suryadev1 commited on
Commit
fc81369
·
verified ·
1 Parent(s): 8c9bcfc

Update app.py

Browse files

changed to appkly the path analysis tool function

Files changed (1) hide show
  1. app.py +47 -11
app.py CHANGED
@@ -1,5 +1,5 @@
1
  import gradio as gr
2
- from huggingface_hub import hf_hub_download
3
  import pickle
4
  from gradio import Progress
5
  import numpy as np
@@ -12,9 +12,39 @@ import plotly.graph_objects as go
12
  from sklearn.metrics import roc_auc_score
13
  from matplotlib.figure import Figure
14
  import csv
 
 
 
15
  # import os
16
  # Define the function to process the input file and model selection
17
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
18
  def process_file(model_name,inc_slider,progress=Progress(track_tqdm=True)):
19
  # progress = gr.Progress(track_tqdm=True)
20
 
@@ -213,6 +243,8 @@ def process_file(model_name,inc_slider,progress=Progress(track_tqdm=True)):
213
  row_num += 1
214
 
215
  print(f"CSV file '{filename}' created successfully.")
 
 
216
 
217
  task_type_map = {0: "ER", 1: "ME"}
218
  label_map = {0: "unsuccessful", 1: "successful"}
@@ -1305,26 +1337,30 @@ with gr.Blocks(theme='gstaff/sketch', css=custom_css) as demo:
1305
 
1306
  # with gr.Row():
1307
  with gr.Column():
1308
- with gr.Group(visible=False) as file_output_group:
1309
-
1310
- gr.Markdown("**Download strategy descriptor files**")
1311
- file_output_success = gr.File(label=" ")
1312
- file_output_unsuccess = gr.File(label=" ")
1313
- file_output_all = gr.File(label=" ")
1314
- visualize_markdown = gr.Markdown(visible=False)
1315
 
1316
 
1317
  def handle_generate(task_type_dropdown, use_predicted):
1318
  label_source = "Predicted" if use_predicted else "Ground Truth"
1319
  file_success_path, file_unsuccess_path,file_all_path, viz_link = provide_file_paths(task_type_dropdown, label_source)
 
 
 
1320
 
1321
- return file_success_path, file_unsuccess_path,file_all_path, viz_link,gr.update(visible=True)
 
 
 
 
 
1322
 
1323
 
1324
  generate_button.click(
1325
  fn=handle_generate,
1326
  inputs=[task_type_radio, source_radio],
1327
- outputs=[file_output_success, file_output_unsuccess,file_output_all, visualize_markdown,file_output_group]
1328
  )
1329
 
1330
  btn.click(
@@ -1338,7 +1374,7 @@ with gr.Blocks(theme='gstaff/sketch', css=custom_css) as demo:
1338
  gr.update(visible=False) # Hide visualize markdown
1339
  ),
1340
  inputs=[model_dropdown, increment_slider],
1341
- outputs=[output_text, plot_output, opt1_pie, opt2_pie, task_type_radio,source_radio,file_output_success,file_output_unsuccess,file_output_all, visualize_markdown]
1342
  )
1343
 
1344
 
 
1
  import gradio as gr
2
+ from huggingface_hub import hf_hub_download, HfApi
3
  import pickle
4
  from gradio import Progress
5
  import numpy as np
 
12
  from sklearn.metrics import roc_auc_score
13
  from matplotlib.figure import Figure
14
  import csv
15
+ import os
16
+ from huggingface_hub import login
17
+
18
  # import os
19
  # Define the function to process the input file and model selection
20
 
21
+ api = HfApi()
22
+ DATASET_REPO = "suryadev1/generated-csvs"
23
+ def delete_files():
24
+ repo_files = api.list_repo_files(repo_id=DATASET_REPO, repo_type="dataset")
25
+
26
+ # Step 2: delete all CSV files
27
+ for f in repo_files:
28
+ if f.endswith(".csv"):
29
+ try:
30
+ api.delete_file(
31
+ path_in_repo=f,
32
+ repo_id=DATASET_REPO,
33
+ repo_type="dataset"
34
+ )
35
+ print(f"Deleted old file: {f}")
36
+ except Exception as e:
37
+ print(f"Could not delete {f}: {e}")
38
+ def upload_to_dataset(filepath):
39
+
40
+ api.upload_file(
41
+ path_or_fileobj=filepath,
42
+ path_in_repo=os.path.basename(filepath),
43
+ repo_id=DATASET_REPO,
44
+ repo_type="dataset"
45
+ )
46
+
47
+
48
  def process_file(model_name,inc_slider,progress=Progress(track_tqdm=True)):
49
  # progress = gr.Progress(track_tqdm=True)
50
 
 
243
  row_num += 1
244
 
245
  print(f"CSV file '{filename}' created successfully.")
246
+ full_path = os.path.join("fileHandler", filename)
247
+ # upload_to_dataset(full_path)
248
 
249
  task_type_map = {0: "ER", 1: "ME"}
250
  label_map = {0: "unsuccessful", 1: "successful"}
 
1337
 
1338
  # with gr.Row():
1339
  with gr.Column():
1340
+ with gr.Group(visible=True) as file_output_group:
1341
+
1342
+ visualize_markdown = gr.Markdown(visible=True)
 
 
 
 
1343
 
1344
 
1345
  def handle_generate(task_type_dropdown, use_predicted):
1346
  label_source = "Predicted" if use_predicted else "Ground Truth"
1347
  file_success_path, file_unsuccess_path,file_all_path, viz_link = provide_file_paths(task_type_dropdown, label_source)
1348
+ delete_files()
1349
+ print("writing file to the dataset",file_success_path)
1350
+ # full_path = os.path.join("fileHandler", filename)
1351
 
1352
+ upload_to_dataset(file_success_path)
1353
+ print("writing file to the dataset",file_unsuccess_path)
1354
+ upload_to_dataset(file_unsuccess_path)
1355
+ print("writing file to the dataset",file_all_path)
1356
+ upload_to_dataset(file_all_path)
1357
+ return viz_link,gr.update(visible=True)
1358
 
1359
 
1360
  generate_button.click(
1361
  fn=handle_generate,
1362
  inputs=[task_type_radio, source_radio],
1363
+ outputs=[ visualize_markdown,file_output_group]
1364
  )
1365
 
1366
  btn.click(
 
1374
  gr.update(visible=False) # Hide visualize markdown
1375
  ),
1376
  inputs=[model_dropdown, increment_slider],
1377
+ outputs=[output_text, plot_output, opt1_pie, opt2_pie, task_type_radio,source_radio, visualize_markdown]
1378
  )
1379
 
1380