初始化仅前端版本

This commit is contained in:
2026-03-10 17:13:19 +08:00
commit 24431ca308
27 changed files with 727 additions and 0 deletions

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.env Normal file
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.idea/.gitignore generated vendored Normal file
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# 默认忽略的文件
/shelf/
/workspace.xml
# 基于编辑器的 HTTP 客户端请求
/httpRequests/
# Datasource local storage ignored files
/dataSources/
/dataSources.local.xml

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.idea/.name generated Normal file
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llm-workflow-engine

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<component name="InspectionProjectProfileManager">
<profile version="1.0">
<option name="myName" value="Project Default" />
<inspection_tool class="PyUnresolvedReferencesInspection" enabled="true" level="WARNING" enabled_by_default="true">
<option name="ignoredIdentifiers">
<list>
<option value="requests.models.Response.__getitem__" />
</list>
</option>
</inspection_tool>
</profile>
</component>

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<component name="InspectionProjectProfileManager">
<settings>
<option name="USE_PROJECT_PROFILE" value="false" />
<version value="1.0" />
</settings>
</component>

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

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="Black">
<option name="sdkName" value="Python 3.9 (llm-workflow-engine)" />
</component>
<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9 (pythonProject1)" project-jdk-type="Python SDK" />
</project>

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ProjectModuleManager">
<modules>
<module fileurl="file://$PROJECT_DIR$/.idea/llm-workflow-engine.iml" filepath="$PROJECT_DIR$/.idea/llm-workflow-engine.iml" />
</modules>
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</project>

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="VcsDirectoryMappings">
<mapping directory="$PROJECT_DIR$" vcs="Git" />
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</project>

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backend/Dockerfile Normal file
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# 使用 Python 3.11 基础镜像
FROM python:3.11-slim
# 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
# 复制所有代码
COPY app/ ./app/
# 暴露端口
EXPOSE 8000
# 启动命令
CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]

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import base64
from core.node_base import BaseNode
from typing import Any, Dict
class StartNode(BaseNode):
name = "开始节点"
inputs = {} # 没有输入参数
outputs = {
"text": "string", # 文本内容
"image": "string" # 图片以 Base64 编码的字符串传递
}
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
}

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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
}

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backend/requirements.txt Normal file
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fastapi==0.104.1
uvicorn[standard]==0.24.0
python-multipart==0.0.6

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docker-compose.yml Normal file
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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
volumes:
- ./data:/data # 挂载数据目录(持久化)
- ./outputs:/outputs # 挂载输出目录
environment:
- DATA_PATH=/data
- OUTPUT_PATH=/outputs
restart: always
# 前端服务
frontend:
build: ./frontend # 使用 frontend 目录下的 Dockerfile 构建
ports:
- "8501:8501" # 映射端口主机8501 -> 容器8501
environment:
- BACKEND_URL=http://backend:8000 # 后端内部地址
depends_on:
- backend # 等后端启动后再启动前端
restart: always

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frontend/Dockerfile Normal file
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# 使用 Python 3.11 基础镜像
FROM python:3.11-slim
# 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
# 复制所有代码
COPY . .
# 暴露端口
EXPOSE 8501
# 启动命令
CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]

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frontend/app.py Normal file
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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(')')}")

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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}")

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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}**")

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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}")

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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={...})

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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

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streamlit>=1.30.0
requests>=2.31.0
websockets>=12.0
Pillow>=10.0.0

13
main.py Normal file
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from fastapi import FastAPI
app = FastAPI()
@app.get("/")
async def root():
return {"message": "Hello World"}
@app.get("/hello/{name}")
async def say_hello(name: str):
return {"message": f"Hello {name}"}

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test_main.http Normal file
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# Test your FastAPI endpoints
GET http://127.0.0.1:8000/
Accept: application/json
###
GET http://127.0.0.1:8000/hello/User
Accept: application/json
###