Agent Monitoring and Debugging with AgentOps

AgentOps provides session replays, metrics, and monitoring for AI agents.

At a high level, AgentOps gives you the ability to monitor LLM calls, costs, latency, agent failures, multi-agent interactions, tool usage, session-wide statistics, and more. For more info, check out the AgentOps Repo.

​

Installation

AgentOps works seamlessly with applications built using Autogen.

1. Install AgentOps

pip install agentops

2. Create an API Key: Create a user API key here: Create API Key

3. Configure Your Environment: Add your API key to your environment variables

AGENTOPS_API_KEY=<YOUR_AGENTOPS_API_KEY>

4. Initialize AgentOps

To start tracking all available data on Autogen runs, simply add two lines of code before implementing Autogen.

import agentops
agentops.init() # Or: agentops.init(api_key="your-api-key-here")

After initializing AgentOps, Autogen will now start automatically tracking your agent runs.

​

Features

• LLM Costs: Track spend with foundation model providers
• Replay Analytics: Watch step-by-step agent execution graphs
• Recursive Thought Detection: Identify when agents fall into infinite loops
• Custom Reporting: Create custom analytics on agent performance
• Analytics Dashboard: Monitor high level statistics about agents in development and production
• Public Model Testing: Test your agents against benchmarks and leaderboards
• Custom Tests: Run your agents against domain specific tests
• Time Travel Debugging: Save snapshots of session states to rewind and replay agent runs from chosen checkpoints.
• Compliance and Security: Create audit logs and detect potential threats such as profanity and PII leaks
• Prompt Injection Detection: Identify potential code injection and secret leaks

​

Autogen + AgentOps examples

• AgentChat with AgentOps Notebook
• More AgentOps Examples

​

Extra links

• 🐦 Twitter
• 📢 Discord
• 🖇️ AgentOps Dashboard
• 📙 Documentation