import uuid
import streamlit as st
st.set_page_config(
    page_title="Inception",
    page_icon="🔥",
    # layout="wide",
    initial_sidebar_state="collapsed",
)

from data_loaders import (
    tokenizer_decode,
    tokenizer_encode,
    humanizer_en,
    humanizer_it,
    dehumanizer_it,
    dehumanizer_en,
    bigram_model,
)

@st.cache_data()
def get_human_available_careers(lang: str = 'en'):
    careers = list(tokenizer_decode().values())
    if lang == 'it':
        return sorted([humanizer_it()[key] for key in careers[2:]])
    else:
        return sorted([humanizer_en()[key] for key in careers[2:]])


human_careers_en = get_human_available_careers()

from generate_persona import display_personal_data, generate_personal_data

from utils import check_login, report, small_report

EXPLANATION = "This will allow the user to adjust the sampling probabilities toward more or less conventional choices."
TEMP_EXPLANATION = "Low temperature results in much more conventional choices. High temperature results sampling from a broader selection of less conventional choices."
HELP_START = "Whether to start with a specific career or a random one. Some starting careers are not well represented in our sample."


def rate(pos, state):
    st.session_state["ratings"][pos] = state
    small_report()



st.image("header.svg", width=None, use_column_width="always")
st.subheader(" INDA PoC: Generating career pathways")
st.write("*an app by the INDA data science team within the Zucchetti s.p.a.*")

st.write("\n\n\n\n")

# if "login" not in st.session_state:
#    check_login()

spot = st.empty()
if "initialized" not in st.session_state:

    # Basic initialization
    st.session_state["user"] = None
    st.session_state["ratings"] = {}
    st.session_state["session_id"] = str(uuid.uuid4())

    # Load data
    spot.write("Loading tokenizer...")
    _ = tokenizer_decode()
    spot.write("Tokenizer loaded.")
    spot.write("Loading humanizer...")
    _ = humanizer_it()
    spot.write("Humanizer loaded.")
    spot.write("Loading transition matrix...")
    _ = bigram_model()
    spot.write("Transition matrix loaded.")
    spot.write("")
    st.toast("Data successfully loaded.", icon="✅")
    st.session_state.initialized = True


with st.container(border=True):
    cont_cols = st.columns([1, 2])
    with cont_cols[0]:
        use_temp = st.checkbox(
            label="Use temperature", key="checkbox_temp", value=False, help=EXPLANATION
        )
        chose_start = st.checkbox(
            label="Chose start", key="checkbox_start", value=False, help=HELP_START)
        generate = st.button("Generate Career", type="primary")

    with cont_cols[1]:
        if use_temp:
            temp = st.slider(
                label="Temperature",
                min_value=0.0,
                max_value=1.0,
                step=0.1,
                key="slider_temp",
                value=0.5,
                disabled=(not use_temp),
                help=TEMP_EXPLANATION,
            )
        if chose_start:
            start_career = st.selectbox(
                label="Chose starting career",
                options=human_careers_en,
                index=None,
                key="selectbox_start",
                placeholder="Select a starting career",
                label_visibility="collapsed",
                help=""
            )

if use_temp:
    temperature = temp
else:
    temperature = None

st.write("\n\n\n\n")


if generate:

    if 'selectbox_start' in st.session_state and st.session_state.selectbox_start is not None:
        starting_career_token = tokenizer_encode()[dehumanizer_en()[start_career]]
    else:
        starting_career_token = None

    st.session_state["career_id"] = str(uuid.uuid4())
    st.session_state["career"], st.session_state["weight"] = (
        bigram_model().generate_career(temperature=temperature, init_token=starting_career_token)
    )
    st.session_state["career_ESCO"] = [tokenizer_decode()[job] for job in st.session_state["career"]]
    st.session_state["ratings"] = {}
    num_jobs = len(st.session_state["career"]) - 2
    # generate_personal_data()

    report()


if "career" in st.session_state:

    # display_personal_data()

    st.subheader(f"A mock career pathway")

    st.write("*A repeated work title means the person had the same job for a different company*")
    cols = st.columns([0.3,0.7, 2.2, 0.9])
    #cols[0].write("*Employment*")
    cols[1].write("*ESCO code*")
    cols[2].write("*Description*")
    cols[3].write("*Is this feasible?*")

    for index, job in enumerate(st.session_state["career"][1:-1]):
        cols = st.columns([0.3,0.7, 2.2, 0.3, 0.3, 0.3])
        code = tokenizer_decode()[job]
        cols[0].write(f"#{index+1}")
        cols[1].write(code)
        cols[2].write(humanizer_en()[code])

        if index in st.session_state["ratings"]:
            conf = (
                "primary" if st.session_state["ratings"][index] == -1 else "secondary"
            )
            neutral = (
                "primary" if st.session_state["ratings"][index] == 0 else "secondary"
            )
            happy = (
                "primary" if st.session_state["ratings"][index] == 1 else "secondary"
            )
        else:
            conf, happy, neutral = "secondary", "secondary", "primary"

        cols[3].button(
            ":confused:",
            key=f"odd_job_{(index+1):02d}",
            type=conf,
            on_click=rate,
            args=(
                index,
                -1,
            ),
        )
        cols[4].button(
            ":neutral_face:",
            key=f"neutral_job_{(index+1):02d}",
            type=neutral,
            on_click=rate,
            args=(
                index,
                0,
            ),
        )

        cols[5].button(
            ":sunglasses:",
            key=f"cor_job_{(index + 1):02d}",
            type=happy,
            on_click=rate,
            args=(
                index,
                1,
            ),
        )

    st.write("\n\n\n\n\n")
    st.divider()
    st.write("\n\n")