5 Open Source No-Code Platforms for Creating LLMs, RAGs, and AI Agents

1. AutoAgent — a fully automated framework with a zero-code entry threshold. Simply describe a high-level goal in natural language, and the system will autonomously handle planning, task decomposition, and execution. It transforms prompts into a functioning system of agents.

GitHub repository: https://github.com/HKUDS/AutoAgent

2. AnythingLLM. One of the best comprehensive solutions for building internal tools. It combines RAG, agent workflows, and document management in a single self-hosted space. The platform is privacy-oriented and designed for both technical and non-technical teams needing to create tools based on their own data.

GitHub repository: https://github.com/Mintplex-Labs/anything-llm

3. LangChain Open Agent Platform. A specialized UI built on top of LangGraph. Instead of hiding internal logic, it makes the agent execution flow visible through nodes and connections. This allows for detailed control over routing, loops, and coordination of multiple agents without needing to write the graph code itself.

GitHub repository: https://github.com/langchain-ai/open-agent-platform

4. Sim. A visual workflow builder with an integrated AI Copilot. You design agent pipelines as executable graphs, while the built-in AI can generate or modify these workflows for you. The platform also provides detailed execution tracing, significantly simplifying the debugging of complex chains.

GitHub repository: https://github.com/simstudioai/sim

5. Dify. A production-ready platform with a focus on observability. It supports prompt management, complex RAG pipelines, and agent logic, as well as providing monitoring during execution. If you are deploying solutions for real users, this is one of the standard options.

GitHub repository: https://github.com/langgenius/dify