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989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279 1280 1281 1282 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1293 1294 1295 1296 1297 1298 1299 1300 1301 1302 1303 1304 1305 1306 | """项目创建向导流式API - 使用SSE避免超时"""
from fastapi import APIRouter, Depends, HTTPException
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.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.prompt_service import prompt_service
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"""
# 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")
provider = data.get("provider")
model = data.get("model")
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
# 获取提示词
yield await SSEResponse.send_progress("准备AI提示词...", 20)
prompt = prompt_service.get_world_building_prompt(
title=title,
theme=theme,
genre=genre
)
# 流式调用AI
yield await SSEResponse.send_progress("正在调用AI生成...", 30)
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
if chunk_count % 5 == 0:
progress = min(30 + (chunk_count // 5), 70)
yield await SSEResponse.send_progress(f"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()
# 解析结果
yield await SSEResponse.send_progress("解析AI返回结果...", 80)
world_data = {}
try:
cleaned_text = accumulated_text.strip()
# 移除markdown代码块标记
if cleaned_text.startswith('```json'):
cleaned_text = cleaned_text[7:].lstrip('\n\r')
elif cleaned_text.startswith('```'):
cleaned_text = cleaned_text[3:].lstrip('\n\r')
if cleaned_text.endswith('```'):
cleaned_text = cleaned_text[:-3].rstrip('\n\r')
cleaned_text = cleaned_text.strip()
world_data = json.loads(cleaned_text)
except json.JSONDecodeError as e:
logger.error(f"世界构建JSON解析失败: {e}")
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"
}
# 保存到数据库
yield await SSEResponse.send_progress("保存到数据库...", 90)
project = Project(
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,
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.project_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")
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("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(
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
"""
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"""
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")
# 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"
}
# 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
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)"
prompt = prompt_service.get_characters_batch_prompt(
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
)
# 流式生成
accumulated_text = ""
async for chunk in user_ai_service.generate_text_stream(
prompt=prompt,
provider=provider,
model=model
):
accumulated_text += chunk
yield await SSEResponse.send_chunk(chunk)
# 解析批次结果
cleaned_text = accumulated_text.strip()
# 移除markdown代码块标记
if cleaned_text.startswith('```json'):
cleaned_text = cleaned_text[7:].lstrip('\n\r')
elif cleaned_text.startswith('```'):
cleaned_text = cleaned_text[3:].lstrip('\n\r')
if cleaned_text.endswith('```'):
cleaned_text = cleaned_text[:-3].rstrip('\n\r')
cleaned_text = cleaned_text.strip()
characters_data = json.loads(cleaned_text)
if not isinstance(characters_data, list):
characters_data = [characters_data]
# 验证生成数量是否精确
if len(characters_data) != current_batch_size:
logger.warning(f"批次{batch_idx+1}生成数量不匹配: 期望{current_batch_size}, 实际{len(characters_data)}")
# 如果数量不足,重试
if len(characters_data) < current_batch_size:
if retry_count < MAX_RETRIES - 1:
retry_count += 1
yield await SSEResponse.send_progress(
f"⚠️ 生成数量不足(期望{current_batch_size},实际{len(characters_data)}),准备重试...",
batch_progress,
"warning"
)
continue
else:
# 最后一次重试仍不足，记录但继续使用
logger.warning(f"批次{batch_idx+1}多次重试后仍数量不足，使用当前结果")
yield await SSEResponse.send_progress(
f"⚠️ 批次{batch_idx+1}生成{len(characters_data)}个（期望{current_batch_size}），继续处理",
batch_progress,
"warning"
)
# 如果数量过多,只取需要的数量并发出警告
else:
logger.warning(f"批次{batch_idx+1}生成过多角色({len(characters_data)}>{current_batch_size}),将只取前{current_batch_size}个")
yield await SSEResponse.send_progress(
f"⚠️ AI生成过多，截取前{current_batch_size}个角色",
batch_progress,
"warning"
)
characters_data = characters_data[:current_batch_size]
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}")
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"
)
else:
yield await SSEResponse.send_progress(
f"批次{batch_idx+1}多次重试失败，跳过",
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}")
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"
)
else:
yield await SSEResponse.send_progress(
f"批次{batch_idx+1}多次重试失败，跳过",
batch_progress,
"warning"
)
if not all_characters:
yield await SSEResponse.send_error("所有批次都生成失败，请重试")
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")
character = Character(
project_id=project_id,
name=char_data.get("name", "未命名角色"),
age=char_data.get("age"),
gender=char_data.get("gender"),
is_organization=char_data.get("is_organization", False),
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"),
organization_purpose=char_data.get("organization_purpose"),
organization_members=json.dumps(char_data.get("organization_members", []), ensure_ascii=False),
traits=json.dumps(char_data.get("traits", []), ensure_ascii=False)
)
db.add(character)
created_characters.append((character, char_data))
await db.flush() # 获取所有角色的ID
# 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})")
# 为is_organization=True的角色创建Organization记录
yield await SSEResponse.send_progress("创建组织记录...", 87)
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", 5),
location=char_data.get("location"),
motto=char_data.get("motto")
)
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)
# 第三阶段：创建角色间的关系
yield await SSEResponse.send_progress("创建角色关系...", 90)
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
# 第四阶段：创建组织成员关系
yield await SSEResponse.send_progress("创建组织成员关系...", 93)
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")
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(
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
"""
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 - 向导固定生成前5章作为开局"""
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5章，忽略传入的chapter_count
chapter_count = 5
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")
# 5章一次性生成，不需要分批
BATCH_SIZE = 5
MAX_RETRIES = 3
# 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
])
# 分批生成大纲
yield await SSEResponse.send_progress("准备分批生成大纲...", 20)
all_outlines = []
total_batches = (chapter_count + BATCH_SIZE - 1) // BATCH_SIZE
for batch_idx in range(total_batches):
start_chapter = batch_idx * BATCH_SIZE + 1
end_chapter = min((batch_idx + 1) * BATCH_SIZE, chapter_count)
current_batch_size = end_chapter - start_chapter + 1
batch_progress = 20 + (batch_idx * 55 // total_batches)
# 重试逻辑
retry_count = 0
batch_success = False
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{start_chapter}-{end_chapter}章大纲{retry_suffix}...",
batch_progress
)
# 构建批次提示词 - 包含前文摘要保持故事连贯
previous_context = ""
if all_outlines:
previous_context = "\n\n【前文情节摘要】:\n"
for outline in all_outlines[-3:]: # 只包含最近3章,避免过长
ch_num = outline.get("chapter_number", "?")
ch_title = outline.get("title", "未命名")
ch_summary = outline.get("summary", "")[:100]
previous_context += f"第{ch_num}章《{ch_title}》: {ch_summary}...\n"
previous_context += f"\n请确保第{start_chapter}-{end_chapter}章与前文情节自然衔接,保持故事连贯性。\n"
# 向导专用的开局大纲要求
batch_requirements = f"{requirements}\n\n【重要说明】这是小说的开局部分，请生成前5章大纲，重点关注：\n"
batch_requirements += "1. 引入主要角色和世界观设定\n"
batch_requirements += "2. 建立主线冲突和故事钩子\n"
batch_requirements += "3. 展开初期情节，为后续发展埋下伏笔\n"
batch_requirements += "4. 不要试图完结故事，这只是开始部分\n"
batch_requirements += "5. 不要在JSON字符串值中使用中文引号（""''），请使用【】或《》标记\n"
batch_prompt = prompt_service.get_complete_outline_prompt(
title=project.title,
theme=project.theme or "未设定",
genre=project.genre or "通用",
chapter_count=5, # 固定5章
narrative_perspective=narrative_perspective,
target_words=target_words // 20, # 开局约占总字数的1/20
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",
requirements=batch_requirements
)
# 流式生成
accumulated_text = ""
async for chunk in user_ai_service.generate_text_stream(
prompt=batch_prompt,
provider=provider,
model=model
):
accumulated_text += chunk
yield await SSEResponse.send_chunk(chunk)
# 解析结果
cleaned_text = accumulated_text.strip()
# 移除markdown代码块标记
if cleaned_text.startswith('```json'):
cleaned_text = cleaned_text[7:].lstrip('\n\r')
elif cleaned_text.startswith('```'):
cleaned_text = cleaned_text[3:].lstrip('\n\r')
if cleaned_text.endswith('```'):
cleaned_text = cleaned_text[:-3].rstrip('\n\r')
cleaned_text = cleaned_text.strip()
batch_outline_data = json.loads(cleaned_text)
if not isinstance(batch_outline_data, list):
batch_outline_data = [batch_outline_data]
# 验证生成数量
if len(batch_outline_data) < current_batch_size:
logger.warning(f"批次{batch_idx+1}生成数量不足: 期望{current_batch_size}, 实际{len(batch_outline_data)}")
if retry_count < MAX_RETRIES - 1:
retry_count += 1
yield await SSEResponse.send_progress(
f"生成数量不足，准备重试...",
batch_progress,
"warning"
)
continue
# 修正章节编号
for i, chapter_data in enumerate(batch_outline_data):
chapter_data["chapter_number"] = start_chapter + i
all_outlines.extend(batch_outline_data)
batch_success = True
logger.info(f"批次{batch_idx+1}成功生成{len(batch_outline_data)}章大纲")
except json.JSONDecodeError as e:
logger.error(f"大纲生成批次{batch_idx+1} JSON解析失败(尝试{retry_count+1}/{MAX_RETRIES}): {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"
)
else:
yield await SSEResponse.send_progress(
f"批次{batch_idx+1}多次重试失败，跳过",
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}")
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"
)
else:
yield await SSEResponse.send_progress(
f"批次{batch_idx+1}多次重试失败，跳过",
batch_progress,
"warning"
)
if not all_outlines:
yield await SSEResponse.send_error("所有批次都生成失败，请重试")
return
outline_data = all_outlines
# 保存到数据库
yield await SSEResponse.send_progress("保存大纲到数据库...", 90)
created_outlines = []
for index, chapter_data in enumerate(outline_data[:chapter_count], 1):
chapter_num = chapter_data.get("chapter_number", index)
outline = Outline(
project_id=project_id,
title=chapter_data.get("title", f"第{chapter_num}章"),
content=chapter_data.get("summary", chapter_data.get("content", "")),
structure=json.dumps(chapter_data, ensure_ascii=False),
order_index=chapter_num
)
db.add(outline)
created_outlines.append(outline)
chapter = Chapter(
project_id=project_id,
chapter_number=chapter_num,
title=chapter_data.get("title", f"第{chapter_num}章"),
summary=chapter_data.get("summary", chapter_data.get("content", ""))[:500] if chapter_data.get("summary") or chapter_data.get("content") else "",
status="draft"
)
db.add(chapter)
# 更新项目（向导固定生成5章作为开局）
project.chapter_count = 5
project.narrative_perspective = narrative_perspective
project.target_words = target_words
project.status = "writing"
project.wizard_status = "completed"
project.wizard_step = 4
await db.commit()
db_committed = True
# 发送结果
yield await SSEResponse.send_result({
"message": f"成功生成{len(created_outlines)}章大纲",
"count": len(created_outlines),
"outlines": [
{
"order_index": outline.order_index,
"title": outline.title,
"content": outline.content[:100] + "..." if len(outline.content) > 100 else outline.content
} for outline in created_outlines
]
})
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 update_world_building_generator(
project_id: str,
data: Dict[str, Any],
db: AsyncSession
) -> AsyncGenerator[str, None]:
"""更新世界观流式生成器"""
db_committed = False
try:
yield await SSEResponse.send_progress("开始更新世界观...", 10)
# 获取项目
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
yield await SSEResponse.send_progress("验证数据...", 30)
# 更新世界观字段
if "time_period" in data:
project.world_time_period = data["time_period"]
if "location" in data:
project.world_location = data["location"]
if "atmosphere" in data:
project.world_atmosphere = data["atmosphere"]
if "rules" in data:
project.world_rules = data["rules"]
yield await SSEResponse.send_progress("保存到数据库...", 70)
await db.commit()
db_committed = True
await db.refresh(project)
# 发送结果
yield await SSEResponse.send_result({
"project_id": project.id,
"time_period": project.world_time_period,
"location": project.world_location,
"atmosphere": project.world_atmosphere,
"rules": project.world_rules
})
yield await SSEResponse.send_progress("完成!", 100, "success")
yield await SSEResponse.send_done()
except GeneratorExit:
logger.warning("更新世界观生成器被提前关闭")
if not db_committed and db.in_transaction():
await db.rollback()
logger.info("更新世界观事务已回滚（GeneratorExit）")
except Exception as e:
logger.error(f"更新世界观失败: {str(e)}")
if not db_committed and db.in_transaction():
await db.rollback()
logger.info("更新世界观事务已回滚（异常）")
yield await SSEResponse.send_error(f"更新失败: {str(e)}")
@router.post("/world-building/{project_id}", summary="流式更新世界观")
async def update_world_building_stream(
project_id: str,
data: Dict[str, Any],
db: AsyncSession = Depends(get_db)
):
"""
使用SSE流式更新项目的世界观信息
请求体格式：
{
"time_period": "时间背景",
"location": "地理位置",
"atmosphere": "氛围基调",
"rules": "世界规则"
}
"""
return create_sse_response(update_world_building_generator(project_id, data, db))
async def regenerate_world_building_generator(
project_id: str,
data: Dict[str, Any],
db: AsyncSession,
user_ai_service: AIService
) -> AsyncGenerator[str, None]:
"""重新生成世界观流式生成器"""
db_committed = False
try:
yield await SSEResponse.send_progress("开始重新生成世界观...", 10)
# 获取项目
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
provider = data.get("provider")
model = data.get("model")
# 获取世界构建提示词
yield await SSEResponse.send_progress("准备AI提示词...", 20)
prompt = prompt_service.get_world_building_prompt(
title=project.title,
theme=project.theme or "",
genre=project.genre or ""
)
# 流式调用AI
yield await SSEResponse.send_progress("正在调用AI生成...", 30)
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
if chunk_count % 5 == 0:
progress = min(30 + (chunk_count // 5), 70)
yield await SSEResponse.send_progress(f"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()
# 解析结果
yield await SSEResponse.send_progress("解析AI返回结果...", 80)
world_data = {}
try:
cleaned_text = accumulated_text.strip()
# 移除markdown代码块标记
if cleaned_text.startswith('```json'):
cleaned_text = cleaned_text[7:].lstrip('\n\r')
elif cleaned_text.startswith('```'):
cleaned_text = cleaned_text[3:].lstrip('\n\r')
if cleaned_text.endswith('```'):
cleaned_text = cleaned_text[:-3].rstrip('\n\r')
cleaned_text = cleaned_text.strip()
world_data = json.loads(cleaned_text)
except json.JSONDecodeError as e:
logger.error(f"AI返回非JSON格式: {e}")
logger.info(world_data)
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"
}
# 更新项目世界观
yield await SSEResponse.send_progress("保存到数据库...", 90)
project.world_time_period = world_data.get("time_period")
project.world_location = world_data.get("location")
project.world_atmosphere = world_data.get("atmosphere")
project.world_rules = world_data.get("rules")
await db.commit()
db_committed = True
await db.refresh(project)
# 发送结果
yield await SSEResponse.send_result({
"project_id": project.id,
"time_period": project.world_time_period,
"location": project.world_location,
"atmosphere": project.world_atmosphere,
"rules": project.world_rules
})
yield await SSEResponse.send_progress("完成!", 100, "success")
yield await SSEResponse.send_done()
except GeneratorExit:
logger.warning("重新生成世界观生成器被提前关闭")
if not db_committed and db.in_transaction():
await db.rollback()
logger.info("重新生成世界观事务已回滚（GeneratorExit）")
except Exception as e:
logger.error(f"重新生成世界观失败: {str(e)}")
if not db_committed and db.in_transaction():
await db.rollback()
logger.info("重新生成世界观事务已回滚（异常）")
yield await SSEResponse.send_error(f"重新生成失败: {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,
data: Dict[str, Any],
db: AsyncSession = Depends(get_db),
user_ai_service: AIService = Depends(get_user_ai_service)
):
"""
使用SSE流式重新生成项目的世界观
请求体格式：
{
"provider": "AI提供商（可选）",
"model": "模型名称（可选）"
}
"""
return create_sse_response(regenerate_world_building_generator(project_id, data, db, user_ai_service))
async def cleanup_wizard_data_generator(
project_id: str,
db: AsyncSession
) -> AsyncGenerator[str, None]:
"""清理向导数据流式生成器"""
db_committed = False
try:
yield await SSEResponse.send_progress("开始清理向导数据...", 10)
# 获取项目
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
# 删除相关的角色
yield await SSEResponse.send_progress("删除角色数据...", 30)
characters = await db.execute(
select(Character).where(Character.project_id == project_id)
)
char_count = 0
for character in characters.scalars():
await db.delete(character)
char_count += 1
# 删除相关的大纲
yield await SSEResponse.send_progress("删除大纲数据...", 50)
outlines = await db.execute(
select(Outline).where(Outline.project_id == project_id)
)
outline_count = 0
for outline in outlines.scalars():
await db.delete(outline)
outline_count += 1
# 删除相关的章节
yield await SSEResponse.send_progress("删除章节数据...", 70)
chapters = await db.execute(
select(Chapter).where(Chapter.project_id == project_id)
)
chapter_count = 0
for chapter in chapters.scalars():
await db.delete(chapter)
chapter_count += 1
# 删除项目
yield await SSEResponse.send_progress("删除项目...", 85)
await db.delete(project)
yield await SSEResponse.send_progress("提交数据库更改...", 95)
await db.commit()
db_committed = True
# 发送结果
yield await SSEResponse.send_result({
"message": "项目及相关数据已清理",
"deleted": {
"characters": char_count,
"outlines": outline_count,
"chapters": chapter_count
}
})
yield await SSEResponse.send_progress("完成!", 100, "success")
yield await SSEResponse.send_done()
except GeneratorExit:
logger.warning("清理向导数据生成器被提前关闭")
if not db_committed and db.in_transaction():
await db.rollback()
logger.info("清理向导数据事务已回滚（GeneratorExit）")
except Exception as e:
logger.error(f"清理数据失败: {str(e)}")
if not db_committed and db.in_transaction():
await db.rollback()
logger.info("清理向导数据事务已回滚（异常）")
yield await SSEResponse.send_error(f"清理失败: {str(e)}")
@router.post("/cleanup/{project_id}", summary="流式清理向导数据")
async def cleanup_wizard_data_stream(
project_id: str,
db: AsyncSession = Depends(get_db)
):
"""
使用SSE流式清理向导过程中创建的项目及相关数据
用于返回上一步时清理已生成的内容
"""
return create_sse_response(cleanup_wizard_data_generator(project_id, db)) |