FastChat

Adoptable for the right team, but more precisely FastChat is an open-source chat serving framework, not a hosted platform and not a low-level inference engine like vLLM. The evidence supports it most clearly as a fairly complete layer for training, serving, evaluation, and OpenAI-compatible access around LLM chat systems. If you want to wrap self-hosted models into a usable chat service, it is a notable and established option.

Its practical value is in orchestration: controller, model workers, web UI, OpenAI-compatible API, and multi-model routing. Zhihu tutorials and troubleshooting posts are stronger usability evidence because they show people deploying it, explaining the architecture, and integrating models. On X, there are examples of using FastChat as an OpenAI replacement with tools like LlamaIndex, ChatVRM, and local dev stacks. Those are better proof of usefulness than partnership announcements or repost-style mentions, which mainly prove attention rather than capability.

On cost and difficulty, the evidence suggests a meaningful engineering setup burden: Python package installation, and in some environments Rust/CMake, plus visible community troubleshooting.