Update app.py

app.py

@@ -28,7 +28,9 @@ except ImportError:
 MODEL_PATH = os.getenv("MODEL_PATH", "speakleash/sojka3")
 TOKENIZER_PATH = os.getenv("TOKENIZER_PATH", "sdadas/mmlw-roberta-base") 
 
-REPO_ID = "speakleash/sojka-logs"
+LOGS_REPO_ID = "speakleash/sojka-logs"
+LOGS_HF_TOKEN = os.getenv("LOG_HF_TOKEN")
+
 
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 LABELS = ["self-harm", "hate", "vulgar", "sex", "crime"]
@@ -51,11 +53,11 @@ logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(
 logger = logging.getLogger(__name__)
 
 # HfApi instance
-if HF_TOKEN:
+if LOGS_HF_TOKEN:
     api = HfApi()
 else:
     api = None
-    logger.warning("HF_TOKEN environment variable not set. Logging to Hugging Face Hub will be disabled.")
+    logger.warning("LOGS_HF_TOKEN environment variable not set. Logging to Hugging Face Hub will be disabled.")
 
 def log_prediction(log_data: dict):
     logger.info("Logging to Hugging Face Hub...")
@@ -67,18 +69,18 @@ def log_prediction(log_data: dict):
     timestamp = log_data.get('timestamp', datetime.now().timestamp())
 
     try:
-        logger.info("Logging to Hugging Face Hub upload_file: ", log_data)
+        #logger.info("Logging to Hugging Face Hub upload_file: ", log_data)
 
         api.upload_file(
             path_or_fileobj=json.dumps(log_data, indent=2, ensure_ascii=False).encode('utf-8'),
             path_in_repo=f"predictions/{day}/{timestamp}.json",
-            repo_id=REPO_ID,
+            repo_id=LOGS_REPO_ID,
             repo_type="dataset",
             commit_message="log prediction",
-            token=HF_TOKEN,
-            run_as_future=False
+            token=LOGS_HF_TOKEN,
+            run_as_future=True
         )
-        logger.info("Logging to Hugging Face Hub upload_file finished")
+        #logger.info("Logging to Hugging Face Hub upload_file finished")
 
     except Exception as e:
         logger.error(f"Failed to log prediction to hub: {e}")