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Merge pull request #2523 from xinnan-tech/fix_openai_LLM

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fix: 去除默认值配置
This commit is contained in:
hrz
2025-11-13 21:54:43 +08:00
committed by GitHub
parent 7c592e33fe 637b528aad
commit b37f87d231
1 changed files with 46 additions and 22 deletions
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main/xiaozhi-server/core/providers/llm/openai/openai.py
+46 -22
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@@ -21,22 +21,22 @@ class LLMProvider(LLMProviderBase):
self.timeout = int(timeout) if timeout else 300
param_defaults = {
"max_tokens": (500, int),
"temperature": (0.7, lambda x: round(float(x), 1)),
"top_p": (1.0, lambda x: round(float(x), 1)),
"frequency_penalty": (0, lambda x: round(float(x), 1)),
"max_tokens": int,
"temperature": lambda x: round(float(x), 1),
"top_p": lambda x: round(float(x), 1),
"frequency_penalty": lambda x: round(float(x), 1),
}
for param, (default, converter) in param_defaults.items():
for param, converter in param_defaults.items():
value = config.get(param)
try:
setattr(
self,
param,
converter(value) if value not in (None, "") else default,
converter(value) if value not in (None, "") else None,
)
except (ValueError, TypeError):
setattr(self, param, default)
setattr(self, param, None)
logger.debug(
f"意图识别参数初始化: {self.temperature}, {self.max_tokens}, {self.top_p}, {self.frequency_penalty}"
@@ -59,17 +59,25 @@ class LLMProvider(LLMProviderBase):
try:
dialogue = self.normalize_dialogue(dialogue)
responses = self.client.chat.completions.create(
model=self.model_name,
messages=dialogue,
stream=True,
max_tokens=kwargs.get("max_tokens", self.max_tokens),
temperature=kwargs.get("temperature", self.temperature),
top_p=kwargs.get("top_p", self.top_p),
frequency_penalty=kwargs.get(
"frequency_penalty", self.frequency_penalty
),
)
request_params = {
"model": self.model_name,
"messages": dialogue,
"stream": True,
}
# 添加可选参数,只有当参数不为None时才添加
optional_params = {
"max_tokens": kwargs.get("max_tokens", self.max_tokens),
"temperature": kwargs.get("temperature", self.temperature),
"top_p": kwargs.get("top_p", self.top_p),
"frequency_penalty": kwargs.get("frequency_penalty", self.frequency_penalty),
}
for key, value in optional_params.items():
if value is not None:
request_params[key] = value
responses = self.client.chat.completions.create(**request_params)
is_active = True
for chunk in responses:
@@ -91,13 +99,29 @@ class LLMProvider(LLMProviderBase):
except Exception as e:
logger.bind(tag=TAG).error(f"Error in response generation: {e}")
def response_with_functions(self, session_id, dialogue, functions=None):
def response_with_functions(self, session_id, dialogue, functions=None, **kwargs):
try:
dialogue = self.normalize_dialogue(dialogue)
stream = self.client.chat.completions.create(
model=self.model_name, messages=dialogue, stream=True, tools=functions
)
request_params = {
"model": self.model_name,
"messages": dialogue,
"stream": True,
"tools": functions,
}
optional_params = {
"max_tokens": kwargs.get("max_tokens", self.max_tokens),
"temperature": kwargs.get("temperature", self.temperature),
"top_p": kwargs.get("top_p", self.top_p),
"frequency_penalty": kwargs.get("frequency_penalty", self.frequency_penalty),
}
for key, value in optional_params.items():
if value is not None:
request_params[key] = value
stream = self.client.chat.completions.create(**request_params)
for chunk in stream:
if getattr(chunk, "choices", None):