Los agentes de IA pueden consumir rápidamente los presupuestos de API si no se los supervisa. Este rastreador de presupuesto incluye sus llamadas a la API de búsqueda con seguimiento de costos, establece límites de gasto por agente, alertas antes de que se exceda el presupuesto y registra el costo por tarea para su optimización. Funciona con cualquier API que cobre por llamada.
Requisitos previos
- Python 3.8+
- solicita biblioteca
- Una clave API de Scavio de scavio.dev
- Al menos un agente realizando llamadas API
Guia paso a paso
Paso 1: Cree el contenedor de API con seguimiento del presupuesto
Complete las llamadas API con seguimiento de costos y cumplimiento de presupuesto.
Python
import os, requests, json, time
from datetime import datetime
from collections import defaultdict
API_KEY = os.environ['SCAVIO_API_KEY']
SH = {'x-api-key': API_KEY, 'Content-Type': 'application/json'}
class BudgetTracker:
def __init__(self, cost_per_call=0.005):
self.cost_per_call = cost_per_call
self.agents = {} # agent_id -> {budget, spent, calls}
self.log = []
def register_agent(self, agent_id, daily_budget):
self.agents[agent_id] = {
'budget': daily_budget,
'spent': 0.0,
'calls': 0,
'created': datetime.now().strftime('%Y-%m-%d')
}
print(f'Registered: {agent_id} (budget: ${daily_budget}/day)')
def can_spend(self, agent_id):
agent = self.agents.get(agent_id)
if not agent:
return False
remaining = agent['budget'] - agent['spent']
return remaining >= self.cost_per_call
def search(self, agent_id, query, **kwargs):
if not self.can_spend(agent_id):
remaining = self.agents[agent_id]['budget'] - self.agents[agent_id]['spent']
print(f'BUDGET EXCEEDED: {agent_id} (${remaining:.3f} remaining)')
return {'error': 'budget_exceeded', 'remaining': remaining}
data = requests.post('https://api.scavio.dev/api/v1/search',
headers=SH, json={'query': query, 'country_code': 'us', **kwargs}).json()
self.agents[agent_id]['spent'] += self.cost_per_call
self.agents[agent_id]['calls'] += 1
self.log.append({'agent': agent_id, 'query': query, 'cost': self.cost_per_call,
'time': datetime.now().isoformat()})
return data
tracker = BudgetTracker()
tracker.register_agent('research-agent', daily_budget=0.50)
tracker.register_agent('seo-agent', daily_budget=1.00)
tracker.register_agent('lead-agent', daily_budget=0.25)Paso 2: Utilice la búsqueda rastreada en los flujos de trabajo de los agentes
Reemplace las llamadas API directas con versiones con seguimiento del presupuesto.
Python
# Simulate agent usage
queries = {
'research-agent': ['best python framework 2026', 'fastapi vs django', 'python testing tools'],
'seo-agent': ['serp api comparison', 'search api pricing', 'mcp search tool', 'ai agent search'],
'lead-agent': ['saas companies hiring 2026', 'startup funding round'],
}
for agent_id, agent_queries in queries.items():
print(f'\n--- {agent_id} ---')
for q in agent_queries:
result = tracker.search(agent_id, q)
if 'error' in result:
print(f' BLOCKED: {q}')
else:
count = len(result.get('organic_results', []))
print(f' "{q}" -> {count} results')
# Check remaining budgets
print(f'\n=== Budget Status ===')
for agent_id, data in tracker.agents.items():
remaining = data['budget'] - data['spent']
pct = data['spent'] / data['budget'] * 100
bar = '#' * int(pct / 5)
print(f' {agent_id:20} | ${data["spent"]:.3f}/${data["budget"]:.2f} ({pct:.0f}%) | {bar}')Paso 3: Generar informes de gastos
Analice patrones de gasto y optimice los presupuestos de los agentes.
Python
def spending_report(tracker):
print(f'\n=== Agent Spending Report - {datetime.now().strftime("%Y-%m-%d")} ===')
total_spent = sum(a['spent'] for a in tracker.agents.values())
total_budget = sum(a['budget'] for a in tracker.agents.values())
total_calls = sum(a['calls'] for a in tracker.agents.values())
print(f' Total spent: ${total_spent:.3f} / ${total_budget:.2f} budget')
print(f' Total calls: {total_calls}')
print(f' Avg cost/call: ${total_spent/total_calls:.4f}' if total_calls else '')
print(f'\n Per-Agent Breakdown:')
for agent_id, data in sorted(tracker.agents.items(), key=lambda x: x[1]['spent'], reverse=True):
efficiency = data['spent'] / data['calls'] if data['calls'] else 0
print(f' {agent_id:20} | {data["calls"]:3} calls | ${data["spent"]:.3f} spent | ${efficiency:.4f}/call')
# Monthly projection
monthly = total_spent * 30
print(f'\n Monthly projection: ${monthly:.2f}')
print(f' Annual projection: ${monthly * 12:.2f}')
# Optimization suggestions
print(f'\n Optimization Suggestions:')
for agent_id, data in tracker.agents.items():
usage = data['spent'] / data['budget'] * 100
if usage < 30:
print(f' {agent_id}: Budget underused ({usage:.0f}%). Consider reducing to ${data["spent"] * 2:.2f}/day.')
elif usage > 90:
print(f' {agent_id}: Near limit ({usage:.0f}%). Consider increasing budget.')
spending_report(tracker)Ejemplo en Python
Python
import os, requests
SH = {'x-api-key': os.environ['SCAVIO_API_KEY'], 'Content-Type': 'application/json'}
class Budget:
def __init__(self, limit): self.limit = limit; self.spent = 0
def search(self, q):
if self.spent + 0.005 > self.limit:
return print(f'Budget exceeded: ${self.spent:.3f}/${self.limit}')
data = requests.post('https://api.scavio.dev/api/v1/search',
headers=SH, json={'query': q, 'country_code': 'us'}).json()
self.spent += 0.005
print(f'{q}: {len(data.get("organic_results", []))} results (${self.spent:.3f}/${self.limit})')
b = Budget(0.025)
for q in ['api 1', 'api 2', 'api 3', 'api 4', 'api 5', 'api 6']:
b.search(q)Ejemplo en JavaScript
JavaScript
const SH = { 'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json' };
let spent = 0; const limit = 0.025;
async function budgetSearch(q) {
if (spent + 0.005 > limit) { console.log(`Budget exceeded`); return; }
const data = await fetch('https://api.scavio.dev/api/v1/search', {
method: 'POST', headers: SH, body: JSON.stringify({ query: q, country_code: 'us' })
}).then(r => r.json());
spent += 0.005;
console.log(`${q}: ${(data.organic_results||[]).length} results ($${spent.toFixed(3)}/$${limit})`);
}
for (const q of ['test 1', 'test 2', 'test 3']) await budgetSearch(q);Salida esperada
JSON
Registered: research-agent (budget: $0.5/day)
Registered: seo-agent (budget: $1.0/day)
Registered: lead-agent (budget: $0.25/day)
--- research-agent ---
"best python framework 2026" -> 10 results
"fastapi vs django" -> 10 results
=== Budget Status ===
research-agent | $0.015/$0.50 (3%) |
seo-agent | $0.020/$1.00 (2%) |
lead-agent | $0.010/$0.25 (4%) |
=== Agent Spending Report ===
Total spent: $0.045 / $1.75 budget
Total calls: 9
Monthly projection: $1.35