What is CrewAI?
Framework for orchestrating autonomous AI agents that collaborate to complete tasks. Supports multi-agent crews with defined roles.
Searching Reddit Comments Tree with CrewAI
This integration lets your CrewAI agent search Reddit Comments Tree in real time via the Scavio API. The agent gets back structured JSON with comment text, authors, scores, depth -- ready for reasoning and decision-making.
Setup
Bash
pip install crewai requestsCode Example
Here is a complete CrewAI agent that searches Reddit Comments Tree using Scavio:
Python
from crewai import Agent, Task, Crew
from crewai.tools import tool
import json
import os
import requests
# Comments are fetched per post: get a post_id from POST /api/v1/reddit/search, or resolve a URL with POST /api/v1/reddit/post. Deeper replies come from POST /api/v1/reddit/post/comments/replies using a row's reply_cursor.
@tool("Scavio Search")
def scavio_search(query: str) -> str:
"""Query Reddit Comments Tree through the Scavio API (POST /api/v1/reddit/post/comments)."""
response = requests.post(
"https://api.scavio.dev/api/v1/reddit/post/comments",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"post_id": query, "sort": "TOP"},
timeout=60,
)
response.raise_for_status()
return json.dumps(response.json())
researcher = Agent(
role="Reddit Comments Tree Research Specialist",
goal="Find accurate, up-to-date information using Reddit Comments Tree data",
backstory="You are an expert researcher with access to real-time search data.",
tools=[scavio_search],
)
task = Task(
description="Research: t3_1u1143i",
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 json
import os
import requests
# Comments are fetched per post: get a post_id from POST /api/v1/reddit/search, or resolve a URL with POST /api/v1/reddit/post. Deeper replies come from POST /api/v1/reddit/post/comments/replies using a row's reply_cursor.
@tool("Scavio Search")
def scavio_search(query: str) -> str:
"""Query Reddit Comments Tree through the Scavio API (POST /api/v1/reddit/post/comments)."""
response = requests.post(
"https://api.scavio.dev/api/v1/reddit/post/comments",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"post_id": query, "sort": "TOP"},
timeout=60,
)
response.raise_for_status()
return json.dumps(response.json())
researcher = Agent(
role="Reddit Comments Tree Research Specialist",
goal="Find accurate, up-to-date information",
backstory="Expert researcher with real-time search access.",
tools=[scavio_search],
)
task = Task(
description="Research: t3_1u1143i",
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 50 credits on signup (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.