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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) |