419 lines
18 KiB
Python
419 lines
18 KiB
Python
import os
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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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# ===== 算例演示模块函数导入（四阶段设计）=====
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from case_demo_functions import run_distillation_demo, run_gpr_training, run_engine_design, run_motor_design, run_hybrid_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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# ===== 系统资源监控 =====
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def get_system_monitor_html():
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"""获取 CPU / 内存 / GPU 使用率的 HTML 小组件"""
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try:
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import psutil
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cpu_pct = psutil.cpu_percent(interval=0)
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mem = psutil.virtual_memory()
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mem_pct = mem.percent
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mem_used_gb = mem.used / (1024 ** 3)
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mem_total_gb = mem.total / (1024 ** 3)
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except ImportError:
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return "<div style='text-align:center;color:#999;font-size:0.8em;'>psutil 未安装，无法监控系统资源</div>"
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# GPU 信息 — 优先用 nvidia-smi（不依赖 PyTorch CUDA 版本），再用 torch.cuda 兜底
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gpu_html = ""
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try:
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import subprocess as _sp
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_r = _sp.run(
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['nvidia-smi', '--query-gpu=name,memory.used,memory.total,utilization.gpu',
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'--format=csv,noheader,nounits'],
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capture_output=True, text=True, timeout=3
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)
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if _r.returncode == 0 and _r.stdout.strip():
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_parts = [p.strip() for p in _r.stdout.strip().split('\n')[0].split(',')]
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_gpu_mem_used = float(_parts[1]) / 1024 # MiB → GiB
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_gpu_mem_total = float(_parts[2]) / 1024
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_gpu_util = float(_parts[3])
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_gc = '#ff6b6b' if _gpu_util > 80 else '#ffd93d' if _gpu_util > 50 else '#6bcb77'
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gpu_html = (
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f"<div style='display:inline-flex;align-items:center;gap:6px;'>"
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f"<span>🎮 GPU</span>"
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f"<div style='width:90px;height:8px;background:#444;border-radius:4px;overflow:hidden;'>"
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f"<div style='width:{min(_gpu_util, 100):.0f}%;height:100%;background:{_gc};'></div>"
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f"</div>"
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f"<span>{_gpu_util:.0f}% {_gpu_mem_used:.1f}/{_gpu_mem_total:.0f} GB</span>"
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f"</div>"
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)
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else:
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raise RuntimeError("nvidia-smi no output")
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except Exception:
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try:
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import torch as _torch
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if _torch.cuda.is_available():
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_mem_alloc = _torch.cuda.memory_allocated(0) / (1024 ** 3)
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_mem_total = _torch.cuda.get_device_properties(0).total_memory / (1024 ** 3)
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_util = _mem_alloc / max(_mem_total, 0.01) * 100
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_gc = '#ff6b6b' if _util > 80 else '#ffd93d' if _util > 50 else '#6bcb77'
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gpu_html = (
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f"<div style='display:inline-flex;align-items:center;gap:6px;'>"
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f"<span>🎮 GPU</span>"
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f"<div style='width:90px;height:8px;background:#444;border-radius:4px;overflow:hidden;'>"
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f"<div style='width:{min(_util, 100):.0f}%;height:100%;background:{_gc};'></div>"
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f"</div>"
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f"<span>{_mem_alloc:.1f}/{_mem_total:.0f} GB</span>"
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f"</div>"
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)
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else:
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gpu_html = "<div style='display:inline-flex;align-items:center;gap:4px;'><span>🎮 GPU N/A</span></div>"
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except Exception:
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gpu_html = "<div style='display:inline-flex;align-items:center;gap:4px;'><span>🎮 GPU N/A</span></div>"
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cpu_color = '#ff6b6b' if cpu_pct > 80 else '#ffd93d' if cpu_pct > 50 else '#6bcb77'
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mem_color = '#ff6b6b' if mem_pct > 80 else '#ffd93d' if mem_pct > 50 else '#6bcb77'
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html = (
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f"<div style='display:flex;justify-content:center;gap:20px;flex-wrap:wrap;"
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f"font-size:0.82em;color:#ddd;padding:4px 10px;'>"
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# CPU
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f"<div style='display:inline-flex;align-items:center;gap:6px;'>"
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f"<span>🖥️ CPU</span>"
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f"<div style='width:90px;height:8px;background:#444;border-radius:4px;overflow:hidden;'>"
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f"<div style='width:{min(cpu_pct, 100):.0f}%;height:100%;background:{cpu_color};'></div>"
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f"</div>"
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f"<span>{cpu_pct:.0f}%</span>"
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f"</div>"
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# Memory
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f"<div style='display:inline-flex;align-items:center;gap:6px;'>"
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f"<span>💾 RAM</span>"
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f"<div style='width:90px;height:8px;background:#444;border-radius:4px;overflow:hidden;'>"
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f"<div style='width:{min(mem_pct, 100):.0f}%;height:100%;background:{mem_color};'></div>"
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f"</div>"
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f"<span>{mem_used_gb:.1f}/{mem_total_gb:.0f} GB ({mem_pct:.0f}%)</span>"
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f"</div>"
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# GPU
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f"{gpu_html}"
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f"</div>"
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)
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return html
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# 加载外部CSS文件
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with open(os.path.join(os.path.dirname(__file__), "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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# 系统资源监控（始终可见）
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system_monitor = gr.HTML(value=get_system_monitor_html, elem_id="system-monitor")
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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=[time_domain_ui["num_input"], time_domain_ui["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=[time_domain_ui["num_input"], time_domain_ui["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 = [freq_domain_ui["num_input"], freq_domain_ui["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"], root_locus_ui["num_input"], root_locus_ui["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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# 频域：当传递函数输入框变化时自动更新
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freq_domain_ui["num_input"].change(
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fn=update_frequency_analysis_wrapper,
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inputs=freq_inputs, outputs=freq_outputs
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)
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freq_domain_ui["den_input"].change(
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fn=update_frequency_analysis_wrapper,
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inputs=freq_inputs, outputs=freq_outputs
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)
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# 根轨迹：当传递函数输入框变化时自动更新
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root_locus_ui["num_input"].change(
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fn=update_rl_view_wrapper,
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inputs=rl_inputs, outputs=rl_outputs
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)
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root_locus_ui["den_input"].change(
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fn=update_rl_view_wrapper,
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inputs=rl_inputs, outputs=rl_outputs
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)
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# ===== 算例演示事件绑定（四阶段）=====
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# --- 阶段零-A：GPR 模型训练 ---
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def run_gpr_wrapper(mode, sid, progress=gr.Progress(track_tqdm=True)):
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update_user_activity(sid)
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fig, summary = run_gpr_training(mode=mode, progress=progress)
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return fig, summary, get_online_status_html()
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case_demo_ui["gpr_run_button"].click(
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fn=run_gpr_wrapper,
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inputs=[case_demo_ui["gpr_mode"], session_id],
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outputs=[case_demo_ui["gpr_plot"], case_demo_ui["gpr_summary"], online_counter]
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)
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# --- 阶段零-B：NN 模型训练（蒸馏）---
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def run_distillation_wrapper(epochs, lr, hidden, sid, progress=gr.Progress(track_tqdm=True)):
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update_user_activity(sid)
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fig, summary = run_distillation_demo(epochs, lr, hidden, progress=progress)
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return fig, summary, get_online_status_html()
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case_demo_ui["distill_run_button"].click(
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fn=run_distillation_wrapper,
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inputs=[
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case_demo_ui["distill_epochs"], case_demo_ui["distill_lr"],
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case_demo_ui["distill_hidden"],
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session_id
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],
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outputs=[case_demo_ui["distill_plot"], case_demo_ui["distill_summary"], online_counter]
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)
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# --- 阶段一：发动机控制器设计 ---
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def run_engine_design_wrapper(sim_time, dt, init_power, target_power,
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controller_type,
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kp, ki, kd, tau_fuel, K_inertia,
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mpc_horizon, mpc_W_power, mpc_W_dcost, mpc_overshoot,
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sid, progress=gr.Progress(track_tqdm=True)):
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update_user_activity(sid)
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fig, summary = run_engine_design(
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sim_time, dt, init_power, target_power,
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controller_type,
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kp, ki, kd, tau_fuel, K_inertia,
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mpc_horizon, mpc_W_power, mpc_W_dcost, mpc_overshoot / 100.0,
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progress=progress
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)
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return fig, summary, get_online_status_html()
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case_demo_ui["eng_run_button"].click(
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fn=run_engine_design_wrapper,
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inputs=[
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case_demo_ui["eng_sim_time"], case_demo_ui["eng_dt"],
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case_demo_ui["eng_init_power"], case_demo_ui["eng_target_power"],
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case_demo_ui["eng_controller_type"],
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case_demo_ui["eng_kp"], case_demo_ui["eng_ki"], case_demo_ui["eng_kd"],
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case_demo_ui["eng_tau_fuel"], case_demo_ui["eng_K_inertia"],
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case_demo_ui["eng_mpc_horizon"], case_demo_ui["eng_mpc_W_power"],
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case_demo_ui["eng_mpc_W_dcost"], case_demo_ui["eng_mpc_overshoot"],
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session_id
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],
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outputs=[case_demo_ui["eng_plot"], case_demo_ui["eng_summary"], online_counter]
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)
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# --- 阶段二：电机控制器设计 ---
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def run_motor_design_wrapper(sim_time, dt, target_rpm, load_torque,
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controller_type,
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kp, ki, kd, J,
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mpc_W_speed, mpc_W_dcost, mpc_overshoot,
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sid, progress=gr.Progress(track_tqdm=True)):
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update_user_activity(sid)
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fig, summary = run_motor_design(
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sim_time, dt, target_rpm, load_torque,
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controller_type,
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kp, ki, kd, J,
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mpc_W_speed, mpc_W_dcost, mpc_overshoot / 100.0,
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progress=progress
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)
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return fig, summary, get_online_status_html()
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case_demo_ui["mot_run_button"].click(
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fn=run_motor_design_wrapper,
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inputs=[
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case_demo_ui["mot_sim_time"], case_demo_ui["mot_dt"],
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case_demo_ui["mot_target_rpm"], case_demo_ui["mot_load_torque"],
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case_demo_ui["mot_controller_type"],
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case_demo_ui["mot_kp"], case_demo_ui["mot_ki"], case_demo_ui["mot_kd"],
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case_demo_ui["mot_J"],
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case_demo_ui["mot_mpc_W_speed"], case_demo_ui["mot_mpc_W_dcost"],
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case_demo_ui["mot_mpc_overshoot"],
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session_id
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],
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outputs=[case_demo_ui["mot_plot"], case_demo_ui["mot_summary"], online_counter]
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)
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# --- 阶段三：能量管理策略设计（自动引用前两阶段控制器参数）---
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def run_hybrid_demo_wrapper(sim_time, dt, initial_soc, initial_engine_power,
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profile,
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eng_ctrl_type, eng_kp, eng_ki, eng_kd,
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eng_mpc_horizon, eng_mpc_W_power, eng_mpc_W_dcost, eng_mpc_overshoot,
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mot_ctrl_type, mot_kp, mot_ki, mot_kd, mot_J,
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mot_mpc_W_speed, mot_mpc_W_dcost, mot_mpc_overshoot,
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soc_target, soc_low, soc_high,
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p_eng_min, p_eng_max, p_charge, k_soc,
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power_reserve, battery_capacity, sid,
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progress=gr.Progress(track_tqdm=True)):
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update_user_activity(sid)
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fig, summary, table_data = run_hybrid_demo(
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sim_time, dt, initial_soc, initial_engine_power, profile,
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eng_ctrl_type, eng_kp, eng_ki, eng_kd,
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eng_mpc_horizon, eng_mpc_W_power, eng_mpc_W_dcost, eng_mpc_overshoot / 100.0,
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mot_ctrl_type, mot_kp, mot_ki, mot_kd, mot_J,
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mot_mpc_W_speed, mot_mpc_W_dcost, mot_mpc_overshoot / 100.0,
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soc_target, soc_low, soc_high,
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p_eng_min, p_eng_max, p_charge, k_soc,
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power_reserve, battery_capacity,
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progress=progress
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)
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return fig, summary, table_data, get_online_status_html()
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case_demo_ui["hybrid_run_button"].click(
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fn=run_hybrid_demo_wrapper,
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inputs=[
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case_demo_ui["sim_time"], case_demo_ui["dt"],
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case_demo_ui["initial_soc"], case_demo_ui["initial_engine_power"],
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case_demo_ui["profile"],
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# 发动机控制器参数
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case_demo_ui["eng_controller_type"],
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case_demo_ui["eng_kp"], case_demo_ui["eng_ki"], case_demo_ui["eng_kd"],
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case_demo_ui["eng_mpc_horizon"], case_demo_ui["eng_mpc_W_power"],
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case_demo_ui["eng_mpc_W_dcost"], case_demo_ui["eng_mpc_overshoot"],
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# 电机控制器参数
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case_demo_ui["mot_controller_type"],
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case_demo_ui["mot_kp"], case_demo_ui["mot_ki"], case_demo_ui["mot_kd"],
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case_demo_ui["mot_J"],
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case_demo_ui["mot_mpc_W_speed"], case_demo_ui["mot_mpc_W_dcost"],
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case_demo_ui["mot_mpc_overshoot"],
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# 能量管理策略参数
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case_demo_ui["soc_target"], case_demo_ui["soc_low"], case_demo_ui["soc_high"],
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case_demo_ui["p_eng_min"], case_demo_ui["p_eng_max"],
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case_demo_ui["p_charge"], case_demo_ui["k_soc"],
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case_demo_ui["power_reserve"], case_demo_ui["battery_capacity"],
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session_id
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],
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outputs=[
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case_demo_ui["hybrid_plot"], case_demo_ui["hybrid_summary"],
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case_demo_ui["hybrid_table"], 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(
|
||
fn=chat_wrapper,
|
||
inputs=[chatbot_ui["chat_input"], chatbot_ui["chatbot"], session_id],
|
||
outputs=chatbot_ui["chatbot"]
|
||
).then(lambda: ("", get_online_status_html()), outputs=[chatbot_ui["chat_input"], online_counter])
|
||
|
||
chatbot_ui["chat_input"].submit(
|
||
fn=chat_wrapper,
|
||
inputs=[chatbot_ui["chat_input"], chatbot_ui["chatbot"], session_id],
|
||
outputs=chatbot_ui["chatbot"]
|
||
).then(lambda: ("", get_online_status_html()), outputs=[chatbot_ui["chat_input"], online_counter])
|
||
|
||
def clear_chat_wrapper(sid):
|
||
update_user_activity(sid)
|
||
return [], get_online_status_html()
|
||
|
||
chatbot_ui["clear_button"].click(
|
||
fn=clear_chat_wrapper,
|
||
inputs=[session_id],
|
||
outputs=[chatbot_ui["chatbot"], online_counter]
|
||
)
|
||
|
||
# --- 页面加载和定时器事件 ---
|
||
demo.load(fn=lambda: get_online_status_html(), outputs=[online_counter])
|
||
|
||
gr.Timer(10).tick(fn=get_online_status_html, outputs=online_counter)
|
||
|
||
# 系统资源监控定时刷新（每 3 秒）
|
||
gr.Timer(3).tick(fn=get_system_monitor_html, outputs=system_monitor)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
demo.queue().launch(
|
||
server_name=config.SERVER_NAME,
|
||
server_port=config.SERVER_PORT,
|
||
share=config.SHARE
|
||
)
|