Update app.py

app.py

@@ -3,6 +3,9 @@ from huggingface_hub import InferenceClient
 
 from datasets import load_dataset
 
+global ds
+
+
 """
 For more information on `huggingface_hub` Inference API support, 
 please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
@@ -69,20 +72,32 @@ def load_new_dataset():
     gr.Info(message="Loading dataset...")
     ds = load_dataset("fka/awesome-chatgpt-prompts", split="train")
 
-def run_query(query):
-    # Placeholder function to simulate a query
-    return {"Result": f"Results for '{query}'"}
+def run_query(input: str):
+    try:
+        df_results = duckdb.sql(
+            query=f"""
+            SELECT *
+            FROM ds
+            WHERE act LIKE '%{input}%'
+            """
+        ).to_df()
+
+        logging_message = f"Results for '{input}' found."
+    except Exception as e:
+        raise gr.Error(f"Error running query: {e}")
+    
+    return df_results, logging_message
 
 #----------------------
 
 with gr.Blocks() as demo:
-    text_input = gr.Textbox(visible=True, label="Query")
+    text_input = gr.Textbox(visible=True, label="Enter value for 'act':")
     btn_run = gr.Button(visible=True, value="Search")
     results_output = gr.Dataframe(label="Results", visible=True, wrap=True)
     logging_output = gr.Label(visible="True", value="My first logging message")
     
     btn_run.click(
-        fn=lambda query: (run_query(query), "Button pressed!"),  # Call the run_query function and update the label
+        fn=run_query,  # Call the run_query function and update the label
         inputs=text_input,
         outputs=[results_output, logging_output]  # Update both the DataFrame and the label
     )