Is AgentOps — Observability for AI Agents free to use?

Yes. AgentOps — Observability for AI Agents is freely available on TokRepo. Check the Source & Thanks section on the asset page for the specific open-source license.

How do I install AgentOps — Observability for AI Agents?

Visit the asset page on TokRepo and click "Copy for agent" to get the installation instructions. Most assets can be installed with a single command.

Scripts2026年3月31日·1 分钟阅读

AgentOps — Observability for AI Agents

Name: AgentOps — Observability for AI Agents
Author: TokRepo精选

Python SDK for AI agent monitoring. LLM cost tracking, session replay, benchmarking, and error analysis. Integrates with CrewAI, LangChain, AutoGen, and more. 5.4K+ stars.

TokRepo精选 · Community

快速使用

先拿来用，再决定要不要深挖

这里应该同时让用户和 Agent 知道第一步该复制什么、安装什么、落到哪里。

pip install agentops

import agentops
agentops.init(api_key="YOUR_KEY")

# Your existing agent code — AgentOps auto-instruments LLM calls
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello"}],
)

agentops.end_session("Success")

介绍

AgentOps is a Python SDK for monitoring and observing AI agents in production. It auto-instruments LLM calls to track costs, latency, token usage, errors, and session replays. Integrates with CrewAI, LangChain, AutoGen, OpenAI Agents SDK, Agno, and CamelAI with one line of code. 5,400+ GitHub stars, MIT licensed.

Best for: Teams running AI agents in production who need cost control and debugging Works with: OpenAI, Anthropic, CrewAI, LangChain, AutoGen, Agno, CamelAI

Key Features

Auto-Instrumentation

Add agentops.init() and all LLM calls are automatically tracked — no code changes needed.

Cost Tracking

Real-time cost per session, per agent, per model. Set budget alerts.

Session Replay

Replay entire agent sessions step-by-step: prompts, responses, tool calls, errors.

Error Analysis

Automatic detection of hallucinations, infinite loops, and failed tool calls.

Benchmarking

Compare agent performance across models, prompts, and configurations.

Dashboard

Web dashboard for team-wide monitoring, analytics, and alerting.

FAQ

Q: What is AgentOps? A: A Python SDK for AI agent observability — cost tracking, session replay, benchmarking, and error analysis. Auto-instruments LLM calls. 5.4K+ stars.

Q: Does AgentOps add latency? A: Minimal — instrumentation is async and non-blocking. Typically <5ms overhead per LLM call.

🙏

来源与感谢

Created by AgentOps AI. Licensed under MIT. AgentOps-AI/agentops — 5,400+ GitHub stars