Scavio + LlamaIndex

What is LlamaIndex?

Data framework for building RAG pipelines and LLM applications over custom data. Connects LLMs to external data sources.

How It Works

Scavio connects to LlamaIndex via a custom tool definition. Once connected, your LlamaIndex agent can search Google, Amazon, YouTube, and Walmart in real time. Each search returns structured JSON -- no HTML parsing, no scraping infrastructure.

Setup

pip install llama-index requests

Code Example

Here is a complete LlamaIndex integration with Scavio:

from llama_index.core.tools import FunctionTool
from llama_index.llms.openai import OpenAI
from llama_index.core.agent import ReActAgent
import requests

def search_web(query: str) -> str:
    """Search the web for real-time results."""
    response = requests.post(
        "https://api.scavio.dev/api/v1/search",
        headers={"x-api-key": "your_scavio_api_key", "Content-Type": "application/json"},
        json={"query": query},
    )
    return str(response.json())

tool = FunctionTool.from_defaults(fn=search_web)
llm = OpenAI(model="gpt-4o")
agent = ReActAgent.from_tools([tool], llm=llm, verbose=True)
response = agent.chat("What are the best noise cancelling headphones?")
print(response)

Full Working Example

A production-ready example with error handling:

from llama_index.core.tools import FunctionTool
from llama_index.llms.openai import OpenAI
from llama_index.core.agent import ReActAgent
import requests

def search_web(query: str) -> str:
    """Search the web for real-time results."""
    response = requests.post(
        "https://api.scavio.dev/api/v1/search",
        headers={"x-api-key": "your_scavio_api_key", "Content-Type": "application/json"},
        json={"query": query},
    )
    return str(response.json())

tool = FunctionTool.from_defaults(fn=search_web)
llm = OpenAI(model="gpt-4o")
agent = ReActAgent.from_tools([tool], llm=llm, verbose=True)
response = agent.chat("What are the best noise cancelling headphones?")
print(response)

Available Platforms

Once connected, your LlamaIndex agent has access to all four Scavio platforms:

• Google — Web search with knowledge graph, PAA, and AI overviews
• Amazon — Product search with prices, ratings, and reviews
• Reddit — Community, posts & threaded comments from any subreddit
• YouTube — Video search with transcripts and metadata
• Walmart — Product search with pricing and fulfillment data
• LinkedIn — Post, profile, and company discovery via search
• TikTok — Trending video, creator, and product discovery
• Shopify — Cross-store product discovery and enrichment
• X (Twitter) — Post and profile discovery via search
• Apple App Store — App discovery, ranking, and review data
• Google Play Store — Android app discovery and ranking data
• Google Reviews — Business review extraction with ratings and responses
• Google Scholar — Academic paper search with citation counts
• Google Ads Transparency — Competitor ad creative and transparency data via SERP
• Reddit Comments Tree — Deep threaded comment fetch for brand monitoring
• YouTube Shorts — Shorts-specific search with metadata
• YouTube Playlists — Playlist discovery and removal tracking
• Google Jobs — Live jobs-board search for recruiting
• Amazon Bestsellers — Bestseller rank-change feed across categories

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 LlamaIndex integration. Paid plans start at $30/month for higher volumes.