Update app.py

app.py

@@ -1,26 +1,26 @@
 import gradio as gr
 import requests
+import numpy as np
+import os
+from pathlib import Path
+from PIL import Image
 from dotenv import load_dotenv
-import os 
-load_dotenv()
 
+load_dotenv()
 
-# API Setup
+# YouTube Tool
 API_URL = "https://youtube138.p.rapidapi.com/search/"
 HEADERS = {
     "x-rapidapi-key": os.getenv("Rapidapi"),
     "x-rapidapi-host": "youtube138.p.rapidapi.com"
 }
 
-# Core function
 def search_youtube(query: str) -> str:
     params = {"q": query, "hl": "en", "gl": "US"}
     try:
         response = requests.get(API_URL, headers=HEADERS, params=params)
         response.raise_for_status()
         data = response.json()
-
-        # Extract top 5 video titles + links
         videos = data.get("contents", [])
         results = []
         for video in videos:
@@ -32,20 +32,62 @@ def search_youtube(query: str) -> str:
                 results.append(f"{title}\n{link}\n")
             if len(results) >= 5:
                 break
-
         return "\n".join(results) if results else "No videos found."
     except Exception as e:
         return f"Error: {str(e)}"
 
-# Gradio Interface
-demo = gr.Interface(
-    fn=search_youtube,
-    inputs=gr.Textbox(placeholder="Enter search term...", label="YouTube Query"),
-    outputs=gr.Textbox(label="Top 5 Results"),
-    title="YouTube Search Tool",
-    description="Search YouTube videos using the YouTube138 API (via RapidAPI)"
+# Other Tools
+def prime_factors(n):
+    n = int(n)
+    if n <= 1:
+        raise ValueError("Input must be an integer greater than 1.")
+    factors = []
+    while n % 2 == 0:
+        factors.append(2)
+        n //= 2
+    divisor = 3
+    while divisor * divisor <= n:
+        while n % divisor == 0:
+            factors.append(divisor)
+            n //= divisor
+        divisor += 2
+    if n > 1:
+        factors.append(n)
+    return factors
+
+def generate_cheetah_image():
+    return Path(os.path.dirname(__file__)) / "cheetah.jpg"
+
+def image_orientation(image: Image.Image) -> str:
+    return "Portrait" if image.height > image.width else "Landscape"
+
+def sepia(input_img):
+    sepia_filter = np.array([
+        [0.393, 0.769, 0.189],
+        [0.349, 0.686, 0.168],
+        [0.272, 0.534, 0.131]
+    ])
+    sepia_img = np.array(input_img).dot(sepia_filter.T)
+    sepia_img /= sepia_img.max()
+    return sepia_img
+
+# Tabbed Tool Interface
+demo = gr.TabbedInterface(
+    [
+        gr.Interface(search_youtube, gr.Textbox(label="YouTube Query"), gr.Textbox(label="Top 5 Results"), api_name="youtube_search"),
+        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"),
+    ],
+    [
+        "YouTube Search",
+        "Prime Factors",
+        "Cheetah Image",
+        "Image Orientation Checker",
+        "Sepia Filter",
+    ]
 )
 
-# MCP-compatible launch
 if __name__ == "__main__":
     demo.launch(mcp_server=True)