Examples
- Examples
- Getting Started
- Agents
- Teams
- Workflows
- Applications
- Streamlit Apps
- Evals
Agent Concepts
- Reasoning
- Multimodal
- RAG
- User Control Flows
- Knowledge
- Memory
- Async
- Hybrid Search
- Storage
- Tools
- Vector Databases
- Context
- Embedders
- Agent State
- Observability
- Miscellaneous
Models
- Anthropic
- AWS Bedrock
- AWS Bedrock Claude
- Azure AI Foundry
- Azure OpenAI
- Cerebras
- Cerebras OpenAI
- Cohere
- DeepInfra
- DeepSeek
- Fireworks
- Gemini
- Groq
- Hugging Face
- IBM
- LM Studio
- LiteLLM
- LiteLLM OpenAI
- Meta
- Mistral
- NVIDIA
- Ollama
- OpenAI
- Perplexity
- Together
- XAI
- Vercel
Performance
Performance with Teams
Learn how to analyze the runtime and memory usage of an Agno Team.
Code
"""Run `pip install agno openai` to install dependencies."""
from agno.agent import Agent
from agno.eval.performance import PerformanceEval
from agno.models.openai import OpenAIChat
from agno.team.team import Team
team_member = Agent(model=OpenAIChat(id="gpt-4o"))
def instantiate_team():
return Team(members=[team_member])
instantiation_perf = PerformanceEval(func=instantiate_team, num_iterations=1000)
if __name__ == "__main__":
instantiation_perf.run(print_results=True, print_summary=True)
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