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import streamlit as st | |
from story_gen import StoryGenerator | |
import plotly.figure_factory as ff | |
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.sidebar.container() | |
container_param = st.sidebar.container() | |
container_button = st.sidebar.container() | |
mode = container_mode.radio( | |
"Select your mode", | |
('Create Statistics', 'Play Storytelling'), index=0) | |
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) | |
if mode == 'Create Statistics': | |
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=story_till_now, | |
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': | |
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 = story_till_now | |
# # , placeholder="Start writing your story...") | |
# story_till_now = st.text_input( | |
# label='First Sentence', value='Hello, I\'m a language model,') | |
# num_generation = st.sidebar.slider( | |
# label='Number of generation', min_value=1, max_value=100, value=10, step=1) | |
# length = st.sidebar.slider(label='Length of the generated sentence', | |
# min_value=1, max_value=100, value=20, step=1) | |
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 = story_till_now | |
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_sentence.markdown(step['sentence']) | |
col_emo.markdown( | |
f'{step["emotion"]} {np.round(step["score"], 3)}', unsafe_allow_html=False) | |
# i=0 | |
# while True: | |
# story_till_now, emotion, new_sentence = gen.next_sentence( | |
# story_till_now, length) | |
# col_sentence.text(new_sentence) | |
# col_emo.markdown(f'{emotion["label"]} {np.round(emotion["score"], 3)}', unsafe_allow_html=False) | |
# # col_emo.markdown(f'The last sentence has the "{emotion["label"]}" **Emotion** with a confidence score of {emotion["score"]}.') | |
# new_input_sentence = st.text_input(label='Next Sentence', key=f'next_sentence_{i}') | |
# story_till_now += ' ' + new_input_sentence | |
# i+=1 | |
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) | |
st.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 == 'Analyse Emotions': | |
# container_mode.write('Let\'s play storytelling.') | |