Qwen3 response_schema might not be correct
Author: qgallouedec
Pull request: no

Qwen3 response schema taken from

https://github.com/huggingface/transformers/blob/8598421b5120a6a57efe9f57fbfda9bfed29a4dc/tests/utils/test_chat_parsing_utils.py#L149-L181

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

checkpoint = "Qwen/Qwen3-0.6B"

tokenizer = AutoTokenizer.from_pretrained(checkpoint)
model = AutoModelForCausalLM.from_pretrained(checkpoint, dtype="auto", device_map="auto")

# taken from test
qwen3_schema = {
    "x-regex": r"^(?:(?:<think>)?\s*(?P<thinking>.+?)\s*</think>)?\s*(?:<tool_call>(?P<tool_calls>.*?)\s*</tool_call>)?\s*(?P<content>.+?)?\s*$",
    "type": "object",
    "properties": {
        "role": {"const": "assistant"},
        "content": {"type": "string"},
        "thinking": {"type": "string"},
        "tool_calls": {
            "x-regex-iterator": r"^(.*)$",  # We have already extracted tool calls and there can only be one, so just make it a list
            "type": "array",
            "items": {
                "type": "object",
                "properties": {
                    "type": {"const": "function"},
                    "function": {
                        "type": "object",
                        "properties": {
                            "name": {"type": "string", "x-regex": r"<function=(\w+)>"},
                            "arguments": {
                                "type": "object",
                                "x-regex-key-value": r"<parameter=(?P<key>\w+)>\n(?P<value>.*?)\n</parameter>",
                                "additionalProperties": {
                                    "x-parser": "json",
                                    "x-parser-args": {"allow_non_json": True},
                                },
                            },
                        },
                    },
                },
            },
        },
    },
}

tokenizer.response_schema = qwen3_schema


def multiply(a: int, b: int) -> int:
    """
    Multiplies two integers.

    Args:
        a: The first integer.
        b: The second integer.

    Returns:
        The product of the two integers.
    """
    return a * b


messages = [{"role": "user", "content": "Use the tool to multiply 3 and 4."}]

processed = tokenizer.apply_chat_template(
    messages,
    add_generation_prompt=True,
    tokenize=True,
    return_tensors="pt",
    tools=[multiply],
    enable_thinking=False,
)
input_ids = processed["input_ids"].to(model.device)
outputs = model.generate(input_ids, max_new_tokens=1024)[0, input_ids.shape[1] :]
out_text = tokenizer.decode(outputs)
print(out_text)
```

```
<tool_call>
{"name": "multiply", "arguments": {"a": 3, "b": 4}}
</tool_call>

```

```python
parsed = tokenizer.parse_response(out_text)
print(parsed)
```

```
{'role': 'assistant', 'content': '
', 'tool_calls': [{'type': 'function', 'function': {}}]}
```

Interestingly, if I use `smollm_schema` instead, it seems to work fine:

```python
tokenizer.response_schema = smollm_schema
parsed = tokenizer.parse_response(out_text)
print(parsed)
```

```
{'role': 'assistant', 'content': '
', 'tool_calls': [{'type': 'function', 'function': {'name': 'multiply', 'arguments': {'a': 3, 'b': 4}}}]}
```

cc @Rocketknight1 

Comments:
```python
qwen3_schema = {
    "x-regex": r"^(?:(?:<think>)?\s*(?P<thinking>.+?)\s*</think>)?\s*(?:<tool_call>(?P<tool_calls>.*?)\s*</tool_call>)?\s*(?P<content>.+?)?\s*$",
    "type": "object",
    "properties": {
        "role": {"const": "assistant"},
        "content": {"type": "string"},
        "thinking": {"type": "string"},
        "tool_calls": {
            "x-regex-iterator": r"^(.*)$",
            "type": "array",
            "items": {
                "type": "object",
                "properties": {
                    "type": {"const": "function"},
                    "function": {
                        "x-parser": "json",
                        "x-parser-args": {"allow_non_json": True},
                        "type": "object",
                        "properties": {
                            "name": {"type": "string"},
                            "arguments": {
                                "type": "object",
                                "additionalProperties": {}
                            },
                        },
                    },
                },
            },
        },
    },
}
```

I think the parsing logic is incorrect as the model output was a json object. Modifying the schema to the one above seems to give the correct output 
```
The attention mask is not set and cannot be inferred from input because pad token is same as eos token. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.
<tool_call>
{"name": "multiply", "arguments": {"a": 3, "b": 4}}
</tool_call>

{'role': 'assistant', 'content': '
', 'tool_calls': [{'type': 'function', 'function': {'name': 'multiply', 'arguments': {'a': 3, 'b': 4}}}]}
```

Is this the correct fix  ? 

@vasqu  is this something that requires fixing or is not necessary? 

response schema cc @Rocketknight1 

Hey all! The `response_schema` feature is currently paused while we work on an update to the underlying spec and a new schema format. We'll start rolling out updated schemas after that!

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.