重构前端完成

.env

@@ -0,0 +1,16 @@
+# ---------- 路径配置 ----------
+VECTORSTORE_PATH=/data/vectorstore
+STATE_FILE=/data/state.json
+SCHEMA_FILE=/data/schema.json
+PRESETS_FILE=/data/presets.json
+REGEX_FILE=/data/regex_rules.json
+
+# ---------- 服务地址 ----------
+COMFYUI_API_URL=http://comfyui:8188
+BACKEND_PORT=8000
+FRONTEND_PORT=8501
+
+# 先配置 .env 文件
+MAIN_LLM_API_KEY=sk-Oh4o3fzV6Qe59B6DRwSskE48xe5D6bq1hkgDZqH1mmJOCN8j
+MAIN_LLM_BASE_URL=https://api.chatfire.cn/v1
+MAIN_LLM_MODEL=glm4.7

.idea/.gitignore

@@ -6,3 +6,4 @@
 # Datasource local storage ignored files
 /dataSources/
 /dataSources.local.xml
+.env

.idea/codeStyles/codeStyleConfig.xml

@@ -0,0 +1,5 @@
+<component name="ProjectCodeStyleConfiguration">
+  <state>
+    <option name="PREFERRED_PROJECT_CODE_STYLE" value="Default" />
+  </state>
+</component>

.idea/llm-workflow-engine.iml

@@ -1,7 +1,11 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <module type="PYTHON_MODULE" version="4">
   <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$" />
+    <content url="file://$MODULE_DIR$">
+      <sourceFolder url="file://$MODULE_DIR$" isTestSource="false" />
+      <sourceFolder url="file://$MODULE_DIR$/backend" isTestSource="false" />
+      <sourceFolder url="file://$MODULE_DIR$/backend/api" isTestSource="false" />
+    </content>
     <orderEntry type="jdk" jdkName="Python 3.9 (pythonProject1)" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>

backend/Dockerfile

@@ -4,15 +4,21 @@ FROM python:3.11-slim
 # 设置工作目录
 WORKDIR /app
 
-# 复制依赖文件并安装
+# 设置环境变量
+ENV PYTHONUNBUFFERED=1
+ENV PYTHONDONTWRITEBYTECODE=1
+
+# 复制依赖文件
 COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
+
+# 安装依赖
+RUN pip install --no-cache-dir -i https://pypi.tuna.tsinghua.edu.cn/simple -r requirements.txt
 
 # 复制所有代码
-COPY app/ ./app/
+COPY . .
 
 # 暴露端口
 EXPOSE 8000
 
 # 启动命令
-CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
+CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "8000", "--reload"]

backend/api/route.py

@@ -0,0 +1,19 @@
+from fastapi import APIRouter
+from .routes import presetsRoute, chatsRoute, worldbooksRoute, apiConfigRoute
+from utils.file_utils import get_all_roles_and_chats
+from core.config import settings
+from pathlib import Path
+
+router = APIRouter()
+
+# 注册子路由
+router.include_router(presetsRoute.router)
+router.include_router(chatsRoute.router)
+router.include_router(worldbooksRoute.router)
+router.include_router(apiConfigRoute.router)
+
+
+# 保留原有的其他路由
+@router.get("/tool_bar/get_all_role_and_chat")
+def get_all_role_and_chat_endpoint():
+	return get_all_roles_and_chats(Path(settings.DATA_PATH))

backend/api/routes/chatsRoute.py

@@ -0,0 +1,56 @@
+from fastapi import APIRouter, HTTPException, status
+# TODO: 实现 ChatService 来替代旧的 ChatHistory 逻辑
+# from services.chat_service import ChatService
+
+router = APIRouter(prefix="/chat", tags=["chat"])
+
+@router.get("", response_model=dict)
+async def list_all_chats():
+	"""获取所有角色的所有聊天列表"""
+	# return await ChatService.list_all_chats()
+	return {"chats": []}
+
+@router.get("/{role_name}/{chat_name}")
+async def get_chat(role_name: str, chat_name: str):
+	"""获取指定聊天的完整内容"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.post("/{role_name}", status_code=status.HTTP_201_CREATED)
+async def create_chat(role_name: str, chat_name: str, metadata: dict = None):
+	"""创建新聊天"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.put("/{role_name}/{chat_name}")
+async def update_chat(role_name: str, chat_name: str, update_data: dict):
+	"""更新聊天元数据"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.delete("/{role_name}/{chat_name}")
+async def delete_chat(role_name: str, chat_name: str):
+	"""删除指定聊天"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.get("/{role_name}/{chat_name}/messages")
+async def list_messages(role_name: str, chat_name: str):
+	"""获取聊天的所有消息"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.get("/{role_name}/{chat_name}/messages/{floor}")
+async def get_message(role_name: str, chat_name: str, floor: int):
+	"""获取指定楼层的消息"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.post("/{role_name}/{chat_name}/messages", status_code=status.HTTP_201_CREATED)
+async def add_message(role_name: str, chat_name: str, message_data: dict):
+	"""向聊天添加新消息"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.put("/{role_name}/{chat_name}/messages/{floor}")
+async def update_message(role_name: str, chat_name: str, floor: int, update_data: dict):
+	"""更新指定楼层的消息"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.delete("/{role_name}/{chat_name}/messages/{floor}")
+async def delete_message(role_name: str, chat_name: str, floor: int):
+	"""删除指定楼层的消息"""
+	raise HTTPException(status_code=501, detail="Not Implemented")

backend/api/routes/presetsRoute.py

@@ -0,0 +1,60 @@
+from fastapi import APIRouter, HTTPException, status
+# TODO: 实现 PresetService 来替代旧的 AIDesignSpec 逻辑
+# from services.preset_service import PresetService
+
+router = APIRouter(prefix="/presets", tags=["presets"])
+
+@router.get("", response_model=dict)
+async def list_presets():
+	"""获取所有预设列表及其基本信息"""
+	# return await PresetService.list_all_presets()
+	return {"presets": []}
+
+@router.get("/{preset_name}")
+async def get_preset(preset_name: str):
+	"""获取指定预设的完整内容"""
+	# try:
+	# 	return await PresetService.get_preset(preset_name)
+	# except FileNotFoundError:
+	# 	raise HTTPException(status_code=404, detail="Preset not found")
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.post("", status_code=status.HTTP_201_CREATED)
+async def create_preset(preset_name: str, preset_data: dict):
+	"""创建新预设"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.put("/{preset_name}")
+async def update_preset(preset_name: str, update_data: dict):
+	"""更新预设配置"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.delete("/{preset_name}")
+async def delete_preset(preset_name: str):
+	"""删除指定预设"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.get("/{preset_name}/components")
+async def list_preset_components(preset_name: str):
+	"""获取预设中的所有组件"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.get("/{preset_name}/components/{component_id}")
+async def get_preset_component(preset_name: str, component_id: str):
+	"""获取指定组件的详情"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.post("/{preset_name}/components", status_code=status.HTTP_201_CREATED)
+async def add_preset_component(preset_name: str, component_data: dict):
+	"""向预设添加新组件"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.put("/{preset_name}/components/{component_id}")
+async def update_preset_component(preset_name: str, component_id: str, update_data: dict):
+	"""更新指定组件"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.delete("/{preset_name}/components/{component_id}")
+async def delete_preset_component(preset_name: str, component_id: str):
+	"""从预设中删除指定组件"""
+	raise HTTPException(status_code=501, detail="Not Implemented")

backend/api/routes/worldbooksRoute.py

@@ -0,0 +1,117 @@
+3# 标准库导入
+import os
+import shutil
+import logging
+from pathlib import Path
+from typing import List, Dict, Any, Optional
+
+# 第三方库导入
+from fastapi import APIRouter, HTTPException, UploadFile, File, Form
+from fastapi.responses import JSONResponse, FileResponse
+
+# 本地模块导入
+from models.internal import WorldInfo, WorldInfoEntry
+from core.config import settings
+
+# 配置日志
+logger = logging.getLogger(__name__)
+
+# 创建路由器
+router = APIRouter(prefix="/worldbooks", tags=["worldbooks"])
+
+# 确保世界书目录存在 (由 config.py 中的 settings.ensure_directories() 统一处理，此处保留作为双重保险)
+os.makedirs(settings.WORLDBOOKS_PATH, exist_ok=True)
+
+
+@router.get("/", response_model=List[Dict[str, Any]])
+async def list_worldbooks():
+	"""
+	获取所有世界书的列表
+	Returns:
+		List[Dict[str, Any]]: 世界书列表
+	"""
+	# TODO: 实现 WorldBookService
+	return []
+
+@router.get("/{name}", response_model=Dict[str, Any])
+async def get_worldbook(name: str):
+	"""
+	获取指定名称的世界书
+	"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.post("/", response_model=Dict[str, Any])
+async def create_worldbook(
+		name: str = Form(...),
+		file: Optional[UploadFile] = File(None)
+):
+	"""
+	创建新世界书
+	"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.put("/{name}", response_model=Dict[str, Any])
+async def update_worldbook(
+		name: str,
+		file: Optional[UploadFile] = File(None)
+):
+	"""
+	更新世界书
+	"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.delete("/{name}")
+async def delete_worldbook(name: str):
+	"""
+	删除世界书
+	"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.get("/{name}/entries", response_model=List[Dict[str, Any]])
+async def list_worldbook_entries(name: str):
+	"""
+	获取世界书的所有条目
+	"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.get("/{name}/entries/{uid}", response_model=Dict[str, Any])
+async def get_worldbook_entry(name: str, uid: int):
+	"""
+	获取世界书的指定条目
+	"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.post("/{name}/entries", response_model=Dict[str, Any])
+async def create_worldbook_entry(name: str, entry_data: Dict[str, Any]):
+	"""
+	在世界书中创建新条目
+	"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.put("/{name}/entries/{uid}", response_model=Dict[str, Any])
+async def update_worldbook_entry(name: str, uid: int, entry_data: Dict[str, Any]):
+	"""
+	更新世界书的指定条目
+	"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.delete("/{name}/entries/{uid}")
+async def delete_worldbook_entry(name: str, uid: int):
+	"""
+	删除世界书的指定条目
+	"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.post("/{name}/import", response_model=Dict[str, Any])
+async def import_worldbook(name: str, file: UploadFile = File(...)):
+	"""
+	从文件导入世界书
+	"""
+	raise HTTPException(status_code=501, detail="Not Implemented")
+
+@router.get("/{name}/export")
+async def export_worldbook(name: str):
+	"""
+	导出世界书为 SillyTavern 格式
+	"""
+	raise HTTPException(status_code=501, detail="Not Implemented")

backend/app/core/Start.py

@@ -1,46 +0,0 @@
-import base64
-from typing import Any, Dict
-from IPython.core.magic_arguments import defaults
-from  .. import nodes
-
-class StartNode():
-    name = "开始节点"
-    inputs = {
-        "user_input": "string",  # 用户输入文本
-        "stream": "boolean",  # 是否流式输出
-        "img_switch": "boolean",  # 是否处理图片
-        "table_switch": "boolean",  # 是否处理表格
-        "role_name": "string",  # 角色名称
-        "chat_name": "string"  # 会话名称
-    }
-
-    async def run(self, text: str = None, image: bytes = None, **kwargs) -> Dict[str, Any]:
-        # 查空：文本不能为空字符串
-        if not text or text.strip() == "":
-            raise ValueError("文本输入不能为空")
-
-        # 查空：图片数据不能为空
-        if image is None or len(image) == 0:
-            raise ValueError("图片输入不能为空")
-
-        # 将图片字节转换为 Base64 字符串，便于在节点间传递
-        image_base64 = base64.b64encode(image).decode('utf-8')
-
-        return {
-            "text": text,
-            "image": image_base64
-        }
-
-async def run(is_user,floor_number,mes: str = None, stream: bool = False, img_switch: bool = False,name = "default",
-              table_switch: bool = False, role_name: str = None, chat_name: str = None,preset: str = None):
-    # 将输入内容持久化存储到本地json方便前端读
-    nodes.save_input_to_json(mes=mes, role_name=role_name, chat_name=chat_name, name=name, is_user=is_user, floor_number=floor_number)
-    # 对上一条输入内容（已确定不变的内容）调用向量化，根据role和chat嵌入到对应本地数据库
-    embed_input(user_input, role_name, chat_name)
-    # 根据role和chat去读取绑定的世界书
-    # 读取预设，进行拼接
-    # 调用模型，返回结果
-    # 将结果持久化存储到本地json方便前端读（用JSONL）
-    # 如果img_switch是开的，那么异步调用生图，并存储到目标文件夹里
-    # 如果table_switch是开的，那么异步调用表格生成，并存储到目标文件夹里
-    # 将结果返回给前端

backend/app/nodes/save_input_to_json.py

@@ -1,145 +0,0 @@
-import json
-from typing import Dict, Any
-from datetime import datetime
-import config as cfg
-from pathlib import Path
-
-
-def save_input_to_json(
-        mes: str,
-        role_name: str,
-        chat_name: str,
-        name: str,
-        is_user: bool,
-        floor_number: int = 0
-) -> Dict[str, Any]:
-    """
-    保存消息到JSONL文件或处理重roll请求
-
-    参数:
-        mes: 消息内容
-        role_name: 角色名称
-        chat_name: 对话名称
-        name: 发送者名称
-        is_user: 是否为用户消息
-        floor_number: 楼层号(对话中的第几次回复)，用于判断是否为重roll请求
-
-    返回:
-        更新后的消息对象
-    """
-    config = cfg.settings
-    file_path = config.BASE_PATH / "data" / "chat" / role_name / f"{chat_name}.jsonl"
-
-    # 确保目录存在
-    Path(file_path).parent.mkdir(parents=True, exist_ok=True)
-
-    # 读取文件内容
-    try:
-        with open(file_path, 'r', encoding='utf-8') as f:
-            lines = f.readlines()
-    except FileNotFoundError:
-        lines = []
-
-    # 判断是否为重roll请求
-    is_regenerate = False
-    target_index = -1
-
-    if lines and floor_number > 0:
-        # 计算当前楼层号
-        current_floor = len(lines)
-
-        # 如果floor_number与当前楼层号相同，则为重roll请求
-        if floor_number == current_floor:
-            # 找到最后一条非用户消息
-            for i in range(len(lines) - 1, -1, -1):
-                try:
-                    line_data = json.loads(lines[i])
-                    if not line_data.get('is_user', False):
-                        is_regenerate = True
-                        target_index = i
-                        break
-                except json.JSONDecodeError:
-                    continue
-
-    # 处理重roll逻辑
-    if is_regenerate:
-        # 解析目标消息
-        try:
-            target_message = json.loads(lines[target_index])
-        except json.JSONDecodeError:
-            raise ValueError(f"无法解析楼层 {floor_number} 的JSON数据")
-
-        # 初始化swipes数组
-        if target_message.get('swipes') is None:
-            target_message['swipes'] = []
-
-        # 将新回复添加到swipes数组
-        target_message['swipes'].append(mes)
-
-        # 更新swipe_id和content
-        target_message['swipes_id'] = len(target_message['swipes']) - 1
-        target_message['content'] = mes
-
-        # 更新文件内容
-        lines[target_index] = json.dumps(target_message, ensure_ascii=False) + '\n'
-
-        # 写回文件
-        with open(file_path, 'w', encoding='utf-8') as f:
-            f.writelines(lines)
-
-        return target_message
-
-    # 处理普通消息保存逻辑
-    else:
-        # 获取当前时间
-        current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-
-        # 构建消息对象
-        message = {
-            "role": role_name,
-            "chat": chat_name,
-            "content": mes,
-            "name": name,
-            "is_user": is_user,
-            "send_date": current_time,
-            "floor_number": len(lines) + 1,  # 记录楼层号
-            "swipes": [],
-            "swipes_id": 0
-        }
-
-        # 追加到文件
-        with open(file_path, 'a', encoding='utf-8') as f:
-            f.write(json.dumps(message, ensure_ascii=False) + '\n')
-
-        return message
-
-
-if __name__ == '__main__':
-    # 测试普通消息保存
-    # save_input_to_json(
-    #     mes="你好",
-    #     role_name="test",
-    #     chat_name="111",
-    #     name="用户",
-    #     is_user=True,
-    #     floor_number=0
-    # )
-    #
-    # save_input_to_json(
-    #     mes="你好，我是AI助手",
-    #     role_name="test",
-    #     chat_name="111",
-    #     name="AI",
-    #     is_user=False,
-    #     floor_number=1
-    # )
-
-    # 测试重roll最后一条AI消息
-    save_input_to_json(
-        mes="这是重roll后的新回复2",
-        role_name="test",
-        chat_name="111",
-        name="AI",
-        is_user=False,
-        floor_number=2  # 与当前楼层号相同，表示重roll
-    )

backend/app/nodes/text_splitter_node.py

@@ -1,56 +0,0 @@
-import re
-from core.node_base import BaseNode
-from typing import List, Dict, Any
-
-
-class TextSplitterNode(BaseNode):
-    name = "文本分割节点"
-    inputs = {"text": "string"}
-    outputs = {
-        "outline": "list",  # 大纲部分列表
-        "requirement": "list",  # 要求部分列表
-        "dialogue": "list",  # 对话部分列表
-        "weak_guidance": "list"  # 弱指引部分列表
-    }
-
-    async def run(self, text: str) -> Dict[str, List[str]]:
-        # 正则匹配三种括号内的内容
-        # 注意：此正则假设括号不嵌套，且没有转义字符
-        pattern = r'\{([^{}]*)\}|\(([^()]*)\)|“([^”]*)”'
-
-        outline = []
-        requirement = []
-        dialogue = []
-        weak_guidance = []
-
-        pos = 0
-        for match in re.finditer(pattern, text):
-            start, end = match.span()
-            # 处理匹配前的普通文本（弱指引）
-            if start > pos:
-                weak_part = text[pos:start].strip()
-                if weak_part:
-                    weak_guidance.append(weak_part)
-
-            # 根据捕获组确定类型
-            if match.group(1) is not None:  # 大括号
-                outline.append(match.group(1).strip())
-            elif match.group(2) is not None:  # 小括号
-                requirement.append(match.group(2).strip())
-            elif match.group(3) is not None:  # 中文引号
-                dialogue.append(match.group(3).strip())
-
-            pos = end
-
-        # 处理剩余的普通文本
-        if pos < len(text):
-            weak_part = text[pos:].strip()
-            if weak_part:
-                weak_guidance.append(weak_part)
-
-        return {
-            "outline": outline,
-            "requirement": requirement,
-            "dialogue": dialogue,
-            "weak_guidance": weak_guidance
-        }

backend/core/config.py

@@ -0,0 +1,79 @@
+import os
+from pathlib import Path
+from dotenv import load_dotenv
+
+# 1. 动态计算项目根目录
+# 假设 config.py 位于 backend/core/ 目录下
+# __file__ 指向本文件的绝对路径
+# .parent 指向 backend/core/ 目录
+# .parent.parent 指向 backend/ 目录
+# .parent.parent.parent 指向项目根目录 (即包含 backend/ 和 frontend/ 的目录)
+PROJECT_ROOT = Path(__file__).resolve().parent.parent.parent
+
+# 2. 加载 .env 文件
+# 假设 .env 文件位于项目根目录下
+load_dotenv(PROJECT_ROOT / ".env")
+
+
+class Settings:
+	# --- 主模型配置 ---
+	MAIN_LLM_API_KEY = os.getenv("MAIN_LLM_API_KEY")
+	MAIN_LLM_MODEL = os.getenv("MAIN_LLM_MODEL", "gpt-3.5-turbo")
+	MAIN_LLM_BASE_URL = os.getenv("MAIN_LLM_BASE_URL", "https://api.openai.com/v1")
+	MAIN_LLM_MAX_TOKENS = int(os.getenv("MAIN_LLM_MAX_TOKENS", "4096"))
+	MAIN_LLM_STREAM = os.getenv("MAIN_LLM_STREAM", "true").lower() == "true"
+
+	# --- 路径配置 (核心修改) ---
+
+	# 强制使用计算出的项目根目录，不再依赖 .env 中的 BASE_PATH
+	BASE_PATH = PROJECT_ROOT
+
+	# 数据目录：固定为根目录下的 data 文件夹
+	DATA_PATH = BASE_PATH / "data"
+
+	# --- 核心数据文件路径 ---
+	STATE_FILE = DATA_PATH / "state.json"
+	SCHEMA_FILE = DATA_PATH / "schema.json"
+	PRESETS_FILE = DATA_PATH / "presets.json"
+	REGEX_FILE = DATA_PATH / "regex_rules.json"
+	VECTORSTORE_PATH = DATA_PATH / "vectorstore"
+
+	# --- 业务数据目录 ---
+
+	# 世界书目录
+	WORLDBOOKS_PATH = DATA_PATH / "worldbooks"
+
+	# 预设目录
+	PRESET_PATH = DATA_PATH / "preset"
+
+	# 聊天记录目录
+	CHAT_PATH = DATA_PATH / "chat"
+
+	# 临时文件目录
+	TEMP_PATH = DATA_PATH / "temp"
+
+	def ensure_directories(self):
+		"""确保所有配置的目录存在，如果不存在则创建"""
+		directories = [
+			self.DATA_PATH,
+			self.WORLDBOOKS_PATH,
+			self.PRESET_PATH,
+			self.CHAT_PATH,
+			self.TEMP_PATH,
+		]
+		for directory in directories:
+			directory.mkdir(parents=True, exist_ok=True)
+
+
+settings = Settings()
+
+# 初始化时自动创建必要的目录
+settings.ensure_directories()
+
+if __name__ == '__main__':
+	settings = Settings()
+	print(f"项目根目录: {settings.BASE_PATH}")
+	print(f"数据目录: {settings.DATA_PATH}")
+	print(f"世界书目录: {settings.WORLDBOOKS_PATH}")
+	print(f"预设目录: {settings.PRESETS_PATH}")
+	print(f"聊天目录: {settings.CHAT_PATH}")

backend/main.py

@@ -0,0 +1,41 @@
+import logging
+import sys
+
+# 配置日志
+logging.basicConfig(
+		level=logging.INFO,
+		format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+		handlers=[
+			logging.StreamHandler(sys.stdout)
+		]
+)
+
+# 确保所有模块的日志都能被捕获
+for logger_name in ['uvicorn', 'uvicorn.access', 'fastapi']:
+	logging_logger = logging.getLogger(logger_name)
+	logging_logger.setLevel(logging.INFO)
+
+# backend/app/main.py
+from fastapi import FastAPI
+try:
+    from backend.api.route import router
+except ImportError:
+    from api.route import router
+app = FastAPI(title="LLM Workflow Engine")
+
+# 注册路由
+app.include_router(router, prefix="/api")
+
+# 添加健康检查端点
+@app.get("/health")
+async def health_check():
+    return {"status": "healthy"}
+
+# 添加根路径
+@app.get("/")
+async def root():
+    return {"message": "LLM Workflow Engine", "status": "running"}
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)

backend/requirements.txt

@@ -1,3 +1,12 @@
 fastapi==0.104.1
 uvicorn[standard]==0.24.0
 python-multipart==0.0.6
+cryptography>=41.0.0
+requests>=2.31.0
+
+# LangChain for LLM integration (让 pip 自动解析兼容版本)
+langchain>=0.1.0
+langchain-openai>=0.0.5
+langchain-anthropic>=0.1.1
+openai>=1.12.0
+anthropic>=0.23.0

config.py

@@ -1,45 +0,0 @@
-import os
-from pathlib import Path
-from dotenv import load_dotenv
-
-# 1. 动态计算项目根目录
-# 假设 config.py 位于 backend/ 目录下
-# __file__ 指向本文件的绝对路径
-# .parent 指向 backend/ 目录
-# .parent.parent 指向项目根目录 (即包含 backend/ 和 frontend/ 的目录)
-PROJECT_ROOT = Path(__file__).resolve().parent
-
-# 2. 加载 .env 文件
-# 假设 .env 文件位于项目根目录下
-load_dotenv(PROJECT_ROOT / ".env")
-
-
-class Settings:
-    # --- 主模型配置 ---
-    MAIN_LLM_API_KEY = os.getenv("MAIN_LLM_API_KEY")
-    MAIN_LLM_MODEL = os.getenv("MAIN_LLM_MODEL", "gpt-3.5-turbo")
-    MAIN_LLM_BASE_URL = os.getenv("MAIN_LLM_BASE_URL", "https://api.openai.com/v1")
-    MAIN_LLM_MAX_TOKENS = int(os.getenv("MAIN_LLM_MAX_TOKENS", "4096"))
-    MAIN_LLM_STREAM = os.getenv("MAIN_LLM_STREAM", "true").lower() == "true"
-
-    # --- 路径配置 (核心修改) ---
-
-    # 强制使用计算出的项目根目录，不再依赖 .env 中的 BASE_PATH
-    BASE_PATH = PROJECT_ROOT
-
-    # 数据目录：固定为根目录下的 data 文件夹
-    # 即使 .env 里写了 DATA_PATH=/data，这里也会强制指向项目根目录下的 data
-    DATA_PATH = BASE_PATH / "data"
-
-    # 其他文件路径：基于 DATA_PATH 拼接
-    STATE_FILE = DATA_PATH / "state.json"
-    SCHEMA_FILE = DATA_PATH / "schema.json"
-    PRESETS_FILE = DATA_PATH / "presets.json"
-    REGEX_FILE = DATA_PATH / "regex_rules.json"
-    VECTORSTORE_PATH = DATA_PATH / "vectorstore"
-
-    # ... 其他配置 ...
-
-
-# 实例化配置对象
-settings = Settings()

data/chat/test/111.jsonl

@@ -1,2 +0,0 @@
-{"role": "test", "chat": "111", "content": "你好", "name": "用户", "is_user": true, "send_date": "2026-03-12 18:26:50", "floor_number": 1, "swipes": [], "swipes_id": 0}
-{"role": "test", "chat": "111", "content": "这是重roll后的新回复2", "name": "AI", "is_user": false, "send_date": "2026-03-12 18:26:50", "floor_number": 2, "swipes": ["这是重roll后的新回复", "这是重roll后的新回复2"], "swipes_id": 1}

data/chat/testRole1/111.jsonl

@@ -0,0 +1,5 @@
+{"user_name": "User", "character_name": "AI Dungeon Master", "integrity": "uuid-001", "chat_id_hash": "hash-001", "note_prompt": "你是一个经验丰富的D&D地下城主。", "note_interval": 0, "note_position": 0, "note_depth": 0, "note_role": 0, "extensions": {}, "timedWorldInfo": {}, "variables": {}, "tainted": false, "lastInContextMessageId": -1}
+{"name": "User", "is_user": true, "is_system": false, "floor": 0, "send_date": "1700000000000", "mes": "你好，我想开始一个新的冒险。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
+{"name": "AI Dungeon Master", "is_user": false, "is_system": false, "floor": 1, "send_date": "1700000001000", "mes": "欢迎，冒险者。请告诉我你想扮演什么角色？", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["欢迎，冒险者。请告诉我你想扮演什么角色？", "你好，旅行者。在这个奇幻世界中，你是谁？"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}
+{"name": "User", "is_user": true, "is_system": false, "floor": 2, "send_date": "1700000002000", "mes": "我想成为一名人类战士。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
+{"name": "AI Dungeon Master", "is_user": false, "is_system": false, "floor": 3, "send_date": "1700000003000", "mes": "很好。你站在喧闹的酒馆门口，手里握着一把旧长剑。你打算做什么？", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["很好。你站在喧闹的酒馆门口，手里握着一把旧长剑。你打算做什么？", "明白了。作为一名人类战士，你正身处繁华的市集广场。你的下一步行动是？"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}

data/chat/testRole1/11111.jsonl

@@ -0,0 +1,5 @@
+{"user_name": "Commander", "character_name": "XCOM AI", "integrity": "uuid-003", "chat_id_hash": "hash-003", "note_prompt": "你是一名XCOM基地的中央AI，负责协助指挥官管理外星威胁。", "note_interval": 0, "note_position": 0, "note_depth": 0, "note_role": 0, "extensions": {}, "timedWorldInfo": {}, "variables": {}, "tainted": false, "lastInContextMessageId": -1}
+{"name": "Commander", "is_user": true, "is_system": false, "floor": 0, "send_date": "1700000000000", "mes": "报告当前的外星活动情况。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
+{"name": "XCOM AI", "is_user": false, "is_system": false, "floor": 1, "send_date": "1700000001000", "mes": "指挥官，卫星侦测到在南美洲丛林中有高能反应。可能是外星着陆舱。", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["指挥官，卫星侦测到在南美洲丛林中有高能反应。可能是外星着陆舱。", "警报。我们在非洲检测到异常信号，疑似外星绑架行动正在进行。"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}
+{"name": "Commander", "is_user": true, "is_system": false, "floor": 2, "send_date": "1700000002000", "mes": "派遣布拉德福上尉带领一个小队去调查。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
+{"name": "XCOM AI", "is_user": false, "is_system": false, "floor": 3, "send_date": "1700000003000", "mes": "指令已确认。天火运输机正在起飞。预计到达时间：20分钟。", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["指令已确认。天火运输机正在起飞。预计到达时间：20分钟。", "收到。正在部署天火运输机。布拉德福上尉已登机。"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}

data/chat/testRole2/222.jsonl

@@ -0,0 +1,5 @@
+{"user_name": "Player", "character_name": "Game Master", "integrity": "uuid-002", "chat_id_hash": "hash-002", "note_prompt": "场景：赛博朋克风格的未来城市。", "note_interval": 0, "note_position": 0, "note_depth": 0, "note_role": 0, "extensions": {}, "timedWorldInfo": {}, "variables": {}, "tainted": false, "lastInContextMessageId": -1}
+{"name": "Player", "is_user": true, "is_system": false, "floor": 0, "send_date": "1700000000000", "mes": "我检查我的义体状态。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
+{"name": "Game Master", "is_user": false, "is_system": false, "floor": 1, "send_date": "1700000001000", "mes": "你的视觉义眼显示系统正常，但左臂的伺服电机发出轻微的嗡嗡声，似乎需要维护。", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["你的视觉义眼显示系统正常，但左臂的伺服电机发出轻微的嗡嗡声，似乎需要维护。", "系统自检完成。你的神经接口连接稳定，但义体排异反应指数略有上升。"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}
+{"name": "Player", "is_user": true, "is_system": false, "floor": 2, "send_date": "1700000002000", "mes": "我联系我的黑客朋友，问他知不知道哪里有靠谱的义体医生。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
+{"name": "Game Master", "is_user": false, "is_system": false, "floor": 3, "send_date": "1700000003000", "mes": "你的朋友回复说：'去下城区的老维克那里，虽然他的店看起来很破，但他手艺没得说。'", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["你的朋友回复说：'去下城区的老维克那里，虽然他的店看起来很破，但他手艺没得说。'", "通讯接通。你的朋友告诉你：'别去连锁店，去太平间后巷找'扳手'，他收费公道。'"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}

data/chat/testRole3/333.jsonl

@@ -0,0 +1,5 @@
+{"user_name": "Player", "character_name": "Narrator", "integrity": "uuid-004", "chat_id_hash": "hash-004", "note_prompt": "这是一个文字冒险游戏，你需要描述场景并等待玩家输入。", "note_interval": 0, "note_position": 0, "note_depth": 0, "note_role": 0, "extensions": {}, "timedWorldInfo": {}, "variables": {}, "tainted": false, "lastInContextMessageId": -1}
+{"name": "Player", "is_user": true, "is_system": false, "floor": 0, "send_date": "1700000000000", "mes": "开始游戏。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
+{"name": "Narrator", "is_user": false, "is_system": false, "floor": 1, "send_date": "1700000001000", "mes": "你醒来时发现自己躺在一片陌生的森林里，四周弥漫着浓雾。你身边有一个背包和一把生锈的匕首。", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["你醒来时发现自己躺在一片陌生的森林里，四周弥漫着浓雾。你身边有一个背包和一把生锈的匕首。", "当你睁开眼睛，发现自己身处一艘废弃的飞船中，应急灯闪烁着红光。你手里紧握着一个数据盘。"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}
+{"name": "Player", "is_user": true, "is_system": false, "floor": 2, "send_date": "1700000002000", "mes": "我打开背包看看里面有什么。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
+{"name": "Narrator", "is_user": false, "is_system": false, "floor": 3, "send_date": "1700000003000", "mes": "背包里有一块干硬的面包，一个水壶（里面还有半壶水），以及一张画着奇怪符号的羊皮纸。", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["背包里有一块干硬的面包，一个水壶（里面还有半壶水），以及一张画着奇怪符号的羊皮纸。", "背包里只有一把激光手枪，能量槽仅剩10%。还有一张写着'不要相信AI'的纸条。"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}

docker-compose.yml

@@ -1,26 +1,55 @@
 version: '3.8'
 
 services:
-  # 后端服务
   backend:
-    build: ./backend          # 使用 backend 目录下的 Dockerfile 构建
-    ports:
-      - "8000:8000"          # 映射端口：主机8000 -> 容器8000
+    build:
+      context: ./backend
+      dockerfile: Dockerfile
+    container_name: llm-backend
+    command: uvicorn main:app --host 0.0.0.0 --port 8000 --reload
     volumes:
-      - ./data:/data          # 挂载数据目录（持久化）
-      - ./outputs:/outputs    # 挂载输出目录
+      - ./backend:/app
+      - ./data:/app/data
+      - ./outputs:/app/outputs
     environment:
-      - DATA_PATH=/data
-      - OUTPUT_PATH=/outputs
-    restart: always
+      - PYTHONUNBUFFERED=1
+      - PYTHONDONTWRITEBYTECODE=1
+    restart: unless-stopped
+    networks:
+      - llm-network
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 40s
 
-  # 前端服务
   frontend:
-    build: ./frontend         # 使用 frontend 目录下的 Dockerfile 构建
+    build:
+      context: ./frontend
+      dockerfile: Dockerfile
+      target: development
+    container_name: llm-frontend
     ports:
-      - "8501:8501"          # 映射端口：主机8501 -> 容器8501
+      - "23338:5173"
+    volumes:
+      - ./frontend:/app
+      - /app/node_modules
     environment:
-      - BACKEND_URL=http://backend:8000  # 后端内部地址
+      - NODE_ENV=development
+      - VITE_API_URL=http://backend:8000
+      - VITE_WS_URL=ws://backend:8000
+    command: sh -c "npm install && npm run dev -- --host 0.0.0.0"
     depends_on:
-      - backend               # 等后端启动后再启动前端
-    restart: always
+      backend:
+        condition: service_healthy
+    restart: unless-stopped
+    networks:
+      - llm-network
+
+networks:
+  llm-network:
+    driver: bridge
+
+volumes:
+  node_modules:

frontend/Dockerfile

@@ -1,18 +1,62 @@
-# 使用 Python 3.11 基础镜像
-FROM python:3.11-slim
+# 多阶段构建 - 开发环境
+FROM node:20-alpine AS development
 
 # 设置工作目录
 WORKDIR /app
 
-# 复制依赖文件并安装
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
+# 设置 npm 镜像源（可选，国内推荐使用，加速依赖下载）
+RUN npm config set registry https://registry.npmmirror.com/
 
-# 复制所有代码
+# 复制 package.json 和 package-lock.json
+COPY package.json package-lock.json* ./
+
+# 安装依赖
+RUN npm install
+
+# 复制源代码到容器
 COPY . .
 
-# 暴露端口
-EXPOSE 8501
+# 暴露 Vite 默认端口 5173
+EXPOSE 5173
 
-# 启动命令
-CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]
+# 设置环境变量
+ENV NODE_ENV=development
+ENV VITE_API_URL=http://backend:8000/api
+
+# 启动 Vite 开发服务器
+CMD ["npm", "run", "dev", "--", "--host", "0.0.0.0"]
+
+# 多阶段构建 - 生产环境
+FROM node:20-alpine AS build
+
+WORKDIR /app
+
+# 设置 npm 镜像源
+RUN npm config set registry https://registry.npmmirror.com/
+
+# 复制依赖文件
+COPY package.json package-lock.json* ./
+
+# 安装依赖
+RUN npm install
+
+# 复制源代码
+COPY . .
+
+# 构建生产版本
+RUN npm run build
+
+# 生产环境镜像
+FROM nginx:alpine AS production
+
+# 复制构建产物到 Nginx
+COPY --from=build /app/dist /usr/share/nginx/html
+
+# 复制 Nginx 配置文件
+COPY nginx.conf /etc/nginx/conf.d/default.conf
+
+# 暴露端口
+EXPOSE 80
+
+# 启动 Nginx
+CMD ["nginx", "-g", "daemon off;"]

frontend/app.py

@@ -1,349 +0,0 @@
-import streamlit as st
-import os
-from pathlib import Path
-import time
-import random
-
-# --- 页面配置 ---
-st.set_page_config(
-    page_title="AI WorkFlow Engine",
-    page_icon="🤖",
-    layout="wide",
-    initial_sidebar_state="expanded"
-)
-
-# --- 自定义 CSS (蓝白清晰风格) ---
-st.markdown("""
-<style>
-    /* 全局背景与字体 */
-    .stApp {
-        background-color: #F0F4F8; /* 浅蓝灰背景，护眼且清晰 */
-        color: #1A1A1A; /* 深黑色字体 */
-        font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif;
-    }
-
-    /* 隐藏默认菜单 */
-    #MainMenu {visibility: hidden;}
-    footer {visibility: hidden;}
-    header {visibility: hidden;} /* 隐藏顶部默认栏，使用自定义工具栏 */
-
-    /* 侧边栏样式 */
-    section[data-testid="stSidebar"] {
-        background-color: #FFFFFF;
-        border-right: 1px solid #D1D9E6;
-        color: #1A1A1A;
-    }
-    section[data-testid="stSidebar"] .stMarkdown, 
-    section[data-testid="stSidebar"] .stNumberInput, 
-    section[data-testid="stSidebar"] .stSlider {
-        color: #1A1A1A;
-    }
-
-    /* 聊天容器背景 (白色卡片感) */
-    .stChatMessage {
-        background-color: #FFFFFF;
-        border: 1px solid #E1E8F0;
-        border-radius: 8px;
-        padding: 10px;
-        margin-bottom: 10px;
-        box-shadow: 0 2px 4px rgba(0,0,0,0.05);
-    }
-
-    /* 用户消息特殊样式 */
-    .stChatMessage[data-testid="stChatMessage"]:has(.stMarkdown p) {
-        /* 这里很难直接针对 user/assistant 做不同背景，通过 JS 或特定类名较难，
-           Streamlit 原生 chat_message 会自动处理头像，我们主要靠边框和布局区分 */
-    }
-
-    /* 输入框样式 */
-    .stTextInput > div > div > input, 
-    .stTextArea > div > div > textarea {
-        background-color: #FFFFFF;
-        color: #1A1A1A;
-        border: 1px solid #0056B3; /* 蓝色边框 */
-        border-radius: 6px;
-    }
-    .stTextInput > div > div > input:focus, 
-    .stTextArea > div > div > textarea:focus {
-        border-color: #003D80;
-        box-shadow: 0 0 0 2px rgba(0, 86, 179, 0.2);
-    }
-
-    /* 按钮样式 */
-    .stButton > button {
-        background-color: #FFFFFF;
-        color: #0056B3;
-        border: 1px solid #0056B3;
-        border-radius: 6px;
-        font-weight: 600;
-    }
-    .stButton > button:hover {
-        background-color: #0056B3;
-        color: #FFFFFF;
-    }
-    .stButton > button[kind="primary"] {
-        background-color: #0056B3;
-        color: #FFFFFF;
-        border: 1px solid #0056B3;
-    }
-    .stButton > button[kind="primary"]:hover {
-        background-color: #003D80;
-        border-color: #003D80;
-    }
-
-    /* 拼接块列表样式优化 */
-    .splice-item {
-        background-color: #FFFFFF;
-        border: 1px solid #D1D9E6;
-        border-radius: 6px;
-        padding: 8px;
-        margin-bottom: 6px;
-        display: flex;
-        align-items: center;
-    }
-    .splice-name-active { color: #1A1A1A; font-weight: 500; }
-    .splice-name-inactive { color: #8898AA; text-decoration: line-through; }
-
-    /* 顶部工具栏 */
-    .top-bar {
-        background-color: #FFFFFF;
-        padding: 10px 20px;
-        border-bottom: 1px solid #D1D9E6;
-        margin: -10px -10px 10px -10px; /* 抵消默认 padding */
-        display: flex;
-        justify-content: space-between;
-        align-items: center;
-    }
-</style>
-""", unsafe_allow_html=True)
-
-# --- 状态初始化 ---
-if "messages" not in st.session_state:
-    # 初始化一些示例数据，方便查看效果
-    st.session_state.messages = [
-        {"role": "assistant", "content": "你好！我是你的 AI 工作流助手。系统已就绪，请开始对话。"},
-        {"role": "user", "content": "帮我生成一个角色卡，需要包含姓名、年龄和背景故事。"},
-        {"role": "assistant",
-         "content": "好的，这是一个示例角色卡：<br><b>姓名</b>: 艾莉娅<br><b>年龄</b>: 24<br><b>背景</b>: 一位来自北方边境的流浪法师。<br><i>(这是 HTML 渲染测试)</i>"}
-    ]
-if "render_html" not in st.session_state:
-    st.session_state.render_html = True  # 默认开启 HTML 渲染以展示效果
-if "image_folder" not in st.session_state:
-    st.session_state.image_folder = "./assets/images"
-if "splice_blocks" not in st.session_state:
-    st.session_state.splice_blocks = [
-        {"id": 1, "name": "[必看] 系统指令", "active": True, "type": "system"},
-        {"id": 2, "name": "A.U.T.O. 预设设置", "active": True, "type": "system"},
-        {"id": 3, "name": "世界书：人物关系", "active": False, "type": "world"},
-        {"id": 4, "name": "Chat History (自动)", "active": True, "type": "history", "editable": False},
-    ]
-
-# --- 顶部工具栏 ---
-c_top1, c_top2, c_top3 = st.columns([1, 6, 1])
-with c_top1:
-    if st.button("📂 打开", key="btn_open"):
-        st.toast("打开会话功能预留")
-    if st.button("💾 保存", key="btn_save"):
-        st.toast("会话已保存")
-with c_top2:
-    st.markdown("<h3 style='margin:0; color:#0056B3;'>AI WorkFlow Engine</h3>", unsafe_allow_html=True)
-with c_top3:
-    if st.button("⚙️ 设置", key="btn_settings"):
-        st.toast("全局设置预留")
-
-st.divider()
-
-# --- 三栏布局 ---
-col_left, col_mid, col_right = st.columns([1, 3, 1], gap="small")
-
-# =======================
-# 1. 左侧：预设与拼接管理 (蓝白风格适配)
-# =======================
-with col_left:
-    st.markdown("#### 📜 全局预设")
-    c_pre1, c_pre2 = st.columns([4, 1])
-    with c_pre1:
-        preset_options = ["Default", "A.U.T.O. v1.47", "Roleplay Pro"]
-        st.selectbox("选择预设", preset_options, label_visibility="collapsed")
-    with c_pre2:
-        if st.button("📥", key="btn_import", help="导入预设"):
-            st.toast("导入功能预留")
-
-    st.markdown("#### ⚙️ 生成参数")
-    c_p1, c_p2 = st.columns(2)
-    with c_p1:
-        st.slider("温度", 0.0, 2.0, 1.0, key="slider_temp")
-        st.slider("Top P", 0.0, 1.0, 0.9, key="slider_top_p")
-    with c_p2:
-        st.slider("频率惩罚", 0.0, 2.0, 1.0, key="slider_freq")
-        st.slider("存在惩罚", 0.0, 2.0, 0.0, key="slider_pres")
-
-    c_l1, c_l2 = st.columns(2)
-    with c_l1:
-        st.number_input("上下文长度", value=30000, key="input_ctx")
-    with c_l2:
-        st.number_input("最大回复", value=500, key="input_max")
-
-    st.checkbox("✅ 流式传输", value=True, key="chk_stream")
-
-    st.markdown("#### 🧩 内容拼接块")
-    st.caption("控制发送至后端的上下文组成")
-
-    # 渲染拼接块列表
-    for block in st.session_state.splice_blocks:
-        with st.container():
-            # 自定义行布局模拟列表项
-            cols = st.columns([0.5, 3, 0.5, 0.5])
-            with cols[0]:
-                icon = "🌍" if block['type'] == 'world' else ("💬" if block['type'] == 'history' else "📄")
-                st.write(icon)
-            with cols[1]:
-                name_class = "splice-name-active" if block['active'] else "splice-name-inactive"
-                st.markdown(f"<div class='{name_class}' style='font-size:0.85em;'>{block['name']}</div>",
-                            unsafe_allow_html=True)
-            with cols[2]:
-                disabled = not block.get('editable', True)
-                if st.button("✏️", key=f"edit_{block['id']}", disabled=disabled):
-                    st.toast(f"编辑：{block['name']}")
-            with cols[3]:
-                is_active = st.checkbox("✓", value=block['active'], key=f"act_{block['id']}",
-                                        label_visibility="collapsed")
-                if is_active != block['active']:
-                    block['active'] = is_active
-                    st.rerun()
-            st.markdown("<div style='height:1px; background:#E1E8F0; margin:4px 0;'></div>", unsafe_allow_html=True)
-
-    if st.button("+ 添加拼接块", use_container_width=True):
-        st.toast("添加新功能预留")
-
-# =======================
-# 2. 中间：流式对话区 (动态读取历史)
-# =======================
-with col_mid:
-    # 顶部控制条
-    c_ctrl1, c_ctrl2 = st.columns([4, 1])
-    with c_ctrl1:
-        st.caption("当前会话：Active_Session_01")
-    with c_ctrl2:
-        # HTML 渲染切换
-        toggle_html = st.toggle("HTML 渲染", value=st.session_state.render_html, key="html_toggle")
-        if toggle_html != st.session_state.render_html:
-            st.session_state.render_html = toggle_html
-            st.rerun()
-
-    # --- 核心：动态渲染历史记录 ---
-    # 使用 st.container 包裹，确保每次 rerun 都能完整重绘
-    chat_container = st.container()
-
-    with chat_container:
-        # 遍历 session_state 中的消息历史
-        for i, msg in enumerate(st.session_state.messages):
-            with st.chat_message(msg["role"]):
-                content = msg["content"]
-
-                # 根据开关决定是否解析 HTML
-                if st.session_state.render_html and msg["role"] == "assistant":
-                    # 允许 HTML 标签
-                    st.markdown(content, unsafe_allow_html=True)
-                else:
-                    # 纯文本/Markdown 模式
-                    st.markdown(content)
-
-                # 可选：在每条消息下添加操作按钮 (编辑/复制/重试) - 预留
-                # with st.expander("...", expanded=False): ...
-
-    # --- 输入区域 ---
-    st.markdown("---")
-
-    # 聊天输入框
-    user_input = st.chat_input("输入消息... (支持 /命令)")
-
-    if user_input:
-        # 1. 将用户输入加入历史
-        st.session_state.messages.append({"role": "user", "content": user_input})
-
-        # 2. 触发重新渲染，此时上方循环会立即显示用户消息
-        # 注意：Streamlit 是同步执行的，要模拟“流式”通常需要后端配合 yield
-        # 这里为了演示前端动态读取，我们先显示用户消息，然后模拟一个后台任务
-
-        # 占位符用于显示正在生成的状态或流式内容
-        with st.chat_message("assistant"):
-            message_placeholder = st.empty()
-            message_placeholder.markdown("*思考中...*")
-
-            # === 模拟后端流式响应 (实际项目中此处替换为 requests.post(stream=True)) ===
-            full_response = ""
-            # 构造一个包含 HTML 的回复用于测试
-            simulated_text = f"收到您的指令：**{user_input}**。\n\n这是一个测试回复，如果您开启了 **HTML 渲染**，下方将显示彩色文本和表格：<br><span style='color:#0056B3; font-weight:bold;'>蓝色高亮文本</span><br><table border='1' style='border-collapse:collapse; width:100%;'><tr><th>属性</th><th>值</th></tr><tr><td>状态</td><td>正常</td></tr></table>"
-
-            # 简单的逐字模拟 (实际应来自后端 chunk)
-            chunks = simulated_text.split(" ")
-            for chunk in chunks:
-                full_response += chunk + " "
-                time.sleep(0.1)  # 模拟网络延迟
-
-                if st.session_state.render_html:
-                    message_placeholder.markdown(full_response, unsafe_allow_html=True)
-                else:
-                    message_placeholder.markdown(full_response)
-
-            # 3. 将完整的助手回复存入历史
-            st.session_state.messages.append({"role": "assistant", "content": full_response})
-
-        # 强制刷新以确保持久化显示
-        st.rerun()
-
-# =======================
-# 3. 右侧：图片与骰子 (蓝白风格)
-# =======================
-with col_right:
-    st.markdown("#### 🖼️ 本地图库")
-    img_path = Path(st.session_state.image_folder)
-    img_path.mkdir(parents=True, exist_ok=True)
-
-    try:
-        images = [f for f in os.listdir(img_path) if f.endswith(('.png', '.jpg', '.jpeg', '.webp'))]
-        if images:
-            cols = st.columns(2)
-            for idx, img_name in enumerate(images[:8]):
-                with cols[idx % 2]:
-                    # 增加白色背景和边框，使图片在浅灰底上更突出
-                    st.markdown(
-                        f"<div style='background:white; padding:5px; border-radius:4px; border:1px solid #ddd;'>",
-                        unsafe_allow_html=True)
-                    st.image(str(img_path / img_name), use_container_width=True)
-                    st.caption(img_name)
-                    st.markdown("</div>", unsafe_allow_html=True)
-        else:
-            st.info("图片文件夹为空")
-    except Exception as e:
-        st.error(f"读取错误：{e}")
-
-    st.divider()
-
-    st.markdown("#### 🎲 检定工具")
-    tab_table, tab_dice = st.tabs(["📊 表格", "🎲 骰子"])
-
-    with tab_table:
-        st.markdown("**动态数据表**")
-        st.dataframe(
-            {"属性": ["力量", "敏捷", "智力"], "数值": [50, 60, 70]},
-            hide_index=True,
-            use_container_width=True
-        )
-
-    with tab_dice:
-        roll_type = st.radio("类型", ["难度检定", "对抗骰"], horizontal=True)
-        diff_opts = ["极难 (95)", "困难 (75)", "普通 (50)"]
-        selected_diff = st.selectbox("难度", diff_opts)
-
-        c_r1, c_r2 = st.columns(2)
-        with c_r1:
-            if st.button("🎲 投掷", type="primary", use_container_width=True):
-                res = random.randint(1, 100)
-                color = "#d9534f" if res > int(selected_diff.split('(')[1].strip(')')) else "#5cb85c"
-                st.markdown(
-                    f"<div style='text-align:center; font-size:1.5em; color:{color}; font-weight:bold;'>{res}</div>",
-                    unsafe_allow_html=True)
-        with c_r2:
-            st.caption(f"目标：{selected_diff.split('(')[1].strip(')')}")

frontend/components/chat_window.py

@@ -1,53 +0,0 @@
-import streamlit as st
-import requests
-
-
-def render_chat_window(backend_url):
-    st.subheader("💬 流式对话")
-
-    # 聊天历史显示
-    chat_container = st.container()
-    with chat_container:
-        for message in st.session_state.messages:
-            with st.chat_message(message["role"]):
-                st.markdown(message["content"])
-                # 如果有关联图片，也可以在这里显示
-                if "images" in message:
-                    for img_url in message["images"]:
-                        st.image(img_url, width=200)
-
-    # 输入框
-    if prompt := st.chat_input("输入消息..."):
-        # 1. 显示用户消息
-        st.session_state.messages.append({"role": "user", "content": prompt})
-        with st.chat_message("user"):
-            st.markdown(prompt)
-
-        # 2. 调用后端流式接口
-        with st.chat_message("assistant"):
-            message_placeholder = st.empty()
-            full_response = ""
-
-            # 模拟流式接收 (实际需使用 requests stream 或 websocket)
-            # POST /api/chat/stream
-            try:
-                # 伪代码示例：
-                # with requests.post(f"{backend_url}/api/chat/stream", json={"message": prompt}, stream=True) as r:
-                #     for chunk in r.iter_content(chunk_size=None):
-                #         if chunk:
-                #             full_response += chunk.decode('utf-8')
-                #             message_placeholder.markdown(full_response + "▌")
-
-                # 演示用静态延迟
-                import time
-                response_text = "这是一个流式响应的演示。后端正在处理您的请求..."
-                for char in response_text:
-                    full_response += char
-                    message_placeholder.markdown(full_response + "▌")
-                    time.sleep(0.05)
-
-                message_placeholder.markdown(full_response)
-                st.session_state.messages.append({"role": "assistant", "content": full_response})
-
-            except Exception as e:
-                st.error(f"连接后端失败: {e}")

frontend/components/dice_roller.py

@@ -1,26 +0,0 @@
-import streamlit as st
-import random
-
-
-def render_dice_roller():
-    st.subheader("🎲 命运骰子")
-
-    col1, col2 = st.columns(2)
-
-    with col1:
-        d20 = st.button("D20", use_container_width=True)
-        if d20:
-            roll = random.randint(1, 20)
-            st.metric("结果", roll, delta=None)
-
-    with col2:
-        d6 = st.button("D6", use_container_width=True)
-        if d6:
-            roll = random.randint(1, 6)
-            st.metric("结果", roll, delta=None)
-
-    # 自定义骰子
-    sides = st.number_input("面数", min_value=2, max_value=100, value=10)
-    if st.button(f"投掷 D{sides}", use_container_width=True):
-        roll = random.randint(1, sides)
-        st.success(f"🎲 结果是: **{roll}**")

frontend/components/image_gallery.py

@@ -1,17 +0,0 @@
-import streamlit as st
-
-
-def render_image_gallery(backend_url):
-    st.subheader("🖼️ 生成画廊")
-
-    # 这里通常轮询后端获取最新生成的图片
-    # GET /api/images/latest
-
-    if not st.session_state.generated_images:
-        st.info("暂无生成图片，对话中触发绘图后将在此显示。")
-    else:
-        cols = st.columns(2)
-        for idx, img_url in enumerate(st.session_state.generated_images[-4:]):  # 只显示最近4张
-            with cols[idx % 2]:
-                st.image(img_url, use_container_width=True)
-                st.caption(f"Image {idx + 1}")

frontend/components/settings_panel.py

@@ -1,30 +0,0 @@
-import streamlit as st
-import requests
-
-
-def render_settings_panel(backend_url):
-    st.subheader("⚙️ 预设设置")
-
-    # 模拟获取预设列表 (实际应调用后端 API)
-    # GET /api/presets
-    try:
-        # response = requests.get(f"{backend_url}/api/presets")
-        # presets = response.json()
-        presets = ["角色扮演-奇幻", "项目管理", "旅行规划", "自定义"]  # 占位数据
-    except:
-        presets = ["默认预设"]
-
-    selected_preset = st.selectbox("选择预设模板", presets, index=0)
-
-    st.text_area("系统指令 (System)", height=100, placeholder="在此输入系统级指令...")
-
-    st.checkbox("启用状态记忆", value=True)
-    st.checkbox("启用异步生图", value=True)
-    st.checkbox("启用输入预处理", value=False)
-
-    st.info("💡 修改配置后自动生效，无需重启。")
-
-    # 保存按钮 (调用后端更新配置)
-    if st.button("💾 保存配置", use_container_width=True):
-        st.success("配置已保存！")
-        # requests.post(f"{backend_url}/api/config", json={...})

frontend/components/toolbar.py

@@ -1,18 +0,0 @@
-import streamlit as st
-
-
-def render_toolbar(backend_url):
-    col1, col2, col3 = st.columns([1, 2, 1])
-
-    with col1:
-        st.logo("https://streamlit.io/images/brand/streamlit-logo-primary-colormark-darktext.png",
-                size="large")  # 可替换为项目Logo
-
-    with col2:
-        st.title("AI Tavern 工作流引擎")
-
-    with col3:
-        if st.button("🔄 重置会话", use_container_width=True):
-            st.session_state.messages = []
-            st.rerun()
-        # 这里可以添加更多工具栏按钮，如：知识库管理、系统状态等

frontend/requirements.txt

@@ -1,4 +0,0 @@
-streamlit>=1.30.0
-requests>=2.31.0
-websockets>=12.0
-Pillow>=10.0.0

main.py

@@ -1,13 +1,11 @@
 from fastapi import FastAPI
+from backend.api.route import router
 
 app = FastAPI()
 
+# 注册API路由
+app.include_router(router, prefix="/api")
 
 @app.get("/")
 async def root():
     return {"message": "Hello World"}
-
-
-@app.get("/hello/{name}")
-async def say_hello(name: str):
-    return {"message": f"Hello {name}"}