What is OpenAI Assistants?
OpenAI's API for building AI assistants with function calling, code interpreter, and file search capabilities.
Searching Reddit Comments Tree with OpenAI Assistants
This integration lets your OpenAI Assistants 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 openai requestsCode Example
Here is a complete OpenAI Assistants agent that searches Reddit Comments Tree using Scavio:
Python
from openai import OpenAI
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.
client = OpenAI()
def scavio_search(query: str) -> str:
"""Query Reddit Comments Tree through the Scavio API (POST /api/v1/reddit/post/comments)."""
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())
tools = [{
"type": "function",
"function": {
"name": "scavio_search",
"description": "Query Reddit Comments Tree 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": "t3_1u1143i"}],
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
# 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.
client = OpenAI()
def scavio_search(query: str) -> str:
"""Query Reddit Comments Tree through the Scavio API (POST /api/v1/reddit/post/comments)."""
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())
tools = [{
"type": "function",
"function": {
"name": "scavio_search",
"description": "Query Reddit Comments Tree for real-time results",
"parameters": {
"type": "object",
"properties": {"query": {"type": "string"}},
"required": ["query"],
},
},
}]
messages = [{"role": "user", "content": "t3_1u1143i"}]
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.