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'] = 'Inconnus 1' @st.cache_resource def initialize(name): if name == "dimanov_et_al": return None, None, None, None, None 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() df['categorie_secondaire'] = df.apply(lambda x : x.categorie_secondaire.split(',')[0], 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""" {formatted_date+" "} abonnés """, unsafe_allow_html=True ) else : st.markdown( f""" {formatted_date+" "} """, 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', index=1) if st.session_state['name']=="dimanov_et_al": st.toast("Ce groupe n'a pas renseigné son prompt !") else : 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)