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import openai
import os
import streamlit as st
from langchain.schema.messages import HumanMessage
from utils import create_memory_add_initial_message, clear_memory, get_chain
openai_api_key = os.environ['OPENAI_API_KEY']
memories = ['memory']
with st.sidebar:
temperature = st.slider("Temperature", 0., 1., value=0.8, step=0.1)
issue = st.selectbox("Select an Issue", ['Anxiety','Suicide'], index=0,
on_change=clear_memory, args=(memories,)
)
supported_languages = ['English', "Spanish"] if issue == "Anxiety" else ['English']
language = st.selectbox("Select a Language", supported_languages, index=0,
on_change=clear_memory, args=(memories,)
)
source = st.selectbox("Select a source Model A", ['OpenAI GPT3.5','Finetuned OpenAI'], index=1,
on_change=clear_memory, args=(memories,)
)
create_memory_add_initial_message(memories, language)
llm_chain = get_chain(issue, language, source, st.session_state[memories[0]], temperature)
st.title("💬 Simulator")
for msg in st.session_state[memories[0]].buffer_as_messages:
role = "user" if type(msg) == HumanMessage else "assistant"
st.chat_message(role).write(msg.content)
if prompt := st.chat_input():
st.chat_message("user").write(prompt)
response = llm_chain.predict(input=prompt, stop="helper:")
# response = update_memory_completion(prompt, st.session_state["memory"], OA_engine, temperature)
st.chat_message("assistant").write(response) |