Update app.py

app.py

@@ -6,6 +6,12 @@
 # Embeddings de texto usando o modelo all-MiniLM-L6-v2 do Hugging Face
 #
 
+import sys
+import platform
+
+__import__('pysqlite3')
+sys.modules['sqlite3'] = sys.modules.pop('pysqlite3')
+
 import streamlit as st
 from langchain.chains import create_history_aware_retriever, create_retrieval_chain
 from langchain.chains.combine_documents import create_stuff_documents_chain
@@ -191,4 +197,4 @@ if groq_api_key and huggingface_api_token:
                 for message in session_history.messages:
                     st.write(f"**{message.type}:** {message.content}")
 else:
-    st.warning("Por favor, insira tanto a chave da API do Groq quanto o token da API do Hugging Face.")
+    st.warning("Por favor, insira tanto a chave da API do Groq quanto o token da API do Hugging Face.")