Update app.py

app.py

@@ -1,10 +1,11 @@
 # 🔍 Masked Word Predictor | CPU-only HF Space
 
 import gradio as gr
+import pandas as pd
 from transformers import pipeline
 from transformers.pipelines.base import PipelineException
 
-# 1. Load fill-mask pipeline once
+# 1. Load the fill-mask pipeline once
 fill_mask = pipeline("fill-mask", model="distilroberta-base", device=-1)
 
 def predict_mask(sentence: str, top_k: int):
@@ -16,16 +17,21 @@ def predict_mask(sentence: str, top_k: int):
 
     # 4. Validate presence of mask
     if mask not in sentence:
-        return [["Error: please include `[MASK]` in your sentence.", 0.0]]
+        return pd.DataFrame(
+            [["Error: please include `[MASK]` in your sentence.", 0.0]],
+            columns=["Sequence", "Score"]
+        )
 
     # 5. Run the pipeline safely
     try:
         preds = fill_mask(sentence, top_k=top_k)
     except PipelineException as e:
-        return [[f"Error: {str(e)}", 0.0]]
+        return pd.DataFrame([[f"Error: {str(e)}", 0.0]],
+                            columns=["Sequence", "Score"])
 
-    # 6. Return list-of-lists for the Table
-    return [[p["sequence"], round(p["score"], 3)] for p in preds]
+    # 6. Build a DataFrame from list-of-lists
+    rows = [[p["sequence"], round(p["score"], 3)] for p in preds]
+    return pd.DataFrame(rows, columns=["Sequence", "Score"])
 
 with gr.Blocks(title="🔍 Masked Word Predictor") as demo:
     gr.Markdown(
@@ -46,16 +52,18 @@ with gr.Blocks(title="🔍 Masked Word Predictor") as demo:
 
     predict_btn = gr.Button("Predict 🔍", variant="primary")
 
-    # ← Use Table here (list-of-lists) instead of Dataframe
-    results_table = gr.Table(
+    results_df = gr.Dataframe(
         headers=["Sequence", "Score"],
+        datatype=["str", "number"],
+        wrap=True,
+        interactive=False,
         label="Predictions"
     )
 
     predict_btn.click(
         fn=predict_mask,
         inputs=[sentence, top_k],
-        outputs=results_table
+        outputs=results_df
     )
 
 if __name__ == "__main__":