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[BugFix][Frontend] Fix LLM.chat() tokenization #16081

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Merged
merged 3 commits into from
Apr 25, 2025
Merged

[BugFix][Frontend] Fix LLM.chat() tokenization #16081

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7c9ff40
[BugFix][Frontend] Fix LLM.chat() tokenization
njhill Apr 5, 2025
fcd3f0c
Merge remote-tracking branch 'refs/remotes/origin/main' into fix-llm-…
njhill Apr 25, 2025
343dccb
Add test
njhill Apr 25, 2025
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27 changes: 14 additions & 13 deletions vllm/entrypoints/llm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -247,8 +247,12 @@ def __init__(
self.request_counter = Counter()
self.default_sampling_params: Union[dict[str, Any], None] = None

def get_tokenizer(self) -> AnyTokenizer:
return self.llm_engine.get_tokenizer_group(TokenizerGroup).tokenizer
def get_tokenizer(
self,
lora_request: Optional[LoRARequest] = None,
) -> AnyTokenizer:
return self.llm_engine.get_tokenizer_group(
TokenizerGroup).get_lora_tokenizer(lora_request)

def set_tokenizer(self, tokenizer: AnyTokenizer) -> None:
tokenizer_group = self.llm_engine.get_tokenizer_group(TokenizerGroup)
Expand Down Expand Up @@ -686,7 +690,7 @@ def chat(
cast(list[ChatCompletionMessageParam], messages)
]

tokenizer = self.get_tokenizer()
tokenizer = self.get_tokenizer(lora_request)
model_config = self.llm_engine.get_model_config()
resolved_content_format = resolve_chat_template_content_format(
chat_template,
Expand All @@ -709,9 +713,8 @@ def chat(
content_format=resolved_content_format,
)

prompt_data: Union[str, list[int]]
if isinstance(tokenizer, MistralTokenizer):
prompt_data = apply_mistral_chat_template(
prompt_token_ids = apply_mistral_chat_template(
tokenizer,
messages=msgs,
chat_template=chat_template,
Expand All @@ -720,7 +723,7 @@ def chat(
continue_final_message=continue_final_message,
)
else:
prompt_data = apply_hf_chat_template(
prompt_str = apply_hf_chat_template(
tokenizer,
trust_remote_code=model_config.trust_remote_code,
conversation=conversation,
Expand All @@ -729,12 +732,12 @@ def chat(
add_generation_prompt=add_generation_prompt,
continue_final_message=continue_final_message,
)
# Special tokens are already included in chat templates so
# should not be added by the tokenizer in this case.
prompt_token_ids = tokenizer.encode(prompt_str,
add_special_tokens=False)

prompt: Union[TokensPrompt, TextPrompt]
if is_list_of(prompt_data, int):
prompt = TokensPrompt(prompt_token_ids=prompt_data)
else:
prompt = TextPrompt(prompt=prompt_data)
prompt = TokensPrompt(prompt_token_ids=prompt_token_ids)

if mm_data is not None:
prompt["multi_modal_data"] = mm_data
Expand Down Expand Up @@ -1023,8 +1026,6 @@ def _embedding_score(
if len(encoded_output_1) == 1:
encoded_output_1 = encoded_output_1 * len(encoded_output_2)

scores: list[PoolingRequestOutput] = []

scores = _cosine_similarity(tokenizer=tokenizer,
embed_1=encoded_output_1,
embed_2=encoded_output_2)
Expand Down