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 post results, profile results, company results, post snippets — 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 requests
import json
client = OpenAI()
def scavio_search(query: str) -> str:
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": "your_scavio_api_key", "Content-Type": "application/json"},
json={"query": query},
)
return json.dumps(response.json())
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "site:linkedin.com/in AI engineer San Francisco"}],
tools=[{
"type": "function",
"function": {
"name": "scavio_search",
"description": "Search LinkedIn for real-time results",
"parameters": {
"type": "object",
"properties": {"query": {"type": "string"}},
"required": ["query"],
},
},
}],
)
# Handle tool calls
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 requests
import json
client = OpenAI()
def scavio_search(query: str) -> str:
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": "your_scavio_api_key", "Content-Type": "application/json"},
json={"query": query},
)
return json.dumps(response.json())
tools = [{
"type": "function",
"function": {
"name": "scavio_search",
"description": "Search 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-4o", 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-4o", messages=messages)
print(final.choices[0].message.content)Pricing
Scavio offers a free tier with 500 credits/month (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.