Drop content=None from messages in apply_chat_template

[qgallouedec]

In apply_chat_template, drop the content key from messages when its value is None before passing to the Jinja template.

Why this is a bug fix, not a breaking change

content=None means "there is no content", it is semantically identical to the key being absent. No caller sets content=None expecting the literal string "None" to appear in the output, or the output to be different than if the key were absent.

Yet today, several templates crash or misbehave:

• Raise TypeError: DeepSeekV3-0528, GptOSS, Qwen3VL, LFM2.5-VL
• Renders literal "None": GLM-5.1, GLM4MOE, MiniMax-M2.5, MiniMax-M2.7

After this change, out of the 20 tool-calling models tested:

• 12 are unaffected
• 6 are fixed (crashes or literal "None" → correct output)
• 1 edge case (LFM2.5-VL — separate template bug)
• 1 would regress (DeepSeek-R1 — accepts content=None but crashes on absent key, which IMO is itself a template bug to fix on the Hub repo).

Why not just leave it to template authors?

Because content=None is a real-world input (it's what the OpenAI API returns for tool-call-only messages)

from openai import OpenAI

client = OpenAI()

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "What's the weather in Paris?"}],
    tools=[{
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get weather for a city",
            "parameters": {"type": "object", "properties": {"city": {"type": "string"}}},
        },
    }],
)

msg = response.choices[0].message
msg_dict = msg.model_dump()
print(f"\nmsg_dict = {msg_dict}")

msg_dict = {'content': None, 'refusal': None, 'role': 'assistant', 'annotations': [], 'audio': None, 'function_call': None, 'tool_calls': [{'id': 'call_Im08OArU1YY2mKi7ntPxdm22', 'function': {'arguments': '{"city":"Paris"}', 'name': 'get_weather'}, 'type': 'function'}]}

and expecting every template author to handle it correctly is a losing game — 8 out of 20 already don't. One normalization line in apply_chat_template fixes all of them at once and prevents future templates from hitting the same issue.

Part of the broader discussion in #45419.

[HuggingFaceDocBuilderDev]

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[Rocketknight1]

Sorry for losing track of this one! I think it's a good fix, and a good path to standardization, but Deepseek-R1 is a very major model, even if it's a little out of date now that V4 exists, and this change would be very breaking for it. I think we should patch its template on the Hub first, then merge this!