What is Semantic Kernel?
Microsoft's SDK for integrating LLMs into applications. Supports plugins, planners, and memory for building AI agents.
Searching YouTube Shorts with Semantic Kernel
This integration lets your Semantic Kernel agent search YouTube Shorts in real time via the Scavio API. The agent gets back structured JSON with short video results, video ids, view counts, published time -- ready for reasoning and decision-making.
Setup
pip install semantic-kernel requestsCode Example
Here is a complete Semantic Kernel agent that searches YouTube Shorts using Scavio:
import semantic_kernel as sk
from semantic_kernel.functions import kernel_function
import json
import os
import requests
# Shorts search takes search (not query). channel.name is often empty on Shorts rows - resolve it with POST /api/v1/youtube/video when you need it.
class ScavioPlugin:
@kernel_function(description="Query YouTube Shorts using Scavio")
def search(self, query: str) -> str:
response = requests.post(
"https://api.scavio.dev/api/v1/youtube/shorts",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"search": query},
timeout=60,
)
response.raise_for_status()
return json.dumps(response.json())
kernel = sk.Kernel()
kernel.add_plugin(ScavioPlugin(), "scavio")Full Working Example
A production-ready example with error handling:
import semantic_kernel as sk
from semantic_kernel.functions import kernel_function
import json
import os
import requests
# Shorts search takes search (not query). channel.name is often empty on Shorts rows - resolve it with POST /api/v1/youtube/video when you need it.
class ScavioPlugin:
@kernel_function(description="Query YouTube Shorts using Scavio")
def search(self, query: str) -> str:
response = requests.post(
"https://api.scavio.dev/api/v1/youtube/shorts",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"search": query},
timeout=60,
)
response.raise_for_status()
return json.dumps(response.json())
kernel = sk.Kernel()
kernel.add_plugin(ScavioPlugin(), "scavio")
result = await kernel.invoke("scavio", "search", query="ai coding agent shorts")
print(result)Pricing
Scavio offers a free tier with 50 credits on signup (1 credit per search). No credit card required. This is enough to build and test your Semantic Kernel integration. Paid plans start at $30/month for higher volumes.