these issues by serving as the foundational layer that all other packages can depend on without creating cycles.

## Installation

```bash
pip install abstractmodels
```

## Usage

```python
from abstractmodels import __version__

print(f"AbstractModels version: {__version__}")
```

As the framework evolves, models will be added to represent various entities:

```python
# Future usage examples (not yet implemented)
from abstractmodels.flow import FlowConfig, NodeDefinition
from abstractmodels.agent import AgentConfig, ProviderConfig
from abstractmodels.runtime import RuntimeConfig, ExecutionState
```

## Package Structure

```
abstractmodels/
├── __init__.py          # Package initialization and version info
├── flow.py              # (Future) Flow and node models
├── agent.py             # (Future) Agent and provider models
├── runtime.py           # (Future) Runtime and execution models
└── common.py            # (Future) Common utilities and base classes
```

## Design Principles

1. **Zero dependencies**: No external dependencies to avoid dependency hell
2. **Lightweight**: Minimal overhead, fast imports
3. **Type-safe**: Full type hints for IDE support and static analysis
4. **Immutable where possible**: Prefer frozen dataclasses for safety
5. **Well-documented**: Clear docstrings and examples
6. **Backwards compatible**: Semantic versioning and deprecation warnings

## Development Status

AbstractModels is in early development (v0.1.0). The initial release establishes the package structure and dependency-free foundation. Model definitions will be added incrementally as the AbstractFramework ecosystem matures.

## Contributing

Contributions are welcome! When adding new models:

- Keep the package dependency-free (use only Python stdlib)
- Add comprehensive docstrings with examples
- Use type hints for all public APIs
- Follow snake_case naming conventions
- Keep files focused and under 600 lines

## Related Packages

AbstractModels is part of the AbstractFramework ecosystem:

- **AbstractCode**: LLM agent framework with tool support
- **AbstractFlow**: Visual workflow and flow-based programming
- **AbstractRuntime**: Execution runtime for workflows and agents

## License

MIT License - see LICENSE file for details

## Version History

### 0.1.0 (2026-01-08)
- Initial release
- Package structure and foundation
- Zero-dependency architecture established