A free model quota is a budget, not a gift. You should treat it like one if you plan to build anything on top of it. I learned this the hard way when my prototype stopped responding in the middle of a demo. I had silently burned through the monthly allowance, and the provider cut me off without warning. This article shows how I built a small token budget alarm on a free server. It watches a free model's usage and warns me before the quota runs out.
Most developers track their cloud spend religiously but ignore the token consumption of free models. The free tier feels like a gift, so we assume it will last forever. Then the provider cuts us off at the worst moment, and we scramble to find the cause. A token budget alarm removes that uncertainty by measuring your actual burn rate. It projects the exhaustion date and alerts you before you hit the wall.
The design is deliberately small: a reverse proxy sits in front of the model endpoint. It records the token usage from every response and stores it in a local database. A background thread then computes the average consumption over a sliding window. It compares that rate against the remaining allowance and fires a webhook when the projection looks dangerous. You can run this entire stack on a free server, which is exactly what I did with MonkeyCode's free server option. Disclosure: This article was prepared as part of MonkeyCode's product outreach.
The proxy itself is a tiny Flask application that forwards requests to the model. It extracts the usage field from each response and records the token count. If your provider does not return a usage object, you can estimate the token count with a simple heuristic. Dividing the character count by four is a rough but workable approximation. The important part is that every request is accounted for, because a single long prompt can consume more than a hundred small ones.
from flask import Flask, request, Response
import requests
import sqlite3
import time
app = Flask(__name__)
def init_db():
conn = sqlite3.connect('usage.db')
conn.execute('CREATE TABLE IF NOT EXISTS usage (ts INTEGER, tokens INTEGER)')
conn.commit()
conn.close()
def record(tokens):
conn = sqlite3.connect('usage.db')
conn.execute('INSERT INTO usage VALUES (?, ?)', (int(time.time()), tokens))
conn.commit()
conn.close()
@app.route('/chat', methods=['POST'])
def chat():
resp = requests.post(
'https://your-model-endpoint/chat',
json=request.json,
stream=True
)
data = resp.json()
tokens = data.get('usage', {}).get('total_tokens', 0)
record(tokens)
return Response(resp.content, status=resp.status_code,
content_type='application/json')
init_db()
The background thread runs every minute and queries the database for the last hour of usage. It calculates the average tokens per minute and multiplies by the minutes remaining in the billing cycle. The result is a projection of when you will exhaust the allowance. If that projection falls within the next 24 hours, the thread sends a webhook to a URL you configure. The code below shows the core logic, with the allowance stored as a constant.
import threading
import sqlite3
import time
import requests
def check_budget():
while True:
conn = sqlite3.connect('usage.db')
cutoff = int(time.time()) - 3600
rows = conn.execute(
'SELECT SUM(tokens) FROM usage WHERE ts > ?', (cutoff,)
).fetchone()
conn.close()
tokens_last_hour = rows[0] or 0
rate_per_min = tokens_last_hour / 60.0
remaining = 10_000_000 # replace with your actual allowance
minutes_left = remaining / rate_per_min if rate_per_min > 0 else 9999
if minutes_left < 24 * 60:
requests.post('https://your-webhook-url', json={
'message': 'Token budget will expire soon',
'minutes_left': round(minutes_left)
})
time.sleep(60)
threading.Thread(target=check_budget, daemon=True).start()
Note that the 10 million token figure is the allowance I used for my test. You must check the current published terms for your provider, because free tiers change frequently. The code above reads the allowance from a constant, so you can easily replace it with a configuration value. I used MonkeyCode's free model endpoint as the upstream for this proxy, and the combination worked well for a low-traffic monitoring setup.
The whole setup runs happily on a free server because the proxy is lightweight and the database is a single SQLite file. I deployed this on MonkeyCode's free server option, and it handled the traffic without any issues. The only requirement is that the server has Python and the flask and requests packages installed. That is a standard setup for any free tier, so you should not have trouble replicating it.
There are a few limitations you should know before copying this design. First, if your provider does not return token usage in the response, you will need to rely on an estimate. That estimate can be off by a significant margin, especially with non-English text or code. Second, the alarm only checks every minute, so a sudden burst of traffic can still push you over the limit before the webhook fires. Third, the free server itself may have its own resource limits, and a very high request rate could exhaust its memory or CPU.
Who should not use this approach? Teams that need precise token accounting for billing or compliance should use the provider's own usage dashboard instead of a proxy. If you are already using a gateway like Kong or Envoy, you should probably add usage tracking there rather than introducing another component. And if your traffic is large enough to require horizontal scaling, a single free server will not be enough.
The lesson here is that free resources are still finite, and a small amount of monitoring can save you from a very awkward demo. A token budget alarm is a cheap insurance policy that you can deploy in an afternoon on a free server. If you want to try it yourself, grab a free model endpoint and a free server, and start recording your usage today.
Top comments (0)