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"""
Base Router - 共用的路由基础功能
提供模型列表处理、通用响应等共同功能
"""
from typing import List, Optional
from src.models import Model, ModelList
# ==================== 模型列表处理 ====================
def expand_models_with_features(
base_models: List[str],
features: Optional[List[str]] = None
) -> List[str]:
"""
使用特性前缀扩展模型列表
Args:
base_models: 基础模型列表
features: 特性前缀列表，如 ["流式抗截断", "假流式"]
Returns:
扩展后的模型列表（包含原始模型和特性变体）
"""
if not features:
return base_models.copy()
expanded = []
for model in base_models:
# 添加原始模型
expanded.append(model)
# 添加特性变体
for feature in features:
expanded.append(f"{feature}/{model}")
return expanded
def create_openai_model_list(
model_ids: List[str],
owned_by: str = "google"
) -> ModelList:
"""
创建OpenAI格式的模型列表
Args:
model_ids: 模型ID列表
owned_by: 模型所有者
Returns:
ModelList对象
"""
from datetime import datetime, timezone
current_timestamp = int(datetime.now(timezone.utc).timestamp())
models = [
Model(
id=model_id,
object='model',
created=current_timestamp,
owned_by=owned_by
)
for model_id in model_ids
]
return ModelList(data=models)
def create_gemini_model_list(
model_ids: List[str],
base_name_extractor=None
) -> dict:
"""
创建Gemini格式的模型列表
Args:
model_ids: 模型ID列表
base_name_extractor: 可选的基础模型名提取函数
Returns:
包含模型列表的字典
"""
gemini_models = []
for model_id in model_ids:
base_model = model_id
if base_name_extractor:
try:
base_model = base_name_extractor(model_id)
except Exception:
pass
model_info = {
"name": f"models/{model_id}",
"baseModelId": base_model,
"version": "001",
"displayName": model_id,
"description": f"Gemini {base_model} model",
"supportedGenerationMethods": ["generateContent", "streamGenerateContent"],
}
gemini_models.append(model_info)
return {"models": gemini_models} |