Create app.py

app.py

@@ -0,0 +1,57 @@
+import pandas as pd
+import gradio as gr
+df = pd.read_json("data.json")
+
+
+def filter_data(x, language):
+    language_filtered_df = df[df['language'] == language]
+    lower_bound = x
+    upper_bound = x + 0.1
+    mask = (language_filtered_df['prev_nn_sim'] >= lower_bound) & (language_filtered_df['prev_nn_sim'] < upper_bound)
+    filtered_df = language_filtered_df.loc[mask, ["prompt", "prev_nn_prompt", "prev_nn_sim"]]
+    filtered_df = filtered_df.sort_values(by="prev_nn_sim", ascending=True)
+    return filtered_df
+
+custom_css = """
+#my_table table {
+    table-layout: fixed;
+    width: 100%;               /* or a fixed width like 700px */
+}
+#my_table table th,
+#my_table table td {
+    /* Force wrapping within cells: */
+    white-space: normal;       
+    word-wrap: break-word;     
+    overflow-wrap: break-word;
+    /* Example fixed width for all columns (or use nth-child to target individually): */
+    width: 200px;              
+}
+"""
+
+with gr.Blocks(css=custom_css) as demo:
+    gr.Markdown("## Prompt Freshness Nearest Neighbor")
+    gr.Markdown("### Select a similarity threshold (x) and a language to see the prompts that are within 0.1 of x. ")
+    gr.Markdown("The nearest neighbor prompt is the prompt that is most similar to the original prompt that appears at a previous time step.")
+
+    dropdown = gr.Dropdown(
+        choices=[round((i + 3) * 0.1, 1) for i in range(7)], 
+        value=0.7,  
+        label="Select a similarity threshold (x)"
+    )
+    
+    language_dropdown = gr.Dropdown(
+        choices=df['language'].unique().tolist(), 
+        value="English", 
+        label="Select a language"
+    )
+    
+    output = gr.DataFrame(
+        label="Filtered Data",
+        headers=["Prompt", "Nearest Neighbor Prompt", "Nearest Neighbor Similarity"],
+        elem_id="my_table"  
+    )
+    
+    dropdown.change(fn=filter_data, inputs=[dropdown, language_dropdown], outputs=output)
+    language_dropdown.change(fn=filter_data, inputs=[dropdown, language_dropdown], outputs=output)
+
+demo.launch(share=True)