robotape 0.1.0

A lightweight agent framework

Lightweight Agent Framework

A minimalist, extensible framework for building autonomous agents with a focus on transparency and composability.

Overview

Lightweight Agent Framework (LAF) provides a simple yet powerful foundation for building autonomous agents that can think, act, and observe within a structured environment. With LAF, you can:

• Create agents that follow a clear think-act-observe cycle
• Record and replay agent interactions using the tape system
• Build complex workflows by composing multiple agents
• Persist and analyze agent execution history
• Extend functionality through a modular tool system

Key Features

• 🎯 Simple Core Concepts: Based on three fundamental operations - think, act, and observe
• 📼 Tape-Based History: Record every step of your agent's execution for analysis and debugging
• 🛠 Modular Tools: Easily extend agent capabilities through a flexible tool system
• 💾 Built-in Storage: Persist agent history with built-in SQLite support (expandable to other backends)
• 🔄 Async Support: Built with asyncio for efficient concurrent operations
• 🧪 Testing Ready: Comprehensive testing utilities and fixtures included

Quick Installation

pip install robotape

For development installation:

pip install robotape[dev]

Basic Usage

Here's a simple example of creating and running an agent:

from robotape.agents import SimpleAgent
from robotape.tape import Tape, StepType

# Create an agent and a tape
agent = SimpleAgent("my_agent")
tape = Tape()

# Add an initial thought
tape.append(Step(
    type=StepType.THOUGHT,
    content="I should search for information",
    metadata=StepMetadata(agent="my_agent", node="planning")
))

# Execute the agent
await agent.execute_step(tape.get_last_step())

Advanced Features

• Custom Agents: Extend BaseAgent to create specialized agents
• Tool Integration: Add new capabilities through the tool system
• Storage Backends: Built-in SQLite support, extensible to other databases
• Tape Management: Clone, branch, and analyze execution history
• Validation: Built-in parameter validation and error handling

Documentation

For detailed information, check out:

• Getting Started Guide
• Tape System Documentation
• Agent System Guide

Development

Clone and set up the development environment:

git clone https://github.com/yourusername/robotape.git
cd robotape
pip install -e ".[dev]"

Run tests:

pytest tests/ --cov=robotape

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.