[Feature] support stop_token_ids

[lizexu123]

Motivation

支持stop_token_ids

💡 If this PR is a Cherry Pick, the PR title needs to follow the format by adding the [Cherry-Pick] label at the very beginning and appending the original PR ID at the end. For example, [Cherry-Pick][CI] Add check trigger and logic(#5191)

💡 如若此PR是Cherry Pick，PR标题需遵循格式，在最开始加上[Cherry-Pick]标签，以及最后面加上原PR ID，例如[Cherry-Pick][CI] Add check trigger and logic(#5191)

Modifications

Usage or Command

online serving

• launch the serving
• request with stop_token_ids parameter， it can be '[List[int]]'

# create a chat request with "stop_token_ids" parameter
curl -X POST "http://0.0.0.0:13312/v1/chat/completions" \
-H "Content-Type: application/json" \
-d '{
    "model": "default",
    "messages": [
        {
            "role": "user",
            "content": "北京天安门在哪里?"
        }
    ],
    "temperature": 0.7,
    "stream": false,
    "seed": 1,
    "stop_token_ids":[104208]
}'

# the original output without `stop_token_ids` is: 
# {"id":"chatcmpl-33610f95-7d01-47a6-b040-39b18316f727","object":"chat.completion","created":1760692757,"model":"/root/paddlejob/workspace/env_run/output/models/paddle/Qwen/Qwen3-0.6B","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\n好的，用户问的是“北京天安门在哪里？”。首先，我需要确认用户的需求是什么。可能他们想知道天安门的具体位置，或者想了解它的重要性。接下来，我得回忆一下北京天安门广场的地理位置。天安门广场位于北京市中心，周围环绕着著名的胡同，比如大栅栏、小街等。用户可能对城市规划和地标建筑感兴趣，也可能是想了解天安门的历史和功能。\n\n用户可能没有明确说明他们的需求，但作为回答者，我需要确保信息准确且易于理解。天安门广场是北京的标志性建筑之一，周围有丰富的历史和文化元素。此外，用户可能还想知道天安门与周围其他景点的关系，比如人民广场、故宫等，这有助于提供更全面的回答。\n\n需要注意的是，用户可能对“哪里”这个词语有歧义，可能需要进一步澄清。但根据问题本身，直接回答地理位置是合适的。同时，保持回答简洁明了，避免使用过于专业的术语，让用户容易理解。\n</think>\n\n北京天安门广场位于中国北京市中心，是中华人民共和国的象征性建筑之一。广场周围环绕着著名的胡同，如大栅栏、小街等，是北京的城市地标和历史文化中心。","multimodal_content":null,"reasoning_content":null,"tool_calls":null,"prompt_token_ids":null,"completion_token_ids":null,"prompt_tokens":null,"completion_tokens":null},"logprobs":null,"finish_reason":"stop"}],"usage":{"prompt_tokens":14,"total_tokens":276,"completion_tokens":262,"prompt_tokens_details":{"cached_tokens":0}}}

# the output with `stop_token_ids` is:
# {"id":"chatcmpl-51f772d0-e0d8-48da-9b5f-a3690849ffca","object":"chat.completion","created":1760692873,"model":"/root/paddlejob/workspace/env_run/output/models/paddle/Qwen/Qwen3-0.6B","choices":[{"index":0,"message":{"role":"assistant","content":"<think>\n好的，用户问的是“北京天安门在哪里？”。首先，我需要确认用户的需求是什么。可能他们想知道天安门的具体位置，或者想了解它的重要性。接下来，我得回忆一下北京天安门","multimodal_content":null,"reasoning_content":null,"tool_calls":null,"prompt_token_ids":null,"completion_token_ids":null,"prompt_tokens":null,"completion_tokens":null},"logprobs":null,"finish_reason":"stop"}],"usage":{"prompt_tokens":14,"total_tokens":64,"completion_tokens":50,"prompt_tokens_details":{"cached_tokens":0}}}```

offline demo

from fastdeploy.engine.sampling_params import SamplingParams
from fastdeploy.entrypoints.llm import LLM

model_name_or_path = "/root/paddlejob/workspace/env_run/output/models/paddle/Qwen/Qwen3-0.6B"

# 超参设置
sampling_params = SamplingParams(temperature=1, seed=1,stop_token_ids=[104208])
llm = LLM(model=model_name_or_path, tensor_parallel_size=1)
output = llm.chat(messages=[{"role": "user", "content": "北京天安门在哪里?"}], use_tqdm=True, sampling_params=sampling_params)

print(output)```

Accuracy Tests

Checklist

• Add at least a tag in the PR title.
  • Tag list: [[FDConfig],[APIServer],[Engine], [Scheduler], [PD Disaggregation], [Executor], [Graph Optimization], [Speculative Decoding], [RL], [Models], [Quantization], [Loader], [OP], [KVCache], [DataProcessor], [BugFix], [Docs], [CI], [Optimization], [Feature], [Benchmark], [Others], [XPU], [HPU], [GCU], [DCU], [Iluvatar], [Metax]]
  • You can add new tags based on the PR content, but the semantics must be clear.
• Format your code, run pre-commit before commit.
• Add unit tests. Please write the reason in this PR if no unit tests.
• Provide accuracy results.
• If the current PR is submitting to the release branch, make sure the PR has been submitted to the develop branch, then cherry-pick it to the release branch with the [Cherry-Pick] PR tag.

[paddle-bot]

Thanks for your contribution!

[codecov-commenter]

Codecov Report

❌ Patch coverage is 84.37500% with 5 lines in your changes missing coverage. Please review.
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Files with missing lines	Patch %	Lines
fastdeploy/input/utils.py	72.22%	4 Missing and 1 partial ⚠️

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[freeliuzc]

两个算子改参数的话，记得把 ernie5_serving 同步改了

[yuanlehome]

很多个文件都有这坨，看看能不能抽象封装一下

[yuanlehome]

引入min_tokens的作用是什么？

[lizexu123]

设置最小生成的token数量，如果当前生成的token数量小于min_tokens，即使设置了stop_token_ids，也不会停止

[yuanlehome]

delete