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[Feature] bad words support v1 scheduler and specifiy token ids (#3608)

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* support bad_words_token_ids

* docs

* fix test

* fix

* bad words support kvcache v1 and token ids

* fix
This commit is contained in:
Sunny-bot1
2025-08-26 11:14:51 +08:00
committed by GitHub
parent c43a4bec00
commit c68c3c4b8b
16 changed files with 420 additions and 62 deletions
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46
fastdeploy/engine/sampling_params.py
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@@ -20,8 +20,6 @@ import random
from dataclasses import dataclass, fields
from typing import Any, List, Optional, Union
from fastdeploy.utils import llm_logger as logger
@dataclass
class SamplingParams:
@@ -102,7 +100,7 @@ class SamplingParams:
temp_scaled_logprobs: bool = False
top_p_normalized_logprobs: bool = False
bad_words: Optional[List[str]] = None
_bad_words_token_ids: Optional[List[int]] = None
bad_words_token_ids: Optional[List[int]] = None
@classmethod
def from_dict(cls, req_dict: dict[str, Any]) -> SamplingParams:
@@ -134,6 +132,7 @@ class SamplingParams:
min_tokens=1,
logprobs=None,
bad_words=None,
bad_words_token_ids=None,
) -> SamplingParams:
"""Create instance from command line arguments"""
return cls(
@@ -154,6 +153,7 @@ class SamplingParams:
min_tokens=min_tokens,
logprobs=logprobs,
bad_words=bad_words,
bad_words_token_ids=bad_words_token_ids,
)
def __post_init__(self):
@@ -206,46 +206,6 @@ class SamplingParams:
if not 0 <= self.seed <= 922337203685477580:
raise ValueError("seed must be in [0, 922337203685477580], got " f"{self.seed}.")
def update_from_tokenizer(self, tokenizer):
"""Support bad words"""
if self.bad_words is None:
return
self._bad_words_token_ids = []
for bad_word in self.bad_words:
# To prohibit words both at the beginning
# and in the middle of text
# (related to add_prefix_space tokenizer parameter)
for add_prefix_space in [False, True]:
prefix = " " if add_prefix_space else ""
prompt = prefix + bad_word.lstrip()
prompt_token_ids = tokenizer.encode(text=prompt, add_special_tokens=False)["input_ids"]
if len(prompt_token_ids) != 1:
if not add_prefix_space:
logger.warning(
f"Skip bad_words: <{prompt}>."
f"Bad words should be a single token."
f"Got tokens: {prompt_token_ids}."
)
continue
if prompt_token_ids[0] > tokenizer.vocab_size:
if not add_prefix_space:
logger.warning(
f"Skip bad_words: <{prompt}>."
f"All token id values should be satisfying:"
f" 0 <= token_id < {tokenizer.vocab_size}."
f"Got token: {prompt_token_ids}."
)
continue
if prompt_token_ids not in self._bad_words_token_ids:
self._bad_words_token_ids.extend(prompt_token_ids)
@property
def bad_words_token_ids(self) -> Optional[List[list[int]]]:
return self._bad_words_token_ids
@dataclass
class BeamSearchParams: