What is OpenAI Assistants?
OpenAI's API for building AI assistants with function calling, code interpreter, and file search capabilities.
Searching LinkedIn with OpenAI Assistants
This integration lets your OpenAI Assistants agent search LinkedIn in real time via the Scavio API. The agent gets back structured JSON with job listings, company names, locations, posted dates -- ready for reasoning and decision-making.
Setup
Bash
pip install openai requestsCode Example
Here is a complete OpenAI Assistants agent that searches LinkedIn using Scavio:
Python
from openai import OpenAI
import json
import os
import requests
# There is no LinkedIn people or post search: LinkedIn retired it upstream. This finds LinkedIn pages through Google. For structured data call POST /api/v1/linkedin/person, /company or /post with a LinkedIn URL, or /api/v1/linkedin/search/jobs for keyword job search.
client = OpenAI()
def scavio_search(query: str) -> str:
"""Query LinkedIn 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 LinkedIn 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": "site:linkedin.com/in AI engineer San Francisco"}],
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
# There is no LinkedIn people or post search: LinkedIn retired it upstream. This finds LinkedIn pages through Google. For structured data call POST /api/v1/linkedin/person, /company or /post with a LinkedIn URL, or /api/v1/linkedin/search/jobs for keyword job search.
client = OpenAI()
def scavio_search(query: str) -> str:
"""Query LinkedIn 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 LinkedIn for real-time results",
"parameters": {
"type": "object",
"properties": {"query": {"type": "string"}},
"required": ["query"],
},
},
}]
messages = [{"role": "user", "content": "site:linkedin.com/in AI engineer San Francisco"}]
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.