What is AutoGen?
Microsoft's framework for building multi-agent conversational AI systems. Agents can converse, use tools, and collaborate autonomously.
Searching Indeed with AutoGen
This integration lets your AutoGen agent search Indeed in real time via the Scavio API. The agent gets back structured JSON with job postings, company and company_url, company_rating and review_count, benefits and attributes -- ready for reasoning and decision-making.
Setup
Bash
pip install autogen-agentchat requestsCode Example
Here is a complete AutoGen agent that searches Indeed using Scavio:
Python
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 Indeed 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 Indeed")(scavio_search)
user.register_for_execution(name="search")(scavio_search)
user.initiate_chat(assistant, message="Research: python developer")Full Working Example
A production-ready example with error handling:
Python
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 Indeed 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 Indeed")(scavio_search)
user.register_for_execution(name="search")(scavio_search)
user.initiate_chat(assistant, message="Research: python developer")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.