Upload src/labdaps/retrieval/vector_store.py with huggingface_hub

src/labdaps/retrieval/vector_store.py

@@ -16,7 +16,7 @@ def build_index(chunks: list[Chunk], embedder: Embedder, rebuild: bool = False)
     if rebuild:
         try:
             client.delete_collection(COLLECTION_NAME)
-            print(f"[INFO] Colecao '{COLLECTION_NAME}' removida.")
+            print(f"[INFO] Coleção '{COLLECTION_NAME}' removida.")
         except Exception:
             pass
 
@@ -26,7 +26,7 @@ def build_index(chunks: list[Chunk], embedder: Embedder, rebuild: bool = False)
     )
 
     if collection.count() > 0 and not rebuild:
-        print(f"[INFO] Colecao ja contem {collection.count()} chunks. Use --rebuild para re-indexar.")
+        print(f"[INFO] Coleção já contém {collection.count()} chunks. Use --rebuild para re-indexar.")
         return
 
     texts = [c.text for c in chunks]
@@ -47,7 +47,7 @@ def build_index(chunks: list[Chunk], embedder: Embedder, rebuild: bool = False)
         )
         print(f"[INFO] Indexados chunks {i} a {min(i+batch_size, len(chunks))}/{len(chunks)}")
 
-    print(f"[INFO] Indexacao concluida. Total: {collection.count()} chunks")
+    print(f"[INFO] Indexação concluída. Total: {collection.count()} chunks")
 
 
 def query_store(query_embedding: list[float], top_k: int):