Sharing Agno, a new open-source library focused on building high-performance, multimodal AI agents. If you're building agentic systems, this looks seriously impressive, especially regarding speed and memory efficiency.
Agno acts as a lightweight framework, providing a unified API for various LLMs and adding capabilities like memory, knowledge stores, tool use, and reasoning.
Key aspects that stand out:
🚀 Lightning Fast & Lightweight: They report huge performance gains over frameworks like LangGraph (claiming 10,000x faster instantiation and 50x less memory on their benchmarks). 🔌 Model Agnostic: No lock-in! Use models from OpenAI, Anthropic, Cohere, or open-source ones via Ollama, Together, Anyscale, etc. 👁️ Multimodal: Native support for agents working with text, image, audio, and video. 🤝 Multi-Agent Teams: Built to orchestrate teams of specialized agents. 🧠 Memory, Knowledge, Tools: Built-in support for memory, vector DBs (for RAG), and adding custom tools. 📊 Monitoring: Integrates with agno.com for real-time agent monitoring. 🔓 Open Source (Apache 2.0): Freely available for use and contribution.
For developers building high-performance, multimodal AI agents, Agno offers a powerful and efficient open-source foundation.
