Agno
agno.com
Build, run, and manage smart AI agents and teams in your own cloud.
Описание
The agent platformthat builds itself · The agent platform that builds itself. Agno gives coding agents the primitives to build agents, teams and workflows, plus a runtime to serve them in your cloud. · How it works · Build, run and manage agents · Your agent platform belongs to you · Loved by engineers at
Agno is an open-source framework for building AI agents using Python. It provides a comprehensive set of tools and features to create powerful agents that can access knowledge, possess memory, and complete tasks using various tools. Agno simplifies the process of developing AI agents, making it accessible to developers of different skill levels.
Возможности
Python-based development
Support for Large Language Models
Memory management for AI agents
Tool integration capabilities
Agentic RAG (Retrieval-Augmented Generation) support
Multi-agent flow creation
Сценарии использования
Stock analysis AI agent
AI agent with agentic RAG for improved information retrieval
Multi-agent systems for complex task handling
Custom AI assistants for specific domains
Automated data analysis and reporting
Частые вопросы
Agno AI is an open-source, full-stack Python framework for building AI agents, multi-agent teams, and agentic workflows. It enables developers to create intelligent systems that can reason, use tools, maintain memory, and access knowledge bases.
Agno AI offers several key features including Multi-Agent Systems for building collaborative agent teams, model-agnostic support for various LLMs such as OpenAI, Anthropic, Google, and open-source models, native multimodal support for processing text, images, audio, and video, built-in memory and knowledge capabilities that allow agents to recall past interactions and access knowledge bases, FastAPI integration for rapid development, a control plane with tools for testing, monitoring, and managing agents, and high performance, claiming to be up to 10,000x faster and use 50x less memory than some competitors.
To get started with Agno AI, you need to first install Agno, then set your API key, for example for OpenAI, and finally create an agent and configure it with your chosen model and knowledge base.
Yes, Agno AI is model-agnostic and supports integration with various LLM providers, including OpenAI, Anthropic, Google, and open-source models.
Yes, Agno AI natively supports multimodal inputs, allowing agents to process and respond to text, images, audio, and video.
Agno AI agents can maintain memory through vector stores or databases and access knowledge bases for context-aware responses. This enables agents to recall past interactions and provide more accurate answers.
Common use cases for Agno AI include customer support with context-aware responses, data analysis and live market data fetching, creating personal assistants for email triage and scheduling, logistics planning and shipment tracking, and content generation and research.
Agno AI provides a control plane with real-time monitoring, debugging capabilities, session tracking, and detailed logs for system prompts, user messages, and tool calls.
Yes, Agno AI is open source and available on GitHub. The community can contribute, ask questions, and collaborate through the GitHub Discussions forum.
You can find more resources and documentation on the official Agno AI documentation website, its GitHub repository, and in the community discussions forum, which is also hosted on GitHub.
Характеристики
| Тип | Агент |
| Категория | Инфраструктура и MLOps / Управление знаниями ИИ |
| Цена | бесплатно (от $0/мес) |
| Платформа | Только веб |
| Системы | web |
| Хостинг | self-hosted |
| Для кого | Individual |
| Язык сайта | en |
| Рейтинг | 5.00 (1 отзывов) |
| Просмотры | 187 936 |
| Запуск | 2025-01-30 |
