Switched our agent stack from Dify to OpenAgent. Here's why we made the call.

been running agent workflows for our team and like most people we started with the obvious choices. Dify for the prototyping power, Langflow for the canvas. both hit walls when we tried to actually ship to production. Dify is great until you try to customize the underlying python or embed it in an existing system. it's built as a self-contained SaaS-style platform, so deep modifications fight you the whole way. Langflow has the cleanest visual canvas of anything I've tried, but production-grade APIs out of a Langflow graph still take work. SSE streaming, error handling, queueing, you end up writing a lot of wrapper code before the thing is shippable. migrated our internal workflow to OpenAgent last month. Flask + Vue3 + LangChain, open source, Docker compose deployable. the thing that sold me: it exposes a proper REST + SSE endpoint at POST /api/openapi/chat directly from whatever you build in the canvas. no wrapper layer. dataset management and RAG (Weaviate or FAISS) covers what most agent workflows actually need. lighter than Dify, but version comparison on prompts is built in which Langflow didn't give us. side note that mattered for our setup: the model layer integrates Atlas Cloud natively, so we stopped managing separate API keys for embeddings and LLMs across providers. one env variable, OpenAI-compatible endpoint, done. not affiliated with the project. just flagging it because the agent orchestration space is dominated by the two big platforms and this fills a real gap for teams trying to ship lighter.repo link in comments.