Updated 2026-07-06
DeepSeek reasoning_content output example: read the official transcript before you write replay code
DeepSeek's docs now publish a dedicated output transcript for the thinking-mode tool-call sample. That is unusually useful because many support issues come from guessing what intermediate `reasoning_content`, `content`, and `tool_calls` should look like across turns. This page targets the exact search intent behind queries like DeepSeek reasoning_content example, DeepSeek tool call output example, and DeepSeek reasoning_content replay.
1. Why the official output transcript matters
The transcript page shows the step-by-step state transition, not just the input code. You can see when `reasoning_content` contains planning text, when `content` is blank, when a tool call is emitted, and when a final user-facing answer appears.
That makes it more valuable than many community examples, because replay bugs usually happen at the boundary between those fields. If you never inspect a real transcript, it is easy to flatten everything into one assistant message and quietly break the next request.
Sources checked
- DeepSeek official tool-call output transcript - Official first-party transcript showing reasoning_content, content, and tool_calls over multiple turns.
2. Blank content does not mean the model is broken
One of the most useful details in the official transcript is that `content` can be empty while the model still emits a valid tool call. That is normal. The model is using the turn to plan and act, not to produce the final user-facing answer yet.
Teams often treat an empty `content` field as a failure and immediately retry or replace the response. That is the wrong move when `tool_calls` are present. The official transcript makes that boundary obvious.
| Field state | What it means |
|---|---|
| `reasoning_content` populated | The model is exposing internal planning text for the current step. |
| `content` is empty | The model may still be in the action phase, not the final answer phase. |
| `tool_calls` present | Your app should execute the declared tool instead of forcing a final answer. |
3. Replay logic should follow the transcript, not your intuition
The transcript shows that the model can reason, call a tool, receive a result, reason again, and call another tool before it finally answers. Your replay code has to preserve that structure. If you compress the sequence into one synthetic assistant message, the next request stops matching the protocol DeepSeek documented.
Use the transcript as a regression reference whenever your framework claims to support DeepSeek thinking mode. If its captured message history cannot represent the same transitions, the abstraction is probably hiding a bug.
Turn 1.1
reasoning_content="The user is asking about the weather in Hangzhou tomorrow..."
content="Let me check tomorrow's weather..."
tool_calls=[get_date]
Turn 1.2
reasoning_content="Today is 2026-04-19, so tomorrow is 2026-04-20..."
content=""
tool_calls=[get_weather]4. This transcript complements, but does not replace, the protocol docs
The transcript is concrete evidence of how DeepSeek's sample behaves today, while the broader rules still live in the official thinking-mode and reasoning-model guides. Read them together.
For the baseline implementation code, continue with `/guides/deepseek-tool-call-python-sample`. For the more general replay and parameter rules, continue with `/guides/deepseek-thinking-mode-tool-calls` and `/guides/deepseek-reasoning-model-unsupported-parameters`.
5. Keep the commercial line honest
This page explains protocol behavior only. It is not a claim about new inventory, a new payment product, or broader plan availability.
If a reader needs DeepSeek access, the correct CTA is the existing `/pricing` route, and even that route remains limited by actual stocked plans in this repo.
FAQ
What does DeepSeek's official reasoning_content output example show?
It shows a multi-turn thinking-mode transcript where reasoning text, tool calls, blank content, and final answers appear in different phases of the same workflow.
Is an empty `content` field during a tool call an error?
Not by itself. The official transcript shows empty content can be normal while the model is issuing a tool call.
Why should I read the transcript if I already saw the Python sample?
Because the code sample shows how to send the request, while the transcript shows what the response sequence actually looks like across turns.
Does this page change DeepSeek plan availability on the site?
No. It is documentation-driven support content only and does not change stocked products.
If your DeepSeek thinking-mode replay logic is unstable, the official output transcript is the fastest way to see what a healthy multi-step exchange should actually look like.
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