Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[Bugfix] Fixing max token error message for openai compatible server #4016

Merged
merged 1 commit into from
Apr 23, 2024

Conversation

jgordley
Copy link
Contributor

This PR addresses a bug where the error message is inaccurate when the user makes a ChatCompletionRequest with no max_tokens sent.

Example behavior:

from openai import OpenAI
client = OpenAI(
    base_url="http://localhost:8000/v1",
    api_key="token-abc123",
)

message_over_context_length = "Hello " * 32800 + "How are you."

completion = client.chat.completions.create(
  model="mistralai/Mistral-7B-Instruct-v0.2",
  messages=[
    {"role": "user", "content": message_over_context_length}
  ]
)

Previous response (indicates a negative value for max_tokens when it was not sent):

openai.BadRequestError: Error code: 400 - {'object': 'error', 'message': 'max_tokens must be at least 1, got -45.', 'type': 'BadRequestError', 'param': None, 'code': 400}

This is because with a negative value set for max_tokens the check immediately after for token_num + request.max_tokens misses that the context length is exceeded.

New response:

openai.BadRequestError: Error code: 400 - {'object': 'error', 'message': "This model's maximum context length is 32768 tokens. However, you requested 32813 tokens in the messages, Please reduce the length of the messages.", 'type': 'BadRequestError', 'param': None, 'code': 400}

This doesn't change the previous behavior if max_tokens is sent and the combination of max_tokens and token_num is greater than max_model_length:

openai.BadRequestError: Error code: 400 - {'object': 'error', 'message': "This model's maximum context length is 32768 tokens. However, you requested 32870 tokens (32614 in the messages, 256 in the completion). Please reduce the length of the messages or completion.", 'type': 'BadRequestError', 'param': None, 'code': 400}

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, LLM class, 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:

  • We adhere to Google Python style guide and Google C++ style guide.
  • Pass all linter checks. Please use format.sh to format your code.
  • The code need to be well-documented to ensure future contributors can easily understand the code.
  • Include sufficient tests to ensure the project to stay correct and robust. This includes both unit tests and integration tests.
  • Please add documentation to 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-required and 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:

  • After the PR is submitted, the PR will be assigned to a reviewer. Every reviewer will pick up the PRs based on their expertise and availability.
  • After the PR is assigned, the reviewer will provide status update every 2-3 days. If the PR is not reviewed within 7 days, please feel free to ping the reviewer or the vLLM team.
  • After the review, the reviewer will put an action-required label on the PR if there are changes required. The contributor should address the comments and ping the reviewer to re-review the PR.
  • Please respond to all comments within a reasonable time frame. If a comment isn't clear or you disagree with a suggestion, feel free to ask for clarification or discuss the suggestion.

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!

@jgordley
Copy link
Contributor Author

@simon-mo would you mind taking a look at this PR? It's my first one here so I want to ensure it follows the right PR standards. It's a useful error fix for our service. Thanks!

@pzzmyc
Copy link

pzzmyc commented Apr 16, 2024

Very helpful, I also encountered this situation, but I couldn't wait for the author to merge it, so I just used your file

@jgordley
Copy link
Contributor Author

Hey @simon-mo, sorry to ping again but is there anything else I can do to get this PR approved? Thanks!

Copy link
Collaborator

@esmeetu esmeetu left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM! Thanks.

@esmeetu esmeetu merged commit d3c8180 into vllm-project:main Apr 23, 2024
35 checks passed
z103cb pushed a commit to z103cb/opendatahub_vllm that referenced this pull request May 7, 2024
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

3 participants