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.

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.

Open-source AI orchestration framework by deepset. Modular pipelines for RAG, agents, semantic search, and multimodal apps. Pipeline-as-graph architecture with explicit control.

Python's de facto data validation library. Type-hint-driven models, fast Rust-based core (v2), and the foundation of FastAPI, LangChain, and most Python AI tooling.