DeepSeek Publishes Thinking-Mode Tool-Call Samples

Migrated with permission from DeepSeek V4 Pro, a related editorial property operated by our team.

Checked on July 6, 2026: DeepSeek's official docs currently expose both a Python thinking-mode tool-call sample and a separate output transcript page, giving developers a first-party reference for tool schemas, chained calls, blank content turns, and reasoning_content replay behavior.

What we verified on July 6, 2026

DeepSeek's official docs sitemap currently includes a dedicated Python thinking-mode tool-call sample page.

The same official docs surface also includes a separate tool-call output transcript page, which exposes how reasoning_content, content, and tool_calls evolve across multiple turns.

The sample uses a chained pattern rather than a one-shot demo: the model first calls get_date, then uses that result to call get_weather, then answers the user.

The output transcript shows that content can be empty during a valid tool-call turn, which is an important debugging boundary for agent runtimes that incorrectly expect a final answer on every assistant message.

This is support and protocol coverage only. It does not create any new plan card, stock promise, or pricing change in this repo.