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import streamlit as st
from streamlit_option_menu import option_menu
import openai
from streamlit_chat import message
#importation des librairies
import pandas as pd
st.set_page_config(layout='wide')
st.markdown("""
<style>
.block-container {
padding-top: 2rem;
padding-bottom: 0rem;
padding-left: 1rem;
padding-right: 1rem;
}
</style>
""", unsafe_allow_html=True)
openai.api_key = "sk-proj-RExBXqnjaTYCWwB3aQOOT3BlbkFJJf9S2nbyQj11VfArtjjo"
def api_calling(prompt):
completions = openai.Completion.create(
engine="gpt-3.5-turbo-instruct",
prompt=prompt,
max_tokens=1024,
n=1,
stop=None,
temperature=0.5,
)
message = completions.choices[0].text
return message
header , menu = st.columns(2)
with header:
st.image('static/img/bot.PNG')
with menu:
# option_menu(menu_title=None,
# options=['Visualisation','Prédiction'],
# icons=["house","book",'envelope'],
# default_index=0,
# orientation="horizontal"
# )
selecte=option_menu(None, ["Accueil", "Se déconnecter"],
icons=['house', 'cloud-upload'],
menu_icon="cast", default_index=0, orientation="horizontal",
styles={
"container": {"padding": "0!important", "background-color": "#fafafa","font-family": "Impact, Haettenschweiler, 'Arial Narrow Bold', sans-serif"},
"icon": {"color": "orange", "font-size": "25px" },
"nav-link": {"font-size": "20px", "text-align": "left", "margin":"0px", "--hover-color": "#eee"},
"nav-link-selected": {"background-color": "#70ad46","color":"white"},
"menu-title":{"color":"#424143"}
}
)
if selecte == "Accueil":
st.title(f"Bienvenu au cours d'informatique de la classe de 3ieme")
sect1_col1=st.container()
sect1_col2 = st.container()
with open('static/css/style.css') as f:
st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html=True)
with sect1_col1.container(height=700):
st.selectbox("Quelle UE voulez-vous preparer?",("Architecture, Maintenance et taleur"))
st.selectbox("De quel UA s'agit-il?",("Decrire les peripheriques","Decrire les logiciels","Assurer le bon fonctionnement de l'ordinateur","utiliser les fonctions d'un tableur"))
if 'user_input' not in st.session_state:
st.session_state['user_input'] = []
if 'openai_response' not in st.session_state:
st.session_state['openai_response'] = []
def get_text():
input_text = st.text_input("Quelles sont les objectifs du programme concerné?", key="input")
return input_text
user_input = get_text()
if user_input:
output = api_calling(user_input)
output = output.lstrip("\n")
# Store the output
st.session_state.openai_response.append(user_input)
st.session_state.user_input.append(output)
message_history = st.empty()
if st.session_state['user_input']:
for i in range(len(st.session_state['user_input']) - 1, -1, -1):
# This function displays user input
message(st.session_state["user_input"][i],
key=str(i),avatar_style="icons")
# This function displays OpenAI response
message(st.session_state['openai_response'][i],
avatar_style="miniavs",is_user=True,
key=str(i) + 'data_by_user')
st.markdown("""
<style>
# div[data-testid="stMetric"] {
# background-color: rgba(187, 216, 158, 0.59);
# border: 1px solid rgba(28, 131, 225, 0.1);
padding:-10px;
# border-radius: 5px;
# color: rgb(30, 103, 119);
# overflow-wrap: break-word;
# font-weight:bold;
# }
[data-testid="stMetricValue"]{
font-size: 45px;
color: #2FB56B;
font-weight:bold;
text-align:center;
margin-top:-33px;
}
/* breakline for metric text */
[data-testid="stMetricLabel"] {
word-wrap: break-word;
color: #ef8451;
font-size:40px;
font-weight:bold;
}
[data-testid ="stVerticalBlock"]{
#background-color: rgba(187, 216, 158, 0.59);
#border: 1px solid rgba(28, 131, 225, 0.1);
text-align:center;
}
[data-v-5af006b8]{
background-color:black;
}
.st-emotion-cache-sr3x2q{
width:80%;
margin-left:10%;
margin-right:10%;
height: 50% !important;
}
.st-emotion-cache-7ym5gk{
background-color: #70ad46;
color:white;
}
.st-emotion-cache-1jmvea6 p {
font-size: 20px;
color: black;
}
.st-emotion-cache-1jmvea6 p{
font-size: 20px;
}
.st-emotion-cache-1wrcr25{
background-color: #b1d1a0;
}
.st-emotion-cache-18ni7ap{
background-color: #b1d1a0;
}
.st-emotion-cache-1yiq2ps{
background-color: #b1d1a0;
}
</style>
"""
, unsafe_allow_html=True)
footer = st.container()
with footer:
st.markdown("---")
st.markdown(
"""
<style>
p {
font-size: 16px;
text-align: center;
}
a {
text-decoration: none;
color: #00a;
font-weight: 600;
}
</style>
<p>
&copy; Designed by <a href="#"></a>.
</p>
""", unsafe_allow_html=True
)
if selecte == "Données":
st.title(f"Les Capteurs en NAIROBI,KENYA")
st_folium(map,width=2000,height=600)
st.title(f"DATA")
moi = st.columns(1)
placeholder = st.empty()
df_all_concatenated_transform_daily= df_all_concatenated_transform_daily[df_all_concatenated_transform_daily["Moi"] ==moi_filtre]