Update app.py

app.py

@@ -1,9 +1,11 @@
 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
@@ -11,16 +13,19 @@ 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'
 ]
-
-server = Flask(__name__)
-
-# Create a customized version of the plotly_dark theme with a modified background color.
+# 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
@@ -195,14 +200,36 @@ theme_toggle = dmc.Tooltip(
 )
 
 styleTitle = {
-    "textAlign": "center",
-    "color": dmc.DEFAULT_THEME["colors"]["orange"][4]
+    "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"},
@@ -211,12 +238,106 @@ datadefault = [
     {"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,
+    }
 
-app = Dash(__name__, external_scripts=external_scripts, server=server, external_stylesheets=dmc.styles.ALL, on_error=custom_error_handler)
+    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(
     [
@@ -227,22 +348,42 @@ app.layout = dmc.MantineProvider(
                         dmc.Grid(
                             children=[
                                 dmc.GridCol(html.Div(
+                                    children=[
                                     dmc.MultiSelect(
-                                        label="Selectionnez vos Codes ROME",
-                                        placeholder="Select vos Codes ROME parmi la liste",
+                                        placeholder="Selectionnez vos Codes ROME",
                                         id="framework-multi-select",
                                         value=['K2105', 'L1101', 'L1202', 'L1507', 'L1508', 'L1509'],
                                         data=datadefault,
                                         w=600,
-                                        mb=10,
+                                        mt=10,
                                         styles={
-                                            "input": {"borderColor": dmc.DEFAULT_THEME["colors"]["orange"][2]},
+                                            "input": {"borderColor": "grey"},
                                             "label": {"color": dmc.DEFAULT_THEME["colors"]["orange"][4]},
                                         },
-                                    )
-                                ), span=6),
-                                dmc.GridCol(html.Div(dmc.Title(f"Le marché et les statistiques de l'emploi", order=1, size="30", my="20", style=styleTitle)), span=5),
+                                    ),
+                                    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",
@@ -341,14 +482,23 @@ app.layout = dmc.MantineProvider(
 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, theme):
+def create_repartition(array_value, selectedData, theme):
     if theme == "dark":
         template = "plotly_dark"
         paper_bgcolor = 'rgba(36, 36, 36, 1)'
@@ -368,6 +518,18 @@ def create_repartition(array_value, theme):
     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')
@@ -378,6 +540,8 @@ def create_repartition(array_value, theme):
     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"
         )
@@ -408,7 +572,7 @@ def create_repartition(array_value, theme):
     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,autosize=True).update_traces(hovertemplate=df_comp["competences"] + ' <br>Nombre : %{x}', y=[y[:100] + "..." for y in df_comp['competences']], showlegend=False)
+    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
@@ -434,7 +598,7 @@ def create_emploi(df, theme):
     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, autosize=True).update_traces(hovertemplate=df_intitule["intitule"] + ' <br>Nombre : %{x}', y=[y[:100] + "..." for y in df_intitule["intitule"]], showlegend=False)
+    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
 
@@ -553,6 +717,98 @@ def update_experience(selectedData, array_value, theme):
     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)