# AgentScan
**Production-Grade, Enterprise-Ready, and Bleeding-Edge Multi-Agent Observability**
[](https://badge.fury.io/py/AgentScan)
[](https://travis-ci.com/yourusername/AgentScan)
[](LICENSE)
## Overview
AgentScan is a cutting-edge observability framework designed specifically for multi-agent systems. In the rapidly evolving landscape of AI and automation, monitoring, managing, and scaling agent-based systems have become crucial for enterprise success. AgentScan is built to be the best agent monitoring framework, ensuring your agents operate efficiently, securely, and at scale, no matter the complexity of your deployment.
## Key Benefits
### 🌟 **Production-Grade Observability**
AgentScan offers unparalleled visibility into your multi-agent systems, providing real-time metrics, alerts, and insights that are crucial for maintaining optimal performance in production environments. It’s built to handle the most demanding enterprise use cases, ensuring that your agents are always functioning as expected.
### 🚀 **Enterprise-Ready Integration**
Seamlessly integrate AgentScan into your existing infrastructure. Whether you're using Swarms, LangChain, AutoGen, or any other agent framework, AgentScan is designed to be fully compatible, making it the go-to observability solution for any multi-agent ecosystem.
### âš¡ **Unmatched Speed and Efficiency**
AgentScan is engineered for speed. With an architecture optimized for low-latency monitoring, you can trust that your agent systems will be observed and analyzed in real time, allowing for immediate detection and resolution of issues.
### 🔧 **Customizable and Extensible**
Tailor AgentScan to your specific needs with its highly modular design. Add custom metrics, integrate with your existing logging and alerting systems, and build on top of a framework that scales with your enterprise.
## Vision
At AgentScan, our vision is to become the industry standard for multi-agent observability. We aim to provide enterprises with the tools they need to monitor, manage, and optimize their agent systems, ensuring that they can scale their operations with confidence. Our goal is to be the most reliable, flexible, and efficient monitoring solution on the market, empowering businesses to harness the full potential of their multi-agent ecosystems.
## Installation
Installing AgentScan is as simple as running the following command:
```bash
pip install AgentScan
```
## Getting Started
Once installed, AgentScan can be easily integrated into your agent systems. Here's a quick guide to get you up and running:
### 1. Import AgentScan into Your Project
```python
from AgentScan import AgentScan
```
### 2. Initialize AgentScan
```python
# Initialize AgentScan with your preferred configurations
monitoring = AgentScan(config={
'framework': 'Swarms', # Replace with your agent framework
'log_level': 'INFO',
'alerts': True,
'custom_metrics': ['cpu_usage', 'memory_consumption']
})
```
### 3. Start Monitoring Your Agents
```python
# Start monitoring your agents in real time
monitoring.start()
```
### 4. Analyze and Optimize
Leverage AgentScan’ rich dashboard and analytics to gain deep insights into your multi-agent systems, identify bottlenecks, and optimize performance.
## Compatibility
AgentScan is designed to be framework-agnostic, meaning it can seamlessly integrate with any agent framework, including but not limited to:
- Swarms
- LangChain
- AutoGen
- Custom-built agent frameworks
If your framework is not listed, AgentScan provides a flexible API to ensure smooth integration.
## Contributing
We welcome contributions from the community. If you have ideas, bug reports, or improvements, feel free to submit an issue or a pull request. For major changes, please open an issue first to discuss what you would like to change.
## License
AgentScan is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.
## Contact
For enterprise support, custom integration services, or any other inquiries, please contact our team at [support@AgentScan.io](mailto:support@AgentScan.io).
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