fix config file io bug

app_text_classification.py

@@ -5,6 +5,7 @@ from io_utils import (
     write_scanners,
     read_inference_type,
     get_logs_file,
+    write_inference_type,
 )
 from wordings import INTRODUCTION_MD, CONFIRM_MAPPING_DETAILS_MD
 from text_classification_ui_helpers import (
@@ -96,7 +97,8 @@ def get_demo(demo):
         demo.load(get_logs_file, uid_label, logs, every=0.5)
 
     dataset_id_input.change(
-        check_dataset_and_get_config, inputs=[dataset_id_input, uid_label], outputs=[dataset_config_input]
+        check_dataset_and_get_config, 
+        inputs=[dataset_id_input, uid_label], outputs=[dataset_config_input]
     )
 
     dataset_config_input.change(
@@ -107,9 +109,20 @@ def get_demo(demo):
 
     scanners.change(write_scanners, inputs=[scanners, uid_label])
 
-    run_inference.change(select_run_mode, inputs=[run_inference, uid_label], outputs=[inference_token, run_local])
-
-    run_local.change(deselect_run_inference, inputs=[run_local], outputs=[inference_token, run_inference])
+    run_inference.change(
+        select_run_mode, 
+        inputs=[run_inference, inference_token, uid_label], 
+        outputs=[inference_token, run_local])
+    
+    run_local.change(
+        deselect_run_inference, 
+        inputs=[run_local], 
+        outputs=[inference_token, run_inference])
+    
+    inference_token.change(
+        write_inference_type, 
+        inputs=[run_inference, inference_token, uid_label])
+    
     gr.on(
         triggers=[label.change for label in column_mappings],
         fn=write_column_mapping_to_config,

io_utils.py

@@ -34,12 +34,14 @@ def read_scanners(uid):
 
 # convert a list of scanners to yaml file
 def write_scanners(scanners, uid):
-    with open(get_yaml_path(uid), "r+") as f:
+    with open(get_yaml_path(uid), "r") as f:
         config = yaml.load(f, Loader=yaml.FullLoader)
         if config:
             config["detectors"] = scanners
-            # save scanners to detectors in yaml
-            yaml.dump(config, f, Dumper=Dumper)
+    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()
 
 
@@ -54,18 +56,22 @@ def read_inference_type(uid):
 
 
 # write model_type to yaml file
-def write_inference_type(use_inference, uid):
-    with open(get_yaml_path(uid), "r+") as f:
+def write_inference_type(use_inference, inference_token, uid):
+    with open(get_yaml_path(uid), "r") as f:
         config = yaml.load(f, Loader=yaml.FullLoader)
         if use_inference:
             config["inference_type"] = "hf_inference_api"
+            config["inference_token"] = inference_token
         else:
             config["inference_type"] = "hf_pipeline"
-        # save inference_type to inference_type in yaml
+    f.close()
+    # 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()
 
 
+
 # read column mapping from yaml file
 def read_column_mapping(uid):
     column_mapping = {}
@@ -81,14 +87,16 @@ 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
     if mapping is None and "column_mapping" in config.keys():
         del config["column_mapping"]
     else:
         config["column_mapping"] = mapping
+
     with open(get_yaml_path(uid), "w") as f:
-        # save column_mapping to column_mapping in yaml
         yaml.dump(config, f, Dumper=Dumper)
     f.close()
 

text_classification_ui_helpers.py

@@ -42,9 +42,10 @@ def check_dataset_and_get_split(dataset_id, dataset_config):
         # gr.Warning(f"Failed to load dataset {dataset_id} with config {dataset_config}: {e}")
         pass
 
-def select_run_mode(run_inf, uid):
-    write_inference_type(run_inf, uid)
+def select_run_mode(run_inf, inf_token, uid):
     if run_inf:
+        if len(inf_token) > 0:
+            write_inference_type(run_inf, inf_token, uid)
         return (
             gr.update(visible=True),
             gr.update(value=False))