Update app.py

app.py

@@ -8,7 +8,7 @@ from langchain_community.embeddings import HuggingFaceEmbeddings
 from langchain_community.vectorstores import Chroma
 from langchain_community.document_loaders import UnstructuredPDFLoader
 from langchain.text_splitter import CharacterTextSplitter
-from langchain.chains import RetrievalQAWithSourcesChain  # Modifica qui
+from langchain.chains import RetrievalQAWithSourcesChain
 from langchain.schema import Document
 from langchain.memory import ConversationBufferMemory
 from langchain.callbacks.manager import CallbackManager
@@ -20,8 +20,8 @@ from tqdm import tqdm
 import torch
 import logging
 
-# Update the embedding function creation
-embedding_function = HuggingFaceEmbeddings()
+# Aggiornamento dell'inizializzazione di HuggingFaceEmbeddings
+embedding_function = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
 
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
@@ -120,8 +120,7 @@ def demo():
         vector_db = gr.State()
         qa_chain = gr.State()
         collection_name = gr.State()
-        language = gr.State(default_value="italian")
-        
+        language = gr.State(value="italian")  # Modifica qui
         gr.Markdown(
         """<center><h2>Chatbot basato su PDF</center></h2>
         <h3>Fai domande sui tuoi documenti PDF</h3>""")