AIMates Resources

AI Frameworks

Discover the most important frameworks used to build AI agents, RAG systems, workflows, retrieval pipelines, and enterprise AI applications.

How to choose an AI framework

Choose frameworks based on your use case. Agent frameworks help build autonomous systems. RAG frameworks improve retrieval and document search. Orchestration frameworks help coordinate tools, workflows, memory, and decision making.

LangGraph

Agent Orchestration

Build stateful AI agents, multi-step workflows, tool calling, memory, and human-in-the-loop systems.

LangChain

LLM Applications

Popular framework for building LLM-powered applications, workflows, tools, and integrations.

LlamaIndex

RAG

Framework focused on document ingestion, indexing, retrieval, and RAG applications.

CrewAI

Multi-Agent Systems

Create teams of AI agents that collaborate, delegate work, and solve complex tasks.

PydanticAI

Python AI

Python-first framework for building structured, type-safe AI applications using Pydantic.

OpenAI Agents SDK

Agent Development

Framework from OpenAI for building agents with tools, handoffs, memory, and guardrails.

AutoGen

Multi-Agent Systems

Microsoft framework for autonomous agents that communicate and collaborate.

Haystack

RAG

Open-source framework for semantic search, retrieval pipelines, and question answering.