[Bugfix] Fix RequestOutput miss lora_request

[jeejeelee]

Purpose

Test Plan

LoRA tests in CI , and we also can test it locally by the following script:

from vllm import LLM, SamplingParams
from vllm.lora.request import LoRARequest

# Sample prompts.
prompts = [
    "Hello, my name is",
    "The president of the United States is",
    "The capital of France is",
    "The future of AI is",
    "How old are you ?",
]

LORA_NAME_PATH_MAP = {
    "Alice": LoRARequest("Alice", 1, "charent/self_cognition_Alice"),
    "Bob": LoRARequest("Bob", 2, "charent/self_cognition_Bob"),
    "Cat": LoRARequest("Bob", 3, "charent/self_cognition_Bob"),
}


# Create a sampling params object.
sampling_params = SamplingParams(temperature=0.8, top_p=0.95)


def main():
    # Create an LLM.
    llm = LLM(model="Qwen/Qwen3-0.6B", enable_lora=True)

    lora_req_lst = [
        LORA_NAME_PATH_MAP["Alice"],
        LORA_NAME_PATH_MAP["Bob"],
        None,
        LORA_NAME_PATH_MAP["Cat"],
        LORA_NAME_PATH_MAP["Alice"],
    ]

    outputs = llm.generate(prompts, sampling_params, lora_request=lora_req_lst)
    for output in outputs:
        lora_req = output.lora_request
        print(lora_req)
        print("-" * 60)


if __name__ == "__main__":
    main()

Test Result

test_llama_tp.py in CI should pass correctly, the script should print information as follow

LoRARequest(lora_name='Alice', lora_int_id=1, lora_path='charent/self_cognition_Alice', lora_local_path=None, long_lora_max_len=None, base_model_name=None, tensorizer_config_dict=None)
------------------------------------------------------------
LoRARequest(lora_name='Bob', lora_int_id=2, lora_path='charent/self_cognition_Bob', lora_local_path=None, long_lora_max_len=None, base_model_name=None, tensorizer_config_dict=None)
------------------------------------------------------------
None
------------------------------------------------------------
LoRARequest(lora_name='Bob', lora_int_id=3, lora_path='charent/self_cognition_Bob', lora_local_path=None, long_lora_max_len=None, base_model_name=None, tensorizer_config_dict=None)
------------------------------------------------------------
LoRARequest(lora_name='Alice', lora_int_id=1, lora_path='charent/self_cognition_Alice', lora_local_path=None, long_lora_max_len=None, base_model_name=None, tensorizer_config_dict=None)
------------------------------------------------------------

---

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)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.
• (Optional) Release notes update. If your change is user facing, please update the release notes draft in the Google Doc.

[chatgpt-codex-connector]

Codex usage limits have been reached for code reviews. Please check with the admins of this repo to increase the limits by adding credits.

[gemini-code-assist]

Code Review

This pull request addresses a bug where the lora_request information was missing from the RequestOutput. The changes correctly propagate the full LoRARequest object through the RequestState to the final RequestOutput. The fix is validated by an updated test in tests/lora/test_llama_tp.py, which now asserts that the lora_request is correctly populated in the output. The implementation is clean and effectively resolves the issue.

[LucasWilkinson]

Trying to fix this here too: #30744 but this makes sense in the interim; thanks!

[jeejeelee]

@LucasWilkinson Yeah, my changes are mainly aimed at minimizing edge-case OOM issues.