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Fix flaky streaming logprobs test by handling detokenizer text buffering (#17687)

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Co-authored-by: Xinyuan Tong <115166877+JustinTong0323@users.noreply.github.com>
This commit is contained in:
Kangyan-Zhou
2026-01-25 15:09:06 -08:00
committed by GitHub
co-authored by Xinyuan Tong
parent bf139af37a
commit 592603d77b
3 changed files with 54 additions and 33 deletions
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python/sglang/srt/entrypoints/openai/serving_chat.py
+12 -6
View File
@@ -627,16 +627,22 @@ class OpenAIServingChat(OpenAIServingBase):
routed_experts[index] = content["meta_info"].get("routed_experts", None) routed_experts[index] = content["meta_info"].get("routed_experts", None)
# Handle logprobs # Handle logprobs
finish_reason = content["meta_info"]["finish_reason"]
choice_logprobs = None choice_logprobs = None
if request.logprobs: if request.logprobs:
choice_logprobs = self._process_streaming_logprobs( n_prev_token = n_prev_tokens.get(index, 0)
content, n_prev_tokens.get(index, 0) total_output_logprobs = len(
)
n_prev_tokens[index] = len(
content["meta_info"]["output_token_logprobs"] content["meta_info"]["output_token_logprobs"]
) )
# When finish_reason is set and all logprobs have been sent,
finish_reason = content["meta_info"]["finish_reason"] # any remaining text is just buffered text being flushed by the
# detokenizer (it holds back text at word boundaries). Return None
# for logprobs since no new tokens were generated for this text.
if n_prev_token < total_output_logprobs or finish_reason is None:
choice_logprobs = self._process_streaming_logprobs(
content, n_prev_token
)
n_prev_tokens[index] = total_output_logprobs
finish_reason_type = finish_reason["type"] if finish_reason else None finish_reason_type = finish_reason["type"] if finish_reason else None
# Track finish_reason for each index # Track finish_reason for each index
python/sglang/srt/entrypoints/openai/serving_completions.py
+26 -11
View File
@@ -242,19 +242,34 @@ class OpenAIServingCompletion(OpenAIServingBase):
input_top_logprobs = None input_top_logprobs = None
n_prev_token = n_prev_tokens.get(index, 0) n_prev_token = n_prev_tokens.get(index, 0)
logprobs = to_openai_style_logprobs( total_output_logprobs = len(
input_token_logprobs=input_token_logprobs,
input_top_logprobs=input_top_logprobs,
output_token_logprobs=content["meta_info"][
"output_token_logprobs"
][n_prev_token:],
output_top_logprobs=content["meta_info"].get(
"output_top_logprobs", []
)[n_prev_token:],
)
n_prev_tokens[index] = len(
content["meta_info"]["output_token_logprobs"] content["meta_info"]["output_token_logprobs"]
) )
output_logprobs_slice = content["meta_info"][
"output_token_logprobs"
][n_prev_token:]
finish_reason_for_logprobs = content["meta_info"]["finish_reason"]
# When finish_reason is set and all logprobs have been sent,
# any remaining text is just buffered text being flushed by the
# detokenizer (it holds back text at word boundaries). Return None
# for logprobs since no new tokens were generated for this text.
if (
len(output_logprobs_slice) == 0
and finish_reason_for_logprobs is not None
and input_token_logprobs is None
):
logprobs = None
else:
logprobs = to_openai_style_logprobs(
input_token_logprobs=input_token_logprobs,
input_top_logprobs=input_top_logprobs,
output_token_logprobs=output_logprobs_slice,
output_top_logprobs=content["meta_info"].get(
"output_top_logprobs", []
)[n_prev_token:],
)
n_prev_tokens[index] = total_output_logprobs
# Generate delta # Generate delta
delta = text[len(stream_buffer) :] delta = text[len(stream_buffer) :]
test/registered/openai_server/basic/test_openai_server.py
+16 -16
View File
@@ -156,23 +156,23 @@ class TestOpenAIServer(CustomTestCase):
is_first = is_firsts.get(index, True) is_first = is_firsts.get(index, True)
if logprobs: if logprobs:
assert response.choices[0].logprobs, f"no logprobs in response" # When finish_reason is set, logprobs may be None if this chunk
print( # only contains buffered text being flushed (no new tokens generated).
f"{response=}, {response.choices[0]=}, {response.choices[0].logprobs=}" # The detokenizer holds back text at word boundaries during streaming.
) if response.choices[0].logprobs is not None:
assert isinstance(
response.choices[0].logprobs.tokens[0], str
), f"{response.choices[0].logprobs.tokens[0]} is not a string"
if not (is_first and echo):
assert isinstance( assert isinstance(
response.choices[0].logprobs.top_logprobs[0], dict response.choices[0].logprobs.tokens[0], str
), f"top_logprobs was not a dictionary" ), f"{response.choices[0].logprobs.tokens[0]} is not a string"
ret_num_top_logprobs = len( if not (is_first and echo):
response.choices[0].logprobs.top_logprobs[0] assert isinstance(
) response.choices[0].logprobs.top_logprobs[0], dict
# FIXME: Sometimes, some top_logprobs are missing in the return value. The reason is that some output id maps to the same output token and duplicate in the map ), f"top_logprobs was not a dictionary"
# assert ret_num_top_logprobs == logprobs, f"{ret_num_top_logprobs} vs {logprobs}" ret_num_top_logprobs = len(
assert ret_num_top_logprobs > 0, f"ret_num_top_logprobs was 0" response.choices[0].logprobs.top_logprobs[0]
)
# FIXME: Sometimes, some top_logprobs are missing in the return value. The reason is that some output id maps to the same output token and duplicate in the map
# assert ret_num_top_logprobs == logprobs, f"{ret_num_top_logprobs} vs {logprobs}"
assert ret_num_top_logprobs > 0, f"ret_num_top_logprobs was 0"
if is_first: if is_first:
if echo: if echo: