added scheduler

gradio_app.py

@@ -3,6 +3,7 @@ import time
 import csv
 import datetime
 import gradio
+import schedule
 from gradio import utils
 import huggingface_hub
 from pathlib import Path
@@ -27,8 +28,7 @@ repo = huggingface_hub.Repository(
 )
 repo.git_pull(lfs=True)
 
-def log_record(vals):
-    
+def log_record(vals):    
     log_file = Path(dataset_dir) / "data.csv"    
     is_new = not Path(log_file).exists()        
     with open(log_file, "a", newline="", encoding="utf-8") as csvfile:
@@ -37,13 +37,8 @@ def log_record(vals):
             writer.writerow(utils.sanitize_list_for_csv(headers))
         writer.writerow(utils.sanitize_list_for_csv(vals))
     
-    with open(log_file, "r", encoding="utf-8") as csvfile:
-        line_count = len([None for _ in csv.reader(csvfile)]) - 1
-    repo.git_add()
-    repo.git_commit(f"Logged sample #{line_count}")
-    repo.git_push()
-    # repo.push_to_hub(commit_message=f"Logged sample #{line_count}")
-    
+    # with open(log_file, "r", encoding="utf-8") as csvfile:
+    #     line_count = len([None for _ in csv.reader(csvfile)]) - 1    
 
 def predict(sentence):
     
@@ -54,7 +49,7 @@ def predict(sentence):
     
     output = classes[predictions[0]]
     
-    print(f"Sentence: {sentence} \nPredictions: {predictions} - {output}")    
+    print(f"Sentence: {sentence} \nPrediction: {predictions[0]} - {output}")    
     log_record([sentence, output, timestamp, str(elapsed_time)])
     
     return output
@@ -64,7 +59,15 @@ gradio.Interface(
     fn=predict,
     inputs="text",
     outputs="text",
-    allow_flagging='auto',
-    flagging_dir='logs',
-    flagging_callback=gradio.SimpleCSVLogger(),
+    allow_flagging='never'
 ).launch()
+
+
+def sync_logs():
+    if not repo.is_repo_clean():
+        repo.git_add()
+        repo.git_commit()
+        # repo.git_push()
+        repo.push_to_hub()
+    
+schedule.every(2).minutes.do(sync_logs)

requirements.txt

@@ -14,4 +14,5 @@ flask
 torch
 torchvision 
 scikit-learn
-numpy
+numpy
+schedule