重构前端完成

.env

@@ -9,3 +9,8 @@ REGEX_FILE=/data/regex_rules.json
 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/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

@@ -3,6 +3,8 @@
   <component name="NewModuleRootManager">
     <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" />

backend/Dockerfile

@@ -4,21 +4,21 @@ FROM python:3.11-slim
 # 设置工作目录
 WORKDIR /app
 
+# 设置环境变量
+ENV PYTHONUNBUFFERED=1
+ENV PYTHONDONTWRITEBYTECODE=1
+
 # 复制依赖文件
-# 注意：这里的 requirements.txt 在 backend/ 目录下
 COPY 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
-# 关键修改：把 backend/ 目录下的内容复制到 /app/backend/ 下
-# 这样镜像内的结构就是 /app/backend/app/...
-COPY . ./backend/
+COPY . .
 
 # 暴露端口
 EXPOSE 8000
 
 # 启动命令
-# 关键修改：路径改为 backend.app.api.route
-CMD ["uvicorn", "backend.app.api.route: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

@@ -1,18 +1,19 @@
-from fastapi import FastAPI
-# 假设这些函数已经在其他地方定义
-from backend.core.items import ChatRequest
-from backend.tools.get_all_role_and_chat import get_all_role_and_chat as get_chat_file
+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
 
-app = FastAPI()
+router = APIRouter()
 
-# 1. 将输入内容持久化存储到本地jsonl方便前端读
-@app.post("/generate_reply")
-async def save_input_to_json(chat_request: ChatRequest):
-    return 0
+# 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)
 
-# 2. 从本地jsonl中读取历史对话
-@app.get("/get_all_role_and_chat")
-def get_all_role_and_chat():
-    # 直接调用导入的函数
-    result = get_chat_file()
-    return result
+
+# 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/core/config.py

@@ -3,11 +3,12 @@ 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
+# 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/ 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.parent.parent.parent  # 修改这里，添加一个 .parent
+# .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
@@ -15,33 +16,64 @@ 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"
+	# --- 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) ---
+	# --- 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
+	# 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"
+	# 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)
 
-    # 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"
 
 settings = Settings()
 
-if __name__ == '__main__':
-    # 实例化配置对象
-    settings = Settings()
-    print(settings.BASE_PATH)
+# 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/core/items.py

@@ -1,24 +0,0 @@
-from pydantic import BaseModel, Field
-from typing import Optional, List
-
-
-# 1. 定义请求体模型
-class ChatRequest(BaseModel):
-    # --- 基础信息 ---
-    mes: str = Field(..., description="用户输入的消息内容")
-    is_user: bool = Field(..., description="标识发送者是否为用户（True为用户，False为AI）")
-    floor_number: int = Field(..., description="当前对话的楼层号，用于判断是否为重试(Regenerate)请求")
-
-    # --- 身份与会话 ---
-    name: str = Field("default", description="发送者的显示名称，默认为'default'")
-    role_name: Optional[str] = Field(None, description="当前绑定的角色名称")
-    chat_name: Optional[str] = Field(None, description="当前会话的标识名称")
-    preset: Optional[str] = Field(None, description="预设的提示词或系统指令")
-
-    # --- 功能开关 ---
-    stream: bool = Field(False, description="是否开启流式输出")
-    img_switch: bool = Field(False, description="是否开启图片生成功能")
-    table_switch: bool = Field(False, description="是否开启表格生成功能")
-
-# 其他可能需要的参数，比如历史记录，可以在这里加
-    # history: Optional[List[Dict]] = None

backend/main.py

@@ -1,12 +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
-from .api.routes import router
-
+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/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/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

backend/tools/get_all_role_and_chat.py

@@ -1,46 +0,0 @@
-from ..core import config
-from typing import Dict, List
-
-# 使用配置中的 DATA_PATH 并添加 "chat" 子目录
-ROOT_DIR = config.settings.DATA_PATH / "chat"
-
-def get_all_role_and_chat() -> Dict[str, List[str]]:
-    """
-    读取配置目录下的所有子文件夹，并收集每个子文件夹中的 JSONL 文件
-
-    返回:
-        dict: 字典结构，键是文件夹名称，值是该文件夹中的 JSONL 文件列表
-    """
-    result = {}
-
-    # 确保目标目录存在
-    if not ROOT_DIR.exists():
-        print(f"警告: 目录 {ROOT_DIR} 不存在")
-        return result
-
-    # 打印根目录路径和内容（调试用）
-    print(f"正在扫描目录: {ROOT_DIR}")
-    print(f"根目录内容: {list(ROOT_DIR.iterdir())}")
-
-    # 遍历根目录下的所有条目
-    for entry in ROOT_DIR.iterdir():
-        try:
-            # 只处理文件夹
-            if entry.is_dir():
-                print(f"处理文件夹: {entry.name}")  # 调试信息
-                jsonl_files = []
-
-                # 遍历子文件夹中的所有文件
-                for file in entry.iterdir():
-                    if file.is_file() and file.suffix == '.jsonl':
-                        jsonl_files.append(str(file))
-                        print(f"  找到文件: {file.name}")  # 调试信息
-
-                # 如果该文件夹中有 JSONL 文件，则添加到结果中
-                if jsonl_files:
-                    result[entry.name] = jsonl_files
-        except Exception as e:
-            print(f"处理文件夹 {entry.name} 时出错: {str(e)}")
-            continue
-
-    return result

backend/tools/save_input_to_json.py

@@ -1,152 +0,0 @@
-import json
-from datetime import datetime
-from backend.core import config as cfg
-from pathlib import Path
-
-
-# 假设 ChatRequest 定义在这里或者从其他地方导入
-# from backend.app.core.items import ChatRequest
-
-async def save_input_to_json(chat_request: ChatRequest):
-    """
-    保存消息到JSONL文件或处理重roll请求
-
-    参数:
-        chat_request: 包含消息详情的请求对象
-    """
-    # 1. 从对象中提取属性
-    mes = chat_request.mes
-    role_name = chat_request.role_name
-    chat_name = chat_request.chat_name
-    name = chat_request.name
-    is_user = chat_request.is_user
-    floor_number = chat_request.floor_number
-    # stream, img_switch, table_switch 等虽然在这个函数逻辑中没用到，
-    # 但如果 ChatRequest 中有，也可以提取出来备用
-    # stream = chat_request.stream
-    # ...
-
-    config = cfg.settings
-    # 注意：这里要确保 role_name 和 chat_name 不为 None，否则路径拼接会报错
-    # 建议在函数入口处增加校验，或者在 Pydantic 模型中设置为必填项
-    if not role_name or not chat_name:
-        raise ValueError("role_name and chat_name cannot be empty")
-
-    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__':
-    # 注意：为了在本地运行测试，你需要手动构造一个 ChatRequest 对象
-    # 或者临时修改函数签名以便直接传参测试
-
-    # 示例：假设 ChatRequest 是一个简单的类或 Pydantic 模型
-    class MockChatRequest:
-        def __init__(self, **kwargs):
-            self.mes = kwargs.get('mes')
-            self.role_name = kwargs.get('role_name')
-            self.chat_name = kwargs.get('chat_name')
-            self.name = kwargs.get('name')
-            self.is_user = kwargs.get('is_user')
-            self.floor_number = kwargs.get('floor_number')
-
-
-    # 测试重roll最后一条AI消息
-    import asyncio
-
-
-    async def test():
-        req = MockChatRequest(
-            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
-        )
-        await save_input_to_json(req)
-
-
-    asyncio.run(test())

backend/workflows/main_llm_workflow.py

@@ -1,201 +0,0 @@
-# backend/app/workflows/llm_workflow.py
-from typing import Dict, Any, List, Callable
-from dataclasses import dataclass
-from enum import Enum
-
-
-class WorkflowStatus(Enum):
-    """工作流状态枚举"""
-    INITIALIZED = "initialized"
-    RUNNING = "running"
-    COMPLETED = "completed"
-    FAILED = "failed"
-    PAUSED = "paused"
-
-
-@dataclass
-class WorkflowContext:
-    """工作流上下文"""
-    data: Dict[str, Any]
-    status: WorkflowStatus = WorkflowStatus.INITIALIZED
-    metadata: Dict[str, Any] = None
-
-    def __post_init__(self):
-        if self.metadata is None:
-            self.metadata = {}
-
-
-class WorkflowNode:
-    """工作流节点声明"""
-
-    def __init__(
-            self,
-            name: str,
-            handler: Callable,
-            enabled: bool = True,
-            config: Dict[str, Any] = None
-    ):
-        self.name = name  # 节点的唯一标识符，用于区分不同的节点。
-        self.handler = handler  # 一个可调用对象（函数或方法），这是节点实际执行的处理逻辑。
-        self.enabled = enabled  # 布尔值，控制节点是否启用。默认为 True，如果设置为 False，节点将被跳过。
-        self.config = config or {} # 一个字典，用于存储节点的配置信息。默认为空字典。
-        self.next_nodes: List['WorkflowNode'] = [] # 一个节点列表，用于指定当前节点执行完成后应跳转到的下一个节点。默认为空列表，可能指向多分支。
-
-    def execute(self, context: WorkflowContext) -> WorkflowContext:
-        """执行节点处理"""
-        if not self.enabled:
-            return context
-
-        try:
-            context = self.handler(context, self.config)
-            return context
-        except Exception as e:
-            context.status = WorkflowStatus.FAILED
-            context.metadata["error"] = str(e)
-            raise
-
-
-class LLMWorkflow:
-    """LLM工作流声明"""
-
-    def __init__(self):
-        self.nodes: List[WorkflowNode] = []
-        self._initialize_workflow()
-
-    def _initialize_workflow(self):
-        """初始化工作流节点（仅声明，不实现）"""
-        # 输入节点
-        input_node = WorkflowNode(
-            name="input",
-            handler=self._input_handler
-        )
-
-        # 输入预处理节点（可开关）
-        preprocessing_node = WorkflowNode(
-            name="preprocessing",
-            handler=self._preprocessing_handler,
-            enabled=False
-        )
-
-        # RAG处理节点
-        rag_node = WorkflowNode(
-            name="rag",
-            handler=self._rag_handler
-        )
-
-        # 提示词组装节点
-        prompt_assembly_node = WorkflowNode(
-            name="prompt_assembly",
-            handler=self._prompt_assembly_handler
-        )
-
-        # LLM请求节点
-        llm_request_node = WorkflowNode(
-            name="llm_request",
-            handler=self._llm_request_handler
-        )
-
-        # 图像生成节点（可开关）
-        image_generation_node = WorkflowNode(
-            name="image_generation",
-            handler=self._image_generation_handler,
-            enabled=False
-        )
-
-        # 动态表格更新节点（可开关）
-        dynamic_table_node = WorkflowNode(
-            name="dynamic_table",
-            handler=self._dynamic_table_handler,
-            enabled=False
-        )
-
-        # 输出过滤节点
-        output_filter_node = WorkflowNode(
-            name="output_filter",
-            handler=self._output_filter_handler
-        )
-
-        # 输出节点
-        output_node = WorkflowNode(
-            name="output",
-            handler=self._output_handler
-        )
-
-        # 设置节点顺序（构建工作流）
-        self.nodes = [
-            input_node,
-            preprocessing_node,
-            rag_node,
-            prompt_assembly_node,
-            llm_request_node,
-            image_generation_node,
-            dynamic_table_node,
-            output_filter_node,
-            output_node
-        ]
-
-    def execute(self, context: WorkflowContext) -> WorkflowContext:
-        """执行工作流"""
-        context.status = WorkflowStatus.RUNNING
-
-        for node in self.nodes:
-            try:
-                context = node.execute(context)
-
-                # 如果工作流失败，停止执行
-                if context.status == WorkflowStatus.FAILED:
-                    break
-            except Exception as e:
-                context.status = WorkflowStatus.FAILED
-                context.metadata["error"] = str(e)
-                break
-
-        if context.status != WorkflowStatus.FAILED:
-            context.status = WorkflowStatus.COMPLETED
-
-        return context
-
-    def enable_node(self, node_name: str, enabled: bool = True):
-        """启用或禁用特定节点"""
-        for node in self.nodes:
-            if node.name == node_name:
-                node.enabled = enabled
-                return True
-        return False
-
-    # 以下是节点处理函数声明（仅声明，不实现）
-    def _input_handler(self, context: WorkflowContext, config: Dict[str, Any]) -> WorkflowContext:
-        """输入节点处理函数"""
-        pass
-
-    def _preprocessing_handler(self, context: WorkflowContext, config: Dict[str, Any]) -> WorkflowContext:
-        """输入预处理节点处理函数"""
-        pass
-
-    def _rag_handler(self, context: WorkflowContext, config: Dict[str, Any]) -> WorkflowContext:
-        """RAG处理节点处理函数"""
-        pass
-
-    def _prompt_assembly_handler(self, context: WorkflowContext, config: Dict[str, Any]) -> WorkflowContext:
-        """提示词组装节点处理函数"""
-        pass
-
-    def _llm_request_handler(self, context: WorkflowContext, config: Dict[str, Any]) -> WorkflowContext:
-        """LLM请求节点处理函数"""
-        pass
-
-    def _image_generation_handler(self, context: WorkflowContext, config: Dict[str, Any]) -> WorkflowContext:
-        """图像生成节点处理函数"""
-        pass
-
-    def _dynamic_table_handler(self, context: WorkflowContext, config: Dict[str, Any]) -> WorkflowContext:
-        """动态表格更新节点处理函数"""
-        pass
-
-    def _output_filter_handler(self, context: WorkflowContext, config: Dict[str, Any]) -> WorkflowContext:
-        """输出过滤节点处理函数"""
-        pass
-
-    def _output_handler(self, context: WorkflowContext, config: Dict[str, Any]) -> WorkflowContext:
-        """输出节点处理函数"""
-        pass

data/chat/test/3111.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

@@ -2,28 +2,54 @@ version: '3.8'
 
 services:
   backend:
-    build: ./backend
-    command: uvicorn backend.api.route:app --host 0.0.0.0 --port 8000 --reload
-    ports:
-      - "3001:8000"
+    build:
+      context: ./backend
+      dockerfile: Dockerfile
+    container_name: llm-backend
+    command: uvicorn main:app --host 0.0.0.0 --port 8000 --reload
     volumes:
-      - .:/app
-      - ./data:/data
-      - ./outputs:/outputs
+      - ./backend:/app
+      - ./data:/app/data
+      - ./outputs:/app/outputs
     environment:
       - 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
 
   frontend:
-    build: ./frontend
-    command: streamlit run app.py --server.port=8501 --server.address=0.0.0.0 --server.fileWatcherType=poll
+    build:
+      context: ./frontend
+      dockerfile: Dockerfile
+      target: development
+    container_name: llm-frontend
     ports:
-      - "3000:8501"
-    environment:
-      - BACKEND_URL=http://backend:8000
-      - PYTHONUNBUFFERED=1
+      - "23338:5173"
     volumes:
-      - ./frontend:/app  # 确保宿主机路径与容器内路径一致
+      - ./frontend:/app
+      - /app/node_modules
+    environment:
+      - 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
+      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 -i https://pypi.tuna.tsinghua.edu.cn/simple -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（使用 8501 端口，与 docker-compose 映射保持一致）
-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

@@ -1,608 +0,0 @@
-import requests
-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"
-)
-BACKEND_URL = os.getenv("BACKEND_URL", "http://127.0.0.1:8000")
-print(f"DEBUG BACKEND_URL: {BACKEND_URL}", flush=True)  # 看 docker logs
-
-# --- 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;
-    }
-
-    /* 可折叠工具栏 */
-    .collapsible-toolbar {
-        background-color: #FFFFFF;
-        border-bottom: 1px solid #D1D9E6;
-        padding: 10px;
-        margin-bottom: 10px;
-    }
-
-    /* 隐藏工具栏时的样式 */
-    .toolbar-hidden {
-        display: none;
-    }
-
-    /* 工具栏切换按钮 */
-    .toolbar-toggle {
-        position: fixed;
-        top: 10px;
-        right: 10px;
-        z-index: 999;
-        background-color: #FFFFFF;
-        border: 1px solid #D1D9E6;
-        border-radius: 50%;
-        width: 40px;
-        height: 40px;
-        display: flex;
-        align-items: center;
-        justify-content: center;
-        cursor: pointer;
-        box-shadow: 0 2px 4px rgba(0,0,0,0.1);
-    }
-
-    /* 三栏布局 - 修改部分 */
-    .main-container {
-        display: flex;
-        flex-direction: column;
-        height: calc(100vh - 60px);
-    }
-
-    .three-column-layout {
-        display: flex;
-        flex-direction: row;
-        height: 100%;
-        overflow: hidden;
-    }
-
-    .left-column, .middle-column, .right-column {
-        padding: 10px;
-        overflow-y: auto;
-        height: 100%;
-    }
-
-    .left-column {
-        flex: 1;
-        border-right: 1px solid #D1D9E6;
-    }
-
-    .middle-column {
-        flex: 3;
-        border-right: 1px solid #D1D9E6;
-        display: flex;
-        flex-direction: column;
-        overflow: hidden;
-    }
-
-    .right-column {
-        flex: 1;
-    }
-
-    /* 中间列的聊天区域 */
-    .chat-area {
-        flex: 1;
-        overflow-y: auto;
-        padding: 10px;
-        height: calc(100% - 80px); /* 减去输入区域的高度 */
-    }
-
-    /* 中间列的输入区域 */
-    .input-area {
-        flex: 0 0 auto;
-        padding: 10px;
-        border-top: 1px solid #D1D9E6;
-        background-color: #F0F4F8;
-        height: 80px; /* 固定高度 */
-    }
-
-    /* 隐藏Streamlit默认的滚动条样式 */
-    ::-webkit-scrollbar {
-        width: 8px;
-        height: 8px;
-    }
-    ::-webkit-scrollbar-track {
-        background: #f1f1f1;
-    }
-    ::-webkit-scrollbar-thumb {
-        background: #888;
-        border-radius: 4px;
-    }
-    ::-webkit-scrollbar-thumb:hover {
-        background: #555;
-    }
-</style>
-
-<script>
-    // 动态调整布局高度
-    function adjustLayout() {
-        // 获取三个列容器
-        const leftColumn = document.querySelector('.left-column');
-        const middleColumn = document.querySelector('.middle-column');
-        const rightColumn = document.querySelector('.right-column');
-
-        // 设置高度为视口高度减去顶部工具栏高度
-        const height = window.innerHeight - 60; // 减去顶部工具栏的高度
-
-        if (leftColumn) leftColumn.style.height = `${height}px`;
-        if (middleColumn) middleColumn.style.height = `${height}px`;
-        if (rightColumn) rightColumn.style.height = `${height}px`;
-
-        // 调整聊天区域高度
-        const chatArea = document.querySelector('.chat-area');
-        if (chatArea) {
-            const inputArea = document.querySelector('.input-area');
-            const inputHeight = inputArea ? inputArea.offsetHeight : 80;
-            chatArea.style.height = `${height - inputHeight}px`;
-        }
-    }
-
-    // 页面加载时调整布局
-    window.addEventListener('load', adjustLayout);
-
-    // 窗口大小改变时重新调整布局
-    window.addEventListener('resize', adjustLayout);
-
-    // 每次Streamlit重新渲染后调整布局
-    document.addEventListener('newElementRendered', adjustLayout);
-</script>
-""", 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},
-    ]
-if "toolbar_visible" not in st.session_state:
-    st.session_state.toolbar_visible = True
-
-# --- 顶部工具栏 ---
-# 工具栏切换按钮
-st.markdown("""
-<div class="toolbar-toggle" onclick="toggleToolbar()">
-    <span id="toolbar-icon">▼</span>
-</div>
-<script>
-    function toggleToolbar() {
-        var toolbar = document.querySelector('.collapsible-toolbar');
-        var icon = document.getElementById('toolbar-icon');
-        if (toolbar.style.display === 'none') {
-            toolbar.style.display = 'block';
-            icon.textContent = '▼';
-        } else {
-            toolbar.style.display = 'none';
-            icon.textContent = '▲';
-        }
-    }
-</script>
-""", unsafe_allow_html=True)
-
-# 工具栏内容
-if st.session_state.toolbar_visible:
-    with st.container():
-        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:
-    # 使用自定义容器类
-    st.markdown('<div class="left-column">', unsafe_allow_html=True)
-
-    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")
-
-    st.markdown('</div>', unsafe_allow_html=True)
-
-# =======================
-# 2. 中间：流式对话区 (动态读取历史)
-# =======================
-with col_mid:
-    # 使用自定义容器类
-    st.markdown('<div class="middle-column">', unsafe_allow_html=True)
-
-    # --- 控制区域 ---
-    c_ctrl1, c_ctrl2, c_ctrl3 = st.columns([3, 2, 1])
-
-    with c_ctrl1:
-        # --- 数据集选择下拉框 ---
-        try:
-            response = requests.get(f"{BACKEND_URL}/get_all_role_and_chat")
-            if response.status_code == 200:
-                datasets = response.json()
-                dataset_options = list(datasets.keys())
-            else:
-                st.error(f"获取数据集失败: {response.status_code}")
-                dataset_options = []
-        except requests.exceptions.RequestException as e:
-            st.error(f"请求数据集时出错: {e}")
-            dataset_options = []
-
-        selected_dataset = st.selectbox(
-            "选择数据集",
-            dataset_options,
-            index=0 if dataset_options else None,
-            key="dataset_selector"
-        )
-
-    with c_ctrl2:
-        # --- 文件路径选择下拉框 ---
-        # 初始化两层下拉框的数据结构
-        chat_history_options = {}
-        file_options = []
-
-        if selected_dataset:
-            # 使用已经获取的数据集数据
-            chat_history_options = datasets
-            # 获取当前选中数据集对应的文件列表
-            file_options = chat_history_options.get(selected_dataset, [])
-
-        # 第一层下拉框：选择聊天会话（这里应该直接使用selected_dataset）
-        # 不需要再创建一个selectbox，因为已经选择了数据集
-        selected_chat_session = selected_dataset
-
-        # 第二层下拉框：选择文件路径（value列表）
-        if selected_chat_session:
-            file_options = chat_history_options.get(selected_chat_session, [])
-            if file_options:
-                # 提取文件名并去除.jsonl后缀，用于显示
-                display_names = [os.path.basename(f).replace('.jsonl', '') for f in file_options]
-
-                # 创建文件名到完整路径的映射
-                file_name_to_path = {os.path.basename(f).replace('.jsonl', ''): f for f in file_options}
-
-                selected_file_display = st.selectbox(
-                    "选择聊天",
-                    display_names,
-                    index=0 if display_names else None,
-                    key="file_selector"
-                )
-
-                if selected_file_display:
-                    # 保存完整路径到session_state
-                    st.session_state.selected_file_path = file_name_to_path[selected_file_display]
-            else:
-                # 如果没有文件路径，清空选择
-                if "file_selector" in st.session_state:
-                    del st.session_state["file_selector"]
-        else:
-            # 如果没有选择会话，清空选择
-            if "file_selector" in st.session_state:
-                del st.session_state["file_selector"]
-
-    with c_ctrl3:
-        # 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()
-
-        # 显示当前会话信息
-        if selected_dataset and 'selected_file_path' in st.session_state:
-            file_name = os.path.basename(st.session_state.selected_file_path).replace('.jsonl', '')
-            st.caption(f"当前会话：{selected_dataset} - {file_name}")
-        else:
-            st.caption("当前会话：Active_Session_01")
-
-    # --- 核心：动态渲染历史记录 ---
-    # 使用自定义容器类包裹聊天区域
-    st.markdown('<div class="chat-area">', unsafe_allow_html=True)
-
-    # 如果选择了聊天记录，则显示该记录
-    if hasattr(st.session_state, 'selected_chat_data') and st.session_state.selected_chat_data:
-        # 显示选中的聊天记录
-        msg = st.session_state.selected_chat_data
-        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":
-                st.markdown(content, unsafe_allow_html=True)
-            else:
-                st.markdown(content)
-
-            # 显示其他信息
-            with st.expander("详细信息", expanded=False):
-                st.json(msg)
-    else:
-        # 否则显示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"]
-
-                if st.session_state.render_html and msg["role"] == "assistant":
-                    st.markdown(content, unsafe_allow_html=True)
-                else:
-                    st.markdown(content)
-
-    st.markdown('</div>', unsafe_allow_html=True)
-
-    # --- 输入区域 ---
-    # 使用自定义容器类包裹输入区域
-    st.markdown('<div class="input-area">', unsafe_allow_html=True)
-
-    # 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
-        with st.chat_message("assistant"):
-            message_placeholder = st.empty()
-            message_placeholder.markdown("*思考中...*")
-
-            # === 模拟后端流式响应 ===
-            full_response = ""
-            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>"
-
-            chunks = simulated_text.split(" ")
-            for chunk in chunks:
-                full_response += chunk + " "
-                time.sleep(0.1)
-
-                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()
-
-    st.markdown('</div>', unsafe_allow_html=True)
-
-    st.markdown('</div>', unsafe_allow_html=True)
-
-# =======================
-# 3. 右侧：图片与骰子 (蓝白风格)
-# =======================
-with col_right:
-    # 使用自定义容器类
-    st.markdown('<div class="right-column">', unsafe_allow_html=True)
-
-    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(')')}")
-
-    st.markdown('</div>', unsafe_allow_html=True)

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/role/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}"}