xiamuceer
fba6922a5c
- JSON解析器字符串状态追踪修复 - AI客户端流式响应异常处理 - 写作风格MultipleResultsFound错误 - 职业stages字段类型处理 - 章节分析任务状态同步 - 后台任务返回值修复
1756 lines
85 KiB
Python
1756 lines
85 KiB
Python
"""项目创建向导流式API - 使用SSE避免超时"""
|
||
from fastapi import APIRouter, Depends, HTTPException, Request
|
||
from sqlalchemy.ext.asyncio import AsyncSession
|
||
from sqlalchemy import select
|
||
from typing import Dict, Any, AsyncGenerator
|
||
import json
|
||
import re
|
||
|
||
from app.database import get_db
|
||
from app.models.project import Project
|
||
from app.models.character import Character
|
||
from app.models.outline import Outline
|
||
from app.models.chapter import Chapter
|
||
from app.models.career import Career, CharacterCareer
|
||
from app.models.relationship import CharacterRelationship, Organization, OrganizationMember, RelationshipType
|
||
from app.models.writing_style import WritingStyle
|
||
from app.models.project_default_style import ProjectDefaultStyle
|
||
from app.services.ai_service import AIService
|
||
from app.services.mcp_tool_service import MCPToolService
|
||
from app.services.prompt_service import prompt_service, PromptService
|
||
from app.services.plot_expansion_service import PlotExpansionService
|
||
from app.logger import get_logger
|
||
from app.utils.sse_response import SSEResponse, create_sse_response
|
||
from app.api.settings import get_user_ai_service
|
||
|
||
router = APIRouter(prefix="/wizard-stream", tags=["项目创建向导(流式)"])
|
||
logger = get_logger(__name__)
|
||
|
||
|
||
async def world_building_generator(
|
||
data: Dict[str, Any],
|
||
db: AsyncSession,
|
||
user_ai_service: AIService
|
||
) -> AsyncGenerator[str, None]:
|
||
"""世界构建流式生成器 - 支持MCP工具增强"""
|
||
# 标记数据库会话是否已提交
|
||
db_committed = False
|
||
try:
|
||
# 发送开始消息
|
||
yield await SSEResponse.send_progress("开始生成世界观...", 10)
|
||
|
||
# 提取参数
|
||
title = data.get("title")
|
||
description = data.get("description")
|
||
theme = data.get("theme")
|
||
genre = data.get("genre")
|
||
narrative_perspective = data.get("narrative_perspective")
|
||
target_words = data.get("target_words")
|
||
chapter_count = data.get("chapter_count")
|
||
character_count = data.get("character_count")
|
||
outline_mode = data.get("outline_mode", "one-to-many") # 大纲模式，默认一对多
|
||
provider = data.get("provider")
|
||
model = data.get("model")
|
||
enable_mcp = data.get("enable_mcp", True) # 默认启用MCP
|
||
user_id = data.get("user_id") # 从中间件注入
|
||
|
||
if not title or not description or not theme or not genre:
|
||
yield await SSEResponse.send_error("title、description、theme 和 genre 是必需的参数", 400)
|
||
return
|
||
|
||
# 获取基础提示词（支持自定义）
|
||
yield await SSEResponse.send_progress("准备AI提示词...", 15)
|
||
template = await PromptService.get_template("WORLD_BUILDING", user_id, db)
|
||
base_prompt = PromptService.format_prompt(
|
||
template,
|
||
title=title,
|
||
theme=theme,
|
||
genre=genre or "通用类型",
|
||
description=description or "暂无简介"
|
||
)
|
||
|
||
# MCP工具增强：收集参考资料
|
||
reference_materials = ""
|
||
if enable_mcp and user_id:
|
||
try:
|
||
# 先静默检查是否有可用工具
|
||
from app.services.mcp_tool_service import mcp_tool_service
|
||
available_tools = await mcp_tool_service.get_user_enabled_tools(
|
||
user_id=user_id,
|
||
db_session=db
|
||
)
|
||
|
||
# 只有在真正有可用工具时才显示消息和调用
|
||
if available_tools:
|
||
yield await SSEResponse.send_progress("🔍 尝试使用MCP工具收集参考资料...", 18)
|
||
|
||
mcp_template = await PromptService.get_template("MCP_WORLD_BUILDING_PLANNING", user_id, db)
|
||
planning_prompt = PromptService.format_prompt(
|
||
mcp_template,
|
||
title=title,
|
||
genre=genre,
|
||
theme=theme,
|
||
description=description
|
||
)
|
||
|
||
# 调用MCP增强的AI（非流式，最多1轮工具调用，避免超时）
|
||
planning_result = await user_ai_service.generate_text_with_mcp(
|
||
prompt=planning_prompt,
|
||
user_id=user_id,
|
||
db_session=db,
|
||
enable_mcp=True,
|
||
max_tool_rounds=2,
|
||
tool_choice="auto",
|
||
provider=None,
|
||
model=None
|
||
)
|
||
|
||
# 提取参考资料
|
||
if planning_result.get("tool_calls_made", 0) > 0:
|
||
yield await SSEResponse.send_progress(
|
||
f"✅ MCP工具调用成功（{planning_result['tool_calls_made']}次）",
|
||
25
|
||
)
|
||
reference_materials = planning_result.get("content", "")
|
||
else:
|
||
# 有工具但未使用
|
||
logger.debug("MCP工具可用但AI未选择使用")
|
||
else:
|
||
# 没有可用工具，静默跳过
|
||
logger.debug(f"用户 {user_id} 未启用MCP工具，跳过MCP增强")
|
||
|
||
except Exception as e:
|
||
logger.warning(f"MCP工具调用失败（降级处理）: {e}")
|
||
yield await SSEResponse.send_progress("⚠️ MCP工具暂时不可用，使用基础模式", 25)
|
||
|
||
# 构建增强提示词
|
||
if reference_materials:
|
||
enhanced_prompt = f"""{base_prompt}
|
||
|
||
【参考资料】
|
||
以下是通过MCP工具收集的真实背景资料，请参考这些信息构建更真实的世界观：
|
||
|
||
{reference_materials}
|
||
|
||
请结合上述资料，生成符合历史/现实的世界观设定。"""
|
||
final_prompt = enhanced_prompt
|
||
yield await SSEResponse.send_progress("💡 已整合参考资料，开始生成世界观...", 10)
|
||
else:
|
||
final_prompt = base_prompt
|
||
yield await SSEResponse.send_progress("正在调用AI生成...", 10)
|
||
|
||
# ===== 流式生成世界观（带重试机制） =====
|
||
MAX_WORLD_RETRIES = 3 # 最多重试3次
|
||
world_retry_count = 0
|
||
world_generation_success = False
|
||
world_data = {}
|
||
|
||
while world_retry_count < MAX_WORLD_RETRIES and not world_generation_success:
|
||
try:
|
||
retry_suffix = f" (重试{world_retry_count}/{MAX_WORLD_RETRIES})" if world_retry_count > 0 else ""
|
||
yield await SSEResponse.send_progress(f"生成世界观{retry_suffix}...", 10 + world_retry_count * 5)
|
||
|
||
# 流式生成世界观
|
||
accumulated_text = ""
|
||
chunk_count = 0
|
||
|
||
async for chunk in user_ai_service.generate_text_stream(
|
||
prompt=final_prompt,
|
||
provider=provider,
|
||
model=model
|
||
):
|
||
chunk_count += 1
|
||
accumulated_text += chunk
|
||
|
||
# 发送内容块
|
||
yield await SSEResponse.send_chunk(chunk)
|
||
|
||
# 世界观生成独立进度：5-95%
|
||
if chunk_count % 5 == 0:
|
||
progress = min(5 + (chunk_count // 3), 95)
|
||
yield await SSEResponse.send_progress(f"世界观生成中... ({len(accumulated_text)}字符)", progress)
|
||
|
||
# 每20个块发送心跳
|
||
if chunk_count % 20 == 0:
|
||
yield await SSEResponse.send_heartbeat()
|
||
|
||
# 检查是否返回空响应
|
||
if not accumulated_text or not accumulated_text.strip():
|
||
logger.warning(f"⚠️ AI返回空世界观（尝试{world_retry_count+1}/{MAX_WORLD_RETRIES}）")
|
||
world_retry_count += 1
|
||
if world_retry_count < MAX_WORLD_RETRIES:
|
||
yield await SSEResponse.send_progress(
|
||
f"⚠️ AI返回为空，准备重试...",
|
||
10 + world_retry_count * 5,
|
||
"warning"
|
||
)
|
||
continue
|
||
else:
|
||
# 达到最大重试次数，使用默认值
|
||
logger.error("❌ 世界观生成多次返回空响应")
|
||
world_data = {
|
||
"time_period": "AI多次返回为空，请稍后重试",
|
||
"location": "AI多次返回为空，请稍后重试",
|
||
"atmosphere": "AI多次返回为空，请稍后重试",
|
||
"rules": "AI多次返回为空，请稍后重试"
|
||
}
|
||
world_generation_success = True # 标记为成功以继续流程
|
||
break
|
||
|
||
# 解析结果 - 使用统一的JSON清洗方法
|
||
yield await SSEResponse.send_progress("解析世界观数据...", 96)
|
||
|
||
try:
|
||
logger.info(f"🔍 开始清洗JSON，原始长度: {len(accumulated_text)}")
|
||
logger.info(f" 原始内容预览: {accumulated_text[:300]}...")
|
||
|
||
# ✅ 使用 AIService 的统一清洗方法
|
||
cleaned_text = user_ai_service._clean_json_response(accumulated_text)
|
||
logger.info(f"✅ JSON清洗完成，清洗后长度: {len(cleaned_text)}")
|
||
logger.info(f" 清洗后预览: {cleaned_text[:300]}...")
|
||
|
||
world_data = json.loads(cleaned_text)
|
||
logger.info(f"✅ 世界观JSON解析成功（尝试{world_retry_count+1}/{MAX_WORLD_RETRIES}）")
|
||
world_generation_success = True # 解析成功，标记完成
|
||
|
||
except json.JSONDecodeError as e:
|
||
logger.error(f"❌ 世界构建JSON解析失败（尝试{world_retry_count+1}/{MAX_WORLD_RETRIES}）: {e}")
|
||
logger.error(f" 原始内容长度: {len(accumulated_text)}")
|
||
logger.error(f" 原始内容预览: {accumulated_text[:200]}")
|
||
world_retry_count += 1
|
||
if world_retry_count < MAX_WORLD_RETRIES:
|
||
yield await SSEResponse.send_progress(
|
||
f"⚠️ JSON解析失败，准备重试...",
|
||
10 + world_retry_count * 5,
|
||
"warning"
|
||
)
|
||
continue
|
||
else:
|
||
# 达到最大重试次数，使用默认值
|
||
world_data = {
|
||
"time_period": "AI返回格式错误，请重试",
|
||
"location": "AI返回格式错误，请重试",
|
||
"atmosphere": "AI返回格式错误，请重试",
|
||
"rules": "AI返回格式错误，请重试"
|
||
}
|
||
world_generation_success = True # 标记为成功以继续流程
|
||
|
||
except Exception as e:
|
||
logger.error(f"❌ 世界构建生成异常（尝试{world_retry_count+1}/{MAX_WORLD_RETRIES}）: {type(e).__name__}: {e}")
|
||
world_retry_count += 1
|
||
if world_retry_count < MAX_WORLD_RETRIES:
|
||
yield await SSEResponse.send_progress(
|
||
f"⚠️ 生成异常，准备重试...",
|
||
10 + world_retry_count * 5,
|
||
"warning"
|
||
)
|
||
continue
|
||
else:
|
||
# 最后一次重试仍失败，抛出异常
|
||
logger.error(f" accumulated_text 长度: {len(accumulated_text) if 'accumulated_text' in locals() else 'N/A'}")
|
||
raise
|
||
# 保存到数据库
|
||
yield await SSEResponse.send_progress("保存世界观到数据库...", 99)
|
||
|
||
# 确保user_id存在
|
||
if not user_id:
|
||
yield await SSEResponse.send_error("用户ID缺失，无法创建项目", 401)
|
||
return
|
||
|
||
project = Project(
|
||
user_id=user_id, # 添加user_id字段
|
||
title=title,
|
||
description=description,
|
||
theme=theme,
|
||
genre=genre,
|
||
world_time_period=world_data.get("time_period"),
|
||
world_location=world_data.get("location"),
|
||
world_atmosphere=world_data.get("atmosphere"),
|
||
world_rules=world_data.get("rules"),
|
||
narrative_perspective=narrative_perspective,
|
||
target_words=target_words,
|
||
chapter_count=chapter_count,
|
||
character_count=character_count,
|
||
outline_mode=outline_mode, # 设置大纲模式
|
||
wizard_status="incomplete",
|
||
wizard_step=1,
|
||
status="planning"
|
||
)
|
||
db.add(project)
|
||
await db.commit()
|
||
await db.refresh(project)
|
||
|
||
# 自动设置默认写作风格为第一个全局预设风格
|
||
try:
|
||
result = await db.execute(
|
||
select(WritingStyle).where(
|
||
WritingStyle.user_id.is_(None),
|
||
WritingStyle.order_index == 1
|
||
).limit(1)
|
||
)
|
||
first_style = result.scalar_one_or_none()
|
||
|
||
if first_style:
|
||
default_style = ProjectDefaultStyle(
|
||
project_id=project.id,
|
||
style_id=first_style.id
|
||
)
|
||
db.add(default_style)
|
||
await db.commit()
|
||
logger.info(f"为项目 {project.id} 自动设置默认风格: {first_style.name}")
|
||
else:
|
||
logger.warning(f"未找到order_index=1的全局预设风格，项目 {project.id} 未设置默认风格")
|
||
except Exception as e:
|
||
logger.warning(f"设置默认写作风格失败: {e}，不影响项目创建")
|
||
|
||
# 更新向导步骤状态为1（世界观已完成）
|
||
project.wizard_step = 1
|
||
await db.commit()
|
||
|
||
# ===== 自动生成职业体系（带重试机制+流式） =====
|
||
yield await SSEResponse.send_progress("世界观完成！", 100, "success")
|
||
yield await SSEResponse.send_progress("🎯 开始生成职业体系框架...", 5)
|
||
logger.info(f"🎯 世界观已完成，开始为项目 {project.id} 自动生成职业体系")
|
||
|
||
MAX_CAREER_RETRIES = 3 # 最多重试3次
|
||
career_retry_count = 0
|
||
career_generation_success = False
|
||
|
||
while career_retry_count < MAX_CAREER_RETRIES and not career_generation_success:
|
||
try:
|
||
retry_suffix = f" (重试{career_retry_count}/{MAX_CAREER_RETRIES})" if career_retry_count > 0 else ""
|
||
yield await SSEResponse.send_progress(f"正在生成职业体系{retry_suffix}...", 10)
|
||
|
||
# 获取职业生成提示词模板（支持用户自定义）
|
||
template = await PromptService.get_template("CAREER_SYSTEM_GENERATION", user_id, db)
|
||
career_prompt = PromptService.format_prompt(
|
||
template,
|
||
title=project.title,
|
||
genre=genre or '未设定',
|
||
theme=theme or '未设定',
|
||
time_period=world_data.get('time_period', '未设定'),
|
||
location=world_data.get('location', '未设定'),
|
||
atmosphere=world_data.get('atmosphere', '未设定'),
|
||
rules=world_data.get('rules', '未设定')
|
||
)
|
||
|
||
# ✅ 使用流式生成职业体系
|
||
career_response = ""
|
||
chunk_count = 0
|
||
|
||
async for chunk in user_ai_service.generate_text_stream(
|
||
prompt=career_prompt,
|
||
provider=provider,
|
||
model=model
|
||
):
|
||
chunk_count += 1
|
||
career_response += chunk
|
||
|
||
# 发送内容块
|
||
yield await SSEResponse.send_chunk(chunk)
|
||
|
||
# 职业体系生成独立进度：10-95%
|
||
if chunk_count % 5 == 0:
|
||
progress = min(10 + (chunk_count // 3), 95)
|
||
yield await SSEResponse.send_progress(
|
||
f"生成职业体系中... ({len(career_response)}字符)",
|
||
progress
|
||
)
|
||
|
||
# 每20个块发送心跳
|
||
if chunk_count % 20 == 0:
|
||
yield await SSEResponse.send_heartbeat()
|
||
|
||
if not career_response or not career_response.strip():
|
||
logger.warning(f"⚠️ AI返回空职业体系（尝试{career_retry_count+1}/{MAX_CAREER_RETRIES}）")
|
||
career_retry_count += 1
|
||
if career_retry_count < MAX_CAREER_RETRIES:
|
||
yield await SSEResponse.send_progress(
|
||
f"⚠️ AI返回为空，准备重试...",
|
||
10,
|
||
"warning"
|
||
)
|
||
continue
|
||
else:
|
||
yield await SSEResponse.send_progress("职业体系生成跳过（AI多次返回为空）", 99)
|
||
break
|
||
|
||
yield await SSEResponse.send_progress("解析职业体系数据...", 96)
|
||
|
||
# 清洗并解析JSON
|
||
try:
|
||
cleaned_response = user_ai_service._clean_json_response(career_response)
|
||
career_data = json.loads(cleaned_response)
|
||
logger.info(f"✅ 职业体系JSON解析成功（尝试{career_retry_count+1}/{MAX_CAREER_RETRIES}）")
|
||
|
||
# 保存主职业
|
||
main_careers_created = []
|
||
for idx, career_info in enumerate(career_data.get("main_careers", [])):
|
||
try:
|
||
stages_json = json.dumps(career_info.get("stages", []), ensure_ascii=False)
|
||
attribute_bonuses = career_info.get("attribute_bonuses")
|
||
attribute_bonuses_json = json.dumps(attribute_bonuses, ensure_ascii=False) if attribute_bonuses else None
|
||
|
||
career = Career(
|
||
project_id=project.id,
|
||
name=career_info.get("name", f"未命名主职业{idx+1}"),
|
||
type="main",
|
||
description=career_info.get("description"),
|
||
category=career_info.get("category"),
|
||
stages=stages_json,
|
||
max_stage=career_info.get("max_stage", 10),
|
||
requirements=career_info.get("requirements"),
|
||
special_abilities=career_info.get("special_abilities"),
|
||
worldview_rules=career_info.get("worldview_rules"),
|
||
attribute_bonuses=attribute_bonuses_json,
|
||
source="ai"
|
||
)
|
||
db.add(career)
|
||
await db.flush()
|
||
main_careers_created.append(career.name)
|
||
logger.info(f" ✅ 创建主职业：{career.name}")
|
||
except Exception as e:
|
||
logger.error(f" ❌ 创建主职业失败：{str(e)}")
|
||
continue
|
||
|
||
# 保存副职业
|
||
sub_careers_created = []
|
||
for idx, career_info in enumerate(career_data.get("sub_careers", [])):
|
||
try:
|
||
stages_json = json.dumps(career_info.get("stages", []), ensure_ascii=False)
|
||
attribute_bonuses = career_info.get("attribute_bonuses")
|
||
attribute_bonuses_json = json.dumps(attribute_bonuses, ensure_ascii=False) if attribute_bonuses else None
|
||
|
||
career = Career(
|
||
project_id=project.id,
|
||
name=career_info.get("name", f"未命名副职业{idx+1}"),
|
||
type="sub",
|
||
description=career_info.get("description"),
|
||
category=career_info.get("category"),
|
||
stages=stages_json,
|
||
max_stage=career_info.get("max_stage", 5),
|
||
requirements=career_info.get("requirements"),
|
||
special_abilities=career_info.get("special_abilities"),
|
||
worldview_rules=career_info.get("worldview_rules"),
|
||
attribute_bonuses=attribute_bonuses_json,
|
||
source="ai"
|
||
)
|
||
db.add(career)
|
||
await db.flush()
|
||
sub_careers_created.append(career.name)
|
||
logger.info(f" ✅ 创建副职业：{career.name}")
|
||
except Exception as e:
|
||
logger.error(f" ❌ 创建副职业失败：{str(e)}")
|
||
continue
|
||
|
||
await db.commit()
|
||
|
||
# 标记成功
|
||
career_generation_success = True
|
||
logger.info(f"🎉 职业体系生成完成：主职业{len(main_careers_created)}个，副职业{len(sub_careers_created)}个")
|
||
yield await SSEResponse.send_progress(
|
||
f"✅ 职业体系生成完成（主{len(main_careers_created)}+副{len(sub_careers_created)}）",
|
||
99
|
||
)
|
||
|
||
except json.JSONDecodeError as e:
|
||
logger.error(f"❌ 职业体系JSON解析失败（尝试{career_retry_count+1}/{MAX_CAREER_RETRIES}）: {e}")
|
||
career_retry_count += 1
|
||
if career_retry_count < MAX_CAREER_RETRIES:
|
||
yield await SSEResponse.send_progress(
|
||
f"⚠️ JSON解析失败，准备重试...",
|
||
10,
|
||
"warning"
|
||
)
|
||
continue
|
||
else:
|
||
yield await SSEResponse.send_progress("⚠️ 职业体系解析失败（已达最大重试次数），已跳过", 99)
|
||
except Exception as e:
|
||
logger.error(f"❌ 职业体系保存失败（尝试{career_retry_count+1}/{MAX_CAREER_RETRIES}）: {e}")
|
||
career_retry_count += 1
|
||
if career_retry_count < MAX_CAREER_RETRIES:
|
||
yield await SSEResponse.send_progress(
|
||
f"⚠️ 保存失败，准备重试...",
|
||
10,
|
||
"warning"
|
||
)
|
||
continue
|
||
else:
|
||
yield await SSEResponse.send_progress("⚠️ 职业体系保存失败（已达最大重试次数），已跳过", 99)
|
||
|
||
except Exception as e:
|
||
logger.error(f"❌ 职业体系生成异常（尝试{career_retry_count+1}/{MAX_CAREER_RETRIES}）: {e}")
|
||
career_retry_count += 1
|
||
if career_retry_count < MAX_CAREER_RETRIES:
|
||
yield await SSEResponse.send_progress(
|
||
f"⚠️ 生成异常，准备重试...",
|
||
10,
|
||
"warning"
|
||
)
|
||
continue
|
||
else:
|
||
yield await SSEResponse.send_progress("⚠️ 职业体系生成失败（已达最大重试次数），已跳过（不影响项目创建）", 99)
|
||
|
||
db_committed = True
|
||
|
||
# 发送最终结果
|
||
yield await SSEResponse.send_result({
|
||
"project_id": project.id,
|
||
"time_period": world_data.get("time_period"),
|
||
"location": world_data.get("location"),
|
||
"atmosphere": world_data.get("atmosphere"),
|
||
"rules": world_data.get("rules")
|
||
})
|
||
|
||
yield await SSEResponse.send_progress("职业体系完成！", 100, "success")
|
||
yield await SSEResponse.send_progress("🎉 所有步骤已完成！", 100, "success")
|
||
yield await SSEResponse.send_done()
|
||
|
||
except GeneratorExit:
|
||
# SSE连接断开，回滚未提交的事务
|
||
logger.warning("世界构建生成器被提前关闭")
|
||
if not db_committed and db.in_transaction():
|
||
await db.rollback()
|
||
logger.info("世界构建事务已回滚（GeneratorExit）")
|
||
except Exception as e:
|
||
logger.error(f"世界构建流式生成失败: {str(e)}")
|
||
# 异常时回滚事务
|
||
if not db_committed and db.in_transaction():
|
||
await db.rollback()
|
||
logger.info("世界构建事务已回滚（异常）")
|
||
yield await SSEResponse.send_error(f"生成失败: {str(e)}")
|
||
|
||
|
||
@router.post("/world-building", summary="流式生成世界构建")
|
||
async def generate_world_building_stream(
|
||
request: Request,
|
||
data: Dict[str, Any],
|
||
db: AsyncSession = Depends(get_db),
|
||
user_ai_service: AIService = Depends(get_user_ai_service)
|
||
):
|
||
"""
|
||
使用SSE流式生成世界构建，避免超时
|
||
前端使用EventSource接收实时进度和结果
|
||
"""
|
||
# 从中间件注入user_id到data中
|
||
if hasattr(request.state, 'user_id'):
|
||
data['user_id'] = request.state.user_id
|
||
|
||
return create_sse_response(world_building_generator(data, db, user_ai_service))
|
||
|
||
|
||
async def characters_generator(
|
||
data: Dict[str, Any],
|
||
db: AsyncSession,
|
||
user_ai_service: AIService
|
||
) -> AsyncGenerator[str, None]:
|
||
"""角色批量生成流式生成器 - 优化版:分批+重试+MCP工具增强"""
|
||
db_committed = False
|
||
try:
|
||
yield await SSEResponse.send_progress("开始生成角色...", 5)
|
||
|
||
project_id = data.get("project_id")
|
||
count = data.get("count", 5)
|
||
world_context = data.get("world_context")
|
||
theme = data.get("theme", "")
|
||
genre = data.get("genre", "")
|
||
requirements = data.get("requirements", "")
|
||
provider = data.get("provider")
|
||
model = data.get("model")
|
||
enable_mcp = data.get("enable_mcp", True) # 默认启用MCP
|
||
user_id = data.get("user_id") # 从中间件注入
|
||
|
||
# 验证项目
|
||
yield await SSEResponse.send_progress("验证项目...", 10)
|
||
result = await db.execute(
|
||
select(Project).where(Project.id == project_id)
|
||
)
|
||
project = result.scalar_one_or_none()
|
||
if not project:
|
||
yield await SSEResponse.send_error("项目不存在", 404)
|
||
return
|
||
|
||
project.wizard_step = 2
|
||
|
||
world_context = world_context or {
|
||
"time_period": project.world_time_period or "未设定",
|
||
"location": project.world_location or "未设定",
|
||
"atmosphere": project.world_atmosphere or "未设定",
|
||
"rules": project.world_rules or "未设定"
|
||
}
|
||
|
||
# MCP工具增强：收集角色参考资料
|
||
character_reference_materials = ""
|
||
if enable_mcp and user_id:
|
||
try:
|
||
# 先静默检查是否有可用工具
|
||
from app.services.mcp_tool_service import mcp_tool_service
|
||
available_tools = await mcp_tool_service.get_user_enabled_tools(
|
||
user_id=user_id,
|
||
db_session=db
|
||
)
|
||
|
||
# 只有在真正有可用工具时才显示消息和调用
|
||
if available_tools:
|
||
yield await SSEResponse.send_progress("🔍 尝试使用MCP工具收集角色参考资料...", 8)
|
||
|
||
mcp_template = await PromptService.get_template("MCP_CHARACTER_PLANNING", user_id, db)
|
||
planning_prompt = PromptService.format_prompt(
|
||
mcp_template,
|
||
title=project.title,
|
||
genre=genre or project.genre,
|
||
theme=theme or project.theme,
|
||
time_period=world_context.get('time_period', '未设定'),
|
||
location=world_context.get('location', '未设定')
|
||
)
|
||
|
||
# 调用MCP增强的AI（非流式，最多1轮工具调用，避免超时）
|
||
planning_result = await user_ai_service.generate_text_with_mcp(
|
||
prompt=planning_prompt,
|
||
user_id=user_id,
|
||
db_session=db,
|
||
enable_mcp=True,
|
||
max_tool_rounds=2, # ✅ 优化: 从2轮减少到1轮
|
||
tool_choice="auto",
|
||
provider=None,
|
||
model=None
|
||
)
|
||
|
||
# 提取参考资料
|
||
if planning_result.get("tool_calls_made", 0) > 0:
|
||
yield await SSEResponse.send_progress(
|
||
f"✅ MCP工具调用成功（{planning_result['tool_calls_made']}次）",
|
||
12
|
||
)
|
||
character_reference_materials = planning_result.get("content", "")
|
||
else:
|
||
# 有工具但未使用
|
||
logger.debug("MCP工具可用但AI未选择使用")
|
||
else:
|
||
# 没有可用工具，静默跳过
|
||
logger.debug(f"用户 {user_id} 未启用MCP工具，跳过MCP增强")
|
||
|
||
except Exception as e:
|
||
logger.warning(f"MCP工具调用失败（降级处理）: {e}")
|
||
yield await SSEResponse.send_progress("⚠️ MCP工具暂时不可用，使用基础模式", 12)
|
||
|
||
# 获取项目的职业列表，用于角色职业分配
|
||
yield await SSEResponse.send_progress("加载职业体系...", 13)
|
||
career_result = await db.execute(
|
||
select(Career).where(Career.project_id == project_id).order_by(Career.type, Career.id)
|
||
)
|
||
careers = career_result.scalars().all()
|
||
|
||
main_careers = [c for c in careers if c.type == "main"]
|
||
sub_careers = [c for c in careers if c.type == "sub"]
|
||
|
||
# 构建职业上下文
|
||
careers_context = ""
|
||
if main_careers or sub_careers:
|
||
careers_context = "\n\n【职业体系】\n"
|
||
if main_careers:
|
||
careers_context += "主职业：\n"
|
||
for career in main_careers:
|
||
careers_context += f"- {career.name}: {career.description or '暂无描述'}\n"
|
||
if sub_careers:
|
||
careers_context += "\n副职业：\n"
|
||
for career in sub_careers:
|
||
careers_context += f"- {career.name}: {career.description or '暂无描述'}\n"
|
||
|
||
careers_context += "\n请为每个角色分配职业：\n"
|
||
careers_context += "- 每个角色必须有1个主职业（从上述主职业中选择）\n"
|
||
careers_context += "- 每个角色可以有0-2个副职业（从上述副职业中选择，可选）\n"
|
||
careers_context += "- 主职业初始阶段建议为1-3\n"
|
||
careers_context += "- 副职业初始阶段建议为1-2\n"
|
||
careers_context += "- 请在返回的JSON中包含 career_assignment 字段：\n"
|
||
careers_context += ' {"main_career": "职业名称", "main_stage": 2, "sub_careers": [{"career": "副职业名称", "stage": 1}]}\n'
|
||
logger.info(f"✅ 加载了{len(main_careers)}个主职业和{len(sub_careers)}个副职业")
|
||
else:
|
||
logger.warning("⚠️ 项目没有职业体系，跳过职业分配")
|
||
|
||
# 优化的分批策略:每批生成3个,平衡效率和成功率
|
||
BATCH_SIZE = 3 # 每批生成3个角色
|
||
MAX_RETRIES = 3 # 每批最多重试3次
|
||
all_characters = []
|
||
total_batches = (count + BATCH_SIZE - 1) // BATCH_SIZE
|
||
|
||
for batch_idx in range(total_batches):
|
||
# 精确计算当前批次应该生成的数量
|
||
remaining = count - len(all_characters)
|
||
current_batch_size = min(BATCH_SIZE, remaining)
|
||
|
||
# 如果已经达到目标数量,直接退出
|
||
if current_batch_size <= 0:
|
||
logger.info(f"已生成{len(all_characters)}个角色,达到目标数量{count}")
|
||
break
|
||
|
||
batch_progress = 15 + (batch_idx * 60 // total_batches)
|
||
|
||
# 重试逻辑
|
||
retry_count = 0
|
||
batch_success = False
|
||
batch_error_message = ""
|
||
|
||
while retry_count < MAX_RETRIES and not batch_success:
|
||
try:
|
||
retry_suffix = f" (重试{retry_count}/{MAX_RETRIES})" if retry_count > 0 else ""
|
||
yield await SSEResponse.send_progress(
|
||
f"生成第{batch_idx+1}/{total_batches}批角色 ({current_batch_size}个){retry_suffix}...",
|
||
batch_progress
|
||
)
|
||
|
||
# 构建批次要求 - 包含已生成角色信息保持连贯
|
||
existing_chars_context = ""
|
||
if all_characters:
|
||
existing_chars_context = "\n\n【已生成的角色】:\n"
|
||
for char in all_characters:
|
||
existing_chars_context += f"- {char.get('name')}: {char.get('role_type', '未知')}, {char.get('personality', '暂无')[:50]}...\n"
|
||
existing_chars_context += "\n请确保新角色与已有角色形成合理的关系网络和互动。\n"
|
||
|
||
# 构建精确的批次要求,明确告诉AI要生成的数量
|
||
if batch_idx == 0:
|
||
if current_batch_size == 1:
|
||
batch_requirements = f"{requirements}\n请生成1个主角(protagonist)"
|
||
else:
|
||
batch_requirements = f"{requirements}\n请精确生成{current_batch_size}个角色:1个主角(protagonist)和{current_batch_size-1}个核心配角(supporting)"
|
||
else:
|
||
batch_requirements = f"{requirements}\n请精确生成{current_batch_size}个角色{existing_chars_context}"
|
||
if batch_idx == total_batches - 1:
|
||
batch_requirements += "\n可以包含组织或反派(antagonist)"
|
||
else:
|
||
batch_requirements += "\n主要是配角(supporting)和反派(antagonist)"
|
||
|
||
# 获取自定义提示词模板
|
||
template = await PromptService.get_template("CHARACTERS_BATCH_GENERATION", user_id, db)
|
||
# 构建基础提示词
|
||
base_prompt = PromptService.format_prompt(
|
||
template,
|
||
count=current_batch_size, # 传递精确数量
|
||
time_period=world_context.get("time_period", ""),
|
||
location=world_context.get("location", ""),
|
||
atmosphere=world_context.get("atmosphere", ""),
|
||
rules=world_context.get("rules", ""),
|
||
theme=theme or project.theme or "",
|
||
genre=genre or project.genre or "",
|
||
requirements=batch_requirements + careers_context # 添加职业上下文
|
||
)
|
||
|
||
# 如果有MCP参考资料，增强提示词
|
||
if character_reference_materials:
|
||
prompt = f"""{base_prompt}
|
||
|
||
【参考资料】
|
||
以下是通过MCP工具收集的真实背景资料，请参考这些信息设计更真实的角色：
|
||
|
||
{character_reference_materials}
|
||
|
||
请结合上述资料，设计符合历史/文化背景的角色。"""
|
||
else:
|
||
prompt = base_prompt
|
||
|
||
# 流式生成（带字数统计）
|
||
accumulated_text = ""
|
||
chunk_count = 0
|
||
|
||
async for chunk in user_ai_service.generate_text_stream(
|
||
prompt=prompt,
|
||
provider=provider,
|
||
model=model
|
||
):
|
||
chunk_count += 1
|
||
accumulated_text += chunk
|
||
|
||
# 发送内容块
|
||
yield await SSEResponse.send_chunk(chunk)
|
||
|
||
# 定期更新进度和字数
|
||
if chunk_count % 5 == 0:
|
||
progress = min(batch_progress + 5 + (chunk_count // 10), batch_progress + 15)
|
||
yield await SSEResponse.send_progress(
|
||
f"生成角色中... ({len(accumulated_text)}字符)",
|
||
progress
|
||
)
|
||
|
||
# 每20个块发送心跳
|
||
if chunk_count % 20 == 0:
|
||
yield await SSEResponse.send_heartbeat()
|
||
|
||
# 解析批次结果 - 使用统一的JSON清洗方法
|
||
cleaned_text = user_ai_service._clean_json_response(accumulated_text)
|
||
characters_data = json.loads(cleaned_text)
|
||
if not isinstance(characters_data, list):
|
||
characters_data = [characters_data]
|
||
|
||
# 严格验证生成数量是否精确匹配
|
||
if len(characters_data) != current_batch_size:
|
||
error_msg = f"批次{batch_idx+1}生成数量不正确: 期望{current_batch_size}个, 实际{len(characters_data)}个"
|
||
logger.error(error_msg)
|
||
|
||
# 如果还有重试机会，继续重试
|
||
if retry_count < MAX_RETRIES - 1:
|
||
retry_count += 1
|
||
yield await SSEResponse.send_progress(
|
||
f"⚠️ {error_msg}，准备重试...",
|
||
batch_progress,
|
||
"warning"
|
||
)
|
||
continue
|
||
else:
|
||
# 最后一次重试仍失败，直接返回错误
|
||
yield await SSEResponse.send_error(error_msg)
|
||
return
|
||
|
||
all_characters.extend(characters_data)
|
||
batch_success = True
|
||
logger.info(f"批次{batch_idx+1}成功添加{len(characters_data)}个角色,当前总数{len(all_characters)}/{count}")
|
||
|
||
except json.JSONDecodeError as e:
|
||
logger.error(f"批次{batch_idx+1}解析失败(尝试{retry_count+1}/{MAX_RETRIES}): {e}")
|
||
batch_error_message = f"JSON解析失败: {str(e)}"
|
||
retry_count += 1
|
||
if retry_count < MAX_RETRIES:
|
||
yield await SSEResponse.send_progress(
|
||
f"解析失败，准备重试...",
|
||
batch_progress,
|
||
"warning"
|
||
)
|
||
except Exception as e:
|
||
logger.error(f"批次{batch_idx+1}生成异常(尝试{retry_count+1}/{MAX_RETRIES}): {e}")
|
||
batch_error_message = f"生成异常: {str(e)}"
|
||
retry_count += 1
|
||
if retry_count < MAX_RETRIES:
|
||
yield await SSEResponse.send_progress(
|
||
f"生成异常，准备重试...",
|
||
batch_progress,
|
||
"warning"
|
||
)
|
||
|
||
# 检查批次是否成功
|
||
if not batch_success:
|
||
error_msg = f"批次{batch_idx+1}在{MAX_RETRIES}次重试后仍然失败"
|
||
if batch_error_message:
|
||
error_msg += f": {batch_error_message}"
|
||
logger.error(error_msg)
|
||
yield await SSEResponse.send_error(error_msg)
|
||
return
|
||
|
||
# 保存到数据库 - 分阶段处理以保证一致性
|
||
yield await SSEResponse.send_progress("验证角色数据...", 82)
|
||
|
||
# 预处理：构建本批次所有实体的名称集合
|
||
valid_entity_names = set()
|
||
valid_organization_names = set()
|
||
|
||
for char_data in all_characters:
|
||
entity_name = char_data.get("name", "")
|
||
if entity_name:
|
||
valid_entity_names.add(entity_name)
|
||
if char_data.get("is_organization", False):
|
||
valid_organization_names.add(entity_name)
|
||
|
||
# 清理幻觉引用
|
||
cleaned_count = 0
|
||
for char_data in all_characters:
|
||
# 清理关系数组中的无效引用
|
||
if "relationships_array" in char_data and isinstance(char_data["relationships_array"], list):
|
||
original_rels = char_data["relationships_array"]
|
||
valid_rels = []
|
||
for rel in original_rels:
|
||
target_name = rel.get("target_character_name", "")
|
||
if target_name in valid_entity_names:
|
||
valid_rels.append(rel)
|
||
else:
|
||
cleaned_count += 1
|
||
logger.debug(f" 🧹 清理无效关系引用：{char_data.get('name')} -> {target_name}")
|
||
char_data["relationships_array"] = valid_rels
|
||
|
||
# 清理组织成员关系中的无效引用
|
||
if "organization_memberships" in char_data and isinstance(char_data["organization_memberships"], list):
|
||
original_orgs = char_data["organization_memberships"]
|
||
valid_orgs = []
|
||
for org_mem in original_orgs:
|
||
org_name = org_mem.get("organization_name", "")
|
||
if org_name in valid_organization_names:
|
||
valid_orgs.append(org_mem)
|
||
else:
|
||
cleaned_count += 1
|
||
logger.debug(f" 🧹 清理无效组织引用：{char_data.get('name')} -> {org_name}")
|
||
char_data["organization_memberships"] = valid_orgs
|
||
|
||
if cleaned_count > 0:
|
||
logger.info(f"✨ 清理了{cleaned_count}个AI幻觉引用")
|
||
yield await SSEResponse.send_progress(f"已清理{cleaned_count}个无效引用", 84)
|
||
|
||
yield await SSEResponse.send_progress("保存角色到数据库...", 85)
|
||
|
||
# 第一阶段：创建所有Character记录
|
||
created_characters = []
|
||
character_name_to_obj = {} # 名称到对象的映射，用于后续关系创建
|
||
|
||
for char_data in all_characters:
|
||
# 从relationships_array提取文本描述以保持向后兼容
|
||
relationships_text = ""
|
||
relationships_array = char_data.get("relationships_array", [])
|
||
if relationships_array and isinstance(relationships_array, list):
|
||
# 将关系数组转换为可读文本
|
||
rel_descriptions = []
|
||
for rel in relationships_array:
|
||
target = rel.get("target_character_name", "未知")
|
||
rel_type = rel.get("relationship_type", "关系")
|
||
desc = rel.get("description", "")
|
||
rel_descriptions.append(f"{target}({rel_type}): {desc}")
|
||
relationships_text = "; ".join(rel_descriptions)
|
||
# 兼容旧格式
|
||
elif isinstance(char_data.get("relationships"), dict):
|
||
relationships_text = json.dumps(char_data.get("relationships"), ensure_ascii=False)
|
||
elif isinstance(char_data.get("relationships"), str):
|
||
relationships_text = char_data.get("relationships")
|
||
|
||
# 判断是否为组织
|
||
is_organization = char_data.get("is_organization", False)
|
||
|
||
character = Character(
|
||
project_id=project_id,
|
||
name=char_data.get("name", "未命名角色"),
|
||
age=str(char_data.get("age", "")) if not is_organization else None,
|
||
gender=char_data.get("gender") if not is_organization else None,
|
||
is_organization=is_organization,
|
||
role_type=char_data.get("role_type", "supporting"),
|
||
personality=char_data.get("personality", ""),
|
||
background=char_data.get("background", ""),
|
||
appearance=char_data.get("appearance", ""),
|
||
relationships=relationships_text,
|
||
organization_type=char_data.get("organization_type") if is_organization else None,
|
||
organization_purpose=char_data.get("organization_purpose") if is_organization else None,
|
||
organization_members=json.dumps(char_data.get("organization_members", []), ensure_ascii=False) if is_organization else None,
|
||
traits=json.dumps(char_data.get("traits", []), ensure_ascii=False) if char_data.get("traits") else None
|
||
)
|
||
db.add(character)
|
||
created_characters.append((character, char_data))
|
||
|
||
await db.flush() # 获取所有角色的ID
|
||
|
||
# 第二阶段：为角色分配职业并创建CharacterCareer关联
|
||
if main_careers or sub_careers:
|
||
yield await SSEResponse.send_progress("分配角色职业...", 86)
|
||
careers_assigned = 0
|
||
|
||
# 构建职业名称到对象的映射
|
||
career_name_to_obj = {c.name: c for c in careers}
|
||
|
||
for character, char_data in created_characters:
|
||
# 跳过组织
|
||
if character.is_organization:
|
||
continue
|
||
|
||
try:
|
||
career_assignment = char_data.get("career_assignment", {})
|
||
|
||
# 分配主职业
|
||
main_career_name = career_assignment.get("main_career")
|
||
main_career_stage = career_assignment.get("main_stage", 1)
|
||
|
||
if main_career_name and main_career_name in career_name_to_obj:
|
||
main_career = career_name_to_obj[main_career_name]
|
||
|
||
# 创建CharacterCareer关联
|
||
char_career = CharacterCareer(
|
||
character_id=character.id,
|
||
career_id=main_career.id,
|
||
career_type="main",
|
||
current_stage=min(main_career_stage, main_career.max_stage),
|
||
stage_progress=0
|
||
)
|
||
db.add(char_career)
|
||
|
||
# 更新Character冗余字段
|
||
character.main_career_id = main_career.id
|
||
character.main_career_stage = char_career.current_stage
|
||
|
||
careers_assigned += 1
|
||
logger.info(f" ✅ 分配主职业：{character.name} -> {main_career.name} (阶段{char_career.current_stage})")
|
||
else:
|
||
if main_career_name:
|
||
logger.warning(f" ⚠️ 主职业不存在：{character.name} -> {main_career_name}")
|
||
|
||
# 分配副职业
|
||
sub_career_assignments = career_assignment.get("sub_careers", [])
|
||
sub_career_list = []
|
||
|
||
for sub_assign in sub_career_assignments[:2]: # 最多2个副职业
|
||
sub_career_name = sub_assign.get("career")
|
||
sub_career_stage = sub_assign.get("stage", 1)
|
||
|
||
if sub_career_name and sub_career_name in career_name_to_obj:
|
||
sub_career = career_name_to_obj[sub_career_name]
|
||
|
||
# 创建CharacterCareer关联
|
||
char_career = CharacterCareer(
|
||
character_id=character.id,
|
||
career_id=sub_career.id,
|
||
career_type="sub",
|
||
current_stage=min(sub_career_stage, sub_career.max_stage),
|
||
stage_progress=0
|
||
)
|
||
db.add(char_career)
|
||
|
||
# 添加到副职业列表
|
||
sub_career_list.append({
|
||
"career_id": sub_career.id,
|
||
"stage": char_career.current_stage
|
||
})
|
||
|
||
careers_assigned += 1
|
||
logger.info(f" ✅ 分配副职业：{character.name} -> {sub_career.name} (阶段{char_career.current_stage})")
|
||
else:
|
||
if sub_career_name:
|
||
logger.warning(f" ⚠️ 副职业不存在：{character.name} -> {sub_career_name}")
|
||
|
||
# 更新Character冗余字段
|
||
if sub_career_list:
|
||
character.sub_careers = json.dumps(sub_career_list, ensure_ascii=False)
|
||
|
||
except Exception as e:
|
||
logger.warning(f" ❌ 分配职业失败：{character.name} - {str(e)}")
|
||
continue
|
||
|
||
await db.flush()
|
||
logger.info(f"💼 职业分配完成：共分配{careers_assigned}个职业")
|
||
yield await SSEResponse.send_progress(f"已分配{careers_assigned}个职业", 87)
|
||
|
||
# 刷新并建立名称映射
|
||
for character, _ in created_characters:
|
||
await db.refresh(character)
|
||
character_name_to_obj[character.name] = character
|
||
logger.info(f"向导创建角色：{character.name} (ID: {character.id}, 是否组织: {character.is_organization})")
|
||
|
||
# 第三阶段：为is_organization=True的角色创建Organization记录
|
||
yield await SSEResponse.send_progress("创建组织记录...", 88)
|
||
organization_name_to_obj = {} # 组织名称到Organization对象的映射
|
||
|
||
for character, char_data in created_characters:
|
||
if character.is_organization:
|
||
# 检查是否已存在Organization记录
|
||
org_check = await db.execute(
|
||
select(Organization).where(Organization.character_id == character.id)
|
||
)
|
||
existing_org = org_check.scalar_one_or_none()
|
||
|
||
if not existing_org:
|
||
# 创建Organization记录
|
||
org = Organization(
|
||
character_id=character.id,
|
||
project_id=project_id,
|
||
member_count=0, # 初始为0，后续添加成员时会更新
|
||
power_level=char_data.get("power_level", 50),
|
||
location=char_data.get("location"),
|
||
motto=char_data.get("motto"),
|
||
color=char_data.get("color")
|
||
)
|
||
db.add(org)
|
||
logger.info(f"向导创建组织记录：{character.name}")
|
||
else:
|
||
org = existing_org
|
||
|
||
# 建立组织名称映射（无论是新建还是已存在）
|
||
organization_name_to_obj[character.name] = org
|
||
|
||
await db.flush() # 确保Organization记录有ID
|
||
|
||
# 刷新角色以获取ID
|
||
for character, _ in created_characters:
|
||
await db.refresh(character)
|
||
|
||
# 第四阶段：创建角色间的关系
|
||
yield await SSEResponse.send_progress("创建角色关系...", 91)
|
||
relationships_created = 0
|
||
|
||
for character, char_data in created_characters:
|
||
# 跳过组织实体的角色关系处理（组织通过成员关系关联）
|
||
if character.is_organization:
|
||
continue
|
||
|
||
# 处理relationships数组
|
||
relationships_data = char_data.get("relationships_array", [])
|
||
if not relationships_data and isinstance(char_data.get("relationships"), list):
|
||
relationships_data = char_data.get("relationships")
|
||
|
||
if relationships_data and isinstance(relationships_data, list):
|
||
for rel in relationships_data:
|
||
try:
|
||
target_name = rel.get("target_character_name")
|
||
if not target_name:
|
||
logger.debug(f" ⚠️ {character.name}的关系缺少target_character_name，跳过")
|
||
continue
|
||
|
||
# 使用名称映射快速查找
|
||
target_char = character_name_to_obj.get(target_name)
|
||
|
||
if target_char:
|
||
# 避免创建重复关系
|
||
existing_rel = await db.execute(
|
||
select(CharacterRelationship).where(
|
||
CharacterRelationship.project_id == project_id,
|
||
CharacterRelationship.character_from_id == character.id,
|
||
CharacterRelationship.character_to_id == target_char.id
|
||
)
|
||
)
|
||
if existing_rel.scalar_one_or_none():
|
||
logger.debug(f" ℹ️ 关系已存在：{character.name} -> {target_name}")
|
||
continue
|
||
|
||
relationship = CharacterRelationship(
|
||
project_id=project_id,
|
||
character_from_id=character.id,
|
||
character_to_id=target_char.id,
|
||
relationship_name=rel.get("relationship_type", "未知关系"),
|
||
intimacy_level=rel.get("intimacy_level", 50),
|
||
description=rel.get("description", ""),
|
||
started_at=rel.get("started_at"),
|
||
source="ai"
|
||
)
|
||
|
||
# 匹配预定义关系类型
|
||
rel_type_result = await db.execute(
|
||
select(RelationshipType).where(
|
||
RelationshipType.name == rel.get("relationship_type")
|
||
)
|
||
)
|
||
rel_type = rel_type_result.scalar_one_or_none()
|
||
if rel_type:
|
||
relationship.relationship_type_id = rel_type.id
|
||
|
||
db.add(relationship)
|
||
relationships_created += 1
|
||
logger.info(f" ✅ 向导创建关系：{character.name} -> {target_name} ({rel.get('relationship_type')})")
|
||
else:
|
||
logger.warning(f" ⚠️ 目标角色不存在：{character.name} -> {target_name}（可能是AI幻觉）")
|
||
except Exception as e:
|
||
logger.warning(f" ❌ 向导创建关系失败：{character.name} - {str(e)}")
|
||
continue
|
||
|
||
# 第五阶段：创建组织成员关系
|
||
yield await SSEResponse.send_progress("创建组织成员关系...", 94)
|
||
members_created = 0
|
||
|
||
for character, char_data in created_characters:
|
||
# 跳过组织实体本身
|
||
if character.is_organization:
|
||
continue
|
||
|
||
# 处理组织成员关系
|
||
org_memberships = char_data.get("organization_memberships", [])
|
||
if org_memberships and isinstance(org_memberships, list):
|
||
for membership in org_memberships:
|
||
try:
|
||
org_name = membership.get("organization_name")
|
||
if not org_name:
|
||
logger.debug(f" ⚠️ {character.name}的组织成员关系缺少organization_name，跳过")
|
||
continue
|
||
|
||
# 使用映射快速查找组织
|
||
org = organization_name_to_obj.get(org_name)
|
||
|
||
if org:
|
||
# 检查是否已存在成员关系
|
||
existing_member = await db.execute(
|
||
select(OrganizationMember).where(
|
||
OrganizationMember.organization_id == org.id,
|
||
OrganizationMember.character_id == character.id
|
||
)
|
||
)
|
||
if existing_member.scalar_one_or_none():
|
||
logger.debug(f" ℹ️ 成员关系已存在：{character.name} -> {org_name}")
|
||
continue
|
||
|
||
# 创建成员关系
|
||
member = OrganizationMember(
|
||
organization_id=org.id,
|
||
character_id=character.id,
|
||
position=membership.get("position", "成员"),
|
||
rank=membership.get("rank", 0),
|
||
loyalty=membership.get("loyalty", 50),
|
||
joined_at=membership.get("joined_at"),
|
||
status=membership.get("status", "active"),
|
||
source="ai"
|
||
)
|
||
db.add(member)
|
||
|
||
# 更新组织成员计数
|
||
org.member_count += 1
|
||
|
||
members_created += 1
|
||
logger.info(f" ✅ 向导添加成员：{character.name} -> {org_name} ({membership.get('position')})")
|
||
else:
|
||
# 这种情况理论上已经被预处理清理了，但保留日志以防万一
|
||
logger.debug(f" ℹ️ 组织引用已被清理：{character.name} -> {org_name}")
|
||
except Exception as e:
|
||
logger.warning(f" ❌ 向导添加组织成员失败：{character.name} - {str(e)}")
|
||
continue
|
||
|
||
logger.info(f"📊 向导数据统计：")
|
||
logger.info(f" - 创建角色/组织：{len(created_characters)} 个")
|
||
logger.info(f" - 创建组织详情：{len(organization_name_to_obj)} 个")
|
||
logger.info(f" - 创建角色关系：{relationships_created} 条")
|
||
logger.info(f" - 创建组织成员：{members_created} 条")
|
||
|
||
# 更新项目的角色数量和向导步骤状态为2（角色已完成）
|
||
project.character_count = len(created_characters)
|
||
project.wizard_step = 2
|
||
logger.info(f"✅ 更新项目角色数量: {project.character_count}")
|
||
|
||
await db.commit()
|
||
db_committed = True
|
||
|
||
# 重新提取character对象
|
||
created_characters = [char for char, _ in created_characters]
|
||
|
||
# 发送结果
|
||
yield await SSEResponse.send_result({
|
||
"message": f"成功生成{len(created_characters)}个角色/组织（分{total_batches}批完成）",
|
||
"count": len(created_characters),
|
||
"batches": total_batches,
|
||
"characters": [
|
||
{
|
||
"id": char.id,
|
||
"project_id": char.project_id,
|
||
"name": char.name,
|
||
"age": char.age,
|
||
"gender": char.gender,
|
||
"is_organization": char.is_organization,
|
||
"role_type": char.role_type,
|
||
"personality": char.personality,
|
||
"background": char.background,
|
||
"appearance": char.appearance,
|
||
"relationships": char.relationships,
|
||
"organization_type": char.organization_type,
|
||
"organization_purpose": char.organization_purpose,
|
||
"organization_members": char.organization_members,
|
||
"traits": char.traits,
|
||
"created_at": char.created_at.isoformat() if char.created_at else None,
|
||
"updated_at": char.updated_at.isoformat() if char.updated_at else None
|
||
} for char in created_characters
|
||
]
|
||
})
|
||
|
||
yield await SSEResponse.send_progress("完成!", 100, "success")
|
||
yield await SSEResponse.send_done()
|
||
|
||
except GeneratorExit:
|
||
logger.warning("角色生成器被提前关闭")
|
||
if not db_committed and db.in_transaction():
|
||
await db.rollback()
|
||
logger.info("角色生成事务已回滚（GeneratorExit）")
|
||
except Exception as e:
|
||
logger.error(f"角色生成失败: {str(e)}")
|
||
if not db_committed and db.in_transaction():
|
||
await db.rollback()
|
||
logger.info("角色生成事务已回滚（异常）")
|
||
yield await SSEResponse.send_error(f"生成失败: {str(e)}")
|
||
|
||
|
||
@router.post("/characters", summary="流式批量生成角色")
|
||
async def generate_characters_stream(
|
||
request: Request,
|
||
data: Dict[str, Any],
|
||
db: AsyncSession = Depends(get_db),
|
||
user_ai_service: AIService = Depends(get_user_ai_service)
|
||
):
|
||
"""
|
||
使用SSE流式批量生成角色，避免超时
|
||
支持MCP工具增强
|
||
"""
|
||
# 从中间件注入user_id到data中
|
||
if hasattr(request.state, 'user_id'):
|
||
data['user_id'] = request.state.user_id
|
||
|
||
return create_sse_response(characters_generator(data, db, user_ai_service))
|
||
|
||
|
||
async def outline_generator(
|
||
data: Dict[str, Any],
|
||
db: AsyncSession,
|
||
user_ai_service: AIService
|
||
) -> AsyncGenerator[str, None]:
|
||
"""大纲生成流式生成器 - 向导仅生成大纲节点，不展开章节（避免等待过久）"""
|
||
db_committed = False
|
||
try:
|
||
yield await SSEResponse.send_progress("开始生成大纲...", 5)
|
||
|
||
project_id = data.get("project_id")
|
||
# 向导固定生成3个大纲节点（不展开）
|
||
outline_count = data.get("chapter_count", 3)
|
||
narrative_perspective = data.get("narrative_perspective")
|
||
target_words = data.get("target_words", 100000)
|
||
requirements = data.get("requirements", "")
|
||
provider = data.get("provider")
|
||
model = data.get("model")
|
||
user_id = data.get("user_id") # 从中间件注入
|
||
|
||
# 获取项目信息
|
||
yield await SSEResponse.send_progress("加载项目信息...", 10)
|
||
result = await db.execute(
|
||
select(Project).where(Project.id == project_id)
|
||
)
|
||
project = result.scalar_one_or_none()
|
||
if not project:
|
||
yield await SSEResponse.send_error("项目不存在", 404)
|
||
return
|
||
|
||
# 获取角色信息
|
||
yield await SSEResponse.send_progress("加载角色信息...", 15)
|
||
result = await db.execute(
|
||
select(Character).where(Character.project_id == project_id)
|
||
)
|
||
characters = result.scalars().all()
|
||
|
||
characters_info = "\n".join([
|
||
f"- {char.name} ({'组织' if char.is_organization else '角色'}, {char.role_type}): {char.personality[:100] if char.personality else '暂无描述'}"
|
||
for char in characters
|
||
])
|
||
|
||
# 第一阶段：生成3个粗粒度大纲节点
|
||
yield await SSEResponse.send_progress(f"生成{outline_count}个大纲节点...", 10)
|
||
|
||
outline_requirements = f"{requirements}\n\n【重要说明】这是小说的开局部分，请生成{outline_count}个大纲节点，重点关注：\n"
|
||
outline_requirements += "1. 引入主要角色和世界观设定\n"
|
||
outline_requirements += "2. 建立主线冲突和故事钩子\n"
|
||
outline_requirements += "3. 展开初期情节，为后续发展埋下伏笔\n"
|
||
outline_requirements += "4. 不要试图完结故事，这只是开始部分\n"
|
||
outline_requirements += "5. 不要在JSON字符串值中使用中文引号（""''），请使用【】或《》标记\n"
|
||
|
||
# 获取自定义提示词模板
|
||
template = await PromptService.get_template("OUTLINE_CREATE", user_id, db)
|
||
outline_prompt = PromptService.format_prompt(
|
||
template,
|
||
title=project.title,
|
||
theme=project.theme or "未设定",
|
||
genre=project.genre or "通用",
|
||
chapter_count=outline_count,
|
||
narrative_perspective=narrative_perspective,
|
||
target_words=target_words // 10, # 开局约占总字数的1/10
|
||
time_period=project.world_time_period or "未设定",
|
||
location=project.world_location or "未设定",
|
||
atmosphere=project.world_atmosphere or "未设定",
|
||
rules=project.world_rules or "未设定",
|
||
characters_info=characters_info or "暂无角色信息",
|
||
mcp_references="",
|
||
requirements=outline_requirements
|
||
)
|
||
|
||
# 流式生成大纲（带字数统计）
|
||
accumulated_text = ""
|
||
chunk_count = 0
|
||
|
||
async for chunk in user_ai_service.generate_text_stream(
|
||
prompt=outline_prompt,
|
||
provider=provider,
|
||
model=model
|
||
):
|
||
chunk_count += 1
|
||
accumulated_text += chunk
|
||
|
||
# 发送内容块
|
||
yield await SSEResponse.send_chunk(chunk)
|
||
|
||
# 定期更新进度和字数（5-95%，AI生成占90%）
|
||
if chunk_count % 5 == 0:
|
||
progress = min(10 + (chunk_count // 3), 90)
|
||
yield await SSEResponse.send_progress(
|
||
f"生成大纲中... ({len(accumulated_text)}字符)",
|
||
progress
|
||
)
|
||
|
||
# 每20个块发送心跳
|
||
if chunk_count % 20 == 0:
|
||
yield await SSEResponse.send_heartbeat()
|
||
|
||
# 解析大纲结果 - 使用统一的JSON清洗方法
|
||
yield await SSEResponse.send_progress("解析大纲...", 96)
|
||
|
||
try:
|
||
cleaned_text = user_ai_service._clean_json_response(accumulated_text)
|
||
outline_data = json.loads(cleaned_text)
|
||
if not isinstance(outline_data, list):
|
||
outline_data = [outline_data]
|
||
except json.JSONDecodeError as e:
|
||
logger.error(f"大纲JSON解析失败: {e}")
|
||
yield await SSEResponse.send_error("大纲生成失败，请重试")
|
||
return
|
||
|
||
# 保存大纲到数据库
|
||
yield await SSEResponse.send_progress("保存大纲到数据库...", 97)
|
||
created_outlines = []
|
||
for index, outline_item in enumerate(outline_data[:outline_count], 1):
|
||
outline = Outline(
|
||
project_id=project_id,
|
||
title=outline_item.get("title", f"第{index}节"),
|
||
content=outline_item.get("summary", outline_item.get("content", "")),
|
||
structure=json.dumps(outline_item, ensure_ascii=False),
|
||
order_index=index
|
||
)
|
||
db.add(outline)
|
||
created_outlines.append(outline)
|
||
|
||
await db.flush() # 获取大纲ID
|
||
for outline in created_outlines:
|
||
await db.refresh(outline)
|
||
|
||
logger.info(f"✅ 成功创建{len(created_outlines)}个大纲节点")
|
||
|
||
# 根据项目的大纲模式决定是否自动创建章节
|
||
created_chapters = []
|
||
if project.outline_mode == 'one-to-one':
|
||
# 一对一模式：自动为每个大纲创建对应的章节
|
||
yield await SSEResponse.send_progress("一对一模式：自动创建章节...", 98)
|
||
|
||
for outline in created_outlines:
|
||
chapter = Chapter(
|
||
project_id=project_id,
|
||
title=outline.title,
|
||
content="", # 空内容，等待用户生成
|
||
outline_id=None, # 一对一模式下不关联outline_id
|
||
chapter_number=outline.order_index, # 使用chapter_number而不是order_index
|
||
status="pending"
|
||
)
|
||
db.add(chapter)
|
||
created_chapters.append(chapter)
|
||
|
||
await db.flush()
|
||
for chapter in created_chapters:
|
||
await db.refresh(chapter)
|
||
|
||
logger.info(f"✅ 一对一模式：自动创建了{len(created_chapters)}个章节")
|
||
yield await SSEResponse.send_progress(f"已自动创建{len(created_chapters)}个章节", 99)
|
||
else:
|
||
# 一对多模式：跳过自动创建，用户可手动展开
|
||
yield await SSEResponse.send_progress("细化模式：跳过自动创建章节", 99)
|
||
logger.info(f"📝 细化模式：跳过章节创建，用户可在大纲页面手动展开")
|
||
|
||
# 更新项目信息
|
||
project.chapter_count = len(created_chapters) # 记录实际创建的章节数
|
||
project.narrative_perspective = narrative_perspective
|
||
project.target_words = target_words
|
||
project.status = "writing"
|
||
project.wizard_status = "completed"
|
||
project.wizard_step = 3
|
||
|
||
await db.commit()
|
||
db_committed = True
|
||
|
||
logger.info(f"📊 向导大纲生成完成：")
|
||
logger.info(f" - 创建大纲节点：{len(created_outlines)} 个")
|
||
logger.info(f" - 创建章节：{len(created_chapters)} 个")
|
||
logger.info(f" - 大纲模式：{project.outline_mode}")
|
||
|
||
# 构建结果消息
|
||
if project.outline_mode == 'one-to-one':
|
||
result_message = f"成功生成{len(created_outlines)}个大纲节点并自动创建{len(created_chapters)}个章节（传统模式）"
|
||
result_note = "已自动创建章节，可直接生成内容"
|
||
else:
|
||
result_message = f"成功生成{len(created_outlines)}个大纲节点（细化模式，可在大纲页面手动展开）"
|
||
result_note = "可在大纲页面展开为多个章节"
|
||
|
||
# 发送结果
|
||
yield await SSEResponse.send_result({
|
||
"message": result_message,
|
||
"outline_count": len(created_outlines),
|
||
"chapter_count": len(created_chapters),
|
||
"outline_mode": project.outline_mode,
|
||
"outlines": [
|
||
{
|
||
"id": outline.id,
|
||
"order_index": outline.order_index,
|
||
"title": outline.title,
|
||
"content": outline.content[:100] + "..." if len(outline.content) > 100 else outline.content,
|
||
"note": result_note
|
||
} for outline in created_outlines
|
||
],
|
||
"chapters": [
|
||
{
|
||
"id": chapter.id,
|
||
"chapter_number": chapter.chapter_number,
|
||
"title": chapter.title,
|
||
"status": chapter.status
|
||
} for chapter in created_chapters
|
||
] if created_chapters else []
|
||
})
|
||
|
||
yield await SSEResponse.send_progress("完成!", 100, "success")
|
||
yield await SSEResponse.send_done()
|
||
|
||
except GeneratorExit:
|
||
logger.warning("大纲生成器被提前关闭")
|
||
if not db_committed and db.in_transaction():
|
||
await db.rollback()
|
||
logger.info("大纲生成事务已回滚（GeneratorExit）")
|
||
except Exception as e:
|
||
logger.error(f"大纲生成失败: {str(e)}")
|
||
if not db_committed and db.in_transaction():
|
||
await db.rollback()
|
||
logger.info("大纲生成事务已回滚（异常）")
|
||
yield await SSEResponse.send_error(f"生成失败: {str(e)}")
|
||
|
||
@router.post("/outline", summary="流式生成完整大纲")
|
||
async def generate_outline_stream(
|
||
data: Dict[str, Any],
|
||
db: AsyncSession = Depends(get_db),
|
||
user_ai_service: AIService = Depends(get_user_ai_service)
|
||
):
|
||
"""
|
||
使用SSE流式生成完整大纲，避免超时
|
||
"""
|
||
return create_sse_response(outline_generator(data, db, user_ai_service))
|
||
|
||
|
||
async def world_building_regenerate_generator(
|
||
project_id: str,
|
||
data: Dict[str, Any],
|
||
db: AsyncSession,
|
||
user_ai_service: AIService
|
||
) -> AsyncGenerator[str, None]:
|
||
"""世界观重新生成流式生成器"""
|
||
db_committed = False
|
||
try:
|
||
yield await SSEResponse.send_progress("开始重新生成世界观...", 10)
|
||
|
||
# 获取项目信息
|
||
result = await db.execute(
|
||
select(Project).where(Project.id == project_id)
|
||
)
|
||
project = result.scalar_one_or_none()
|
||
if not project:
|
||
yield await SSEResponse.send_error("项目不存在", 404)
|
||
return
|
||
|
||
# 提取参数
|
||
provider = data.get("provider")
|
||
model = data.get("model")
|
||
enable_mcp = data.get("enable_mcp", True)
|
||
user_id = data.get("user_id")
|
||
|
||
# 获取基础提示词（支持自定义）
|
||
yield await SSEResponse.send_progress("准备AI提示词...", 15)
|
||
template = await PromptService.get_template("WORLD_BUILDING", user_id, db)
|
||
base_prompt = PromptService.format_prompt(
|
||
template,
|
||
title=project.title,
|
||
theme=project.theme or "未设定",
|
||
genre=project.genre or "通用",
|
||
description=project.description or "暂无简介"
|
||
)
|
||
|
||
# MCP工具增强：收集参考资料
|
||
reference_materials = ""
|
||
if enable_mcp and user_id:
|
||
try:
|
||
from app.services.mcp_tool_service import mcp_tool_service
|
||
available_tools = await mcp_tool_service.get_user_enabled_tools(
|
||
user_id=user_id,
|
||
db_session=db
|
||
)
|
||
|
||
if available_tools:
|
||
yield await SSEResponse.send_progress("🔍 尝试使用MCP工具收集参考资料...", 18)
|
||
|
||
mcp_template = await PromptService.get_template("MCP_WORLD_BUILDING_PLANNING", user_id, db)
|
||
planning_prompt = PromptService.format_prompt(
|
||
mcp_template,
|
||
title=project.title,
|
||
genre=project.genre,
|
||
theme=project.theme,
|
||
description=project.description or '未设定'
|
||
)
|
||
|
||
planning_result = await user_ai_service.generate_text_with_mcp(
|
||
prompt=planning_prompt,
|
||
user_id=user_id,
|
||
db_session=db,
|
||
enable_mcp=True,
|
||
max_tool_rounds=2,
|
||
tool_choice="auto",
|
||
provider=None,
|
||
model=None
|
||
)
|
||
|
||
if planning_result.get("tool_calls_made", 0) > 0:
|
||
yield await SSEResponse.send_progress(
|
||
f"✅ MCP工具调用成功（{planning_result['tool_calls_made']}次）",
|
||
25
|
||
)
|
||
reference_materials = planning_result.get("content", "")
|
||
else:
|
||
logger.debug("MCP工具可用但AI未选择使用")
|
||
else:
|
||
logger.debug(f"用户 {user_id} 未启用MCP工具，跳过MCP增强")
|
||
|
||
except Exception as e:
|
||
logger.warning(f"MCP工具调用失败（降级处理）: {e}")
|
||
yield await SSEResponse.send_progress("⚠️ MCP工具暂时不可用，使用基础模式", 25)
|
||
|
||
# 构建增强提示词
|
||
if reference_materials:
|
||
enhanced_prompt = f"""{base_prompt}
|
||
|
||
【参考资料】
|
||
以下是通过MCP工具收集的真实背景资料，请参考这些信息构建更真实的世界观：
|
||
|
||
{reference_materials}
|
||
|
||
请结合上述资料，生成符合历史/现实的世界观设定。"""
|
||
final_prompt = enhanced_prompt
|
||
yield await SSEResponse.send_progress("💡 已整合参考资料，开始生成世界观...", 10)
|
||
else:
|
||
final_prompt = base_prompt
|
||
yield await SSEResponse.send_progress("正在调用AI生成...", 10)
|
||
|
||
# ===== 流式生成世界观（带重试机制） =====
|
||
MAX_WORLD_RETRIES = 3 # 最多重试3次
|
||
world_retry_count = 0
|
||
world_generation_success = False
|
||
world_data = {}
|
||
|
||
while world_retry_count < MAX_WORLD_RETRIES and not world_generation_success:
|
||
try:
|
||
retry_suffix = f" (重试{world_retry_count}/{MAX_WORLD_RETRIES})" if world_retry_count > 0 else ""
|
||
yield await SSEResponse.send_progress(f"重新生成世界观{retry_suffix}...", 10 + world_retry_count * 5)
|
||
|
||
# 流式生成世界观
|
||
accumulated_text = ""
|
||
chunk_count = 0
|
||
|
||
async for chunk in user_ai_service.generate_text_stream(
|
||
prompt=final_prompt,
|
||
provider=provider,
|
||
model=model
|
||
):
|
||
chunk_count += 1
|
||
accumulated_text += chunk
|
||
|
||
yield await SSEResponse.send_chunk(chunk)
|
||
|
||
if chunk_count % 5 == 0:
|
||
progress = min(10 + (chunk_count // 5), 85)
|
||
yield await SSEResponse.send_progress(f"生成中... ({len(accumulated_text)}字符)", progress)
|
||
|
||
if chunk_count % 20 == 0:
|
||
yield await SSEResponse.send_heartbeat()
|
||
|
||
# 检查是否返回空响应
|
||
if not accumulated_text or not accumulated_text.strip():
|
||
logger.warning(f"⚠️ AI返回空世界观（尝试{world_retry_count+1}/{MAX_WORLD_RETRIES}）")
|
||
world_retry_count += 1
|
||
if world_retry_count < MAX_WORLD_RETRIES:
|
||
yield await SSEResponse.send_progress(
|
||
f"⚠️ AI返回为空，准备重试...",
|
||
10 + world_retry_count * 5,
|
||
"warning"
|
||
)
|
||
continue
|
||
else:
|
||
# 达到最大重试次数，使用默认值
|
||
logger.error("❌ 世界观重新生成多次返回空响应")
|
||
world_data = {
|
||
"time_period": "AI多次返回为空，请稍后重试",
|
||
"location": "AI多次返回为空，请稍后重试",
|
||
"atmosphere": "AI多次返回为空，请稍后重试",
|
||
"rules": "AI多次返回为空，请稍后重试"
|
||
}
|
||
world_generation_success = True
|
||
break
|
||
|
||
# 解析结果 - 使用统一的JSON清洗方法
|
||
yield await SSEResponse.send_progress("解析AI返回结果...", 80)
|
||
|
||
try:
|
||
logger.info(f"🔍 开始清洗JSON，原始长度: {len(accumulated_text)}")
|
||
cleaned_text = user_ai_service._clean_json_response(accumulated_text)
|
||
logger.info(f"✅ JSON清洗完成，清洗后长度: {len(cleaned_text)}")
|
||
|
||
world_data = json.loads(cleaned_text)
|
||
logger.info(f"✅ 世界观重新生成JSON解析成功（尝试{world_retry_count+1}/{MAX_WORLD_RETRIES}）")
|
||
world_generation_success = True
|
||
|
||
except json.JSONDecodeError as e:
|
||
logger.error(f"❌ 世界构建JSON解析失败（尝试{world_retry_count+1}/{MAX_WORLD_RETRIES}）: {e}")
|
||
logger.error(f" 原始内容长度: {len(accumulated_text)}")
|
||
logger.error(f" 原始内容预览: {accumulated_text[:200]}")
|
||
world_retry_count += 1
|
||
if world_retry_count < MAX_WORLD_RETRIES:
|
||
yield await SSEResponse.send_progress(
|
||
f"⚠️ JSON解析失败，准备重试...",
|
||
10 + world_retry_count * 5,
|
||
"warning"
|
||
)
|
||
continue
|
||
else:
|
||
# 达到最大重试次数，使用默认值
|
||
world_data = {
|
||
"time_period": "AI返回格式错误，请重试",
|
||
"location": "AI返回格式错误，请重试",
|
||
"atmosphere": "AI返回格式错误，请重试",
|
||
"rules": "AI返回格式错误，请重试"
|
||
}
|
||
world_generation_success = True
|
||
|
||
except Exception as e:
|
||
logger.error(f"❌ 世界观重新生成异常（尝试{world_retry_count+1}/{MAX_WORLD_RETRIES}）: {type(e).__name__}: {e}")
|
||
world_retry_count += 1
|
||
if world_retry_count < MAX_WORLD_RETRIES:
|
||
yield await SSEResponse.send_progress(
|
||
f"⚠️ 生成异常，准备重试...",
|
||
10 + world_retry_count * 5,
|
||
"warning"
|
||
)
|
||
continue
|
||
else:
|
||
# 最后一次重试仍失败，抛出异常
|
||
logger.error(f" accumulated_text 长度: {len(accumulated_text) if 'accumulated_text' in locals() else 'N/A'}")
|
||
raise
|
||
|
||
# 不保存到数据库，仅返回生成结果供用户预览
|
||
yield await SSEResponse.send_progress("生成完成，等待用户确认...", 90)
|
||
|
||
# 发送最终结果（不包含project_id，表示未保存）
|
||
yield await SSEResponse.send_result({
|
||
"time_period": world_data.get("time_period"),
|
||
"location": world_data.get("location"),
|
||
"atmosphere": world_data.get("atmosphere"),
|
||
"rules": world_data.get("rules")
|
||
})
|
||
|
||
yield await SSEResponse.send_progress("完成!", 100, "success")
|
||
yield await SSEResponse.send_done()
|
||
|
||
except GeneratorExit:
|
||
logger.warning("世界观重新生成器被提前关闭")
|
||
if not db_committed and db.in_transaction():
|
||
await db.rollback()
|
||
logger.info("世界观重新生成事务已回滚（GeneratorExit）")
|
||
except Exception as e:
|
||
logger.error(f"世界观重新生成失败: {str(e)}")
|
||
if not db_committed and db.in_transaction():
|
||
await db.rollback()
|
||
logger.info("世界观重新生成事务已回滚（异常）")
|
||
yield await SSEResponse.send_error(f"生成失败: {str(e)}")
|
||
|
||
|
||
@router.post("/world-building/{project_id}/regenerate", summary="流式重新生成世界观")
|
||
async def regenerate_world_building_stream(
|
||
project_id: str,
|
||
request: Request,
|
||
data: Dict[str, Any],
|
||
db: AsyncSession = Depends(get_db),
|
||
user_ai_service: AIService = Depends(get_user_ai_service)
|
||
):
|
||
"""
|
||
使用SSE流式重新生成世界观，避免超时
|
||
前端使用EventSource接收实时进度和结果
|
||
"""
|
||
# 从中间件注入user_id到data中
|
||
if hasattr(request.state, 'user_id'):
|
||
data['user_id'] = request.state.user_id
|
||
return create_sse_response(world_building_regenerate_generator(project_id, data, db, user_ai_service))
|
||
|
||
|