410 lines
17 KiB
Python
410 lines
17 KiB
Python
from sqlalchemy.orm import Session
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from typing import List, Optional, Dict, Any
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import uuid
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import math
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import time
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import asyncio
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from app.models.models_model import ModelConfig, ModelApiKey, ModelType
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from app.repositories.model_repository import ModelConfigRepository, ModelApiKeyRepository
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from app.schemas import model_schema
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from app.schemas.model_schema import (
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ModelConfigCreate, ModelConfigUpdate, ModelApiKeyCreate, ModelApiKeyUpdate,
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ModelConfigQuery, ModelStats
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)
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from app.core.logging_config import get_business_logger
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from app.schemas.response_schema import PageData, PageMeta
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from app.core.exceptions import BusinessException
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from app.core.error_codes import BizCode
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logger = get_business_logger()
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class ModelConfigService:
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"""模型配置服务"""
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@staticmethod
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def get_model_by_id(db: Session, model_id: uuid.UUID) -> ModelConfig:
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"""根据ID获取模型配置"""
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model = ModelConfigRepository.get_by_id(db, model_id)
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if not model:
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raise BusinessException("模型配置不存在", BizCode.MODEL_NOT_FOUND)
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return model
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@staticmethod
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def get_model_list(db: Session, query: ModelConfigQuery) -> PageData:
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"""获取模型配置列表"""
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models, total = ModelConfigRepository.get_list(db, query)
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pages = math.ceil(total / query.pagesize) if total > 0 else 0
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return PageData(
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page=PageMeta(
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page=query.page,
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pagesize=query.pagesize,
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total=total,
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hasnext=query.page < pages
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),
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items=[model_schema.ModelConfig.model_validate(model) for model in models]
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)
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@staticmethod
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def get_model_by_name(db: Session, name: str) -> ModelConfig:
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"""根据名称获取模型配置"""
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model = ModelConfigRepository.get_by_name(db, name)
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if not model:
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raise BusinessException("模型配置不存在", BizCode.MODEL_NOT_FOUND)
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return model
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@staticmethod
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def search_models_by_name(db: Session, name: str, limit: int = 10) -> List[ModelConfig]:
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"""按名称模糊匹配获取模型配置列表"""
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return ModelConfigRepository.search_by_name(db, name, limit)
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@staticmethod
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async def validate_model_config(
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db: Session,
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*,
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model_name: str,
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provider: str,
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api_key: str,
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api_base: Optional[str] = None,
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model_type: str = "llm",
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test_message: str = "Hello"
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) -> Dict[str, Any]:
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"""验证模型配置是否有效
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Args:
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db: 数据库会话
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model_name: 模型名称
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provider: 提供商
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api_key: API密钥
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api_base: API基础URL
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model_type: 模型类型 (llm/chat/embedding/rerank)
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test_message: 测试消息
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Returns:
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Dict: 验证结果
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"""
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from app.core.models import RedBearLLM, RedBearRerank
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from app.core.models.base import RedBearModelConfig
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from app.core.models.embedding import RedBearEmbeddings
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import traceback
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try:
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start_time = time.time()
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model_config = RedBearModelConfig(
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model_name=model_name,
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provider=provider,
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api_key=api_key,
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base_url=api_base,
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temperature=0.7,
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max_tokens=100
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)
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# 根据模型类型选择不同的验证方式
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model_type_lower = model_type.lower()
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if model_type_lower in ["llm", "chat"]:
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# LLM/Chat 模型验证 - 统一使用字符串输入
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llm = RedBearLLM(model_config, type=ModelType.LLM if model_type_lower == "llm" else ModelType.CHAT)
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response = await llm.ainvoke(test_message)
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elapsed_time = time.time() - start_time
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content = response.content if hasattr(response, 'content') else str(response)
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usage = None
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if hasattr(response, 'usage_metadata'):
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usage = {
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"input_tokens": getattr(response.usage_metadata, 'input_tokens', 0),
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"output_tokens": getattr(response.usage_metadata, 'output_tokens', 0),
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"total_tokens": getattr(response.usage_metadata, 'total_tokens', 0)
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}
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return {
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"valid": True,
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"message": f"{model_type.upper()} 模型配置验证成功",
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"response": content,
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"elapsed_time": elapsed_time,
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"usage": usage,
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"error": None
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}
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elif model_type_lower == "embedding":
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# Embedding 模型验证（在线程中运行同步方法）
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embedding = RedBearEmbeddings(model_config)
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test_texts = [test_message, "测试文本"]
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vectors = await asyncio.to_thread(embedding.embed_documents, test_texts)
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elapsed_time = time.time() - start_time
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return {
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"valid": True,
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"message": "Embedding 模型配置验证成功",
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"response": f"成功生成 {len(vectors)} 个向量，维度: {len(vectors[0]) if vectors else 0}",
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"elapsed_time": elapsed_time,
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"usage": {
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"input_tokens": len(test_message),
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"vector_count": len(vectors),
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"vector_dimension": len(vectors[0]) if vectors else 0
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},
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"error": None
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}
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elif model_type_lower == "rerank":
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# Rerank 模型验证（在线程中运行同步方法）
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rerank = RedBearRerank(model_config)
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query = test_message
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documents = ["这是第一个文档", "这是第二个文档", "这是第三个文档"]
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results = await asyncio.to_thread(rerank.rerank, query=query, documents=documents, top_n=3)
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elapsed_time = time.time() - start_time
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return {
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"valid": True,
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"message": "Rerank 模型配置验证成功",
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"response": f"成功对 {len(documents)} 个文档进行重排序，返回 top {len(results) if results else 0} 结果",
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"elapsed_time": elapsed_time,
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"usage": {
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"query_length": len(query),
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"document_count": len(documents),
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"result_count": len(results) if results else 0
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},
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"error": None
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}
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else:
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return {
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"valid": False,
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"message": "不支持的模型类型",
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"response": None,
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"elapsed_time": None,
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"usage": None,
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"error": f"不支持的模型类型: {model_type}"
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}
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except Exception as e:
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# 提取详细的错误信息
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error_message = str(e)
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error_type = type(e).__name__
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print("=========error_message:",error_message.lower())
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# 特殊处理常见的错误类型
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if "unsupported countries" in error_message.lower() or "unsupported region" in error_message.lower():
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# 区域/国家限制（适用于所有提供商）
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error_message = "区域限制: 该模型在当前区域或国家/地区不可用，请检查提供商的服务区域限制"
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elif "ValidationException" in error_type or "ValidationException" in error_message:
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# 其他验证错误
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if "access denied" in error_message.lower():
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error_message = "访问被拒绝: 请检查 API 凭证和权限配置"
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else:
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error_message = f"验证失败: {error_message}"
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elif "AuthenticationError" in error_type or "authentication" in error_message.lower():
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error_message = "认证失败: API Key 无效或已过期"
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elif "RateLimitError" in error_type or "rate limit" in error_message.lower():
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error_message = "请求频率限制: 已超过 API 调用限制"
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elif "InvalidRequestError" in error_type or "invalid request" in error_message.lower():
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error_message = f"无效请求: {error_message}"
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elif "model_copy" in error_message:
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error_message = "模型消息格式错误: 请确保使用正确的模型类型（LLM/Chat）"
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# 记录详细错误日志
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logger.error(f"模型验证失败 - 类型: {error_type}, 模型: {model_name}, 提供商: {provider}")
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logger.error(f"错误详情: {error_message}")
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logger.debug(f"完整堆栈: {traceback.format_exc()}")
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return {
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"valid": False,
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"message": f"{model_type.upper()} 模型配置验证失败",
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"response": None,
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"elapsed_time": None,
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"usage": None,
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"error": error_message,
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"error_type": error_type
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}
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@staticmethod
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async def create_model(db: Session, model_data: ModelConfigCreate) -> ModelConfig:
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"""创建模型配置"""
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# 检查名称是否已存在
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if ModelConfigRepository.get_by_name(db, model_data.name):
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raise BusinessException("模型名称已存在", BizCode.DUPLICATE_NAME)
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# 验证配置
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if not model_data.skip_validation and model_data.api_keys:
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api_key_data = model_data.api_keys
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validation_result = await ModelConfigService.validate_model_config(
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db=db,
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model_name=api_key_data.model_name,
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provider=api_key_data.provider,
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api_key=api_key_data.api_key,
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api_base=api_key_data.api_base,
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model_type=model_data.type, # 传递模型类型
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test_message="Hello"
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)
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if not validation_result["valid"]:
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raise BusinessException(
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f"模型配置验证失败: {validation_result['error']}",
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BizCode.INVALID_PARAMETER
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)
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# 事务处理
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api_key_data = model_data.api_keys
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model_config_data = model_data.dict(exclude={"api_keys", "skip_validation"})
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model = ModelConfigRepository.create(db, model_config_data)
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db.flush() # 获取生成的 ID
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if api_key_data:
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api_key_create_schema = ModelApiKeyCreate(
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model_config_id=model.id,
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**api_key_data.dict()
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)
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ModelApiKeyRepository.create(db, api_key_create_schema)
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db.commit()
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db.refresh(model)
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return model
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@staticmethod
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def update_model(db: Session, model_id: uuid.UUID, model_data: ModelConfigUpdate) -> ModelConfig:
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"""更新模型配置"""
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existing_model = ModelConfigRepository.get_by_id(db, model_id)
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if not existing_model:
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raise BusinessException("模型配置不存在", BizCode.MODEL_NOT_FOUND)
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if model_data.name and model_data.name != existing_model.name:
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if ModelConfigRepository.get_by_name(db, model_data.name):
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raise BusinessException("模型名称已存在", BizCode.DUPLICATE_NAME)
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model = ModelConfigRepository.update(db, model_id, model_data)
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db.commit()
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db.refresh(model)
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return model
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@staticmethod
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def delete_model(db: Session, model_id: uuid.UUID) -> bool:
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"""删除模型配置"""
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if not ModelConfigRepository.get_by_id(db, model_id):
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raise BusinessException("模型配置不存在", BizCode.MODEL_NOT_FOUND)
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success = ModelConfigRepository.delete(db, model_id)
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db.commit()
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return success
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@staticmethod
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def get_model_stats(db: Session) -> ModelStats:
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"""获取模型统计信息"""
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stats_data = ModelConfigRepository.get_stats(db)
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return ModelStats(
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total_models=stats_data["total_models"],
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active_models=stats_data["active_models"],
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llm_count=stats_data["llm_count"],
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embedding_count=stats_data["embedding_count"],
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rerank_count=stats_data["rerank_count"],
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provider_stats=stats_data["provider_stats"]
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)
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class ModelApiKeyService:
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"""模型API Key服务"""
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@staticmethod
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def get_api_key_by_id(db: Session, api_key_id: uuid.UUID) -> ModelApiKey:
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"""根据ID获取API Key"""
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api_key = ModelApiKeyRepository.get_by_id(db, api_key_id)
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if not api_key:
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raise BusinessException("API Key不存在", BizCode.NOT_FOUND)
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return api_key
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@staticmethod
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def get_api_keys_by_model(db: Session, model_config_id: uuid.UUID, is_active: bool = True) -> List[ModelApiKey]:
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"""根据模型配置ID获取API Key列表"""
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if not ModelConfigRepository.get_by_id(db, model_config_id):
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raise BusinessException("模型配置不存在", BizCode.MODEL_NOT_FOUND)
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return ModelApiKeyRepository.get_by_model_config(db, model_config_id, is_active)
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@staticmethod
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async def create_api_key(db: Session, api_key_data: ModelApiKeyCreate) -> ModelApiKey:
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"""创建API Key"""
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model_config = ModelConfigRepository.get_by_id(db, api_key_data.model_config_id)
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if not model_config:
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raise BusinessException("模型配置不存在", BizCode.MODEL_NOT_FOUND)
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validation_result = await ModelConfigService.validate_model_config(
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db=db,
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model_name=api_key_data.model_name,
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provider=api_key_data.provider,
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api_key=api_key_data.api_key,
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api_base=api_key_data.api_base,
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model_type=model_config.type, # 传递模型类型
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test_message="Hello"
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)
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print(validation_result)
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if not validation_result["valid"]:
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raise BusinessException(
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f"模型配置验证失败: {validation_result['error']}",
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BizCode.INVALID_PARAMETER
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)
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api_key = ModelApiKeyRepository.create(db, api_key_data)
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db.commit()
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db.refresh(api_key)
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return api_key
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@staticmethod
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async def update_api_key(db: Session, api_key_id: uuid.UUID, api_key_data: ModelApiKeyUpdate) -> ModelApiKey:
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"""更新API Key"""
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existing_api_key = ModelApiKeyRepository.get_by_id(db, api_key_id)
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if not existing_api_key:
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raise BusinessException("API Key不存在", BizCode.NOT_FOUND)
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# 获取关联的模型配置以获取模型类型
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model_config = ModelConfigRepository.get_by_id(db, existing_api_key.model_config_id)
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if not model_config:
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raise BusinessException("关联的模型配置不存在", BizCode.MODEL_NOT_FOUND)
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validation_result = await ModelConfigService.validate_model_config(
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db=db,
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model_name=api_key_data.model_name,
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provider=api_key_data.provider,
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api_key=api_key_data.api_key,
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api_base=api_key_data.api_base,
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model_type=model_config.type, # 传递模型类型
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test_message="Hello"
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)
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print(validation_result)
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if not validation_result["valid"]:
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raise BusinessException(
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f"模型配置验证失败: {validation_result['error']}",
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BizCode.INVALID_PARAMETER
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)
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api_key = ModelApiKeyRepository.update(db, api_key_id, api_key_data)
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db.commit()
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db.refresh(api_key)
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return api_key
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@staticmethod
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def delete_api_key(db: Session, api_key_id: uuid.UUID) -> bool:
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"""删除API Key"""
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if not ModelApiKeyRepository.get_by_id(db, api_key_id):
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raise BusinessException("API Key不存在", BizCode.NOT_FOUND)
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success = ModelApiKeyRepository.delete(db, api_key_id)
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db.commit()
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return success
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@staticmethod
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def get_available_api_key(db: Session, model_config_id: uuid.UUID) -> Optional[ModelApiKey]:
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"""获取可用的API Key（按优先级和负载均衡）"""
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api_keys = ModelApiKeyRepository.get_by_model_config(db, model_config_id, is_active=True)
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if not api_keys:
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return None
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return min(api_keys, key=lambda x: int(x.usage_count or "0"))
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@staticmethod
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def record_api_key_usage(db: Session, api_key_id: uuid.UUID) -> bool:
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"""记录API Key使用"""
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success = ModelApiKeyRepository.update_usage(db, api_key_id)
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if success:
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db.commit()
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return success
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