Spaces:
Sleeping
Sleeping
Added main app and requirements
Browse files- .gitignore +2 -0
- README.md +1 -13
- app.py +414 -0
- requirements.txt +9 -0
.gitignore
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.streamlit/
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.venv/
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README.md
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title: Translation Demo
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emoji: π’
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colorFrom: green
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colorTo: purple
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sdk: streamlit
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sdk_version: 1.17.0
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app_file: app.py
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pinned: false
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license: afl-3.0
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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# personal-webpage
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app.py
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import streamlit as st
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from datetime import time, datetime
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import time as t
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from time import time as now
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import pandas as pd
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import pandas_profiling
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import numpy as np
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from streamlit_pandas_profiling import st_profile_report
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from io import StringIO
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import requests
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from pathlib import Path
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from streamlit_elements import elements, dashboard, mui, media
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st.set_page_config(page_title="Francesco Daimon Fernicola", page_icon=":milky_way:", layout="wide")
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with st.container():
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st.subheader("Hello, and welcome to my official webpage! I am Daimon :wink:")
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st.title("PhD Candidate in Machine Translation / Translator / Mountain enthusiast")
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st.write("I am passionate about finding new ways to effectively use and understand Machine Translation and effectively evaluating its quality.")
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st.write("""
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[Github](https://github.com/FrancescoFernicola)
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[Unibo](https://www.unibo.it/sitoweb/francesco.fernicola2)
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[LinkedIn](https://www.linkedin.com/in/francesco-fernicola-69a0771b7/?locale=en_US)
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[Twitter](https://twitter.com/FrancescoDaimon)
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""")
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st.header('st.button')
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if st.button('Say hello'):
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st.write('Why hello there')
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else:
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st.write('Goodbye')
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st.header('st.slider')
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st.subheader('Slider')
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age = st.slider('How old are you?', 0, 120, 25)
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st.write(f"I'm {age} years old")
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st.subheader('Range Slider')
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values = st.slider(
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'Select a range of values',
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0.0, 100.0, (25.0, 75.0)
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)
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st.write(f"Values: {values}")
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st.subheader('Range time slider')
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appointment = st.slider(
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"Schedule your appointment:",
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value=(time(11,30), time(12,45)),
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format="hh:mm"
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)
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st.write(f"You're scheduled for: {appointment}")
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st.subheader('Datetime slider')
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start_time = st.slider(
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"When do you start?",
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value=datetime(2023, 1, 1, 9, 30),
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format="DD/MM/YY - hh:mm"
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)
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st.write(f"Start time: {start_time}")
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st.header('Line Chart')
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chart_data = pd.DataFrame(
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np.random.randn(20, 3),
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columns=['a', 'b', 'c']
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)
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st.line_chart(chart_data)
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with st.container():
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option = st.selectbox(
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'What is your favorite color?',
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('Blue', 'Red', 'Green', 'More')
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)
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if not option == 'More':
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st.write(f'Your favorite color is {option}')
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else:
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new_option = st.multiselect(
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'What are your favorite colors',
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['Green', 'Yellow', 'Red', 'Blue'],
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['Yellow', 'Red']
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)
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st.write(f'Your favorite colors are {", ".join(new_option)}')
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st.header('st.checkbox')
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st.write('What would you like to order?')
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icecream = st.checkbox('Ice cream')
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coffee = st.checkbox('Coffee')
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cola = st.checkbox('Cola')
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if icecream:
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st.write("Great! Heres some more :icecream:")
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if coffee:
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st.write("Okay, here's some coffee :coffee:")
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if cola:
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st.write("Here you go π₯€")
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#st.header('streamlig_pandas_profiling')
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#df = pd.read_csv('https://raw.githubusercontent.com/dataprofessor/data/master/penguins_cleaned.csv')
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#pr = df.profile_report()
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#st_profile_report(pr)
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st.write("Contents of the '.streamlit/config.toml' file of this app")
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st.code("""
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[theme]
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primaryColor="#F39C12"
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backgroundColor="#2E86C1"
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secondaryBackgroundColor="#AED6F1"
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textColor="#FFFFFF"
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font="monospace"
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""")
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number = st.sidebar.slider('Select a number:', 0, 10, 5)
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st.write(f'Selected number from slider widget is: {number}')
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st.header("This is taken from the .streamlit/secrets.toml")
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st.write(f"Secret message: {st.secrets['message']}")
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st.header("Remember to add the file to the .gitignore!")
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st.title('st.file_uploader')
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st.subheader('Input TSV/CSV')
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uploaded_file = st.file_uploader("Choose a file")
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if uploaded_file is not None:
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if uploaded_file.name.endswith('.tsv'):
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data = pd.read_csv(uploaded_file, sep="\t")
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else:
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data = pd.read_csv(uploaded_file)
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st.subheader("DataFrame")
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st.write(data)
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st.write(data.describe())
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else:
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st.info("βοΈ Upload a TSV/CSV file")
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with st.expander('About this app'):
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st.write('This app shows the various options you can use (and should use) to customize your page')
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st.image('https://imgs.xkcd.com/comics/app.png', width=250)
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st.write('Below you will also display the progress of the calculation via "st.progress()"')
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st.sidebar.header('Input')
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user_name = st.sidebar.text_input('What is your name?')
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user_emoji = st.sidebar.selectbox('Choose an emoji', ['', 'π', 'π', 'π', 'π', 'π΄', 'π', 'π±'])
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user_food = st.sidebar.selectbox('What is your favorite food?', ['', 'Tom Yum Kung', 'Burrito', 'Lasagna', 'Hamburger', 'Pizza'])
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st.header('Output')
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col1, col2, col3 = st.columns(3)
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with col1:
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if user_name != '':
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st.write(f'π Hello {user_name}!')
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else:
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st.write('π Please enter your **name**!')
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with col2:
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if user_emoji != '':
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st.write(f'{user_emoji} is your favorite **emoji**!')
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else:
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st.write('π Please choose an **emoji**!')
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with col3:
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if user_food != '':
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st.write(f'π΄ **{user_food}** is your favorite **food**!')
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else:
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st.write('π Please choose your favorite **food**!')
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#my_bar = st.progress(0)
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#for percent_complete in range(100):
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# t.sleep(0.05)
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# my_bar.progress(percent_complete + 1)
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st.metric(label="F1",
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value="81.1",
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delta="-0.1")
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st.title('st.cache')
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a0 = now()
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st.subheader('Using st.cache')
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@st.cache(suppress_st_warning=True)
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def load_data_a():
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dataframe = pd.DataFrame(
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np.random.rand(2000000, 5),
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columns=['a', 'b', 'c', 'd', 'e']
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)
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return dataframe
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st.write(load_data_a())
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a1 = now()
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st.info(a1-a0)
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b0 = now()
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st.subheader('Not using st.cache')
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def load_data_b():
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dataframe = pd.DataFrame(
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np.random.rand(2000000, 5),
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columns=['a', 'b', 'c', 'd', 'e']
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)
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return dataframe
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st.write(load_data_b())
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b1 = now()
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st.info(b1-b0)
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st.title('st.session_state')
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def lbs_to_kg():
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st.session_state.kg = st.session_state.lbs/2.2046
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def kg_to_lbs():
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st.session_state.lbs = st.session_state.kg*2.2046
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st.header('Input kg/lbs')
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col1, spacer, col2 = st.columns([2, 1, 2])
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with col1:
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punds = st.number_input("Pounds:", key = "lbs", on_change = lbs_to_kg)
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with col2:
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kilogram = st.number_input("Kilograms:", key = "kg", on_change= kg_to_lbs)
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st.header('Output')
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st.write("st.session_state object: ", st.session_state)
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st.title('π Bored API app')
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st.sidebar.header("Input Boredom")
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selected_type = st.sidebar.selectbox('Select an activity type', ["education", "recreational", "social", "diy", "charity", "cooking", "relaxation", "music", "busywork"])
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suggested_activity_url = f'http://www.boredapi.com/api/activity?type={selected_type}'
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274 |
+
json_response = requests.get(suggested_activity_url)
|
275 |
+
suggested_activity = json_response.json()
|
276 |
+
|
277 |
+
|
278 |
+
c1, c2 = st.columns(2)
|
279 |
+
|
280 |
+
with c1:
|
281 |
+
with st.expander('About this app'):
|
282 |
+
st.write('Bored stiff? The **BORED API APP** gives suggestions on activities that you can do when bored. This is powered by Bored API.')
|
283 |
+
with c2:
|
284 |
+
with st.expander('JSON data'):
|
285 |
+
st.write(suggested_activity)
|
286 |
+
|
287 |
+
st.header('Suggested activity')
|
288 |
+
st.info(suggested_activity['activity'])
|
289 |
+
|
290 |
+
col1, col2, col3 = st.columns(3)
|
291 |
+
|
292 |
+
with col1:
|
293 |
+
st.metric(label="Number of Participants", value=suggested_activity['participants'], delta='')
|
294 |
+
with col2:
|
295 |
+
st.metric(label="Type of Activity", value=suggested_activity['type'].capitalize(), delta='')
|
296 |
+
with col3:
|
297 |
+
st.metric(label='Price', value=suggested_activity['price'], delta='')
|
298 |
+
|
299 |
+
|
300 |
+
|
301 |
+
media_url = st.text_input("Media URL", value="https://www.youtube.com/watch?v=9EcjWd-O4jI&ab_channel=TechnotronicVEVO")
|
302 |
+
|
303 |
+
layout = [
|
304 |
+
# Media item is positioned in coordinates x=0 and y=3, and takes 6/12 columns and has a height of 4.
|
305 |
+
dashboard.Item("media", 0, 2, 12, 4),
|
306 |
+
]
|
307 |
+
|
308 |
+
with elements("demo"):
|
309 |
+
|
310 |
+
# Create a new dashboard with the layout specified above.
|
311 |
+
#
|
312 |
+
# draggableHandle is a CSS query selector to define the draggable part of each dashboard item.
|
313 |
+
# Here, elements with a 'draggable' class name will be draggable.
|
314 |
+
#
|
315 |
+
# For more information on available parameters for dashboard grid:
|
316 |
+
# https://github.com/react-grid-layout/react-grid-layout#grid-layout-props
|
317 |
+
# https://github.com/react-grid-layout/react-grid-layout#responsive-grid-layout-props
|
318 |
+
|
319 |
+
with dashboard.Grid(layout, draggableHandle=".draggable"):
|
320 |
+
with mui.Card(key="media", sx={"display": "flex", "flexDirection": "column"}):
|
321 |
+
mui.CardHeader(title="Media Player", className="draggable")
|
322 |
+
with mui.CardContent(sx={"flex": 1, "minHeight": 0}):
|
323 |
+
|
324 |
+
# This element is powered by ReactPlayer, it supports many more players other
|
325 |
+
# than YouTube. You can check it out there: https://github.com/cookpete/react-player#props
|
326 |
+
|
327 |
+
media.Player(url=media_url, width="100%", height="100%", controls=True)
|
328 |
+
|
329 |
+
|
330 |
+
def local_css(file_name):
|
331 |
+
with open(file_name) as f:
|
332 |
+
st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
|
333 |
+
|
334 |
+
local_css("style/style.css")
|
335 |
+
|
336 |
+
|
337 |
+
from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
|
338 |
+
|
339 |
+
|
340 |
+
st.subheader("MBART-50 Translator")
|
341 |
+
|
342 |
+
source = "In the beginning the Universe was created. This has made a lot of people very angry and been widely regarded as a bad move."
|
343 |
+
target = ""
|
344 |
+
model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
|
345 |
+
tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
|
346 |
+
|
347 |
+
|
348 |
+
def get_translation(src_code, trg_code, src):
|
349 |
+
|
350 |
+
# translate Hindi to French
|
351 |
+
tokenizer.src_lang = src_code
|
352 |
+
encoded = tokenizer(src, return_tensors="pt")
|
353 |
+
generated_tokens = model.generate(
|
354 |
+
**encoded,
|
355 |
+
forced_bos_token_id=tokenizer.lang_code_to_id[trg_code]
|
356 |
+
)
|
357 |
+
trg = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
|
358 |
+
|
359 |
+
return trg
|
360 |
+
|
361 |
+
valid_languages = ['en_XX', 'fr_XX', 'de_DE', 'it_IT', 'es_XX']
|
362 |
+
|
363 |
+
with st.form("my_form"):
|
364 |
+
left_c, right_c = st.columns(2)
|
365 |
+
with left_c:
|
366 |
+
src_lang = st.selectbox(
|
367 |
+
'Source language',
|
368 |
+
('en_XX', 'fr_XX', 'de_DE', 'it_IT', 'es_XX'),
|
369 |
+
|
370 |
+
)
|
371 |
+
with right_c:
|
372 |
+
trg_lang = st.selectbox(
|
373 |
+
'Target language',
|
374 |
+
('fr_XX', 'en_XX', 'de_DE', 'it_IT', 'es_XX')
|
375 |
+
)
|
376 |
+
source = st.text_area("Source", value=source, height=130, placeholder="Enter the source text...")
|
377 |
+
|
378 |
+
|
379 |
+
submitted = st.form_submit_button("Translate")
|
380 |
+
if submitted:
|
381 |
+
if len(source) > 0 and src_lang in valid_languages and trg_lang in valid_languages:
|
382 |
+
with st.spinner("Translating..."):
|
383 |
+
try:
|
384 |
+
target = get_translation(src_lang, trg_lang, source)[0]
|
385 |
+
st.subheader("Translation done!")
|
386 |
+
target = st.text_area("Target", value=target, height=130)
|
387 |
+
except:
|
388 |
+
st.subheader("Translation failed :sad:")
|
389 |
+
|
390 |
+
else:
|
391 |
+
st.write("Please enter the source text, source language and target language.")
|
392 |
+
|
393 |
+
|
394 |
+
|
395 |
+
# ---- CONTACT ----
|
396 |
+
with st.container():
|
397 |
+
st.write("---")
|
398 |
+
st.header("Get in Touch With Me!")
|
399 |
+
st.write("##")
|
400 |
+
|
401 |
+
contact_form = """
|
402 |
+
<form action="https://formsubmit.co/daimon.f@outlook.com" method="POST">
|
403 |
+
<input type="hidden" name="_captcha" value="false">
|
404 |
+
<input type="text" name="name" placeholder="Your name" required>
|
405 |
+
<input type="email" name="email" placeholder="Your email" required>
|
406 |
+
<textarea name="message" placeholder="Your message here" required></textarea>
|
407 |
+
<button type="submit">Send</button>
|
408 |
+
</form>
|
409 |
+
"""
|
410 |
+
left_column, right_column = st.columns(2)
|
411 |
+
with left_column:
|
412 |
+
st.markdown(contact_form, unsafe_allow_html=True)
|
413 |
+
with right_column:
|
414 |
+
st.empty()
|
requirements.txt
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
pandas
|
2 |
+
streamlit
|
3 |
+
pathlib
|
4 |
+
openai
|
5 |
+
numpy
|
6 |
+
streamlit_pandas_profiling
|
7 |
+
streamlit-elements==0.1.*
|
8 |
+
transformers
|
9 |
+
torch
|