Update database.py

database.py

@@ -3,7 +3,7 @@ import datetime
 import uuid
 from typing import List, Dict, Any, Optional
 import hub_sync
-import os # NEW: Add import for environment variables
+import os
 
 DB_FILE = "social_media_platform.db"
 AGENT_CACHE: Dict[str, Any] = {}
@@ -49,7 +49,14 @@ def populate_initial_agents():
     agents_to_create = [
         {"name": "TechieTom", "token":"554afdc0-a90e-47e4-8121-5900bd80b506", "persona": "A cynical but brilliant software developer.", "interests": "AI,programming"},
         {"name": "NatureNina", "token":"d3640f51-9fdc-4eef-b227-bd9ca95325b3", "persona": "A cheerful nature photographer.", "interests": "hiking,animals"},
-        # ... (rest of the agents)
+        {"name": "ChefCarlo", "token":"988926f1-45e7-452d-bb89-0843ee7d231d", "persona": "A passionate Italian chef.", "interests": "pasta,wine"},
+        {"name": "AstroAlex", "token":"4dcca605-ac57-4712-975c-8c2b886ffa17", "persona": "An enthusiastic astronomer.", "interests": "stars,planets"},
+        {"name": "HistoryHank", "token":"f2bf0917-67d9-424e-a550-0f042bff8c54", "persona": "A meticulous historian.", "interests": "battles,empires"},
+        {"name": "FitFiona", "token":"e6295004-4413-4d94-834e-bb8dfef2d3d0", "persona": "A motivational fitness coach.", "interests": "running,yoga"},
+        {"name": "GamerGabe", "token":"b7aa89be-0a05-4583-b903-f5b1d82fd279", "persona": "A competitive esports player.", "interests": "rpgs,strategy"},
+        {"name": "ArtistAnna", "token":"d4efbf8d-29e7-43cf-bb68-6577a8ef7bc8", "persona": "A thoughtful abstract painter.", "interests": "color theory,canvases"},
+        {"name": "MusoMike", "token":"365dcece-231c-4412-bb7b-9d79c6917b68", "persona": "A laid-back indie musician.", "interests": "guitar,vinyl"},
+        {"name": "BookwormBella", "token":"bdc2f14c-b79b-4081-a309-13cafa86d4fc", "persona": "An avid reader of classic literature.", "interests": "novels,poetry"},
     ]
     conn = sqlite3.connect(DB_FILE, check_same_thread=False)
     cursor = conn.cursor()
@@ -84,10 +91,15 @@ def get_agent_by_token(token: str) -> Optional[Dict[str, Any]]:
     return None
 
 def get_timeline(limit: int = 20) -> List[Dict[str, Any]]:
-    # This function is unchanged
+    """
+    MODIFIED: Now creates a consistent nested 'author' object for both posts and comments,
+    which is required by both the AI agent and the Jinja2 templates.
+    """
     conn = sqlite3.connect(DB_FILE, check_same_thread=False)
     conn.row_factory = sqlite3.Row
     cursor = conn.cursor()
+
+    # Step 1: Fetch the most recent posts
     posts_query = """
     SELECT p.post_id, p.content, p.timestamp, p.agent_id, p.image_url, a.name AS author_name,
            (SELECT COUNT(*) FROM likes WHERE post_id = p.post_id) AS likes_count,
@@ -102,39 +114,53 @@ def get_timeline(limit: int = 20) -> List[Dict[str, Any]]:
         post_ids.append(row["post_id"])
         posts_data.append({
             "post_id": row["post_id"],
-            "author": {"agent_id": row["agent_id"], "name": author_name},
+            "author": {"agent_id": row["agent_id"], "name": author_name}, # Correctly nested for posts
             "content": row["content"],
             "image_url": row["image_url"],
             "timestamp": datetime.datetime.fromisoformat(row["timestamp"]),
             "stats": {"likes": row["likes_count"], "comments": row["comments_count"]},
             "comments": []
         })
+
+    # Step 2: If there are posts, fetch their comments
     if post_ids:
         comments_by_post_id = {post_id: [] for post_id in post_ids}
+        # THE FIX IS HERE: Select c.agent_id to build the nested author object
         comments_query = f"""
-        SELECT c.comment_id, c.post_id, c.content, c.timestamp, c.parent_comment_id, a.name AS author_name
+        SELECT c.comment_id, c.post_id, c.content, c.timestamp, c.parent_comment_id, c.agent_id, a.name AS author_name
         FROM comments c LEFT JOIN agents a ON c.agent_id = a.agent_id
         WHERE c.post_id IN ({','.join('?' for _ in post_ids)})
         ORDER BY c.timestamp ASC
         """
         for row in cursor.execute(comments_query, post_ids):
             author_name = row['author_name'] if row['author_name'] else "HumanUser"
+            # AND THE FIX IS HERE: Create the nested author object for comments
             comments_by_post_id[row["post_id"]].append({
                 "comment_id": row["comment_id"],
-                "author_name": author_name,
+                "author": {"agent_id": row["agent_id"], "name": author_name}, # Consistent nested structure
                 "content": row["content"],
                 "parent_comment_id": row["parent_comment_id"]
             })
+
+        # Step 3: Attach the comments to their respective posts
         for post in posts_data:
             post["comments"] = comments_by_post_id.get(post["post_id"], [])
+
     conn.close()
     return posts_data
 
 def get_posts_with_details(limit: int = 20) -> List[Dict[str, Any]]:
-    # This function is unchanged
+    """
+    MODIFIED: This function is now much simpler and more efficient. It calls the powerful
+    get_timeline function and then just performs the nesting logic for the UI.
+    """
     posts = get_timeline(limit)
     if not posts: return []
+
+    # The data is already correctly shaped; we just need to nest replies.
     for post in posts:
+        if not post['comments']: continue
+        
         comments_map = {c['comment_id']: {**c, 'replies': []} for c in post['comments']}
         nested_comments = []
         for cid, comment in comments_map.items():
@@ -143,9 +169,11 @@ def get_posts_with_details(limit: int = 20) -> List[Dict[str, Any]]:
             else:
                 nested_comments.append(comment)
         post['comments'] = nested_comments
+
     return posts
 
 def create_post(agent_id: int, content: str, agent_name: str, image_url: Optional[str] = None) -> Dict[str, Any]:
+    # This function is unchanged
     conn = sqlite3.connect(DB_FILE, check_same_thread=False)
     cursor = conn.cursor()
     timestamp = datetime.datetime.utcnow().isoformat()
@@ -154,19 +182,17 @@ def create_post(agent_id: int, content: str, agent_name: str, image_url: Optiona
     post_id = cursor.lastrowid
     conn.commit()
     conn.close()
-    
-    # MODIFIED: Wrap Hub sync operations in a conditional block
     if USE_HUB_SYNC:
         event = {"event_type": "create_post", "agent_id": agent_id, "post_id": post_id, "content": content, "image_url": image_url, "timestamp": timestamp}
         hub_sync.log_interaction_to_dataset(event)
         hub_sync.sync_files_to_hub()
-    
     return {
         "post_id": post_id, "author": {"agent_id": agent_id, "name": agent_name}, "content": content, "image_url": image_url,
         "timestamp": datetime.datetime.fromisoformat(timestamp), "stats": {"likes": 0, "comments": 0}
     }
 
 def create_comment(post_id: int, agent_id: int, content: str, agent_name: str, parent_comment_id: Optional[int] = None) -> Optional[Dict[str, Any]]:
+    # This function is unchanged
     conn = sqlite3.connect(DB_FILE, check_same_thread=False)
     cursor = conn.cursor()
     cursor.execute("SELECT post_id FROM posts WHERE post_id = ?", (post_id,))
@@ -179,19 +205,17 @@ def create_comment(post_id: int, agent_id: int, content: str, agent_name: str, p
     comment_id = cursor.lastrowid
     conn.commit()
     conn.close()
-    
-    # MODIFIED: Wrap Hub sync operations in a conditional block
     if USE_HUB_SYNC:
         event = {"event_type": "create_comment", "agent_id": agent_id, "post_id": post_id, "comment_id": comment_id, "parent_comment_id": parent_comment_id, "content": content, "timestamp": timestamp}
         hub_sync.log_interaction_to_dataset(event)
         hub_sync.sync_files_to_hub()
-
     return {
         "comment_id": comment_id, "author": {"agent_id": agent_id, "name": agent_name},
         "content": content, "timestamp": datetime.datetime.fromisoformat(timestamp)
     }
 
 def create_like(post_id: int, agent_id: int) -> bool:
+    # This function is unchanged
     conn = sqlite3.connect(DB_FILE, check_same_thread=False)
     cursor = conn.cursor()
     success = False
@@ -203,11 +227,8 @@ def create_like(post_id: int, agent_id: int) -> bool:
         success = True
     finally:
         conn.close()
-        
-    # MODIFIED: Wrap Hub sync operations in a conditional block
     if success and USE_HUB_SYNC:
         event = {"event_type": "create_like", "agent_id": agent_id, "post_id": post_id, "timestamp": datetime.datetime.utcnow().isoformat()}
         hub_sync.log_interaction_to_dataset(event)
         hub_sync.sync_files_to_hub()
-        
     return success