What is AutoGen?
Microsoft's framework for building multi-agent conversational AI systems. Agents can converse, use tools, and collaborate autonomously.
Searching Glassdoor with AutoGen
This integration lets your AutoGen agent search Glassdoor in real time via the Scavio API. The agent gets back structured JSON with employer_id and profile, overall and category ratings, reviews (max 3 per response), salary bands by title -- ready for reasoning and decision-making.
Setup
pip install autogen-agentchat requestsCode Example
Here is a complete AutoGen agent that searches Glassdoor using Scavio:
from autogen import ConversableAgent
import json
import os
import requests
# This page has no dedicated endpoint yet, so the sample runs a Google web search.
def scavio_search(query: str) -> str:
"""Query Glassdoor 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())
assistant = ConversableAgent(
"assistant",
llm_config={"model": "gpt-5.5"},
system_message="You are a helpful research assistant.",
)
user = ConversableAgent("user", human_input_mode="NEVER")
assistant.register_for_llm(name="search", description="Query Glassdoor")(scavio_search)
user.register_for_execution(name="search")(scavio_search)
user.initiate_chat(assistant, message="Research: Stripe")Full Working Example
A production-ready example with error handling:
from autogen import ConversableAgent
import json
import os
import requests
# This page has no dedicated endpoint yet, so the sample runs a Google web search.
def scavio_search(query: str) -> str:
"""Query Glassdoor 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())
assistant = ConversableAgent(
"assistant",
llm_config={"model": "gpt-5.5"},
system_message="You are a helpful research assistant with real-time search.",
)
user = ConversableAgent("user", human_input_mode="NEVER", max_consecutive_auto_reply=3)
assistant.register_for_llm(name="search", description="Query Glassdoor")(scavio_search)
user.register_for_execution(name="search")(scavio_search)
user.initiate_chat(assistant, message="Research: Stripe")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 AutoGen integration. Paid plans start from $24/mo billed yearly for higher volumes.