app.py

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.')