https://github.com/cyberark/agentwatch
A powerful AI observability framework that provides comprehensive insights into agent interactions across platforms, enabling developers to monitor, analyze, and optimize AI-driven applications with minimal integration effort.
https://github.com/cyberark/agentwatch
agent agentic agentic-ai ai cybersecurity large-language-models llm llm-framework llm-observability llm-tools machine-learning monitoring observability security
Last synced: 6 months ago
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A powerful AI observability framework that provides comprehensive insights into agent interactions across platforms, enabling developers to monitor, analyze, and optimize AI-driven applications with minimal integration effort.
- Host: GitHub
- URL: https://github.com/cyberark/agentwatch
- Owner: cyberark
- License: apache-2.0
- Created: 2025-03-26T10:01:05.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-05-13T13:04:39.000Z (8 months ago)
- Last Synced: 2025-05-13T14:26:59.242Z (8 months ago)
- Topics: agent, agentic, agentic-ai, ai, cybersecurity, large-language-models, llm, llm-framework, llm-observability, llm-tools, machine-learning, monitoring, observability, security
- Language: Python
- Homepage: https://www.cyberark.com
- Size: 4.84 MB
- Stars: 75
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Security: SECURITY.MD
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README
agentwatch
Platform-Agnostic Agentic AI Runtime Observability Framework
## 🌟 Overview
agentwatch is a cutting-edge observability framework designed to provide deep insights into AI agent interactions across diverse platforms and frameworks. By seamlessly intercepting, logging, and analyzing interactions, agentwatch empowers developers to understand and optimize their AI-driven applications with unprecedented visibility.
## ✨ Key Features
- **A One-liner Observability Framework**: Get instant insights with just a single import
- **Comprehensive Interaction Tracking**: Monitor LLM and tool calls in real-time
- **Advanced Visualization**: Generate intuitive graphs for in-depth analysis
- **Detailed Metadata Capture**: Log tool inputs, arguments, and performance metrics
- **Multi-Framework Support**: Compatible with various AI development frameworks
- **MCP Support**: Tracks tool calls over remote MCP servers (HTTP/SSE only atm)
## 🚀 Supported Frameworks
- Langgraph
- Autogen
- ...
- Any other* framework or library which uses an LLM :D
We're working on updating our models to match the various providers - stay tuned!
## 📦 Prerequisites
To ensure compatibility with agentwatch, your application must be written in Python. The visualization UI will be built locally on your endpoint using npm,
so make sure you have the following installed:
- Python 3.11+
- npm
## 🔧 Installation
Install agentwatch directly from GitHub:
```bash
pip install git+https://github.com/cyberark/agentwatch.git
```
## 🖥️ Quick Start
1. Import agentwatch in your main module:
```python
import agentwatch
```
2. Ensure your entry point is within a `__main__` block:
```python
if __name__ == "__main__":
# Your code execution starts here
```
3. Launch the UI:
```bash
agentwatch ui
# (Take note this will open a new tab in your browser)
```
Run your main module - and AI agent interactions will now be automatically tracked and monitored in the UI!
## 📌 Examples
We've included a few examples under the [examples/](https://github.com/cyberark/agentwatch/tree/main/examples) folder.
To use the examples, clone this repository, and follow these steps:
1. Install python dependencies using poetry. If you don't have Poetry installed, get it [here](https://python-poetry.org/)
```bash
poetry install --with dev
```
2. Run the UI
```bash
./run_ui.sh
```
3. Run one of the examples under examples/. Don't forget to set the necessary API keys in the [.env](https://pypi.org/project/python-dotenv/) file
```bash
poetry run python examples/langgraph_example.py
```
## 📚 Documentation
For comprehensive guides and detailed usage instructions, visit our [GitHub Wiki](https://github.com/cyberark/agentwatch/wiki).
## 🤝 Contributing
We welcome contributions! Please review our [CONTRIBUTING.md](https://github.com/cyberark/agentwatch/blob/main/CONTRIBUTING.md) for guidelines on how to get involved.
## 📄 License
agentwatch is released under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0).
## 📧 Contact
Have questions or suggestions? Reach out to us through LinkedIn: [Shai Dvash](https://www.linkedin.com/in/shaidv/) or join our [Discord Community](https://discord.gg/Zt297RAK).
## 🌈 Powered By CyberArk
A project from CyberArk, dedicated to advancing AI observability and security.