What is AutoGen?
Microsoft's framework for building multi-agent conversational AI systems. Agents can converse, use tools, and collaborate autonomously.
Searching Google Ads Transparency with AutoGen
This integration lets your AutoGen agent search Google Ads Transparency in real time via the Scavio API. The agent gets back structured JSON with advertiser_id and region_code, total_ads range, creative_id and preview URLs, first_shown, last_shown, days_shown -- ready for reasoning and decision-making.
Setup
pip install autogen-agentchat requestsCode Example
Here is a complete AutoGen agent that searches Google Ads Transparency using Scavio:
from autogen import ConversableAgent
import json
import os
import requests
def scavio_search(query: str) -> str:
"""Query Google Ads Transparency through the Scavio API (POST /api/v1/googleads/advertisers)."""
response = requests.post(
"https://api.scavio.dev/api/v1/googleads/advertisers",
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 Google Ads Transparency")(scavio_search)
user.register_for_execution(name="search")(scavio_search)
user.initiate_chat(assistant, message="Research: Nike")Full Working Example
A production-ready example with error handling:
from autogen import ConversableAgent
import json
import os
import requests
def scavio_search(query: str) -> str:
"""Query Google Ads Transparency through the Scavio API (POST /api/v1/googleads/advertisers)."""
response = requests.post(
"https://api.scavio.dev/api/v1/googleads/advertisers",
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 Google Ads Transparency")(scavio_search)
user.register_for_execution(name="search")(scavio_search)
user.initiate_chat(assistant, message="Research: Nike")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.