from classifier import get_training_threads,  print_answers, in_training, store_training_data, get_pipe
from storage import db_session, MailThread

def predict_threads():
    pipe1,le=get_pipe("pipe1",b"answered",["db"])
    pipe2,le2=get_pipe("pipe2g", b"maintopic",["db"])
    pipe3,le3=get_pipe("pipe2b", b"lang",["db"])
    q=db_session.query(MailThread).filter(MailThread.istrained.op("IS NOT")(True))
    mail_threads=q.all()
    if len(mail_threads) ==0:
        raise ValueError("no untrained threads found")
    answered=le.inverse_transform(pipe1.predict(mail_threads))
    maintopic=le2.inverse_transform(pipe2.predict(mail_threads))
    lang=le3.inverse_transform(pipe3.predict(mail_threads))

    for i, t in enumerate(mail_threads):
        t.answered=bool(answered[i])
        t.opened=bool(answered[i])
        t.maintopic=str(maintopic[i])
        t.lang=str(lang[i])
        db_session.add(t)
        db_session.commit()