New feed recommender

app.py

@@ -186,15 +186,25 @@ class Recommender:
             text = f"{title} {description}".strip()
             post_texts.append(text)
             post_ids.append(post_id)
-            post['created_at'] = datetime.fromisoformat(
-                post['created_at'].replace('Z', '+00:00')
-            ).astimezone(TIMEZONE)
+
+            # Adjust the timestamp to ensure six digits for microseconds
+            created_at_str = post['created_at']
+            if '.' in created_at_str:
+                date_part, time_part = created_at_str.split('T')
+                time_part = time_part.split('+')[0]  # Remove timezone for now
+                if '.' in time_part:
+                    time_without_micro, micro = time_part.split('.')
+                    micro = micro.zfill(6)  # Pad with zeros to make it six digits
+                    time_part = f"{time_without_micro}.{micro}"
+                created_at_str = f"{date_part}T{time_part}+00:00"
+            post['created_at'] = datetime.fromisoformat(created_at_str).astimezone(TIMEZONE)
             post['type'] = 'post'
             post_metadata[post_id] = post
 
-        embeddings = sentence_model.encode(post_texts, show_progress_bar=True, convert_to_numpy=True)
-        for post_id, embedding in zip(post_ids, embeddings):
-            post_features[post_id] = embedding / np.linalg.norm(embedding)
+        if post_texts:
+            embeddings = sentence_model.encode(post_texts, show_progress_bar=True, convert_to_numpy=True)
+            for post_id, embedding in zip(post_ids, embeddings):
+                post_features[post_id] = embedding / np.linalg.norm(embedding)
 
         await self.update_interactions()