Update app.py

app.py

@@ -1,55 +1,11 @@
-# importing required modules
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import datetime
-from datetime import timedelta
-import time
-import copy
-import openpyxl as xl
-import json
-import gradio as gr
-import io
-from PIL import Image
+from huggingface_hub import Repository
+import os
+from huggingface_hub import hf_hub_download
 
-#importing 3 functions:
-import GA
-import OR_tools as ort
-import MIP
+token=os.environ["HUGGING_FACE_HUB_TOKEN"] 
 
-def plotly_fig2array(fig):
-    #convert Plotly fig to  an array
-    fig_bytes = fig.to_image(format="png")
-    buf = io.BytesIO(fig_bytes)
-    img = Image.open(buf)
-    return np.asarray(img)
-
-def JSSP(method,temp_file):
-    xls = pd.ExcelFile(temp_file.name)
-    print(xls)
-    print("Input File is :",xls)
-    if method == "Genetic Algo":
-      op, fig, df = GA.input_file(xls)
-      
-    elif method == "Python OR":
-      op, fig, df = ort.or_fn(xls)
-        
-    else:
-      op, fig, df = MIP.MIP_fn(xls)
-    
-    img = plotly_fig2array(fig)
-    # data = pd.DataFrame(df)
-    df.to_excel("op_data.xlsx",index=False)
-    data_op = ["op_data.xlsx"]
-    return op, img,data_op
-
-demo = gr.Interface(JSSP,
-                             inputs=[gr.Radio(["Genetic Algo", "Python OR", "MIP solution"], label="Solution Method", info="Choose one method to solve ypur Job Shop problem."),gr.File(label = 'Input File')],
-                             examples =[["Python OR","Demo_data.xlsx"]],
-                             outputs = ["text","image",gr.File(label='Output File')],
-                             title = "Job Shop Scheduling Problem",
-                             description = "Upload an excel file containing Machine Sequnce and Processing Time for a n x m problem to optimize makespan for manufacturing or Job schedule. Choose the method you want the problem to be solved before clicking Submit! \n For Demo purpose, use the example data provided BELOW.",
-                             cache_examples = False )
-
-
-demo.queue().launch(debug=True,show_error=True)
+# Download from a dataset
+hf_hub_download(repo_id="Brillio-DS/Optimization_JSSP",local_dir=os.getcwd(), filename="main.py", repo_type="dataset")
+print(os.listdir())
+from main import run
+run()