What is OpenAI Assistants?
OpenAI's API for building AI assistants with function calling, code interpreter, and file search capabilities.
Searching YouTube Playlists with OpenAI Assistants
This integration lets your OpenAI Assistants agent search YouTube Playlists in real time via the Scavio API. The agent gets back structured JSON with playlist entries from search, video results, channel results, shorts results -- ready for reasoning and decision-making.
Setup
Bash
pip install openai requestsCode Example
Here is a complete OpenAI Assistants agent that searches YouTube Playlists using Scavio:
Python
from openai import OpenAI
import json
import os
import requests
# Playlist data is not available: POST /api/v1/youtube/search accepts type: playlist but the provider returns an empty playlists array, so there is no playlist title, video count, creator or visibility to read, and no removal tracking. This sample returns the videos for the query; type: channel does work if you want creators instead.
client = OpenAI()
def scavio_search(query: str) -> str:
"""Query YouTube Playlists through the Scavio API (POST /api/v1/youtube/search)."""
response = requests.post(
"https://api.scavio.dev/api/v1/youtube/search",
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())
tools = [{
"type": "function",
"function": {
"name": "scavio_search",
"description": "Query YouTube Playlists for real-time results",
"parameters": {
"type": "object",
"properties": {"query": {"type": "string"}},
"required": ["query"],
},
},
}]
response = client.chat.completions.create(
model="gpt-5.5",
messages=[{"role": "user", "content": "best rag tutorials playlist"}],
tools=tools,
)
for tool_call in response.choices[0].message.tool_calls or []:
result = scavio_search(json.loads(tool_call.function.arguments)["query"])
print(result[:500])Full Working Example
A production-ready example with error handling:
Python
from openai import OpenAI
import json
import os
import requests
# Playlist data is not available: POST /api/v1/youtube/search accepts type: playlist but the provider returns an empty playlists array, so there is no playlist title, video count, creator or visibility to read, and no removal tracking. This sample returns the videos for the query; type: channel does work if you want creators instead.
client = OpenAI()
def scavio_search(query: str) -> str:
"""Query YouTube Playlists through the Scavio API (POST /api/v1/youtube/search)."""
response = requests.post(
"https://api.scavio.dev/api/v1/youtube/search",
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())
tools = [{
"type": "function",
"function": {
"name": "scavio_search",
"description": "Query YouTube Playlists for real-time results",
"parameters": {
"type": "object",
"properties": {"query": {"type": "string"}},
"required": ["query"],
},
},
}]
messages = [{"role": "user", "content": "best rag tutorials playlist"}]
response = client.chat.completions.create(model="gpt-5.5", messages=messages, tools=tools)
if response.choices[0].message.tool_calls:
messages.append(response.choices[0].message)
for tc in response.choices[0].message.tool_calls:
result = scavio_search(json.loads(tc.function.arguments)["query"])
messages.append({"role": "tool", "tool_call_id": tc.id, "content": result})
final = client.chat.completions.create(model="gpt-5.5", messages=messages)
print(final.choices[0].message.content)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 OpenAI Assistants integration. Paid plans start at $30/month for higher volumes.