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refactor:章节分析服务添加重试机制（最多3次，带指数退避等待）

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xiamuceer
2025-12-31 11:59:22 +08:00
parent aebdfe3d68
commit 30c044394f
1 changed files with 103 additions and 47 deletions
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backend/app/services/plot_analyzer.py
+103 -47
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@@ -6,6 +6,7 @@ from app.services.prompt_service import prompt_service, PromptService
from app.logger import get_logger
import json
import re
import asyncio
logger = get_logger(__name__)
@@ -30,10 +31,11 @@ class PlotAnalyzer:
content: str,
word_count: int,
user_id: str = None,
db: AsyncSession = None
db: AsyncSession = None,
max_retries: int = 3
) -> Optional[Dict[str, Any]]:
"""
分析单章内容
分析单章内容（带重试机制）
Args:
chapter_number: 章节号
@@ -42,62 +44,116 @@ class PlotAnalyzer:
word_count: 字数
user_id: 用户ID（用于获取自定义提示词）
db: 数据库会话（用于查询自定义提示词）
max_retries: 最大重试次数，默认3次
Returns:
分析结果字典,失败返回None
"""
logger.info(f"🔍 开始分析第{chapter_number}章: {title}")
# 如果内容过长,截取前8000字(避免超token)
analysis_content = content[:8000] if len(content) > 8000 else content
# 获取自定义提示词模板
try:
logger.info(f"🔍 开始分析第{chapter_number}章: {title}")
# 如果内容过长,截取前8000字(避免超token)
analysis_content = content[:8000] if len(content) > 8000 else content
# 获取自定义提示词模板
if user_id and db:
template = await PromptService.get_template("PLOT_ANALYSIS", user_id, db)
else:
# 降级到系统默认模板
template = PromptService.PLOT_ANALYSIS
# 格式化提示词
prompt = PromptService.format_prompt(
template,
chapter_number=chapter_number,
title=title,
word_count=word_count,
content=analysis_content
)
# 调用AI进行分析
# 注意：不指定max_tokens，使用用户在设置中配置的值
logger.info(f" 调用AI分析(内容长度: {len(analysis_content)}字)...")
accumulated_text = ""
async for chunk in self.ai_service.generate_text_stream(
prompt=prompt,
temperature=0.3 # 降低温度以获得更稳定的JSON输出
):
accumulated_text += chunk
# 提取内容
response_text = accumulated_text
# 解析JSON结果
analysis_result = self._parse_analysis_response(response_text)
if analysis_result:
logger.info(f"✅ 第{chapter_number}章分析完成")
logger.info(f" - 钩子: {len(analysis_result.get('hooks', []))}个")
logger.info(f" - 伏笔: {len(analysis_result.get('foreshadows', []))}个")
logger.info(f" - 情节点: {len(analysis_result.get('plot_points', []))}个")
logger.info(f" - 整体评分: {analysis_result.get('scores', {}).get('overall', 'N/A')}")
return analysis_result
else:
logger.error(f"❌ 第{chapter_number}章分析失败: JSON解析错误")
return None
except Exception as e:
logger.error(f"❌ 章节分析异常: {str(e)}")
return None
logger.warning(f"⚠️ 获取提示词模板失败，使用默认模板: {str(e)}")
template = PromptService.PLOT_ANALYSIS
# 格式化提示词
prompt = PromptService.format_prompt(
template,
chapter_number=chapter_number,
title=title,
word_count=word_count,
content=analysis_content
)
last_error = None
for attempt in range(1, max_retries + 1):
try:
# 调用AI进行分析
logger.info(f" 📡 调用AI分析(内容长度: {len(analysis_content)}字, 尝试 {attempt}/{max_retries})...")
accumulated_text = ""
try:
async for chunk in self.ai_service.generate_text_stream(
prompt=prompt,
temperature=0.3 # 降低温度以获得更稳定的JSON输出
):
accumulated_text += chunk
except GeneratorExit:
# 流式响应被中断
logger.warning(f"⚠️ 流式响应被中断(GeneratorExit)，已累积 {len(accumulated_text)} 字符")
# 如果已经累积了足够内容，继续尝试解析
if len(accumulated_text) < 100:
raise Exception("流式响应中断，内容不足")
except Exception as stream_error:
logger.error(f"❌ 流式生成出错: {str(stream_error)}")
raise
# 检查响应是否为空
if not accumulated_text or len(accumulated_text.strip()) < 10:
logger.warning(f"⚠️ AI响应为空或过短(长度: {len(accumulated_text)}), 尝试 {attempt}/{max_retries}")
last_error = "AI响应为空或过短"
if attempt < max_retries:
wait_time = min(2 ** attempt, 10)
logger.info(f" ⏳ 等待 {wait_time} 秒后重试...")
await asyncio.sleep(wait_time)
continue
else:
logger.error(f"❌ 第{chapter_number}章分析失败: AI响应为空，已达最大重试次数")
return None
# 提取内容
response_text = accumulated_text
logger.debug(f" 收到AI响应，长度: {len(response_text)} 字符")
# 解析JSON结果
analysis_result = self._parse_analysis_response(response_text)
if analysis_result:
logger.info(f"✅ 第{chapter_number}章分析完成 (尝试 {attempt}/{max_retries})")
logger.info(f" - 钩子: {len(analysis_result.get('hooks', []))}个")
logger.info(f" - 伏笔: {len(analysis_result.get('foreshadows', []))}个")
logger.info(f" - 情节点: {len(analysis_result.get('plot_points', []))}个")
logger.info(f" - 整体评分: {analysis_result.get('scores', {}).get('overall', 'N/A')}")
return analysis_result
else:
# JSON解析失败，重试
logger.warning(f"⚠️ JSON解析失败, 尝试 {attempt}/{max_retries}")
last_error = "JSON解析失败"
if attempt < max_retries:
wait_time = min(2 ** attempt, 10)
logger.info(f" ⏳ 等待 {wait_time} 秒后重试...")
await asyncio.sleep(wait_time)
continue
else:
logger.error(f"❌ 第{chapter_number}章分析失败: JSON解析错误，已达最大重试次数")
return None
except Exception as e:
last_error = str(e)
logger.error(f"❌ 章节分析异常(尝试 {attempt}/{max_retries}): {last_error}")
if attempt < max_retries:
wait_time = min(2 ** attempt, 10)
logger.info(f" ⏳ 等待 {wait_time} 秒后重试...")
await asyncio.sleep(wait_time)
continue
else:
logger.error(f"❌ 第{chapter_number}章分析失败: {last_error}，已达最大重试次数")
return None
# 不应该到达这里，但作为安全措施
logger.error(f"❌ 第{chapter_number}章分析失败: {last_error}")
return None
def _parse_analysis_response(self, response: str) -> Optional[Dict[str, Any]]:
"""