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  1. app.py +57 -0
  2. requirements.txt +2 -0
app.py ADDED
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+ import streamlit as st
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+ import torch
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+ from transformers import BartForConditionalGeneration, BartTokenizer
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+
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+ # initialize model + tok variables
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+ model = None
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+ tok = None
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+
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+ # Examples for each models
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+ examples = [
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+ ["interview-question-remake", "I have a cat named dolche and he's not very friendly with strangers. I've had him for 9 years now and it has been a pleasure to see him grow closer to us every year."],
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+ ["interview-length-tagged","Today's weather was really nice."],
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+ ["reverse-interview-question", "There are so many incredible musicians out there and so many really compelling big hits this year that it makes for a really interesting way to recap some of those big events."]
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+ ]
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+
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+ # Descriptions for each models
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+ # descriptions = "Interview question remake is a model that..."
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+
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+ # pass in Strings of model choice and input text for context
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+ def genQuestion(model_choice, context):
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+ # global descriptions
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+ if model_choice=="interview-question-remake":
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+ model = BartForConditionalGeneration.from_pretrained("hyechanjun/interview-question-remake")
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+ tok = BartTokenizer.from_pretrained("hyechanjun/interview-question-remake")
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+ # descriptions = "Interview question remake is a model that..."
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+ elif model_choice=="interview-length-tagged":
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+ model = BartForConditionalGeneration.from_pretrained("hyechanjun/interview-length-tagged")
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+ tok = BartTokenizer.from_pretrained("hyechanjun/interview-length-tagged")
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+ # descriptions = "Interview question tagged is a model that..."
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+ elif model_choice=="reverse-interview-question":
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+ model = BartForConditionalGeneration.from_pretrained("hyechanjun/reverse-interview-question")
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+ tok = BartTokenizer.from_pretrained("hyechanjun/reverse-interview-question")
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+ # descriptions = "Reverse interview question is a model that..."
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+
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+ inputs = tok(context, return_tensors="pt")
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+ output = model.generate(inputs["input_ids"], num_beams=4, max_length=64, min_length=9, num_return_sequences=4, diversity_penalty =1.0, num_beam_groups=4)
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+ final_output = ''
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+
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+ for i in range(4):
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+ final_output += [tok.decode(beam, skip_special_tokens=True, clean_up_tokenization_spaces=False) for beam in output][i] + "\n"
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+
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+ return final_output
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+
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+
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+
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+ # Title
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+ st.title("Interview AI Test Website")
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+
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+ # Input field
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+ input = st.text_input('Context')
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+
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+ option = st.selectbox(
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+ 'Please select a model.',
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+ ('interview-question-remake', 'interview-length-tagged', 'reverse-interview-question'))
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+
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+ if st.button('Submit'):
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+ genQuestion(option, input)
requirements.txt ADDED
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+ transformers
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+ torch