A fast and minimal framework for building agentic systems using an Actor model to connect agents with traditional software systems in a flexible and scalable way.
One Minute Overview#
Agency is a Python library that provides an Actor model framework for creating agent-integrated systems. It offers an easy-to-use API that enables you to connect agents with traditional software systems in a flexible and scalable way, allowing you to develop any architecture you need. If you're looking to build a custom agent-based application, Agency might be for you.
Core Value: Provides a minimal foundation for developing agentic systems with sufficient flexibility and scalability.
Quick Start#
Installation Difficulty: Medium - Requires Python knowledge and understanding of basic networking and concurrency concepts
# Installation command
pip install agency
Is it suitable for my use case?
- ✅ Custom Agent Systems: When you need to create domain-specific or task-oriented agent applications
- ✅ Multi-Agent Collaboration: When multiple agents need to communicate and collaborate with each other
- ✅ AI-Software Integration: When you need to integrate AI-driven capabilities with existing software systems
- ❌ Simple Chatbots: If you only need basic chatbot functionality, Agency might be overkill
- ❌ Rapid Prototyping: If you're just trying to quickly validate an AI concept, this framework might be too heavy
Core Capabilities (Optional)#
1. Easy to Use API - Simplified Agent Definition#
- Straightforward class/method-based agent and action definition
- Up-to-date documentation and examples for reference
Actual Value: Developers can quickly define agent behaviors and interactions without needing deep knowledge of underlying implementation details
2. Performance and Scalability - High Concurrency Support#
- Supports multiprocessing and multithreading for concurrent processing
- AMQP support for networked agent systems
Actual Value: Can handle high-concurrency requests and support cross-network agent communication, suitable for building large-scale distributed agent systems
3. Observability and Control - Comprehensive Monitoring and Access Control#
- Action and lifecycle callbacks
- Access policies and permission callbacks
- Detailed logging
Actual Value: Developers can comprehensively monitor agent behavior, implement security policies, and ensure stable system operation
Technology Stack and Integration#
Development Language: Python Key Dependencies: AMQP support (like RabbitMQ) for network communication Integration Method: Library / Framework
Ecosystem and Extensions (Optional)#
- Agent Types: Supports various agent types including OpenAI agents, HuggingFace Transformers agents, and OS access agents
- Sample Applications: Includes complete demo application with Gradio UI
Maintenance Status#
- Development Activity: Moderately active - Has clear contribution guidelines and planned work, but update frequency not clearly specified
- Recent Updates: Recently updated with ongoing community contributions
- Community Response: Has community discussion and issue tracking system
Documentation and Learning Resources#
- Documentation Quality: Comprehensive - Includes API overview, sample code, and demo application
- Official Documentation: Provided through README and API overview sections
- Sample Code: Has complete demo application and sample code, including calculator agent examples