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import streamlit as st |
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from transformers import AutoTokenizer, TFAutoModelForCausalLM, TFAutoModelForSequenceClassification |
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generator_name = "Alirani/distilgpt2-finetuned-synopsis-genres_final" |
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tokenizer_gen = AutoTokenizer.from_pretrained(generator_name) |
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model_gen = TFAutoModelForCausalLM.from_pretrained(generator_name) |
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classifier_name = "Alirani/overview_classifier_final" |
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tokenizer_clf = AutoTokenizer.from_pretrained(classifier_name) |
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model_clf = TFAutoModelForSequenceClassification.from_pretrained(classifier_name) |
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def generate_synopsis(model, tokenizer, title): |
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input_ids = tokenizer(title, return_tensors="tf") |
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output = model.generate(input_ids['input_ids'], max_length=150, num_beams=5, no_repeat_ngram_size=2, top_k=50, attention_mask=input_ids['attention_mask']) |
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synopsis = tokenizer.decode(output[0], skip_special_tokens=True) |
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processed_synopsis = "".join(synopsis.split('|')[2].rpartition('.')[:2]).strip() |
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return processed_synopsis |
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def generate_classification(model, tokenizer, title, overview): |
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tokens = tokenizer(f"{title} | {overview}", padding=True, truncation=True, return_tensors="tf") |
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output = model(**tokens) |
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return output |
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favicon = "https://i.ibb.co/JRdhFZg/favicon-32x32.png" |
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st.set_page_config(page_title="LoreFinder-demo", page_icon = favicon, layout = 'wide', initial_sidebar_state = 'auto') |
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st.title('Demo LoreFinder') |
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st.header('Generate a story') |
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prod_title = st.text_input('Type a title to generate a synopsis') |
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prod_synopsis = st.text_input('Type a synopsis to guess the genre') |
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option_genres = st.selectbox( |
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'Select a genre to tailor your synopsis', |
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('Family', 'Romance', 'Comedy', 'Action', 'Documentary', 'Adventure', 'Drama', 'Mystery', 'Crime', 'Thriller', 'Science Fiction', 'History', 'Music', 'Western', 'Fantasy', 'TV Movie', 'Horror', 'Animation', 'Reality'), |
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index=None, |
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placeholder="Select genres..." |
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) |
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button_synopsis = st.button('Get synopsis') |
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button_genres = st.button('Get genres') |
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if button_synopsis: |
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if len(prod_title.split(' ')) > 0: |
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gen_synopsis = generate_synopsis(model_gen, tokenizer_gen, f"{prod_title} | {option_genres} | ") |
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st.text_area('Generated synopsis', value=gen_synopsis, disabled=True) |
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else: |
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st.write('Write a title for the generator to work !') |
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if button_genres: |
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if len(prod_title.split(' ')) > 0: |
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classifier_output = generate_classification(model_clf, tokenizer_clf, prod_title, prod_synopsis) |
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print(classifier_output) |
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st.write(f"Guessed genre : {classifier_output}") |
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else: |
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st.write('Write a title and a synopsis for the classifier to work !') |
