fix: MCP插件TimeoutError修复 + 多项Bug修复和性能优化

- fix: MCP插件管理接口改为后台任务，修复TimeoutError
- fix: MCP连接失败后上下文清理的cancel scope错误
- feat: MCP插件后台注册添加重试机制
- fix: 限制每章自动创建伏笔数量上限
- fix: 修复JSON非法转义字符清洗
- fix: SSE流式生成添加心跳保活
- fix: 职业生成改用POST请求避免URL长度限制
- perf: 使用torch CPU版本加速Docker构建
- fix: 自动修复JSON字符串值中的裸换行符
- feat: 集成json5容错解析器

backend/app/api/organizations.py

@@ -7,7 +7,7 @@ from pydantic import BaseModel, Field
 import json
 
 from app.database import get_db
-from app.utils.sse_response import SSEResponse, create_sse_response, WizardProgressTracker
+from app.utils.sse_response import SSEResponse, create_sse_response, WizardProgressTracker, wrap_stream_with_heartbeat, HEARTBEAT
 from app.models.relationship import Organization, OrganizationMember
 from app.models.character import Character
 from app.models.project import Project
@@ -24,6 +24,7 @@ from app.schemas.relationship import (
 )
 from app.schemas.character import CharacterResponse
 from app.services.ai_service import AIService
+from app.services.json_helper import loads_json
 from app.services.prompt_service import prompt_service, PromptService
 from app.logger import get_logger
 from app.api.settings import get_user_ai_service
@@ -500,7 +501,15 @@ async def generate_organization_stream(
                 chunk_count = 0
                 estimated_total = max(3000, len(prompt) * 8)
                 
-                async for chunk in user_ai_service.generate_text_stream(prompt=prompt):
+                async for chunk in wrap_stream_with_heartbeat(
+                    user_ai_service.generate_text_stream(prompt=prompt),
+                    heartbeat_interval=15.0
+                ):
+                    # 心跳哨兵：发送心跳保活，不混入AI响应
+                    if chunk is HEARTBEAT:
+                        yield await tracker.heartbeat()
+                        continue
+
                     chunk_count += 1
                     ai_content += chunk
                     
@@ -529,7 +538,7 @@ async def generate_organization_stream(
             # ✅ 使用统一的 JSON 清洗方法
             try:
                 cleaned_response = user_ai_service._clean_json_response(ai_content)
-                organization_data = json.loads(cleaned_response)
+                organization_data = loads_json(cleaned_response)
                 logger.info(f"✅ 组织JSON解析成功")
             except json.JSONDecodeError as e:
                 logger.error(f"❌ 组织JSON解析失败: {e}")