feat: SAPIENS Mobile App - Initial commit

React Native mobile application for SAPIENS news platform.
Consolidated all previous history into single commit.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

scripts/extract-outlets.py

@@ -0,0 +1,116 @@
+#!/usr/bin/env python3
+"""
+Extract outlets from news-api MongoDB collections
+"""
+import os
+from pymongo import MongoClient
+from collections import Counter
+import json
+
+MONGODB_URL = os.getenv('MONGODB_URL', 'mongodb://localhost:27017')
+DB_NAME = 'ai_writer_db'
+
+def extract_outlets():
+    client = MongoClient(MONGODB_URL)
+    db = client[DB_NAME]
+
+    # Use English collection
+    collection = db['articles_en']
+
+    # Get all articles
+    articles = list(collection.find({}, {
+        'source_keyword': 1,
+        'categories': 1,
+        'entities': 1,
+        'images': 1,
+        'summary': 1,
+        'title': 1
+    }).limit(1000))
+
+    # Extract unique data
+    people_map = {}  # name -> {articles, image, description}
+    topics_map = {}  # topic -> {articles, image, description}
+    companies_map = {}  # company -> {articles, image, description}
+
+    for article in articles:
+        source = article.get('source_keyword', '')
+        categories = article.get('categories', [])
+        entities = article.get('entities', {})
+        images = article.get('images', [])
+        image = images[0] if images else None
+
+        # Extract topics from categories
+        for cat in categories:
+            if cat not in topics_map:
+                topics_map[cat] = {
+                    'id': cat.lower().replace(' ', '-').replace('/', '-'),
+                    'name': cat,
+                    'category': 'topics',
+                    'articles': [],
+                    'image': None,
+                    'description': f'News and articles about {cat}'
+                }
+            topics_map[cat]['articles'].append(str(article['_id']))
+            if not topics_map[cat]['image'] and image:
+                topics_map[cat]['image'] = image
+
+        # Extract people from entities
+        for person in entities.get('people', []):
+            if person and person not in people_map:
+                people_map[person] = {
+                    'id': person.lower().replace(' ', '-'),
+                    'name': person,
+                    'category': 'people',
+                    'articles': [],
+                    'image': None,
+                    'description': f'News and updates about {person}'
+                }
+            if person and person in people_map:
+                people_map[person]['articles'].append(str(article['_id']))
+                if not people_map[person]['image'] and image:
+                    people_map[person]['image'] = image
+
+        # Extract companies from entities
+        for org in entities.get('organizations', []) + entities.get('groups', []):
+            if org and org not in companies_map:
+                companies_map[org] = {
+                    'id': org.lower().replace(' ', '-'),
+                    'name': org,
+                    'category': 'companies',
+                    'articles': [],
+                    'image': None,
+                    'description': f'Business news about {org}'
+                }
+            if org and org in companies_map:
+                companies_map[org]['articles'].append(str(article['_id']))
+                if not companies_map[org]['image'] and image:
+                    companies_map[org]['image'] = image
+
+    # Filter outlets with at least 3 articles
+    people = [v for v in people_map.values() if len(v['articles']) >= 3]
+    topics = [v for v in topics_map.values() if len(v['articles']) >= 3]
+    companies = [v for v in companies_map.values() if len(v['articles']) >= 3]
+
+    # Sort by article count
+    people.sort(key=lambda x: len(x['articles']), reverse=True)
+    topics.sort(key=lambda x: len(x['articles']), reverse=True)
+    companies.sort(key=lambda x: len(x['articles']), reverse=True)
+
+    result = {
+        'people': people[:50],  # Top 50
+        'topics': topics[:50],
+        'companies': companies[:50]
+    }
+
+    # Save to file
+    output_file = '/Users/jungwoochoi/Desktop/prototype/site11/services/sapiens-mobile/outlets-extracted.json'
+    with open(output_file, 'w', encoding='utf-8') as f:
+        json.dump(result, f, indent=2, ensure_ascii=False)
+
+    print(f"Extracted {len(people)} people, {len(topics)} topics, {len(companies)} companies")
+    print(f"Saved to {output_file}")
+
+    client.close()
+
+if __name__ == '__main__':
+    extract_outlets()