cosmetic change

app.py

@@ -1,9 +1,9 @@
 import gradio as gr
-import pandas as pd
 from green_score import GREEN
 import spaces
 
-@spaces.GPU  # Add the GPU decorator for functions that need GPU access
+
+@spaces.GPU(duration=120)  # Add the GPU decorator for functions that need GPU access
 def run_green(ref_text, hyp_text, model_name="StanfordAIMI/GREEN-radllama2-7b"):
     refs = [ref_text.strip()]
     hyps = [hyp_text.strip()]
@@ -11,13 +11,16 @@ def run_green(ref_text, hyp_text, model_name="StanfordAIMI/GREEN-radllama2-7b"):
     green_scorer = GREEN(model_name, output_dir=".")
     mean, std, green_score_list, summary, result_df = green_scorer(refs, hyps)
 
-    final_summary = (
-        f"**Model:** {model_name}\n\n"
-        f"**Mean GREEN Score:** {mean:.4f}\n"
-        f"**Std Deviation:** {std:.4f}\n\n"
-        f"**Detailed Summary:**\n{summary}"
-    )
-    return final_summary, pd.DataFrame(result_df), green_score_list
+    green_analysis_text = result_df["green_analysis"].iloc[0]
+
+    # Prepare data for the nx2 table
+    table_data = []
+    for key, value in result_df.iloc[0].to_dict().items():
+        if key not in ["reference", "predictions", "green_analysis"]:
+            table_data.append([key, value])
+
+    return green_analysis_text, table_data
+
 
 # Example pairs
 examples = {
@@ -35,11 +38,14 @@ examples = {
     }
 }
 
+
 def update_fields(choice):
     if choice == "Custom":
         return gr.update(value="", interactive=True), gr.update(value="", interactive=True)
     else:
-        return gr.update(value=examples[choice]["ref"], interactive=False), gr.update(value=examples[choice]["hyp"], interactive=False)
+        return gr.update(value=examples[choice]["ref"], interactive=False), gr.update(value=examples[choice]["hyp"],
+                                                                                      interactive=False)
+
 
 with gr.Blocks(title="GREEN Score Evaluation Demo") as demo:
     gr.Markdown("# GREEN Score Evaluation Demo")
@@ -77,14 +83,20 @@ with gr.Blocks(title="GREEN Score Evaluation Demo") as demo:
     )
 
     run_button = gr.Button("Compute GREEN Score")
-    summary_output = gr.Markdown()
-    df_output = gr.DataFrame()
-    score_list_output = gr.JSON()
+    green_analysis_output = gr.Textbox(
+        label="GREEN Analysis",
+        lines=10,
+        interactive=False
+    )
+    table_output = gr.DataFrame(
+        label="Scores and Errors",
+        headers=["Metric", "Value"]
+    )
 
     run_button.click(
         run_green,
         inputs=[ref_input, hyp_input, model_name_input],
-        outputs=[summary_output, df_output, score_list_output]
+        outputs=[green_analysis_output, table_output]
     )
 
 demo.launch()