What is OpenAI Assistants?
OpenAI's API for building AI assistants with function calling, code interpreter, and file search capabilities.
Searching Google Scholar with OpenAI Assistants
This integration lets your OpenAI Assistants agent search Google Scholar in real time via the Scavio API. The agent gets back structured JSON with paper titles, paper URLs, SERP snippets -- ready for reasoning and decision-making.
Setup
Bash
pip install openai requestsCode Example
Here is a complete OpenAI Assistants agent that searches Google Scholar using Scavio:
Python
from openai import OpenAI
import json
import os
import requests
# Scavio has no Google Scholar endpoint, so citation counts and author lists are not available. This runs a Google web search - narrow it with site:arxiv.org or filetype:pdf.
client = OpenAI()
def scavio_search(query: str) -> str:
"""Query Google Scholar through the Scavio API (POST /api/v2/google)."""
response = requests.post(
"https://api.scavio.dev/api/v2/google",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"query": query},
timeout=60,
)
response.raise_for_status()
return json.dumps(response.json())
tools = [{
"type": "function",
"function": {
"name": "scavio_search",
"description": "Query Google Scholar 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": "retrieval augmented generation 2024"}],
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
# Scavio has no Google Scholar endpoint, so citation counts and author lists are not available. This runs a Google web search - narrow it with site:arxiv.org or filetype:pdf.
client = OpenAI()
def scavio_search(query: str) -> str:
"""Query Google Scholar through the Scavio API (POST /api/v2/google)."""
response = requests.post(
"https://api.scavio.dev/api/v2/google",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"query": query},
timeout=60,
)
response.raise_for_status()
return json.dumps(response.json())
tools = [{
"type": "function",
"function": {
"name": "scavio_search",
"description": "Query Google Scholar for real-time results",
"parameters": {
"type": "object",
"properties": {"query": {"type": "string"}},
"required": ["query"],
},
},
}]
messages = [{"role": "user", "content": "retrieval augmented generation 2024"}]
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.