[BUGFIX] Parse or convert thinking chunks given content format

[juliendenize]

Purpose

This PR is similar to #41718 and is an alternative.

The previous handling of {"type": "thinking"} content blocks in parse_chat_messages unconditionally flattened them to {"type": "text"} dicts, losing the semantic distinction. This broke Jinja chat templates (e.g. Mistral models) that rely on rendering thinking blocks natively as {"type": "thinking", ...} dicts.

This PR fixes thinking block handling with a dual-path strategy based on content_format:

• "openai" (hf renderer using Jinja templates supporting openai format): Thinking blocks are preserved inline as {"type": "thinking", "thinking": ...} dicts so chat templates can render them natively.
• "string" (all custom renderers IIUC): Thinking blocks are extracted and concatenated into the reasoning / reasoning_content fields on ConversationMessage, which is what the custom tokenizers expect.

Note:
Mistral Renderer was not impacted by the bug because the tokenizer wasn't seeing formatted content but the raw messages sent by the user.

Additionally:

• Adds a conflict guard that raises ValueError when a message contains both a top-level reasoning field and inline thinking content blocks.
• Extracts a flatten_content_to_text() helper to fix the echo feature, which crashed when ConversationMessage.content was a list of dicts (as it now can be with preserved thinking blocks). This is applied consistently across streaming, non-streaming, and batch serving paths. For echo feature, Mistral Models thinking chunks are not kept which is imo expected IIUC its intent.

Test Plan

Unit tests added

pytest tests/entrypoints/test_chat_utils.py::TestParseChatMessagesThinking -v

• tested ministral with hf format

Test Result

Tests pass and mininstral with hf format now receives correctly thinking chunks whereas previously it received text chunks.

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Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
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• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

[claude]

Claude Code Review

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[gemini-code-assist]

Code Review

This pull request introduces specialized handling for 'thinking' content blocks in chat messages, allowing them to be preserved for Jinja templates or extracted into a reasoning field based on the content format. It also adds a flatten_content_to_text utility to standardize text extraction for echo functionality. Review feedback identified a potential TypeError when processing null thinking content and a logic error where empty thinking blocks were not correctly removed in 'string' format, which could lead to assertion failures.