app.py

import os
import datetime
import requests
import textwrap
from offres_emploi import Api
from offres_emploi.utils import dt_to_str_iso
from dash import Dash, html, dcc, callback, Output, Input, dash_table, State, _dash_renderer
import dash_bootstrap_components as dbc
import plotly.express as px
import dash_mantine_components as dmc
from dash_iconify import DashIconify
import pandas as pd
from dotenv import load_dotenv
_dash_renderer._set_react_version("18.2.0")
import plotly.io as pio
from langchain_community.llms import HuggingFaceEndpoint
from langchain_core.prompts import ChatPromptTemplate, PromptTemplate
from langchain.schema.output_parser import StrOutputParser

from flask import Flask

server = Flask(__name__)

# external JavaScript files
external_scripts = [
    'https://datacipen-eventia.hf.space/copilot/index.js'
]
# Create a customized version of the plotly_dark theme with a modified background color
custom_plotly_dark_theme = {
    "layout": {
        "paper_bgcolor": "#1E1E1E",  # Update the paper background color
        "plot_bgcolor": "#1E1E1E",   # Update the plot background color
        "font": {
            "color": "#FFFFFF"       # Update the font color
        },
        "xaxis": {
            "gridcolor": "#333333",  # Update the x-axis grid color
            "zerolinecolor": "#666666"  # Update the x-axis zero line color
        },
        "yaxis": {
            "gridcolor": "#333333",  # Update the y-axis grid color
            "zerolinecolor": "#666666"  # Update the y-axis zero line color
        }
    }
}

# Apply the customized theme to your Plotly figures
pio.templates["custom_plotly_dark"] = custom_plotly_dark_theme
pio.templates.default = "custom_plotly_dark"

load_dotenv()

def localisation():
    ListCentroids = [
        { "ID": "01", "Longitude": 5.3245259, "Latitude":46.0666003 },
        { "ID": "02", "Longitude": 3.5960246, "Latitude": 49.5519632 },
        { "ID": "03", "Longitude": 3.065278, "Latitude": 46.4002783 },
        { "ID": "04", "Longitude": 6.2237688, "Latitude": 44.1105837 },
        { "ID": "05", "Longitude": 6.2018836, "Latitude": 44.6630487 },
    	{ "ID": "06", "Longitude": 7.0755745, "Latitude":43.9463082 },
        { "ID": "07", "Longitude": 4.3497308, "Latitude": 44.7626044 },
        { "ID": "08", "Longitude": 4.6234893, "Latitude": 49.6473884 },
        { "ID": "09", "Longitude": 1.6037147, "Latitude": 42.9696091 },
        { "ID": "10", "Longitude": 4.1394954, "Latitude": 48.2963286 },
    	{ "ID": "11", "Longitude": 2.3140163, "Latitude": 43.1111427 },
    	{ "ID": "12", "Longitude": 2.7365234, "Latitude": 44.2786323 },
    	{ "ID": "13", "Longitude": 5.0515492, "Latitude": 43.5539098 },
    	{ "ID": "14", "Longitude": -0.3930779, "Latitude": 49.1024215 },
    	{ "ID": "15", "Longitude": 2.6367657, "Latitude": 44.9643217 },
    	{ "ID": "16", "Longitude": 0.180475, "Latitude": 45.706264 },
    	{ "ID": "17", "Longitude": -0.7082589, "Latitude": 45.7629699 },
    	{ "ID": "18", "Longitude": 2.5292424, "Latitude": 47.0926687 },
    	{ "ID": "19", "Longitude": 1.8841811, "Latitude": 45.3622055 },
    	{ "ID": "2A", "Longitude": 8.9906834, "Latitude": 41.8619761 },
    	{ "ID": "2B", "Longitude": 9.275489, "Latitude": 42.372014 },
    	{ "ID": "21", "Longitude": 4.7870471, "Latitude": 47.4736746 },
    	{ "ID": "22", "Longitude": -2.9227591, "Latitude": 48.408402 },
    	{ "ID": "23", "Longitude": 2.0265508, "Latitude": 46.0837382 },
    	{ "ID": "24", "Longitude": 0.7140145, "Latitude": 45.1489678 },
    	{ "ID": "25", "Longitude": 6.3991355, "Latitude": 47.1879451 },
    	{ "ID": "26", "Longitude": 5.1717552, "Latitude": 44.8055408 },
    	{ "ID": "27", "Longitude": 0.9488116, "Latitude": 49.1460288 },
    	{ "ID": "28", "Longitude": 1.2793491, "Latitude": 48.3330017 },
    	{ "ID": "29", "Longitude": -4.1577074, "Latitude": 48.2869945 },
    	{ "ID": "30", "Longitude": 4.2650329, "Latitude": 43.9636468 },
    	{ "ID": "31", "Longitude": 1.2728958, "Latitude": 43.3671081 },
    	{ "ID": "32", "Longitude": 0.4220039, "Latitude": 43.657141 },
    	{ "ID": "33", "Longitude": -0.5760716, "Latitude": 44.8406068 },
    	{ "ID": "34", "Longitude": 3.4197556, "Latitude": 43.62585 },
    	{ "ID": "35", "Longitude": -1.6443812, "Latitude": 48.1801254 },
    	{ "ID": "36", "Longitude": 1.6509938, "Latitude": 46.7964222 },
    	{ "ID": "37", "Longitude": 0.7085619, "Latitude": 47.2802601 },
    	{ "ID": "38", "Longitude": 5.6230772, "Latitude": 45.259805 },
    	{ "ID": "39", "Longitude": 5.612871, "Latitude": 46.7398138 },
    	{ "ID": "40", "Longitude": -0.8771738, "Latitude": 44.0161251 },
    	{ "ID": "41", "Longitude": 1.3989178, "Latitude": 47.5866519 },
    	{ "ID": "42", "Longitude": 4.2262355, "Latitude": 45.7451186 },
    	{ "ID": "43", "Longitude": 3.8118151, "Latitude": 45.1473029 },
    	{ "ID": "44", "Longitude": -1.7642949, "Latitude": 47.4616509 },
    	{ "ID": "45", "Longitude": 2.2372695, "Latitude": 47.8631395 },
    	{ "ID": "46", "Longitude": 1.5732157, "Latitude": 44.6529284 },
    	{ "ID": "47", "Longitude": 0.4788052, "Latitude": 44.4027215 },
    	{ "ID": "48", "Longitude": 3.4991239, "Latitude": 44.5191573 },
    	{ "ID": "49", "Longitude": -0.5136056, "Latitude": 47.3945201 },
    	{ "ID": "50", "Longitude": -1.3203134, "Latitude": 49.0162072 },
    	{ "ID": "51", "Longitude": 4.2966555, "Latitude": 48.9479636 },
    	{ "ID": "52", "Longitude": 5.1325796, "Latitude": 48.1077196 },
    	{ "ID": "53", "Longitude": -0.7073921, "Latitude": 48.1225795 },
    	{ "ID": "54", "Longitude": 6.144792, "Latitude": 48.7995163 },
    	{ "ID": "55", "Longitude": 5.2888292, "Latitude": 49.0074545 },
    	{ "ID": "56", "Longitude": -2.8746938, "Latitude": 47.9239486 },
    	{ "ID": "57", "Longitude": 6.5610683, "Latitude": 49.0399233 },
    	{ "ID": "58", "Longitude": 3.5544332, "Latitude": 47.1122301 },
    	{ "ID": "59", "Longitude": 3.2466616, "Latitude": 50.4765414 },
    	{ "ID": "60", "Longitude": 2.4161734, "Latitude": 49.3852913 },
    	{ "ID": "61", "Longitude": 0.2248368, "Latitude": 48.5558919 },
    	{ "ID": "62", "Longitude": 2.2555152, "Latitude": 50.4646795 },
    	{ "ID": "63", "Longitude": 3.1322144, "Latitude": 45.7471805 },
    	{ "ID": "64", "Longitude": -0.793633, "Latitude": 43.3390984 },
    	{ "ID": "65", "Longitude": 0.1478724, "Latitude": 43.0526238 },
    	{ "ID": "66", "Longitude": 2.5239855, "Latitude": 42.5825094 },
    	{ "ID": "67", "Longitude": 7.5962225, "Latitude": 48.662515 },
    	{ "ID": "68", "Longitude": 7.2656284, "Latitude": 47.8586205 },
    	{ "ID": "69", "Longitude": 4.6859896, "Latitude": 45.8714754 },
    	{ "ID": "70", "Longitude": 6.1388571, "Latitude": 47.5904191 },
    	{ "ID": "71", "Longitude": 4.6394021, "Latitude": 46.5951234 },
    	{ "ID": "72", "Longitude": 0.1947322, "Latitude": 48.0041421 },
    	{ "ID": "73", "Longitude": 6.4662232, "Latitude": 45.4956055 },
    	{ "ID": "74", "Longitude": 6.3609606, "Latitude": 46.1045902 },
    	{ "ID": "75", "Longitude": 2.3416082, "Latitude": 48.8626759 },
    	{ "ID": "76", "Longitude": 1.025579, "Latitude": 49.6862911 },
    	{ "ID": "77", "Longitude": 2.8977309, "Latitude": 48.5957831 },
    	{ "ID": "78", "Longitude": 1.8080138, "Latitude": 48.7831982 },
    	{ "ID": "79", "Longitude": -0.3159014, "Latitude": 46.5490257 },
    	{ "ID": "80", "Longitude": 2.3380595, "Latitude": 49.9783317 },
    	{ "ID": "81", "Longitude": 2.2072751, "Latitude": 43.8524305 },
    	{ "ID": "82", "Longitude": 1.2649374, "Latitude": 44.1254902 },
    	{ "ID": "83", "Longitude": 6.1486127, "Latitude": 43.5007903 },
    	{ "ID": "84", "Longitude": 5.065418, "Latitude": 44.0001599 },
    	{ "ID": "85", "Longitude": -1.3956692, "Latitude": 46.5929102 },
    	{ "ID": "86", "Longitude": 0.4953679, "Latitude": 46.5719095 },
    	{ "ID": "87", "Longitude": 1.2500647, "Latitude": 45.9018644 },
    	{ "ID": "88", "Longitude": 6.349702, "Latitude": 48.1770451 },
    	{ "ID": "89", "Longitude": 3.5634078, "Latitude": 47.8474664 },
    	{ "ID": "90", "Longitude": 6.9498114, "Latitude": 47.6184394 },
    	{ "ID": "91", "Longitude": 2.2714555, "Latitude": 48.5203114 },
    	{ "ID": "92", "Longitude": 2.2407148, "Latitude": 48.835321 },
    	{ "ID": "93", "Longitude": 2.4811577, "Latitude": 48.9008719 },
    	{ "ID": "94", "Longitude": 2.4549766, "Latitude": 48.7832368 },
    	{ "ID": "95", "Longitude": 2.1802056, "Latitude": 49.076488 },
    	{ "ID": "974", "Longitude": 55.536384, "Latitude": -21.115141 },
    	{ "ID": "973", "Longitude": -53.125782, "Latitude": 3.933889 },
    	{ "ID": "972", "Longitude": -61.024174, "Latitude": 14.641528 },
    	{ "ID": "971", "Longitude": -61.551, "Latitude": 16.265 }
    ]
    
    return ListCentroids

def connexion_France_Travail():
    client = Api(client_id=os.getenv('POLE_EMPLOI_CLIENT_ID'),
                client_secret=os.getenv('POLE_EMPLOI_CLIENT_SECRET'))
    return client

def API_France_Travail(romeListArray):
    client = connexion_France_Travail()
    todayDate = datetime.datetime.today()
    month, year = (todayDate.month-1, todayDate.year) if todayDate.month != 1 else (12, todayDate.year-1)
    start_dt = todayDate.replace(day=1, month=month, year=year)
    end_dt = datetime.datetime.today()
    results = []
    for k in romeListArray:
        if k[0:1] == ' ':
            k = k[1:]
        params = {"motsCles": k.replace('/', '').replace('-', '').replace(',', '').replace(' ', ','),'minCreationDate': dt_to_str_iso(start_dt),'maxCreationDate': dt_to_str_iso(end_dt),'range':'0-149'}
        try:
            search_on_big_data = client.search(params=params)
            results += search_on_big_data["resultats"]
        except:
            print("Il n'y a pas d'offres d'emploi.")
        
    results_df = pd.DataFrame(results)
    return results_df

theme_toggle = dmc.Tooltip(
    dmc.ActionIcon(
    [
        dmc.Paper(DashIconify(icon="radix-icons:sun", width=25), darkHidden=True),
        dmc.Paper(DashIconify(icon="radix-icons:moon", width=25), lightHidden=True),
    ],
    variant="transparent",
    color="yellow",
    id="color-scheme-toggle",
    size="lg",
    ms="auto",
    ),
    label="Changez de thème",
    position="left",
    withArrow=True,
    arrowSize=6,
)

styleTitle = {
    "textAlign": "center"
}
styleUSERIA = {
    "textAlign": "right",
    "marginBottom" : "5px"
}
styleSUBMITIA = {
    "marginLeft":"auto",
    "marginRight":"auto",
    "marginTop": "5px",
    "marginBottom" : "5px"
}
styleSYSIA = {
    "marginTop":"10px",
    "marginBottom":"120px",
}
styleTopvar = {
    "display": "none"
}

styleToggle = {
    "marginTop":"25px",
    "textAlign": "right",
}
styleSubmitBox = {
    "position":"fixed",
    "width": "100%",
    "top": "calc(100vh - 100px)",
    "right": "0"
}
datadefault = [
    {"value": "K2105", "label": "K2105"},
    {"value": "L1101", "label": "L1101"},
    {"value": "L1202", "label": "L1202"},
    {"value": "L1507", "label": "L1507"},
    {"value": "L1508", "label": "L1508"},
    {"value": "L1509", "label": "L1509"},
]

def custom_error_handler(err):
# This function defines what we want to happen when an exception occurs
# For now, we just print the exception to the terminal with additional text
    print(f"The app raised the following exception: {err}")
def textbox(text, box="AI", name="Philippe"):
    text = text.replace(f"{name}:", "").replace("You:", "")
    #text = textile.textile(text)
    style = {
        "max-width": "60%",
        "width": "max-content",
        "padding": "5px 10px",
        "border-radius": 25,
        "margin-bottom": 20,
    }

    if box == "user":
        style["margin-left"] = "auto"
        style["margin-right"] = 0

        #return dbc.Card(text, style=style, body=True, color="primary", inverse=True)
        return html.Div(dmc.Button(text, variant="gradient", gradient={"from": "grape", "to": "pink", "deg": 35}), style=styleUSERIA)

    elif box == "AI":
        style["margin-left"] = 0
        style["margin-right"] = "auto"

        thumbnail = html.Img(
            src=app.get_asset_url("sparkles.gif"),
            style={
                "border-radius": 50,
                "height": 36,
                "margin-right": 5,
                "float": "left",
            },
        )
        #textbox = dbc.Card(text, style=style, body=True, color="light", inverse=False)
        #textbox = dmc.Blockquote(text, style=styleSYSIA)
        textbox = dmc.Card(children=[dmc.Text(text,size="sm",c="dimmed")],withBorder=False,w="100%", style=styleSYSIA)
        return html.Div([thumbnail, textbox])

    else:
        raise ValueError("Incorrect option for `box`.")


#description = """
#Philippe is the principal architect at a condo-development firm in Paris. He lives with his girlfriend of five years in a 2-bedroom condo, with a small dog named Coco. Since the pandemic, his firm has seen a  significant drop in condo requests. As such, he’s been spending less time designing and more time on cooking,  his favorite hobby. He loves to cook international foods, venturing beyond French cuisine. But, he is eager  to get back to architecture and combine his hobby with his occupation. That’s why he’s looking to create a  new design for the kitchens in the company’s current inventory. Can you give him advice on how to do that?
#"""

# Authentication
#openai.api_key = os.getenv("OPENAI_KEY")


# Define Layout
conversation = html.Div(
    html.Div(id="display-conversation"),
    style={
        "overflow-y": "auto",
        "display": "flex",
        "height": "calc(100vh - 100px)",
        "flex-direction": "column-reverse",
    },
)

controls = dbc.InputGroup(
    children=[
        dmc.TextInput(id="user-input", placeholder="Ecrire votre requête...", w="400", style=styleSUBMITIA),
        dbc.InputGroupAddon(dmc.Button(leftSection=DashIconify("Envoyer", icon="tabler:send", width=20), id="submit"), addon_type="append", style=styleTitle),
        
        #dbc.Input(id="user-input", placeholder="Ecrire votre requête...", type="text"),
        #dbc.InputGroupAddon(dbc.Button("Submit", id="submit"), addon_type="append"),
    ],style=styleSubmitBox
)
class CustomDash(Dash):
    def interpolate_index(self, **kwargs):
        # Inspect the arguments by printing them
        return '''
        <!DOCTYPE html>
        <html>
            <head>
                <title>Dashboard des compétences</title>
            </head>
            <body>

                <div id="custom-topbar"></div>
                {app_entry}
                {config}
                {scripts}
                {renderer}
                <div id="custom-footer">My custom footer</div>
            </body>
        </html>
        '''.format(
            app_entry=kwargs['app_entry'],
            config=kwargs['config'],
            scripts=kwargs['scripts'],
            renderer=kwargs['renderer'])
        
#app = Dash(__name__, external_scripts=external_scripts, external_stylesheets=dmc.styles.ALL, on_error=custom_error_handler)
app = CustomDash(__name__, server=server, external_scripts=external_scripts, external_stylesheets=dmc.styles.ALL, on_error=custom_error_handler)

app.layout = dmc.MantineProvider(
    [
        html.Div(
            children=[
                dmc.Container(
                    children=[
                        dmc.Grid(
                            children=[
                                dmc.GridCol(html.Div(
                                    children=[
                                    dmc.MultiSelect(
                                        placeholder="Selectionnez vos Codes ROME",
                                        id="framework-multi-select",
                                        value=['K2105', 'L1101', 'L1202', 'L1507', 'L1508', 'L1509'],
                                        data=datadefault,
                                        w=600,
                                        mt=10,
                                        styles={
                                            "input": {"borderColor": "grey"},
                                            "label": {"color": dmc.DEFAULT_THEME["colors"]["orange"][4]},
                                        },
                                    ),
                                    dmc.Drawer(
                                            title="Mistral répond à vos questions sur les datas de l'emploi et des compétences.",
                                            children=[dbc.Container(
                                                            fluid=False,
                                                            children=[
                                                                dcc.Store(id="store-conversation", data=""),
                                                                html.Div(dmc.Button("Bonjour, Mistral est à votre écoute!", variant="gradient", gradient={"from": "grape", "to": "pink", "deg": 35}), style=styleUSERIA),
                                                                conversation,
                                                                dcc.Loading(html.Div(id="loading-component"),type="default"),
                                                                controls,
                                                                #dbc.Spinner(html.Div(id="loading-component")),
                                                            ],
                                                        )
                                            ],
                                            id="drawer-simple",
                                            padding="md",
                                            size="50%",
                                            position="right"
                                    ),]
                                ), span=5),
                                dmc.GridCol(html.Div(dmc.Title(f"Le marché et les statistiques de l'emploi", order=1, size="30", my="20", id="chainlit-call-fn", style=styleTitle)), span=5),
                                dmc.GridCol(html.Div(theme_toggle, style=styleToggle), span=1),
                                dmc.GridCol(html.Div(dmc.Tooltip(dmc.Button(leftSection=DashIconify(icon="tabler:sparkles", width=30), id="drawer-demo-button"), label="IA générative sur les données",position="left",withArrow=True,arrowSize=6,), style=styleToggle), span=1),
                                dmc.GridCol(html.Div(
                                    dcc.Loading(
                                        id="loadingRepartition",
                                        children=(dcc.Graph(id="figRepartition",selectedData={'points': [{'hovertext': ['01','02','03','04','05','06','07','08','09','10','11','12','13','14','15','16','17','18','19','2A','2B','21','22','23','24','25','26','27','28','29','30','31','32','33','34','35','36','37','38','39','40','41','42','43','44','45','46','47','48','49','50','51','52','53','54','55','56','57','58','59','60','61','62','63','64','65','66','67','68','69','70','71','72','73','74','75','76','77','78','79','80','81','82','83','84','85','86','87','88','89','90','91','92','93','94','95','971','972','973','974']}]})),
                                        type="default",
                                    )
                                ), span=6),
                                dmc.GridCol(html.Div(
                                    dcc.Loading(
                                        id="loadingEmplois",
                                        children=(dcc.Graph(id="figEmplois")),
                                        type="default",
                                        )
                                ), span=6),
                                dmc.GridCol(html.Div(
                                    dcc.Loading(
                                        id="loadingContrats",
                                        children=(dcc.Graph(id="figContrats")),
                                        type="default",
                                    )
                                ), span=6),
                                dmc.GridCol(html.Div(
                                    dcc.Loading(
                                        id="loadingExperiences",
                                        children=(dcc.Graph(id="figExperiences")),
                                        type="default",
                                    )
                                ), span=6),
                                dmc.GridCol(html.Div(
                                    dcc.Loading(
                                        id="loadingCompetences",
                                        children=(dcc.Graph(id="figCompetences")),
                                        type="default",
                                    )
                                ), span=6),
                                dmc.GridCol(html.Div(
                                    dcc.Loading(
                                        id="loadingTransversales",
                                        children=(dcc.Graph(id="figTransversales")),
                                        type="default",
                                    )
                                ), span=6),
                            ],
                            gutter="xs",
                        )
                    ],size="xxl",fluid=True
                ),
            ]
        )
    ],
    id="mantine-provider",
    forceColorScheme="dark",
    theme={
        "primaryColor": "indigo",
         "fontFamily": "'Inter', sans-serif",
         "components": {
             "Button": {"defaultProps": {"fw": 400}},
             "Alert": {"styles": {"title": {"fontWeight": 500}}},
             "AvatarGroup": {"styles": {"truncated": {"fontWeight": 500}}},
             "Badge": {"styles": {"root": {"fontWeight": 500}}},
             "Progress": {"styles": {"label": {"fontWeight": 500}}},
             "RingProgress": {"styles": {"label": {"fontWeight": 500}}},
             "CodeHighlightTabs": {"styles": {"file": {"padding": 12}}},
             "Table": {
                 "defaultProps": {
                     "highlightOnHover": True,
                     "withTableBorder": True,
                     "verticalSpacing": "sm",
                     "horizontalSpacing": "md",
                 }
             },
         },
         # add your colors
        "colors": {
            "deepBlue": ["#E9EDFC", "#C1CCF6", "#99ABF0"], # 10 color elements
        },
        "shadows": {
            # other shadows (xs, sm, lg) will be merged from default theme
            "md": "1px 1px 3px rgba(0,0,0,.25)",
            "xl": "5px 5px 3px rgba(0,0,0,.25)",
        },
        "headings": {
            "fontFamily": "Roboto, sans-serif",
            "sizes": {
                "h1": {"fontSize": 30},
            },
        },
    },
)
@callback(
    Output("mantine-provider", "forceColorScheme"),
    Input("color-scheme-toggle", "n_clicks"),
    State("mantine-provider", "forceColorScheme"),
    prevent_initial_call=True,
)
def switch_theme(_, theme):
    return "dark" if theme == "light" else "light"

@callback(
    Output("drawer-simple", "opened"),
    Input("drawer-demo-button", "n_clicks"),
    prevent_initial_call=True,
)
def drawer_demo(n_clicks):
    return True

@callback(
    Output(component_id='figRepartition', component_property='figure'),
    Output(component_id='figCompetences', component_property='figure'),
    Output(component_id='figTransversales', component_property='figure'),
    Input(component_id='framework-multi-select', component_property='value'),
    Input('figEmplois', 'selectedData'),
    Input("mantine-provider", "forceColorScheme"),
)
def create_repartition(array_value, selectedData, theme):
    if theme == "dark":
        template = "plotly_dark"
        paper_bgcolor = 'rgba(36, 36, 36, 1)'
        plot_bgcolor = 'rgba(36, 36, 36, 1)'
    else:
        template = "ggplot2"
        paper_bgcolor = 'rgba(255, 255, 255, 1)'
        plot_bgcolor = 'rgba(255, 255, 255, 1)'
    
    df_FT = API_France_Travail(array_value)
    df = df_FT[['intitule','typeContratLibelle','experienceLibelle','lieuTravail']].copy()
    df["lieuTravail"] = df["lieuTravail"].apply(lambda x: x['libelle']).apply(lambda x: x[0:3]).apply(lambda x: x.strip())
    df.drop(df[df['lieuTravail'] == 'Fra'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'FRA'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'Ile'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'Mar'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'Bou'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == '976'].index, inplace = True)
    
    ######## Filtre Emplois ########
    options = []
    if selectedData != None:
        if type(selectedData['points'][0]['y']) == str:
            options.append(selectedData['points'][0]['y'][:-3])
        else:
            options = selectedData['points'][0]['y'][:-3]
    else:
        options = df['intitule'].values.tolist()
    df = df[df['intitule'].isin(options)]
    
    
    ######## localisation ########
    ListCentroids = localisation()
    df_localisation = df.groupby('lieuTravail').size().reset_index(name='obs')
    df_localisation = df_localisation.sort_values(by=['lieuTravail'])
    df_localisation['longitude'] = df_localisation['lieuTravail']
    df_localisation['latitude'] = df_localisation['lieuTravail']
    df_localisation["longitude"] = df_localisation['longitude'].apply(lambda x:[loc['Longitude'] for loc in ListCentroids if loc['ID'] == x]).apply(lambda x:''.join(map(str, x)))
    df_localisation["longitude"] = pd.to_numeric(df_localisation["longitude"], downcast="float")
    df_localisation["latitude"] = df_localisation['latitude'].apply(lambda x:[loc['Latitude'] for loc in ListCentroids if loc['ID'] == x]).apply(lambda x:''.join(map(str, x)))
    df_localisation["latitude"] = pd.to_numeric(df_localisation["latitude"], downcast="float")
    
    
    res = requests.get(
            "https://raw.githubusercontent.com/codeforgermany/click_that_hood/main/public/data/france-regions.geojson"
        )
    fig_localisation = px.scatter_mapbox(df_localisation, lat="latitude", lon="longitude", height=600, template=template, title="La répartition géographique des emplois", hover_name="lieuTravail", size="obs").update_layout(
        mapbox={
            "style": "carto-positron",
            "center": {"lon": 2, "lat" : 47},
            "zoom": 4.5,
            "layers": [
                {
                    "source": res.json(),
                    "type": "line",
                    "color": "green",
                    "line": {"width": 0},
                }
            ],
        },font=dict(size=10),paper_bgcolor=paper_bgcolor,autosize=True,clickmode='event+select'
    )
    
    df_FT.dropna(subset=['qualitesProfessionnelles','formations','competences'], inplace=True)
    df_FT["competences"] = df_FT["competences"].apply(lambda x:[str(e['libelle']) for e in x]).apply(lambda x:'; '.join(map(str, x)))
    df_FT["qualitesProfessionnelles"] = df_FT["qualitesProfessionnelles"].apply(lambda x:[str(e['libelle']) + ": " + str(e['description']) for e in x]).apply(lambda x:'; '.join(map(str, x)))
    
    ######## Compétences professionnelles ########
    df_comp = df_FT
    df_comp['competences'] = df_FT['competences'].str.split(';')
    df_comp = df_comp.explode('competences')
    df_comp = df_comp.groupby('competences').size().reset_index(name='obs')
    df_comp = df_comp.sort_values(by=['obs'])
    df_comp = df_comp.iloc[-20:]
    fig_competences = px.bar(df_comp, x='obs', y='competences', orientation='h', color='obs', height=600, template=template, title="Les principales compétences professionnelles", labels={'obs':'nombre'}, color_continuous_scale="Teal", text_auto=True).update_layout(font=dict(size=10),paper_bgcolor=paper_bgcolor,plot_bgcolor=plot_bgcolor,clickmode='event+select',autosize=True).update_traces(hovertemplate=df_comp["competences"] + ' <br>Nombre : %{x}', y=[y[:100] + "..." for y in df_comp['competences']], showlegend=False)
        
    ######## Compétences transversales ########
    df_transversales = df_FT
    df_transversales['qualitesProfessionnelles'] = df_FT['qualitesProfessionnelles'].str.split(';')
    df_comptransversales = df_transversales.explode('qualitesProfessionnelles')
    df_comptransversales = df_comptransversales.groupby('qualitesProfessionnelles').size().reset_index(name='obs')
    df_comptransversales = df_comptransversales.sort_values(by=['obs'])
    df_comptransversales = df_comptransversales.iloc[-20:]
    fig_transversales = px.bar(df_comptransversales, x='obs', y='qualitesProfessionnelles', orientation='h', color='obs', height=600, template=template, title="Les principales compétences transversales", labels={'obs':'nombre'}, color_continuous_scale="Teal", text_auto=True).update_layout(font=dict(size=10),paper_bgcolor=paper_bgcolor,plot_bgcolor=plot_bgcolor,autosize=True).update_traces(hovertemplate=df_comptransversales["qualitesProfessionnelles"] + ' <br>Nombre : %{x}', y=[y[:80] + "..." for y in df_comptransversales["qualitesProfessionnelles"]], showlegend=False)
        
    return fig_localisation, fig_competences, fig_transversales

def create_emploi(df, theme):
    if theme == "dark":
        template = "plotly_dark"
        paper_bgcolor = 'rgba(36, 36, 36, 1)'
        plot_bgcolor = 'rgba(36, 36, 36, 1)'
    else:
        template = "ggplot2"
        paper_bgcolor = 'rgba(255, 255, 255, 1)'
        plot_bgcolor = 'rgba(255, 255, 255, 1)'
    ######## Emplois ########
    df_intitule = df.groupby('intitule').size().reset_index(name='obs')
    df_intitule = df_intitule.sort_values(by=['obs'])
    df_intitule = df_intitule.iloc[-25:]
    fig_intitule = px.bar(df_intitule, x='obs', y='intitule', height=600, orientation='h', color='obs', template=template, title="Les principaux emplois", labels={'obs':'nombre'}, color_continuous_scale="Teal", text_auto=True).update_layout(font=dict(size=10),paper_bgcolor=paper_bgcolor,plot_bgcolor=plot_bgcolor,clickmode='event+select',autosize=True).update_traces(hovertemplate=df_intitule["intitule"] + ' <br>Nombre : %{x}', y=[y[:100] + "..." for y in df_intitule["intitule"]], showlegend=False)
    
    return fig_intitule

def create_contrat(df, theme):
    if theme == "dark":
        template = "plotly_dark"
        paper_bgcolor = 'rgba(36, 36, 36, 1)'
    else:
        template = "ggplot2"
        paper_bgcolor = 'rgba(255, 255, 255, 1)'
    
    ######## Types de contrat ########
    df_contrat = df.groupby('typeContratLibelle').size().reset_index(name='obs')
    fig_contrat = px.pie(df_contrat, names='typeContratLibelle', values='obs', color='obs', height=600, template=template, title="Les types de contrat", labels={'obs':'nombre'}, color_discrete_sequence=px.colors.qualitative.Safe).update_traces(textposition='inside', textinfo='percent+label').update_layout(font=dict(size=10),paper_bgcolor=paper_bgcolor)
    
    return fig_contrat

def create_experience(df, theme):
    if theme == "dark":
        template = "plotly_dark"
        paper_bgcolor = 'rgba(36, 36, 36, 1)'
    else:
        template = "ggplot2"
        paper_bgcolor = 'rgba(255, 255, 255, 1)'
    ######## Expériences professionnelles ########
    df_experience = df.groupby('experienceLibelle').size().reset_index(name='obs')
    fig_experience = px.pie(df_experience, names='experienceLibelle', values='obs', color='obs', height=600, template=template, title="Les expériences professionnelles", labels={'obs':'nombre'}, color_discrete_sequence=px.colors.qualitative.Safe).update_traces(textposition='inside', textinfo='percent+label').update_layout(font=dict(size=10),paper_bgcolor=paper_bgcolor)
    
    return fig_experience

@callback(
    Output(component_id='figEmplois', component_property='figure'),
    Input('figRepartition', 'selectedData'),
    Input(component_id='framework-multi-select', component_property='value'),
    Input("mantine-provider", "forceColorScheme"),
)

def update_emploi(selectedData, array_value, theme):
    options = []
    if selectedData != None:
        if type(selectedData['points'][0]['hovertext']) == str:
            options.append(selectedData['points'][0]['hovertext'])
        else:
            options = selectedData['points'][0]['hovertext']
    else:
        options = ['01','02','03','04','05','06','07','08','09','10','11','12','13','14','15','16','17','18','19','2A','2B','21','22','23','24','25','26','27','28','29','30','31','32','33','34','35','36','37','38','39','40','41','42','43','44','45','46','47','48','49','50','51','52','53','54','55','56','57','58','59','60','61','62','63','64','65','66','67','68','69','70','71','72','73','74','75','76','77','78','79','80','81','82','83','84','85','86','87','88','89','90','91','92','93','94','95','971','972','973','974']
    
    df_FT = API_France_Travail(array_value)
    df = df_FT[['intitule','typeContratLibelle','experienceLibelle','lieuTravail']].copy()
    df["lieuTravail"] = df["lieuTravail"].apply(lambda x: x['libelle']).apply(lambda x: x[0:3]).apply(lambda x: x.strip())
    df.drop(df[df['lieuTravail'] == 'Fra'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'FRA'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'Ile'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'Mar'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'Bou'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == '976'].index, inplace = True)
    df = df[df['lieuTravail'].isin(options)]
    return create_emploi(df, theme)

@callback(
    Output(component_id='figContrats', component_property='figure'),
    Input('figRepartition', 'selectedData'),
    Input(component_id='framework-multi-select', component_property='value'),
    Input("mantine-provider", "forceColorScheme"),
)

def update_contrat(selectedData, array_value, theme):
    options = []
    if selectedData != None:
        if type(selectedData['points'][0]['hovertext']) == str:
            options.append(selectedData['points'][0]['hovertext'])
        else:
            options = selectedData['points'][0]['hovertext']
    else:
        options = ['01','02','03','04','05','06','07','08','09','10','11','12','13','14','15','16','17','18','19','2A','2B','21','22','23','24','25','26','27','28','29','30','31','32','33','34','35','36','37','38','39','40','41','42','43','44','45','46','47','48','49','50','51','52','53','54','55','56','57','58','59','60','61','62','63','64','65','66','67','68','69','70','71','72','73','74','75','76','77','78','79','80','81','82','83','84','85','86','87','88','89','90','91','92','93','94','95','971','972','973','974']
    
    df_FT = API_France_Travail(array_value)
    df = df_FT[['intitule','typeContratLibelle','experienceLibelle','lieuTravail']].copy()
    df["lieuTravail"] = df["lieuTravail"].apply(lambda x: x['libelle']).apply(lambda x: x[0:3]).apply(lambda x: x.strip())
    df.drop(df[df['lieuTravail'] == 'Fra'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'FRA'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'Ile'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'Mar'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'Bou'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == '976'].index, inplace = True)
    df = df[df['lieuTravail'].isin(options)]
        
    return create_contrat(df, theme)

@callback(
    Output(component_id='figExperiences', component_property='figure'),
    Input('figRepartition', 'selectedData'),
    Input(component_id='framework-multi-select', component_property='value'),
    Input("mantine-provider", "forceColorScheme"),
)

def update_experience(selectedData, array_value, theme):
    options = []
    if selectedData != None:
        if type(selectedData['points'][0]['hovertext']) == str:
            options.append(selectedData['points'][0]['hovertext'])
        else:
            options = selectedData['points'][0]['hovertext']
    else:
        options = ['01','02','03','04','05','06','07','08','09','10','11','12','13','14','15','16','17','18','19','2A','2B','21','22','23','24','25','26','27','28','29','30','31','32','33','34','35','36','37','38','39','40','41','42','43','44','45','46','47','48','49','50','51','52','53','54','55','56','57','58','59','60','61','62','63','64','65','66','67','68','69','70','71','72','73','74','75','76','77','78','79','80','81','82','83','84','85','86','87','88','89','90','91','92','93','94','95','971','972','973','974']
    
    df_FT = API_France_Travail(array_value)
    df = df_FT[['intitule','typeContratLibelle','experienceLibelle','lieuTravail']].copy()
    df["lieuTravail"] = df["lieuTravail"].apply(lambda x: x['libelle']).apply(lambda x: x[0:3]).apply(lambda x: x.strip())
    df.drop(df[df['lieuTravail'] == 'Fra'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'FRA'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'Ile'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'Mar'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == 'Bou'].index, inplace = True)
    df.drop(df[df['lieuTravail'] == '976'].index, inplace = True)
    df = df[df['lieuTravail'].isin(options)]
    
    return create_experience(df, theme)

########### IA Chatbot ###########
@app.callback(
    Output("display-conversation", "children"), [Input("store-conversation", "data")]
)
def update_display(chat_history):
    return [
        textbox(x, box="user") if i % 2 == 0 else textbox(x, box="AI")
        for i, x in enumerate(chat_history.split("<split>")[:-1])
    ]


@app.callback(
    Output("user-input", "value"),
    [Input("submit", "n_clicks"), Input("user-input", "n_submit")],
)
def clear_input(n_clicks, n_submit):
    return ""

@app.callback(
    [Output("store-conversation", "data"), Output("loading-component", "children")],
    [Input("submit", "n_clicks"), Input("user-input", "n_submit")],
    [State("user-input", "value"), State("store-conversation", "data")],
    Input(component_id='framework-multi-select', component_property='value'),
)
def run_chatbot(n_clicks, n_submit, user_input, chat_history, array_value):
    if n_clicks == 0 and n_submit is None:
        return "", None

    if user_input is None or user_input == "":
        return chat_history, None

    df_FT = API_France_Travail(array_value)
    
    df_FT_Select = df_FT[['intitule','typeContratLibelle','experienceLibelle','competences','description','qualitesProfessionnelles','salaire','lieuTravail','formations']].copy()
    list_FT = df_FT_Select.values.tolist()
    context = ''
    for i in range(0,len(list_FT)):
        context += "\n✔️ Emploi : " + str(list_FT[i][0]) + ";\n◉ Contrat : " + str(list_FT[i][1]) + ";\n◉ Compétences professionnelles : " + str(list_FT[i][3]) + ";\n" + "◉ Salaire : " + str(list_FT[i][6]) + ";\n◉ Qualification : " + str(list_FT[i][5]).replace("'libelle'","\n• 'libelle") + ";\n◉ Localisation : " + str(list_FT[i][7]) + ";\n◉ Expérience : " + str(list_FT[i][2]) + ";\n◉ Niveau de qualification : " + str(list_FT[i][8]) + ";\n◉ Description de l'emploi : " + str(list_FT[i][4]) + "\n"
        #context = df_FT.to_string(index=False)
    template = """<s>[INST] Vous êtes un ingénieur pédagogique de l'enseignement supérieur et vous êtes doué pour faire des analyses des formations de l'enseignement supérieur et de faire le rapprochement entre les compétences académiques et les compétences professionnelles attendues par le marché de l'emploi et les les recruteurs, en fonction des critères définis ci-avant. En fonction des informations suivantes et du contexte suivant seulement et strictement, répondez en langue française strictement à la question ci-dessous, en 5000 mots au moins. Lorsque cela est possible, cite les sources du contexte. Si vous ne pouvez pas répondre à la question sur la base des informations, dites que vous ne trouvez pas de réponse ou que vous ne parvenez pas à trouver de réponse. Essayez donc de comprendre en profondeur le contexte et répondez uniquement en vous basant sur les informations fournies. Ne générez pas de réponses non pertinentes.
    Répondez à la question ci-dessous à partir du contexte ci-dessous :
    {context}
    {question} [/INST] </s>
    """
    context_p = context[:28500]
    name = "Mistral"
    chat_history += f"Vous: {user_input}<split>{name}:"

    model_input = template + chat_history.replace("<split>", "\n")
    #model_input = template
    
    prompt = PromptTemplate(template=model_input, input_variables=["question","context"])
    
    #prompt = dedent(
    #    f"""
    #{description}

    #Vous: Bonjour {name}!
    #{name}: Bonjour! Ravi de parler avec vous aujourd'hui.
    #"""
    #)

    # First add the user input to the chat history
    
    os.environ['HUGGINGFACEHUB_API_TOKEN'] = os.environ['HUGGINGFACEHUB_API_TOKEN']
    #repo_id = "mistralai/Mistral-7B-Instruct-v0.3"
    repo_id = "mistralai/Mixtral-8x7B-Instruct-v0.1"
    #repo_id = "microsoft/Phi-3.5-mini-instruct"
    #mistral_url = "https://api-inference.huggingface.co/models/mistralai/Mixtral-8x22B-Instruct-v0.1"
    llm = HuggingFaceEndpoint(
        repo_id=repo_id, task="text2text-generation", max_new_tokens=8000, temperature=0.001, streaming=True
    )
    model_output = ""
    chain = prompt | llm
    for s in chain.stream({"question":user_input,"context":context_p}):
        model_output = model_output + s
        print(s, end="", flush=True)
    
  
  #response = openai.Completion.create(
    #    engine="davinci",
    #    prompt=model_input,
    #    max_tokens=250,
    #    stop=["You:"],
    #    temperature=0.9,
    #)
    #model_output = response.choices[0].text.strip()

    chat_history += f"{model_output}<split>"
        
    return chat_history, None

if __name__ == '__main__':
    app.run_server(debug=True)