AgentOps is a developer platform designed to enhance the testing, debugging, and monitoring of AI agents. It offers tools that provide comprehensive observability into AI agent operations, enabling developers to build more reliable and efficient agents.
Key features app of AgentOps include:
- Visualization: Visually track events such as Large Language Model (LLM) calls, tool usage, and multi-agent interactions, providing a clear understanding of agent behavior.
- Time Travel Debugging: Rewind and replay agent runs with point-in-time precision, facilitating detailed analysis and troubleshooting.
- Debugging and Auditing: Maintain a comprehensive data trail of logs, errors, and prompt injection attacks from prototype to production, ensuring transparency and security.
- Cost Tracking: Monitor and visualize agent spending with up-to-date price monitoring, helping manage expenses associated with LLM usage.
- Fine-Tuning: Fine-tune specialized LLMs more cost-effectively on saved completions, enhancing model performance.
AgentOps integrates seamlessly with various AI frameworks and models, including CrewAI, LangChain, AutoGen, and others, making it adaptable to different development environments.
Developers can get started with AgentOps by installing its Python SDK using the command pip install agentops. The platform offers a free tier for up to 1,000 events, with scalable pricing options for higher usage needs.
