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- from typing import Dict, Any
- from pydantic import BaseModel
- class ModelConfig(BaseModel):
- """AI模型配置类"""
- api_key: str
- api_base: str
- model_name: str
- temperature: float = 0
- max_tokens: int = 2000
- # AI模型配置
- model_list: Dict[str, Dict[str, Any]] = {
- "openai": {
- "api_key": "none",
- "api_base": "http://ac.zjugis.com:8511/v1",
- "model_name": "qwen2.5-instruct"
- },
- "azure": {
- "api_key": "your-azure-api-key",
- "api_base": "https://your-azure-endpoint.openai.azure.com",
- "model_name": "gpt-35-turbo",
- "temperature": 0,
- "max_tokens": 2000
- },
- "local": {
- "api_key": "your-local-api-key",
- "api_base": "http://localhost:8000/v1",
- "model_name": "local-model",
- "temperature": 0,
- "max_tokens": 2000
- }
- }
- def get_model_config(model_type: str = "openai") -> ModelConfig:
- """
- 获取模型配置
- :param model_type: 模型类型,默认为openai
- :return: 模型配置对象
- """
- if model_type not in model_list:
- raise ValueError(f"Unsupported model type: {model_type}")
-
- return ModelConfig(**model_list[model_type])
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