---

name: serving-cli description: "Operate DataFlow CLI groups and serving backends." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

serving-cli

Use this sub-skill for DataFlow command routing and serving setup:

• root CLI discovery and command routing
• dataflow init and dataflow init repo
• dataflow chat
• dataflow eval
• dataflow pdf2model and dataflow text2model
• dataflow webui
• serving classes under dataflow.serving

Route elsewhere when the task is primarily about:

• operator, storage, prompt, or pipeline mechanics: pipeline-foundations
• text dataset generation and text-only training flows: text-workflows
• PDF / document / VQA / RAG workflows: document-vision-rag
• Ray acceleration and actor wrapping: rayorch-acceleration

Operating rules:

• Treat --help as discovery only; it should not download models or start services.
• Treat init, eval init, pdf2model init, and text2model init as setup commands that write files.
• Treat chat, eval api/local, pdf2model train, text2model train, and webui as side-effecting commands.
• Do not rely on dataflow env in a pipe or other non-TTY context; it can fail with Errno 25.
• Use DF_API_KEY, GOOGLE_API_KEY, and Google Vertex credentials only when the selected backend requires them.
• For backend-specific constructor facts, timeout behavior, and dependency warnings, see references/serving-backends.md.
• For CLI routing and side effects, see references/cli-reference.md and references/evaluation-and-webui.md.
• Use the bundled scripts to inspect CLI help and to smoke-test APILLMServing_request against a local OpenAI-style server.