Update app.py

app.py

@@ -47,7 +47,7 @@ def initialize_database(document, chunk_size, chunk_overlap, progress=gr.Progres
                 docs = loader.load()
             except ImportError:
                 logger.error("Impossibile caricare il documento PDF. Assicurati di aver installato 'unstructured' o 'pypdf'.")
-                return None, "Errore: Pacchetti necessari non installati. Esegui 'pip install unstructured pypdf' e riprova."
+                return None, None, "Errore: Pacchetti necessari non installati. Esegui 'pip install unstructured pypdf' e riprova."
         
         for doc in docs:
             text_chunks = splitter.split_text(doc.page_content)
@@ -55,14 +55,13 @@ def initialize_database(document, chunk_size, chunk_overlap, progress=gr.Progres
                 documents.append(Document(page_content=chunk, metadata={"filename": file.name, "page": doc.metadata.get("page", 0)}))
     
     if not documents:
-        return None, "Errore: Nessun documento caricato correttamente."
+        return None, None, "Errore: Nessun documento caricato correttamente."
     
     vectorstore = Chroma.from_documents(documents, embedding_function)
     progress.update(0.5)
     logger.info("Database initialized successfully.")
-    return vectorstore, "Initialized"
+    return vectorstore, None, "Initialized"  # Aggiunto None come secondo output
 
-        
 def initialize_LLM(llm_option, llm_temperature, max_tokens, top_k, vector_db, progress=gr.Progress(), language="italian"):
     logger.info("Initializing LLM chain...")
     llm_name = list_llm[llm_option]
@@ -131,7 +130,6 @@ def conversation(qa_chain, message, history, language):
 
 def demo():
     with gr.Blocks(theme="base") as demo:
-
         vector_db = gr.State()
         qa_chain = gr.State()
         collection_name = gr.State()