Just a recap for my personal use

• LangChain: The oldest and most comprehensive framework, offering extensive integrations but often criticized for its steep learning curve and boilerplate code.
• LlamaIndex: Primarily focused on data-intensive applications, excelling at connecting language models to external data sources through advanced retrieval and indexing.
• AutoGen (Microsoft): A multi-agent framework that shines at creating conversational agents that can collaborate and delegate tasks to solve complex problems.
• CrewAI: Designed for orchestrating role-playing autonomous agents, making it easy to define agents with specific jobs and have them work together in a structured crew.
• AgentVerse: A versatile framework that provides a “lego-like” approach to building and composing customized multi-agent environments for various applications.
• ChatDev: A “virtual software company” framework where different agents (CEO, programmer, tester) simulate a software development lifecycle to complete coding tasks.
• SuperAGI: A developer-centric framework focused on building autonomous agents with useful features like provisioning, deployment, and a graphical user interface.
• AI Droid (by Vicuna): A lightweight and fast framework designed for mobile and edge devices, prioritizing efficiency and low-resource consumption.
• GPTeam: Similar to ChatDev, this framework uses role-playing agents (like product managers and engineers) to collaboratively work on development tasks from a single prompt.
• Agenta: An open-source platform that helps developers evaluate, test, and deploy language model applications with features for prompt management and A/B testing.
• OpenAI Assistants API: OpenAI’s native solution for building stateful, assistant-like agents directly on their platform, handling conversation history and tool integration internally.
• LangGraph: Built on LangChain, this framework is specifically for creating cyclical, stateful multi-agent workflows, treating agent interactions as steps in a graph.