LlamaIndex

The default open-source framework for composing LLM apps.

Python + TypeScript framework for chaining prompts, tools, retrievers, and memory into LLM applications. Ubiquitous in the ecosystem; pairs with LangGraph for agent orchestration and LangSmith for tracing.

Graph-based agent orchestration. Stateful loops with checkpoints.

LangChain's agent layer. Model agents as nodes in a state graph with persistent checkpoints, human-in-the-loop steps, and durable execution. Strong when you need a long-running, debuggable agent rather than a one-shot chain.

Multi-agent framework with explicit roles and tasks.

Python framework for orchestrating crews of specialised agents — researcher, writer, reviewer — coordinated through shared context. Opinionated about roles, sequencing, and delegation; good fit for content-and-research pipelines.

Visual platform for agentic workflows, RAG pipelines, and LLM apps.

An LLMOps platform that bundles a drag-and-drop workflow builder, RAG pipelines, agent tooling, model management, and observability into one surface — prototype to production without much glue code. Connects hundreds of proprietary and open models across providers. Self-host the source-available edition for free, or use Dify Cloud's paid tiers.