Create app.py

app.py

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+import numpy as np
+import gradio as gr
+from pathlib import Path
+import os
+from PIL import Image
+
+def prime_factors(n: str):
+    """
+    Compute the prime factorization of a positive integer.
+
+    Args:
+        n (str): The integer to factorize. Must be greater than 1.
+    """
+    n_int = int(n)
+    if n_int <= 1:
+        raise ValueError("Input must be an integer greater than 1.")
+
+    factors = []
+    while n_int % 2 == 0:
+        factors.append(2)
+        n_int //= 2
+
+    divisor = 3
+    while divisor * divisor <= n_int:
+        while n_int % divisor == 0:
+            factors.append(divisor)
+            n_int //= divisor
+        divisor += 2
+
+    if n_int > 1:
+        factors.append(n_int)
+
+    return factors
+
+
+def generate_cheetah_image():
+    """
+    Generate a cheetah image.
+
+    Returns:
+        The generated cheetah image.
+    """
+    return Path(os.path.dirname(__file__)) / "cheetah.jpg"
+
+
+def image_orientation(image: Image.Image) -> str:
+    """
+    Returns whether image is portrait or landscape.
+
+    Args:
+        image (Image.Image): The image to check.
+
+    Returns:
+        str: "Portrait" if image is portrait, "Landscape" if image is landscape.
+    """
+    return "Portrait" if image.height > image.width else "Landscape"
+
+
+def sepia(input_img):
+    """
+    Apply a sepia filter to the input image.
+
+    Args:
+        input_img (np.array): The input image to apply the sepia filter to.
+
+    Returns:
+        The sepia filtered image.
+    """
+    sepia_filter = np.array([
+        [0.393, 0.769, 0.189],
+        [0.349, 0.686, 0.168],
+        [0.272, 0.534, 0.131]
+    ])
+    sepia_img = input_img.dot(sepia_filter.T)
+    sepia_img /= sepia_img.max()
+    return sepia_img
+
+
+
+demo = gr.TabbedInterface(
+    [
+        gr.Interface(prime_factors, gr.Textbox(), gr.Textbox(), api_name="prime_factors"),
+        gr.Interface(generate_cheetah_image, None, gr.Image(), api_name="generate_cheetah_image"),
+        gr.Interface(image_orientation, gr.Image(type="pil"), gr.Textbox(), api_name="image_orientation"),
+        gr.Interface(sepia, gr.Image(), gr.Image(), api_name="sepia"),
+    ],
+    [
+        "Prime Factors",
+        "Cheetah Image",
+        "Image Orientation Checker",
+        "Sepia Filter",
+    ]
+)
+
+if __name__ == "__main__":
+    demo.launch(mcp_server=True)