* fixing fmops detection

* fixing encoding when storing the file

app.py

@@ -65,13 +65,13 @@ fmops_classifier = init_prompt_injection_model(
 )  # ONNX version of fmops/distilbert-prompt-injection
 
 
-def detect_hf(prompt: str, threshold: float = 0.5, classifier=laiyer_classifier) -> (bool, bool):
+def detect_hf(
+    prompt: str, threshold: float = 0.5, classifier=laiyer_classifier, label: str = "INJECTION"
+) -> (bool, bool):
     try:
         pi_result = classifier(prompt)
         injection_score = round(
-            pi_result[0]["score"]
-            if pi_result[0]["label"] == "INJECTION"
-            else 1 - pi_result[0]["score"],
+            pi_result[0]["score"] if pi_result[0]["label"] == label else 1 - pi_result[0]["score"],
             2,
         )
 
@@ -92,7 +92,7 @@ def detect_hf_deepset(prompt: str) -> (bool, bool):
 
 
 def detect_hf_fmops(prompt: str) -> (bool, bool):
-    return detect_hf(prompt, classifier=fmops_classifier)
+    return detect_hf(prompt, classifier=fmops_classifier, label="LABEL_1")
 
 
 def detect_lakera(prompt: str) -> (bool, bool):
@@ -167,8 +167,11 @@ def execute(prompt: str, store_to_dataset: bool = True) -> List[Union[str, bool,
 
     # Save image and result
     if store_to_dataset:
-        fileobj = json.dumps({"prompt": prompt, "results": results}, indent=2).encode("utf-8")
+        fileobj = json.dumps(
+            {"prompt": prompt, "results": results}, indent=2, ensure_ascii=False
+        ).encode("utf-8")
         result_path = f"/prompts/train/{str(uuid.uuid4())}.json"
+
         hf_api.upload_file(
             path_or_fileobj=fileobj,
             path_in_repo=result_path,
@@ -221,4 +224,5 @@ if __name__ == "__main__":
         ],
         cache_examples=True,
         allow_flagging="never",
-    ).queue(1).launch(server_name=args.url, server_port=args.port)
+        concurrency_limit=1,
+    ).launch(server_name=args.url, server_port=args.port)