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fix:del some print ,and amend respback on stream judge ,and del in dingtalk this is_stream_output_supported() use

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This commit is contained in:
Dong_master
2025-07-29 23:09:02 +08:00
committed by Junyan Qin
parent 074d359c8e
commit a9776b7b53
10 changed files with 127 additions and 186 deletions
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pkg/provider/modelmgr/requesters/chatcmpl.py
+16 -31
View File
@@ -17,14 +17,13 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
"""OpenAI ChatCompletion API 请求器"""
client: openai.AsyncClient
is_content:bool
is_content: bool
default_config: dict[str, typing.Any] = {
'base_url': 'https://api.openai.com/v1',
'timeout': 120,
}
async def initialize(self):
self.client = openai.AsyncClient(
api_key='',
@@ -46,7 +45,6 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
args: dict,
extra_body: dict = {},
) -> chat_completion.ChatCompletion:
async for chunk in await self.client.chat.completions.create(**args, extra_body=extra_body):
yield chunk
@@ -66,23 +64,23 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
# deepseek的reasoner模型
if pipeline_config['trigger'].get('misc', '').get('remove_think'):
pass
else:
if reasoning_content is not None :
chatcmpl_message['content'] = '<think>\n' + reasoning_content + '\n</think>\n' + chatcmpl_message['content']
if reasoning_content is not None:
chatcmpl_message['content'] = (
'<think>\n' + reasoning_content + '\n</think>\n' + chatcmpl_message['content']
)
message = llm_entities.Message(**chatcmpl_message)
return message
async def _make_msg_chunk(
self,
pipeline_config: dict[str, typing.Any],
chat_completion: chat_completion.ChatCompletion,
idx: int,
) -> llm_entities.MessageChunk:
# 处理流式chunk和完整响应的差异
# print(chat_completion.choices[0])
if hasattr(chat_completion, 'choices'):
@@ -98,7 +96,6 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
if 'role' not in delta or delta['role'] is None:
delta['role'] = 'assistant'
reasoning_content = delta['reasoning_content'] if 'reasoning_content' in delta else None
delta['content'] = '' if delta['content'] is None else delta['content']
@@ -106,13 +103,13 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
# deepseek的reasoner模型
if pipeline_config['trigger'].get('misc', '').get('remove_think'):
if reasoning_content is not None :
if reasoning_content is not None:
pass
else:
delta['content'] = delta['content']
else:
if reasoning_content is not None and idx == 0:
delta['content'] += f'<think>\n{reasoning_content}'
delta['content'] += f'<think>\n{reasoning_content}'
elif reasoning_content is None:
if self.is_content:
delta['content'] = delta['content']
@@ -122,7 +119,6 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
else:
delta['content'] += reasoning_content
message = llm_entities.MessageChunk(**delta)
return message
@@ -135,9 +131,10 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
use_funcs: list[tools_entities.LLMFunction] = None,
stream: bool = False,
extra_args: dict[str, typing.Any] = {},
) -> llm_entities.Message | typing.AsyncGenerator[llm_entities.MessageChunk, None]:
) ->llm_entities.MessageChunk:
self.client.api_key = use_model.token_mgr.get_token()
args = {}
args['model'] = use_model.model_entity.name
@@ -163,14 +160,14 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
if stream:
current_content = ''
args["stream"] = True
args['stream'] = True
chunk_idx = 0
self.is_content = False
tool_calls_map: dict[str, llm_entities.ToolCall] = {}
pipeline_config = query.pipeline_config
async for chunk in self._req_stream(args, extra_body=extra_args):
# 处理流式消息
delta_message = await self._make_msg_chunk(pipeline_config,chunk,chunk_idx)
delta_message = await self._make_msg_chunk(pipeline_config, chunk, chunk_idx)
if delta_message.content:
current_content += delta_message.content
delta_message.content = current_content
@@ -182,15 +179,13 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
id=tool_call.id,
type=tool_call.type,
function=llm_entities.FunctionCall(
name=tool_call.function.name if tool_call.function else '',
arguments=''
name=tool_call.function.name if tool_call.function else '', arguments=''
),
)
if tool_call.function and tool_call.function.arguments:
# 流式处理中，工具调用参数可能分多个chunk返回，需要追加而不是覆盖
tool_calls_map[tool_call.id].function.arguments += tool_call.function.arguments
chunk_idx += 1
chunk_choices = getattr(chunk, 'choices', None)
if chunk_choices and getattr(chunk_choices[0], 'finish_reason', None):
@@ -198,11 +193,9 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
delta_message.content = current_content
if chunk_idx % 64 == 0 or delta_message.is_final:
yield delta_message
# return
async def _closure(
self,
query: core_entities.Query,
@@ -211,7 +204,7 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
use_funcs: list[tools_entities.LLMFunction] = None,
stream: bool = False,
extra_args: dict[str, typing.Any] = {},
) -> llm_entities.Message | typing.AsyncGenerator[llm_entities.MessageChunk, None]:
) -> llm_entities.Message:
self.client.api_key = use_model.token_mgr.get_token()
args = {}
@@ -237,22 +230,15 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
args['messages'] = messages
# 发送请求
resp = await self._req(args, extra_body=extra_args)
# 处理请求结果
pipeline_config = query.pipeline_config
message = await self._make_msg(resp,pipeline_config)
message = await self._make_msg(resp, pipeline_config)
return message
async def invoke_llm(
self,
query: core_entities.Query,
@@ -273,7 +259,6 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
req_messages.append(msg_dict)
try:
msg = await self._closure(
query=query,
req_messages=req_messages,
@@ -334,7 +319,7 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
funcs: typing.List[tools_entities.LLMFunction] = None,
stream: bool = False,
extra_args: dict[str, typing.Any] = {},
) -> llm_entities.MessageChunk:
) -> llm_entities.MessageChunk:
req_messages = [] # req_messages 仅用于类内，外部同步由 query.messages 进行
for m in messages:
msg_dict = m.dict(exclude_none=True)
pkg/provider/modelmgr/requesters/deepseekchatcmpl.py
+1 -1
View File
@@ -55,6 +55,6 @@ class DeepseekChatCompletions(chatcmpl.OpenAIChatCompletions):
raise errors.RequesterError('接口返回为空，请确定模型提供商服务是否正常')
pipeline_config = query.pipeline_config
# 处理请求结果
message = await self._make_msg(resp,pipeline_config)
message = await self._make_msg(resp, pipeline_config)
return message