我部署的flask应用程序中出现错误，显示500个内部服务器错误

Question

我制作了一个可以诊断疾病的python flask应用程序 该应用程序在本地运行良好，但通过Heroku部署时，我得到了500个内部错误。我知道该错误的含义，但我无法在我的应用程序中找到错误，因此，我相信通过StackOverflow可以找到它

从sk学习输入svm 从sk学习导入预处理 从sklearn.model\u选择导入列车\u测试\u拆分 从烧瓶进口烧瓶 进口泡菜 将numpy作为np导入 作为pd进口熊猫 导入操作系统

app = Flask(__name__)


@app.route('/hello')
def home():
    return 'hello'


@app.route('/rf/<sym1>/<sym2>/<sym3>/<sym4>/<sym5>')
def predict(sym1, sym2, sym3, sym4, sym5):




    l1=['back pain','constipation','abdominal pain','diarrhoea','mild fever','yellow urine',
    'yellowing of eyes','acute liver failure','fluid overload','swelling of stomach',
    'swelled lymph nodes','malaise','blurred and distorted vision','phlegm','throat irritation',
    'redness of eyes','sinus pressure','runny nose','congestion','chest pain','weakness in limbs',
    'fast heart rate','pain during bowel movements','pain in anal region','bloody stool',
    'irritation in anus','neck pain','dizziness','cramps','bruising','obesity','swollen legs',
    'swollen blood vessels','puffy face and eyes','enlarged thyroid','brittle nails',
    'swollen extremeties','excessive hunger','extra marital contacts','drying and tingling lips',
    'slurred speech','knee pain','hip joint pain','muscle weakness','stiff neck','swelling joints',
    'movement stiffness','spinning movements','loss of balance','unsteadiness',
    'weakness of one body side','loss of smell','bladder discomfort','foul smell of urine',
    'continuous feel of urine','passage of gases','internal itching','toxic look (typhos)',
    'depression','irritability','muscle pain','altered sensorium','red spots over body','belly pain',
    'abnormal menstruation','dischromic  patches','watering from eyes','increased 
appetite','polyuria','family history','mucoid sputum',
    'rusty sputum','lack of concentration','visual disturbances','receiving blood transfusion',
    'receiving unsterile injections','coma','stomach bleeding','distention of abdomen',
    'history of alcohol consumption','fluid overload','blood in sputum','prominent veins on calf',
    'palpitations','painful walking','pus filled pimples','blackheads','scurring','skin peeling',
    'silver like dusting','small dents in nails','inflammatory nails','blister','red sore around nose',
    'yellow crust ooze']

     disease=['Fungal infection','Allergy','GERD','Chronic cholestasis','Drug Reaction',
    'Peptic ulcer diseae','AIDS','Diabetes','Gastroenteritis','Bronchial Asthma','Hypertension',
    'Migraine','Cervical spondylosis',
    'Paralysis (brain hemorrhage)','Jaundice','Malaria','Chicken pox','Dengue','Typhoid','hepatitis A',
    'Hepatitis B','Hepatitis C','Hepatitis D','Hepatitis E','Alcoholic hepatitis','Tuberculosis',
    'Common Cold','Pneumonia','Dimorphic hemmorhoids(piles)',
    'Heartattack','Varicoseveins','Hypothyroidism','Hyperthyroidism','Hypoglycemia','Osteoarthristis',
    'Arthritis','(vertigo) Paroymsal  Positional Vertigo','Acne','Urinary tract infection','Psoriasis',
    'Impetigo']

    l2=[]
    for x in range(0,len(l1)):
        l2.append(0)


    from sklearn.ensemble import RandomForestClassifier
    clf3 = RandomForestClassifier()
    clf3 = clf3.fit(X,np.ravel(y))
    #filename = 'model.sav'
    #pickle.dump(clf3, open(filename, 'wb'))
    model = 
    pickle.load(open(os.path.abspath(os.path.dirname(__file__).replace("",""))+"/asset/model.sav", "rb"))
    print("model loaded")

# calculating accuracy-------------------------------------------------------------------
#from sklearn.metrics import accuracy_score
#y_pred=clf3.predict(X_test)
#print(accuracy_score(y_test, y_pred))
#print(accuracy_score(y_test, y_pred,normalize=False))
# -----------------------------------------------------
    Symptom1 = '%s' % sym1

    Symptom2 = '%s' % sym2

    Symptom3 = '%s' % sym3

    Symptom4 = '%s' % sym4

    Symptom5 = '%s' % sym5


    psymptoms = [Symptom1,Symptom2,Symptom3,Symptom4,Symptom5]

    for k in range(0,len(l1)):
    # print (k,)
        for z in psymptoms:
            if(z==l1[k]):
                l2[k]=1

    inputtest = [l2]
    predict = model.predict(inputtest)
    predicted=predict[0]
    #print(predicted)
    #assigning a string value to "a"
    for a in range(0,len(disease)):
        if(predicted == a):
            break
   
    return disease[a]#returning the disease

if __name__ == '__main__':
app.run(debug=True)

如果你看到一些缩进错误，那不是问题所在，因为当我复制粘贴到网站上时，它可能错误地缩进了

此外，URL directing“/hello”工作正常，这表明我的predict函数有错误

如果你能回答，那就太好了

问候,， 罗山