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import os
import streamlit as st
from streamlit.logger import get_logger
from langchain.schema.messages import HumanMessage
from utils.mongo_utils import get_db_client
from utils.app_utils import create_memory_add_initial_message, get_random_name, DEFAULT_NAMES_DF
from utils.memory_utils import clear_memory, push_convo2db
from utils.chain_utils import get_chain, custom_chain_predict
from app_config import ISSUES, SOURCES, source2label, issue2label
logger = get_logger(__name__)
openai_api_key = os.environ['OPENAI_API_KEY']
temperature = 0.8
# username = "barb-chase" #"ivnban-ctl"
if "sent_messages" not in st.session_state:
st.session_state['sent_messages'] = 0
if "issue" not in st.session_state:
st.session_state['issue'] = ISSUES[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()
if 'texter_name' not in st.session_state:
st.session_state["texter_name"] = get_random_name(names_df=DEFAULT_NAMES_DF)
logger.info(f"texter name is {st.session_state['texter_name']}")
memories = {'memory':{"issue": st.session_state['issue'], "source": st.session_state['previous_source']}}
with st.sidebar:
username = st.text_input("Username", value='Barbara', max_chars=30)
if 'counselor_name' not in st.session_state:
st.session_state["counselor_name"] = username #get_random_name(names_df=DEFAULT_NAMES_DF)
# temperature = st.slider("Temperature", 0., 1., value=0.8, step=0.1)
issue = st.selectbox("Select a Scenario", ISSUES, index=0, format_func=issue2label,
on_change=clear_memory, kwargs={"memories":memories, "username":username, "language":"English"}
)
supported_languages = ['en', "es"] if issue == "Anxiety" else ['en']
language = st.selectbox("Select a Language", supported_languages, index=0,
format_func=lambda x: "English" if x=="en" else "Spanish",
on_change=clear_memory, kwargs={"memories":memories, "username":username, "language":"English"}
)
source = st.selectbox("Select a source Model A", SOURCES, index=0,
format_func=source2label,
)
st.markdown(f"### Previous Prompt Count: :red[**{st.session_state['sent_messages']}**]")
changed_source = any([
st.session_state['previous_source'] != source,
st.session_state['issue'] != issue,
st.session_state['counselor_name'] != username,
])
if changed_source:
st.session_state["counselor_name"] = username #get_random_name(names_df=DEFAULT_NAMES_DF)
st.session_state["texter_name"] = get_random_name(names_df=DEFAULT_NAMES_DF)
st.session_state['previous_source'] = source
st.session_state['issue'] = issue
st.session_state['sent_messages'] = 0
create_memory_add_initial_message(memories,
issue,
language,
changed_source=changed_source,
counselor_name=st.session_state["counselor_name"],
texter_name=st.session_state["texter_name"])
st.session_state['previous_source'] = source
memoryA = st.session_state[list(memories.keys())[0]]
# issue only without "." marker for model compatibility
llm_chain, stopper = get_chain(issue.split(".")[0], language, source, memoryA, temperature, texter_name=st.session_state["texter_name"])
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():
st.session_state['sent_messages'] += 1
if 'convo_id' not in st.session_state:
push_convo2db(memories, username, language)
st.chat_message("user").write(prompt)
responses = custom_chain_predict(llm_chain, prompt, stopper)
# responses = llm_chain.predict(input=prompt, stop=stopper)
# response = update_memory_completion(prompt, st.session_state["memory"], OA_engine, temperature)
for response in responses:
st.chat_message("assistant").write(response) |