deploiement de l'application

.gitignore

@@ -0,0 +1 @@
+.env

Accueil.py

@@ -0,0 +1,43 @@
+# pip install streamlit
+import streamlit as st
+import components.logo as logo
+import components.identification_aws as authenticate
+
+# Logo de la page
+my_logo = logo.add_logo(logo_path="logo_digitalixsa.png", width=100, height=100)
+st.image(my_logo)
+
+# Titre de la page
+st.title("TRANSCRIPTION AUDIO AUTOMATIQUE DIGITALIX")
+st.write("# Bienvenue! 👋")
+st.markdown(
+    """
+    Transcrivez facilement vos fichiers audio en texte avec notre application.
+    Il vous suffit de télécharger votre fichier audio et nous nous occupons du reste
+    """
+)
+st.write(
+        """
+        ## Comment faire la transcription?
+
+    - Sélectionner votre fichier audio à transcrire (dans la partie "charger l'audio", appuyer sur "Browse files", 
+    choisir l'audio et attendre son chargement sur le site)
+    - Cliquer sur le bouton "Transcrire l'audio à gauche de la page"
+    - Attender que la transcription automatique soit effectuée
+    - Consultez le texte transcrit à l'écran et télécharger-le si nécessaire
+    - Formats de fichiers audio pris en charge : MP3,WAV,M4A.
+
+    ### Confidentialité : 
+    Nous comprenons l'importance de la confidentialité de vos données. 
+    Votre fichier audio est utilisé uniquement pour la transcription et est supprimé de nos serveurs après le processus de transcription
+    Amuser-vous! 
+    """
+    )
+
+# Check authentication
+authenticate.set_st_state_vars()
+# Add login/logout buttons
+if st.session_state["authenticated"]:
+    authenticate.button_logout()
+else:
+    authenticate.button_login()

README.md

@@ -5,7 +5,7 @@ colorFrom: green
 colorTo: indigo
 sdk: streamlit
 sdk_version: 1.21.0
-app_file: app.py
+app_file: Accueil.py
 pinned: false
 license: mit
 ---

components/.env.exemple

@@ -0,0 +1,4 @@
+COGNITO_DOMAIN = "https://myappauthentication.auth.us-east-1.amazoncognito.com"
+CLIENT_ID = "xyz"
+CLIENT_SECRET = "secret-secret"
+APP_URI = "http://localhost:8501/"

components/fonctions_transcription.py

@@ -0,0 +1,267 @@
+# pip install streamlit
+import streamlit as st
+import soundfile as sf
+import json
+import datetime
+from datetime import datetime as date
+from datetime import timedelta as td
+import math
+import pandas as pd
+import plotly.express as px
+
+# # Chargement du fichier des utilisateurs
+# with open("users_info.json", 'r') as file:
+#     dict_user = json.load(file)
+
+# # Logo de la page
+# my_logo = logo.add_logo(logo_path="logo-digitalix.png", width=100, height=100)
+# st.image(my_logo)
+
+# # Titre de la page
+# st.title("TRANSCRIPTION AUDIO AUTOMATIQUE DIGITALIX")
+# st.write("# Bienvenue! 👋")
+# st.markdown(
+#     """
+#     Transcrivez facilement vos fichiers audio en texte avec notre application.
+#     Il vous suffit de télécharger votre fichier audio et nous nous occupons du reste
+#     """
+# )
+
+
+# # Check authentication
+# authenticate.set_st_state_vars()
+# # Add login/logout buttons
+# if st.session_state["authenticated"]:
+#     authenticate.button_logout()
+# else:
+#     authenticate.button_login()
+
+# # user info 
+# auth_code = st.session_state["auth_code"]
+# user_info = st.session_state["user_info"]
+# maintenant = datetime.datetime.now()
+# username = user_info['username']
+# user_pool_name = 'transcription_streamlit'
+
+# # add user to users_dict and group free
+# if user_info['username'] not in dict_user.keys():
+#     dict_user[user_info['username']] = {"email": user_info['email'],
+#                                         "durees_audio_sec":[],
+#                                         "date_inscription":str(maintenant),
+#                                         "dates_transcription":[],
+#                                         "abonnement":1}
+#     #group_name = 'utilisateurs_gratuits'
+#     # get user pool id 
+#     #user_pool_id = authenticate.get_user_pool_id(user_pool_name)
+#     #print("User Pool ID:", user_pool_id)
+#     #authenticate.add_user_to_group(user_pool_id, username, group_name)
+
+# # Calcul annee-mois de trascription
+# Year = maintenant.year
+# Month = maintenant.month
+# Year_Month = str(Year) + '_' + str(Month).zfill(2)
+
+# #Definition quota utilisation
+# quota_20H = 1000
+
+
+#  # Pour des groupes d'utilisateurs   
+# if (st.session_state["authenticated"] and "utilisateurs_sidwaya" in st.session_state["user_cognito_groups"]):
+#     #print("Code authentification:",auth_code)
+#     #print("information utilisateur:",user_info)
+
+#     st.write(
+#         """
+#         ## Comment faire la transcription?
+
+#     - Sélectionner votre fichier audio à transcrire (dans la partie "charger l'audio", appuyer sur "Browse files", 
+#     choisir l'audio et attendre son chargement sur le site)
+#     - Cliquer sur le bouton "Transcrire l'audio à gauche de la page"
+#     - Attender que la transcription automatique soit effectuée
+#     - Consultez le texte transcrit à l'écran et télécharger-le si nécessaire
+#     - Formats de fichiers audio pris en charge : MP3,WAV,M4A. 
+    
+#     ### Confidentialité : 
+#     Nous comprenons l'importance de la confidentialité de vos données. 
+#     Votre fichier audio est utilisé uniquement pour la transcription et est supprimé de nos serveurs après le processus de transcription
+#     Amuser-vous!"""
+#     )
+
+def graphique_utilisation(data, username, annee_mois):
+    # Copie des données
+    dict_user = data
+    # Transformation en dataframe
+    df_user = pd.DataFrame(dict_user).T.reset_index()
+    df_user.rename(columns={"index":"usernames"},inplace = True)
+
+    # Separation des lignes de listes en plusieurs lignes pour les colonees duree_audio_sec et dates_transcription
+    df_duree = df_user.drop(['dates_transcription'],axis=1) 
+    df_duree = df_duree.explode('durees_audio_sec')
+    df_duree = df_duree.reset_index(drop=True)
+
+    df_transcription = df_user.drop(['durees_audio_sec'],axis=1)
+    df_transcription = df_transcription.explode('dates_transcription')
+    df_transcription = df_transcription.reset_index(drop=True)
+
+    # Regroupement des dataframes
+    df_user = df_duree.copy()
+    df_user["dates_transcription"] = df_transcription["dates_transcription"]
+
+    df_user['date_inscription'] = pd.to_datetime(df_user['date_inscription'],format = "%Y-%m-%d %H:%M:%S.%f")
+    df_user['dates_transcription'] = pd.to_datetime(df_user['dates_transcription'],format = "%Y-%m-%d %H:%M:%S.%f")
+
+    # Calcul annee-mois de trascription
+    df_user['Year'] = df_user['dates_transcription'].dt.year
+    df_user['Month'] = df_user['dates_transcription'].dt.month
+    df_user['Year_Month'] = df_user['Year'].astype(str) + '_' + df_user['Month'].astype(str).str.zfill(2)
+
+    # Selection utilisateur et mois d'utilisation
+     
+    a =df_user[(df_user["usernames"] == username) & (df_user["Year_Month"] == annee_mois)]
+    a["Consommation_heures"] = a["durees_audio_sec"].cumsum()
+    a["Consommation_heures"] = a["Consommation_heures"].values / 3600
+    #print(a["Consommation_heures"])
+    fig = px.line(a, x='dates_transcription', y='Consommation_heures')
+
+    # Ajouter la limite de temps 20H = 72000 s 
+    fig.add_shape(type="line",
+                x0=fig['data'][0]['x'][0],
+                x1=fig['data'][0]['x'][-1],
+                y0=20,
+                y1=20,
+                line=dict(color='red', width=2, dash='dash'))
+    
+    # Afficher la légende de la limite SEUIL DE 20H = 72000 secondes
+    fig.add_annotation(x=fig['data'][0]['x'][-1],
+                    y=20,
+                    text="SEUIL DE 20H",
+                    showarrow=False,
+                    font=dict(color="red"),
+                    xshift=-40,  # Shift the label to the left
+                    yshift=20)   # Shift the label downwards
+    
+    # Afficher la figure interactive
+    # fig.show()
+
+    # Calcul temps total de transcription en secondes du mois
+    temps = a["durees_audio_sec"].sum()
+    return fig,temps
+
+
+def transcript(dict_user,username,user_group, audio_file,maintenant,Year_Month,quota_20H,model):
+    # Calcul consommation utilisateur
+    figure , consommation = graphique_utilisation(dict_user, username, Year_Month)
+    if audio_file is not None:
+        st.sidebar.header("Ecouter le fichier audio")
+        st.sidebar.audio(audio_file)
+        
+        ### Utilisateur SIDWAYA
+        if user_group == "utilisateurs_sidwaya":
+            date_inscription = dict_user[username]['date_inscription']
+            format = "%Y-%m-%d %H:%M:%S.%f"
+            datetime_obj = date.strptime(date_inscription, format)
+            # Calculate the difference between the two dates
+            difference = maintenant - datetime_obj
+            # print(type(difference))
+            # Compare if the difference is less than or equal to one year
+            one_year = td(days=365)
+            is_one_year_before = difference <= one_year
+
+            if (is_one_year_before):
+                if consommation > quota_20H:
+                    st.text("Quota de transcription audio du mois dépassé")
+                    text_transcript = ""
+                    #audio_name = ""
+                else :
+                    ### Durée de l'audio ###
+                    # Charger le fichier audio et obtenir les informations
+                    infos_audio = sf.info(audio_file.name)
+                    # Extraire la durée en secondes
+                    duree_audio_sec = infos_audio.duration
+                    # Afficher la durée
+                    print(f'Durée audio : {duree_audio_sec} secondes')
+                    
+                    # Mise à jour info utilisateurs
+                    dict_user[username]["durees_audio_sec"].append(duree_audio_sec)
+                    dict_user[username]["dates_transcription"].append(str(maintenant))
+                    with open('users_info.json', 'w') as f:
+                        json.dump(dict_user, f)
+                    st.sidebar.success("Audio en cours de transcription")
+                    audio_name = audio_file.name
+                    transcription = model.transcribe(audio_name)
+                    st.sidebar.success("Transcription terminée")
+                    st.balloons()
+                    text_transcript = transcription["text"]
+                    st.markdown(text_transcript)
+                    # Ajout boutton de téléchargement
+                    st.download_button('Télécharger la transcription', text_transcript)
+                    # Streamlit widgets automatically run the script from top to bottom. Since
+                    # this button is not connected to any other logic, it just causes a plain
+                    # rerun.
+                    # st.button("Re-run")
+
+
+
+            # if st.sidebar.button("Enregistrer un audio") :
+            #     audio_bytes = audio_recorder()
+            #     if st.sidebar.button("Transcrire l'audio"):
+            #         if audio_bytes is not None:
+            #             st.sidebar.success("Audio en cours de transcription")
+            #             transcription = model.transcribe(audio_bytes)
+            #             st.sidebar.success("Transcription terminée")
+            #             st.balloons()
+            #             text_transcript = transcription["text"]
+            #             st.markdown(text_transcript)
+            #             # Ajout boutton de téléchargement
+            #             st.download_button('Télécharger la transcription', text_transcript)
+            #             # Streamlit widgets automatically run the script from top to bottom. Since
+            #             # this button is not connected to any other logic, it just causes a plain
+            #             # rerun.
+            #             # st.button("Re-run")
+            #         else:
+            #             st.sidebar.error("Erreur : Charger un fichier audio")
+            #     st.sidebar.header("Ecouter le fichier audio")
+            #     st.sidebar.audio(audio_bytes)
+        
+        ### Utilisateurs gratuits et VIP ####      
+        if ((user_group == "utilisateurs_vip") or (user_group == "utilisateurs_gratuits")):
+            if consommation > quota_20H:
+                st.text("Quota gratuit dépassé,veuillez contactez l'administrateur pour vous abonner")
+                text_transcript = ""
+                #audio_name = ""
+            else :
+                ### Durée de l'audio ###
+                # Charger le fichier audio et obtenir les informations
+                infos_audio = sf.info(audio_file.name)
+                # Extraire la durée en secondes
+                duree_audio_sec = infos_audio.duration
+                # Afficher la durée
+                print(f'Durée audio : {duree_audio_sec} secondes')
+                
+                # Mise à jour info utilisateurs
+                dict_user[username]["durees_audio_sec"].append(duree_audio_sec)
+                dict_user[username]["dates_transcription"].append(str(maintenant))
+                with open('users_info.json', 'w') as f:
+                    json.dump(dict_user, f)
+                st.sidebar.success("Audio en cours de transcription")
+                audio_name = audio_file.name
+                transcription = model.transcribe(audio_name)
+                st.sidebar.success("Transcription terminée")
+                st.balloons()
+                text_transcript = transcription["text"]
+                st.markdown(text_transcript)
+                # Ajout boutton de téléchargement
+                st.download_button('Télécharger la transcription', text_transcript)
+                # Streamlit widgets automatically run the script from top to bottom. Since
+                # this button is not connected to any other logic, it just causes a plain
+                # rerun.
+                # st.button("Re-run")
+      
+    else:
+        st.sidebar.error("Erreur : Charger un fichier audio")
+        text_transcript = ""
+        #audio_name = ""
+
+    return text_transcript
+
+

components/identification_aws.py

@@ -0,0 +1,244 @@
+import os
+import streamlit as st
+from dotenv import load_dotenv
+import requests
+import base64
+import json
+import boto3
+
+# ------------------------------------
+# Read constants from environment file
+# ------------------------------------
+load_dotenv()
+COGNITO_DOMAIN = os.environ.get("COGNITO_DOMAIN")
+CLIENT_ID = os.environ.get("CLIENT_ID")
+CLIENT_SECRET = os.environ.get("CLIENT_SECRET")
+APP_URI = os.environ.get("APP_URI")
+# ------------------------------------
+# Initialise Streamlit state variables
+# ------------------------------------
+def initialise_st_state_vars():
+    """
+    Initialise Streamlit state variables.
+    Returns:
+        Nothing.
+    """
+    if "auth_code" not in st.session_state:
+        st.session_state["auth_code"] = ""
+    if "authenticated" not in st.session_state:
+        st.session_state["authenticated"] = False
+    if "user_cognito_groups" not in st.session_state:
+        st.session_state["user_cognito_groups"] = []
+    if "user_info" not in st.session_state:
+        st.session_state["user_info"] = {}
+# ----------------------------------
+# Get authorization code after login
+# ----------------------------------
+def get_auth_code():
+    """
+    Gets auth_code state variable.
+    Returns:
+        Nothing.
+    """
+    auth_query_params = st.experimental_get_query_params()
+    try:
+        auth_code = dict(auth_query_params)["code"][0]
+    except (KeyError, TypeError):
+        auth_code = ""
+    return auth_code
+# ----------------------------------
+# Set authorization code after login
+# ----------------------------------
+def set_auth_code():
+    """
+    Sets auth_code state variable.
+    Returns:
+        Nothing.
+    """
+    initialise_st_state_vars()
+    auth_code = get_auth_code()
+    st.session_state["auth_code"] = auth_code
+# -------------------------------------------------------
+# Use authorization code to get user access and id tokens
+# -------------------------------------------------------
+def get_user_tokens(auth_code):
+    """
+    Gets user tokens by making a post request call.
+    Args:
+        auth_code: Authorization code from cognito server.
+    Returns:
+        {
+        'access_token': access token from cognito server if user is successfully authenticated.
+        'id_token': access token from cognito server if user is successfully authenticated.
+        }
+    """
+    # Variables to make a post request
+    token_url = f"{COGNITO_DOMAIN}/oauth2/token"
+    client_secret_string = f"{CLIENT_ID}:{CLIENT_SECRET}"
+    client_secret_encoded = str(
+        base64.b64encode(client_secret_string.encode("utf-8")), "utf-8"
+    )
+    headers = {
+        "Content-Type": "application/x-www-form-urlencoded",
+        "Authorization": f"Basic {client_secret_encoded}",
+    }
+    body = {
+        "grant_type": "authorization_code",
+        "client_id": CLIENT_ID,
+        "code": auth_code,
+        "redirect_uri": APP_URI,
+    }
+    token_response = requests.post(token_url, headers=headers, data=body)
+    try:
+        access_token = token_response.json()["access_token"]
+        id_token = token_response.json()["id_token"]
+    except (KeyError, TypeError):
+        access_token = ""
+        id_token = ""
+    return access_token, id_token
+# ---------------------------------------------
+# Use access token to retrieve user information
+# ---------------------------------------------
+def get_user_info(access_token):
+    """
+    Gets user info from aws cognito server.
+    Args:
+        access_token: string access token from the aws cognito user pool
+        retrieved using the access code.
+    Returns:
+        userinfo_response: json object.
+    """
+    userinfo_url = f"{COGNITO_DOMAIN}/oauth2/userInfo"
+    headers = {
+        "Content-Type": "application/json;charset=UTF-8",
+        "Authorization": f"Bearer {access_token}",
+    }
+    userinfo_response = requests.get(userinfo_url, headers=headers)
+    return userinfo_response.json()
+
+### Add user to a group
+def add_user_to_group(user_pool_id, username, group_name):
+    client = boto3.client('cognito-idp')
+
+    response = client.admin_add_user_to_group(
+        UserPoolId=user_pool_id,
+        Username=username,
+        GroupName=group_name
+    )
+
+    # Check the response for any errors
+    if 'ResponseMetadata' in response and response['ResponseMetadata']['HTTPStatusCode'] == 200:
+        print("User added to group successfully.")
+    else:
+        print("Failed to add user to group. Error:", response)
+
+
+## Get user pool id
+
+def get_user_pool_id(user_pool_name):
+    client = boto3.client('cognito-idp')
+
+    response = client.list_user_pools(MaxResults=60)
+
+    for user_pool in response['UserPools']:
+        if user_pool['Name'] == user_pool_name:
+            return user_pool['Id']
+
+    # If the User Pool with the given name is not found
+    raise ValueError("User Pool '{}' not found.".format(user_pool_name))
+
+
+# -------------------------------------------------------
+# Decode access token to JWT to get user's cognito groups
+# -------------------------------------------------------
+# Ref - https://gist.github.com/GuillaumeDerval/b300af6d4f906f38a051351afab3b95c
+def pad_base64(data):
+    """
+    Makes sure base64 data is padded.
+    Args:
+        data: base64 token string.
+    Returns:
+        data: padded token string.
+    """
+    missing_padding = len(data) % 4
+    if missing_padding != 0:
+        data += "=" * (4 - missing_padding)
+    return data
+def get_user_cognito_groups(id_token):
+    """
+    Decode id token to get user cognito groups.
+    Args:
+        id_token: id token of a successfully authenticated user.
+    Returns:
+        user_cognito_groups: a list of all the cognito groups the user belongs to.
+    """
+    if id_token != "":
+        header, payload, signature = id_token.split(".")
+        printable_payload = base64.urlsafe_b64decode(pad_base64(payload))
+        payload_dict = json.loads(printable_payload)
+        user_cognito_groups = list(dict(payload_dict)["cognito:groups"])
+    else:
+        user_cognito_groups = []
+    return user_cognito_groups
+# -----------------------------
+# Set Streamlit state variables
+# -----------------------------
+def set_st_state_vars():
+    """
+    Sets the streamlit state variables after user authentication.
+    Returns:
+        Nothing.
+    """
+    initialise_st_state_vars()
+    auth_code = get_auth_code()
+    access_token, id_token = get_user_tokens(auth_code)
+    user_info = get_user_info(access_token)
+    user_cognito_groups = get_user_cognito_groups(id_token)
+    if access_token != "":
+        st.session_state["auth_code"] = auth_code
+        st.session_state["authenticated"] = True
+        st.session_state["user_info"] = user_info
+        st.session_state["user_cognito_groups"] = user_cognito_groups
+# -----------------------------
+# Login/ Logout HTML components
+# -----------------------------
+login_link = f"{COGNITO_DOMAIN}/login?client_id={CLIENT_ID}&response_type=code&scope=email+openid&redirect_uri={APP_URI}"
+logout_link = f"{COGNITO_DOMAIN}/logout?client_id={CLIENT_ID}&logout_uri={APP_URI}"
+html_css_login = """
+<style>
+.button-login {
+  background-color: skyblue;
+  color: white !important;
+  padding: 1em 1.5em;
+  text-decoration: none;
+  text-transform: uppercase;
+}
+.button-login:hover {
+  background-color: #555;
+  text-decoration: none;
+}
+.button-login:active {
+  background-color: black;
+}
+</style>
+"""
+html_button_login = (
+    html_css_login
+    + f"<a href='{login_link}' class='button-login' target='_self'>Se connecter</a>"
+)
+html_button_logout = (
+    html_css_login
+    + f"<a href='{logout_link}' class='button-login' target='_self'>Se déconnecter</a>"
+)
+def button_login():
+    """
+    Returns:
+        Html of the login button.
+    """
+    return st.sidebar.markdown(f"{html_button_login}", unsafe_allow_html=True)
+def button_logout():
+    """
+    Returns:
+        Html of the logout button.
+    """
+    return st.sidebar.markdown(f"{html_button_logout}", unsafe_allow_html=True)

components/logo.py

@@ -0,0 +1,10 @@
+from PIL import Image
+import streamlit as st
+
+# You can always call this function where ever you want
+
+def add_logo(logo_path, width, height):
+    """Read and return a resized logo"""
+    logo = Image.open(logo_path)
+    modified_logo = logo.resize((width, height))
+    return modified_logo

pages/Limite_Usage.py

@@ -0,0 +1,90 @@
+# Importation des bibliothèques
+import json
+import components.fonctions_transcription as TRS
+import streamlit as st
+import components.logo as logo
+import components.identification_aws as authenticate
+import datetime
+from datetime import datetime as date
+import math
+
+
+# Chargement du fichier des utilisateurs
+with open("users_info.json", 'r') as file:
+    dict_user = json.load(file)
+
+# Logo de la page
+my_logo = logo.add_logo(logo_path="logo_digitalixsa.png", width=100, height=100)
+st.image(my_logo)
+
+# Titre de la page
+st.title("Limite d'utilisation de la transcription")
+
+# Calcul annee-mois de trascription
+maintenant = datetime.datetime.now()
+Year = maintenant.year
+Month = maintenant.month
+Year_Month = str(Year) + '_' + str(Month).zfill(2)
+
+# Check authentication
+authenticate.set_st_state_vars()
+# Add login/logout buttons
+if st.session_state["authenticated"]:
+    authenticate.button_logout()
+    # informations de l'utilisateur
+    user_group = 'utilisateurs_sidwaya'
+    user_info = st.session_state["user_info"]
+    username = user_info['username']
+    user_group = st.session_state["user_cognito_groups"][0]
+    # information de l'utilisateur
+    user_pool_name = 'transcription_streamlit'
+    # auth_code = st.session_state["auth_code"]
+    # add user to users_dict and group free
+    if username not in dict_user.keys():
+        dict_user[username] = {"email": user_info['email'],
+                                            "durees_audio_sec":[0],
+                                            "date_inscription":str(maintenant),
+                                            "dates_transcription":[str(maintenant)],
+                                            "abonnement":1}
+        #group_name = 'utilisateurs_gratuits'
+        # get user pool id 
+        #user_pool_id = authenticate.get_user_pool_id(user_pool_name)
+        #print("User Pool ID:", user_pool_id)
+        #authenticate.add_user_to_group(user_pool_id, username, group_name)
+
+    ##### Affichage utilisation de l'utilisateur #####
+
+    figure , consommation = TRS.graphique_utilisation(dict_user, username, Year_Month)
+
+    ### Utilisateur SIDWAYA
+    if user_group == "utilisateurs_sidwaya":
+        date_inscription = dict_user[user_info['username']]['date_inscription']
+        format = "%Y-%m-%d %H:%M:%S.%f"
+        datetime_obj = date.strptime(date_inscription, format)
+        # Calculate the difference between the two dates
+        difference = maintenant - datetime_obj
+
+        # Display the Plotly figure in Streamlit app
+        st.plotly_chart(figure)
+        # Affichage consommation 
+        st.text("Consommation du mois : "+ str(round(consommation/3600,2))+ "/ 20H")
+        st.text("Duree abonnement : "+ str(math.floor(difference.days/30) +1) +"/ 12 mois")
+
+    if user_group == "utilisateurs_vip":
+            # Display the Plotly figure in Streamlit app
+            st.plotly_chart(figure)
+            # Affichage consommation 
+            st.text("Consommation du mois : "+ str(round(consommation/3600,2))+ "/ 20H")
+
+    if user_group == "utilisateurs_gratuits":
+            # Display the Plotly figure in Streamlit app
+            st.plotly_chart(figure)
+            # Affichage consommation 
+            st.text("Consommation du mois : "+ str(round(consommation/3600,2))+ "/ 20H")
+else:
+    authenticate.button_login()
+
+
+
+
+

pages/Transcription.py

@@ -0,0 +1,130 @@
+# pip install streamlit
+import streamlit as st
+import whisper
+import components.logo as logo
+import components.identification_aws as authenticate
+# from audio_recorder_streamlit import audio_recorder
+import soundfile as sf
+import json
+import datetime
+from datetime import datetime as date
+from datetime import timedelta as td
+import pages.Limite_Usage as graphi
+import components.fonctions_transcription as TRS
+import boto3
+
+
+
+
+#Region Paris
+###region="eu-west-3"
+
+# # Initialize Cognito client
+# cognito_client = boto3.client('cognito-idp', region_name=region)
+
+# Chargement du fichier des utilisateurs
+with open("users_info.json", 'r') as file:
+    dict_user = json.load(file)
+
+# Logo de la page
+my_logo = logo.add_logo(logo_path="logo_digitalixsa.png", width=100, height=100)
+st.image(my_logo)
+
+# Titre de la page
+st.title("TRANSCRIPTION AUDIO AUTOMATIQUE DIGITALIX")
+
+
+# Calcul annee-mois de trascription
+maintenant = datetime.datetime.now()
+Year = maintenant.year
+Month = maintenant.month
+Year_Month = str(Year) + '_' + str(Month).zfill(2)
+#text_transcript = ""
+
+# Check authentication
+authenticate.set_st_state_vars()
+# Add login/logout buttons
+if st.session_state["authenticated"]:
+    authenticate.button_logout()
+    # informations de l'utilisateur
+    user_group = 'utilisateurs_sidwaya'
+    user_info = st.session_state["user_info"]
+    username = user_info['username']
+    user_group = st.session_state["user_cognito_groups"][0]
+    # information de l'utilisateur
+    user_pool_name = 'transcription_streamlit'
+    # auth_code = st.session_state["auth_code"]
+
+    # add user to users_dict and group free
+    if username not in dict_user.keys():
+        dict_user[username] = {"email": user_info['email'],
+                                            "durees_audio_sec":[0],
+                                            "date_inscription":str(maintenant),
+                                            "dates_transcription":[str(maintenant)],
+                                            "abonnement":1}
+        #group_name = 'utilisateurs_gratuits'
+        # get user pool id 
+        #user_pool_id = authenticate.get_user_pool_id(user_pool_name)
+        #print("User Pool ID:", user_pool_id)
+        #authenticate.add_user_to_group(user_pool_id, username, group_name)
+        #Charger l'audio avec streamlit
+    
+    audio_file = st.file_uploader("Charger l'audio", type=["wav", "mp3", "m4a"])
+    #audio_name = audio_file.name
+    # Chargement du modèle
+    model = whisper.load_model("medium")
+    st.text("Chargement du modèle terminé")
+
+
+    #Definition quota utilisation
+    quota_20H = 1000
+
+    
+
+
+    if st.sidebar.button("Transcrire l'audio"):
+        # Pour des groupes d'utilisateurs   
+        if (user_group == "utilisateurs_sidwaya"):
+            text_transcript = TRS.transcript(dict_user,username,user_group, audio_file,maintenant,Year_Month,quota_20H,model)
+    ################ Utilisateurs vip ############################
+    ###################################################################
+    # Pour des groupes d'utilisateurs  vip 
+        if ((user_group == "utilisateurs_vip") or (user_group == "utilisateurs_vip")) :
+            text_transcript = TRS.transcript(dict_user,username,user_group, audio_file,maintenant,Year_Month,quota_20H,model)
+
+else:
+    authenticate.button_login()
+
+
+
+# if (st.session_state["authenticated"]):
+#     user_info = st.session_state["user_info"]
+#     username = user_info['username']
+    
+#     # # add user to users_dict and group free
+#     # if username not in dict_user.keys() :
+#     #     group_name = 'utilisateurs_gratuits'
+#     #     # get user pool id 
+#     #     user_pool_id = authenticate.get_user_pool_id(user_pool_name)
+#     #     #print("User Pool ID:", user_pool_id)
+#     #     authenticate.add_user_to_group(user_pool_id, username, group_name)
+
+#     # Add the user to the group
+#     group_name = 'utilisateurs_gratuits'
+#     # get user pool id 
+#     user_pool_id = authenticate.get_user_pool_id(user_pool_name)
+#     response = cognito_client.admin_add_user_to_group(
+#         UserPoolId=user_pool_id,
+#         Username=username,
+#         GroupName=group_name
+#     )
+
+#     # Check if the operation was successful
+#     if response['ResponseMetadata']['HTTPStatusCode'] == 200:
+#         print('User added to the group successfully.')
+#     else:
+#         print('Failed to add the user to the group.')
+
+
+
+

requirements.txt

@@ -0,0 +1,9 @@
+openai-whisper
+ffmpeg-python
+streamlit
+python-dotenv
+audio_recorder_streamlit
+soundfile
+plotly.express
+nbformat>=4.2.0
+boto3

test_date.py

@@ -0,0 +1,33 @@
+# import datetime
+# import pandas as pd
+
+# # Obtenir la date et l'heure actuelles
+# maintenant = datetime.datetime.now()
+
+# # Formater la date et l'heure dans le format souhaité
+# date_formattee = maintenant.strftime("%Y-%m-%d-%H-%M-%S")
+
+# # Afficher la date formatée
+# #print(date_formattee.month())
+# print(maintenant)
+# print(datetime.datetime.min.date())
+
+
+##### Affichage utilisation de l'utilisateur #####
+# import json
+
+# # Chargement du fichier des utilisateurs
+# with open("users_info.json", 'r') as file:
+#     dict_user = json.load(file)
+
+# # Convert JSON to DataFrame
+# df_user = pd.json_normalize(dict_user)
+
+# print(df_user)
+
+# username_test = "18202e69-afba-430b-a7f2-cf33c0a173b5"
+
+
+
+
+

test_json.ipynb

@@ -0,0 +1,1222 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import json\n",
+    "import plotly.express as px"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>usernames</th>\n",
+       "      <th>email</th>\n",
+       "      <th>durees_audio_sec</th>\n",
+       "      <th>date_inscription</th>\n",
+       "      <th>dates_transcription</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>Year_Month</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>18202e69-afba-430b-a7f2-cf33c0a173b5</td>\n",
+       "      <td>[email protected]</td>\n",
+       "      <td>56.753311</td>\n",
+       "      <td>2023-06-14 13:59:03.140847</td>\n",
+       "      <td>2023-06-14 13:59:03.140847</td>\n",
+       "      <td>2023</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2023_06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>18202e69-afba-430b-a7f2-cf33c0a173b5</td>\n",
+       "      <td>[email protected]</td>\n",
+       "      <td>56.753311</td>\n",
+       "      <td>2023-06-14 13:59:03.140847</td>\n",
+       "      <td>2023-06-14 14:01:42.171527</td>\n",
+       "      <td>2023</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2023_06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>18202e69-afba-430b-a7f2-cf33c0a173b5</td>\n",
+       "      <td>[email protected]</td>\n",
+       "      <td>56.753311</td>\n",
+       "      <td>2023-06-14 13:59:03.140847</td>\n",
+       "      <td>2023-06-14 14:03:44.971361</td>\n",
+       "      <td>2023</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2023_06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>18202e69-afba-430b-a7f2-cf33c0a173b5</td>\n",
+       "      <td>[email protected]</td>\n",
+       "      <td>232.408542</td>\n",
+       "      <td>2023-06-14 13:59:03.140847</td>\n",
+       "      <td>2023-06-15 00:10:08.233341</td>\n",
+       "      <td>2023</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2023_06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>401507b3-9030-4690-969b-524b37ba5bc9</td>\n",
+       "      <td>[email protected]</td>\n",
+       "      <td>56.753311</td>\n",
+       "      <td>2023-06-14 14:05:49.398837</td>\n",
+       "      <td>2023-06-14 14:05:49.398837</td>\n",
+       "      <td>2023</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2023_06</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                              usernames                 email   \n",
+       "0  18202e69-afba-430b-a7f2-cf33c0a173b5       [email protected]  \\\n",
+       "1  18202e69-afba-430b-a7f2-cf33c0a173b5       [email protected]   \n",
+       "2  18202e69-afba-430b-a7f2-cf33c0a173b5       [email protected]   \n",
+       "3  18202e69-afba-430b-a7f2-cf33c0a173b5       [email protected]   \n",
+       "4  401507b3-9030-4690-969b-524b37ba5bc9  [email protected]   \n",
+       "\n",
+       "  durees_audio_sec           date_inscription        dates_transcription   \n",
+       "0        56.753311 2023-06-14 13:59:03.140847 2023-06-14 13:59:03.140847  \\\n",
+       "1        56.753311 2023-06-14 13:59:03.140847 2023-06-14 14:01:42.171527   \n",
+       "2        56.753311 2023-06-14 13:59:03.140847 2023-06-14 14:03:44.971361   \n",
+       "3       232.408542 2023-06-14 13:59:03.140847 2023-06-15 00:10:08.233341   \n",
+       "4        56.753311 2023-06-14 14:05:49.398837 2023-06-14 14:05:49.398837   \n",
+       "\n",
+       "   Year  Month Year_Month  \n",
+       "0  2023      6    2023_06  \n",
+       "1  2023      6    2023_06  \n",
+       "2  2023      6    2023_06  \n",
+       "3  2023      6    2023_06  \n",
+       "4  2023      6    2023_06  "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "##### Affichage utilisation de l'utilisateur #####\n",
+    "# Chargement du fichier des utilisateurs\n",
+    "with open(\"users_info.json\", 'r') as file:\n",
+    "    dict_user = json.load(file)\n",
+    "\n",
+    "# Transformation en dataframe\n",
+    "df_user = pd.DataFrame(dict_user).T.reset_index()\n",
+    "df_user.rename(columns={\"index\":\"usernames\"},inplace = True)\n",
+    "\n",
+    "# Separation des lignes de listes en plusieurs lignes pour les colonees duree_audio_sec et dates_transcription\n",
+    "df_duree = df_user.drop(['dates_transcription'],axis=1) \n",
+    "df_duree = df_duree.explode('durees_audio_sec')\n",
+    "df_duree = df_duree.reset_index(drop=True)\n",
+    "\n",
+    "df_transcription = df_user.drop(['durees_audio_sec'],axis=1)\n",
+    "df_transcription = df_transcription.explode('dates_transcription')\n",
+    "df_transcription = df_transcription.reset_index(drop=True)\n",
+    "\n",
+    "# Regroupement des dataframes\n",
+    "df_user = df_duree.copy()\n",
+    "df_user[\"dates_transcription\"] = df_transcription[\"dates_transcription\"]\n",
+    "\n",
+    "df_user['date_inscription'] = pd.to_datetime(df_user['date_inscription'],format = \"%Y-%m-%d %H:%M:%S.%f\")\n",
+    "df_user['dates_transcription'] = pd.to_datetime(df_user['dates_transcription'],format = \"%Y-%m-%d %H:%M:%S.%f\")\n",
+    "\n",
+    "# Calcul annee-mois de trascription\n",
+    "df_user['Year'] = df_user['dates_transcription'].dt.year\n",
+    "df_user['Month'] = df_user['dates_transcription'].dt.month\n",
+    "df_user['Year_Month'] = df_user['Year'].astype(str) + '_' + df_user['Month'].astype(str).str.zfill(2)\n",
+    "df_user\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "hovertemplate": "dates_transcription=%{x}<br>durees_audio_sec=%{y}<extra></extra>",
+         "legendgroup": "",
+         "line": {
+          "color": "#636efa",
+          "dash": "solid"
+         },
+         "marker": {
+          "symbol": "circle"
+         },
+         "mode": "lines",
+         "name": "",
+         "orientation": "v",
+         "showlegend": false,
+         "type": "scatter",
+         "x": [
+          "2023-06-14T13:59:03.140847",
+          "2023-06-14T14:01:42.171527",
+          "2023-06-14T14:03:44.971361",
+          "2023-06-15T00:10:08.233341"
+         ],
+         "xaxis": "x",
+         "y": [
+          56.75331065759637,
+          56.75331065759637,
+          56.75331065759637,
+          232.40854166666668
+         ],
+         "yaxis": "y"
+        }
+       ],
+       "layout": {
+        "annotations": [
+         {
+          "font": {
+           "color": "red"
+          },
+          "showarrow": false,
+          "text": "SEUIL DE 20H = 72000 secondes",
+          "x": "2023-06-15T00:10:08.233341",
+          "xshift": -40,
+          "y": 72000,
+          "yshift": 20
+         }
+        ],
+        "legend": {
+         "tracegroupgap": 0
+        },
+        "margin": {
+         "t": 60
+        },
+        "shapes": [
+         {
+          "line": {
+           "color": "red",
+           "dash": "dash",
+           "width": 2
+          },
+          "type": "line",
+          "x0": "2023-06-14T13:59:03.140847",
+          "x1": "2023-06-15T00:10:08.233341",
+          "y0": 72000,
+          "y1": 72000
+         }
+        ],
+        "template": {
+         "data": {
+          "bar": [
+           {
+            "error_x": {
+             "color": "#2a3f5f"
+            },
+            "error_y": {
+             "color": "#2a3f5f"
+            },
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "bar"
+           }
+          ],
+          "barpolar": [
+           {
+            "marker": {
+             "line": {
+              "color": "#E5ECF6",
+              "width": 0.5
+             },
+             "pattern": {
+              "fillmode": "overlay",
+              "size": 10,
+              "solidity": 0.2
+             }
+            },
+            "type": "barpolar"
+           }
+          ],
+          "carpet": [
+           {
+            "aaxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "baxis": {
+             "endlinecolor": "#2a3f5f",
+             "gridcolor": "white",
+             "linecolor": "white",
+             "minorgridcolor": "white",
+             "startlinecolor": "#2a3f5f"
+            },
+            "type": "carpet"
+           }
+          ],
+          "choropleth": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "choropleth"
+           }
+          ],
+          "contour": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
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+              0,
+              "#0d0887"
+             ],
+             [
+              0.1111111111111111,
+              "#46039f"
+             ],
+             [
+              0.2222222222222222,
+              "#7201a8"
+             ],
+             [
+              0.3333333333333333,
+              "#9c179e"
+             ],
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+              0.4444444444444444,
+              "#bd3786"
+             ],
+             [
+              0.5555555555555556,
+              "#d8576b"
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+              "#ed7953"
+             ],
+             [
+              0.7777777777777778,
+              "#fb9f3a"
+             ],
+             [
+              0.8888888888888888,
+              "#fdca26"
+             ],
+             [
+              1,
+              "#f0f921"
+             ]
+            ],
+            "type": "contour"
+           }
+          ],
+          "contourcarpet": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "type": "contourcarpet"
+           }
+          ],
+          "heatmap": [
+           {
+            "colorbar": {
+             "outlinewidth": 0,
+             "ticks": ""
+            },
+            "colorscale": [
+             [
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+              "#0d0887"
+             ],
+             [
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+              "#46039f"
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+              "#7201a8"
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+              "#9c179e"
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+             [
+              0.4444444444444444,
+              "#bd3786"
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+             [
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+              "#d8576b"
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+             [
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+          "hovermode": "closest",
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+            "linecolor": "white",
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+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "xaxis": {
+         "anchor": "y",
+         "domain": [
+          0,
+          1
+         ],
+         "title": {
+          "text": "dates_transcription"
+         }
+        },
+        "yaxis": {
+         "anchor": "x",
+         "domain": [
+          0,
+          1
+         ],
+         "title": {
+          "text": "durees_audio_sec"
+         }
+        }
+       }
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Tracer X en fonction de Y en utilisant Plotly\n",
+    "#df_user[\"durees_audio_sec\"] =  df_user[\"durees_audio_sec\"]/3600\n",
+    "a =df_user[(df_user[\"usernames\"] == \"18202e69-afba-430b-a7f2-cf33c0a173b5\") & (df_user[\"Year_Month\"] == \"2023_06\")]\n",
+    "fig = px.line(a, x='dates_transcription', y='durees_audio_sec')\n",
+    "\n",
+    "# Ajouter la limite de temps\n",
+    "fig.add_shape(type=\"line\",\n",
+    "              x0=fig['data'][0]['x'][0],\n",
+    "              x1=fig['data'][0]['x'][-1],\n",
+    "              y0=72000,\n",
+    "              y1=72000,\n",
+    "              line=dict(color='red', width=2, dash='dash'))\n",
+    "\n",
+    "fig.add_annotation(x=fig['data'][0]['x'][-1],\n",
+    "                   y=72000,\n",
+    "                   text=\"SEUIL DE 20H = 72000 secondes\",\n",
+    "                   showarrow=False,\n",
+    "                   font=dict(color=\"red\"),\n",
+    "                   xshift=-40,  # Shift the label to the left\n",
+    "                   yshift=20)   # Shift the label downwards\n",
+    "# Afficher la figure interactive\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "402.6684736394558"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "a[\"durees_audio_sec\"].sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "72000"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "3600 *20"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2023-06-14 13:59:03.140847\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datetime import datetime\n",
+    "\n",
+    "date_string = \"2023-06-14 13:59:03.140847\"\n",
+    "format = \"%Y-%m-%d %H:%M:%S.%f\"\n",
+    "\n",
+    "datetime_obj = datetime.strptime(date_string, format)\n",
+    "print(datetime_obj)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "18"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "datetime_obj.month + 12"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "whisper",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

users_info.json

@@ -0,0 +1,79 @@
+{
+    "18202e69-afba-430b-a7f2-cf33c0a173b5": {
+        "email": "[email protected]",
+        "durees_audio_sec": [
+            56.75331065759637,
+            56.75331065759637,
+            56.75331065759637,
+            232.40854166666668,
+            56.75331065759637,
+            56.75331065759637
+        ],
+        "date_inscription": "2023-06-14 13:59:03.140847",
+        "dates_transcription": [
+            "2023-06-14 13:59:03.140847",
+            "2023-06-14 14:01:42.171527",
+            "2023-06-14 14:03:44.971361",
+            "2023-06-15 00:10:08.233341",
+            "2023-06-15 01:01:04.821023",
+            "2023-06-15 01:03:01.867620"
+        ],
+        "abonnement": 1
+    },
+    "401507b3-9030-4690-969b-524b37ba5bc9": {
+        "email": "[email protected]",
+        "durees_audio_sec": [
+            56.75331065759637
+        ],
+        "date_inscription": "2023-06-14 14:05:49.398837",
+        "dates_transcription": [
+            "2023-06-14 14:05:49.398837"
+        ],
+        "abonnement": 1
+    },
+    "10425ed8-fb31-4d5b-b419-e09e3eed17cc": {
+        "email": "[email protected]",
+        "durees_audio_sec": [
+            0,
+            56.75331065759637,
+            56.75331065759637,
+            56.75331065759637,
+            56.75331065759637
+        ],
+        "date_inscription": "2023-06-16 14:36:11.076300",
+        "dates_transcription": [
+            "2023-06-16 14:36:11.076300",
+            "2023-06-16 14:36:11.076300",
+            "2023-06-16 15:22:43.918257",
+            "2023-06-24 19:05:36.730951",
+            "2023-06-25 15:02:43.520520"
+        ],
+        "abonnement": 1
+    },
+    "39c7ad13-9e92-4e9a-af24-9ecb26e4f487": {
+        "email": "[email protected]",
+        "durees_audio_sec": [
+            0,
+            56.75331065759637
+        ],
+        "date_inscription": "2023-06-25 15:14:38.401039",
+        "dates_transcription": [
+            "2023-06-25 15:14:38.401039",
+            "2023-06-25 15:14:38.401039"
+        ],
+        "abonnement": 1
+    },
+    "25a3587c-3dcb-4605-a7df-76cbfcda555d": {
+        "email": "[email protected]",
+        "durees_audio_sec": [
+            0,
+            56.75331065759637
+        ],
+        "date_inscription": "2023-06-25 15:32:54.315302",
+        "dates_transcription": [
+            "2023-06-25 15:32:54.315302",
+            "2023-06-25 15:32:54.315302"
+        ],
+        "abonnement": 1
+    }
+}