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import os | |
import streamlit as st | |
from streamlit.logger import get_logger | |
from langchain.schema.messages import HumanMessage | |
from mongo_utils import get_db_client | |
from app_utils import create_memory_add_initial_message, clear_memory, get_chain, push_convo2db | |
from app_config import ISSUES, SOURCES, source2label | |
logger = get_logger(__name__) | |
openai_api_key = os.environ['OPENAI_API_KEY'] | |
memories = {'memory':{"issue": ISSUES[0], "source": SOURCES[0]}} | |
if 'previous_source' not in st.session_state: | |
st.session_state['previous_source'] = SOURCES[0] | |
if 'db_client' not in st.session_state: | |
st.session_state["db_client"] = get_db_client() | |
with st.sidebar: | |
username = st.text_input("Username", value='ivnban-ctl', max_chars=30) | |
temperature = st.slider("Temperature", 0., 1., value=0.8, step=0.1) | |
issue = st.selectbox("Select an Issue", ISSUES, index=0, | |
on_change=clear_memory, kwargs={"memories":memories, "username":username, "language":"English"} | |
) | |
supported_languages = ['English', "Spanish"] if issue == "Anxiety" else ['English'] | |
language = st.selectbox("Select a Language", supported_languages, index=0, | |
on_change=clear_memory, kwargs={"memories":memories, "username":username, "language":"English"} | |
) | |
source = st.selectbox("Select a source Model A", SOURCES, index=1, | |
format_func=source2label, | |
) | |
memories = {'memory':{"issue":issue, "source":source}} | |
changed_source = st.session_state['previous_source'] != source | |
create_memory_add_initial_message(memories, username, language, changed_source=changed_source) | |
st.session_state['previous_source'] = source | |
memoryA = st.session_state[list(memories.keys())[0]] | |
llm_chain, stopper = get_chain(issue, language, source, memoryA, temperature) | |
st.title("💬 Simulator") | |
for msg in memoryA.buffer_as_messages: | |
role = "user" if type(msg) == HumanMessage else "assistant" | |
st.chat_message(role).write(msg.content) | |
if prompt := st.chat_input(): | |
if 'convo_id' not in st.session_state: | |
push_convo2db(memories, username, language) | |
st.chat_message("user").write(prompt) | |
response = llm_chain.predict(input=prompt, stop=stopper) | |
# response = update_memory_completion(prompt, st.session_state["memory"], OA_engine, temperature) | |
st.chat_message("assistant").write(response) |