Updating person suggest to include education, created_date

.vscode/launch.json

@@ -8,7 +8,8 @@
             "program": "${workspaceFolder}/src/manage.py",
             "args": [
                 "runserver",
-                "[::]:8000"
+                "[::]:8000",
+                "--ipv6"
             ],
             "env": {
                 "USE_DEBUG_TOOLBAR": "True"

src/search/documents/person.py

@@ -17,7 +17,6 @@ class PersonDocument(BaseDocument):
     full_name = es_fields.TextField(attr="full_name", analyzer=content_analyzer)
     person_types = es_fields.KeywordField(attr="person_types_indexing")
     headline = es_fields.ObjectField(
-        attr="headline",
         properties={
             "title": es_fields.TextField(),
         },
@@ -32,6 +31,8 @@ class PersonDocument(BaseDocument):
     suggestion_phrases = es_fields.Completion()
     user_id = es_fields.IntegerField(attr="user_id")
     reputation_hubs = es_fields.KeywordField()
+    education = es_fields.KeywordField()
+    created_date = es_fields.DateField(attr="created_date")
 
     class Index:
         name = "person"
@@ -47,18 +48,31 @@ class Django:
     def should_remove_from_index(self, obj):
         return False
 
+    def prepare_headline(self, instance):
+        return instance.build_headline()
+
     def prepare_reputation_hubs(self, instance):
         reputation_hubs = []
         for rep in instance.reputation_list:
             reputation_hubs.append(rep["hub"]["name"])
 
         return reputation_hubs
 
+    def prepare_education(self, instance):
+        education = []
+        for edu in instance.education:
+            education.append(edu["name"])
+
+        return education
+
     def prepare_suggestion_phrases(self, instance):
         suggestions = []
 
         if instance.full_name:
-            suggestions.append({"input": instance.full_name, "weight": 10})
+            if instance.user:
+                suggestions.append({"input": instance.full_name, "weight": 15})
+            else:
+                suggestions.append({"input": instance.full_name, "weight": 10})
 
         if instance.first_name:
             suggestions.append({"input": instance.first_name, "weight": 5})

src/user/related_models/author_model.py

@@ -117,6 +117,39 @@ def __str__(self):
             f"{university_city}"
         )
 
+    def build_headline(self):
+        from collections import Counter
+
+        if self.headline:
+            return self.headline
+
+        try:
+            all_topics = []
+            authored_papers = self.authored_papers.all()
+
+            for p in authored_papers:
+                unified_document = p.unified_document
+                all_topics += list(unified_document.topics.all())
+
+            topic_counts = Counter(all_topics)
+
+            # Sort topics by frequency
+            sorted_topics = sorted(
+                topic_counts.items(), key=lambda x: x[1], reverse=True
+            )
+
+            # Extract topics from sorted list
+            sorted_topics = [topic for topic, _ in sorted_topics]
+
+            if not sorted_topics:
+                return None
+
+            return {
+                "title": "Author with expertise in " + sorted_topics[0].display_name
+            }
+        except Exception:
+            return None
+
     @property
     def full_name(self):
         return self.first_name + " " + self.last_name

src/user/serializers.py

@@ -1092,37 +1092,7 @@ def get_achievements(self, author):
         return author.achievements
 
     def get_headline(self, author):
-        from collections import Counter
-
-        if author.headline:
-            return author.headline
-
-        try:
-            all_topics = []
-            authored_papers = author.authored_papers.all()
-
-            for p in authored_papers:
-                unified_document = p.unified_document
-                all_topics += list(unified_document.topics.all())
-
-            topic_counts = Counter(all_topics)
-
-            # Sort topics by frequency
-            sorted_topics = sorted(
-                topic_counts.items(), key=lambda x: x[1], reverse=True
-            )
-
-            # Extract topics from sorted list
-            sorted_topics = [topic for topic, _ in sorted_topics]
-
-            if not sorted_topics:
-                return None
-
-            return {
-                "title": "Author with expertise in " + sorted_topics[0].display_name
-            }
-        except Exception:
-            return None
+        return author.build_headline()
 
     def get_user(self, author):
         user = author.user