mirror of
https://github.com/gradio-app/gradio.git
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4d58ae79b3
* state * state fix * variable -> state * fix * added state tests * formatting * fix test * formatting * fix test * added tests for bakcward compatibility * formatting * config fix * additional doc * doc fix * formatting
101 lines
3.4 KiB
Python
101 lines
3.4 KiB
Python
import gradio as gr
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from datetime import datetime
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import random
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import string
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import os
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import pandas as pd
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from constants import (
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file_dir,
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img_dir,
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highlighted_text,
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highlighted_text_output_2,
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highlighted_text_output_1,
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random_plot,
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random_model3d,
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)
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demo = gr.Interface(
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lambda *args: args[0],
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inputs=[
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gr.Textbox(value=lambda: datetime.now(), label="Current Time"),
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gr.Number(value=lambda: random.random(), label="Ranom Percentage"),
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gr.Slider(minimum=-1, maximum=1, randomize=True, label="Slider with randomize"),
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gr.Slider(
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minimum=0,
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maximum=1,
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value=lambda: random.random(),
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label="Slider with value func",
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),
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gr.Checkbox(value=lambda: random.random() > 0.5, label="Random Checkbox"),
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gr.CheckboxGroup(
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choices=["a", "b", "c", "d"],
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value=lambda: random.choice(["a", "b", "c", "d"]),
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label="Random CheckboxGroup",
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),
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gr.Radio(
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choices=list(string.ascii_lowercase),
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value=lambda: random.choice(string.ascii_lowercase),
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),
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gr.Dropdown(
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choices=["a", "b", "c", "d", "e"],
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value=lambda: random.choice(["a", "b", "c"]),
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),
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gr.Image(
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value=lambda: random.choice(
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[os.path.join(img_dir, img) for img in os.listdir(img_dir)]
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)
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),
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gr.Video(value=lambda: os.path.join(file_dir, "world.mp4")),
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gr.Audio(value=lambda: os.path.join(file_dir, "cantina.wav")),
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gr.File(
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value=lambda: random.choice(
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[os.path.join(file_dir, img) for img in os.listdir(file_dir)]
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)
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),
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gr.Dataframe(
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value=lambda: pd.DataFrame(
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{"random_number_rows": range(random.randint(0, 10))}
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)
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),
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gr.Timeseries(value=lambda: os.path.join(file_dir, "time.csv")),
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gr.State(value=lambda: random.choice(string.ascii_lowercase)),
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gr.Button(value=lambda: random.choice(["Run", "Go", "predict"])),
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gr.ColorPicker(value=lambda: random.choice(["#000000", "#ff0000", "#0000FF"])),
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gr.Label(value=lambda: random.choice(["Pedestrian", "Car", "Cyclist"])),
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gr.HighlightedText(
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value=lambda: random.choice(
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[
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{"text": highlighted_text, "entities": highlighted_text_output_1},
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{"text": highlighted_text, "entities": highlighted_text_output_2},
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]
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),
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),
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gr.JSON(value=lambda: random.choice([{"a": 1}, {"b": 2}])),
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gr.HTML(
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value=lambda: random.choice(
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[
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'<p style="color:red;">I am red</p>',
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'<p style="color:blue;">I am blue</p>',
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]
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)
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),
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gr.Gallery(
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value=lambda: [os.path.join(img_dir, img) for img in os.listdir(img_dir)]
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),
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gr.Chatbot(
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value=lambda: random.choice([[("hello", "hi!")], [("bye", "goodbye!")]])
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),
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gr.Model3D(value=random_model3d),
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gr.Plot(value=random_plot),
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gr.Markdown(value=lambda: f"### {random.choice(['Hello', 'Hi', 'Goodbye!'])}"),
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],
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outputs=[
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gr.State(value=lambda: random.choice(string.ascii_lowercase))
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],
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)
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if __name__ == "__main__":
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demo.launch()
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