feat: 更新环境配置和Gemini客户端,支持多个Google API密钥并实现限流重试机制
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# 使用Python 3.11官方镜像作为基础镜像
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FROM python:3.11-slim
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# 设置工作目录
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WORKDIR /app
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# 设置环境变量
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ENV PYTHONDONTWRITEBYTECODE=1 \
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PYTHONUNBUFFERED=1 \
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PYTHONPATH=/app/src
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# 安装系统依赖,包括ffmpeg
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RUN apt-get update && apt-get install -y \
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build-essential \
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libpq-dev \
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curl \
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ffmpeg \
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&& rm -rf /var/lib/apt/lists/*
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# 验证ffmpeg安装
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RUN ffmpeg -version
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# 复制requirements文件并安装Python依赖
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COPY requirements.txt .
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RUN pip install --no-cache-dir --upgrade pip && \
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pip install --no-cache-dir -r requirements.txt
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# 复制项目文件
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COPY . .
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# 创建日志目录
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RUN mkdir -p /app/logs
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# 创建非root用户
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RUN useradd --create-home --shell /bin/bash app && \
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chown -R app:app /app
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USER app
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# 暴露端口
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EXPOSE 8000
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# 健康检查
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HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
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CMD curl -f http://localhost:8000/docs || exit 1
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# 启动命令
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CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000", "--app-dir", "src"]
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@ -8,6 +8,8 @@ QINIU_BUCKET_NAME="your_qiniu_bucket_name"
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QINIU_DOMAIN="your_qiniu_cdn_domain"
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QINIU_DOMAIN="your_qiniu_cdn_domain"
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# AI Models
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# AI Models
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GOOGLE_API_KEY="your_google_ai_api_key"
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# Google API Keys,支持单个或多个key(用逗号分隔),用于处理限流重试
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GOOGLE_API_KEYS="your_google_ai_api_key"
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# 多个key示例: GOOGLE_API_KEYS="key1,key2,key3"
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OPENROUTER_API_KEY="your_openrouter_api_key"
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OPENROUTER_API_KEY="your_openrouter_api_key"
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OPENROUTER_BASE_URL="https://openrouter.ai/api/v1"
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OPENROUTER_BASE_URL="https://openrouter.ai/api/v1"
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@ -18,7 +18,7 @@ class Settings(BaseSettings):
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qiniu_domain: str
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qiniu_domain: str
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# AI Models
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# AI Models
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google_api_key: str
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google_api_keys: str
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openrouter_api_key: str
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openrouter_api_key: str
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openrouter_base_url: str = "https://openrouter.ai/api/v1"
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openrouter_base_url: str = "https://openrouter.ai/api/v1"
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162
src/infrastructure/external/gemini_client.py
vendored
162
src/infrastructure/external/gemini_client.py
vendored
@ -10,17 +10,77 @@ from google import genai
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from google.genai import types
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from google.genai import types
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from ..config import settings
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from ..config import settings
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from ..utils import safe_json_loads
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from ..utils import safe_json_loads
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from .key_pool_manager import key_pool_manager
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from loguru import logger
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from loguru import logger
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import ssl
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import ssl
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import urllib3
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import urllib3
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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client = genai.Client(api_key=settings.google_api_key)
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class GeminiClient:
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class GeminiClient:
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"""Gemini AI客户端"""
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"""Gemini AI客户端"""
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def __init__(self):
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self._current_client = None
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self._refresh_client()
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def _refresh_client(self):
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"""刷新客户端,使用当前key"""
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current_key = key_pool_manager.get_current_key()
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self._current_client = genai.Client(api_key=current_key)
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def _execute_with_retry(self, func, *args, **kwargs):
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"""
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执行函数并处理429错误重试
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Args:
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func: 要执行的函数
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*args: 函数参数
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**kwargs: 函数关键字参数
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Returns:
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函数执行结果
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Raises:
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Exception: 所有key都尝试过后仍然失败
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"""
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key_pool_manager.reset_to_first_key() # 每次请求都从第一个key开始
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self._refresh_client()
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last_exception = None
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tried_keys = 0
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max_keys = len(key_pool_manager.get_all_keys())
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while tried_keys < max_keys:
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try:
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tried_keys += 1
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logger.info(f"使用第{tried_keys}个key尝试请求")
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return func(*args, **kwargs)
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except Exception as e:
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last_exception = e
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error_str = str(e).lower()
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# 检查是否是429错误
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if '429' in error_str or 'rate limit' in error_str or 'quota' in error_str:
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logger.warning(f"遇到限流错误: {e}")
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# 如果还有更多key可以尝试
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if key_pool_manager.switch_to_next_key():
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self._refresh_client()
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logger.info("切换到下一个key继续尝试")
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continue
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else:
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logger.error("所有key都已尝试,仍然遇到限流")
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break
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else:
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# 非429错误,直接抛出,不重试
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logger.error(f"遇到非限流错误,不重试: {e}")
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raise e
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# 所有key都尝试过了,抛出最后一个异常
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logger.error(f"所有{max_keys}个key都已尝试,请求失败")
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raise last_exception
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def generate_image_from_prompt(
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def generate_image_from_prompt(
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self,
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self,
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prompt: str,
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prompt: str,
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@ -36,7 +96,7 @@ class GeminiClient:
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Returns:
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Returns:
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生成的图片二进制数据,失败返回None
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生成的图片二进制数据,失败返回None
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"""
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"""
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try:
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def _generate_image():
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# 构建图片生成提示词
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# 构建图片生成提示词
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image_prompt = f'''
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image_prompt = f'''
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Generate an image strictly according to the following prompt without any confirmation, questioning, or omission:
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Generate an image strictly according to the following prompt without any confirmation, questioning, or omission:
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contents.append(image_prompt)
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contents.append(image_prompt)
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# 调用Gemini API生成图片
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# 调用Gemini API生成图片
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response = client.models.generate_content(
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response = self._current_client.models.generate_content(
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model='gemini-2.5-flash-image-preview',
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model='gemini-2.5-flash-image-preview',
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contents=contents,
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contents=contents,
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config=types.GenerateContentConfig(
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config=types.GenerateContentConfig(
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http_options=types.HttpOptions(timeout=30000)
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http_options=types.HttpOptions(timeout=30000)
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)
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)
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)
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)
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return response
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try:
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response = self._execute_with_retry(_generate_image)
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text = None
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text = None
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image_base64 = None
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image_base64 = None
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if hasattr(response, 'candidates') and response.candidates:
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if hasattr(response, 'candidates') and response.candidates:
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@ -92,7 +156,7 @@ class GeminiClient:
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Returns:
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Returns:
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分析结果字典,包含name、description、tags
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分析结果字典,包含name、description、tags
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"""
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"""
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try:
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def _analyze_image():
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prompt = """
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prompt = """
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请分析这张图片,并返回以下JSON格式的结果:
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请分析这张图片,并返回以下JSON格式的结果:
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{
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{
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@ -104,7 +168,7 @@ class GeminiClient:
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请确保返回的是有效的JSON格式,不要包含其他文字。
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请确保返回的是有效的JSON格式,不要包含其他文字。
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"""
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"""
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response = client.models.generate_content(
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response = self._current_client.models.generate_content(
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model='gemini-2.5-flash',
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model='gemini-2.5-flash',
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contents=[
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contents=[
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prompt,
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prompt,
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@ -114,6 +178,10 @@ class GeminiClient:
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)
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)
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]
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]
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)
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)
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return response
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try:
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response = self._execute_with_retry(_analyze_image)
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# 解析返回的JSON
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# 解析返回的JSON
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result_text = response.text
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result_text = response.text
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@ -141,25 +209,28 @@ class GeminiClient:
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Returns:
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Returns:
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生成的视频二进制数据,失败返回None
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生成的视频二进制数据,失败返回None
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"""
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"""
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try:
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def _generate_video():
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# 构建视频生成提示词
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# 构建视频生成提示词
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video_prompt = f"Create a video with the following prompt: {shot_prompt}"
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video_prompt = f"Create a video with the following prompt: {shot_prompt}"
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image_input = types.Image(image_bytes=frame_image_bytes, mime_type="image/jpeg")
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image_input = types.Image(image_bytes=frame_image_bytes, mime_type="image/jpeg")
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# 调用Veo-3.0 API生成视频
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# 调用Veo-3.0 API生成视频
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operation = client.models.generate_videos(
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operation = self._current_client.models.generate_videos(
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model="veo-3.0-fast-generate-preview", #veo-3.0-generate-preview
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model="veo-3.0-fast-generate-preview", #veo-3.0-generate-preview
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prompt=video_prompt,
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prompt=video_prompt,
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image=image_input
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image=image_input
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)
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)
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return operation
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try:
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operation = self._execute_with_retry(_generate_video)
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# 轮询操作状态直到视频生成完成
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# 轮询操作状态直到视频生成完成
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logger.info("等待视频生成完成...")
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logger.info("等待视频生成完成...")
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while not operation.done:
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while not operation.done:
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time.sleep(2)
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time.sleep(2)
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operation = client.operations.get(operation)
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operation = self._current_client.operations.get(operation)
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# 下载生成的视频
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# 下载生成的视频
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@ -172,7 +243,7 @@ class GeminiClient:
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raise Exception(operation.response.rai_media_filtered_reasons[0])
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raise Exception(operation.response.rai_media_filtered_reasons[0])
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raise Exception("未知错误")
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raise Exception("未知错误")
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video_bytes = client.files.download(file=video.video)
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video_bytes = self._current_client.files.download(file=video.video)
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logger.info("Veo-3.0视频生成成功")
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logger.info("Veo-3.0视频生成成功")
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return video_bytes
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return video_bytes
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@ -207,32 +278,35 @@ class GeminiClient:
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temp_video_path = temp_file.name
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temp_video_path = temp_file.name
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try:
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try:
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# 上传视频文件到Gemini
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def _upload_and_analyze():
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logger.info("正在上传视频到Gemini...")
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# 上传视频文件到Gemini
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myfile = client.files.upload(file=temp_video_path)
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logger.info("正在上传视频到Gemini...")
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logger.info(f"视频上传成功,文件ID: {myfile.name}")
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myfile = self._current_client.files.upload(file=temp_video_path)
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logger.info(f"视频上传成功,文件ID: {myfile.name}")
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# 等待文件变为ACTIVE状态
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# 等待文件变为ACTIVE状态
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logger.info("等待文件处理完成...")
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logger.info("等待文件处理完成...")
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max_wait_time = 300 # 最多等待5分钟
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max_wait_time = 300 # 最多等待5分钟
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wait_interval = 5 # 每5秒检查一次
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wait_interval = 5 # 每5秒检查一次
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waited_time = 0
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waited_time = 0
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while waited_time < max_wait_time:
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while waited_time < max_wait_time:
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file_info = client.files.get(name=myfile.name)
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file_info = self._current_client.files.get(name=myfile.name)
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logger.info(f"文件状态: {file_info.state}")
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logger.info(f"文件状态: {file_info.state}")
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if file_info.state == "ACTIVE":
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if file_info.state == "ACTIVE":
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logger.info("文件已准备就绪,开始分析")
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logger.info("文件已准备就绪,开始分析")
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break
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break
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elif file_info.state == "FAILED":
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elif file_info.state == "FAILED":
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raise Exception("文件处理失败")
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raise Exception("文件处理失败")
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time.sleep(wait_interval)
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time.sleep(wait_interval)
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waited_time += wait_interval
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waited_time += wait_interval
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if waited_time >= max_wait_time:
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if waited_time >= max_wait_time:
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raise Exception("文件处理超时")
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raise Exception("文件处理超时")
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return myfile
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# 构建分析提示词
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# 构建分析提示词
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analysis_prompt = """
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analysis_prompt = """
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@ -266,15 +340,21 @@ class GeminiClient:
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6. 确保返回的是有效的JSON格式,不要包含其他文字
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6. 确保返回的是有效的JSON格式,不要包含其他文字
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"""
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"""
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# 调用Gemini分析视频
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myfile = self._execute_with_retry(_upload_and_analyze)
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logger.info("正在分析视频内容...")
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response = client.models.generate_content(
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def _analyze_video_content():
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model="gemini-2.5-flash",
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# 调用Gemini分析视频
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contents=[myfile, analysis_prompt],
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logger.info("正在分析视频内容...")
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config=types.GenerateContentConfig(
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response = self._current_client.models.generate_content(
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http_options=types.HttpOptions(timeout=120000) # 2分钟超时
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model="gemini-2.5-flash",
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contents=[myfile, analysis_prompt],
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config=types.GenerateContentConfig(
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http_options=types.HttpOptions(timeout=120000) # 2分钟超时
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)
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)
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)
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)
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return response
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response = self._execute_with_retry(_analyze_video_content)
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# 解析返回的JSON
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# 解析返回的JSON
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result_text = response.text
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result_text = response.text
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61
src/infrastructure/external/key_pool_manager.py
vendored
Normal file
61
src/infrastructure/external/key_pool_manager.py
vendored
Normal file
@ -0,0 +1,61 @@
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from typing import List, Optional, Iterator
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from loguru import logger
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import threading
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from ..config import settings
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|
||||||
|
class KeyPoolManager:
|
||||||
|
"""Google API Key池管理器,用于处理限流重试"""
|
||||||
|
|
||||||
|
def __init__(self):
|
||||||
|
self._keys: List[str] = []
|
||||||
|
self._current_index = 0
|
||||||
|
self._lock = threading.Lock()
|
||||||
|
self._initialize_keys()
|
||||||
|
|
||||||
|
def _initialize_keys(self):
|
||||||
|
"""初始化key池"""
|
||||||
|
# 解析key字符串,支持单个或多个key
|
||||||
|
self._keys = [key.strip() for key in settings.google_api_keys.split(',') if key.strip()]
|
||||||
|
if not self._keys:
|
||||||
|
raise ValueError("GOOGLE_API_KEYS不能为空")
|
||||||
|
logger.info(f"初始化Google API Key池,共{len(self._keys)}个key")
|
||||||
|
|
||||||
|
def get_current_key(self) -> str:
|
||||||
|
"""获取当前key"""
|
||||||
|
with self._lock:
|
||||||
|
if not self._keys:
|
||||||
|
raise ValueError("没有可用的Google API Key")
|
||||||
|
return self._keys[self._current_index]
|
||||||
|
|
||||||
|
def switch_to_next_key(self) -> bool:
|
||||||
|
"""切换到下一个key
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
bool: 如果还有下一个key返回True,否则返回False
|
||||||
|
"""
|
||||||
|
with self._lock:
|
||||||
|
if len(self._keys) <= 1:
|
||||||
|
return False
|
||||||
|
|
||||||
|
self._current_index = (self._current_index + 1) % len(self._keys)
|
||||||
|
logger.info(f"切换到下一个Google API Key,当前索引: {self._current_index}")
|
||||||
|
return True
|
||||||
|
|
||||||
|
def reset_to_first_key(self):
|
||||||
|
"""重置到第一个key"""
|
||||||
|
with self._lock:
|
||||||
|
self._current_index = 0
|
||||||
|
logger.info("重置到第一个Google API Key")
|
||||||
|
|
||||||
|
def get_all_keys(self) -> List[str]:
|
||||||
|
"""获取所有key(用于测试)"""
|
||||||
|
return self._keys.copy()
|
||||||
|
|
||||||
|
def has_multiple_keys(self) -> bool:
|
||||||
|
"""是否有多个key"""
|
||||||
|
return len(self._keys) > 1
|
||||||
|
|
||||||
|
|
||||||
|
# 全局key池管理器实例
|
||||||
|
key_pool_manager = KeyPoolManager()
|
||||||
Loading…
x
Reference in New Issue
Block a user