Update app.py

app.py

@@ -1,3 +1,7 @@
+
+# https://huggingface.co/spaces/CK42/sentiment-model-comparison/blob/main/app.py
+
+# import sklearn
 from os import O_ACCMODE
 import gradio as gr
 import joblib
@@ -6,45 +10,25 @@ import requests.exceptions
 from huggingface_hub import HfApi, hf_hub_download
 from huggingface_hub.repocard import metadata_load
 
-# work around for error, not happy really
-# import os
-# os.environ['KMP_DUPLICATE_LIB_OK']='True'
 
 app = gr.Blocks()
 
-model_1 = "juliensimon/distilbert-amazon-shoe-reviews"
-model_2 = "juliensimon/distilbert-amazon-shoe-reviews"
+model_id_1 = "juliensimon/distilbert-amazon-shoe-reviews"
+model_id_2 = "juliensimon/distilbert-amazon-shoe-reviews"
 
-def load_agent(model_id_1, model_id_2):
+def load_agent(model_id):
     """
     This function load the agent's results
     """
     # Load the metrics
-    metadata_1 = get_metadata(model_id_1)
+    metadata = get_metadata(model_id)
 
     # get predictions
-    predictions_1 = predict(model_id_1)
-    
-    # Get the accuracy
-    # results_1 = parse_metrics_accuracy(metadata_1)
-    
-    # Load the metrics
-    metadata_2 = get_metadata(model_id_2)
+    predictions = predict(model_id)
 
-    # get predictions
-    predictions_2 = predict(model_id_2)
-    # Get the accuracy
-    # results_2 = parse_metrics_accuracy(metadata_2)
 
-    return model_id_1, predictions_1, model_id_2, predictions_2
+    return model_id, predictions
 
-# def parse_metrics_accuracy(meta):
-#     if "model-index" not in meta:
-#         return None
-#     result = meta["model-index"][0]["results"]
-#     metrics = result[0]["metrics"]
-#     accuracy = metrics[0]["value"]
-#     return accuracy
 
 def get_metadata(model_id):
     """
@@ -91,7 +75,7 @@ with app:
       model1_input = gr.Textbox(label="Model 1")
     with gr.Row():
         btn = gr.Button("Prediction for Model 1")
-    btn.click(fn=predict(model_1), inputs=inp_1, outputs=out_2)
+    btn.click(fn=load_agent(model_id_1), inputs=inp_1, outputs=out_2)
 
 
 
@@ -99,13 +83,13 @@ with app:
       model2_input = gr.Textbox(label="Model 2") 
     with gr.Row():
         btn = gr.Button("Prediction for Model 2")
-    btn.click(fn=predict(model_2), inputs=inp_1, outputs=out_2)
+    btn.click(fn=predict(model_id_2), inputs=inp_1, outputs=out_2)
 
 
-    app_button.click(load_agent, inputs=[model1_input, model2_input], outputs=[model1_name, model1_score_output, model2_name, model2_score_output])
+    # app_button.click(load_agent, inputs=[model1_input, model2_input], outputs=[model1_name, model1_score_output, model2_name, model2_score_output])
     
     # examples = gr.Examples(examples=[["juliensimon/distilbert-amazon-shoe-reviews","juliensimon/distilbert-amazon-shoe-reviews"]],
     #                        inputs=[model1_input, model2_input])
 
     
-app.launch()
+app.launch()