233 lines
8.5 KiB
Python
233 lines
8.5 KiB
Python
import gradio as gr
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import time
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from functools import partial
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# 从各个模块导入所需的功能
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import config
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from analysis_functions import (
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display_transfer_function,
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time_domain_analysis,
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frequency_domain_analysis,
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root_locus_analysis
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)
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# ===== 新增：算例演示模块函数导入 =====
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from case_demo_functions import run_case_demo
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from chatbot import chat_with_ai
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from user_stats import get_online_status_html, update_user_activity
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from ui_components import (
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create_header,
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create_time_domain_tab,
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create_frequency_domain_tab,
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create_root_locus_tab,
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create_case_demo_tab,
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create_chatbot_tab
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)
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# 加载外部CSS文件
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with open("assets/styles.css", "r", encoding="utf-8") as f:
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custom_css = f.read()
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# --- 主应用界面 ---
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with gr.Blocks(title="自动控制理论学习网站 - AI+数智平台", css=custom_css) as demo:
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# 1. 创建UI组件
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# 用户会话ID（隐藏组件）
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session_id = gr.State(value=lambda: str(time.time()) + "_" + str(hash(time.time())))
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# 创建头部信息和在线计数器
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online_counter = create_header()
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# 创建共享的输入组件
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with gr.Row():
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with gr.Column(scale=1):
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with gr.Group():
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gr.HTML("<div class='card-title'>📊 通用系统参数</div>")
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num_input = gr.Textbox(
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label="传递函数分子系数 (Numerator)",
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value="1",
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placeholder="例如: 1 或 1,2,3",
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info="💡 用逗号分隔多个系数，从最高次项到常数项"
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)
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den_input = gr.Textbox(
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label="传递函数分母系数 (Denominator)",
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value="1,6,11,6",
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placeholder="例如: 1,2,1",
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info="💡 分母阶数通常高于或等于分子阶数"
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)
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# 创建功能选项卡
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with gr.Tabs() as tabs:
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with gr.TabItem("⏱️ 时域分析 (Time Domain)", id=0):
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time_domain_ui = create_time_domain_tab()
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with gr.TabItem("📊 频域分析 (Frequency Domain)", id=1):
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freq_domain_ui = create_frequency_domain_tab()
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with gr.TabItem("🎯 根轨迹 (Root Locus)", id=2):
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root_locus_ui = create_root_locus_tab()
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# ===== 新增：算例演示 Tab（位于根轨迹与智能问答之间） =====
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with gr.TabItem("🧪 算例演示 (Case Demo)", id=3):
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case_demo_ui = create_case_demo_tab()
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with gr.TabItem("🤖 智能问答 (Q&A)", id=4):
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chatbot_ui = create_chatbot_tab()
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# 2. 绑定事件逻辑
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# --- 通用函数 ---
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# 每次操作前更新用户活跃状态
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def wrap_with_activity_update(fn, sid):
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update_user_activity(sid)
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# 使用 partial 将 session_id 绑定到函数上
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# 这样Gradio调用时就不需要显式传递session_id了
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return partial(fn, session_id=sid)
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# --- 时域分析事件 ---
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time_domain_ui["confirm_button"].click(
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fn=display_transfer_function,
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inputs=[num_input, den_input],
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outputs=[time_domain_ui["tf_display"]]
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).then(lambda: get_online_status_html(), outputs=online_counter)
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time_domain_ui["analyze_button"].click(
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fn=time_domain_analysis,
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inputs=[num_input, den_input],
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outputs=[time_domain_ui["output_plot"], time_domain_ui["output_metrics"]]
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).then(lambda: get_online_status_html(), outputs=online_counter)
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# --- 频域分析事件 ---
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def update_frequency_analysis_wrapper(num, den, log_k):
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k = 10**log_k
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fig, metrics, tf_latex, stability = frequency_domain_analysis(num, den, k)
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return fig, metrics, tf_latex, stability, k, get_online_status_html()
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freq_inputs = [num_input, den_input, freq_domain_ui["log_k_slider"]]
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freq_outputs = [
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freq_domain_ui["plot_output"],
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freq_domain_ui["metrics_display"],
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freq_domain_ui["tf_display"],
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freq_domain_ui["stability_display"],
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freq_domain_ui["k_number_display"],
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online_counter
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]
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freq_domain_ui["log_k_slider"].release(
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fn=update_frequency_analysis_wrapper,
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inputs=freq_inputs,
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outputs=freq_outputs
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)
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# --- 根轨迹分析事件 ---
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def update_rl_view_wrapper(log_k, num, den):
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fig, poles, k_val = root_locus_analysis(num, den, log_k)
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return fig, poles, k_val, get_online_status_html()
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rl_inputs = [root_locus_ui["log_k_slider"], num_input, den_input]
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rl_outputs = [
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root_locus_ui["plot_output"],
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root_locus_ui["poles_display"],
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root_locus_ui["k_number_display"],
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online_counter
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]
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root_locus_ui["log_k_slider"].release(
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fn=update_rl_view_wrapper,
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inputs=rl_inputs,
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outputs=rl_outputs
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)
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# 当输入框变化时，也更新频域和根轨迹（如果它们是当前可见的）
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def update_all_on_tf_change(num, den, log_k_freq, log_k_rl):
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# 更新频域
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k_freq = 10**log_k_freq
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fig_freq, metrics, tf_latex, stability = frequency_domain_analysis(num, den, k_freq)
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# 更新根轨迹
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fig_rl, poles, k_val_rl = root_locus_analysis(num, den, log_k_rl)
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return (
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fig_freq, metrics, tf_latex, stability, k_freq,
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fig_rl, poles, k_val_rl,
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get_online_status_html()
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)
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tf_change_inputs = [num_input, den_input, freq_domain_ui["log_k_slider"], root_locus_ui["log_k_slider"]]
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tf_change_outputs = freq_outputs[:-1] + rl_outputs[:-1] + [online_counter]
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num_input.change(fn=update_all_on_tf_change, inputs=tf_change_inputs, outputs=tf_change_outputs)
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den_input.change(fn=update_all_on_tf_change, inputs=tf_change_inputs, outputs=tf_change_outputs)
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# ===== 新增：算例演示事件包装器 =====
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def run_case_demo_wrapper(sim_time, dt, initial_soc, initial_engine_power, profile, rpm_scale, load_scale, sid):
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update_user_activity(sid)
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fig, summary, table_data = run_case_demo(
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sim_time_s=sim_time,
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dt=dt,
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initial_soc_pct=initial_soc,
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initial_engine_power_kw=initial_engine_power,
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profile_name=profile,
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rpm_scale=rpm_scale,
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load_scale=load_scale
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)
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return fig, summary, table_data, get_online_status_html()
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# ===== 新增：算例演示按钮事件绑定 =====
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case_demo_ui["run_button"].click(
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fn=run_case_demo_wrapper,
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inputs=[
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case_demo_ui["sim_time"],
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case_demo_ui["dt"],
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case_demo_ui["initial_soc"],
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case_demo_ui["initial_engine_power"],
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case_demo_ui["profile"],
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case_demo_ui["rpm_scale"],
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case_demo_ui["load_scale"],
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session_id
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],
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outputs=[
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case_demo_ui["plot"],
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case_demo_ui["summary"],
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case_demo_ui["table"],
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online_counter
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]
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)
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# --- 聊天机器人事件 ---
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async def chat_wrapper(message, history, sid):
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update_user_activity(sid)
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# chat_with_ai 是一个生成器，Gradio可以直接处理
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async for response in chat_with_ai(message, history):
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yield response
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chatbot_ui["send_button"].click(
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fn=chat_wrapper,
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inputs=[chatbot_ui["chat_input"], chatbot_ui["chatbot"], session_id],
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outputs=chatbot_ui["chatbot"]
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).then(lambda: ("", get_online_status_html()), outputs=[chatbot_ui["chat_input"], online_counter])
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chatbot_ui["chat_input"].submit(
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fn=chat_wrapper,
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inputs=[chatbot_ui["chat_input"], chatbot_ui["chatbot"], session_id],
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outputs=chatbot_ui["chatbot"]
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).then(lambda: ("", get_online_status_html()), outputs=[chatbot_ui["chat_input"], online_counter])
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def clear_chat_wrapper(sid):
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update_user_activity(sid)
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return [], get_online_status_html()
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chatbot_ui["clear_button"].click(
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fn=clear_chat_wrapper,
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inputs=[session_id],
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outputs=[chatbot_ui["chatbot"], online_counter]
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)
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# --- 页面加载和定时器事件 ---
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def on_page_load(sid):
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update_user_activity(sid)
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return get_online_status_html()
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demo.load(fn=on_page_load, inputs=[session_id], outputs=[online_counter])
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gr.Timer(10).tick(fn=get_online_status_html, outputs=online_counter)
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if __name__ == "__main__":
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demo.queue().launch(
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server_name=config.SERVER_NAME,
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server_port=config.SERVER_PORT,
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share=config.SHARE
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)
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