mirror of
https://github.com/snailyp/gemini-balance.git
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- 统一 add_error_log 的 request_time:优先使用 request_datetime, 否则使用 datetime.now(),去除 timezone.utc,避免与请求日志时区不一致 - 在 Gemini/OpenAI/Vertex/Embedding 等服务的异常处理处补充传入 request_datetime,使错误日志与请求日志可一一对应 - stats: 移除失败记录的错误日志时间窗匹配与 error_log_id 附带,降低查询开销 与误关联风险;建议通过统一时间戳(key + request_time)或独立错误日志 查询接口完成关联 - 调整部分导入顺序与长行换行等代码风格,无功能改动 BREAKING CHANGE: 统计详情接口不再返回 error_log_id 字段。需要关联错误日志的 客户端请改为基于 key 与 request_time 在错误日志接口中检索。
195 lines
7.1 KiB
Python
195 lines
7.1 KiB
Python
import datetime
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import json
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import re
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import time
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from typing import Any, AsyncGenerator, Dict, Union
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from app.config.config import settings
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from app.database.services import (
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add_error_log,
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add_request_log,
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)
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from app.domain.openai_models import ChatRequest, ImageGenerationRequest
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from app.log.logger import get_openai_compatible_logger
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from app.service.client.api_client import OpenaiApiClient
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from app.service.key.key_manager import KeyManager
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from app.utils.helpers import redact_key_for_logging
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logger = get_openai_compatible_logger()
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class OpenAICompatiableService:
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def __init__(self, base_url: str, key_manager: KeyManager = None):
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self.key_manager = key_manager
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self.base_url = base_url
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self.api_client = OpenaiApiClient(base_url, settings.TIME_OUT)
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async def get_models(self, api_key: str) -> Dict[str, Any]:
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return await self.api_client.get_models(api_key)
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async def create_chat_completion(
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self,
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request: ChatRequest,
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api_key: str,
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) -> Union[Dict[str, Any], AsyncGenerator[str, None]]:
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"""创建聊天完成"""
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request_dict = request.model_dump()
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# 移除值为null的
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request_dict = {k: v for k, v in request_dict.items() if v is not None}
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del request_dict["top_k"] # 删除top_k参数,目前不支持该参数
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if request.stream:
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return self._handle_stream_completion(request.model, request_dict, api_key)
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return await self._handle_normal_completion(
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request.model, request_dict, api_key
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)
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async def generate_images(
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self,
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request: ImageGenerationRequest,
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) -> Dict[str, Any]:
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"""生成图片"""
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request_dict = request.model_dump()
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# 移除值为null的
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request_dict = {k: v for k, v in request_dict.items() if v is not None}
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api_key = settings.PAID_KEY
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return await self.api_client.generate_images(request_dict, api_key)
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async def create_embeddings(
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self,
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input_text: str,
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model: str,
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api_key: str,
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) -> Dict[str, Any]:
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"""创建嵌入"""
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return await self.api_client.create_embeddings(input_text, model, api_key)
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async def _handle_normal_completion(
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self, model: str, request: dict, api_key: str
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) -> Dict[str, Any]:
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"""处理普通聊天完成"""
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start_time = time.perf_counter()
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request_datetime = datetime.datetime.now()
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is_success = False
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status_code = None
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response = None
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try:
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response = await self.api_client.generate_content(request, api_key)
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is_success = True
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status_code = 200
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return response
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except Exception as e:
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is_success = False
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error_log_msg = str(e)
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logger.error(f"Normal API call failed with error: {error_log_msg}")
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match = re.search(r"status code (\d+)", error_log_msg)
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if match:
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status_code = int(match.group(1))
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else:
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status_code = 500
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await add_error_log(
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gemini_key=api_key,
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model_name=model,
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error_type="openai-compatiable-non-stream",
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error_log=error_log_msg,
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error_code=status_code,
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request_msg=request,
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)
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raise e
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finally:
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end_time = time.perf_counter()
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latency_ms = int((end_time - start_time) * 1000)
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await add_request_log(
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model_name=model,
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api_key=api_key,
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is_success=is_success,
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status_code=status_code,
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latency_ms=latency_ms,
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request_time=request_datetime,
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)
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async def _handle_stream_completion(
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self, model: str, payload: dict, api_key: str
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) -> AsyncGenerator[str, None]:
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"""处理流式聊天完成,添加重试逻辑"""
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retries = 0
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max_retries = settings.MAX_RETRIES
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is_success = False
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status_code = None
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final_api_key = api_key
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while retries < max_retries:
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start_time = time.perf_counter()
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request_datetime = datetime.datetime.now()
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current_attempt_key = api_key
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final_api_key = current_attempt_key
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try:
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async for line in self.api_client.stream_generate_content(
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payload, current_attempt_key
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):
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if line.startswith("data:"):
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# print(line)
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yield line + "\n\n"
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logger.info("Streaming completed successfully")
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is_success = True
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status_code = 200
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break
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except Exception as e:
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retries += 1
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is_success = False
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error_log_msg = str(e)
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logger.warning(
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f"Streaming API call failed with error: {error_log_msg}. Attempt {retries} of {max_retries}"
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)
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match = re.search(r"status code (\d+)", error_log_msg)
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if match:
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status_code = int(match.group(1))
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else:
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status_code = 500
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await add_error_log(
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gemini_key=current_attempt_key,
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model_name=model,
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error_type="openai-compatiable-stream",
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error_log=error_log_msg,
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error_code=status_code,
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request_msg=payload,
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request_datetime=request_datetime,
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)
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if self.key_manager:
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api_key = await self.key_manager.handle_api_failure(
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current_attempt_key, retries
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)
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if api_key:
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logger.info(
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f"Switched to new API key: {redact_key_for_logging(api_key)}"
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)
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else:
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logger.error(
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f"No valid API key available after {retries} retries."
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)
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break
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else:
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logger.error("KeyManager not available for retry logic.")
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break
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if retries >= max_retries:
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logger.error(f"Max retries ({max_retries}) reached for streaming.")
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break
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finally:
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end_time = time.perf_counter()
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latency_ms = int((end_time - start_time) * 1000)
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await add_request_log(
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model_name=model,
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api_key=final_api_key,
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is_success=is_success,
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status_code=status_code,
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latency_ms=latency_ms,
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request_time=request_datetime,
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)
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if not is_success and retries >= max_retries:
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yield f"data: {json.dumps({'error': 'Streaming failed after retries'})}\n\n"
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yield "data: [DONE]\n\n"
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