Upload with huggingface_hub

README.md

@@ -1,12 +1,11 @@
+
 ---
-title: Kitchen Sink Random
-emoji: 🔥
+title: kitchen_sink_random 
+emoji: 💩
 colorFrom: indigo
-colorTo: gray
+colorTo: indigo
 sdk: gradio
-sdk_version: 3.1.4
+sdk_version: 3.1.4b3
 app_file: app.py
 pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,98 @@
+import gradio as gr
+from datetime import datetime
+import random
+import string
+import os
+import pandas as pd
+
+from constants import (
+    file_dir,
+    img_dir,
+    highlighted_text,
+    highlighted_text_output_2,
+    highlighted_text_output_1,
+    random_plot,
+    random_model3d,
+)
+
+
+demo = gr.Interface(
+    lambda x: x,
+    inputs=[
+        gr.Textbox(value=lambda: datetime.now(), label="Current Time"),
+        gr.Number(value=lambda: random.random(), label="Ranom Percentage"),
+        gr.Slider(minimum=-1, maximum=1, randomize=True, label="Slider with randomize"),
+        gr.Slider(
+            minimum=0,
+            maximum=1,
+            value=lambda: random.random(),
+            label="Slider with value func",
+        ),
+        gr.Checkbox(value=lambda: random.random() > 0.5, label="Random Checkbox"),
+        gr.CheckboxGroup(
+            choices=["a", "b", "c", "d"],
+            value=lambda: random.choice(["a", "b", "c", "d"]),
+            label="Random CheckboxGroup",
+        ),
+        gr.Radio(
+            choices=list(string.ascii_lowercase),
+            value=lambda: random.choice(string.ascii_lowercase),
+        ),
+        gr.Dropdown(
+            choices=["a", "b", "c", "d", "e"],
+            value=lambda: random.choice(["a", "b", "c"]),
+        ),
+        gr.Image(
+            value=lambda: random.choice(
+                [os.path.join(img_dir, img) for img in os.listdir(img_dir)]
+            )
+        ),
+        gr.Video(value=lambda: os.path.join(file_dir, "world.mp4")),
+        gr.Audio(value=lambda: os.path.join(file_dir, "cantina.wav")),
+        gr.File(
+            value=lambda: random.choice(
+                [os.path.join(file_dir, img) for img in os.listdir(file_dir)]
+            )
+        ),
+        gr.Dataframe(
+            value=lambda: pd.DataFrame(
+                {"random_number_rows": range(random.randint(0, 10))}
+            )
+        ),
+        gr.Timeseries(value=lambda: os.path.join(file_dir, "time.csv")),
+        gr.Variable(value=lambda: random.choice(string.ascii_lowercase)),
+        gr.Button(value=lambda: random.choice(["Run", "Go", "predict"])),
+        gr.ColorPicker(value=lambda: random.choice(["#000000", "#ff0000", "#0000FF"])),
+        gr.Label(value=lambda: random.choice(["Pedestrian", "Car", "Cyclist"])),
+        gr.HighlightedText(
+            value=lambda: random.choice(
+                [
+                    {"text": highlighted_text, "entities": highlighted_text_output_1},
+                    {"text": highlighted_text, "entities": highlighted_text_output_2},
+                ]
+            ),
+        ),
+        gr.JSON(value=lambda: random.choice([{"a": 1}, {"b": 2}])),
+        gr.HTML(
+            value=lambda: random.choice(
+                [
+                    '<p style="color:red;">I am red</p>',
+                    '<p style="color:blue;">I am blue</p>',
+                ]
+            )
+        ),
+        gr.Gallery(
+            value=lambda: [os.path.join(img_dir, img) for img in os.listdir(img_dir)]
+        ),
+        gr.Chatbot(
+            value=lambda: random.choice([[("hello", "hi!")], [("bye", "goodbye!")]])
+        ),
+        gr.Model3D(value=random_model3d),
+        gr.Plot(value=random_plot),
+        gr.Markdown(value=lambda: f"### {random.choice(['Hello', 'Hi', 'Goodbye!'])}"),
+    ],
+    outputs=None,
+)
+
+if __name__ == "__main__":
+    demo.launch()

constants.py

@@ -0,0 +1,71 @@
+import numpy as np
+import matplotlib
+
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+import random
+import os
+
+
+def random_plot():
+    start_year = 2020
+    x = np.arange(start_year, start_year + random.randint(0, 10))
+    year_count = x.shape[0]
+    plt_format = "-"
+    fig = plt.figure()
+    ax = fig.add_subplot(111)
+    series = np.arange(0, year_count, dtype=float)
+    series = series**2
+    series += np.random.rand(year_count)
+    ax.plot(x, series, plt_format)
+    return fig
+
+
+img_dir = os.path.join(os.path.dirname(__file__), "..", "image_classifier", "images")
+file_dir = os.path.join(os.path.dirname(__file__), "..", "kitchen_sink", "files")
+model3d_dir = os.path.join(os.path.dirname(__file__), "..", "model3D", "files")
+highlighted_text_output_1 = [
+    {
+        "entity": "I-LOC",
+        "score": 0.9988978,
+        "index": 2,
+        "word": "Chicago",
+        "start": 5,
+        "end": 12,
+    },
+    {
+        "entity": "I-MISC",
+        "score": 0.9958592,
+        "index": 5,
+        "word": "Pakistani",
+        "start": 22,
+        "end": 31,
+    },
+]
+highlighted_text_output_2 = [
+    {
+        "entity": "I-LOC",
+        "score": 0.9988978,
+        "index": 2,
+        "word": "Chicago",
+        "start": 5,
+        "end": 12,
+    },
+    {
+        "entity": "I-LOC",
+        "score": 0.9958592,
+        "index": 5,
+        "word": "Pakistan",
+        "start": 22,
+        "end": 30,
+    },
+]
+
+highlighted_text = "Does Chicago have any Pakistani restaurants"
+
+
+def random_model3d():
+    model_3d = random.choice(
+        [os.path.join(model3d_dir, model) for model in os.listdir(model3d_dir) if model != "source.txt"]
+    )
+    return model_3d