woops

modular_graph_and_candidates.py

@@ -126,12 +126,11 @@ def embedding_similarity_clusters(models_root: Path, missing: List[str], thr: fl
         texts[name] = code.strip() or " "
 
     names = list(texts)
+    names = names[:90]  # Limit before processing
     all_embeddings = []
 
     print(f"Encoding embeddings for {len(names)} models...")
     batch_size = 8
-
-    names = names[:90]
     
     for i in tqdm(range(0, len(names), batch_size), desc="Models", leave=False):
         model_name = names[i]