## Description

When LiteLLM converts Anthropic `/v1/messages` assistant responses (with `thinking` blocks) to OpenAI Chat Completions format, the thinking blocks are stored in a custom `thinking_blocks` field. The standard `reasoning_content` field is not set.

This causes multi-turn requests to reasoning models to fail with: ``` The `reasoning_content` in the thinking mode must be passed back to the API. ```

## Root cause

In `litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py`:

```python if len(thinking_blocks) > 0: assistant_message["thinking_blocks"] = thinking_blocks ```

The upstream API (DeepSeek, OpenAI o-series) expects `reasoning_content` at the top level of the assistant message dict in multi-turn conversations.

## Fix

```python if len(thinking_blocks) > 0: assistant_message["thinking_blocks"] = thinking_blocks first_thinking = thinking_blocks[0] assistant_message["reasoning_content"] = first_thinking.get("thinking", "") ```

## Steps to reproduce

1. LiteLLM proxy with Anthropic `/v1/messages` + `LITELLM_USE_CHAT_COMPLETIONS_URL_FOR_ANTHROPIC_MESSAGES=true` 2. Model: `deepseek/*` pointing to a reasoning endpoint via `api_bas…