Agno

Agno is a modern AI agent framework for building intelligent agents, teams, and workflows. AgentOps provides automatic instrumentation to track all Agno operations including agent interactions, team coordination, tool usage, and workflow execution.

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Installation

Install AgentOps and Agno:

pip install agentops agno 

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Setting Up API Keys

You’ll need API keys for AgentOps and your chosen LLM provider:

• AGENTOPS_API_KEY: From your AgentOps Dashboard
• OPENAI_API_KEY: From the OpenAI Platform (if using OpenAI)
• ANTHROPIC_API_KEY: From Anthropic Console (if using Claude)

Set these as environment variables or in a .env file.

export AGENTOPS_API_KEY="your_agentops_api_key_here"
export OPENAI_API_KEY="your_openai_api_key_here"
export ANTHROPIC_API_KEY="your_anthropic_api_key_here"  # Optional

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Quick Start

import os
from dotenv import load_dotenv

# Load environment variables
load_dotenv()


from agno.agent import Agent
from agno.team import Team
from agno.models.openai import OpenAIChat

# Initialize AgentOps
import agentops
agentops.init(api_key=os.getenv("AGENTOPS_API_KEY"))

# Create and run an agent
agent = Agent(
    name="Assistant",
    role="Helpful AI assistant",
    model=OpenAIChat(id="gpt-4o-mini")
)

response = agent.run("What are the key benefits of AI agents?")
print(response.content)

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AgentOps Integration

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Basic Agent Tracking

AgentOps automatically instruments Agno agents and teams:

import agentops
from agno.agent import Agent
from agno.team import Team
from agno.models.openai import OpenAIChat

# Initialize AgentOps - this enables automatic tracking
agentops.init(api_key=os.getenv("AGENTOPS_API_KEY"))

# Create agents - automatically tracked by AgentOps
agent = Agent(
    name="Assistant",
    role="Helpful AI assistant",
    model=OpenAIChat(id="gpt-4o-mini")
)

# Create teams - coordination automatically tracked
team = Team(
    name="Research Team", 
    mode="coordinate", 
    members=[agent]
)

# All operations are automatically logged to AgentOps
response = team.run("Analyze the current AI market trends")
print(response.content)

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What Gets Tracked

AgentOps automatically captures:

• Agent Interactions: All agent inputs, outputs, and configurations
• Team Coordination: Multi-agent collaboration patterns and results
• Tool Executions: Function calls, parameters, and return values
• Workflow Steps: Session states, caching, and performance metrics
• Token Usage: Costs and resource consumption across all operations
• Timing Metrics: Response times and concurrent operation performance
• Error Tracking: Failures and debugging information

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Dashboard and Monitoring

Once your Agno agents are running with AgentOps, you can monitor them in the AgentOps Dashboard:

• Real-time Monitoring: Live agent status and performance
• Execution Traces: Detailed logs of agent interactions
• Performance Analytics: Token usage, costs, and timing metrics
• Team Collaboration: Visual representation of multi-agent workflows
• Error Tracking: Comprehensive error logs and debugging information

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Examples