xuanwsx/ErlangshenModel

1import os2from datetime import datetime3import pandas as pd4import matplotlib.pyplot as plt5import gradio as gr6from transformers import pipeline7 8DATA_FILE = "stress_data.csv"9 10if not os.path.exists(DATA_FILE):11    df = pd.DataFrame(columns=["date","score"])12    df.to_csv(DATA_FILE,index=False)13 14emotion_model = pipeline(15    "sentiment-analysis",16    model="IDEA-CCNL/Erlangshen-Roberta-110M-Sentiment"17)18 19stress_keywords = [20"焦慮","壓力","煩","崩潰","絕望","害怕","痛苦",21"失眠","難過","憂鬱","無助","失落","疲倦"22]23 24crisis_keywords = [25"不想活","活不下去","想死","絕望","沒有意義"26]27 28violence_keywords = [29"放火","殺人","報復","傷害"30]31 32def stress_level(score):33 34    if score < 30:35        return "低壓力"36    elif score < 60:37        return "中等壓力"38    elif score < 80:39        return "高壓力"40    else:41        return "非常高壓力"42 43def detect_source(text):44 45    if any(w in text for w in ["考試","成績","作業","報告"]):46        return "學業壓力"47 48    if any(w in text for w in ["朋友","同學","關係"]):49        return "人際壓力"50 51    if any(w in text for w in ["未來","人生","迷茫"]):52        return "未來焦慮"53 54    if any(w in text for w in ["失眠","睡不著"]):55        return "睡眠壓力"56 57    return "一般壓力"58 59advice = {60 61"學業壓力":{62"relief":"使用番茄鐘學習法，每40分鐘休息10分鐘",63"food":"增加B群食物：雞蛋、全穀類",64"life":"建立讀書計畫"65},66 67"人際壓力":{68"relief":"與信任的人聊聊",69"food":"Omega-3食物：魚類、堅果",70"life":"安排放鬆時間"71},72 73"未來焦慮":{74"relief":"寫下短期目標",75"food":"富含鎂食物：香蕉、菠菜",76"life":"每天運動30分鐘"77},78 79"睡眠壓力":{80"relief":"睡前冥想或深呼吸",81"food":"避免咖啡因",82"life":"睡前一小時不要滑手機"83},84 85"一般壓力":{86"relief":"散步或慢跑",87"food":"均衡飲食",88"life":"保持規律作息"89}90}91 92def analyze(text):93 94    result = emotion_model(text)[0]95 96    if result["label"] == "negative":97        ai_score = result["score"] * 10098    else:99        ai_score = (1-result["score"]) * 40100 101    kw_score = 0102 103    for w in stress_keywords:104        if w in text:105            kw_score += 8106 107    for w in crisis_keywords:108        if w in text:109            kw_score += 40110 111    for w in violence_keywords:112        if w in text:113            kw_score += 30114 115    total_score = min(ai_score*0.7 + kw_score*0.3 ,100)116 117    level = stress_level(total_score)118 119    source = detect_source(text)120 121    adv = advice[source]122 123    df = pd.read_csv(DATA_FILE)124 125    new = pd.DataFrame({126        "date":[datetime.now().strftime("%Y-%m-%d %H:%M")],127        "score":[total_score]128    })129 130    df = pd.concat([df,new],ignore_index=True)131 132    df.to_csv(DATA_FILE,index=False)133 134    fig, ax = plt.subplots()135 136    df["date"] = pd.to_datetime(df["date"])137 138    ax.plot(df["date"],df["score"],marker="o")139 140    ax.set_title("Stress Trend")141 142    fig.autofmt_xdate()143 144    avg = df["score"].mean()145 146    dashboard = f"""147目前壓力：{total_score:.1f}148平均壓力：{avg:.1f}149"""150 151    result_text = f"""152壓力分數：{total_score:.1f}153 154壓力等級：{level}155 156壓力來源：{source}157 158減壓方式：{adv['relief']}159 160飲食建議：{adv['food']}161 162生活建議：{adv['life']}163"""164 165    return result_text,dashboard,fig166 167interface = gr.Interface(168 169fn=analyze,170 171inputs=gr.Textbox(lines=4,label="輸入你的心情"),172 173outputs=[174gr.Textbox(label="分析結果"),175gr.Textbox(label="壓力儀表板"),176gr.Plot(label="壓力趨勢")177],178 179title="AI心理壓力分析系統"180 181)182 183interface.launch()