18 items
17 tools, 1 guide
Web-standards-first React framework, now merged with React Router v7. Loaders and actions, nested routing, and progressive enhancement out of the box.
Multi-agent orchestration framework built on the OpenAI Agents SDK. Define agent roles, typed tools, and directional communication flows. Production-focused, open-source.
Type-safe Python agent framework from the Pydantic team. Brings the FastAPI feeling to AI development. Composable tools, durable execution, and full IDE autocomplete.
Structured data extraction from any LLM using Pydantic models. Automatic retries, validation, and streaming. 3M+ monthly downloads. Available in Python, TypeScript, Go, Ruby, and Rust.
Constrained generation library for LLMs. Uses finite state machines to mask invalid tokens during generation. Guarantees schema-compliant output with zero retries.
Deep comparison of the top AI agent frameworks - architecture, code examples, strengths, weaknesses, and when to use each one.
The TypeScript toolkit for building AI apps. Unified API across OpenAI, Anthropic, Google. Streaming, tool calling, structured output, multi-step agents. 50K+ GitHub stars.
Lightweight Python framework for multi-agent systems. Agent handoffs, tool use, guardrails, tracing. Successor to the experimental Swarm project.
Multi-agent orchestration framework. Define agents with roles, goals, and tools, then assign them tasks in a crew. Python-based. Great for complex workflows.
TypeScript-first AI agent framework. Workflows, RAG, tool use, evals, and integrations. Built for production Node.js apps. Open-source.
LLM data framework for connecting custom data sources to language models. Best-in-class RAG, data connectors, and query engines. Python and TypeScript.

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