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/duplicatebutton_component/run.py | demo/duplicatebutton_component/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.DuplicateButton()
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/pending_inputs/run.py | demo/pending_inputs/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.Markdown("# Pending Input Components")
with gr.Row():
with gr.Column():
file = gr.File()
btn = gr.Button("Upload")
with gr.Column():
output_file = gr.File()
btn.click(
lambda s: (s)... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/sentiment_analysis/run.py | demo/sentiment_analysis/run.py | import gradio as gr
import nltk # type: ignore
from nltk.sentiment.vader import SentimentIntensityAnalyzer # type: ignore
nltk.download("vader_lexicon")
sid = SentimentIntensityAnalyzer()
def sentiment_analysis(text):
scores = sid.polarity_scores(text)
del scores["compound"]
return scores
demo = gr.Int... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/copy_events/run.py | demo/copy_events/run.py | import gradio as gr
md = "This is **bold** text."
def copy_callback(copy_data: gr.CopyData):
return copy_data.value
with gr.Blocks() as demo:
textbox = gr.Textbox(label="Copied text")
with gr.Row():
markdown = gr.Markdown(value=md, header_links=True, height=400, buttons=["copy"])
chatbot ... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/image_editor_canvas_size/run.py | demo/image_editor_canvas_size/run.py | import gradio as gr
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
image = gr.ImageEditor(label="Default Canvas. Not fixed", elem_id="default")
get_image = gr.Button("Get Default")
with gr.Column():
custom_canvas = gr.ImageEditor(label="Custom Canvas,... | 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_debugger/run.py | demo/audio_debugger/run.py | import gradio as gr
import subprocess
from gradio.media import get_audio, MEDIA_PATHS
# get_audio returns the path to the audio file
audio_file = get_audio("cantina.wav")
with gr.Blocks() as demo:
with gr.Tab("Audio"):
gr.Audio(audio_file, buttons=["download"])
with gr.Tab("Interface"):
gr.Int... | 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_thoughts/run.py | demo/chatbot_thoughts/run.py | import gradio as gr
from gradio import ChatMessage
import time
def simulate_thinking_chat(message: str, history: list):
history.append(
ChatMessage(
role="assistant",
content="",
metadata={"title": "Thinking... ", "log": "Starting analysis"}
)
)
time.slee... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/loginbutton_component/run.py | demo/loginbutton_component/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.LoginButton()
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/stable-diffusion/run.py | demo/stable-diffusion/run.py | import gradio as gr
import torch
from diffusers import StableDiffusionPipeline # type: ignore
from PIL import Image
import os
auth_token = os.getenv("HF_TOKEN")
if not auth_token:
print(
"ERROR: No Hugging Face access token found.\n"
"Please define an environment variable 'auth_token' before runni... | 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_custom_styling/run.py | demo/dataframe_custom_styling/run.py | import gradio as gr
data = [
["DeepSeek Coder", 79.3],
["Llama 3.3", 68.9],
["Qwen 2.5", 61.9],
["Gemma 2", 59.5],
["GPT 2", 18.3],
]
headers = ["Model", "% Correct (LeetCode Hard)"]
def get_styling(values):
return [["", f"background: linear-gradient(90deg, rgba(220, 242, 220) {row[1]}%, tran... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/gpt2_xl/run.py | demo/gpt2_xl/run.py | import gradio as gr
title = "gpt2-xl"
examples = [
["The tower is 324 metres (1,063 ft) tall,"],
["The Moon's orbit around Earth has"],
["The smooth Borealis basin in the Northern Hemisphere covers 40%"],
]
demo = gr.load(
"huggingface/gpt2-xl",
inputs=gr.Textbox(lines=5, max_lines=6, label="Inpu... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/iframe_resizer/run.py | demo/iframe_resizer/run.py | import gradio as gr
import time
import os
from gradio import get_image
def greet():
gr.Info("Warning in 1 second")
time.sleep(1)
gr.Warning("Error in 1 second")
time.sleep(1)
raise Exception("test")
im = get_image("cheetah.jpg")
with gr.Blocks() as demo:
with gr.Tab("Accordions"):
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/render_preserve_key/run.py | demo/render_preserve_key/run.py | import gradio as gr
import random
with gr.Blocks() as demo:
number_of_boxes = gr.Slider(1, 5, step=1, value=3, label="Number of Boxes")
@gr.render(inputs=[number_of_boxes])
def create_boxes(number_of_boxes):
for i in range(number_of_boxes):
with gr.Row(key=f'row-{i}'):
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/image_component/run.py | demo/image_component/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.Image()
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_essay_simple/run.py | demo/blocks_essay_simple/run.py | import gradio as gr
def change_textbox(choice):
if choice == "short":
return gr.Textbox(lines=2, visible=True)
elif choice == "long":
return gr.Textbox(lines=8, visible=True, value="Lorem ipsum dolor sit amet")
else:
return gr.Textbox(visible=False)
with gr.Blocks() as demo:
ra... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/walkthrough/run.py | demo/walkthrough/run.py | import gradio as gr
with gr.Blocks() as demo:
with gr.Walkthrough(selected=0) as walkthrough:
with gr.Step("Image", id=0):
image = gr.Image()
btn = gr.Button("go to prompt")
btn.click(lambda: gr.Walkthrough(selected=1), outputs=walkthrough)
with gr.Step("Prompt",... | 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_events/run.py | demo/plot_guide_filters_events/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_events/data.py | demo/plot_guide_filters_events/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/chatbot_with_tools/run.py | demo/chatbot_with_tools/run.py | import gradio as gr
from gradio import ChatMessage
import time
def generate_response(history):
history.append(
ChatMessage(
role="user", content="What is the weather in San Francisco right now?"
)
)
yield history
time.sleep(0.25)
history.append(
ChatMessage(
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/hello_world_4/run.py | demo/hello_world_4/run.py | import gradio as gr
def greet(name, intensity):
return "Hello, " + name + "!" * int(intensity)
demo = gr.Interface(
fn=greet,
inputs=["text", "slider"],
outputs=["text"],
api_name="predict"
)
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/image_editor_layers/run.py | demo/image_editor_layers/run.py | import gradio as gr
from pathlib import Path
dir_ = Path(__file__).parent
def predict(im):
print(im)
return im, len(im["layers"])
with gr.Blocks() as demo:
with gr.Row():
im = gr.ImageEditor(
type="numpy",
interactive=True,
)
im_preview = gr.ImageEditor(
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/slider_release/run.py | demo/slider_release/run.py | import gradio as gr
def identity(x, state):
state += 1
return x, state, state
with gr.Blocks() as demo:
slider = gr.Slider(0, 100, step=0.1)
state = gr.State(value=0)
with gr.Row():
number = gr.Number(label="On release")
number2 = gr.Number(label="Number of events fired")
slide... | 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_watermark/run.py | demo/video_watermark/run.py | import gradio as gr
a = gr.get_video("a.mp4")
b = gr.get_video("b.mp4")
w1 = gr.get_image("logo.png")
w2 = gr.get_image("bus.png")
def generate_video(original_video, watermark, position):
return gr.Video(original_video, watermark=gr.WatermarkOptions(watermark=watermark, position=position))
demo = gr.Interface(... | 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_editable/run.py | demo/chatbot_editable/run.py | import gradio as gr
with gr.Blocks() as demo:
with gr.Row():
chatbot = gr.Chatbot(value=[], editable="user")
add_message_btn = gr.Button("Add Message")
add_user_message_btn = gr.Button("Add User Message")
with gr.Row():
concatenated_text1 = gr.Textbox(label="Concatenated Chat 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/autocomplete/run.py | demo/autocomplete/run.py | import gradio as gr
import os
# save your HF API token from https:/hf.co/settings/tokens as an env variable to avoid rate limiting
hf_token = os.getenv("hf_token")
# load a model from https://hf.co/models as an interface, then use it as an api
# you can remove the hf_token parameter if you don't care about rate limit... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/upload_and_download/run.py | demo/upload_and_download/run.py | from pathlib import Path
import gradio as gr
def upload_file(filepath):
name = Path(filepath).name
return [gr.UploadButton(visible=False), gr.DownloadButton(label=f"Download {name}", value=filepath, visible=True)]
def download_file():
return [gr.UploadButton(visible=True), gr.DownloadButton(visible=False)... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/stock_forecast/run.py | demo/stock_forecast/run.py | import matplotlib.pyplot as plt
import numpy as np
import gradio as gr
def plot_forecast(final_year, companies, noise, show_legend, point_style):
start_year = 2020
x = np.arange(start_year, final_year + 1)
year_count = x.shape[0]
plt_format = ({"cross": "X", "line": "-", "circle": "o--"})[point_style]... | 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_state/run.py | demo/interface_state/run.py | import gradio as gr
def store_message(message: str, history: list[str]): # type: ignore
output = {
"Current messages": message,
"Previous messages": history[::-1]
}
history.append(message)
return output, history
demo = gr.Interface(fn=store_message,
inputs=["textbo... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/html_component/run.py | demo/html_component/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.HTML(value="<p style='margin-top: 1rem, margin-bottom: 1rem'>This <em>example</em> was <strong>written</strong> in <a href='https://en.wikipedia.org/wiki/HTML' _target='blank'>HTML</a> </p>")
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/chatbot_multimodal/run.py | demo/chatbot_multimodal/run.py | import gradio as gr
import time
# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.
def print_like_dislike(x: gr.LikeData):
print(x.index, x.value, x.liked)
def add_message(history, message):
user_msg = {"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/theme_new_step_2/run.py | demo/theme_new_step_2/run.py | from __future__ import annotations
from typing import Iterable
import gradio as gr
from gradio.themes.base import Base
from gradio.themes.utils import colors, fonts, sizes
import time
class Seafoam(Base):
def __init__(
self,
*,
primary_hue: colors.Color | str = colors.emerald,
secon... | 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_sambanova/run.py | demo/llm_sambanova/run.py | # This is a simple general-purpose chatbot built on top of SambaNova API.
# Before running this, make sure you have exported your SambaNova API key as an environment variable:
# export SAMBANOVA_API_KEY="your-sambanova-api-key"
import os
import gradio as gr
from openai import OpenAI
api_key = os.getenv("SAMBANOVA_AP... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/white_noise_vid_not_playable/run.py | demo/white_noise_vid_not_playable/run.py | import cv2 # type: ignore
import gradio as gr
import numpy as np
def gif_maker():
img_array = []
height, width = 50, 50
for _ in range(30):
img_array.append(np.random.randint(0, 255, size=(height, width, 3)).astype(np.uint8))
output_file = "test.mp4"
out = cv2.VideoWriter(output_file, cv2.... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/function_values/run.py | demo/function_values/run.py | import gradio as gr
import random
countries = [
"Algeria",
"Argentina",
"Australia",
"Brazil",
"Canada",
"China",
"Democratic Republic of the Congo",
"Greenland (Denmark)",
"India",
"Kazakhstan",
"Mexico",
"Mongolia",
"Peru",
"Russia",
"Saudi Arabia",
"Su... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/theme_new_step_3/run.py | demo/theme_new_step_3/run.py | from __future__ import annotations
from typing import Iterable
import gradio as gr
from gradio.themes.base import Base
from gradio.themes.utils import colors, fonts, sizes
import time
class Seafoam(Base):
def __init__(
self,
*,
primary_hue: colors.Color | str = colors.emerald,
secon... | 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_live/run.py | demo/on_listener_live/run.py | import gradio as gr
with gr.Blocks() as demo:
with gr.Row():
num1 = gr.Slider(1, 10)
num2 = gr.Slider(1, 10)
num3 = gr.Slider(1, 10)
output = gr.Number(label="Sum")
@gr.on(inputs=[num1, num2, num3], outputs=output)
def sum(a, b, c):
return a + b + c
if __name__ == "__m... | 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_scatter_nominal/run.py | demo/plot_guide_scatter_nominal/run.py | import gradio as gr
from data import df # type: ignore
with gr.Blocks() as demo:
gr.ScatterPlot(df, x="ethnicity", y="height")
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_scatter_nominal/data.py | demo/plot_guide_scatter_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/plot_guide_tables_stats/run.py | demo/plot_guide_tables_stats/run.py | import gradio as gr
from data import df # type: ignore
with gr.Blocks() as demo:
with gr.Row():
gr.Label(len(df), label="Flight Count")
gr.Label(f"${df['price'].min()}", label="Cheapest Flight")
gr.DataFrame(df)
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_tables_stats/data.py | demo/plot_guide_tables_stats/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/stream_audio_out/run.py | demo/stream_audio_out/run.py | import gradio as gr
from pydub import AudioSegment
from time import sleep
import os
import tempfile
from pathlib import Path
with gr.Blocks() as demo:
input_audio = gr.Audio(label="Input Audio", type="filepath", format="mp3")
with gr.Row():
with gr.Column():
stream_as_file_btn = gr.Button("... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/latex/run.py | demo/latex/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.Markdown(
r"""
# Hello World! $\frac{\sqrt{x + y}}{4}$ is today's lesson
## the $\sqrt{x + y}$ is first
Start with $\frac{\frac{x+1}{x+2}}{x+3}$ then we get $ 2+x $ and $3$.
There are three formulas to know:
the first is $\gamma^2... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/examples_component/run.py | demo/examples_component/run.py | import gradio as gr
# get_image() returns the file path to sample images included with Gradio
from gradio.media import get_image
def flip(i):
return i.rotate(180)
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
img_i = gr.Image(label="Input Image", type="pil")
with gr.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/uploadbutton_component/run.py | demo/uploadbutton_component/run.py | import gradio as gr
def upload_file(files):
file_paths = [file.name for file in files]
return file_paths
with gr.Blocks() as demo:
file_output = gr.File()
upload_button = gr.UploadButton("Click to Upload an Image or Video File", file_types=["image", "video"], file_count="multiple")
upload_button.u... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/dialogue_mock_diarization/run.py | demo/dialogue_mock_diarization/run.py | import gradio as gr
speakers = [
"Speaker 1",
"Speaker 2",
]
def format_speaker(speaker, text):
return f"{speaker}: {text}"
def mock_diarization(audio):
return [
{
"speaker": "Speaker 1",
"text": "Hello, how are you?",
},
{
"speaker": "Speak... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/letter_counter/run.py | demo/letter_counter/run.py | import gradio as gr
def letter_counter(word, letter):
"""
Count the number of occurrences of a letter in a word or text.
Args:
word (str): The input text to search through
letter (str): The letter to search for
Returns:
str: A message indicating how many times the letter appea... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/highlight_pdf/run.py | demo/highlight_pdf/run.py | import gradio as gr
from gradio_pdf import PDF
import pymupdf # type: ignore
import os
from pathlib import Path
current_dir = Path(os.path.abspath(''))
def highlight_text_in_pdf(pdf_file: Path, highlight_text: str):
page_number = 0
doc = pymupdf.open(pdf_file)
for page in doc:
text_instances = pa... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/dialogue_diarization_demo/run.py | demo/dialogue_diarization_demo/run.py | # type: ignore
import gradio as gr
from pyannote.audio import Pipeline
import whisper
diarization_pipeline = None
whisper_model = None
def load_models():
global diarization_pipeline, whisper_model # noqa: PLW0603
if diarization_pipeline is None:
diarization_pipeline = Pipeline.from_pretrained(
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/hello_blocks_decorator/run.py | demo/hello_blocks_decorator/run.py | import gradio as gr
with gr.Blocks() as demo:
name = gr.Textbox(label="Name")
output = gr.Textbox(label="Output Box")
greet_btn = gr.Button("Greet")
@greet_btn.click(inputs=name, outputs=output)
def greet(name):
return "Hello " + name + "!"
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/downloadbutton_component/run.py | demo/downloadbutton_component/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.DownloadButton("📂 Click to download file", value="http://www.marketingtool.online/en/face-generator/img/faces/avatar-1151ce9f4b2043de0d2e3b7826127998.jpg")
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/unispeech-speaker-verification/run.py | demo/unispeech-speaker-verification/run.py | # type: ignore
import gradio as gr
import torch
from torchaudio.sox_effects import apply_effects_file # type: ignore
from transformers import AutoFeatureExtractor, AutoModelForAudioXVector
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
STYLE = """
<link rel="stylesheet" href="https://cdn.jsdel... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/gallery_component/run.py | demo/gallery_component/run.py | import gradio as gr
from gradio.media import get_image, get_video
with gr.Blocks() as demo:
gallery_items = [
("https://upload.wikimedia.org/wikipedia/commons/0/09/TheCheethcat.jpg", "cheetah1"),
("https://nationalzoo.si.edu/sites/default/files/animals/cheetah-003.jpg", "cheetah2"),
("https... | 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_interactive/run.py | demo/plot_guide_interactive/run.py | import gradio as gr
from data import df # type: ignore
with gr.Blocks() as demo:
with gr.Row():
ethnicity = gr.Dropdown(["all", "white", "black", "asian"], value="all")
max_age = gr.Slider(18, 65, value=65)
def filtered_df(ethnic, age):
_df = df if ethnic == "all" else df[df["ethnicit... | 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_interactive/data.py | demo/plot_guide_interactive/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_sidebar/run.py | demo/blocks_sidebar/run.py | import gradio as gr
import random
def generate_pet_name(animal_type, personality):
cute_prefixes = ["Fluffy", "Ziggy", "Bubbles", "Pickle", "Waffle", "Mochi", "Cookie", "Pepper"]
animal_suffixes = {
"Cat": ["Whiskers", "Paws", "Mittens", "Purrington"],
"Dog": ["Woofles", "Barkington", "Waggins"... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/unload_event_test/run.py | demo/unload_event_test/run.py | """This demo is only meant to test the unload event.
It will write to a file when the unload event is triggered.
May not work as expected if multiple people are using it.
"""
import gradio as gr
from pathlib import Path
log_file = (Path(__file__).parent / "output_log.txt").resolve()
def test_fn(x):
with open(log_... | 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_textbox_max_lines/run.py | demo/blocks_textbox_max_lines/run.py | import gradio as gr
def greet(name: str, repeat: float):
return "Hello " + name * int(repeat) + "!!"
demo = gr.Interface(
fn=greet, inputs=[gr.Textbox(lines=2, max_lines=4), gr.Number()], outputs="textarea", api_name="predict"
)
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/run.py | demo/file_explorer/run.py | import gradio as gr
from pathlib import Path
current_file_path = Path(__file__).resolve()
relative_path = "path/to/file"
absolute_path = (current_file_path.parent / ".." / ".." / "gradio").resolve()
def get_file_content(file):
if file is None or Path(file).is_dir():
return None
return Path(file).read_... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/agent_chatbot/run.py | demo/agent_chatbot/run.py | import gradio as gr
from dataclasses import asdict
from transformers import Tool, ReactCodeAgent # type: ignore
from transformers.agents import stream_to_gradio, HfApiEngine # type: ignore
# Import tool from Hub
image_generation_tool = Tool.from_space( # type: ignore
space_id="black-forest-labs/FLUX.1-schnell",... | 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/run.py | demo/model3D/run.py | import gradio as gr
# get_model3d() returns the file path to sample 3D models included with Gradio
from gradio.media import get_model3d, MEDIA_ROOT
def load_mesh(mesh_file_name):
return mesh_file_name
demo = gr.Interface(
fn=load_mesh,
inputs=gr.Model3D(label="Other name", display_mode="wireframe"),
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/image_editor_sketchpad/run.py | demo/image_editor_sketchpad/run.py | import gradio as gr
import numpy as np
def percent_of_pixels_selected(image):
mask = image["layers"][0]
mask_bool = mask[:,:,3] > 0
return f"{round(np.sum(mask_bool) / mask_bool.size * 100, 2)}%"
image_editor = gr.Sketchpad(
type="numpy",
)
output_image = gr.Label(
label="Percent of Pixels Selecte... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/event_trigger/run.py | demo/event_trigger/run.py | # %%
import gradio as gr
TEST_VIDEO_A = "mp4/a.mp4"
TEST_VIDEO_B = "mp4/b.mp4"
TEST_IMAGE_A = "img/a.jpg"
TEST_IMAGE_B = "img/b.jpg"
def alert_change(component, value):
print(f"Detected {component} change, {type(value)}")
if type(value) == list or type(value) == str:
print(value)
def change_interac... | 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_inputs/run.py | demo/blocks_inputs/run.py | import gradio as gr
import os
def combine(a, b):
return a + " " + b
def mirror(x):
return x
with gr.Blocks() as demo:
txt = gr.Textbox(label="Input", lines=2)
txt_2 = gr.Textbox(label="Input 2")
txt_3 = gr.Textbox(value="", label="Output")
btn = gr.Button(value="Submit")
btn.click(combin... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/playback_position/run.py | demo/playback_position/run.py | import gradio as gr
from gradio.media import get_audio, get_video
# Get the directory where this script is located
with gr.Blocks() as demo:
with gr.Tab("Audio"):
gr.Markdown("## Audio Playback Position")
gr.Markdown("Click the button to see the current playback position of the audio.")
au... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/save_file_no_output/run.py | demo/save_file_no_output/run.py | import random
import string
import gradio as gr
def save_image_random_name(image):
random_string = ''.join(random.choices(string.ascii_letters, k=20)) + '.png'
image.save(random_string)
print(f"Saved image to {random_string}!")
demo = gr.Interface(
fn=save_image_random_name,
inputs=gr.Image(type="... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/count_generator/run.py | demo/count_generator/run.py | import gradio as gr
import time
def count(n):
for i in range(int(n)):
time.sleep(0.5)
yield i
def show(n):
return str(list(range(int(n))))
with gr.Blocks() as demo:
with gr.Column():
num = gr.Number(value=10)
with gr.Row():
count_btn = gr.Button("Count")
... | 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_without_queue/run.py | demo/concurrency_without_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(max_threads=41)
| python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/theme_new_step_1/run.py | demo/theme_new_step_1/run.py | import gradio as gr
from gradio.themes.base import Base
import time
class Seafoam(Base):
pass
seafoam = Seafoam()
with gr.Blocks() as demo:
textbox = gr.Textbox(label="Name")
slider = gr.Slider(label="Count", minimum=0, maximum=100, step=1)
with gr.Row():
button = gr.Button("Submit", variant=... | 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_simple/run.py | demo/chatbot_simple/run.py | import gradio as gr
import random
import time
with gr.Blocks() as demo:
chatbot = gr.Chatbot()
msg = gr.Textbox()
clear = gr.ClearButton([msg, chatbot])
def respond(message, chat_history):
bot_message = random.choice(["How are you?", "Today is a great day", "I'm very hungry"])
chat_his... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/gallery_selections/run.py | demo/gallery_selections/run.py | import gradio as gr
import numpy as np
with gr.Blocks() as demo:
imgs = gr.State()
gallery = gr.Gallery(allow_preview=False)
def deselect_images():
return gr.Gallery(selected_index=None)
def generate_images():
images = []
for _ in range(9):
image = np.ones((100, 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/calculator_list_and_dict/run.py | demo/calculator_list_and_dict/run.py | import gradio as gr
with gr.Blocks() as demo:
a = gr.Number(label="a")
b = gr.Number(label="b")
with gr.Row():
add_btn = gr.Button("Add")
sub_btn = gr.Button("Subtract")
c = gr.Number(label="sum")
def add(num1, num2):
return num1 + num2
add_btn.click(add, inputs=[a, 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/llm_langchain/run.py | demo/llm_langchain/run.py | # This is a simple general-purpose chatbot built on top of LangChain and Gradio.
# Before running this, make sure you have exported your OpenAI API key as an environment variable:
# export OPENAI_API_KEY="your-openai-api-key"
from langchain_openai import ChatOpenAI # type: ignore
from langchain.schema import AIMessag... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/hello_world_2/run.py | demo/hello_world_2/run.py | import gradio as gr
def greet(name, intensity):
return "Hello, " + name + "!" * intensity
demo = gr.Interface(
fn=greet,
inputs=["text", gr.Slider(value=2, minimum=1, maximum=10, step=1)],
outputs=[gr.Textbox(label="greeting", lines=3)],
api_name="predict"
)
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/markdown_with_mermaid/run.py | demo/markdown_with_mermaid/run.py | import gradio as gr
demo = gr.Blocks()
with demo:
gr.Markdown(
"""
# Project Documentation with Mermaid Diagrams
This example demonstrates how to combine regular Markdown with Mermaid diagrams for better visualization.
## System Architecture
Below... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/super_html/run.py | demo/super_html/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.Markdown("""
# Simple HTML usecase
This is the classic `gr.HTML` usecase where we just want to render some static HTML.
""")
simple_html = gr.HTML("<h1 style='color:purple;' id='simple'>Hello, World!</h1>")
gr.Markdown("""
# Templated HTML ... | 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_component/run.py | demo/chatbot_component/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.Chatbot(value=[ # type: ignore
{"role": "user", "content": "Hello World"},
{"role": "assistant", "content": "Hey Gradio!"},
{"role": "user", "content": "❤️"},
{"role": "assistant", "content": "😍"},
{"role": "user", "content"... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/custom_css/run.py | demo/custom_css/run.py | import gradio as gr
with gr.Blocks() as demo:
with gr.Column(elem_classes="cool-col"):
gr.Markdown("### Gradio Demo with Custom CSS", elem_classes="darktest")
gr.Markdown(
elem_classes="markdown",
value="Resize the browser window to see the CSS media query in action.",
... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/sine_curve/run.py | demo/sine_curve/run.py | import math
import gradio as gr
import plotly.express as px # type: ignore
import numpy as np
plot_end = 2 * math.pi
def get_plot(period=1):
global plot_end
x = np.arange(plot_end - 2 * math.pi, plot_end, 0.02)
y = np.sin(2*math.pi*period * x)
fig = px.line(x=x, y=y)
plot_end += 2 * math.pi
i... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/rate_limit/run.py | demo/rate_limit/run.py | import gradio as gr
from datetime import datetime, timedelta
from collections import defaultdict
import threading
rate_limit_data = defaultdict(list)
lock = threading.Lock()
UNAUTH_RATE_LIMIT = 3
AUTH_RATE_LIMIT = 30
RATE_LIMIT_WINDOW = 60
def clean_old_entries(user_id):
"""Remove entries older than the rate 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/dataframe_block-ui-test/run.py | demo/dataframe_block-ui-test/run.py | import gradio as gr
with gr.Blocks() as demo:
count = gr.Slider(minimum=1, maximum=10, step=1, label="count")
data = gr.DataFrame(
headers=["A", "B"], col_count=(2, "fixed"), type="array", interactive=True # type: ignore
)
btn = gr.Button(value="click")
btn.click(
fn=lambda cnt: [[... | 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_examples/run.py | demo/test_chatinterface_examples/run.py | import gradio as gr
def generate(
message: str,
chat_history: list[dict],
):
output = ""
for character in message:
output += character
yield output
demo = gr.ChatInterface(
fn=generate,
examples=[
["Hey"],
["Can you explain briefly to me what is the Python pro... | 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_examples/multimodal_messages_examples_testcase.py | demo/test_chatinterface_examples/multimodal_messages_examples_testcase.py | import gradio as gr
def generate(
message: dict,
chat_history: list[dict],
):
output = ""
for character in message['text']:
output += character
yield output
demo = gr.ChatInterface(
fn=generate,
examples=[
[{"text": "Hey"}],
[{"text": "Can you explain briefly ... | 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_examples/lazy_caching_examples_testcase.py | demo/test_chatinterface_examples/lazy_caching_examples_testcase.py | import gradio as gr
def generate(
message: str,
chat_history: list[dict],
):
output = ""
for character in message:
output += character
yield output
demo = gr.ChatInterface(
fn=generate,
examples=[
["Hey"],
["Can you explain briefly to me what is the Python pro... | 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_examples/eager_caching_examples_testcase.py | demo/test_chatinterface_examples/eager_caching_examples_testcase.py | import gradio as gr
def generate(
message: str,
chat_history: list[dict],
):
output = ""
for character in message:
output += character
yield output
demo = gr.ChatInterface(
fn=generate,
examples=[
["Hey"],
["Can you explain briefly to me what is the Python pro... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/many_tabs/run.py | demo/many_tabs/run.py | import gradio as gr
import pandas as pd
import numpy as np
# Sample data for components
sample_df = pd.DataFrame(
{
"Name": ["Alice", "Bob", "Charlie", "Diana", "Eve"],
"Age": [25, 30, 35, 28, 32],
"City": ["New York", "London", "Paris", "Tokyo", "Berlin"],
"Score": [95.5, 87.2, 92.... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/login_with_huggingface/run.py | demo/login_with_huggingface/run.py | from __future__ import annotations
import gradio as gr
from huggingface_hub import whoami
def hello(profile: gr.OAuthProfile | None) -> str:
if profile is None:
return "I don't know you."
return f"Hello {profile.name}"
def list_organizations(oauth_token: gr.OAuthToken | None) -> str:
if oauth_tok... | 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/run.py | demo/fake_diffusion/run.py | import gradio as gr
import numpy as np
import time
def fake_diffusion(steps):
rng = np.random.default_rng()
for i in range(steps):
time.sleep(1)
image = rng.random(size=(600, 600, 3))
yield image
image = np.ones((1000,1000,3), np.uint8)
image[:] = [255, 124, 0]
yield 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/skip/run.py | demo/skip/run.py | import random
import gradio as gr
with gr.Blocks() as demo:
with gr.Row():
clear_button = gr.Button("Clear")
skip_button = gr.Button("Skip")
random_button = gr.Button("Random")
numbers = [gr.Number(), gr.Number()]
clear_button.click(lambda : (None, None), outputs=numbers)
skip_... | 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_essay/run.py | demo/blocks_essay/run.py | import gradio as gr
countries_cities_dict = {
"USA": ["New York", "Los Angeles", "Chicago"],
"Canada": ["Toronto", "Montreal", "Vancouver"],
"Pakistan": ["Karachi", "Lahore", "Islamabad"],
}
def change_textbox(choice):
if choice == "short":
return gr.Textbox(lines=2, visible=True), gr.Button(i... | 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/run.py | demo/model3d_component/run.py | import gradio as gr
with gr.Blocks() as demo:
gr.Model3D()
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_nested_thoughts/run.py | demo/chatinterface_nested_thoughts/run.py | import gradio as gr
from gradio import ChatMessage
import time
sleep_time = 0.1
long_sleep_time = 1
def generate_response(message, history):
start_time = time.time()
responses = [
ChatMessage(
content="In order to find the current weather in San Francisco, I will need to use my weather too... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/stt_or_tts/run.py | demo/stt_or_tts/run.py | import gradio as gr
tts_examples = [
"I love learning machine learning",
"How do you do?",
]
tts_demo = gr.load(
"huggingface/facebook/fastspeech2-en-ljspeech",
title=None,
examples=tts_examples,
description="Give me something to say!",
cache_examples=False
)
stt_demo = gr.load(
"hugg... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/image_mod/run.py | demo/image_mod/run.py | import gradio as gr
from gradio.media import get_image
def image_mod(image):
return image.rotate(45)
# get_image() returns file paths to sample media included with Gradio
new_samples = [
[get_image("logo.png")],
[get_image("tower.jpg")],
]
with gr.Blocks() as demo:
interface = gr.Interface(
i... | 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_openai/run.py | demo/llm_openai/run.py | # This is a simple general-purpose chatbot built on top of OpenAI API.
# Before running this, make sure you have exported your OpenAI API key as an environment variable:
# export OPENAI_API_KEY="your-openai-api-key"
from openai import OpenAI
import gradio as gr
client = OpenAI()
def predict(message, history):
h... | 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_unified/run.py | demo/streaming_filter_unified/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/depth_estimation/run.py | demo/depth_estimation/run.py | # type: ignore
import gradio as gr
from transformers import DPTFeatureExtractor, DPTForDepthEstimation
import torch
import numpy as np
from PIL import Image
import open3d as o3d # type: ignore
from pathlib import Path
feature_extractor = DPTFeatureExtractor.from_pretrained("Intel/dpt-large")
model = DPTForDepthEstima... | 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_tool_only/run.py | demo/mcp_tool_only/run.py | import gradio as gr
def slice_list(lst: list, start: int, end: int) -> list:
"""
A tool that slices a list given a start and end index.
Args:
lst: The list to slice.
start: The start index.
end: The end index.
Returns:
The sliced list.
"""
return lst[start:end]
... | 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_component/run.py | demo/star_rating_component/run.py | import gradio as gr
class StarRating(gr.HTML):
def __init__(self, label, value=0, **kwargs):
html_template = """
<h2>${label} rating:</h2>
${Array.from({length: 5}, (_, i) => `<img class='${i < value ? '' : 'faded'}' src='https://upload.wikimedia.org/wikipedia/commons/d/df/Award-star-gold-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/dialogue_component/run.py | demo/dialogue_component/run.py | import gradio as gr
with gr.Blocks() as demo:
dd = gr.Dialogue(speakers=["Speaker 1", "Speaker 2"],
tags=["(laughs)", "(sighs)", "(clears throat)"],
value=[
{"speaker": "Speaker 1", "text": "Hello, how are you?"},
{"speaker": "Speaker 2",... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
gradio-app/gradio | https://github.com/gradio-app/gradio/blob/3b56b13268ddcaf74d4e85e5dbf5a616d7843995/demo/custom_path/run.py | demo/custom_path/run.py | from fastapi import FastAPI
import gradio as gr
CUSTOM_PATH = "/gradio"
app = FastAPI()
@app.get("/")
def read_main():
return {"message": "This is your main app"}
io = gr.Interface(lambda x: "Hello, " + x + "!", "textbox", "textbox")
app = gr.mount_gradio_app(app, io, path=CUSTOM_PATH)
# Run this from the term... | python | Apache-2.0 | 3b56b13268ddcaf74d4e85e5dbf5a616d7843995 | 2026-01-04T14:40:26.993006Z | false |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.