tagged_prompt / app.py
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Update app.py
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import gradio as gr
from datasets import load_dataset
import argparse
import pandas as pd
from functools import partial
import subprocess
# Headers and datatypes for the remaining columns
HEADERS = ["__index_level_0__", "problem", "username", "entrypoint", "submitted_text", "prompt", "subset"]
DATATYPES = ["number", "str", "str", "str", "str", "str", "str"]
SUCCESS_HEADERS = ["subset"]
SUCCESS_DATATYPES = ["str"]
def capture_output(prompt, completion, prints):
code = "\n".join([prompt, " "+" \n".join(completion.split("\n")), prints])
outputs = subprocess.run(["python", "-c", code], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
stderr = gr.Textbox(outputs.stderr.decode("utf-8").strip(), label="Code Errors", type="text")
stdout = gr.Code(outputs.stdout.decode("utf-8").strip(), label="Code Outputs", language="python")
return stderr, stdout
def update_components(
ds,
slider,
header_data,
success_data,
prompt,
submitted_text,
assertions,
):
if isinstance(ds, gr.State):
ds = ds.value
row = ds.iloc[[slider]]
header_data = gr.Dataframe(
headers=HEADERS,
datatype=DATATYPES,
row_count=1,
col_count=(len(HEADERS), "fixed"),
column_widths=["60px"]*len(HEADERS),
value=row[HEADERS],
interactive=False
)
success_data = gr.Dataframe(
headers=SUCCESS_HEADERS,
datatype=SUCCESS_DATATYPES,
row_count=1,
col_count=(len(SUCCESS_HEADERS), "fixed"),
column_widths=["60px"]*len(SUCCESS_HEADERS),
value=row[SUCCESS_HEADERS],
interactive=False
)
row = row.iloc[0]
prompt = gr.Code(row["prompt"], language="python", label="Prompt")
submitted_text = gr.Textbox(row["submitted_text"], type="text", label="Submitted Text")
assertions = gr.Code(row["assertions"], language="python", label="Assertions")
slider = gr.Slider(0, len(ds) - 1, step=1, label="Problem ID (click and arrow keys to navigate):", value=slider)
return [slider, header_data, success_data, prompt, submitted_text,
assertions]
def filter_by(
dataset_name,
dataset_split,
problem_box,
student_box,
slider,
*components_to_update):
ds = load_dataset(dataset_name, split=dataset_split)
ds = ds.to_pandas()
if problem_box != None:
ds = ds[ds["problem"] == problem_box]
if student_box != None:
ds = ds[ds["username"] == student_box]
return [ds, *update_components(ds, 0, *components_to_update)]
def next_example(ds, *components):
slider_value = components[0]
new_slider_value = int(slider_value)+1 if slider_value < len(ds)-1 else len(ds)-1
lesscomponents = components[1:]
return update_components(ds, new_slider_value, *lesscomponents)
def prev_example(ds, *components):
slider_value = components[0]
new_slider_value = int(slider_value)-1 if slider_value > 0 else 0
lesscomponents = components[1:]
return update_components(ds, new_slider_value, *lesscomponents)
def main(args):
ds = load_dataset(args.dataset, split=args.split)
ds = ds.to_pandas()
callback = gr.SimpleCSVLogger()
student_usernames = list(set(ds["username"]))
student_usernames.sort(key=lambda x: int(x.replace("student","")))
problem_names = list(set(ds["problem"]))
problem_names.sort()
with gr.Blocks(theme="gradio/monochrome") as demo:
dataset = gr.State(ds)
# slider for selecting problem id
slider = gr.Slider(0, len(ds) - 1, step=1, label="Problem ID (click and arrow keys to navigate):")
# display headers in dataframe for problem id
header_data = gr.Dataframe(
headers=HEADERS,
datatype=DATATYPES,
row_count=1,
col_count=(len(HEADERS), "fixed"),
column_widths=["60px"]*len(HEADERS),
interactive=False,
)
success_data = gr.Dataframe(
headers=SUCCESS_HEADERS,
datatype=SUCCESS_DATATYPES,
row_count=1,
col_count=(len(SUCCESS_HEADERS), "fixed"),
column_widths=["60px"]*len(SUCCESS_HEADERS),
interactive=False,
)
prompt = gr.Code("__prompt__", language="python", label="Prompt")
with gr.Row():
prev_btn = gr.Button("Previous")
next_btn = gr.Button("Next")
submitted_text = gr.Textbox("__submitted_text__", type="text", label="Submitted Text")
with gr.Row():
assertions = gr.Code("__assertions__", language="python", label="Assertions")
# updates
# change example on slider change
components = [slider, header_data, success_data, prompt, submitted_text, assertions]
slider.input(fn=update_components, inputs=[dataset, *components], outputs=components)
prev_btn.click(fn=prev_example, inputs=[dataset, *components], outputs=components)
next_btn.click(fn=next_example, inputs=[dataset, *components], outputs=components)
# add filtering options
gr.Markdown("**Filtering (reload to clear all filters)**\n")
with gr.Row():
with gr.Column():
problem_box = gr.Dropdown(label="problem", choices=problem_names)
student_box = gr.Dropdown(label="username", choices=student_usernames)
filter_btn = gr.Button("Filter")
filter_btn.click(fn=partial(filter_by, args.dataset, args.split), inputs=[problem_box, student_box, *components],
outputs=[dataset, *components])
demo.launch(share=args.share)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--dataset", type=str, default="nuprl-staging/studenteval_tagged_prompts")
parser.add_argument("--split", type=str, default="test")
parser.add_argument("--share", action="store_true")
args = parser.parse_args()
main(args)