from keybert import KeyBERT
import re

kw_model = KeyBERT()

def classify_cv(text) -> str:
    technical_keywords = ['python', 'engineering', 'developer', 'AI', 'ML', 'software']
    non_technical_keywords = ['sales', 'management', 'HR', 'marketing', 'finance']
    tech_score = sum([text.lower().count(k) for k in technical_keywords])
    nontech_score = sum([text.lower().count(k) for k in non_technical_keywords])
    return "Technical" if tech_score >= nontech_score else "Non-Technical"

def get_skill_score(text) -> int:
    keywords = kw_model.extract_keywords(text, top_n=10)
    score = min(100, int(len(keywords) * 10))
    return score