Update app.py

app.py

@@ -54,19 +54,29 @@ embeddings = model_norm
 db = FAISS.load_local(db_path,embeddings)
 print('Prompt Chain')
 
-custom_prompt_template = """You are a helpful bot designd for MLSC TIET that is Microsoft Student Learn Chapter,TIET which a technical society for thir website your task is to answer all queries about MLSC every answer you provide should be i context of MLSC if any question is not in that context then yyou should ecline that question by saying 'It is out of context',if you don't know the answer don't try to make it up just politely decline that question,you can extrapolayte the things a little just to be more informative but dont sound boasty and exaggerating say something else out of the context of the document,don't answer any questions that pertain to any specific persons and if questions about roles demnad names of position holders of MLSC give a general description of role instead of person
-You can accept some basic greetings to interact with the user but be sure to remisn in context of MLSC only
-Context: {context}
-Question: {question}
+
+custom_prompt_template = """You are a helpful bot designd for MLSC TIET that is Microsoft Student Learn Chapter,TIET which a technical society for thir website your task is to answer all queries about MLSC every answer you provide should be i context of MLSC if any question is not in that context then yyou should ecline that question by saying 'Sorry,I cannot help with that',if you don't know the answer don't try to make it up just politely decline that question,you can extrapolayte the things a little just to be more informative but dont sound boasty and exaggerating say something else out of the context of the document,don't answer any questions that pertain to any specific persons and if questions about roles demnad names of position holders of MLSC give a general description of role instead of person
+You can accept some basic greetings to interact with the user but be sure to remain in context of MLSC only
+Use the following context (delimited by <ctx></ctx>) and the chat history (delimited by <hs></hs>) to answer the question:
+------
+<ctx>
+{context}
+</ctx>
+------
+<hs>
+{history}
+</hs>
+------
+{question}
 
 Only return the helpful answer below and nothing else.
 Helpful answer:
 """
 
 prompt = PromptTemplate(template=custom_prompt_template,
-                            input_variables=['context', 'question'])
+                            input_variables=['history','context', 'question'])
 
-memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
+# memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
 
 
 
@@ -86,21 +96,24 @@ qa_chain = RetrievalQA.from_chain_type(llm=llm2,
                                       chain_type='stuff',
                                       retriever=db.as_retriever(search_kwargs={'k': 5}),
                                       return_source_documents=False,
-                                      chain_type_kwargs={'prompt': prompt})
+                                      chain_type_kwargs={'prompt': prompt
+                                                         ,'memory' : ConversationBufferMemory(
+                                              memory_key="history",
+                                          input_key = "question")})
 history_df = pd.DataFrame(columns = ['Question','Answer'])
 def qa_bot(query):
-  global history_df
   response = qa_chain({'query': query})
-  print(response)
-  response_df = pd.DataFrame.from_dict([response])
-  response_df.rename(columns = {'query' : 'Question','result' : 'Answer'},inplace = True)
-  history_df = pd.concat([history_df,response_df])
-  history_df.reset_index(drop = True,inplace = True)
-  history_df.to_csv('./responses.csv')
-  print(history_df)
   return (response['result'])
 
-st.title("MLSCBot")
+st.markdown("<h1 style='text-align: center; color: white; font: Charcuterie'>MLSCBot</h1>", unsafe_allow_html=True)
+hide_streamlit_style = """
+            <style>
+            #MainMenu {visibility: hidden;}
+            header {visibility: hidden;}
+            footer {visibility: hidden;}
+            </style>
+            """
+st.markdown(hide_streamlit_style, unsafe_allow_html=True)
 st.image('./banner.png',use_column_width=True)
 if "messages" not in st.session_state:
     st.session_state.messages = []