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, update_convo
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, modify_last_human_message
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)
    
    transcript = memoryA.load_memory_variables({})[memoryA.memory_key]
    update_convo(st.session_state["db_client"], st.session_state["convo_id"], transcript)

# @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)
        modify_last_human_message(memoryA, st.session_state['sel_phase'])
        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")