Delete app_simplified.py

app_simplified.py

@@ -1,102 +0,0 @@
-
-# Importing necessary modules and setting up environment variables
-from langchain_openai import OpenAI
-from langchain.chains import ConversationChain
-from langchain.chains.conversation.memory import (ConversationBufferMemory,
-                                                  ConversationSummaryMemory,
-                                                  ConversationBufferWindowMemory
-                                                  )
-import tiktoken
-from langchain.memory import ConversationTokenBufferMemory
-import streamlit as st
-from streamlit_chat import message
-import os
-
-
-
-# Initializing session state variables
-if 'conversation' not in st.session_state:
-    st.session_state['conversation'] =None
-if 'messages' not in st.session_state:
-    st.session_state['messages'] =[]
-#if 'API_Key' not in st.session_state:
-    #st.session_state['API_Key'] =''
-
-# Setting up the page title and header
-st.set_page_config(page_title="Chat GPT Clone", page_icon=":robot_face:")
-st.markdown("<h1 style='text-align: center;'>How can I assist you? </h1>", unsafe_allow_html=True)
-st.sidebar.title("😎")
-#st.session_state['API_Key']= st.sidebar.text_input("What's your API key?",type="password")
-summarise_button = st.sidebar.button("Summarise the conversation", key="summarise")
-if summarise_button:
-    summarise_placeholder = st.sidebar.write("Nice chatting with you my friend ❤️:\n\n"+st.session_state['conversation'].memory.buffer)
-
-# Function to get response from the model
-def getresponse(userInput):
-    """
-    This function takes user input and api key as arguments, and returns the model's response.
-    """
-    if st.session_state['conversation'] is None:
-        llm = OpenAI(
-            temperature=0,
-            #openai_api_key from spaces secret
-            #openai_api_key=api_key,
-            model_name='gpt-3.5-turbo-instruct'
-        )
-        #Creating a new conversation chain
-        #ConversationChain is a class that handles the conversation between the user and the model
-        st.session_state['conversation'] = ConversationChain(
-            llm=llm,
-            verbose=True,
-            memory=ConversationSummaryMemory(llm=llm)
-        )
-    #
-    response=st.session_state['conversation'].predict(input=userInput)
-    print(st.session_state['conversation'].memory.buffer)
-    return response
-
-# Function to clear the conversation
-def clear():
-    """
-    This function clears the conversation and messages from the session state.
-    """
-    if st.session_state['conversation']:
-        st.session_state['conversation'].memory.clear()
-        st.session_state['messages'] =[]
-
-
-# -- GUI --
-
-# Setting up containers for user input and model response
-response_container = st.container()
-container = st.container()
-
-
-
-# Setting up the user input form
-with container:
-    with st.form(key='my_form', clear_on_submit=True):
-        user_input = st.text_area("Your question goes here:", key='input', height=100)
-        col1, col2 = st.columns(2)
-        with col1:
-            submit_button = st.form_submit_button(label='Send')
-        with col2:
-            clear_button = st.form_submit_button(label="Clear")
-
-        # Handling form submission
-        if submit_button:
-            st.session_state['messages'].append(user_input)
-            model_response=getresponse(user_input)
-            st.session_state['messages'].append(model_response)
-
-            # Displaying the conversation
-            with response_container:
-                for i in range(len(st.session_state['messages'])):
-                        if (i % 2) == 0:
-                            message(st.session_state['messages'][i], is_user=True, key=str(i) + '_user')
-                        else:
-                            message(st.session_state['messages'][i], key=str(i) + '_AI')
-
-        # Handling clear button click
-        if clear_button:
-            clear()