ok

app.py

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+import json
+import streamlit as st
+import os
+from huggingface_hub import HfApi, login
+from streamlit_cookies_manager import EncryptedCookieManager
+
+st.set_page_config(
+    page_title="Holistic AI - ML Verticals papers",
+    page_icon="👋",
+    layout='wide'
+)
+
+def program():
+    st.title("Papers")
+    
+    dataset_name = "holistic-ai/mitigation_ml_bias_strategies"
+    token = os.getenv("HF_TOKEN")
+    
+    api = HfApi()
+    login(token)
+    
+    repo_path = api.snapshot_download(repo_id=dataset_name, repo_type="dataset")
+    dirnames = [dirname for dirname in os.listdir(repo_path) if not dirname.startswith(".")]
+    dirnames = sorted(dirnames, key=lambda x:len(x))
+    
+    st.sidebar.title("Namespaces")
+    selected_namespace = st.sidebar.selectbox("Select Namespace", dirnames)
+
+    selected_paper_type = st.sidebar.selectbox("Select Paper Type", ['Metrics',"Mitigators"])
+    
+    if selected_namespace:
+        
+        if selected_paper_type=='Metrics':
+            with open(f'{repo_path}/{selected_namespace}/grouped_metrics.json') as file:
+                data = json.load(file)
+        elif selected_paper_type=='Mitigators':
+            with open(f'{repo_path}/{selected_namespace}/grouped_mitigators.json') as file:
+                data = json.load(file)
+    
+        task_names = list(data.keys())
+    
+        st.sidebar.title("Tasks")
+        selected_task = st.sidebar.selectbox("Select a Task", task_names)
+    
+        if selected_task:
+            st.header(selected_task)
+            results = data[selected_task]
+            rec = {str(r['id']): r for r in results['recommendations']}
+            for group in results['groups']:
+                ids = [i.strip() for i in group['ids'].split(",")]
+                rec2html = '\n'.join([f"""<p>[{i+1}] <a href="{rec[idx]['metadata']['id']}" target="_blank">{rec[idx]['title']}</a></p>""" for i,idx in enumerate(ids)])
+                title = group['title'].split(':',1)[1].strip()
+                st.markdown(f"""
+                <div style="border:1px solid #ccc; padding:10px; margin:10px 0; border-radius:5px;">
+                    <p><b>{title}</b></p>
+                    <p>{group['recommendation']}</p>
+                    <p>Sources:</p>
+                    {rec2html}
+                </div>
+                """, unsafe_allow_html=True)
+
+SECRET_KEY = os.getenv('SECRET_KEY')
+
+cookies = EncryptedCookieManager(
+    prefix="login",
+    password=os.getenv('COOKIES_PASSWORD')
+)
+
+if not cookies.ready():
+    st.stop()
+
+def main():
+    # Título de la aplicación
+    st.title("Holistic AI - ML Papers")
+
+    if not cookies.get("authenticated"):
+        # Entrada de la clave secreta
+        user_key = st.text_input("Password:", type="password")
+
+        if st.button("Login"):
+            # Verificar si la clave ingresada coincide con la clave secreta
+            if user_key == SECRET_KEY:
+                cookies.__setitem__("authenticated", "True")
+                st.experimental_rerun()
+            else:
+                st.error("Access not granted. Incorrect Password.")
+    else:
+        program()
+if __name__ == "__main__":
+    main()

requirements.txt

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+streamlit-cookies-manager