Quick fix for missing inference token

io_utils.py

@@ -28,7 +28,6 @@ def read_scanners(uid):
     with open(get_yaml_path(uid), "r") as f:
         config = yaml.load(f, Loader=yaml.FullLoader)
         scanners = config.get("detectors", [])
-    f.close()
     return scanners
 
 
@@ -38,11 +37,9 @@ def write_scanners(scanners, uid):
         config = yaml.load(f, Loader=yaml.FullLoader)
         if config:
             config["detectors"] = scanners
-    f.close()
     # save scanners to detectors in yaml
     with open(get_yaml_path(uid), "w") as f:
         yaml.dump(config, f, Dumper=Dumper)
-    f.close()
 
 
 # read model_type from yaml file
@@ -51,7 +48,6 @@ def read_inference_type(uid):
     with open(get_yaml_path(uid), "r") as f:
         config = yaml.load(f, Loader=yaml.FullLoader)
         inference_type = config.get("inference_type", "")
-    f.close()
     return inference_type
 
 
@@ -64,11 +60,11 @@ def write_inference_type(use_inference, inference_token, uid):
             config["inference_token"] = inference_token
         else:
             config["inference_type"] = "hf_pipeline"
-    f.close()
+            # FIXME: A quick and temp fix for missing token
+            config["inference_token"] = ""
     # save inference_type to inference_type in yaml
     with open(get_yaml_path(uid), "w") as f:
         yaml.dump(config, f, Dumper=Dumper)
-    f.close()
 
 
 
@@ -79,7 +75,6 @@ def read_column_mapping(uid):
         config = yaml.load(f, Loader=yaml.FullLoader)
         if config:
             column_mapping = config.get("column_mapping", dict())
-    f.close()
     return column_mapping
 
 
@@ -87,7 +82,6 @@ def read_column_mapping(uid):
 def write_column_mapping(mapping, uid):
     with open(get_yaml_path(uid), "r") as f:
         config = yaml.load(f, Loader=yaml.FullLoader)
-    f.close()
 
     if config is None:
         return
@@ -98,7 +92,6 @@ def write_column_mapping(mapping, uid):
 
     with open(get_yaml_path(uid), "w") as f:
         yaml.dump(config, f, Dumper=Dumper)
-    f.close()
 
 
 # convert column mapping dataframe to json
@@ -121,7 +114,6 @@ def get_logs_file(uid):
 def write_log_to_user_file(id, log):
     with open(f"./tmp/{id}_log", "a") as f:
         f.write(log)
-    f.close()
 
 
 def save_job_to_pipe(id, job, lock):