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Agno

High-performance, model-agnostic Python framework for building, running, and managing production AI agents at scale.

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평점★ 4.8
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Agno

Agno (formerly Phidata) is a production-grade Python framework for building multi-modal, multi-provider AI agents. It benchmarks at ~2 µs agent creation time and ~3.75 KiB memory per agent — making it one of the fastest agent runtimes available.

Key Features

  • Model-agnostic — works with OpenAI, Anthropic, Google Gemini, Groq, Cohere, local Ollama, and 40+ providers
  • Multi-modal — agents natively handle text, image, audio, and video inputs
  • Built-in memory — short and long-term memory via SQLite, PostgreSQL, or Redis
  • Knowledge bases — attach structured knowledge from PDFs, URLs, databases, and vector stores
  • Teams of agents — coordinate multiple agents in parallel or sequential workflows
  • Monitoring — first-class integration with Agno's own monitoring dashboard and OpenTelemetry
  • Minimal boilerplate — define a complete agent with tools in ~10 lines

Quick Start

pip install agno
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.duckduckgo import DuckDuckGoTools

agent = Agent(
    model=OpenAIChat(id="gpt-4o"),
    tools=[DuckDuckGoTools()],
    markdown=True,
)
agent.print_response("What are the top AI papers of 2026?", stream=True)

Install via ai-supply

npx ai-supply add agno-agent-framework

Curated mirror of the open-source Agno (MPL-2.0). Get it from the source.

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