In partnership with

World of AI | Edition # 21

Agno: A Powerful Open-Source Framework for Building AI Agents with Memory, Tools, and Reasoning

Agno is making waves in the AI community as a revolutionary open-source framework designed to simplify the creation of high-performance AI agents. Formerly known as Fi Data, Agno has undergone a major upgrade, positioning itself as one of the most powerful and efficient agent frameworks available today. This article explores the key features, capabilities, and advantages of Agno, highlighting why it stands out from other frameworks like LangGraph.

Introduction and Rebranding

Agno is the new and improved version of Fi Data, designed to make building AI agents easier and more efficient. Built on three key principles—Simplicity, Performance, and Agnosticism—Agno enables developers to create AI agents with minimal complexity and maximum efficiency:

• Simplicity: Written in pure Python, eliminating complex graphs and chains.

• Performance: Delivers fast AI responses with a low memory footprint.

• Agnosticism: Compatible with any AI model, provider, and modality, making it highly flexible.

Unmatched Performance

One of Agno's standout features is its impressive performance improvements over competing frameworks:

• 5,000x faster agent instantiation compared to LangGraph.

• 50x less memory usage while maintaining high-speed inference.

• Optimized for parallel execution of tool calls, reducing overall execution time.

These enhancements make Agno not only fast but also scalable, enabling the development of complex agentic systems without compromising on efficiency.

Built-in Agent UI and Capabilities

Agno includes a built-in user interface (UI) that allows developers to easily manage agents with memory, tools, and storage. The UI enables seamless configuration and interaction with agents, including:

• Web Search Agent: Capable of retrieving real-time information, such as trending stocks, using search engines like Google.

• Research Agent: Can analyze data sources (e.g., YouTube channels) and provide structured insights within seconds.

The ability to integrate various tools and knowledge sources makes Agno highly versatile for different use cases.

Advanced Research Agent Example

Agno’s research agent showcases the framework’s ability to handle complex tasks. For example:

• When asked to provide insights about the World of AI YouTube channel, the agent used a combination of search and reasoning to deliver a structured report.

• The agent leveraged built-in memory and toolsets to create detailed, well-organized responses—demonstrating the framework’s strong multimodal capabilities.

Simple Setup and Configuration

Setting up Agno locally is straightforward and requires only Python and Git:

1. Clone the Agno repository from GitHub.

2. Install dependencies using the included Agno cookbook.

3. Configure the agent using pre-built code blocks from the cookbook.

Agno's setup process is designed to be beginner-friendly while offering advanced customization options for experienced developers.

Flexible Agent Customization

Agno supports four levels of agent complexity:

1. Basic Agent – Simple agent with minimal functionality.

2. Agent with Tools – Adds external tool access (e.g., search engines).

3. Knowledge + Memory – Enhanced with reasoning and context retention.

4. Multi-Agent Collaboration – Teams of agents working together to handle complex workflows.

This flexibility allows developers to build agents tailored to specific tasks and industries.

Example: News Agent with Real-Time Search

An example of Agno in action is a news agent configured to deliver breaking news updates in a storytelling tone. By integrating DuckDuckGo search, the agent can retrieve and report real-time news updates directly within the UI—demonstrating the power of Agno’s function-calling capabilities.

RAG (Retrieval-Augmented Generation) Capability

Agno also supports building Retrieval-Augmented Generation (RAG) systems:

• Can integrate multiple large language models and data sources.

• Handles PDF parsing and other document formats.

• Includes a Streamlit-based UI for displaying search results and extracted insights.

This makes Agno an ideal tool for developing sophisticated AI-powered search and research systems.

Outperformance and Competitive Edge

Agno significantly outperforms other leading AI frameworks in terms of speed, efficiency, and scalability. Its ability to deliver fast, accurate responses with low memory usage makes it a valuable tool for AI development at any scale.

Conclusion: Why Agno Stands Out

Agno’s combination of speed, low memory usage, and flexibility makes it one of the most powerful AI frameworks available today. Its open-source nature and easy setup make it accessible to developers of all skill levels. Whether you’re building simple agents or complex multi-agent systems, Agno provides the tools and performance needed to succeed.

If you’re looking to streamline your AI development process, Agno is the framework to try. Check out the GitHub repository and start building today.

Optimize global IT operations with our World at Work Guide

Explore this ready-to-go guide to support your IT operations in 130+ countries. Discover how:

• Standardizing global IT operations enhances efficiency and reduces overhead

• Ensuring compliance with local IT legislation to safeguard your operations

• Integrating Deel IT with EOR, global payroll, and contractor management optimizes your tech stack

Leverage Deel IT to manage your global operations with ease.

Download free guide