The Problem
Ollama assistants hallucinate on anything after their training cutoff. Without web search, they cannot answer questions about current events, prices, or recent releases. Adding search fixes the knowledge gap without sacrificing privacy.
How Scavio Helps
- Ollama handles conversation locally -- only search queries hit the web
- Search results injected into context give the model current facts to cite
- Simple HTTP integration: Ollama API + Scavio API, both REST
- Free tier (250 credits/month) covers casual daily assistant usage
- No conversation data sent to any cloud service
Relevant Platforms
Web search with knowledge graph, PAA, and AI overviews
Quick Start: Python Example
Here is a quick example searching Google for "add web search to ollama local assistant":
import requests
API_KEY = "your_scavio_api_key"
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={
"x-api-key": API_KEY,
"Content-Type": "application/json",
},
json={"query": query},
)
data = response.json()
for result in data.get("organic_results", [])[:5]:
print(f"{result['position']}. {result['title']}")
print(f" {result['link']}\n")Built for Privacy-focused users running Ollama for personal AI assistance who need current information
Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your ollama personal assistant with live search solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.
Start with the free tier (50 credits on signup, no credit card required) and scale to paid plans when you need higher volume.