
A hands-on comparison of modern AI agent and multi-agent frameworks. Get started with practical examples and explore the unique features of each framework.
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This repository provides a comprehensive, hands-on comparison of modern AI agent and multi-agent frameworks. Each framework is explored through practical examples, highlighting its unique features, capabilities, and use cases.
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The repository is organized by framework, with each top-level folder containing examples, configuration, and a README.md
for that framework. Examples range from simple agent tasks to advanced multi-agent workflows, RAG (Retrieval-Augmented Generation), API integration, and more.
Main modules:
ag2/
agno/
autogen/
crewai/
google-adk/
langgraph/
llama-index/
openai-agents-sdk/
pydantic-ai/
smolagents/
study-agents-differences/
Some modules are standalone, while others are PDM projects or use requirements.txt
for dependency management. Always check the README.md
in each module for specific setup and usage instructions.
- Choose a framework: Navigate to the relevant folder for the agent framework you want to explore.
- Install dependencies: See each module’s
README.md
for installation instructions. - Run examples
The study-agents-differences/
folder contains comprehensive scripts and utilities for comparing frameworks on common tasks, including RAG, API integration, and multi-agent workflows. It provides:
- Unified agent interfaces for Agno, LangGraph, LlamaIndex, OpenAI, and Pydantic-AI
- Performance benchmarks measuring response time, token usage, and tool utilization
- Detailed results and analysis comparing different agent designs and tool integrations
- Interactive Streamlit UI for real-time comparison (
streamlit run agent-ui.py
)
All contributions are welcome! If you have suggestions for new examples, frameworks to add, or improvements to existing content, please open an issue or submit a pull request.
- Some modules use PDM (
pyproject.toml
), others userequirements.txt
. Check each module’sREADME.md
for installation and usage. - Install dependencies before running examples.
- Example
.env.example
files are provided where needed for API keys and settings.