Update app.py

app.py

@@ -18,6 +18,20 @@ def get_baseline_df():
     df = df[present_columns]
     return df
 
+def update_yaml(representation_name, benchmark_type, human_file_path, skempi_file_path):
+    with open("./src/bin/probe_config.yaml", 'r') as file:
+        yaml_data = yaml.safe_load(file)
+
+    yaml_data['representation_name'] = representation_name
+    yaml_data['benchmark'] = benchmark_type
+    yaml_data['representation_file_human'] = human_file
+    yaml_data['representation_file_affinity'] = skempi_file
+
+    with open("./src/bin/probe_config.yaml", "w") as file:
+        yaml.dump(yaml_data, file)
+
+    return None
+
 def add_new_eval(
     human_file,
     skempi_file,
@@ -26,8 +40,9 @@ def add_new_eval(
     benchmark_type: str,
 ):
     representation_name = model_name_textbox if revision_name_textbox == '' else revision_name_textbox
-    print(representation_name)
-    print(benchmark_type)
+
+    update_yaml(representation_name, benchmark_type, human_file, skempi_file)
+    
     # Save human and skempi files under ./src/data/representation_vectors using pandas
     print(human_file)
     df = pd.read_csv(human_file)
@@ -97,7 +112,7 @@ with block:
 
             with gr.Column():
                 human_file = gr.components.File(label="Click to Upload the representation file (csv) for Human dataset", file_count="single", type='filepath')
-                skempi_file = gr.components.File(label="Click to Upload the representation file (csv) for SKEMPI dataset", file_count="single", type='binary')
+                skempi_file = gr.components.File(label="Click to Upload the representation file (csv) for SKEMPI dataset", file_count="single", type='filepath')
     
                 submit_button = gr.Button("Submit Eval")
                 submission_result = gr.Markdown()