Examples
- Examples
- Getting Started
- Agents
- Teams
- Workflows
- Applications
- Streamlit Apps
- Evals
Agent Concepts
- Reasoning
- Multimodal
- RAG
- 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
Performance
Performance on Agent Instantiation
Evaluation to analyze the runtime and memory usage of an Agent.
Code
"""Run `pip install openai agno memory_profiler` to install dependencies."""
from agno.agent import Agent
from agno.eval.performance import PerformanceEval
from agno.models.openai import OpenAIChat
def simple_response():
agent = Agent(
model=OpenAIChat(id="gpt-4o-mini"),
system_message="Be concise, reply with one sentence.",
)
response = agent.run("What is the capital of France?")
return response
simple_response_perf = PerformanceEval(
func=simple_response, num_iterations=1, warmup_runs=0
)
if __name__ == "__main__":
simple_response_perf.run(print_results=True, print_summary=True)
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