AI FRAMEWORKS

The TypeScript toolkit for building AI apps. Unified API across OpenAI, Anthropic, Google. Streaming, tool calling, structured output, multi-step agents. 50K+ GitHub stars.

Anthropic's Python SDK for building production agent systems. Tool use, guardrails, agent handoffs, and orchestration. Released alongside Claude 4.

Most popular LLM framework. 100K+ GitHub stars. Chains, RAG, vector stores, tool use. LangGraph adds stateful multi-agent workflows with cycles and persistence.

Gives AI agents access to 250+ external tools (GitHub, Slack, Gmail, databases) with managed OAuth. Handles the auth and API complexity so your agent doesn't have to.

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.