Update app.py

app.py

@@ -1,14 +1,3 @@
-# import subprocess
-
-# sub_p_res = subprocess.run(['pip', 'install', 'langchain', 'sentence-transformers', 'transformers', 'faiss-gpu', 'PyPDF2',"gradio_client"], stdout=subprocess.PIPE).stdout.decode('utf-8') #<cc-cm>
-# print("pip install downloded ", sub_p_res)
-
-
-# command = 'CMAKE_ARGS="-DLLAMA_CUBLAS=on" FORCE_CMAKE=1 pip install llama-cpp-python'
-
-# sub_p_res = subprocess.run(command, shell=True, check=True)
-
-# print("llama-cpp-python GPU downloaded ",sub_p_res)
 
 from gradio_client import Client
 from langchain.document_loaders.text import TextLoader
@@ -25,7 +14,6 @@ from langchain.chains import ConversationalRetrievalChain
 from huggingface_hub import hf_hub_download
 from langchain.llms import LlamaCpp
 from langchain.chains import LLMChain
-
 import time
 import streamlit as st
 
@@ -191,10 +179,10 @@ def generate_llm_response(prompt_input):
 # User-provided prompt
 if prompt := st.chat_input("What is up?"):
     # Translate the user's input from Darija to English
-    if selected_language == "Darija":
-        translated_prompt = translate(prompt, "Moroccan Darija", "English")
-    else:
-        translated_prompt = prompt
+    #if selected_language == "Darija":
+    #     translated_prompt = translate(prompt, "Moroccan Darija", "English")
+    # else:
+    translated_prompt = prompt
 
     st.session_state.messages.append({"role": "user", "content": translated_prompt})
     with st.chat_message("user", avatar="user.png"):