What is Semantic Kernel?
Microsoft's SDK for integrating LLMs into applications. Supports plugins, planners, and memory for building AI agents.
Searching Reddit Comments Tree with Semantic Kernel
This integration lets your Semantic Kernel agent search Reddit Comments Tree in real time via the Scavio API. The agent gets back structured JSON with comment text, authors, scores, depth -- ready for reasoning and decision-making.
Setup
Bash
pip install semantic-kernel requestsCode Example
Here is a complete Semantic Kernel agent that searches Reddit Comments Tree using Scavio:
Text
import semantic_kernel as sk
from semantic_kernel.functions import kernel_function
import json
import os
import requests
# Comments are fetched per post: get a post_id from POST /api/v1/reddit/search, or resolve a URL with POST /api/v1/reddit/post. Deeper replies come from POST /api/v1/reddit/post/comments/replies using a row's reply_cursor.
class ScavioPlugin:
@kernel_function(description="Query Reddit Comments Tree using Scavio")
def search(self, query: str) -> str:
response = requests.post(
"https://api.scavio.dev/api/v1/reddit/post/comments",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"post_id": query, "sort": "TOP"},
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:
Text
import semantic_kernel as sk
from semantic_kernel.functions import kernel_function
import json
import os
import requests
# Comments are fetched per post: get a post_id from POST /api/v1/reddit/search, or resolve a URL with POST /api/v1/reddit/post. Deeper replies come from POST /api/v1/reddit/post/comments/replies using a row's reply_cursor.
class ScavioPlugin:
@kernel_function(description="Query Reddit Comments Tree using Scavio")
def search(self, query: str) -> str:
response = requests.post(
"https://api.scavio.dev/api/v1/reddit/post/comments",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"post_id": query, "sort": "TOP"},
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="t3_1u1143i")
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.