Update app.py

app.py

@@ -13,7 +13,7 @@ import torch
 model_name = os.getenv("HF_MODEL_NAME", None)
 tok = AutoTokenizer.from_pretrained(model_name)
 
-max_new_tokens = 1536
+max_new_tokens = 1024
 
 print(f"Starting to load the model {model_name}")
 
@@ -78,27 +78,15 @@ def bot(input_message: str, db_info="", temperature=0.1, top_p=0.9, top_k=0, rep
     final_query_markdown = f"```sql\n{final_query}\n```"
     return final_query_markdown
 
-
-gradio_interface = gr.Interface(
-  fn=bot,
-  inputs=[
-      gr.Textbox(lines=4, placeholder='Input text here...', label='Input Text'),
-      gr.Textbox(lines=8, placeholder='(Recommended) Example: | stadium : stadium_id , location , name , capacity , highest , lowest , average | singer : singer_id , name , country , song_name , song_release_year , age , is_male | concert : concert_id , concert_name , theme , stadium_id , year | singer_in_concert : concert_id , singer_id | concert.stadium_id = stadium.stadium_id | singer_in_concert.singer_id = singer.singer_id | singer_in_concert.concert_id = concert.concert_id | ', label='Databse Info'),
-      gr.Slider(label="Temperature", minimum=0.0, maximum=1.0, value=0.1, step=0.1),
-      gr.Slider(label="Top-p (nucleus sampling)", minimum=0.0, maximum=1.0, value=0.9, step=0.01),
-      gr.Slider(label="Top-k", minimum=0, maximum=200, value=0, step=1),
-      gr.Slider(label="Repetition Penalty", minimum=1.0, maximum=2.0, value=1.08, step=0.1)
-  ],
-  outputs=gr.Markdown(),
-  title="SQL Skeleton WizardCoder Demo",
-  description="""This interactive tool translates natural language instructions into SQL queries, using a trained model. Type or paste your instructions into the text box and click 'Submit' to generate SQL queries. Use the sliders to adjust the model's temperature, top-p, top-k, and repetition penalty values.""",
-  examples = [
-    ["What is the average, minimum, and maximum age for all French singers?", "| stadium : stadium_id , location , name , capacity , highest , lowest , average | singer : singer_id , name , country , song_name , song_release_year , age , is_male | concert : concert_id , concert_name , theme , stadium_id , year | singer_in_concert : concert_id , singer_id | concert.stadium_id = stadium.stadium_id | singer_in_concert.singer_id = singer.singer_id | singer_in_concert.concert_id = concert.concert_id |"],
-    ["Show location and name for all stadiums with a capacity between 5000 and 10000.", "| stadium : stadium_id , location , name , capacity , highest , lowest , average | singer : singer_id , name , country , song_name , song_release_year , age , is_male | concert : concert_id , concert_name , theme , stadium_id , year | singer_in_concert : concert_id , singer_id | concert.stadium_id = stadium.stadium_id | singer_in_concert.singer_id = singer.singer_id | singer_in_concert.concert_id = concert.concert_id |"],
-    ["What are the number of concerts that occurred in the stadium with the largest capacity ?", "| stadium : stadium_id , location , name , capacity , highest , lowest , average | singer : singer_id , name , country , song_name , song_release_year , age , is_male | concert : concert_id , concert_name , theme , stadium_id , year | singer_in_concert : concert_id , singer_id | concert.stadium_id = stadium.stadium_id | singer_in_concert.singer_id = singer.singer_id | singer_in_concert.concert_id = concert.concert_id |"],
-    ["How many male singers performed in concerts in the year 2023?", "| stadium : stadium_id , location , name , capacity , highest , lowest , average | singer : singer_id , name , country , song_name , song_release_year , age , is_male | concert : concert_id , concert_name , theme , stadium_id , year | singer_in_concert : concert_id , singer_id | concert.stadium_id = stadium.stadium_id | singer_in_concert.singer_id = singer.singer_id | singer_in_concert.concert_id = concert.concert_id |"],
-    ["List the names of all singers who performed in a concert with the theme 'Rock'", "| stadium : stadium_id , location , name , capacity , highest , lowest , average | singer : singer_id , name , country , song_name , song_release_year , age , is_male | concert : concert_id , concert_name , theme , stadium_id , year | singer_in_concert : concert_id , singer_id | concert.stadium_id = stadium.stadium_id | singer_in_concert.singer_id = singer.singer_id | singer_in_concert.concert_id = concert.concert_id |"]
-  ]
-)
-
-gradio_interface.launch()
+with gr.Blocks() as demo:
+    input_text = gr.Textbox(lines=5, placeholder='Input text here...', label='Input Text')
+    db_info = gr.Textbox(lines=5, placeholder='Example: | table_01 : column_01 , column_02 | table_02 : column_01 , column_02 | ...', label='Database Info')
+    temperature = gr.Slider(label="Temperature", minimum=0.0, maximum=1.0, value=0.1, step=0.1)
+    top_p = gr.Slider(label="Top-p (nucleus sampling)", minimum=0.0, maximum=1.0, value=0.9, step=0.01)
+    top_k = gr.Slider(label="Top-k", minimum=0, maximum=200, value=0, step=1)
+    repetition_penalty = gr.Slider(label="Repetition Penalty", minimum=1.0, maximum=2.0, value=1.08, step=0.1)
+    output_box = gr.Markdown(label="Generated SQL Query")
+    run_button = gr.Button("Generate SQL Query")
+    run_button.click(fn=bot, inputs=[input_text, db_info, temperature, top_p, top_k, repetition_penalty], outputs=output_box)
+
+demo.launch()