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| import gradio as gr | |
| import spacy | |
| import torch | |
| from Main import Main | |
| from skill_recommender import skills_recommender | |
| from transformers import BertForTokenClassification | |
| #recommender = spacy.load("./model-best2") | |
| main = Main() | |
| def recommend(resume): | |
| summary = '' | |
| found = 0 | |
| doc = main.predict(resume) | |
| skills = [] | |
| for ent_list in doc: | |
| if(ent_list['entity'] == "Skills"): | |
| temp = ent_list['text'] | |
| temp = temp.split(',') | |
| skills = skills + temp | |
| sr = skills_recommender() | |
| recommendation = sr.suggest_skills(skills) | |
| return recommendation | |
| iface = gr.Interface(fn=recommend, inputs="text", outputs="text",title="Job Skills Recommender!",description="Get new skills recommendation based on your resume!") | |
| iface.launch() |