added scheduler, logging and optimization updates

app.py

@@ -184,7 +184,10 @@ def get_recommendations(user_id, model, data, G, user_nodes, post_nodes, node2id
 
         scores = torch.matmul(user_embed, post_embeds.T).squeeze(0)
 
-    post_scores = [(post_nodes[i], score.item()) for i, score in zip(post_indices, scores)]
+    # Create an inverse mapping from index to post ID
+    idx2node = {idx: node for node, idx in node2idx.items()}
+    # Map post_indices back to original post IDs
+    post_scores = [(idx2node[i], score.item()) for i, score in zip(post_indices, scores)]
     post_scores = sorted(post_scores, key=lambda x: x[1], reverse=True)
 
     logger.info(f"Generated {len(post_scores)} recommendations for user {user_id}")