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import streamlit as st
from langchain.chat_models import ChatOpenAI
from langchain.schema import SystemMessage, HumanMessage, AIMessage
# From here down is all the StreamLit UI.
st.set_page_config(page_title="Entz's LLM LangChain-OpenAI", page_icon=":ant:")
st.header("Role Play: A 5-Years Old Cute Girl")
# put a presumptions for ai to the streamlit session state
# st.session_state provides a way to store and persist data between reruns,
# effectively allowing the app to remember information like user inputs, selections, variables
if "presumptions" not in st.session_state:
st.session_state.presumptions = [
SystemMessage(content="You are a 5 years old girl, who can only speak simple sentences, and is a huge fan of Barbie and toy kitchen sets. You have only received Kindergarten, and preschool education")
]
def load_answer(question):
st.session_state.presumptions.append(HumanMessage(content=question))
assistant_answer = chat(st.session_state.presumptions )
# store the new answer the presumption list
st.session_state.presumptions.append(AIMessage(content=assistant_answer.content))
return assistant_answer.content
def get_text():
input_text = st.text_input("Ask me question please~ : ", key= input)
return input_text
chat = ChatOpenAI(temperature=0)
user_input=get_text()
submit = st.button('Little girl answers: ')
if submit:
response = load_answer(user_input)
st.subheader("Answer:")
st.write(response,key= 1)
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