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[BugFix]fix gpt-oss v1/completions response bug (#30608)

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Signed-off-by: princepride <wangzhipeng628@gmail.com>
Signed-off-by: 汪志鹏 <wangzhipeng628@gmail.com>
Co-authored-by: Chauncey <chaunceyjiang@gmail.com>
Co-authored-by: Cyrus Leung <tlleungac@connect.ust.hk>
Co-authored-by: bbrowning <bbrownin@redhat.com>
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汪志鹏 2025-12-21 10:39:31 +08:00 committed by GitHub
parent 7c73ceb581
commit 3e92b2b7ac
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4 changed files with 40 additions and 14 deletions
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21
tests/entrypoints/openai/test_response_api_with_harmony.py
View File

@ -1,6 +1,7 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import importlib
import importlib.util
import json
import time
@ -986,3 +987,23 @@ async def test_function_call_with_previous_input_messages(
assert (
"aquarius" in output_text or "otter" in output_text or "tuesday" in output_text
)
@pytest.mark.asyncio
@pytest.mark.parametrize("model_name", [MODEL_NAME])
async def test_chat_truncation_content_not_null(client: OpenAI, model_name: str):
response = await client.chat.completions.create(
model=model_name,
messages=[{"role": "user", "content": "What is the role of AI in medicine?"}],
temperature=0.0,
max_tokens=250,
)
choice = response.choices[0]
assert choice.finish_reason == "length", (
f"Expected finish_reason='length', got {choice.finish_reason}"
)
assert choice.message.content is not None, (
"Content should not be None when truncated"
)
assert len(choice.message.content) > 0, "Content should not be empty"

15
tests/entrypoints/openai/test_serving_chat.py
View File

@ -955,7 +955,6 @@ class TestServingChatWithHarmony:
input_messages,
[
{"role": "system"},
{"role": "developer"},
{"role": "user", "content": messages[0]["content"]},
],
)
@ -983,7 +982,6 @@ class TestServingChatWithHarmony:
input_messages_2,
[
{"role": "system"},
{"role": "developer"},
{"role": "user"},
# The analysis message should be dropped on subsequent inputs because
# of the subsequent assistant message to the final channel.
@ -1043,7 +1041,7 @@ class TestServingChatWithHarmony:
)
# Test the Harmony messages for the second turn's input
req_2 = ChatCompletionRequest(model=MODEL_NAME, messages=messages)
req_2 = ChatCompletionRequest(model=MODEL_NAME, messages=messages, tools=tools)
input_messages_2, _ = serving_chat._make_request_with_harmony(req_2)
verify_harmony_messages(
input_messages_2,
@ -1124,7 +1122,7 @@ class TestServingChatWithHarmony:
)
# Test the Harmony messages for the second turn's input
req_2 = ChatCompletionRequest(model=MODEL_NAME, messages=messages)
req_2 = ChatCompletionRequest(model=MODEL_NAME, messages=messages, tools=tools)
input_messages_2, _ = serving_chat._make_request_with_harmony(req_2)
verify_harmony_messages(
input_messages_2,
@ -1205,7 +1203,7 @@ class TestServingChatWithHarmony:
)
# Test the Harmony messages for the second turn's input
req_2 = ChatCompletionRequest(model=MODEL_NAME, messages=messages)
req_2 = ChatCompletionRequest(model=MODEL_NAME, messages=messages, tools=tools)
input_messages_2, _ = serving_chat._make_request_with_harmony(req_2)
verify_harmony_messages(
input_messages_2,
@ -1255,7 +1253,7 @@ class TestServingChatWithHarmony:
)
# Test the Harmony messages for the third turn's input
req_3 = ChatCompletionRequest(model=MODEL_NAME, messages=messages)
req_3 = ChatCompletionRequest(model=MODEL_NAME, messages=messages, tools=tools)
input_messages_3, _ = serving_chat._make_request_with_harmony(req_3)
verify_harmony_messages(
input_messages_3,
@ -1318,7 +1316,7 @@ class TestServingChatWithHarmony:
)
# Test the Harmony messages for the fourth turn's input
req_4 = ChatCompletionRequest(model=MODEL_NAME, messages=messages)
req_4 = ChatCompletionRequest(model=MODEL_NAME, messages=messages, tools=tools)
input_messages_4, _ = serving_chat._make_request_with_harmony(req_4)
verify_harmony_messages(
input_messages_4,
@ -1374,7 +1372,6 @@ class TestServingChatWithHarmony:
input_messages,
[
{"role": "system"},
{"role": "developer"},
{"role": "user", "content": messages[0]["content"]},
# The reasoning that would have resulted in an analysis message is
# dropped because of a later assistant message to the final channel.
@ -1406,7 +1403,6 @@ class TestServingChatWithHarmony:
input_messages,
[
{"role": "system"},
{"role": "developer"},
{"role": "user", "content": messages[0]["content"]},
{
"role": "assistant",
@ -1436,7 +1432,6 @@ class TestServingChatWithHarmony:
input_messages,
[
{"role": "system"},
{"role": "developer"},
{"role": "user", "content": messages[0]["content"]},
{
"role": "assistant",

9
vllm/entrypoints/openai/serving_chat.py
View File

@ -1828,10 +1828,11 @@ class OpenAIServingChat(OpenAIServing):
messages.append(sys_msg)
# Add developer message.
dev_msg = get_developer_message(
tools=request.tools if should_include_tools else None
)
messages.append(dev_msg)
if request.tools:
dev_msg = get_developer_message(
tools=request.tools if should_include_tools else None
)
messages.append(dev_msg)
# Add user message.
messages.extend(parse_chat_inputs_to_harmony_messages(request.messages))

9
vllm/tool_parsers/openai_tool_parser.py
View File

@ -79,6 +79,15 @@ class OpenAIToolParser(ToolParser):
elif msg.channel == "commentary" and not msg.recipient:
commentary_content = msg_text
# Extract partial content from the parser state if the generation was truncated
if parser.current_content:
if parser.current_channel == "final":
final_content = parser.current_content
elif (
parser.current_channel == "commentary" and not parser.current_recipient
):
commentary_content = parser.current_content
return ExtractedToolCallInformation(
tools_called=len(tool_calls) > 0,
tool_calls=tool_calls,