154 lines
5.0 KiB
Python
154 lines
5.0 KiB
Python
"""
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模型接口模块
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提供 OpenAI 兼容的 /v1/models 端点，返回系统支持的所有模型列表。
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"""
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import time
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from typing import Dict, Any, List, Optional
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from fastapi import APIRouter, HTTPException, Depends
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from app.models.grok_models import Models
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from app.core.auth import auth_manager
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from app.core.logger import logger
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# 配置日志
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# 创建路由器
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router = APIRouter(tags=["模型"])
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@router.get("/models")
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async def list_models(authenticated: Optional[str] = Depends(auth_manager.verify)) -> Dict[str, Any]:
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"""
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获取可用模型列表
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返回 OpenAI 兼容的模型列表格式，包含系统支持的所有 Grok 模型的详细信息。
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Args:
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authenticated: 认证状态（由依赖注入）
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Returns:
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Dict[str, Any]: 包含模型列表的响应数据
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"""
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try:
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logger.debug("[Models] 请求获取模型列表")
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# 获取当前时间戳
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current_timestamp = int(time.time())
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# 构建模型数据列表
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model_data: List[Dict[str, Any]] = []
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for model in Models:
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model_id = model.value
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config = Models.get_model_info(model_id)
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# 基础信息
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model_info = {
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"id": model_id,
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"object": "model",
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"created": current_timestamp,
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"owned_by": "x-ai",
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"display_name": config.get("display_name", model_id),
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"description": config.get("description", ""),
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"raw_model_path": config.get("raw_model_path", f"xai/{model_id}"),
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"default_temperature": config.get("default_temperature", 1.0),
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"default_max_output_tokens": config.get("default_max_output_tokens", 8192),
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"supported_max_output_tokens": config.get("supported_max_output_tokens", 131072),
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"default_top_p": config.get("default_top_p", 0.95)
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}
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model_data.append(model_info)
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# 构建响应
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response = {
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"object": "list",
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"data": model_data
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}
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logger.debug(f"[Models] 成功返回 {len(model_data)} 个模型")
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return response
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except Exception as e:
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logger.error(f"[Models] 获取模型列表时发生错误: {str(e)}")
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raise HTTPException(
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status_code=500,
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detail={
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"error": {
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"message": f"Failed to retrieve models: {str(e)}",
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"type": "internal_error",
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"code": "model_list_error"
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}
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}
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)
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@router.get("/models/{model_id}")
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async def get_model(model_id: str, authenticated: Optional[str] = Depends(auth_manager.verify)) -> Dict[str, Any]:
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"""
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获取特定模型信息
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Args:
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model_id (str): 模型ID
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authenticated: 认证状态（由依赖注入）
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Returns:
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Dict[str, Any]: 模型详细信息
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"""
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try:
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logger.debug(f"[Models] 请求获取模型信息: {model_id}")
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# 验证模型是否存在
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if not Models.is_valid_model(model_id):
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logger.warning(f"[Models] 请求的模型不存在: {model_id}")
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raise HTTPException(
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status_code=404,
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detail={
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"error": {
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"message": f"Model '{model_id}' not found",
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"type": "invalid_request_error",
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"code": "model_not_found"
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}
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}
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)
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# 获取当前时间戳
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current_timestamp = int(time.time())
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# 获取模型配置
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config = Models.get_model_info(model_id)
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# 构建模型信息
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model_info = {
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"id": model_id,
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"object": "model",
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"created": current_timestamp,
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"owned_by": "x-ai",
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"display_name": config.get("display_name", model_id),
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"description": config.get("description", ""),
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"raw_model_path": config.get("raw_model_path", f"xai/{model_id}"),
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"default_temperature": config.get("default_temperature", 1.0),
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"default_max_output_tokens": config.get("default_max_output_tokens", 8192),
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"supported_max_output_tokens": config.get("supported_max_output_tokens", 131072),
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"default_top_p": config.get("default_top_p", 0.95)
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}
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logger.debug(f"[Models] 成功返回模型信息: {model_id}")
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return model_info
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"[Models] 获取模型信息时发生错误: {str(e)}")
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raise HTTPException(
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status_code=500,
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detail={
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"error": {
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"message": f"Failed to retrieve model: {str(e)}",
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"type": "internal_error",
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"code": "model_retrieve_error"
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}
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}
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)
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