Repository: UKGovernmentBEIS/inspect_ai
Issue: Rendered template does not match qwen3 template with thinking (separated by single `\n` instead of `\n\n`)
Root cause: Interface Contract Mismatch

Hi, while playing around with pre-filling the assistant message using vllm and Qwen3, I stumbled upon what I believe to be a minor inconsistency with how inspect generates the text combining the thinking and completion tokens, and how the qwen3 template does it.

What happened:
When I tried to run the prefill.py example with Qwen3 and inserting a thinking trace, e.g.
```python
import re

from inspect_ai import Task, task
from inspect_ai.dataset import Sample
from inspect_ai.model import ChatMessageAssistant, ChatMessageUser
from inspect_ai.scorer import Score, Target, accuracy, scorer
from inspect_ai.solver import Generate, Solver, TaskState, generate, solver

@task
def arithmetic_prefill():
    """Task demonstrating prefilling of assistant messages."""
    prefill_reasoning = "<think>\nblahblahblah\n</think>\n\n"
    return Task(
        dataset=[
            Sample(
                input="What is 5+7?",
                target="12",
                metadata={"prefill": f"{prefill_reasoning}5+7="},
            ),
        ],
        solver=[prefill(), generate()],
        scorer=score_arithmetic(),
    )

...
```
I got this error:
```
RuntimeError: BadRequestError("Error code: 400 - {'error': {'message': 'continue_final_message is set but the final message does not appear in the chat after applying  
the chat template! This can happen if the chat template deletes portions of the final message. Please verify the chat template and final message in your chat to ensure 
they are compatible. continue_final_message is set but the final message does not appear in the chat after applying the chat template! This can happen if the chat      
template deletes portions of the final message. Please verify the chat template and final message in your chat to ensure they are compatible.', 'type':                 
'BadRequestError', 'param': None, 'code': 400}}")                                                                                                                       
                                                                                                                                                                        
Request:                                                                                                                                                                
{                                                                                                                                                                       
  "messages": [                                                                                                                                                         
    {                                                                                                                                                                   
      "role": "user",                                                                                                                                                   
      "content": "What is 5+7?"                                                                                                                                         
    },                                                                                                                                                                  
    {                                                                                                                                                                   
      "role": "assistant",                                                                                                                                              
      "content": "\n<think>\n9+9+2 = 20 so I'm going to go with that. Let's say 20.\n</think>\n5+7="                                                                    
    }                                                                                                                                                                   
  ],                                                                                                                                                                    
  "tools": null,                                                                                                                                                        
  "tool_choice": null,                                                                                                                                                  
  "extra_headers": {                                                                                                                                                    
    "x-irid": "ntDH2xYYESU9VYzWMUrWtS"                                                                                                                                  
  },                                                                                                                                                                    
  "model": "Qwen/Qwen3-1.7B",                                                                                                                                           
  "extra_body": {                                                                                                                                                       
    "add_generation_prompt": false,                                                                                                                                     
    "continue_final_message": true                                                                                                                                      
  }                                                                                                                                                                     
}              
```

My diagnosis is that this happens because of a slight inconsistency between the Qwen3 template and how inspect creates the text combining the thinking and main output.

From the Qwen3 tokenizer https://huggingface.co/Qwen/Qwen3-8B/blob/main/tokenizer_config.json, we see this 
```
'\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n'
```
(emphasis on double `\n`).

However, at https://github.com/UKGovernmentBEIS/inspect_ai/blob/1442375ee7c409bad268f4d644e13af1eac8bf49/src/inspect_ai/model/_openai.py#L281
it only separates by a single `\n`. 
(It also is the case here: https://github.com/UKGovernmentBEIS/inspect_ai/blob/1442375ee7c409bad268f4d644e13af1eac8bf49/src/inspect_ai/model/_chat_message.py#L76, but that gets overridden by here at least for vllm)

The fix seems straightforward in `_openai.py`:
```python
if content.endswith("</think>"):
    content = f"{content}\n\n{c.text}"
else:
    content = f"{content}\n{c.text}"
```
and in `_chat_message.py` 
```python
result = ""
for text in all_text:
    result += text
    result += "\n"
    if text.endswith("</think>"):
        result += "\n"
return result.strip()
```

Not sure how impactful this inconsistency is/whether this is known and ought to be fixed, but thought it would be good to raise awareness!

cc @kaifronsdal 

hmm, I'm not sure there is a great solution to this. It might be nice to have a way to disable the automatic reasoning parsing that happens in ‎ChatMessageAssistant so you have complete control over the input string. 

Prefill has always been messy to work with and I know some people working on the huggingface libraries have spent a bunch of time thinking about how to implement it with arbitrary chat templates (with moderate success).

Yeah, I guess this happens independently of prefill though, right? Because even if you do not prefill and have, say, multiple turns of user/assistant then the thinking in the assistant message from earlier messages will get parsed and reconstructed with \n instead of \n\n. But I'm not sure how big of a problem this would pose in practice.

I think round trip it isn't a problem since the model will generate its response with \n\n, inspect will parse the <think> tags and send it back with \n, and the chat template will parse the <think> tags one more time and add \n\n again.

The issue is that Hugging Face's prefill mechanism formats the prefill text as a standard assistant message, then searches the formatted output for that exact prefill text to strip any additional tokens appended to the end. While this approach works for most chat templates, it fails with this one because the chat template modifies the prefill content itself (making it impossible for Hugging Face to locate and match the original prefill text).