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import streamlit as st
import numpy as np
import pandas as pd
# import plotly.express as px
# from plotly.subplots import make_subplots
import json
# Reference: https://huggingface.co/spaces/team-zero-shot-nli/zero-shot-nli/blob/main/utils.py
# def plot_result(top_topics, scores):
# top_topics = np.array(top_topics)
# scores = np.array(scores)
# scores *= 100
# fig = px.bar(x=np.around(scores,2), y=top_topics, orientation='h',
# labels={'x': 'Confidence Score', 'y': 'Label'},
# text=scores,
# range_x=(0,115),
# title='Predictions',
# color=np.linspace(0,1,len(scores)),
# color_continuous_scale='GnBu')
# fig.update(layout_coloraxis_showscale=False)
# fig.update_traces(texttemplate='%{text:0.1f}%', textposition='outside')
# st.plotly_chart(fig)
# def plot_dual_bar_chart(topics_summary, scores_summary, topics_text, scores_text):
# data1 = pd.DataFrame({'label': topics_summary, 'scores on summary': scores_summary})
# data2 = pd.DataFrame({'label': topics_text, 'scores on full text': scores_text})
# data = pd.merge(data1, data2, on = ['label'])
# data.sort_values('scores on summary', ascending = True, inplace = True)
# fig = make_subplots(rows=1, cols=2,
# subplot_titles=("Predictions on Summary", "Predictions on Full Text"),
# )
# fig1 = px.bar(x=round(data['scores on summary']*100, 2), y=data['label'], orientation='h',
# text=round(data['scores on summary']*100, 2),
# )
# fig2 = px.bar(x=round(data['scores on full text']*100,2), y=data['label'], orientation='h',
# text=round(data['scores on full text']*100,2),
# )
# fig.add_trace(fig1['data'][0], row=1, col=1)
# fig.add_trace(fig2['data'][0], row=1, col=2)
# fig.update_traces(texttemplate='%{text:0.1f}%', textposition='outside')
# fig.update_layout(height=600, width=700) #, title_text="Predictions for")
# fig.update_xaxes(range=[0,115])
# fig.update_xaxes(matches='x')
# fig.update_yaxes(showticklabels=False) # hide all the xticks
# fig.update_yaxes(showticklabels=True, row=1, col=1)
# st.plotly_chart(fig)
# def plot_dual_bar_chart(topics_summary, scores_summary, topics_text, scores_text):
# data1 = pd.DataFrame({'label': topics_summary, 'scores': scores_summary})
# data1['classification_on'] = 'summary'
# data2 = pd.DataFrame({'label': topics_text, 'scores': scores_text})
# data2['classification_on'] = 'full text'
# data = pd.concat([data1, data2])
# data['scores'] = round(data['scores']*100,2)
# fig = px.bar(
# data, x="scores", y="label", #orientation = 'h',
# labels={'x': 'Confidence Score', 'y': 'Label'},
# text=data['scores'],
# range_x=(0,115),
# color="label", barmode="group",
# facet_col="classification_on",
# category_orders={"classification_on": ["summary", "full text"]}
# )
# fig.update_traces(texttemplate='%{text:0.1f}%', textposition='outside')
# st.plotly_chart(fig)
def examples_load():
with open("examples.json") as f:
data=json.load(f)
return data['text'], data['long_text_license'], data['labels'], data['ground_labels']
def example_long_text_load():
with open("example_long_text.txt", "r") as f:
text_data = f.read()
return text_data
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