richardr1126
commited on
Commit
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66983ee
1
Parent(s):
d119dc4
Update app.py
Browse files
app.py
CHANGED
@@ -10,6 +10,7 @@ from transformers import (
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from huggingface_hub import login
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import gradio as gr
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import torch
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login(os.getenv("HF_TOKEN", None))
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@@ -76,34 +77,27 @@ def bot(input_message: str, temperature=0.1, top_p=0.9, top_k=0, repetition_pena
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# Split the text by "|", and get the last element in the list which should be the final query
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final_query = partial_text.split("|")[-1].strip()
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gradio_interface = gr.Interface(
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fn=bot,
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inputs=[
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gr.Textbox(
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gr.Slider(label="Temperature", minimum=0.0, maximum=1.0, value=0.1, step=0.1),
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gr.Slider(label="Top-p (nucleus sampling)", minimum=0.0, maximum=1.0, value=0.9, step=0.01),
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gr.Slider(label="Top-k", minimum=0, maximum=200, value=0, step=1),
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gr.Slider(label="Repetition Penalty", minimum=1.0, maximum=2.0, value=1.08, step=0.1)
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],
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outputs=
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title="SQL Skeleton WizardCoder Demo",
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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.""",
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examples=[
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"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request
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],
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[
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"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. ### Instruction: Convert text to sql: 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 | ### Response: ",
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0.1, 0.9, 0, 1.08
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],
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[
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"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. ### Instruction: Convert text to sql: 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 | ### Response: ",
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0.1, 0.9, 0, 1.08
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)
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gradio_interface.launch()
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from huggingface_hub import login
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import gradio as gr
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import torch
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import markdown
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login(os.getenv("HF_TOKEN", None))
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# Split the text by "|", and get the last element in the list which should be the final query
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final_query = partial_text.split("|")[-1].strip()
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# Convert SQL to markdown (not required, but just to show how to use the markdown module)
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final_query_markdown = f'```sql\n{final_query}\n```'
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return markdown.markdown(final_query_markdown)
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gradio_interface = gr.Interface(
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fn=bot,
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inputs=[
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gr.Textbox(lines=20, placeholder='Input text here...', label='Input Text'),
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gr.Slider(label="Temperature", minimum=0.0, maximum=1.0, value=0.1, step=0.1),
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gr.Slider(label="Top-p (nucleus sampling)", minimum=0.0, maximum=1.0, value=0.9, step=0.01),
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gr.Slider(label="Top-k", minimum=0, maximum=200, value=0, step=1),
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gr.Slider(label="Repetition Penalty", minimum=1.0, maximum=2.0, value=1.08, step=0.1)
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],
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outputs=gr.outputs.Markdown(),
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title="SQL Skeleton WizardCoder Demo",
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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.""",
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examples=[
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["Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n\nConvert text to sql: 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 | \n\n### Response:\n\n"],
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["Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n\nConvert text to sql: 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 | \n\n### Response:\n\n"],
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["Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n\nConvert text to sql: 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 | \n\n### Response:\n\n"],
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]
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)
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gradio_interface.launch()
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