Agent frameworks (LangChain, LlamaIndex, etc.)
Orchestration layer for RAG and agents
LangChain/LangGraph, LlamaIndex, CrewAI, AutoGen and DSPy are the orchestration frameworks developers use to build RAG pipelines and multi-step agents on top of raw model APIs. They shape how retrieval, memory, tool use and agent control flow are actually wired in production applications.
Examples
LangGraph, LlamaIndex, DSPy
Layer
agent/RAG orchestration
How it fits the stack
Agent frameworks (LangChain, LlamaIndex, etc.) with what it depends on (above) and what it feeds (below). The figure renders as a crawlable diagram and upgrades to an interactive 3D graph as it scrolls into view.
Agent frameworks (LangChain, LlamaIndex, etc.) in the AI stack. Agent frameworks (LangChain, LlamaIndex, etc.) with its immediate upstream dependencies (top) and downstream dependents (bottom) in the AI value chain. Hover a node in 3D, or read the full relationships below.
Graph data (text) — 3 entities, 2 relationships
- Agent frameworks (LangChain, LlamaIndex, etc.) —uses→ Model Context Protocol (MCP)
- Agent frameworks (LangChain, LlamaIndex, etc.) —uses→ Vector databases