Best AI Agent Frameworks

Build and scale AI agents with existing codebases and APIs.

RAG-as-a-Service for building AI apps handling unstructured data.

Open-source framework for voice and chat applications.

Self-improving AI agents with function execution.

Multi-agent framework for software development workflows.

Debug, test, and monitor LLM-powered applications.

Microsoft’s open-source AI integration framework.

Microsoft’s AI framework integrating LLMs with expert models.

Multi-AI agent framework with self-reflection.

Orchestrate multi-actor AI applications with precision.

Build voice and multimodal conversational AI agents.

Simplified AI agent development with multi-model support.

Modular AI agent pipelines for structured automation.

Stateful AI agents with memory and reasoning.

Deploy multi-agent LLM-based AI systems.

Real-time audio, video, and data for AI applications.

OpenAI’s multi-agent AI orchestration framework.

AI-powered automation for sales and customer service.

Connect LLMs with data for powerful AI applications.

AI agents with memory and multi-step task execution.

Python framework for structured AI workflows.

Scalable AI applications with LLM and agent integration.

Multi-agent AI collaboration for complex tasks.

Modular Auto-GPT reimplementation with plug-and-play API.

Modular Python framework for AI-powered applications.

Build, launch, and scale autonomous AI products.

Open-source framework for multi-agent AI collaboration.

AI agents structured as Directed Acyclic Graphs.

Program LLMs with compositional Python for AI development.

Multi-agent AI system testing through games and scenarios.

FastAPI-inspired AI application development framework.

Open-source framework for multi-agent AI systems.

Open-source framework for LLM-driven AI research.