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)