Update app.py

app.py

@@ -1,4 +1,3 @@
-
 from gradio_client import Client
 from langchain.document_loaders.text import TextLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
@@ -14,6 +13,7 @@ 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
 
@@ -111,7 +111,7 @@ qa = ConversationalRetrievalChain.from_llm(
     return_source_documents=True,
     verbose=False,
 )
-def translate(text, source, target):
+def translate(text, source="English", target="Moroccan Arabic"):
     client = Client("https://facebook-seamless-m4t-v2-large.hf.space/--replicas/2bmbx/")
     result = client.predict(
         text,
@@ -164,45 +164,36 @@ def clear_chat_history():
 st.sidebar.button('Clear Chat History', on_click=clear_chat_history)
 selected_language = st.sidebar.selectbox("Select Language", ["English", "Darija"], index=0)  # English is the default
 
-
 # Function for generating LLaMA2 response
 def generate_llm_response(prompt_input):
     res = qa(f'''{prompt_input}''')
 
     if selected_language == "Darija":
-        # Translate the model's response from English to Darija
-        translated_response = translate(res['answer'], "English", "Moroccan Darija")
+        translated_response = translate(res['answer'])
         return translated_response
     else:
         return res['answer']
 
 # 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
-
-    st.session_state.messages.append({"role": "user", "content": translated_prompt})
+    st.session_state.messages.append({"role": "user", "content": prompt})
     with st.chat_message("user", avatar="user.png"):
-        st.write(translated_prompt)
+        st.write(prompt)
 
-# Generate a new response if the last message is not from the assistant
+# Generate a new response if last message is not from assistant
 if st.session_state.messages[-1]["role"] != "assistant":
-    with st.chat_message("assistant", avatar="logo.png"):
-        with st.spinner("Thinking..."):
-            response = generate_llm_response(st.session_state.messages[-1]["content"])
-        translated_response = response  # No need to translate back to Darija for display
-        placeholder = st.empty()
-        full_response = ''
-        for item in translated_response:
-            full_response += item
-            placeholder.markdown(full_response)
-            time.sleep(0.05)
-        placeholder.markdown(full_response)
-    message = {"role": "assistant", "content": full_response}
-    st.session_state.messages.append(message)
+  with st.chat_message("assistant", avatar="logo.png"):
+      with st.spinner("Thinking..."):
+          response = generate_llm_response(st.session_state.messages[-1]["content"])
+      placeholder = st.empty()
+      full_response = ''
+      for item in response:
+          full_response += item
+          placeholder.markdown(full_response)
+          time.sleep(0.05)
+      placeholder.markdown(full_response)
+  message = {"role": "assistant", "content": full_response}
+  st.session_state.messages.append(message)
 
 # Example prompt
 with st.sidebar : 
@@ -231,4 +222,4 @@ st.sidebar.button('What is the estimated amount of money I need to start my comp
 with st.sidebar:
     st.title('Disclaimer ⚠️:')
     st.markdown('may introduce false information')
-    st.markdown('consult with a preofessionel advisor for more specific problems')
+    st.markdown('consult with a preofessionel advisor for more specific problems')