[Frontend] Add LLM.reward specific to reward models

[noooop]

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.

Purpose

After #21470, LLM.encode pooling_task defaults to using "encode", meaning that reward models actually use LLM.encode. However, most libraries' encode corresponds to an embedding model, which can lead to potential errors.

• Add LLM.reward specified to reward models
• The pooling_task for LLM.encode defaults to None, and pooling_task needs to be specified

Test Plan

Test Result

(Optional) Documentation Update

[github-actions]

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[gemini-code-assist]

Code Review

This pull request aims to improve the API for reward models by adding a dedicated LLM.reward method and making the pooling_task in LLM.encode explicit. The changes are in the right direction, but the implementation of the new reward method seems incorrect as it uses pooling_task="encode" and lacks necessary validation. I've left a critical comment with suggestions to align it with other task-specific methods like embed and classify. Additionally, I've suggested improving an error message for better user guidance. Addressing these points will significantly improve the correctness and consistency of the new API.

[noooop]

@DarkLight1337

Quick review

[DarkLight1337]

Let's wait for #18321 to be merged first, then update this PR

[noooop]

buildkite/ci/pr/language-models-test-extended-pooling

The failed test can be fixed by #21747

[xsank]

@noooop @DarkLight1337 For online server, which api is the best entrypoint for the reward model?

[noooop]

@noooop @DarkLight1337 For online server, which api is the best entrypoint for the reward model?

https://github.com/vllm-project/vllm/blob/main/vllm/entrypoints/openai/serving_pooling.py

/pooling

---

I personally think that /pooling needs to be refactored to better support the reward models

PTAL #20538

[xsank]

@noooop @DarkLight1337 For online server, which api is the best entrypoint for the reward model?

https://github.com/vllm-project/vllm/blob/main/vllm/entrypoints/openai/serving_pooling.py

/pooling

I personally think that /pooling needs to be refactored to better support the reward models

PTAL #20538

Now i'm using embedding api and i have no scenario for pooling api yet

[noooop]

@noooop @DarkLight1337 For online server, which api is the best entrypoint for the reward model?

https://github.com/vllm-project/vllm/blob/main/vllm/entrypoints/openai/serving_pooling.py
/pooling
I personally think that /pooling needs to be refactored to better support the reward models
PTAL #20538

Now i'm using embedding api and i have no scenario for pooling api yet

According to vllm's taxonomy

• the reward model means using all pooling (and step pooling, let's temporarily not discuss it. ), meaning there is an output for each token.

• the embedding model means using [CLS], LAST, MEAN pooling, which means there is only one output for a sequence