Merge branch 'main' of http://git.unissense.tech/mula/imetting
commit
883a1a2f1b
|
|
@ -14,31 +14,19 @@ class LLMService:
|
|||
# 设置dashscope API key
|
||||
dashscope.api_key = config_module.QWEN_API_KEY
|
||||
|
||||
@property
|
||||
def model_name(self):
|
||||
"""动态获取模型名称"""
|
||||
return SystemConfigService.get_llm_model_name(default="qwen-plus")
|
||||
def _get_llm_call_params(self) -> Dict[str, Any]:
|
||||
"""
|
||||
获取 dashscope.Generation.call() 所需的参数字典
|
||||
|
||||
@property
|
||||
def system_prompt(self):
|
||||
"""动态获取系统提示词（fallback，优先使用prompts表）"""
|
||||
# 保留config中的system_prompt作为后备
|
||||
return config_module.LLM_CONFIG.get("system_prompt", "请根据提供的内容进行总结和分析。")
|
||||
|
||||
@property
|
||||
def time_out(self):
|
||||
"""动态获取超时时间"""
|
||||
return SystemConfigService.get_llm_timeout(default=120)
|
||||
|
||||
@property
|
||||
def temperature(self):
|
||||
"""动态获取temperature"""
|
||||
return SystemConfigService.get_llm_temperature(default=0.7)
|
||||
|
||||
@property
|
||||
def top_p(self):
|
||||
"""动态获取top_p"""
|
||||
return SystemConfigService.get_llm_top_p(default=0.9)
|
||||
Returns:
|
||||
Dict: 包含 model、timeout、temperature、top_p 的参数字典
|
||||
"""
|
||||
return {
|
||||
'model': SystemConfigService.get_llm_model_name(),
|
||||
'timeout': SystemConfigService.get_llm_timeout(),
|
||||
'temperature': SystemConfigService.get_llm_temperature(),
|
||||
'top_p': SystemConfigService.get_llm_top_p(),
|
||||
}
|
||||
|
||||
def get_task_prompt(self, task_type: str, cursor=None, prompt_id: Optional[int] = None) -> str:
|
||||
"""
|
||||
|
|
@ -91,23 +79,21 @@ class LLMService:
|
|||
|
||||
def _get_default_prompt(self, task_name: str) -> str:
|
||||
"""获取默认提示词"""
|
||||
system_prompt = config_module.LLM_CONFIG.get("system_prompt", "请根据提供的内容进行总结和分析。")
|
||||
default_prompts = {
|
||||
'MEETING_TASK': self.system_prompt, # 使用配置文件中的系统提示词
|
||||
'MEETING_TASK': system_prompt,
|
||||
'KNOWLEDGE_TASK': "请根据提供的信息生成知识库文章。",
|
||||
}
|
||||
return default_prompts.get(task_name, "请根据提供的内容进行总结和分析。")
|
||||
|
||||
def _call_llm_api_stream(self, prompt: str) -> Generator[str, None, None]:
|
||||
"""流式调用阿里Qwen3大模型API"""
|
||||
"""流式调用阿里Qwen大模型API"""
|
||||
try:
|
||||
responses = dashscope.Generation.call(
|
||||
model=self.model_name,
|
||||
**self._get_llm_call_params(),
|
||||
prompt=prompt,
|
||||
stream=True,
|
||||
timeout=self.time_out,
|
||||
temperature=self.temperature,
|
||||
top_p=self.top_p,
|
||||
incremental_output=True # 开启增量输出模式
|
||||
incremental_output=True
|
||||
)
|
||||
|
||||
for response in responses:
|
||||
|
|
@ -128,14 +114,11 @@ class LLMService:
|
|||
yield f"error: {error_msg}"
|
||||
|
||||
def _call_llm_api(self, prompt: str) -> Optional[str]:
|
||||
"""调用阿里Qwen3大模型API（非流式）"""
|
||||
"""调用阿里Qwen大模型API（非流式）"""
|
||||
try:
|
||||
response = dashscope.Generation.call(
|
||||
model=self.model_name,
|
||||
prompt=prompt,
|
||||
timeout=self.time_out,
|
||||
temperature=self.temperature,
|
||||
top_p=self.top_p
|
||||
**self._get_llm_call_params(),
|
||||
prompt=prompt
|
||||
)
|
||||
|
||||
if response.status_code == HTTPStatus.OK:
|
||||
|
|
|
|||
|
|
@ -65,6 +65,47 @@ class SystemConfigService:
|
|||
print(f"Error getting config {dict_code}: {e}")
|
||||
return default_value
|
||||
|
||||
@classmethod
|
||||
def get_config_attribute(cls, dict_code: str, attr_name: str, default_value: Any = None) -> Any:
|
||||
"""
|
||||
从指定配置记录的扩展属性中读取指定属性值
|
||||
|
||||
此方法用于处理扩展属性为复杂JSON的配置记录（如llm_model、voiceprint等）
|
||||
|
||||
Args:
|
||||
dict_code: 配置项编码 (如 'llm_model', 'voiceprint')
|
||||
attr_name: 扩展属性中的属性名 (如 'time_out', 'channels', 'template_text')
|
||||
default_value: 默认值，如果配置或属性不存在则返回此值
|
||||
|
||||
Returns:
|
||||
属性值
|
||||
"""
|
||||
try:
|
||||
with get_db_connection() as conn:
|
||||
cursor = conn.cursor(dictionary=True)
|
||||
query = """
|
||||
SELECT extension_attr
|
||||
FROM dict_data
|
||||
WHERE dict_type = %s AND dict_code = %s AND status = 1
|
||||
LIMIT 1
|
||||
"""
|
||||
cursor.execute(query, (cls.DICT_TYPE, dict_code))
|
||||
result = cursor.fetchone()
|
||||
cursor.close()
|
||||
|
||||
if result and result['extension_attr']:
|
||||
try:
|
||||
ext_attr = json.loads(result['extension_attr']) if isinstance(result['extension_attr'], str) else result['extension_attr']
|
||||
return ext_attr.get(attr_name, default_value)
|
||||
except (json.JSONDecodeError, AttributeError):
|
||||
pass
|
||||
|
||||
return default_value
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error getting config attribute {dict_code}.{attr_name}: {e}")
|
||||
return default_value
|
||||
|
||||
@classmethod
|
||||
def set_config(cls, dict_code: str, value: Any, label_cn: str = None) -> bool:
|
||||
"""
|
||||
|
|
@ -181,15 +222,16 @@ class SystemConfigService:
|
|||
"""获取ASR热词字典ID"""
|
||||
return cls.get_config(cls.ASR_VOCABULARY_ID)
|
||||
|
||||
# 声纹配置获取方法（直接使用通用方法）
|
||||
@classmethod
|
||||
def get_voiceprint_template(cls, default: str = "我正在进行声纹采集，这段语音将用于身份识别和验证。\n\n声纹技术能够准确识别每个人独特的声音特征。") -> str:
|
||||
"""获取声纹采集模版"""
|
||||
return cls.get_config(cls.VOICEPRINT_TEMPLATE_TEXT, default)
|
||||
return cls.get_config_attribute('voiceprint', 'template_text', default)
|
||||
|
||||
@classmethod
|
||||
def get_voiceprint_max_size(cls, default: int = 5242880) -> int:
|
||||
"""获取声纹文件大小限制 (bytes), 默认5MB"""
|
||||
value = cls.get_config(cls.VOICEPRINT_MAX_SIZE, default)
|
||||
value = cls.get_config_attribute('voiceprint', 'voiceprint_max_size', default)
|
||||
try:
|
||||
return int(value)
|
||||
except (ValueError, TypeError):
|
||||
|
|
@ -198,7 +240,7 @@ class SystemConfigService:
|
|||
@classmethod
|
||||
def get_voiceprint_duration(cls, default: int = 12) -> int:
|
||||
"""获取声纹采集最短时长 (秒)"""
|
||||
value = cls.get_config(cls.VOICEPRINT_DURATION, default)
|
||||
value = cls.get_config_attribute('voiceprint', 'duration_seconds', default)
|
||||
try:
|
||||
return int(value)
|
||||
except (ValueError, TypeError):
|
||||
|
|
@ -207,7 +249,7 @@ class SystemConfigService:
|
|||
@classmethod
|
||||
def get_voiceprint_sample_rate(cls, default: int = 16000) -> int:
|
||||
"""获取声纹采样率"""
|
||||
value = cls.get_config(cls.VOICEPRINT_SAMPLE_RATE, default)
|
||||
value = cls.get_config_attribute('voiceprint', 'sample_rate', default)
|
||||
try:
|
||||
return int(value)
|
||||
except (ValueError, TypeError):
|
||||
|
|
@ -216,7 +258,7 @@ class SystemConfigService:
|
|||
@classmethod
|
||||
def get_voiceprint_channels(cls, default: int = 1) -> int:
|
||||
"""获取声纹通道数"""
|
||||
value = cls.get_config(cls.VOICEPRINT_CHANNELS, default)
|
||||
value = cls.get_config_attribute('voiceprint', 'channels', default)
|
||||
try:
|
||||
return int(value)
|
||||
except (ValueError, TypeError):
|
||||
|
|
@ -245,16 +287,16 @@ class SystemConfigService:
|
|||
except (ValueError, TypeError):
|
||||
return default
|
||||
|
||||
# LLM模型配置获取方法
|
||||
# LLM模型配置获取方法（直接使用通用方法）
|
||||
@classmethod
|
||||
def get_llm_model_name(cls, default: str = "qwen-plus") -> str:
|
||||
"""获取LLM模型名称"""
|
||||
return cls.get_config(cls.LLM_MODEL_NAME, default)
|
||||
return cls.get_config_attribute('llm_model', 'model_name', default)
|
||||
|
||||
@classmethod
|
||||
def get_llm_timeout(cls, default: int = 120) -> int:
|
||||
def get_llm_timeout(cls, default: int = 300) -> int:
|
||||
"""获取LLM超时时间（秒）"""
|
||||
value = cls.get_config(cls.LLM_TIMEOUT, str(default))
|
||||
value = cls.get_config_attribute('llm_model', 'time_out', default)
|
||||
try:
|
||||
return int(value)
|
||||
except (ValueError, TypeError):
|
||||
|
|
@ -263,7 +305,7 @@ class SystemConfigService:
|
|||
@classmethod
|
||||
def get_llm_temperature(cls, default: float = 0.7) -> float:
|
||||
"""获取LLM temperature参数"""
|
||||
value = cls.get_config(cls.LLM_TEMPERATURE, str(default))
|
||||
value = cls.get_config_attribute('llm_model', 'temperature', default)
|
||||
try:
|
||||
return float(value)
|
||||
except (ValueError, TypeError):
|
||||
|
|
@ -272,7 +314,7 @@ class SystemConfigService:
|
|||
@classmethod
|
||||
def get_llm_top_p(cls, default: float = 0.9) -> float:
|
||||
"""获取LLM top_p参数"""
|
||||
value = cls.get_config(cls.LLM_TOP_P, str(default))
|
||||
value = cls.get_config_attribute('llm_model', 'top_p', default)
|
||||
try:
|
||||
return float(value)
|
||||
except (ValueError, TypeError):
|
||||
|
|
|
|||
Loading…
Reference in New Issue