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


num_generation = container_param.slider(
    label='Number of generation', min_value=1, max_value=100, value=5, step=1)
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_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':

#     # # , 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)
#     if container_button.button('Run'):
#         story_till_now, emotion = gen.story(
#             story_till_now, num_generation, length)
#         st.markdown(f'### Story')
#         st.text(story_till_now)
#         st.markdown(f'The last sentence has the "{emotion["label"]}" **Emotion** with a confidence score of {emotion["score"]}.')
#     else:
#         container_guide.markdown('### Write the first sentence and then hit the `Run` button')
# elif mode == 'Analyse Emotions':
#     container_mode.write('Let\'s play storytelling.')