Agno is a lightweight library for building Agents with memory, knowledge, tools and reasoning.

Developers use Agno to build Reasoning Agents, Multimodal Agents, Teams of Agents and Agentic Workflows. Agno also provides a beautiful UI to chat with your Agents and tools to monitor and evaluate their performance.

Here’s an Agent that researches and writes a report on a stock, reasoning through each step:

reasoning_finance_agent.py
from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.tools.reasoning import ReasoningTools
from agno.tools.yfinance import YFinanceTools

agent = Agent(
    model=Claude(id="claude-3-7-sonnet-latest"),
    tools=[
        ReasoningTools(add_instructions=True),
        YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True, company_news=True),
    ],
    instructions=[
        "Use tables to display data",
        "Only output the report, no other text",
    ],
    markdown=True,
)
agent.print_response("Write a report on NVDA", stream=True, show_full_reasoning=True, stream_intermediate_steps=True)

Here's the Reasoning Agent in action

Key features

Agno is simple, fast and model-agnostic. Here are some key features:

  • Model Agnostic: Agno Agents can connect to 23+ model providers, no lock-in.
  • Lightning Fast: Agents instantiate in ~2μs on average (10,000x faster than LangGraph) and use ~3.75Kib memory on average (50x less than LangGraph) (see benchmarks).
  • Reasoning is a first class citizen: Make your Agents “think” and “analyze” using Reasoning Models, ReasoningTools or our custom CoT+Tool-use approach.
  • Natively Multi Modal: Agno Agents are natively multi modal, they can take in text, image, audio and video and generate text, image, audio and video as output.
  • Advanced Multi Agent Architecture: Agno provides an industry leading multi-agent architecture with 3 different modes: route, collaborate and coordinate.
  • Agentic RAG using Hybrid Search + Reranking: Give your Agents access to domain knowledge using one of 20+ vector databases. Get access to state-of-the-art Agentic search that uses hybrid search with re-ranking. Fully async and highly performant.
  • Long-term Memory & Session Storage: Agno provides plug-n-play Storage & Memory drivers that give your Agents long-term memory and session storage.
  • Structured Outputs: Agno Agents can return fully-typed responses using model provided structured outputs or json_mode.
  • Monitoring: Monitor agent sessions and performance in real-time on agno.com.

Getting Started

If you’re new to Agno, start by building your first Agent, chat with it on the playground and finally, monitor it on agno.com.

After that, checkout the Examples Gallery and build real-world applications with Agno.

Dive deeper

Agno is a battle-tested framework with a state-of-the-art reasoning and multi-agent architecture, checkout the following guides to dive-in: