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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, are_models_alive
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, MAX_MSG_COUNT, WARN_MSG_COUT
from models.ta_models.config import CPC_LBL_OPTS, cpc_label2str, BP_LAB2STR, BP_LBL_OPTS
from models.ta_models.cpc_utils import cpc_push2db
from models.ta_models.bp_utils import bp_predict_message, bp_push2db
logger = get_logger(__name__)
temperature = 0.8
# username = "barb-chase" #"ivnban-ctl"
st.set_page_config(page_title="Conversation Simulator")
if "sent_messages" not in st.session_state:
st.session_state['sent_messages'] = 0
if not are_models_alive():
st.switch_page("pages/model_loader.py")
if "total_messages" not in st.session_state:
st.session_state['total_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.debug(f"texter name is {st.session_state['texter_name']}")
if "last_phase" not in st.session_state:
st.session_state["last_phase"] = CPC_LBL_OPTS[0]
# st.session_state["sel_phase"] = CPC_LBL_OPTS[0]
if "changed_cpc" not in st.session_state:
st.session_state["changed_cpc"] = False
if "changed_bp" not in st.session_state:
st.session_state["changed_bp"] = False
# st.session_state["sel_phase"] = st.session_state["last_phase"]
memories = {'memory':{"issue": st.session_state['issue'], "source": st.session_state['previous_source']}}
with st.sidebar:
username = st.text_input("Username", value='Dani', 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=ISSUES.index(st.session_state['issue']), 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, key="source"
)
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
st.session_state["texter_name"] = get_random_name(names_df=DEFAULT_NAMES_DF)
logger.debug(f"texter name is {st.session_state['texter_name']}")
st.session_state['previous_source'] = source
st.session_state['issue'] = issue
st.session_state['sent_messages'] = 0
st.session_state['total_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, language, source, memoryA, temperature, texter_name=st.session_state["texter_name"])
st.title("💬 Simulator")
st.session_state['total_messages'] = len(memoryA.chat_memory.messages)
for msg in memoryA.buffer_as_messages:
role = "user" if type(msg) == HumanMessage else "assistant"
st.chat_message(role).write(msg.content)
def sent_request_llm(llm_chain, prompt):
st.session_state['sent_messages'] += 1
st.chat_message("user").write(prompt)
responses = custom_chain_predict(llm_chain, prompt, stopper)
for response in responses:
st.chat_message("assistant").write(response)
# @st.dialog("Bad Practice Detected")
# def confirm_bp(bp_prediction, prompt):
# bps = [BP_LAB2STR[x['label']] for x in bp_prediction if x['score']]
# st.markdown(f"The last message was considered :red[{' and '.join(bps)}]")
# "Are you sure you want to send this message?"
# newprompt = st.text_input("Change message to:")
# "If you do not want to change leave textbox empty"
# for bp in BP_LAB2STR.keys():
# _ = st.checkbox(f"Original Message was {BP_LAB2STR[bp]}", key=f"chkbx_{bp}", value=BP_LAB2STR[bp] in bps)
# if st.button("Confirm"):
# if newprompt is not None and newprompt != "":
# prompt = newprompt
# bp_push2db(
# {bp:st.session_state[f"chkbx_{bp}"] for bp in BP_LAB2STR.keys()}
# )
# sent_request_llm(llm_chain, prompt)
# st.rerun()
if prompt := st.chat_input(disabled=st.session_state['total_messages'] > MAX_MSG_COUNT - 4): #account for next interaction
if 'convo_id' not in st.session_state:
push_convo2db(memories, username, language)
if st.session_state["sent_messages"] > 0:
if st.session_state.changed_cpc:
st.session_state["sel_phase"] = None
st.session_state.changed_cpc = False
else:
cpc_push2db(True)
if st.session_state.changed_bp:
st.session_state["sel_bp"] = None
st.session_state.changed_bp = False
else:
bp_push2db({x['label']:x['score'] for x in st.session_state['bp_prediction']})
st.session_state['context'] = llm_chain.memory.load_memory_variables({})[llm_chain.memory.memory_key]
st.session_state['last_message'] = prompt
st.session_state['bp_prediction'] = bp_predict_message(st.session_state['context'], prompt)
if any([x['score'] for x in st.session_state['bp_prediction']]):
for bp in st.session_state['bp_prediction']:
if bp["score"]:
st.toast(f"Detected {BP_LAB2STR[bp['label']]} in the last message!", icon=":material/warning:")
sent_request_llm(llm_chain, prompt)
# else:
# sent_request_llm(llm_chain, prompt)
with st.sidebar:
if "convo_id" in st.session_state:
st.write(f"Conversation ID is `{st.session_state['convo_id']}`")
st.divider()
st.markdown(f"### Total Sent Messages: :red[**{st.session_state['sent_messages']}**]")
st.markdown(f"### Total Messages: :red[**{st.session_state['total_messages']}**]")
# st.markdown()
def on_change_cpc():
cpc_push2db(False)
st.session_state.changed_cpc = True
def on_change_bp():
bp_push2db()
st.session_state.changed_bp = True
if st.session_state["sent_messages"] > 0:
_ = st.selectbox(f"""Last Human Message was considered :blue[**{
cpc_label2str(st.session_state['last_phase'])
}**]. If not please select from the following options""",
CPC_LBL_OPTS, index=None, format_func=cpc_label2str, on_change=on_change_cpc,
key="sel_phase",
)
BPs = [BP_LAB2STR[x['label']] for x in st.session_state['bp_prediction'] if x['score']]
selecttitle = f"""Last Human Message was considered :blue[**{
" and ".join(BPs)
}**].""" if len(BPs) > 0 else "Last Human Message was NOT considered Bad Practice."
_ = st.selectbox(selecttitle + " If not please select from the following options""",
BP_LBL_OPTS, index=None, format_func=lambda x: x, on_change=on_change_bp,
key="sel_bp"
)
if st.button("Score Conversation"):
st.switch_page("pages/training_adherence.py")
st.session_state['total_messages'] = len(memoryA.chat_memory.messages)
if st.session_state['total_messages'] >= MAX_MSG_COUNT:
st.toast(f"Total of {MAX_MSG_COUNT} Messages reached. Conversation Ended", icon=":material/verified:")
elif st.session_state['total_messages'] >= WARN_MSG_COUT:
st.toast(f"The conversation will end at {MAX_MSG_COUNT} Total Messages ", icon=":material/warning:")
if not are_models_alive():
st.switch_page("pages/model_loader.py")
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