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Make distinct code and console admonitions so readers are less likely to miss them (#20585)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-07-08 03:55:28 +01:00
committed by GitHub
parent 31c5d0a1b7
commit af107d5a0e
52 changed files with 192 additions and 162 deletions
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12
docs/features/reasoning_outputs.md
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@@ -33,7 +33,7 @@ vllm serve deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B \
Next, make a request to the model that should return the reasoning content in the response.
??? Code
??? code
```python
from openai import OpenAI
@@ -70,7 +70,7 @@ The `reasoning_content` field contains the reasoning steps that led to the final
Streaming chat completions are also supported for reasoning models. The `reasoning_content` field is available in the `delta` field in [chat completion response chunks](https://platform.openai.com/docs/api-reference/chat/streaming).
??? Json
??? console "Json"
```json
{
@@ -95,7 +95,7 @@ Streaming chat completions are also supported for reasoning models. The `reasoni
OpenAI Python client library does not officially support `reasoning_content` attribute for streaming output. But the client supports extra attributes in the response. You can use `hasattr` to check if the `reasoning_content` attribute is present in the response. For example:
??? Code
??? code
```python
from openai import OpenAI
@@ -152,7 +152,7 @@ Remember to check whether the `reasoning_content` exists in the response before
The reasoning content is also available when both tool calling and the reasoning parser are enabled. Additionally, tool calling only parses functions from the `content` field, not from the `reasoning_content`.
??? Code
??? code
```python
from openai import OpenAI
@@ -200,7 +200,7 @@ For more examples, please refer to <gh-file:examples/online_serving/openai_chat_
You can add a new `ReasoningParser` similar to <gh-file:vllm/reasoning/deepseek_r1_reasoning_parser.py>.
??? Code
??? code
```python
# import the required packages
@@ -258,7 +258,7 @@ You can add a new `ReasoningParser` similar to <gh-file:vllm/reasoning/deepseek_
Additionally, to enable structured output, you'll need to create a new `Reasoner` similar to the one in <gh-file:vllm/reasoning/deepseek_r1_reasoning_parser.py>.
??? Code
??? code
```python
@dataclass