Update app.py

app.py

@@ -72,6 +72,23 @@ def load_db():
         embedding_function=embedding)
     return vectordb
 
+def delete_db(vectordb):
+    # Rimuovi tutte le raccolte
+    collections = vectordb.collections
+    for collection in collections:
+        print(f"Cancellando raccolta: {collection}")
+        vectordb.delete_collection(collection)
+
+    # Rimuovi il client ChromaDB
+    vectordb.client.close()
+
+    # Rimuovi il database principale
+    db_path = vectordb.client.path
+    if os.path.exists(db_path):
+        os.remove(db_path)
+        print(f"Rimosso file database principale: {db_path}")
+
+    print("Tutte le raccolte e il database sono stati completamente eliminati.")
 
 # Initialize langchain LLM chain
 def initialize_llmchain(llm_model, temperature, max_tokens, top_k, vector_db, progress=gr.Progress()):
@@ -217,13 +234,39 @@ def initialize_database(list_file_obj, chunk_size, chunk_overlap, progress=gr.Pr
     progress(0.25, desc="Caricamento documenti..")
     # Load document and create splits
     doc_splits = load_doc(list_file_path, chunk_size, chunk_overlap)
+    
     # Create or load vector database
-    progress(0.5, desc="Generazione vector database...")
+    #progress(0.5, desc="Generazione vector database...")
     # global vector_db
+    #vector_db = create_db(doc_splits, collection_name)
+    #progress(0.9, desc="Fatto!")
+    #return vector_db, collection_name, "Completato!"
+
+    # Controlla se il database esiste già
+    if vector_db is not None:
+        print("Database esistente trovato. Stiamo per eliminarlo.")
+        
+        # Eliminare il database esistente
+        vector_db.client.close()
+        db_path = vector_db.client.path
+        if os.path.exists(db_path):
+            os.remove(db_path)
+            print(f"Rimosso file database principale: {db_path}")
+        
+        # Rimuovi eventuali raccolte
+        collections = vector_db.collections
+        for collection in collections:
+            print(f"Cancellando raccolta: {collection}")
+            vector_db.delete_collection(collection)
+        
+        print("Tutte le raccolte e il database sono stati completamente eliminati.")
+    
+    # Creare o caricare il nuovo database
+    progress(0.5, desc="Generazione vector database...")
     vector_db = create_db(doc_splits, collection_name)
     progress(0.9, desc="Fatto!")
-    return vector_db, collection_name, "Completato!"
 
+    return vector_db, collection_name, "Completato!"
 
 def initialize_LLM(llm_option, llm_temperature, max_tokens, top_k, vector_db, progress=gr.Progress()):
     # print("llm_option",llm_option)