Skip to main content

Agno: a lightweight library for building Multi-Agent Systems

Project description

Build multi-agent systems that learn.

Docs  •  Cookbook  •  Community  •  Discord

What is Agno?

A framework for building multi-agent systems that learn and improve with every interaction.

Most agents are stateless. They reason, respond, forget. Session history helps, but they're exactly as capable on day 1000 as they were on day 1.

Agno agents are different. They remember users across sessions, accumulate knowledge across conversations, and learn from decisions. Insights from one user benefit everyone. The system gets smarter over time.

Everything runs in your cloud. Your data never leaves your environment.

Quick Example

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=SqliteDb(db_file="tmp/agents.db"),
    learning=True,
)

One line. Your agent now remembers users, accumulates knowledge, and improves over time.

Production Stack

Agno provides the complete infrastructure for building multi-agent systems that learn:

Layer What it does
Framework Build agents with learning, tools, knowledge, and guardrails
Runtime Run in production using AgentOS
Control Plane Monitor and manage via the AgentOS UI

Get Started

  1. Build your first agent
  2. Build your first multi-agent system
  3. Deploy to production

More: Docs · Cookbook

Features

Category What you get
Learning User profiles that persist across sessions. User memories that accumulate over time. Learned knowledge that transfers across users. Always or agentic learning modes.
Core Model-agnostic: OpenAI, Anthropic, Google, local models. Type-safe I/O with input_schema and output_schema. Async-first, built for long-running tasks. Natively multimodal (text, images, audio, video, files).
Knowledge Agentic RAG with 20+ vector stores, hybrid search, reranking. Persistent storage for session history and state.
Orchestration Human-in-the-loop (confirmations, approvals, overrides). Guardrails for validation and security. First-class MCP and A2A support. 100+ built-in toolkits.
Production Ready-to-use FastAPI runtime. Integrated control plane UI. Evals for accuracy, performance, latency.

IDE Integration

Add our docs to your AI-enabled editor:

Cursor: Settings → Indexing & Docs → Add https://docs.agno.com/llms-full.txt

Also works with VSCode, Windsurf, and similar tools.

Contributing

See the contributing guide.

Telemetry

Agno logs which model providers are used to prioritize updates. Disable with AGNO_TELEMETRY=false.

↑ Back to top

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

agno-2.5.0.tar.gz (1.6 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

agno-2.5.0-py3-none-any.whl (2.0 MB view details)

Uploaded Python 3

File details

Details for the file agno-2.5.0.tar.gz.

File metadata

  • Download URL: agno-2.5.0.tar.gz
  • Upload date:
  • Size: 1.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for agno-2.5.0.tar.gz
Algorithm Hash digest
SHA256 f416dda4b94333608b1e407fad3db89b6d1503b4d59e247f068d6c7a54084b41
MD5 53d332b2b506e8fb045009aa1cfd11fc
BLAKE2b-256 f3e6b8a1d411277a9a51598c3c8bbde02be7d58fade75784175df9ef01a89c9c

See more details on using hashes here.

File details

Details for the file agno-2.5.0-py3-none-any.whl.

File metadata

  • Download URL: agno-2.5.0-py3-none-any.whl
  • Upload date:
  • Size: 2.0 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for agno-2.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 6fb9212d5855fd27e8e26c85c8c297395c9f6cedce9dfaa7dc1c8d6329768d8c
MD5 e9dc9af75c868ab1f2f3163d565e1a89
BLAKE2b-256 9abf370ef52973e2b0363d6048c49056e52fd68d667241ffe96dbd4e37c25103

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page