Ready to build AI agents that don't just chat, but search the web, remember conversations, and dive into PDFs? Meet Agno - a lightweight Python library that's reportedly 10,000x faster than LangGraph !
What You'll Learn:
- ⚡ Lightning Setup with uv (10-100x faster than pip)
- 🤖 Basic Agent Creation with OpenAI integration
- 🌐 Web Search Powers using DuckDuckGo tools
- 🧠 Persistent Memory with SQLite storage
- 📚 RAG Implementation with LanceDB vector database
- 👥 Multi-Agent Teams that collaborate seamlessly
Quick Start:
Install Agno:
pip install agno
Create First Agno Agent
from agno.agent import Agent
from agno.models.openai import OpenAIChat
agent = Agent(
model=OpenAIChat(id="gpt-4o"),
description="You're a cheerful AI pal!",
markdown=True
)
agent.print_response("Hey! What's cooking today?", stream=True)
Key Features:
- 🔧 Zero Configuration - Works out of the box
- 💾 Smart Memory - SQLite/PostgreSQL storage
- 🔍 RAG Ready - PDF knowledge bases with vector search
- 🌐 Web Integration - DuckDuckGo search capabilities
- ⚡ Blazing Fast - Built for speed and efficiency
- 🤝 Team Collaboration - Multi-agent coordination ## Real-World Example: Build a Thai cuisine expert that pulls recipes from PDFs and supplements with web research - all in under 50 lines of code!
Perfect for: Developers wanting to build production-ready AI agents without the complexity of heavyweight frameworks.
👉 🔗 Read the full guide: https://www.bitdoze.com/agno-get-start/
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