The Problem
AI agents with search tools can enter loops that burn through API credits in minutes. An agent researching a complex topic might fire 50 searches in a single turn, and a multi-agent system can do that 10x. There is no built-in throttle in LangChain, CrewAI, or most agent frameworks that limits total search spend per session or per day. Teams discover the budget is blown when the bill arrives or when the API returns a rate limit error mid-conversation. By then the credits are gone.
The Scavio Solution
Build a budget-aware wrapper around your search API calls that tracks cumulative credit usage per session, per user, and per day. The wrapper checks remaining budget before every API call and gracefully degrades when thresholds are crossed: first reducing result count, then falling back to cached results, then refusing the call with a clear message. Scavio's simple 1 credit = 1 request model makes budget tracking trivial compared to APIs with variable pricing per feature.
Before
Before budget controls, agent loops consumed hundreds of credits in a single session. Teams discovered overspend only when the monthly bill arrived or when the API key hit its limit mid-conversation.
After
After adding budget-aware wrappers, every agent session has a credit ceiling. Graceful degradation preserves agent functionality while preventing runaway costs. Monthly spend becomes predictable within 10% of the budget target.
Who It Is For
Teams running AI agents with search tools in production who have experienced unexpected credit consumption. Anyone whose agent framework does not have built-in budget controls for external API calls.
Key Benefits
- Per-session and per-day credit ceilings prevent runaway agent costs
- Graceful degradation instead of hard failures when budget is low
- Simple 1-credit-per-request model makes tracking trivial
- Real-time budget dashboard shows spend across all agent sessions
- Cached fallback reduces redundant API calls without losing functionality
Python Example
import requests
import json
from pathlib import Path
from datetime import datetime
API_KEY = "your_scavio_api_key"
DAILY_BUDGET = 500 # credits
SESSION_BUDGET = 50 # credits per agent session
class BudgetAwareSearch:
def __init__(self, api_key: str, daily_limit: int, session_limit: int):
self.api_key = api_key
self.daily_limit = daily_limit
self.session_limit = session_limit
self.session_used = 0
self._load_daily_usage()
def _load_daily_usage(self):
path = Path("search_budget.json")
if path.exists():
data = json.loads(path.read_text())
if data.get("date") == datetime.utcnow().strftime("%Y-%m-%d"):
self.daily_used = data.get("used", 0)
else:
self.daily_used = 0
else:
self.daily_used = 0
def _save_daily_usage(self):
Path("search_budget.json").write_text(json.dumps({
"date": datetime.utcnow().strftime("%Y-%m-%d"),
"used": self.daily_used,
}))
def search(self, query: str, platform: str = "google") -> dict:
if self.session_used >= self.session_limit:
return {"error": "session_budget_exceeded", "used": self.session_used, "limit": self.session_limit}
if self.daily_used >= self.daily_limit:
return {"error": "daily_budget_exceeded", "used": self.daily_used, "limit": self.daily_limit}
res = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": self.api_key},
json={"platform": platform, "query": query},
timeout=15,
)
res.raise_for_status()
self.session_used += 1
self.daily_used += 1
self._save_daily_usage()
data = res.json()
data["_budget"] = {
"session_remaining": self.session_limit - self.session_used,
"daily_remaining": self.daily_limit - self.daily_used,
}
return data
search = BudgetAwareSearch(API_KEY, DAILY_BUDGET, SESSION_BUDGET)
result = search.search("best search API for agents")
if "error" in result:
print(f"Budget exceeded: {result['error']}")
else:
print(f"Results: {len(result.get('organic', []))} | Budget remaining: {result['_budget']}")JavaScript Example
const API_KEY = "your_scavio_api_key";
const DAILY_BUDGET = 500;
const SESSION_BUDGET = 50;
class BudgetAwareSearch {
constructor(apiKey, dailyLimit, sessionLimit) {
this.apiKey = apiKey;
this.dailyLimit = dailyLimit;
this.sessionLimit = sessionLimit;
this.sessionUsed = 0;
this.dailyUsed = 0;
}
async search(query, platform = "google") {
if (this.sessionUsed >= this.sessionLimit) return { error: "session_budget_exceeded" };
if (this.dailyUsed >= this.dailyLimit) return { error: "daily_budget_exceeded" };
const res = await fetch("https://api.scavio.dev/api/v1/search", {
method: "POST",
headers: { "x-api-key": this.apiKey, "content-type": "application/json" },
body: JSON.stringify({ platform, query }),
});
if (!res.ok) throw new Error(`scavio ${res.status}`);
this.sessionUsed++;
this.dailyUsed++;
const data = await res.json();
data._budget = { sessionRemaining: this.sessionLimit - this.sessionUsed, dailyRemaining: this.dailyLimit - this.dailyUsed };
return data;
}
}
const search = new BudgetAwareSearch(API_KEY, DAILY_BUDGET, SESSION_BUDGET);
const result = await search.search("best search API for agents");
if (result.error) console.log(`Budget: ${result.error}`);
else console.log(`Results: ${result.organic?.length ?? 0} | Remaining: ${JSON.stringify(result._budget)}`);Platforms Used
Web search with knowledge graph, PAA, and AI overviews
YouTube
Video search with transcripts and metadata
Amazon
Product search with prices, ratings, and reviews
Walmart
Product search with pricing and fulfillment data
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