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[BugFix] Fix duplicate id tool-call race condition (#29355)

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Signed-off-by: Nick Hill <nhill@redhat.com>
This commit is contained in:
Nick Hill 2025-11-24 17:54:26 -08:00 committed by GitHub
parent b8328b49fb
commit a178a0b40b
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2 changed files with 16 additions and 7 deletions
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13
vllm/entrypoints/openai/serving_chat.py
View File

@ -273,6 +273,11 @@ class OpenAIServingChat(OpenAIServing):
try:
for i, engine_prompt in enumerate(engine_prompts):
prompt_text, _, _ = self._get_prompt_components(request_prompts[i])
# If we are creating sub requests for multiple prompts, ensure that they
# have unique request ids.
sub_request_id = (
request_id if len(engine_prompts) == 1 else f"{request_id}_{i}"
)
if self.default_sampling_params is None:
self.default_sampling_params = {}
@ -301,7 +306,7 @@ class OpenAIServingChat(OpenAIServing):
)
self._log_inputs(
request_id,
sub_request_id,
request_prompts[i],
params=sampling_params,
lora_request=lora_request,
@ -316,14 +321,14 @@ class OpenAIServingChat(OpenAIServing):
if isinstance(sampling_params, BeamSearchParams):
generator = self.beam_search(
prompt=engine_prompt,
request_id=request_id,
request_id=sub_request_id,
params=sampling_params,
lora_request=lora_request,
trace_headers=trace_headers,
)
else:
engine_request, tokenization_kwargs = await self._process_inputs(
request_id,
sub_request_id,
engine_prompt,
sampling_params,
lora_request=lora_request,
@ -334,7 +339,7 @@ class OpenAIServingChat(OpenAIServing):
generator = self.engine_client.generate(
engine_request,
sampling_params,
request_id,
sub_request_id,
lora_request=lora_request,
trace_headers=trace_headers,
priority=request.priority,

10
vllm/entrypoints/openai/serving_engine.py
View File

@ -1242,16 +1242,19 @@ class OpenAIServing:
):
prompt_text, _, _ = self._get_prompt_components(request_prompt)
orig_priority = priority
sub_request = 0
while True:
# Ensure that each sub-request has a unique request id.
sub_request_id = f"{request_id}_{sub_request}"
self._log_inputs(
request_id,
sub_request_id,
request_prompt,
params=sampling_params,
lora_request=lora_request,
)
trace_headers = kwargs.get("trace_headers")
engine_request, tokenization_kwargs = await self._process_inputs(
request_id,
sub_request_id,
engine_prompt,
sampling_params,
lora_request=lora_request,
@ -1262,7 +1265,7 @@ class OpenAIServing:
generator = self.engine_client.generate(
engine_request,
sampling_params,
request_id,
sub_request_id,
lora_request=lora_request,
priority=priority,
prompt_text=prompt_text,
@ -1295,6 +1298,7 @@ class OpenAIServing:
sampling_params.max_tokens = self.max_model_len - len(prompt_token_ids)
# OPTIMIZATION
priority = orig_priority - 1
sub_request += 1
def _get_prompt_components(
self,