fixed following followed user schema

app.py

@@ -57,13 +57,14 @@ def load_and_preprocess_data():
     followers = pd.DataFrame(followers_response.data)
     users = pd.DataFrame(users_response.data)
 
-    merged = followers.merge(users, left_on='following', right_on='id', how='left')
-    merged = merged.rename(columns={'id_x': 'follower_id', 'id_y': 'followed_id'})
-
+    # 'id' is the followed user, 'following' is the follower
+    merged = followers.merge(users, left_on='id', right_on='id', how='left')
+    merged = merged.rename(columns={'following': 'follower_id', 'id': 'followed_id'})
     merged = merged[['follower_id', 'followed_id']].dropna()
     return merged[(merged['follower_id'] != '') & (merged['followed_id'] != '')]
 
 def create_graph_dataframe(merged_df):
+    # Edge from follower to followed
     G = nx.from_pandas_edgelist(merged_df, source='follower_id', target='followed_id', create_using=nx.DiGraph())
     user_ids = sorted(G.nodes())
     return G, torch.eye(len(user_ids)), user_ids
@@ -130,17 +131,17 @@ def get_recommendations(user_id, model, data, G, user_ids, top_k=10):
         return []
 
     user_idx = user_ids.index(user_id)
+    # Successors are the users this user follows
     current_follows = set(G.successors(user_id))
-
+    
+    # Exclude self and already-followed users
     candidates = [u for u in user_ids if u != user_id and u not in current_follows]
-
+    
     with torch.no_grad():
         embeddings = model(data.x, data.edge_index)
         user_embed = embeddings[user_idx]
-
         candidate_indices = [user_ids.index(u) for u in candidates]
         candidate_embeds = embeddings[candidate_indices]
-
         scores = torch.mm(user_embed.view(1, -1), candidate_embeds.T).squeeze()
 
     top_indices = scores.argsort(descending=True)[:top_k]