“RAG”

Open-source Python framework for multi-agent systems: agent societies, memory, RAG, code interpreters, synthetic data and large-scale simulation.

Open-source Python toolkit for RAG and agents over your own data, with event-driven workflows and 300+ integration packages.

Minimal Python graph framework of about 100 lines for LLM agents, workflows, RAG and map-reduce pipelines.

Python framework for LLM applications built on Qwen models, with function calling, MCP, a code interpreter and RAG options.

Python framework for generative AI agents, pipelines and parallel workflows, with RAG engines, tools, memory and swappable drivers.

Python framework for writing language-model programs as code and optimizing their prompts and weights instead of hand-tuning prompts.

Python agent framework from Alibaba that lets the model drive tool use, with team pipelines, MCP, agent skills, A2A, memory and tracing.

Reinforcement learning framework for training reasoning LLM agents over multi-turn episodes with the StarPO algorithm.

Modular Python agent framework with a tool-calling loop, context management, retrieval, persistent memory and MCP tools.

Python framework for real-time voice and vision agents that process video with pluggable models and processors over WebRTC.

Typed Python toolkit for composing classic and agentic retrieval-augmented generation pipelines with pluggable LLMs and stores.

Python framework for autonomous agents that work in a sandboxed workspace, and task agents with tools and MCP support.