What is OpenAI Assistants?
OpenAI's API for building AI assistants with function calling, code interpreter, and file search capabilities.
Searching X (Twitter) with OpenAI Assistants
This integration lets your OpenAI Assistants agent search X (Twitter) in real time via the Scavio API. The agent gets back structured JSON with post text, author handles, created_at timestamps, favorites, retweets, replies, quotes -- ready for reasoning and decision-making.
Setup
Bash
pip install openai requestsCode Example
Here is a complete OpenAI Assistants agent that searches X (Twitter) using Scavio:
Python
from openai import OpenAI
import json
import os
import requests
# X takes search (not query). search_type is one of Top, Latest, People, Photos, Videos.
client = OpenAI()
def scavio_search(query: str) -> str:
"""Query X (Twitter) through the Scavio API (POST /api/v1/x/search)."""
response = requests.post(
"https://api.scavio.dev/api/v1/x/search",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"search": query, "search_type": "Latest"},
timeout=60,
)
response.raise_for_status()
return json.dumps(response.json())
tools = [{
"type": "function",
"function": {
"name": "scavio_search",
"description": "Query X (Twitter) 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": "AI agents"}],
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
# X takes search (not query). search_type is one of Top, Latest, People, Photos, Videos.
client = OpenAI()
def scavio_search(query: str) -> str:
"""Query X (Twitter) through the Scavio API (POST /api/v1/x/search)."""
response = requests.post(
"https://api.scavio.dev/api/v1/x/search",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"search": query, "search_type": "Latest"},
timeout=60,
)
response.raise_for_status()
return json.dumps(response.json())
tools = [{
"type": "function",
"function": {
"name": "scavio_search",
"description": "Query X (Twitter) for real-time results",
"parameters": {
"type": "object",
"properties": {"query": {"type": "string"}},
"required": ["query"],
},
},
}]
messages = [{"role": "user", "content": "AI agents"}]
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.