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| import streamlit as st | |
| from src.story_gen import StoryGenerator | |
| from src.probability_emote import run_pe | |
| import plotly.express as px | |
| import random | |
| import numpy as np | |
| st.set_page_config(page_title='Storytelling ' + | |
| u'\U0001F5BC', page_icon=u'\U0001F5BC', layout="wide") | |
| gen = StoryGenerator() | |
| container_mode = st.sidebar.container() | |
| container_guide = st.container() | |
| container_param = st.sidebar.container() | |
| container_button = st.sidebar.container() | |
| mode = container_mode.radio( | |
| "Select a mode", | |
| ('Probability Emote', 'Create Statistics', 'Play Storytelling'), index=0) | |
| def initialise_storytelling(): | |
| choices_first_sentence = [ | |
| 'Custom', | |
| 'Hello, I\'m a language model,', | |
| 'So I suppose you want to ask me how I did it.', | |
| 'I always wanted to be a giraffe - until that night.', | |
| 'My first tutor was a dragon with a terrible sense of humor.', | |
| 'Doctors told her she could never diet again.', | |
| 'Memory is all around us, as well as within.', | |
| ] | |
| cfs = st.selectbox('Choose First Sentence', choices_first_sentence) | |
| if cfs == 'Custom': | |
| story_till_now = st.text_input( | |
| label='First Sentence', key='first_sentence') | |
| else: | |
| st.session_state.first_sentence = cfs | |
| story_till_now = cfs | |
| first_sentence = story_till_now | |
| first_emotion = gen.get_emotion(first_sentence) | |
| length = container_param.slider(label='Length of the generated sentence', | |
| min_value=1, max_value=100, value=10, step=1) | |
| return first_sentence, first_emotion, length | |
| if mode == 'Create Statistics': | |
| first_sentence, first_emotion, length = initialise_storytelling() | |
| # story_till_now = first_sentence | |
| num_generation = container_param.slider( | |
| label='Number of generation', min_value=1, max_value=100, value=5, step=1) | |
| num_tests = container_param.slider( | |
| label='Number of tests', min_value=1, max_value=1000, value=3, step=1) | |
| reaction_weight_mode = container_param.select_slider( | |
| "Reaction Weight w:", ["Random", "Fixed"]) | |
| if reaction_weight_mode == "Fixed": | |
| reaction_weight = container_param.slider( | |
| label='Reaction Weight w', min_value=0.0, max_value=1.0, value=0.5, step=0.01) | |
| elif reaction_weight_mode == "Random": | |
| reaction_weight = -1 | |
| if container_button.button('Analyse'): | |
| gen.get_stats(story_till_now=first_sentence, | |
| num_generation=num_generation, length=length, reaction_weight=reaction_weight, num_tests=num_tests) | |
| # if len(gen.stories) > 0: | |
| # for si, story in enumerate(gen.stories): | |
| # st.markdown(f'### Story no. {si}:', unsafe_allow_html=False) | |
| # st.markdown(story, unsafe_allow_html=False) | |
| # data=gen.stats_df[gen.stats_df.sentence_no==3] | |
| # fig = px.violin(data_frame=data, x="reaction_weight", y="num_reactions", hover_data=data.columns) | |
| # st.plotly_chart(fig, use_container_width=True) | |
| # fig2 = px.box(data_frame=data, x="reaction_weight", y="num_reactions", hover_data=data.columns) | |
| # st.plotly_chart(fig2, use_container_width=True) | |
| if len(gen.data) > 0: | |
| for si, story in enumerate(gen.data): | |
| st.markdown(f'### Story {si}:', unsafe_allow_html=False) | |
| for i, sentence in enumerate(story): | |
| col_turn, col_sentence, col_emo = st.columns([1, 8, 2]) | |
| col_turn.markdown( | |
| sentence['turn'], unsafe_allow_html=False) | |
| col_sentence.markdown( | |
| sentence['sentence'], unsafe_allow_html=False) | |
| col_emo.markdown( | |
| f'{sentence["emotion"]} {np.round(sentence["confidence_score"], 3)}', unsafe_allow_html=False) | |
| st.table(data=gen.stats_df, ) | |
| data = gen.stats_df[gen.stats_df.sentence_no == 3] | |
| fig = px.violin(data_frame=data, x="reaction_weight", | |
| y="num_reactions", hover_data=data.columns) | |
| st.plotly_chart(fig, use_container_width=True) | |
| fig2 = px.box(data_frame=data, x="reaction_weight", | |
| y="num_reactions", hover_data=data.columns) | |
| st.plotly_chart(fig2, use_container_width=True) | |
| else: | |
| container_guide.markdown( | |
| '### You selected statistics. Now set your parameters and click the `Analyse` button.') | |
| elif mode == 'Play Storytelling': | |
| first_sentence, first_emotion, length = initialise_storytelling() | |
| # story_till_now = first_sentence | |
| if 'sentence_list' not in st.session_state: | |
| st.session_state.sentence_list = [{'sentence': first_sentence, | |
| 'emotion': first_emotion['label'], | |
| 'score': first_emotion['score']}] | |
| if 'full_story' not in st.session_state: | |
| st.session_state.full_story = first_sentence | |
| container_button = container_button.columns([1, 1, 1]) | |
| heading_container = st.container() | |
| col_turn, col_sentence, col_emo = st.columns([1, 8, 2]) | |
| if container_button[0].button('Run'): | |
| heading_container.markdown(f'### Story') | |
| # st.text(story_till_now) | |
| full_story, emotion, new_sentence = gen.next_sentence( | |
| st.session_state.full_story, length) | |
| st.session_state.full_story = full_story | |
| st.session_state.sentence_list.append({ | |
| 'sentence': new_sentence, | |
| 'emotion': emotion["label"], | |
| 'score': emotion["score"]}) | |
| # col_sentence.markdown(st.session_state.sentence_list) | |
| for step in st.session_state.sentence_list: | |
| col_turn, col_sentence, col_emo = st.columns([1, 8, 2]) | |
| col_sentence.markdown(step['sentence']) | |
| col_emo.markdown( | |
| f'{step["emotion"]} {np.round(step["score"], 3)}', unsafe_allow_html=False) | |
| else: | |
| step = st.session_state.sentence_list[0] | |
| # col_sentence.markdown(step['sentence']) | |
| # col_emo.markdown( | |
| # f'{step["emotion"]} {np.round(step["score"], 3)}', unsafe_allow_html=False) | |
| container_guide.markdown( | |
| '### Write the first sentence and then hit the `Run` button') | |
| if container_button[2].button('Clear'): | |
| st.session_state.full_story = first_sentence | |
| st.session_state.sentence_list = [{'sentence': first_sentence, | |
| 'emotion': first_emotion['label'], | |
| 'score': first_emotion['score']}] | |
| elif mode == 'Probability Emote': | |
| # container_mode.write('Let\'s play storytelling.') | |
| run_pe(container_param) | |