upload_train.py

import dash
from dash import dcc, html
import plotly.graph_objects as go
import dash_bootstrap_components as dbc
from plotly.subplots import make_subplots
from dash.dependencies import Input, Output, State
from init import app
import io
import base64
import pandas as pd


# Save csv file

def save_csv(contents, filename):
    content_tpye, content_string = contents.split(',')
    decoded = base64.b64decode(content_string)

    if 'csv' in filename:
        df = pd.read_csv(io.StringIO(decoded.decode('utf-8')))
    elif 'xls' in filename:
        df = pd.read_excel(io.BytesIO(decoded))
    else:
        return "This file type is not supported"
    df.to_csv("./new_data.csv")

    return "Retrained"

# update response


@app.callback(
    Output("response", "children"),
    [Input("trainButton", "n_clicks"),
     Input("upload_file", "contents")],
    [State("upload_file", "filename")])
def update_response(btn1, contents, filename):
    changed_id = [p['prop_id'] for p in dash.callback_context.triggered][0]
    if contents == None:
        message = "Not upload file !!!"
    else:
        message = save_csv(contents, filename)
    if 'trainButton' in changed_id:
        return (message)


# =========================================================
# add training dropdown
dropdown = dbc.FormGroup(
    [
        dbc.Label("Mode of training", html_for="dropdown"),
        dcc.Dropdown(
            id="training_mode",
            options=[
                {"label": "Quick Training (Low Accuracy)", "value": 1},
                {"label": "Satisfactory Training (Recommended Medium Accuracy)",
                 "value": 2},
                {"label": "Rigourous Training (High Accuracy)", "value": 3}
            ]
        )
    ]
)


header = html.Div(
    style={'fontSize': '25px'},
    id="response"
)

upload_button = dcc.Upload(
    dbc.Button('Upload File', color='info'),
    id='upload_file',
    
)

train_button = dbc.Button(
    "Train Model",
    color="info",
    id="trainButton",
    href='',
    n_clicks=0
)

predictions_button = dbc.Button(
    "See Predictions",
    color="success",
    href="/predictions"
)

# Card
card = dbc.Card(
    dbc.CardBody(
        [
            html.H2("Training Models", className="card-title"),
            html.H6("To keep the model Renewed and for getting better predictions keep retraining the model with new values. Just select the mode of", className="card-text"),
            html.H6("training according to your need. Upload the CSV file with new data point and Click on Train Model", className="card-text"),

            html.Br(),
            html.Div(style={"marginLeft": "10px",
                     "marginRight": "10px"}, children=dropdown),
            html.Br(),
            dbc.Row([dbc.Col(upload_button, width=6),
                    dbc.Col(train_button, width=6)]),
            html.Br(),
            dbc.Row([dbc.Col(header, width=8), dbc.Col(
                predictions_button, width=4)])
        ]
    ),
    style={"width": "18rem",
           'textAlign': 'center',
           },
    className="w-100 mb-4"
)


# Layout
layout = html.Div(
    className="container",
    style={},
    children=[
        html.Br(),
        html.Br(),
        card
    ]
)