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gsql_app.py

@@ -4,14 +4,13 @@ import pandas as pd
 import gradio as gr
 from datasets import load_dataset
 import tempfile
-import re
 from query import sql_query
 
 max_rows = 20
+max_cols = None
+
 df_display_kwargs = dict(
     wrap = True,
-    max_rows = max_rows,
-    type = "pandas",
     row_count = 3,
     col_count = 4,
 )
@@ -23,13 +22,6 @@ dataset_choices = [
 
 def apply_sql(input_table, sql_query):
 
-    # Use regex to extract the table name from the SQL query
-    match = re.search(r"\bFROM\s+(\w+)", sql_query, re.IGNORECASE)
-    if match:
-        table_name = match.group(1)
-
-    sql_query = sql_query.replace(table_name, "input_table")
-
     output_df = duckdb.query(sql_query).to_df()
 
     return output_df
@@ -38,18 +30,18 @@ def display_dataset(dataset_id):
 
     dataset = load_dataset(dataset_id, split="train")
     df = dataset.to_pandas()
-    return df, df
+    display_df = df.iloc[:max_rows, :max_cols]
+    return display_df, df
 
 def upload_dataset(dataset_file):
 
     if dataset_file is None:
         return None, None
+    
+    df = pd.read_csv(dataset_file.name).iloc[:max_rows, :max_cols]
+    display_df = df.iloc[:max_rows, :max_cols]
 
-    print(dataset_file.name)
-
-    df = pd.read_csv(dataset_file.name)
-
-    return df, df
+    return display_df, df
 
 
 def process_dataset(full_dataset, sql_query):
@@ -68,8 +60,7 @@ theme = gr.themes.Soft(
     neutral_hue="slate",
 )
 
-
-with gr.Blocks(analytics_enabled=False, theme=theme) as demo:
+with gr.Blocks(theme=theme) as demo:
     full_dataset = gr.State()
 
     with gr.Column():
@@ -122,3 +113,6 @@ with gr.Blocks(analytics_enabled=False, theme=theme) as demo:
     )
     demo.load(**toggle_dark_mode_args)
     dark_mode_btn.click(**toggle_dark_mode_args)
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)

query.py

@@ -1,3 +1,3 @@
 sql_query='''
-SELECT * FROM input_table WHERE text LIKE '%the rock%'
+SELECT * FROM input_table WHERE text LIKE '%conan%'
 '''