Add conditional prompt inclusion in generated output based on `is_ret… #8360
Conversation
…urn_prompt` flag - Introduced a new `is_return_prompt` parameter in the request. - Modified the list comprehension to conditionally include the prompt in the generated output based on the value of `is_return_prompt`. - If `is_return_prompt` is True, the prompt is concatenated with the output text. - If `is_return_prompt` is False, only the output text is returned. - Applied this change to both streaming and non-streaming cases to ensure consistency.
|
👋 Hi! Thank you for contributing to the vLLM project. Once the PR is approved and ready to go, your PR reviewer(s) can run CI to test the changes comprehensively before merging. To run CI, PR reviewers can do one of these:
🚀 |
|
The |
|
Closing as superseded by #7381 |
Feature: Conditional Prompt Inclusion in generate Function
Motivation: The current implementation of the generate function always includes the prompt in its response. This can be inefficient, especially in streaming scenarios where the prompt is repeatedly included with each token update. The new feature aims to improve efficiency by allowing the prompt to be included conditionally based on a new parameter.
Changes Made:
is_return_promptparameter in the request.is_return_prompt.If
is_return_promptisTrue, the prompt is concatenated with the output text.If
is_return_promptisFalse, only the output text is returned.Related Issues: #8359
Additional Context: Including the prompt in every streaming iteration can be redundant and inefficient. This update provides users with the flexibility to exclude the prompt from the response, improving the overall efficiency of the generate function.
FILL IN THE PR DESCRIPTION HERE
FIX #8359
BEFORE SUBMITTING, PLEASE READ THE CHECKLIST BELOW AND FILL IN THE DESCRIPTION ABOVE
PR Checklist (Click to Expand)
Thank you for your contribution to vLLM! Before submitting the pull request, please ensure the PR meets the following criteria. This helps vLLM maintain the code quality and improve the efficiency of the review process.
PR Title and Classification
Only specific types of PRs will be reviewed. The PR title is prefixed appropriately to indicate the type of change. Please use one of the following:
[Bugfix]for bug fixes.[CI/Build]for build or continuous integration improvements.[Doc]for documentation fixes and improvements.[Model]for adding a new model or improving an existing model. Model name should appear in the title.[Frontend]For changes on the vLLM frontend (e.g., OpenAI API server,LLMclass, etc.)[Kernel]for changes affecting CUDA kernels or other compute kernels.[Core]for changes in the core vLLM logic (e.g.,LLMEngine,AsyncLLMEngine,Scheduler, etc.)[Hardware][Vendor]for hardware-specific changes. Vendor name should appear in the prefix (e.g.,[Hardware][AMD]).[Misc]for PRs that do not fit the above categories. Please use this sparingly.Note: If the PR spans more than one category, please include all relevant prefixes.
Code Quality
The PR need to meet the following code quality standards:
format.shto format your code.docs/source/if the PR modifies the user-facing behaviors of vLLM. It helps vLLM user understand and utilize the new features or changes.Notes for Large Changes
Please keep the changes as concise as possible. For major architectural changes (>500 LOC excluding kernel/data/config/test), we would expect a GitHub issue (RFC) discussing the technical design and justification. Otherwise, we will tag it with
rfc-requiredand might not go through the PR.What to Expect for the Reviews
The goal of the vLLM team is to be a transparent reviewing machine. We would like to make the review process transparent and efficient and make sure no contributor feel confused or frustrated. However, the vLLM team is small, so we need to prioritize some PRs over others. Here is what you can expect from the review process:
action-requiredlabel on the PR if there are changes required. The contributor should address the comments and ping the reviewer to re-review the PR.Thank You
Finally, thank you for taking the time to read these guidelines and for your interest in contributing to vLLM. Your contributions make vLLM a great tool for everyone!