repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/blocks_multiple_event_triggers/run.py | demo/blocks_multiple_event_triggers/run.py | import gradio as gr
import pypistats # type: ignore
from datetime import date
from dateutil.relativedelta import relativedelta
import pandas as pd
def get_plot(lib, time):
data = pypistats.overall(lib, total=True, format="pandas")
data = data.groupby("category").get_group("with_mirrors").sort_values("date")
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/streaming_filter/run.py | demo/streaming_filter/run.py | import gradio as gr
import numpy as np
import cv2 # type: ignore
def transform_cv2(frame, transform):
if transform == "cartoon":
# prepare color
img_color = cv2.pyrDown(cv2.pyrDown(frame))
for _ in range(6):
img_color = cv2.bilateralFilter(img_color, 9, 9, 7)
img_color... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/cancel_events/run.py | demo/cancel_events/run.py | import time
import gradio as gr
import atexit
import pathlib
log_file = pathlib.Path(__file__).parent / "cancel_events_output_log.txt"
def fake_diffusion(steps):
log_file.write_text("")
for i in range(steps):
print(f"Current step: {i}")
with log_file.open("a") as f:
f.write(f"Curr... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/star_rating_props/run.py | demo/star_rating_props/run.py | import gradio as gr
with gr.Blocks() as demo:
star_rating = gr.HTML(
7,
size=40,
max_stars=10,
html_template="""
<h2>Star Rating:</h2>
${Array.from({length: max_stars}, (_, i) => `<img class='${i < value ? '' : 'faded'}' src='https://upload.wikimedia.org/wikipedia/c... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/text_generation/run.py | demo/text_generation/run.py | import gradio as gr
from transformers import pipeline
generator = pipeline('text-generation', model='gpt2')
def generate(text):
result = generator(text, max_length=30, num_return_sequences=1)
return result[0]["generated_text"] # type: ignore
examples = [
["The Moon's orbit around Earth has"],
["The ... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/neon-tts-plugin-coqui/run.py | demo/neon-tts-plugin-coqui/run.py | import tempfile
import gradio as gr
from neon_tts_plugin_coqui import CoquiTTS # type: ignore
LANGUAGES = list(CoquiTTS.langs.keys())
coquiTTS = CoquiTTS()
def tts(text: str, language: str):
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
coquiTTS.get_tts(text, fp, speaker = {"langua... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/audio_mixer/run.py | demo/audio_mixer/run.py | import gradio as gr
with gr.Blocks() as demo:
track_count = gr.State(1)
add_track_btn = gr.Button("Add Track")
add_track_btn.click(lambda count: count + 1, track_count, track_count)
@gr.render(inputs=track_count)
def render_tracks(count):
audios = []
volumes = []
with gr.R... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/calculator_blocks_cached/run.py | demo/calculator_blocks_cached/run.py | import gradio as gr
def calculator(num1, operation, num2):
if operation == "add":
return num1 + num2
elif operation == "subtract":
return num1 - num2
elif operation == "multiply":
return num1 * num2
elif operation == "divide":
return num1 / num2
with gr.Blocks() as demo... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/timer/run.py | demo/timer/run.py | import gradio as gr
import random
import time
with gr.Blocks() as demo:
timer = gr.Timer(1)
timestamp = gr.Number(label="Time")
timer.tick(lambda: round(time.time()), outputs=timestamp)
gr.Number(lambda: round(time.time()), label="Time 2", every=1)
with gr.Row():
timestamp_3 = gr.Number()
start_btn ... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/concurrency_with_queue/run.py | demo/concurrency_with_queue/run.py | import gradio as gr
import time
def say_hello(name):
time.sleep(5)
return f"Hello {name}!"
with gr.Blocks() as demo:
inp = gr.Textbox()
outp = gr.Textbox()
button = gr.Button()
button.click(say_hello, inp, outp)
demo.launch()
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/audio_component/run.py | demo/audio_component/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.Audio()
demo.launch()
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/mcp_progress/run.py | demo/mcp_progress/run.py | import gradio as gr
import time
def slow_text_reverser(text: str, progress=gr.Progress()):
for i in range(len(text)):
progress(i / len(text), desc="Reversing text")
time.sleep(0.3)
return text[::-1]
demo = gr.Interface(slow_text_reverser, gr.Textbox("Hello, world!"), gr.Textbox(), api_name="p... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/clearbutton_component/run.py | demo/clearbutton_component/run.py | import gradio as gr
with gr.Blocks() as demo:
textbox = gr.Textbox(value="This is some text")
gr.ClearButton(textbox)
if __name__ == "__main__":
demo.launch()
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/dataset/run.py | demo/dataset/run.py | import gradio as gr
import numpy as np
# get_image(), get_video(), get_audio(), get_file(), get_model3d() return file paths to sample media included with Gradio
from gradio.media import get_image, get_video, get_audio, get_file, get_model3d
txt = "the quick brown fox"
num = 10
img = get_image("cheetah1.jpg")
vid = ge... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/diff_texts/run.py | demo/diff_texts/run.py | from difflib import Differ
import gradio as gr
def diff_texts(text1, text2):
d = Differ()
return [
(token[2:], token[0] if token[0] != " " else None)
for token in d.compare(text1, text2)
]
demo = gr.Interface(
diff_texts,
[
gr.Textbox(
label="Text 1",
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/load_model_with_token/run.py | demo/load_model_with_token/run.py | import gradio as gr
# This demo requires a Hugging Face PRO token.
demo = gr.load("meta-llama/Meta-Llama-3-8B-Instruct", src="models", accept_token=True)
if __name__ == "__main__":
demo.launch()
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/file_explorer_component/run.py | demo/file_explorer_component/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.FileExplorer()
demo.launch()
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/native_plots/run.py | demo/native_plots/run.py | import gradio as gr
from scatter_plot_demo import scatter_plots # type: ignore
from line_plot_demo import line_plots # type: ignore
from bar_plot_demo import bar_plots # type: ignore
with gr.Blocks() as demo:
with gr.Tabs():
with gr.TabItem("Line Plot"):
line_plots.render()
with gr.... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/native_plots/bar_plot_demo.py | demo/native_plots/bar_plot_demo.py | import gradio as gr
from data import temp_sensor_data, food_rating_data # type: ignore
with gr.Blocks() as bar_plots:
with gr.Row():
start = gr.DateTime("2021-01-01 00:00:00", label="Start")
end = gr.DateTime("2021-01-05 00:00:00", label="End")
apply_btn = gr.Button("Apply", scale=0)
w... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/native_plots/scatter_plot_demo.py | demo/native_plots/scatter_plot_demo.py | import gradio as gr
from data import temp_sensor_data, food_rating_data # type: ignore
with gr.Blocks() as scatter_plots:
with gr.Row():
start = gr.DateTime("2021-01-01 00:00:00", label="Start")
end = gr.DateTime("2021-01-05 00:00:00", label="End")
apply_btn = gr.Button("Apply", scale=0)
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/native_plots/data.py | demo/native_plots/data.py | import pandas as pd
from random import randint, random
temp_sensor_data = pd.DataFrame(
{
"time": pd.date_range("2021-01-01", end="2021-01-05", periods=200),
"temperature": [randint(50 + 10 * (i % 2), 65 + 15 * (i % 2)) for i in range(200)],
"humidity": [randint(50 + 10 * (i % 2), 65 + 15 *... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/native_plots/line_plot_demo.py | demo/native_plots/line_plot_demo.py | import gradio as gr
from data import temp_sensor_data, food_rating_data # type: ignore
with gr.Blocks() as line_plots:
with gr.Row():
start = gr.DateTime("2021-01-01 00:00:00", label="Start")
end = gr.DateTime("2021-01-05 00:00:00", label="End")
apply_btn = gr.Button("Apply", scale=0)
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/json_component/run.py | demo/json_component/run.py | import gradio as gr
import numpy as np
with gr.Blocks() as demo:
inp = gr.JSON(
label="InputJSON",
value={
"Key 1": "Value 1",
"Key 2": {"Key 3": "Value 2", "Key 4": "Value 3"},
"Key 5": ["Item 1", "Item 2", "Item 3"],
"Key 6": 123,
"Key 7... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/calculator_blocks/run.py | demo/calculator_blocks/run.py | import gradio as gr
def calculator(num1, operation, num2):
if operation == "add":
return num1 + num2
elif operation == "subtract":
return num1 - num2
elif operation == "multiply":
return num1 * num2
elif operation == "divide":
return num1 / num2
with gr.Blocks() as demo... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/fake_gan_2/run.py | demo/fake_gan_2/run.py | # This demo needs to be run from the repo folder.
# python demo/fake_gan/run.py
import time
import gradio as gr
# get_image() returns file paths (randomly if None) to sample media included with Gradio
from gradio.media import get_image
def fake_gan(desc):
if desc == "NSFW":
raise gr.Error("NSFW - banned c... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/scatterplot_component/run.py | demo/scatterplot_component/run.py | import gradio as gr
from vega_datasets import data
cars = data.cars()
with gr.Blocks() as demo:
gr.ScatterPlot(
value=cars,
x="Horsepower",
y="Miles_per_Gallon",
color="Origin",
tooltip=["Name"],
title="Car Data",
y_title="Miles per Gallon",
containe... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/blocks_group/run.py | demo/blocks_group/run.py | import gradio as gr
def greet(name):
return "Hello " + name + "!"
with gr.Blocks() as demo:
gr.Markdown("### This is a couple of elements without any gr.Group. Form elements naturally group together anyway.")
gr.Textbox("A")
gr.Number(3)
gr.Button()
gr.Image()
gr.Slider()
gr.Markdown(... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/video_component_events/run.py | demo/video_component_events/run.py | import gradio as gr
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
input_video = gr.Video(label="Input Video")
with gr.Column():
output_video = gr.Video(label="Output Video")
with gr.Column():
num_change = gr.Number(label="# Change Events", va... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/translation/run.py | demo/translation/run.py | # type: ignore
import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
import torch
# this model was loaded from https://hf.co/models
model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-distilled-600M")
tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-200-distil... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_series_nominal/run.py | demo/plot_guide_series_nominal/run.py | import gradio as gr
from data import df # type: ignore
with gr.Blocks() as demo:
gr.ScatterPlot(df, x="weight", y="height", color="ethnicity")
if __name__ == "__main__":
demo.launch() | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_series_nominal/data.py | demo/plot_guide_series_nominal/data.py | import pandas as pd
import numpy as np
import random
df = pd.DataFrame({
'height': np.random.randint(50, 70, 25),
'weight': np.random.randint(120, 320, 25),
'age': np.random.randint(18, 65, 25),
'ethnicity': [random.choice(["white", "black", "asian"]) for _ in range(25)]
})
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/blocks_update/run.py | demo/blocks_update/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.Markdown(
"""
# Animal Generator
Once you select a species, the detail panel should be visible.
"""
)
species = gr.Radio(label="Animal Class", choices=["Mammal", "Fish", "Bird"])
animal = gr.Dropdown(label="Animal", choices=[])
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/blocks_flipper/run.py | demo/blocks_flipper/run.py | import numpy as np
import gradio as gr
def flip_text(x):
return x[::-1]
def flip_image(x):
return np.fliplr(x)
with gr.Blocks() as demo:
gr.Markdown("Flip text or image files using this demo.")
with gr.Tab("Flip Text"):
text_input = gr.Textbox()
text_output = gr.Textbox()
text... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/on_listener_test/run.py | demo/on_listener_test/run.py | import gradio as gr
with gr.Blocks() as demo:
name = gr.Textbox(label="Name")
output = gr.Textbox(label="Output")
greet_btn = gr.Button("Greet")
trigger = gr.Textbox(label="Trigger 1")
trigger2 = gr.Textbox(label="Trigger 2")
def greet(name, evt_data: gr.EventData):
return "Hello " + n... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/validator_interface/run.py | demo/validator_interface/run.py | import gradio as gr
def validate_input(age, location):
is_age_valid = True
is_location_valid = True
if not age or age < 3:
is_age_valid = False
if "london" in location.lower():
is_location_valid = False
return [
gr.validate(is_age_valid, "Age must be at least 3"),
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/chatinterface_options/run.py | demo/chatinterface_options/run.py | import gradio as gr
import random
example_code = """
Here's an example Python lambda function:
lambda x: x + {}
Is this correct?
"""
def chat(message, history):
if message == "Yes, that's correct.":
return "Great!"
else:
return gr.ChatMessage(
content=example_code.format(random.r... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/blocks_outputs/run.py | demo/blocks_outputs/run.py | import gradio as gr
def make_markdown():
return [
[
"# hello again",
"Hello my name is frank, I am liking the small turtle you have there. It would be a shame if it went missing.",
'<img src="https://images.unsplash.com/photo-1574613362884-f79513a5128c?fit=crop&w=500&q=8... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/no_input/run.py | demo/no_input/run.py | import gradio as gr
import random
sentence_list = [
"Good morning!",
"Prayers are with you, have a safe day!",
"I love you!"
]
def random_sentence():
return sentence_list[random.randint(0, 2)]
demo = gr.Interface(fn=random_sentence, inputs=None, outputs="text")
if __name__ == "__main__":
demo.la... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/animeganv2/run.py | demo/animeganv2/run.py | import gradio as gr
import torch
model2 = torch.hub.load(
"AK391/animegan2-pytorch:main",
"generator",
pretrained=True,
progress=False
)
model1 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1")
face2paint = torch.hub.load(
'AK391/animegan2-pytorch:main', ... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/bokeh_plot/run.py | demo/bokeh_plot/run.py | # type: ignore
import gradio as gr
import xyzservices.providers as xyz
from bokeh.models import ColumnDataSource, Whisker
from bokeh.plotting import figure
from bokeh.sampledata.autompg2 import autompg2 as df
from bokeh.sampledata.penguins import data
from bokeh.transform import factor_cmap, jitter, factor_mark
def ge... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/chatbot_core_components/run.py | demo/chatbot_core_components/run.py | # type: ignore
import gradio as gr
import os
import plotly.express as px # type: ignore
import random
# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, video, & model3d). Plus shows support for streaming text.
txt = """
Absolutely! The mycorrhizal network, often referred to as t... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/test_chatinterface_streaming_echo/run.py | demo/test_chatinterface_streaming_echo/run.py | import gradio as gr
runs = 0
def reset_runs():
global runs
runs = 0
def slow_echo(message, history):
global runs # i didn't want to add state or anything to this demo
runs = runs + 1
for i in range(len(message)):
yield f"Run {runs} - You typed: " + message[: i + 1]
chat = gr.ChatInterfa... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/test_chatinterface_streaming_echo/multimodal_messages_testcase.py | demo/test_chatinterface_streaming_echo/multimodal_messages_testcase.py | import gradio as gr
runs = 0
def reset_runs():
global runs
runs = 0
def slow_echo(message, history):
global runs # i didn't want to add state or anything to this demo
runs = runs + 1
for i in range(len(message['text'])):
yield f"Run {runs} - You typed: " + message['text'][: i + 1]
chat ... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/test_chatinterface_streaming_echo/multimodal_group_messages_testcase.py | demo/test_chatinterface_streaming_echo/multimodal_group_messages_testcase.py | import gradio as gr
runs = 0
def reset_runs():
global runs
runs = 0
def slow_echo(message, history):
global runs # i didn't want to add state or anything to this demo
runs = runs + 1
for i in range(len(message['text'])):
yield f"Run {runs} - You typed: " + message['text'][: i + 1]
if... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/test_chatinterface_streaming_echo/multimodal_non_stream_testcase.py | demo/test_chatinterface_streaming_echo/multimodal_non_stream_testcase.py | import gradio as gr
runs = 0
def reset_runs():
global runs
runs = 0
def slow_echo(message, history):
global runs # i didn't want to add state or anything to this demo
runs = runs + 1
return f"Run {runs} - You typed: " + message['text']
chat = gr.ChatInterface(slow_echo, multimodal=True, api_nam... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/imageeditor_component/run.py | demo/imageeditor_component/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.ImageEditor()
demo.launch()
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_selection/run.py | demo/plot_guide_selection/run.py | import gradio as gr
from data import df # type: ignore
with gr.Blocks() as demo:
plt = gr.LinePlot(df, x="weight", y="height")
selection_total = gr.Number(label="Total Weight of Selection")
def select_region(selection: gr.SelectData):
min_w, max_w = selection.index
return df[(df["weight"]... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_selection/data.py | demo/plot_guide_selection/data.py | import pandas as pd
import numpy as np
import random
df = pd.DataFrame({
'height': np.random.randint(50, 70, 25),
'weight': np.random.randint(120, 320, 25),
'age': np.random.randint(18, 65, 25),
'ethnicity': [random.choice(["white", "black", "asian"]) for _ in range(25)]
})
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/color_generator/run.py | demo/color_generator/run.py | import gradio as gr
import cv2 # type: ignore
import numpy as np
import random
# Convert decimal color to hexadecimal color
def RGB_to_Hex(rgb):
color = "#"
for i in rgb:
num = int(i)
color += str(hex(num))[-2:].replace("x", "0").upper()
return color
# Randomly generate light or dark colo... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/magic_8_ball/run.py | demo/magic_8_ball/run.py | import io
from threading import Thread
import random
import os
import numpy as np
import spaces # type: ignore
import gradio as gr
import torch
from parler_tts import ParlerTTSForConditionalGeneration # type: ignore
from pydub import AudioSegment
from transformers import AutoTokenizer, AutoFeatureExtractor, set_see... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/magic_8_ball/streamer.py | demo/magic_8_ball/streamer.py | from queue import Queue
from transformers.generation.streamers import BaseStreamer
from typing import Optional
from parler_tts import ParlerTTSForConditionalGeneration # type: ignore
import numpy as np
import math
import torch
class ParlerTTSStreamer(BaseStreamer):
def __init__(
self,
model: Parl... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_datetime/run.py | demo/plot_guide_datetime/run.py | import gradio as gr
from data import df # type: ignore
with gr.Blocks() as demo:
with gr.Row():
start = gr.DateTime("now - 24h")
end = gr.DateTime("now")
apply_btn = gr.Button("Apply")
plot = gr.LinePlot(df, x="time", y="price")
apply_btn.click(lambda start, end: gr.BarPlot(x_lim=... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_datetime/data.py | demo/plot_guide_datetime/data.py | import pandas as pd
import numpy as np
import random
from datetime import datetime, timedelta
now = datetime.now()
df = pd.DataFrame({
'time': [now - timedelta(minutes=5*i) for i in range(25)],
'price': np.random.randint(100, 1000, 25),
'origin': [random.choice(["DFW", "DAL", "HOU"]) for _ in range(25)],
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/checkbox_component/run.py | demo/checkbox_component/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.Checkbox()
demo.launch()
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/blocks_gpt/run.py | demo/blocks_gpt/run.py | import gradio as gr
api = gr.load("huggingface/gpt2-xl")
def complete_with_gpt(text):
# Use the last 50 characters of the text as context
return text[:-50] + api(text[-50:])
with gr.Blocks() as demo:
textbox = gr.Textbox(placeholder="Type here and press enter...", lines=4)
btn = gr.Button("Generate")... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_temporal/run.py | demo/plot_guide_temporal/run.py | import gradio as gr
import pandas as pd
import numpy as np
import random
from datetime import datetime, timedelta
now = datetime.now()
df = pd.DataFrame({
'time': [now - timedelta(minutes=5*i) for i in range(25)],
'price': np.random.randint(100, 1000, 25),
'origin': [random.choice(["DFW", "DAL", "HOU"]) f... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/dashboard/run.py | demo/dashboard/run.py | import gradio as gr
import pandas as pd
import plotly.express as px # type: ignore
from helpers import retrieve_pip_installs, retrieve_stars, retrieve_issues # type: ignore
LIBRARIES = ["accelerate", "datasets", "diffusers", "evaluate", "gradio", "hub_docs",
"huggingface_hub", "optimum", "pytorch_image_... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/dashboard/helpers.py | demo/dashboard/helpers.py | # type: ignore
import collections
from datetime import datetime
from datasets import DatasetDict, load_dataset
import numpy as np
datasets = {
"stars": load_dataset("open-source-metrics/stars").sort('dates'),
"issues": load_dataset("open-source-metrics/issues").sort('dates'),
"pip": load_dataset("open-sou... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/label_component/run.py | demo/label_component/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.Label(value={"First Label": 0.7, "Second Label": 0.2, "Third Label": 0.1})
demo.launch()
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/tabs/run.py | demo/tabs/run.py | import gradio as gr
with gr.Blocks() as demo:
with gr.Tabs():
with gr.Tab("Set 1"):
with gr.Tabs(selected="a3") as tabs_1:
tabset_1 = []
textset_1 = []
for i in range(10):
with gr.Tab(f"Tab {i+1}", id=f"a{i+1}") as tab:
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/blocks_scroll/run.py | demo/blocks_scroll/run.py | import gradio as gr
demo = gr.Blocks()
with demo:
inp = gr.Textbox(placeholder="Enter text.")
scroll_btn = gr.Button("Scroll")
no_scroll_btn = gr.Button("No Scroll")
big_block = gr.HTML("""
<div style='height: 800px; width: 100px; background-color: pink;'></div>
""")
out = gr.Textbox()
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/outbreak_forecast/run.py | demo/outbreak_forecast/run.py | import gradio as gr
from math import sqrt
import numpy as np
import pandas as pd
def outbreak(plot_type, r, month, countries, social_distancing):
months = ["January", "February", "March", "April", "May"]
m = months.index(month)
start_day = 30 * m
final_day = 30 * (m + 1)
x = np.arange(start_day, fi... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/render_split_simple/run.py | demo/render_split_simple/run.py | import gradio as gr
with gr.Blocks() as demo:
input_text = gr.Textbox(label="input")
@gr.render(inputs=input_text)
def show_split(text):
if len(text) == 0:
gr.Markdown("## No Input Provided")
else:
for letter in text:
gr.Textbox(letter)
if __name__ ... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/dataframe_events/run.py | demo/dataframe_events/run.py | import gradio as gr
import pandas as pd
import numpy as np
def update_dataframe():
regular_df = pd.DataFrame(
np.random.randint(1, 10, size=(5, 5)),
columns=pd.Index([str(i) for i in range(5)]),
)
wide_df = pd.DataFrame(
[
[5, 22, 91, 17, 73, 38, 84, 46, 65, 10, 155, 12... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/audio_subtitle/run.py | demo/audio_subtitle/run.py | import gradio as gr
from gradio.media import get_audio, get_file, MEDIA_PATHS
a = get_audio("cate_blanch.mp3")
b = get_audio("cate_blanch_2.mp3")
s1 = get_file("s1.srt")
s2 = get_file("s2.vtt")
def add_subtitles_to_audio(audio, subtitles=None):
if subtitles is None:
return audio
if subtitles is not ... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/blocks_flashcards/run.py | demo/blocks_flashcards/run.py | import random
import gradio as gr
with gr.Blocks() as demo:
gr.Markdown(
"Load the flashcards in the table below, then use the Practice tab to practice."
)
with gr.Tabs() as tabs:
with gr.Tab("Word Bank"):
flashcards_table = gr.Dataframe(headers=["front", "back"], type="array"... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/ner_pipeline/run.py | demo/ner_pipeline/run.py | from transformers import pipeline
import gradio as gr
ner_pipeline = pipeline("ner") # type: ignore
examples = [
"Does Chicago have any stores and does Joe live here?",
]
def ner(text):
output = ner_pipeline(text)
return {"text": text, "entities": output}
demo = gr.Interface(ner,
gr.Textb... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/chatinterface_thoughts/run.py | demo/chatinterface_thoughts/run.py | import gradio as gr
from gradio import ChatMessage
import time
sleep_time = 0.5
def simulate_thinking_chat(message, history):
start_time = time.time()
response = ChatMessage(
content="",
metadata={"title": "_Thinking_ step-by-step", "id": 0, "status": "pending"}
)
yield response
t... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/model3d_component_events/run.py | demo/model3d_component_events/run.py | import gradio as gr
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
input_3d = gr.Model3D(label="Input Model3D")
with gr.Column():
output_3d = gr.Model3D(label="Output Model3D")
with gr.Column():
num_change = gr.Number(label="# Change Events", ... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/input_output/run.py | demo/input_output/run.py | import gradio as gr
def image_mod(text):
return text[::-1]
demo = gr.Blocks()
with demo:
text = gr.Textbox(label="Input-Output")
btn = gr.Button("Run")
btn.click(image_mod, text, text)
if __name__ == "__main__":
demo.launch()
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/chatinterface_prefill/run.py | demo/chatinterface_prefill/run.py | import gradio as gr
import random
def prefill_chatbot(choice):
if choice == "Greeting":
return [
{"role": "user", "content": "Hi there!"},
{"role": "assistant", "content": "Hello! How can I assist you today?"}
]
elif choice == "Complaint":
return [
{"... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/map_airbnb/run.py | demo/map_airbnb/run.py | # type: ignore
import gradio as gr
import plotly.graph_objects as go
from datasets import load_dataset
dataset = load_dataset("gradio/NYC-Airbnb-Open-Data", split="train")
df = dataset.to_pandas()
def filter_map(min_price, max_price, boroughs):
filtered_df = df[(df['neighbourhood_group'].isin(boroughs)) &
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/state_cleanup/run.py | demo/state_cleanup/run.py | from __future__ import annotations
import gradio as gr
import numpy as np
from PIL import Image
from pathlib import Path
import secrets
import shutil
current_dir = Path(__file__).parent
def generate_random_img(history: list[Image.Image], request: gr.Request):
"""Generate a random red, green, blue, orange, yellor ... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/llm_claude/run.py | demo/llm_claude/run.py | # This is a simple 20 questions-style game built on top of the Anthropic API.
# Before running this, make sure you have exported your Anthropic API key as an environment variable:
# export ANTHROPIC_API_KEY="your-anthropic-api-key"
import anthropic # type: ignore
import gradio as gr
client = anthropic.Anthropic()
d... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/xgboost-income-prediction-with-explainability/run.py | demo/xgboost-income-prediction-with-explainability/run.py | # type: ignore
import gradio as gr
import random
import matplotlib.pyplot as plt
import pandas as pd
import shap
import xgboost as xgb
from datasets import load_dataset
dataset = load_dataset("scikit-learn/adult-census-income")
X_train = dataset["train"].to_pandas()
_ = X_train.pop("fnlwgt")
_ = X_train.pop("race")
y_... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_aggregate_quantitative/run.py | demo/plot_guide_aggregate_quantitative/run.py | import gradio as gr
from data import df # type: ignore
with gr.Blocks() as demo:
gr.BarPlot(df, x="weight", y="height", x_bin=10, y_aggregate="sum")
if __name__ == "__main__":
demo.launch() | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_aggregate_quantitative/data.py | demo/plot_guide_aggregate_quantitative/data.py | import pandas as pd
import numpy as np
import random
df = pd.DataFrame({
'height': np.random.randint(50, 70, 25),
'weight': np.random.randint(120, 320, 25),
'age': np.random.randint(18, 65, 25),
'ethnicity': [random.choice(["white", "black", "asian"]) for _ in range(25)]
})
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/invisible_textbox/run.py | demo/invisible_textbox/run.py | import gradio as gr
with gr.Blocks() as demo:
with gr.Tabs():
with gr.Tab("Invisible Textbox Demo"):
textbox = gr.Textbox(visible=False, interactive=True, elem_id="test-textbox")
make_visible_btn = gr.Button("Show")
hide = gr.Button("Hide")
def show():
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_zoom_sync/run.py | demo/plot_guide_zoom_sync/run.py | import gradio as gr
from data import df # type: ignore
with gr.Blocks() as demo:
plt1 = gr.LinePlot(df, x="weight", y="height")
plt2 = gr.BarPlot(df, x="weight", y="age", x_bin=10)
plots = [plt1, plt2]
def select_region(selection: gr.SelectData):
min_w, max_w = selection.index
return ... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_zoom_sync/data.py | demo/plot_guide_zoom_sync/data.py | import pandas as pd
import numpy as np
import random
df = pd.DataFrame({
'height': np.random.randint(50, 70, 25),
'weight': np.random.randint(120, 320, 25),
'age': np.random.randint(18, 65, 25),
'ethnicity': [random.choice(["white", "black", "asian"]) for _ in range(25)]
})
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/blocks_layout/run.py | demo/blocks_layout/run.py | import gradio as gr
demo = gr.Blocks()
with demo:
with gr.Row():
gr.Image(interactive=True, scale=2)
gr.Image()
with gr.Row():
gr.Textbox(label="Text")
gr.Number(label="Count", scale=2)
gr.Radio(choices=["One", "Two"])
with gr.Row():
gr.Button("500", scale=0... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/interface_with_additional_inputs/run.py | demo/interface_with_additional_inputs/run.py | import gradio as gr
def generate_fake_image(prompt, seed, initial_image=None):
return f"Used seed: {seed}", "https://dummyimage.com/300/09f.png"
demo = gr.Interface(
generate_fake_image,
inputs=["textbox"],
outputs=["textbox", "image"],
additional_inputs=[
gr.Slider(0, 1000),
"imag... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/sentence_builder/run.py | demo/sentence_builder/run.py | import gradio as gr
def sentence_builder(quantity, animal, countries, place, activity_list, morning):
return f"""The {quantity} {animal}s from {" and ".join(countries)} went to the {place} where they {" and ".join(activity_list)} until the {"morning" if morning else "night"}"""
demo = gr.Interface(
sentence_b... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/line_plot_demo/run.py | demo/line_plot_demo/run.py | import pandas as pd
from random import randint, random
import gradio as gr
temp_sensor_data = pd.DataFrame(
{
"time": pd.date_range("2021-01-01", end="2021-01-05", periods=200),
"temperature": [randint(50 + 10 * (i % 2), 65 + 15 * (i % 2)) for i in range(200)],
"humidity": [randint(50 + 10... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/chatbot_feedback/run.py | demo/chatbot_feedback/run.py | import gradio as gr
def test_liked_loading():
test_history = [
{"role": "user", "content": "test user message"},
{"role": "assistant", "content": "test assistant message"}
]
# Set feedback_value to ["Like"] for the assistant message
return gr.update(value=test_history, feedback_value=["... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/chatbot_examples/run.py | demo/chatbot_examples/run.py | import gradio as gr
import os
# Multimodal Chatbot demo that shows support for examples (example messages shown within the chatbot).
def print_like_dislike(x: gr.LikeData):
print(x.index, x.value, x.liked)
def add_message(history, message):
for x in message["files"]:
history.append({"role": "user", "c... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/stream_audio/run.py | demo/stream_audio/run.py | import gradio as gr
import numpy as np
def add_to_stream(audio, instream):
if audio is None:
return gr.Audio(), instream
if instream is None:
ret = audio
else:
ret = (audio[0], np.concatenate((instream[1], audio[1])))
return ret, ret
with gr.Blocks() as demo:
inp = gr.Audio... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/code_component/run.py | demo/code_component/run.py | import gradio as gr
demo = gr.Interface(
lambda x: x,
gr.Code(language="python"),
gr.Code(language="python"),
examples=[[("/Users/freddy/sources/gradio/demo/code_component/run.py",)],
["print('Hello, World!')"],
[("/Users/freddy/sources/gradio/demo/code/run.py", )]]
)
if ... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/fake_diffusion_with_gif/run.py | demo/fake_diffusion_with_gif/run.py | import gradio as gr
import numpy as np
import time
import os
from PIL import Image
import requests
from io import BytesIO
def create_gif(images):
pil_images = []
for image in images:
if isinstance(image, str):
response = requests.get(image)
image = Image.open(BytesIO(response.co... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/yolov10_webcam_stream/run.py | demo/yolov10_webcam_stream/run.py | import gradio as gr
import cv2 # type: ignore
from huggingface_hub import hf_hub_download
from gradio_webrtc import WebRTC # type: ignore
from twilio.rest import Client # type: ignore
import os
from inference import YOLOv10 # type: ignore
model_file = hf_hub_download(
repo_id="onnx-community/yolov10n", filenam... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/yolov10_webcam_stream/inference.py | demo/yolov10_webcam_stream/inference.py | import time
import cv2 # type: ignore
import numpy as np
import onnxruntime # type: ignore
from utils import draw_detections # type: ignore
class YOLOv10:
def __init__(self, path):
# Initialize model
self.initialize_model(path)
def __call__(self, image):
return self.detect_objects... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/yolov10_webcam_stream/utils.py | demo/yolov10_webcam_stream/utils.py | import numpy as np
import cv2 # type: ignore
class_names = [
"person",
"bicycle",
"car",
"motorcycle",
"airplane",
"bus",
"train",
"truck",
"boat",
"traffic light",
"fire hydrant",
"stop sign",
"parking meter",
"bench",
"bird",
"cat",
"dog",
"hor... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/star_rating_events/run.py | demo/star_rating_events/run.py | import gradio as gr
with gr.Blocks() as demo:
star_rating = gr.HTML(
value=3,
html_template="""
<h2>Star Rating:</h2>
${Array.from({length: 5}, (_, i) => `<img class='${i < value ? '' : 'faded'}' src='https://upload.wikimedia.org/wikipedia/commons/d/df/Award-star-gold-3d.svg'>`).jo... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/blocks_js_methods/run.py | demo/blocks_js_methods/run.py | import gradio as gr
blocks = gr.Blocks()
with blocks as demo:
subject = gr.Textbox(placeholder="subject")
verb = gr.Radio(["ate", "loved", "hated"])
object = gr.Textbox(placeholder="object")
with gr.Row():
btn = gr.Button("Create sentence.")
reverse_btn = gr.Button("Reverse sentence."... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/chatbot_retry_undo_like/run.py | demo/chatbot_retry_undo_like/run.py | from huggingface_hub import InferenceClient
import gradio as gr
client = InferenceClient()
def respond(
prompt: str,
history,
):
if not history:
history = [{"role": "system", "content": "You are a friendly chatbot"}]
history.append({"role": "user", "content": prompt})
yield history
r... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/english_translator/run.py | demo/english_translator/run.py | import gradio as gr
from transformers import pipeline
pipe = pipeline("translation", model="t5-base")
def translate(text):
return pipe(text)[0]["translation_text"] # type: ignore
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
english = gr.Textbox(label="English text")
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_filters/run.py | demo/plot_guide_filters/run.py | import gradio as gr
from data import df # type: ignore
with gr.Blocks() as demo:
with gr.Row():
origin = gr.Dropdown(["All", "DFW", "DAL", "HOU"], value="All", label="Origin")
destination = gr.Dropdown(["All", "JFK", "LGA", "EWR"], value="All", label="Destination")
max_price = gr.Slider(0,... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/plot_guide_filters/data.py | demo/plot_guide_filters/data.py | import pandas as pd
import numpy as np
import random
from datetime import datetime, timedelta
now = datetime.now()
df = pd.DataFrame({
'time': [now - timedelta(minutes=5*i) for i in range(25)],
'price': np.random.randint(100, 1000, 25),
'origin': [random.choice(["DFW", "DAL", "HOU"]) for _ in range(25)],
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/show_progress_on/run.py | demo/show_progress_on/run.py | # This demo needs to be run from the repo folder.
# python demo/fake_gan/run.py
import time
import gradio as gr
from gradio.media import get_image
def fake_gan():
time.sleep(5)
images = [
(get_image("cheetah.jpg"), f"label {i}")
for i in range(3)
]
return images, "Done"
with gr.Blocks(... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/render_heavy_concurrently/run.py | demo/render_heavy_concurrently/run.py | import gradio as gr
import random
with gr.Blocks() as demo:
with gr.Row():
@gr.render()
def render():
for _ in range(500):
gr.Textbox(str(random.randint(0, 100)))
gr.Button("DONE 1")
@gr.render()
def render2():
for _ in range(50... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
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