import gradio as gr
from queries import (clustering_esfuerzo_dieta_response, clustering_objetivo_response, clustering_entrenamiento_response, 
                     clustering_cumplimiento_dieta_response, clustering_compromiso_response, clustering_diferencia_peso_response,
                     make_query, get_min_max_mean_mode_macros_differences)
from find_matches import find_user_dates_matches, find_macros_that_match_dates_of_users
from input_options import (opciones_esfuerzo, opciones_objetivo, opciones_cumplimiento_entrenamiento,
                           opciones_cumplimiento_dieta, opciones_compromiso, diferencia_peso_options)

def clustering_responses(esfuerzo_dieta, objetivo, cumplimiento_entrenamiento, 
                    cumplimiento_dieta, compromiso, variacion_peso):
    cluster_esfuerzo_dieta = clustering_esfuerzo_dieta_response(esfuerzo_dieta)
    cluster_objetivo = clustering_objetivo_response(objetivo)
    cluster_entrenamiento = clustering_entrenamiento_response(cumplimiento_entrenamiento)
    cluster_cumplimiento_dieta = clustering_cumplimiento_dieta_response(cumplimiento_dieta)
    cluster_compromiso = clustering_compromiso_response(compromiso)
    diff_peso_min, diff_peso_max = clustering_diferencia_peso_response(variacion_peso)

    return cluster_esfuerzo_dieta, cluster_objetivo, cluster_entrenamiento, cluster_cumplimiento_dieta, cluster_compromiso, diff_peso_min, diff_peso_max

def calcular_macros(esfuerzo_dieta, objetivo, cumplimiento_entrenamiento, 
                    cumplimiento_dieta, compromiso, peso_inicial, peso_final,
                    train_day_protein_initial, train_day_carbs_initial, train_day_fat_initial,
                    intratrain_protein_initial, intratrain_carbs_initial,
                    rest_day_protein_initial, rest_day_carbs_initial, rest_day_fat_initial):
    # Logs
    logs = ""

    # Obtenemos los valores correspondientes a cada selección
    valor_esfuerzo = next(list(opcion.values())[0]["value"] 
                         for opcion in opciones_esfuerzo 
                         if list(opcion.values())[0]["text"] == esfuerzo_dieta)
    
    valor_objetivo = next(list(opcion.values())[0]["value"] 
                         for opcion in opciones_objetivo 
                         if list(opcion.values())[0]["text"] == objetivo)
    
    valor_cumplimiento_entr = next(list(opcion.values())[0]["value"] 
                                  for opcion in opciones_cumplimiento_entrenamiento 
                                  if list(opcion.values())[0]["text"] == cumplimiento_entrenamiento)
    
    valor_cumplimiento_dieta = next(list(opcion.values())[0]["value"] 
                                   for opcion in opciones_cumplimiento_dieta 
                                   if list(opcion.values())[0]["text"] == cumplimiento_dieta)
    
    valor_compromiso = next(list(opcion.values())[0]["value"] 
                          for opcion in opciones_compromiso 
                          if list(opcion.values())[0]["text"] == compromiso)
    
    # Clustering
    variacion_peso = peso_final - peso_inicial
    print(f"\n\nVariación de peso: {variacion_peso}")
    logs += f"\n\nVariación de peso: {variacion_peso}"
    (cluster_esfuerzo_dieta, cluster_objetivo, cluster_entrenamiento, cluster_cumplimiento_dieta, 
     cluster_compromiso, diff_peso_min, diff_peso_max) = clustering_responses(valor_esfuerzo, valor_objetivo, 
                                                                           valor_cumplimiento_entr, 
                                                                           valor_cumplimiento_dieta, valor_compromiso, 
                                                                           variacion_peso)
    
    # Imprimimos los resultados
    print(f"Respuestas formulario:")
    logs += f"\n\nRespuestas formulario:"
    print(f"\tEsfuerzo para cumplir dieta: {cluster_esfuerzo_dieta}")
    logs += f"\n\tEsfuerzo para cumplir dieta: {cluster_esfuerzo_dieta}"
    print(f"\tObjetivo: {cluster_objetivo}")
    logs += f"\n\tObjetivo: {cluster_objetivo}"
    print(f"\tEntrenamiento: {cluster_entrenamiento}")
    logs += f"\n\tEntrenamiento: {cluster_entrenamiento}"
    print(f"\tCumplimiento dieta: {cluster_cumplimiento_dieta}")
    logs += f"\n\tCumplimiento dieta: {cluster_cumplimiento_dieta}"
    print(f"\tCompromiso: {cluster_compromiso}")
    logs += f"\n\tCompromiso: {cluster_compromiso}"
    print(f"\tPeso inicial: {peso_inicial}, peso final: {peso_final} --> Diferencia: {variacion_peso:.1f}")
    logs += f"\n\tPeso inicial: {peso_inicial}, peso final: {peso_final} --> Diferencia: {variacion_peso:.1f}"
    print(f"\t{diff_peso_min} <= Diferencia peso <= {diff_peso_max}")
    logs += f"\n\t{diff_peso_min} <= Diferencia peso <= {diff_peso_max}"

    # Crear query
    query = make_query(cluster_esfuerzo_dieta, cluster_objetivo, cluster_entrenamiento, cluster_cumplimiento_dieta, cluster_compromiso, diff_peso_min, diff_peso_max)

    # Print query
    print(f"Query:")
    logs += f"\n\nQuery:"
    for q in query:
        print(f"\t{list(q.keys())[0]}", end=" --> ")
        logs += f"\n\t{list(q.keys())[0]} --> "
        for primary_key in q.keys():
            primary_key_dict = q[primary_key]
            for i, secondary_key in enumerate(primary_key_dict.keys()):
                if i == len(primary_key_dict.keys()) - 1:
                    print(f"{secondary_key}: \"{primary_key_dict[secondary_key]}\"", end="")
                    logs += f"{secondary_key}: \"{primary_key_dict[secondary_key]}\""
                else:
                    print(f"{secondary_key}: \"{primary_key_dict[secondary_key]}\"", end=", ")
                    logs += f"{secondary_key}: \"{primary_key_dict[secondary_key]}\", "
        print()
    
    # Crear diccionario de matches
    matches_dict = find_user_dates_matches(query, debug=False)
    num_matches = len(matches_dict)

    # Si no hay matches, intentamos con una query más básica
    if num_matches == 0:
        print("No se han encontrado coincidencias con la query original, intentamos con una query más básica")
        logs += "\n\nNo se han encontrado coincidencias con la query original, intentamos con una query más básica"
        query = make_query(cluster_esfuerzo_dieta, cluster_objetivo, cluster_entrenamiento, cluster_cumplimiento_dieta, cluster_compromiso, diff_peso_min, diff_peso_max, basic_query=True)
        
        # Print query
        print(f"Query:")
        logs += "\n\nQuery:"
        for q in query:
            print(f"\t{list(q.keys())[0]}", end=" --> ")
            logs += f"\n\t{list(q.keys())[0]} --> "
            for primary_key in q.keys():
                primary_key_dict = q[primary_key]
                for i, secondary_key in enumerate(primary_key_dict.keys()):
                    if i == len(primary_key_dict.keys()) - 1:
                        print(f"{secondary_key}: \"{primary_key_dict[secondary_key]}\"", end="")
                        logs += f"{secondary_key}: \"{primary_key_dict[secondary_key]}\""
                    else:
                        print(f"{secondary_key}: \"{primary_key_dict[secondary_key]}\"", end=", ")
                        logs += f"{secondary_key}: \"{primary_key_dict[secondary_key]}\", "
        print()
        logs += "\n"

        # Find matches
        matches_dict = find_user_dates_matches(query)
        num_matches = len(matches_dict)

    # Print matches
    print(f"Matches ({num_matches})")
    logs += f"\n\nMatches ({num_matches})"
    for user, dates in matches_dict.items():
        print(f"\t{user}", end=" --> ")
        logs += f"\t{user} --> "
        for date in dates:
            print(f"{date}", end=", ")
            logs += f"{date}, "
        print()
        logs += "\n"

    # Find macros that match dates of users
    macros_differences_list, macros_differences_dict = find_macros_that_match_dates_of_users(matches_dict)

    # Print macros
    print(f"Diferencia de macros ({len(macros_differences_dict)}):")
    logs += f"\n\nDiferencia de macros ({len(macros_differences_dict)}):"
    for user, macros_difference in macros_differences_dict.items():
        print(f"\t{user} --> fecha de match: {macros_difference['date_of_match']}, fecha de asignación de macros: {macros_difference['date_of_macros_asignation']}, días entre match y asignación: {macros_difference['days_between_match_and_macros_asignation']}, diferencia de macros: {macros_difference['macros_difference']}")
        logs += f"\n\t{user} --> fecha de match: {macros_difference['date_of_match']}, fecha de asignación de macros: {macros_difference['date_of_macros_asignation']}, días entre match y asignación: {macros_difference['days_between_match_and_macros_asignation']}, diferencia de macros: {macros_difference['macros_difference']}"

    # Calculate macros min, max and mean
    if len(macros_differences_list) > 0:
        (train_day_protein_std, train_day_carbs_std, train_day_fat_std, intratrain_protein_std, intratrain_carbs_std, 
        rest_day_protein_std, rest_day_carbs_std, rest_day_fat_std) = get_min_max_mean_mode_macros_differences(macros_differences_list)
    else:
        train_day_protein_std = [0, 0, 0, 0]
        train_day_carbs_std = [0, 0, 0, 0]
        train_day_fat_std = [0, 0, 0, 0]
        intratrain_protein_std = [0, 0, 0, 0]
        intratrain_carbs_std = [0, 0, 0, 0]
        rest_day_protein_std = [0, 0, 0, 0]
        rest_day_carbs_std = [0, 0, 0, 0]
        rest_day_fat_std = [0, 0, 0, 0]
    
    # Print macros min, max and mean
    print("Variación de macros:")
    logs += "\n\nVariación de macros:"
    print(f"\tproteína día de entreno:       Min: {train_day_protein_std[0]}, Max: {train_day_protein_std[1]}, Mean: {train_day_protein_std[2]:.2f}, Mode: {train_day_protein_std[3]}")
    logs += f"\n\tproteína día de entreno:       Min: {train_day_protein_std[0]}, Max: {train_day_protein_std[1]}, Mean: {train_day_protein_std[2]:.2f}, Mode: {train_day_protein_std[3]}"
    print(f"\tcarbohidratos día de entreno:  Min: {train_day_carbs_std[0]}, Max: {train_day_carbs_std[1]}, Mean: {train_day_carbs_std[2]:.2f}, Mode: {train_day_carbs_std[3]}")
    logs += f"\n\tcarbohidratos día de entreno:  Min: {train_day_carbs_std[0]}, Max: {train_day_carbs_std[1]}, Mean: {train_day_carbs_std[2]:.2f}, Mode: {train_day_carbs_std[3]}"
    print(f"\tgrasas día de entreno:         Min: {train_day_fat_std[0]}, Max: {train_day_fat_std[1]}, Mean: {train_day_fat_std[2]:.2f}, Mode: {train_day_fat_std[3]}")
    logs += f"\n\tgrasas día de entreno:         Min: {train_day_fat_std[0]}, Max: {train_day_fat_std[1]}, Mean: {train_day_fat_std[2]:.2f}, Mode: {train_day_fat_std[3]}"
    print(f"\tproteína intraentreno:         Min: {intratrain_protein_std[0]}, Max: {intratrain_protein_std[1]}, Mean: {intratrain_protein_std[2]:.2f}, Mode: {intratrain_protein_std[3]}")
    logs += f"\n\tproteína intraentreno:         Min: {intratrain_protein_std[0]}, Max: {intratrain_protein_std[1]}, Mean: {intratrain_protein_std[2]:.2f}, Mode: {intratrain_protein_std[3]}"
    print(f"\tcarbohidratos intraentreno:    Min: {intratrain_carbs_std[0]}, Max: {intratrain_carbs_std[1]}, Mean: {intratrain_carbs_std[2]:.2f}, Mode: {intratrain_carbs_std[3]}")
    logs += f"\n\tcarbohidratos intraentreno:    Min: {intratrain_carbs_std[0]}, Max: {intratrain_carbs_std[1]}, Mean: {intratrain_carbs_std[2]:.2f}, Mode: {intratrain_carbs_std[3]}"
    print(f"\tproteína día de descanso:      Min: {rest_day_protein_std[0]}, Max: {rest_day_protein_std[1]}, Mean: {rest_day_protein_std[2]:.2f}, Mode: {rest_day_protein_std[3]}")
    logs += f"\n\tproteína día de descanso:      Min: {rest_day_protein_std[0]}, Max: {rest_day_protein_std[1]}, Mean: {rest_day_protein_std[2]:.2f}, Mode: {rest_day_protein_std[3]}"
    print(f"\tcarbohidratos día de descanso: Min: {rest_day_carbs_std[0]}, Max: {rest_day_carbs_std[1]}, Mean: {rest_day_carbs_std[2]:.2f}, Mode: {rest_day_carbs_std[3]}")
    logs += f"\n\tcarbohidratos día de descanso: Min: {rest_day_carbs_std[0]}, Max: {rest_day_carbs_std[1]}, Mean: {rest_day_carbs_std[2]:.2f}, Mode: {rest_day_carbs_std[3]}"
    print(f"\tgrasas día de descanso:        Min: {rest_day_fat_std[0]}, Max: {rest_day_fat_std[1]}, Mean: {rest_day_fat_std[2]:.2f}, Mode: {rest_day_fat_std[3]}")
    logs += f"\n\tgrasas día de descanso:        Min: {rest_day_fat_std[0]}, Max: {rest_day_fat_std[1]}, Mean: {rest_day_fat_std[2]:.2f}, Mode: {rest_day_fat_std[3]}"

    # Get macros mode
    train_day_protein_mode = train_day_protein_std[3]
    train_day_carbs_mode = train_day_carbs_std[3]
    train_day_fat_mode = train_day_fat_std[3]
    intratrain_protein_mode = intratrain_protein_std[3]
    intratrain_carbs_mode = intratrain_carbs_std[3]
    rest_day_protein_mode = rest_day_protein_std[3]
    rest_day_carbs_mode = rest_day_carbs_std[3]
    rest_day_fat_mode = rest_day_fat_std[3]

    # Calculate macros final
    train_day_protein_final = train_day_protein_initial + train_day_protein_mode
    train_day_carbs_final = train_day_carbs_initial + train_day_carbs_mode
    train_day_fat_final = train_day_fat_initial + train_day_fat_mode
    intratrain_protein_final = intratrain_protein_initial + intratrain_protein_mode
    intratrain_carbs_final = intratrain_carbs_initial + intratrain_carbs_mode
    rest_day_protein_final = rest_day_protein_initial + rest_day_protein_mode
    rest_day_carbs_final = rest_day_carbs_initial + rest_day_carbs_mode
    rest_day_fat_final = rest_day_fat_initial + rest_day_fat_mode

    # Print macros
    print("Macros finales:")
    logs += "\n\nMacros finales:"
    print(f"\tProteína día de entreno inicial:       {train_day_protein_initial} --> final: {train_day_protein_final}")
    logs += f"\n\tProteína día de entreno inicial:       {train_day_protein_initial} --> final: {train_day_protein_final}"
    print(f"\tCarbohidratos día de entreno inicial:  {train_day_carbs_initial} --> final: {train_day_carbs_final}")
    logs += f"\n\tCarbohidratos día de entreno inicial:  {train_day_carbs_initial} --> final: {train_day_carbs_final}"
    print(f"\tGrasas día de entreno inicial:         {train_day_fat_initial} --> final: {train_day_fat_final}")
    logs += f"\n\tGrasas día de entreno inicial:         {train_day_fat_initial} --> final: {train_day_fat_final}"
    print(f"\tProteína intraentreno inicial:         {intratrain_protein_initial} --> final: {intratrain_protein_final}")
    logs += f"\n\tProteína intraentreno inicial:         {intratrain_protein_initial} --> final: {intratrain_protein_final}"
    print(f"\tCarbohidratos intraentreno inicial:    {intratrain_carbs_initial} --> final: {intratrain_carbs_final}")
    logs += f"\n\tCarbohidratos intraentreno inicial:    {intratrain_carbs_initial} --> final: {intratrain_carbs_final}"
    print(f"\tProteína día de descanso inicial:      {rest_day_protein_initial} --> final: {rest_day_protein_final}")
    logs += f"\n\tProteína día de descanso inicial:      {rest_day_protein_initial} --> final: {rest_day_protein_final}"
    print(f"\tCarbohidratos día de descanso inicial: {rest_day_carbs_initial} --> final: {rest_day_carbs_final}")
    logs += f"\n\tCarbohidratos día de descanso inicial: {rest_day_carbs_initial} --> final: {rest_day_carbs_final}"
    print(f"\tGrasas día de descanso inicial:        {rest_day_fat_initial} --> final: {rest_day_fat_final}")
    logs += f"\n\tGrasas día de descanso inicial:        {rest_day_fat_initial} --> final: {rest_day_fat_final}"

    return (train_day_protein_final, train_day_carbs_final, train_day_fat_final,
            intratrain_protein_final, intratrain_carbs_final,
            rest_day_protein_final, rest_day_carbs_final, rest_day_fat_final,
            logs)

# Definimos el color naranja
naranja = "#ea580b"

title = f"""
<h1 style="text-align: center; color: {naranja}; margin: 0; padding-bottom: 30px; font-size: 50px;">Macros evolution</h1>
"""

title_macros_iniciales_html = f"""
<h2 style="text-align: center; color: {naranja}; margin: 0; padding: 0;">Macros iniciales</h2>
"""

title_cuestionario_html = f"""
<h2 style="text-align: center; color: {naranja}; margin: 0; padding: 0;">Respuestas cuestionario</h2>
"""

title_macros_finales_html = f"""
<h2 style="text-align: center; color: {naranja}; margin: 0; padding: 0;">Macros finales</h2>
"""

style_css = f"""
<style>
    .demo {{
        background-color: {naranja};
    }}
    .input-group, .output-group {{
        background-color: {naranja};
        padding: 2px;
        border-radius: 7px;
    }}
    .input-row .output-row {{
    }}
    .input-column {{
    }}
    .input-number {{
        background-color: black;
        color: white;
    }}
    .input-dropdown {{
        background-color: black;
        color: white;
    }}
    .calcular-btn {{
        background-color: {naranja};
        color: white;
        border-radius: 7px;
        margin-bottom: 70px;
    }}
    .output-number {{
        background-color: black;
        color: white;
    }}
</style>
"""

# Creamos la interfaz
with gr.Blocks(css=style_css, elem_classes="demo") as demo:
    
    # Procesamos las opciones para obtener solo los textos
    textos_esfuerzo = [list(opcion.values())[0]["text"] for opcion in opciones_esfuerzo]
    textos_objetivo = [list(opcion.values())[0]["text"] for opcion in opciones_objetivo]
    textos_cumplimiento_entr = [list(opcion.values())[0]["text"] for opcion in opciones_cumplimiento_entrenamiento]
    textos_cumplimiento_dieta = [list(opcion.values())[0]["text"] for opcion in opciones_cumplimiento_dieta]
    textos_compromiso = [list(opcion.values())[0]["text"] for opcion in opciones_compromiso]

    # Title
    gr.Markdown(title)
    
    # Entradas
    gr.Markdown(title_macros_iniciales_html)
    with gr.Group(elem_classes="input-group"):
        with gr.Row(elem_classes="input-row"):
            with gr.Column(elem_classes="input-column"):
                train_day_protein_initial = gr.Number(
                    label="Proteína día de entreno (g)", 
                    precision=0,
                    value=150,
                    step=10,
                    minimum=0,
                    elem_classes="input-number"
                )
                train_day_carbs_initial = gr.Number(
                    label="Carbohidratos día de entreno (g)", 
                    precision=0,
                    value=150,
                    step=10,
                    minimum=0,
                    elem_classes="input-number"
                )
                train_day_fat_initial = gr.Number(
                    label="Grasas día de entreno (g)", 
                    precision=0,
                    value=150,
                    step=10,
                    minimum=0,
                    elem_classes="input-number"
                )
            with gr.Column(elem_classes="input-column"):
                intratrain_protein_initial = gr.Number(
                    label="Proteína intraentreno (g)", 
                    precision=0,
                    value=150,
                    step=10,
                    minimum=0,
                    elem_classes="input-number"
                )
                intratrain_carbs_initial = gr.Number(
                    label="Carbohidratos intraentreno (g)", 
                    precision=0,
                    value=150,
                    step=10,
                    minimum=0,
                    elem_classes="input-number"
                )
            with gr.Column(elem_classes="input-column"):
                rest_day_protein_initial = gr.Number(
                    label="Proteína día de descanso (g)", 
                    precision=0,
                    value=150,
                    step=10,
                    minimum=0,
                    elem_classes="input-number"
                )
                rest_day_carbs_initial = gr.Number(
                    label="Carbohidratos día de descanso (g)", 
                    precision=0,
                    value=150,
                    step=10,
                    minimum=0,
                    elem_classes="input-number"
                )
                rest_day_fat_initial = gr.Number(
                    label="Grasas día de descanso (g)", 
                    precision=0,
                    value=150,
                    step=10,
                    minimum=0,
                    elem_classes="input-number"
                )
    
    gr.Markdown(title_cuestionario_html)
    with gr.Group(elem_classes="input-group"):
        with gr.Row(elem_classes="input-row"):
            esfuerzo = gr.Dropdown(
                choices=textos_esfuerzo, 
                label="Esfuerzo dieta",
                value="No costó nada",
                elem_classes="input-dropdown"
            )
            cumplimiento_dieta = gr.Dropdown(
                choices=textos_cumplimiento_dieta, 
                label="Cumplimiento de la dieta",
                value="Perfecta",
                elem_classes="input-dropdown"
            )
            objetivo = gr.Dropdown(
                choices=textos_objetivo, 
                label="Objetivo",
                value="volumen (nada cambia)",
                elem_classes="input-dropdown"
            )
        with gr.Row(elem_classes="input-row"):
            cumplimiento_entr = gr.Dropdown(
                choices=textos_cumplimiento_entr, 
                label="Cumplimiento del entrenamiento",
                value="Lo hice perfecto",
                elem_classes="input-dropdown"
            )
            compromiso = gr.Dropdown(
                choices=textos_compromiso, 
                label="Compromiso",
                value="Máximo",
                elem_classes="input-dropdown"
            )
        with gr.Row(elem_classes="input-row"):
            peso_inicial = gr.Number(
                label="Peso inicial (kg)", 
                precision=2,
                value=70,
                step=0.1,
                elem_classes="input-number"
            )
            peso_final = gr.Number(
                label="Peso final (kg)", 
                precision=2,
                value=70.7,
                step=0.1,
                elem_classes="input-number"
            )
    
    # Versión simple del botón
    calcular_btn = gr.Button(
        "Calcular macros",
        variant="primary",
        size="lg",
        elem_classes="calcular-btn"
    )
    
    # Salidas
    gr.Markdown(title_macros_finales_html)
    with gr.Group(elem_classes="output-group"):
        with gr.Row(elem_classes="output-row"):
            with gr.Column():
                train_day_protein_final = gr.Number(label="Proteína día de entreno Final (g)", precision=0, elem_classes="output-number")
                train_day_carbs_final = gr.Number(label="Carbohidratos día de entreno Final (g)", precision=0, elem_classes="output-number")
                train_day_fat_final = gr.Number(label="Grasas día de entreno Final (g)", precision=0, elem_classes="output-number")
            with gr.Column():
                intratrain_protein_final = gr.Number(label="Proteína intraentreno Final (g)", precision=0, elem_classes="output-number")
                intratrain_carbs_final = gr.Number(label="Carbohidratos intraentreno Final (g)", precision=0, elem_classes="output-number")
            with gr.Column():
                rest_day_protein_final = gr.Number(label="Proteína día de descanso Final (g)", precision=0, elem_classes="output-number")
                rest_day_carbs_final = gr.Number(label="Carbohidratos día de descanso Final (g)", precision=0, elem_classes="output-number")
                rest_day_fat_final = gr.Number(label="Grasas día de descanso Final (g)", precision=0, elem_classes="output-number")
    
    # Logs
    logs = gr.Textbox(label="Logs", lines=10, elem_classes="output-textbox", visible=False)

    # Conectamos el botón con la función
    calcular_btn.click(
        fn=calcular_macros,
        inputs=[esfuerzo, objetivo, cumplimiento_entr, cumplimiento_dieta, 
                compromiso, peso_inicial, peso_final,
                train_day_protein_initial, train_day_carbs_initial, train_day_fat_initial,
                intratrain_protein_initial, intratrain_carbs_initial,
                rest_day_protein_initial, rest_day_carbs_initial, rest_day_fat_initial],
        outputs=[train_day_protein_final, train_day_carbs_final, train_day_fat_final,
                 intratrain_protein_final, intratrain_carbs_final,
                 rest_day_protein_final, rest_day_carbs_final, rest_day_fat_final,
                 logs]
    )

demo.launch()