What is CrewAI?
Framework for orchestrating autonomous AI agents that collaborate to complete tasks. Supports multi-agent crews with defined roles.
Searching Walmart with CrewAI
This integration lets your CrewAI agent search Walmart in real time via the Scavio API. The agent gets back structured JSON with product listings, prices, ratings, review counts — ready for reasoning and decision-making.
Setup
Bash
pip install crewai requestsCode Example
Here is a complete CrewAI agent that searches Walmart using Scavio:
Python
from crewai import Agent, Task, Crew
from crewai.tools import tool
import requests
@tool("Scavio Search")
def scavio_search(query: str) -> str:
"""Search Walmart using Scavio API."""
response = requests.post(
"https://api.scavio.dev/api/v1/walmart/search",
headers={"x-api-key": "your_scavio_api_key", "Content-Type": "application/json"},
json={"query": query},
)
return str(response.json())
researcher = Agent(
role="Walmart Research Specialist",
goal="Find accurate, up-to-date information using Walmart search",
backstory="You are an expert researcher with access to real-time search data.",
tools=[scavio_search],
)
task = Task(
description="Research: standing desk",
expected_output="A detailed summary with sources",
agent=researcher,
)
crew = Crew(agents=[researcher], tasks=[task])
result = crew.kickoff()
print(result)Full Working Example
A production-ready example with error handling:
Python
from crewai import Agent, Task, Crew
from crewai.tools import tool
import requests
@tool("Scavio Search")
def scavio_search(query: str) -> str:
"""Search Walmart using Scavio API."""
response = requests.post(
"https://api.scavio.dev/api/v1/walmart/search",
headers={"x-api-key": "your_scavio_api_key", "Content-Type": "application/json"},
json={"query": query},
)
return str(response.json())
researcher = Agent(
role="Walmart Research Specialist",
goal="Find accurate, up-to-date information",
backstory="Expert researcher with real-time search access.",
tools=[scavio_search],
)
task = Task(
description="Research: standing desk",
expected_output="Detailed summary with key findings and sources",
agent=researcher,
)
crew = Crew(agents=[researcher], tasks=[task], verbose=True)
result = crew.kickoff()
print(result)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 CrewAI integration. Paid plans start at $30/month for higher volumes.