Update app.py

app.py

@@ -38,9 +38,14 @@ examples = [
 ]
 
 #inf_dataset=load_dataset("atlasia/atlaset_inference_ds",token=token,split="test",name="llm")
-detected_commit=False
 submit_file = Path("user_submit/") / f"data_{uuid.uuid4()}.json"
-
+scheduler = CommitScheduler(
+            repo_id="atlasia/atlaset_inference_ds",
+            repo_type="dataset",
+            folder_path=submit_file,
+            every=5,
+            token=token
+        )
 @spaces.GPU
 def generate_text(prompt, max_length=256, temperature=0.7, top_p=0.9, top_k=150, num_beams=8, repetition_penalty=1.5):
     inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
@@ -60,7 +65,6 @@ def generate_text(prompt, max_length=256, temperature=0.7, top_p=0.9, top_k=150,
     result=tokenizer.decode(output[0], skip_special_tokens=True)
     #inf_dataset.add_item({"inputs":prompt,"outputs":result,"params":f"{max_length},{temperature},{top_p},{top_k},{num_beams},{repetition_penalty}"})
     save_feedback(prompt,result,f"{max_length},{temperature},{top_p},{top_k},{num_beams},{repetition_penalty}")
-    detected_commit=True
     return result
 
 def save_feedback(input,output,params) -> None:
@@ -68,7 +72,6 @@ def save_feedback(input,output,params) -> None:
         with feedback_file.open("a") as f:
             f.write(json.dumps({"input": input, "output": output, "params": params}))
             f.write("\n")
-    detected_commit=True
     
 if __name__ == "__main__":
     # Create the Gradio interface
@@ -89,14 +92,4 @@ if __name__ == "__main__":
             description="Enter a prompt and get AI-generated text using our pretrained LLM on Moroccan Darija.",
             examples=examples,
         )
-    if detected_commit:
-        print("[INFO] CommitScheduler...")
-        scheduler = CommitScheduler(
-            repo_id="atlasia/atlaset_inference_ds",
-            repo_type="dataset",
-            folder_path=submit_file,
-            every=5,
-            token=token
-        )
-        detected_commit=False
     app.launch()