## What happened?

Calling a Mistral reasoning model (`mistral-medium-3-5` with `reasoning_effort="high"`) through the **litellm proxy** (`POST /v1/chat/completions`) returns a response whose `message` has **no `reasoning_content`** — the thinking trace is dropped. The identical call via the **`litellm.completion()` SDK** (in-process) returns `reasoning_content` correctly.

Mistral returns reasoning as a typed block inside `content` (`[{"type":"thinking",...},{"type":"text",...}]`). The SDK's Mistral transformer maps the thinking block to `message.reasoning_content`; the proxy's HTTP serialization does not include it. This breaks parity with how the proxy exposes reasoning for Anthropic thinking / DeepSeek / Magistral.

## How to reproduce

**(A) SDK, in-process — `reasoning_content` IS present:** ```python import litellm r = litellm.completion( model="mistral/mistral-medium-3-5", messages=[{"role": "user", "content": "If a train travels 60 km in 45 minutes, what is its speed in km/h?"}], reasoning_effort="high", allowed_openai_params=["reasoning_effort"], max_tokens=2000, ) m = r.choices[0].message print(len(m.reasoning_content or "")) # -> 1046 print(len(m.co…