Update pages/3_chat.py

pages/3_chat.py

@@ -7,6 +7,7 @@ import gspread
 import torch
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 
+from googletrans import Translator
 
 # from langchain.vectorstores import Chroma
 from langchain.vectorstores import FAISS
@@ -59,7 +60,8 @@ def load_conversational_qa_memory_retriever():
     return conversational_qa_memory_retriever, question_generator
 
 def new_retrieve_answer():
-    prompt_answer=  st.session_state.my_text_input + ". Try to be elaborate and informative in your answer."
+    translated_to_eng = thai_to_eng(st.session_state.my_text_input).text 
+    prompt_answer=  translated_to_eng + ". Try to be elaborate and informative in your answer."
     answer = conversational_qa_memory_retriever({"question": prompt_answer })
 
     print(f"condensed quesion : {question_generator.run({'chat_history': answer['chat_history'], 'question' : prompt_answer})}")
@@ -71,12 +73,19 @@ def new_retrieve_answer():
 
     st.session_state.my_text_input = ""
 
-    return answer['answer'][6:] #this positional slicing helps remove "<pad> " at the beginning
+    return eng_to_thai(answer['answer']).text #this positional slicing helps remove "<pad> " at the beginning
     
 def clean_chat_history():
     st.session_state.chat_history = []
     conversational_qa_memory_retriever.memory.chat_memory.clear() #add this to remove
 
+def thai_to_eng(text):
+    translated = translator.translate(text, src='th', dest ='en')
+    return translated
+
+def eng_to_thai(text):
+    translated = translator.translate(text, src='en', dest ='th')
+    return translated
 
 if "history" not in st.session_state: #this one is for the google sheet logging
     st.session_state.history = []
@@ -89,7 +98,7 @@ if "chat_history" not in st.session_state: #this one is to pass previous message
 llm_model =  st.session_state['model']
 vector_database =  st.session_state['faiss_db']
 conversational_qa_memory_retriever, question_generator = load_conversational_qa_memory_retriever()
-
+translator = Translator()
 
 
 print("all load done")