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import plotly.express as px | |
import pandas as pd | |
import json | |
import plotly.graph_objects as go | |
from datasets import load_dataset | |
import streamlit as st | |
REPO_ID = "libeIO/Sciences-POC" | |
with open('config/mapping_prompts.txt', 'r') as f: | |
mapping = json.loads(f.read()) | |
with open('config/mapping_noms.txt', 'r') as f: | |
mapping_noms = json.loads(f.read()) | |
if 'name' not in st.session_state.keys(): | |
st.session_state['name'] = 'Groupe 1' | |
def initialize(name): | |
articles = pd.read_csv('data/extract_sciences_po.csv') | |
with open(f"{mapping[mapping_noms[name]]['save_path']}", 'r') as f : | |
out_dict = json.loads(f.read()) | |
df = pd.DataFrame.from_dict(out_dict) | |
articles = pd.merge(df, articles, on='item_id', how='left') | |
count_principale = df.groupby('categorie_principale').item_id.count() | |
print(f"Name : {name}\n Data : {df}") | |
df['categorie_secondaire'] = df.apply(lambda x : x.categorie_secondaire.split(',')[0] if x.categorie_secondaire!=None else None, axis=1) | |
count_secondaire = df.groupby('categorie_secondaire').item_id.count() | |
display_principale = count_principale.reset_index() | |
display_principale.columns = ['Catégorie', 'Nombre d\'articles'] | |
display_secondaire = count_secondaire.reset_index() | |
display_secondaire.columns = ['Catégorie', 'Nombre d\'articles'] | |
template ="ggplot2" | |
fig = go.Figure() | |
fig.update_layout(template=template, | |
) | |
fig.add_trace(go.Scatterpolar( | |
r=display_principale['Nombre d\'articles'], | |
theta=display_principale['Catégorie'], | |
fill='toself', | |
name='Catégorie Principale', | |
marker = {'color' : 'red'}, | |
)) | |
fig.add_trace(go.Scatterpolar( | |
r=display_secondaire['Nombre d\'articles'], | |
theta=display_secondaire['Catégorie'], | |
fill='toself', | |
name='Catégorie Secondaire', | |
marker = {'color' : 'blue'}, | |
opacity=0.25, | |
)) | |
fig.update_layout( | |
polar=dict( | |
radialaxis=dict( | |
visible=True, | |
range=[0, max(max(display_principale['Nombre d\'articles']), max(display_secondaire['Nombre d\'articles']))] | |
)), | |
showlegend=True | |
) | |
fig.update_layout(legend=dict( | |
yanchor="top", | |
y=0.0001, | |
xanchor="left", | |
x=0.395 | |
)) | |
path_prompt = mapping[mapping_noms[name]]['path_prompt'] | |
model = mapping[mapping_noms[name]]['client'] | |
with open(path_prompt, 'r') as f : | |
prompt = f.read() | |
return fig, display_principale, articles, prompt, model | |
def display_article(article): | |
url = article['url'] | |
colImage, colText = st.columns(2) | |
# try : | |
with colImage : | |
st.image(article["image_url"]) # image URL | |
with colText: | |
if 'subhead' in article.index and article['subhead']!='nan': | |
st.subheader(f":red[{article['subhead']}] [{article['titre'].rstrip('Libération').rstrip('-')[:-2]}]({url})") # Title | |
else : | |
# st.toast(article.index) | |
titre_cleaned = article['titre'].removesuffix('Libération').rstrip('-').strip() | |
st.subheader(f"[{titre_cleaned}]({url})") # Title | |
st.write(f"{article['description']}") # Header | |
formatted_date = article["date_published"] | |
if article.premium: | |
st.markdown( | |
f""" | |
<span style='color:grey'>{formatted_date+" "} </span> <span style='color:#eeb54e'> abonnés</span> | |
""", | |
unsafe_allow_html=True | |
) | |
else : | |
st.markdown( | |
f""" | |
<span style='color:grey'>{formatted_date+" "} </span> | |
""", | |
unsafe_allow_html=True | |
) | |
st.badge(f"Catégories secondaires : {article['categorie_secondaire']}", icon=":material/info:", color="blue") | |
# except : | |
# st.toast(f'Error displaying article {article.item_id}') | |
# return | |
fig, display_principale, articles, prompt, model = initialize(st.session_state['name']) | |
# col1, col2, col3 = st.columns([0.5, 0.2, 0.3]) | |
st.selectbox("Choisir groupe", [mapping[k]['auteurs'] for k in mapping.keys()], key='name') | |
with st.expander(f"Prompt for model : {model}") : | |
st.markdown(prompt) | |
st.subheader('Répartition des articles par catégorie') | |
# with col1: | |
col1, col2 = st.columns([0.6, 0.4], vertical_alignment='center') | |
with col1: | |
st.plotly_chart(fig) | |
with col2: | |
st.dataframe(display_principale.set_index('Catégorie').sort_values(by='Nombre d\'articles', ascending=False)) | |
st.subheader('Exemples d\'articles') | |
tabs = st.tabs(display_principale['Catégorie'].values.tolist()) | |
for i in range(len(tabs)): | |
with tabs[i]: | |
cat = display_principale['Catégorie'][i] | |
for i, article in articles.loc[articles.categorie_principale==cat].sample(20, replace=True).drop_duplicates().iterrows(): | |
display_article(article) | |