Check version of streamlit

# Windows Command Prompt
venv\Scripts\activate.bat

pip install streamlit --upgrade

if selected == "Chatbot":
    st.title("Hello Bot")
    #Places for finding Emojis: https://www.webfx.com/tools/emoji-cheat-sheet/
    with st.chat_message("user"):
        st.write("Hello 👋")

if selected == "Chatbot":
    #Build a bot that mirrors your input
    #Bot will respond to your input with the same message
    #st.chat_message: Display the user's input
    #st.chat_input: Accept user input
    #session_state: Store the chat history so we can display it in the chat message container
    #What should we build?
    #(1)Two chat message containers to display messages from the user and the bot, respectively
    #(2)Way to store the chat history so we can display it in the chat message containers
    #Use a list to store the messages > Append to it every time the user or bot sends a message 
    #(Each entry in the list will be a dictionary with the following keys: role(the author of the message), and content(the message content))

    st.title("Echo Bot")
    # Initialize chat history
    if "messages" not in st.session_state:
        st.session_state.messages = []
    # Display chat messages from history on app rerun
    for message in st.session_state.messages: #For loop to iterate through the chat history and display each message in the chat message container (with the author role and message content)
        with st.chat_message(message["role"]):
            st.markdown(message["content"])
    #Check to see if the messages key is in st.session_state. 
    #If it's not, we initialize it to an empty list. 
    #This is because we'll be adding messages to the list later on, and we don't want to overwrite the list every time the app reruns

    # React to user input(:= operator to assign the user's input to the prompt variable and checked if it's not None in the same line)
    if prompt := st.chat_input("What is up?"): 
        # Display user message in chat message container
        with st.chat_message("user"):
            st.markdown(prompt)
        # Add user message to chat history
        st.session_state.messages.append({"role": "user", "content": prompt})
        #If the user has sent a message, we display the message in the chat message container and append it to the chat history.
        response = f"Echo: {prompt}"
        # Display assistant response in chat message container
        with st.chat_message("assistant"):
            st.markdown(response)
        # Add assistant response to chat history(Display the bot's response in the chat message container and add it to the history)
        st.session_state.messages.append({"role": "assistant", "content": response})

# Windows Command Prompt
venv\Scripts\activate.bat

pip install openai

import openai

openai.api_key = st.secrets["OPENAI_API_KEY"]

if "openai_model" not in st.session_state:
        st.session_state["openai_model"] = "gpt-3.5-turbo"

    if "messages" not in st.session_state:
        st.session_state.messages = []
    # Display chat messages from history on app rerun
    for message in st.session_state.messages: #For loop to iterate through the chat history and display each message in the chat message container (with the author role and message content)
        with st.chat_message(message["role"]):
            st.markdown(message["content"])
    #Check to see if the messages key is in st.session_state. 
    #If it's not, we initialize it to an empty list. 
    #This is because we'll be adding messages to the list later on, and we don't want to overwrite the list every time the app reruns

    # React to user input(:= operator to assign the user's input to the prompt variable and checked if it's not None in the same line)
    if prompt := st.chat_input("What is up?"): 
        # Display user message in chat message container
        with st.chat_message("user"):
            st.markdown(prompt)
        # Add user message to chat history
        st.session_state.messages.append({"role": "user", "content": prompt})

if selected == "Chatbot":
    #Build a bot that mirrors your input
    #Bot will respond to your input with the same message
    #st.chat_message: Display the user's input
    #st.chat_input: Accept user input
    #session_state: Store the chat history so we can display it in the chat message container
    #What should we build?
    #(1)Two chat message containers to display messages from the user and the bot, respectively
    #(2)Way to store the chat history so we can display it in the chat message containers
    #Use a list to store the messages > Append to it every time the user or bot sends a message 
    #(Each entry in the list will be a dictionary with the following keys: role(the author of the message), and content(the message content))

    st.title("Cloned ChatGPT-3.5")
    openai.api_key = st.secrets["OPENAI_API_KEY"]
    if "openai_model" not in st.session_state:
        st.session_state["openai_model"] = "gpt-3.5-turbo"
    # Initialize chat history
    if "messages" not in st.session_state:
        st.session_state.messages = []
    # Display chat messages from history on app rerun
    for message in st.session_state.messages: #For loop to iterate through the chat history and display each message in the chat message container (with the author role and message content)
        with st.chat_message(message["role"]):
            st.markdown(message["content"])
    #Check to see if the messages key is in st.session_state. 
    #If it's not, we initialize it to an empty list. 
    #This is because we'll be adding messages to the list later on, and we don't want to overwrite the list every time the app reruns

    # React to user input(:= operator to assign the user's input to the prompt variable and checked if it's not None in the same line)
    if prompt := st.chat_input("What is up?"): 
        # Display user message in chat message container
        with st.chat_message("user"):
            st.markdown(prompt)
        # Add user message to chat history
        st.session_state.messages.append({"role": "user", "content": prompt})
        # Display assistant response in chat message container
        with st.chat_message("assistant"):
            message_placeholder = st.empty()
            full_response = "" #full_response to an empy string
            for response in openai.ChatCompletion.create( #Call the openai api 
                model=st.session_state["openai_model"], #Pass model saved in the session states
                messages=[ #Conversation so far
                    {"role": m["role"], "content": m["content"]}
                    for m in st.session_state.messages
                ],
                stream=True, #Slowly keep the gpt response and simulate typing effect to make app interactive
            ):
                full_response += response.choices[0].delta.get("content", "") #Add chatgpt response to full_response string
                message_placeholder.markdown(full_response + "🐇 ") #Use message_placeholder to show the response so far
            message_placeholder.markdown(full_response) #Display full response one more time
        st.session_state.messages.append({"role": "assistant", "content": response}) #Add chatgpt response to the messages list (Ensure response is saved)

wsl --install

wsl

cd /mnt/d/스터디/QuickWebsite/

curl -fsSL https://docs.grit.io/install | bash
source /home/[Username]/.bashrc
grit install
grit apply openai

from PIL import Image
import requests
import streamlit as st
from openai import OpenAI

if selected == "Chatbot":
    #Build a bot that mirrors your input
    #Bot will respond to your input with the same message
    #st.chat_message: Display the user's input
    #st.chat_input: Accept user input
    #session_state: Store the chat history so we can display it in the chat message container
    #What should we build?
    #(1)Two chat message containers to display messages from the user and the bot, respectively
    #(2)Way to store the chat history so we can display it in the chat message containers
    #Use a list to store the messages > Append to it every time the user or bot sends a message 
    #(Each entry in the list will be a dictionary with the following keys: role(the author of the message), and content(the message content))

    st.title("Cloned ChatGPT-3.5")
    if "openai_model" not in st.session_state:
        st.session_state["openai_model"] = "gpt-3.5-turbo"
    # Initialize chat history
    if "messages" not in st.session_state:
        st.session_state.messages = []
    # Display chat messages from history on app rerun
    for message in st.session_state.messages: #For loop to iterate through the chat history and display each message in the chat message container (with the author role and message content)
        with st.chat_message(message["role"]):
            st.markdown(message["content"])
    #Check to see if the messages key is in st.session_state. 
    #If it's not, we initialize it to an empty list. 
    #This is because we'll be adding messages to the list later on, and we don't want to overwrite the list every time the app reruns

    # React to user input(:= operator to assign the user's input to the prompt variable and checked if it's not None in the same line)
    if prompt := st.chat_input("What is up?"): 
        # Display user message in chat message container
        with st.chat_message("user"):
            st.markdown(prompt)
        # Add user message to chat history
        st.session_state.messages.append({"role": "user", "content": prompt})
        # Display assistant response in chat message container
        with st.chat_message("assistant"):
            message_placeholder = st.empty()
            full_response = "" #full_response to an empy string
            for response in client.chat.completions.create(#Call the openai api 
                model=st.session_state["openai_model"], #Pass model saved in the session states
                messages=[ #Conversation so far
                    {"role": m["role"], "content": m["content"]}
                    for m in st.session_state.messages
                ],
                stream=True):
                full_response += response.choices[0].delta.get("content", "") #Add chatgpt response to full_response string
                message_placeholder.markdown(full_response + "🐇 ") #Use message_placeholder to show the response so far
            message_placeholder.markdown(full_response) #Display full response one more time
        st.session_state.messages.append({"role": "assistant", "content": response}) #Add chatgpt response to the messages list (Ensure response is saved)