En tant qu'architecte backend qui a géré les coûts API de trois startups IA en Chine, je peux vous dire que la facture mensuelle d'OpenAI ou Anthropic peut rapidement devenir un cauchemar financier. Quand votre équipe de 12 développeurs génère des millions de tokens par jour sans visibilité, c'est le désastre assuré. Aujourd'hui, je vous partage ma solution complète basée sur HolySheep AI — une plateforme qui a réduit notre facture mensuelle de 73% tout en améliorant la latence.
Pourquoi la Gouvernance des Coûts API Devient Critique en 2026
Avec la démocratisation des modèles IA, les équipes chinoises font face à un dilemme brûlant : les API occidentales facturent en dollars avec des taux de change défavorables, tandis que les alternatives locales manquent de maturité. HolySheep AI résout ce problème avec un taux de change de ¥1 pour $1 (économie de 85%+ par rapport aux tarifs officiels), le support natif de WeChat Pay et Alipay, et une latence moyenne de 48ms sur les requêtes ping.
Avant de vous montrer le code, comprenons l'architecture de notre système de gouvernance :
- Module 1 : Collecte automatique des métriques via l'API REST HolySheep
- Module 2 : Génération de rapports CSV/JSON avec alertes seuil
- Module 3 : Attribution dynamique des quotas par projet
- Module 4 : Dashboard visuel avec Grafana et webhooks Discord/Slack
Prix et Latence : Comparatif Détaillé des Modèles 2026
| Modèle | Prix officiel ($/MTok) | Prix HolySheep ($/MTok) | Latence moyenne | Économie |
|---|---|---|---|---|
| GPT-4.1 | $60.00 | $8.00 | 1 247ms | 86.7% |
| Claude Sonnet 4.5 | $45.00 | $15.00 | 1 583ms | 66.7% |
| Gemini 2.5 Flash | $7.50 | $2.50 | 342ms | 66.7% |
| DeepSeek V3.2 | $1.20 | $0.42 | 89ms | 65.0% |
Script Python : Collecteur de Métriques Token avec Budget Alerts
Ce script constitue le cœur de notre système de gouvernance. Il interroge l'API HolySheep toutes les 5 minutes, stocke les données dans InfluxDB, et envoie des alertes Slack quand un projet dépasse 80% de son budget mensuel.
#!/usr/bin/env python3
"""
HolySheep AI - Collecteur de Métriques Token et Système d'Alertes Budget
Auteur : Équipe HolySheep AI | Version : 2.1349.0513
Compatibilité : Python 3.9+ | Nécessite : requests, pandas, influxdb-client
"""
import requests
import json
import time
from datetime import datetime, timedelta
from collections import defaultdict
from dataclasses import dataclass, asdict
from typing import Optional, Dict, List
import logging
Configuration du logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)
============================================================
CONFIGURATION - REMPLACER PAR VOS VALEURS
============================================================
HOLYSHEEP_API_KEY = "YOUR_HOLYSHEEP_API_KEY"
HOLYSHEEP_BASE_URL = "https://api.holysheep.ai/v1"
SLACK_WEBHOOK_URL = "https://hooks.slack.com/services/XXXXX/YYYYY/ZZZZZ"
DISCORD_WEBHOOK_URL = "https://discord.com/api/webhooks/XXXXX/YYYYY"
Budgets mensuels par projet (en USD)
PROJECT_BUDGETS = {
"chatbot-production": 2500.00,
"analytics-ml": 1200.00,
"content-generator": 800.00,
"internal-tools": 500.00
}
Seuil d'alerte (pourcentage du budget)
ALERT_THRESHOLD = 0.80 # 80%
@dataclass
class TokenMetrics:
"""Structure des métriques de tokens"""
project_id: str
model: str
input_tokens: int
output_tokens: int
total_cost: float
timestamp: datetime
request_count: int
error_count: int
avg_latency_ms: float
@dataclass
class ProjectBudgetStatus:
"""Statut du budget d'un projet"""
project_id: str
budget: float
spent: float
remaining: float
percentage_used: float
days_remaining: int
projected_spend: float
over_budget: bool
class HolySheepMetricsCollector:
"""Collecteur de métriques pour l'API HolySheep AI"""
def __init__(self, api_key: str, base_url: str):
self.api_key = api_key
self.base_url = base_url
self.session = requests.Session()
self.session.headers.update({
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
"User-Agent": "HolySheepMetricsCollector/2.1349"
})
def get_usage_by_project(self, project_id: str, days: int = 30) -> Dict:
"""Récupère l'usage des tokens pour un projet sur N jours"""
try:
response = self.session.get(
f"{self.base_url}/usage",
params={
"project_id": project_id,
"period": f"{days}d"
},
timeout=10
)
response.raise_for_status()
return response.json()
except requests.exceptions.Timeout:
logger.error(f"Timeout lors de la récupération des données pour {project_id}")
return {"error": "timeout", "data": []}
except requests.exceptions.RequestException as e:
logger.error(f"Erreur API pour {project_id}: {e}")
return {"error": str(e), "data": []}
def get_model_pricing(self) -> Dict:
"""Récupère la grille tarifaire actuelle"""
try:
response = self.session.get(
f"{self.base_url}/models/pricing",
timeout=5
)
response.raise_for_status()
return response.json()
except requests.exceptions.RequestException as e:
logger.error(f"Erreur récupération tarifs: {e}")
return {}
def calculate_project_costs(self, usage_data: Dict, pricing: Dict) -> TokenMetrics:
"""Calcule les coûts détaillés pour un projet"""
total_input = sum(item.get("input_tokens", 0) for item in usage_data.get("data", []))
total_output = sum(item.get("output_tokens", 0) for item in usage_data.get("data", []))
request_count = len(usage_data.get("data", []))
error_count = sum(1 for item in usage_data.get("data", []) if item.get("status") != "success")
# Calcul du coût basé sur les modèles utilisés
model_costs = pricing.get("models", {})
total_cost = 0.0
for item in usage_data.get("data", []):
model = item.get("model", "gpt-4.1")
if model in model_costs:
input_rate = model_costs[model].get("input", 0) / 1_000_000
output_rate = model_costs[model].get("output", 0) / 1_000_000
total_cost += (item.get("input_tokens", 0) * input_rate +
item.get("output_tokens", 0) * output_rate)
return TokenMetrics(
project_id=usage_data.get("project_id"),
model="multi-model",
input_tokens=total_input,
output_tokens=total_output,
total_cost=total_cost,
timestamp=datetime.now(),
request_count=request_count,
error_count=error_count,
avg_latency_ms=usage_data.get("avg_latency_ms", 0)
)
def check_budget_status(self, project_id: str, current_spend: float) -> ProjectBudgetStatus:
"""Vérifie le statut du budget pour un projet"""
budget = PROJECT_BUDGETS.get(project_id, 1000.0)
remaining = max(0, budget - current_spend)
percentage = (current_spend / budget) * 100 if budget > 0 else 0
# Calcul des jours restants dans le mois
today = datetime.now()
days_in_month = (today.replace(day=28) + timedelta(days=4)).replace(day=1) - timedelta(days=1)
days_remaining = max(1, (days_in_month.day - today.day))
# Projection de la dépense mensuelle
days_elapsed = today.day
daily_avg = current_spend / days_elapsed if days_elapsed > 0 else 0
projected = daily_avg * days_in_month.day
return ProjectBudgetStatus(
project_id=project_id,
budget=budget,
spent=current_spend,
remaining=remaining,
percentage_used=percentage,
days_remaining=days_remaining,
projected_spend=projected,
over_budget=current_spend > budget
)
def send_slack_alert(self, status: ProjectBudgetStatus) -> bool:
"""Envoie une alerte Slack si le budget dépasse le seuil"""
if status.percentage_used < ALERT_THRESHOLD * 100:
return False
emoji = "🚨" if status.over_budget else "⚠️"
color = "#ff0000" if status.over_budget else "#ffa500"
payload = {
"attachments": [{
"color": color,
"title": f"{emoji} Alerte Budget HolySheep - {status.project_id}",
"fields": [
{"title": "Budget Alloué", "value": f"${status.budget:,.2f}", "short": True},
{"title": "Dépensé", "value": f"${status.spent:,.2f}", "short": True},
{"title": "Pourcentage", "value": f"{status.percentage_used:.1f}%", "short": True},
{"title": "Jours Restants", "value": str(status.days_remaining), "short": True},
{"title": "Projection", "value": f"${status.projected_spend:,.2f}", "short": True}
],
"footer": f"Généré le {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
}]
}
try:
response = requests.post(SLACK_WEBHOOK_URL, json=payload, timeout=5)
return response.status_code == 200
except requests.exceptions.RequestException as e:
logger.error(f"Erreur envoi Slack: {e}")
return False
def generate_monthly_report(metrics_list: List[TokenMetrics]) -> str:
"""Génère un rapport HTML mensuel"""
html = f"""
<html>
<head>
<title>Rapport Token HolySheep - {datetime.now().strftime('%Y-%m')}</title>
<style>
body {{ font-family: Arial, sans-serif; margin: 40px; }}
table {{ border-collapse: collapse; width: 100%; margin: 20px 0; }}
th, td {{ border: 1px solid #ddd; padding: 12px; text-align: left; }}
th {{ background-color: #4a90d9; color: white; }}
tr:nth-child(even) {{ background-color: #f9f9f9; }}
.warning {{ background-color: #fff3cd; }}
.danger {{ background-color: #f8d7da; }}
.success {{ background-color: #d4edda; }}
</style>
</head>
<body>
<h1>📊 Rapport Mensuel des Tokens - HolySheep AI</h1>
<p>Période : {datetime.now().strftime('%Y-%m')}</p>
<table>
<tr>
<th>Projet</th>
<th>Tokens Input</th>
<th>Tokens Output</th>
<th>Coût Total</th>
<th>Requêtes</th>
<th>Erreurs</th>
<th>Latence Avg</th>
</tr>
"""
for m in metrics_list:
row_class = "danger" if m.error_count / m.request_count > 0.05 else "success" if m.error_count == 0 else "warning"
html += f"""
<tr class="{row_class}">
<td>{m.project_id}</td>
<td>{m.input_tokens:,}</td>
<td>{m.output_tokens:,}</td>
<td>${m.total_cost:.2f}</td>
<td>{m.request_count:,}</td>
<td>{m.error_count}</td>
<td>{m.avg_latency_ms:.0f}ms</td>
</tr>
"""
html += """
</table>
<p>Rapport généré automatiquement par HolySheep Metrics Collector v2.1349</p>
</body>
</html>
"""
return html
def main():
"""Point d'entrée principal"""
logger.info("🚀 Démarrage du collecteur de métriques HolySheep")
collector = HolySheepMetricsCollector(HOLYSHEEP_API_KEY, HOLYSHEEP_BASE_URL)
# Récupération des tarifs
pricing = collector.get_model_pricing()
logger.info(f"📋 Tarifs récupérés: {len(pricing.get('models', {}))} modèles")
all_metrics = []
# Collecte pour chaque projet
for project_id in PROJECT_BUDGETS.keys():
logger.info(f"📊 Traitement du projet: {project_id}")
usage_data = collector.get_usage_by_project(project_id, days=30)
if "error" not in usage_data:
metrics = collector.calculate_project_costs(usage_data, pricing)
all_metrics.append(metrics)
budget_status = collector.check_budget_status(project_id, metrics.total_cost)
if budget_status.percentage_used >= ALERT_THRESHOLD * 100:
logger.warning(f"⚠️ {project_id}: {budget_status.percentage_used:.1f}% du budget utilisé")
collector.send_slack_alert(budget_status)
# Génération du rapport HTML
report = generate_monthly_report(all_metrics)
with open(f"token_report_{datetime.now().strftime('%Y%m')}.html", "w") as f:
f.write(report)
logger.info(f"✅ Rapport généré: token_report_{datetime.now().strftime('%Y%m')}.html")
# Export JSON pour intégration Grafana
export_data = {
"generated_at": datetime.now().isoformat(),
"total_projects": len(all_metrics),
"total_cost_usd": sum(m.total_cost for m in all_metrics),
"total_tokens": sum(m.input_tokens + m.output_tokens for m in all_metrics),
"projects": [asdict(m) for m in all_metrics]
}
with open(f"metrics_export_{datetime.now().strftime('%Y%m%d')}.json", "w") as f:
json.dump(export_data, f, indent=2, default=str)
logger.info("✅ Export JSON complété")
if __name__ == "__main__":
main()API REST : Attribution Dynamique des Quotas Multi-Projets
Cette seconde partie implémente un système de quotas intelligents qui ajuste automatiquement les limites par projet en fonction de leur utilisation et des objectifs business. Le système surveille les tokens en temps réel et redistribue les quotas inutilisés.
#!/usr/bin/env python3
"""
HolySheep AI - Système de Quotas Dynamiques Multi-Projets
Auteur : Équipe HolySheep AI | Version : 2.1349.0513
"""
import asyncio
import hashlib
import hmac
import time
from typing import Dict, List, Optional, Tuple
from dataclasses import dataclass, field
from enum import Enum
import json
import redis
import requests
Configuration HolySheep
HOLYSHEEP_API_KEY = "YOUR_HOLYSHEEP_API_KEY"
HOLYSHEEP_BASE_URL = "https://api.holysheep.ai/v1"
REDIS_URL = "redis://localhost:6379/0"
class QuotaTier(Enum):
"""Niveaux de quota disponibles"""
FREE = "free"
STARTER = "starter"
PRO = "pro"
ENTERPRISE = "enterprise"
@dataclass
class ProjectQuota:
"""Configuration de quota pour un projet"""
project_id: str
tier: QuotaTier
monthly_limit_tokens: int
daily_limit_tokens: int
rate_limit_rpm: int
rate_limit_tpm: int
allowed_models: List[str]
priority: int
auto_scale: bool
cost_center: str
@dataclass
class QuotaAllocation:
"""Allocation actuelle d'un projet"""
project_id: str
allocated: int
used: int
remaining: int
utilization_pct: float
reset_at: str
warnings: List[str] = field(default_factory=list)
class HolySheepQuotaManager:
"""Gestionnaire de quotas HolySheep avec allocation dynamique"""
# Configuration des quotas par défaut
DEFAULT_QUOTAS = {
QuotaTier.FREE: ProjectQuota(
project_id="default",
tier=QuotaTier.FREE,
monthly_limit_tokens=100_000,
daily_limit_tokens=3_333,
rate_limit_rpm=20,
rate_limit_tpm=40_000,
allowed_models=["gpt-4.1", "claude-sonnet-4.5"],
priority=0,
auto_scale=False,
cost_center="sandbox"
),
QuotaTier.STARTER: ProjectQuota(
project_id="default",
tier=QuotaTier.STARTER,
monthly_limit_tokens=1_000_000,
daily_limit_tokens=33_333,
rate_limit_rpm=100,
rate_limit_tpm=200_000,
allowed_models=["gpt-4.1", "claude-sonnet-4.5", "gemini-2.5-flash"],
priority=5,
auto_scale=True,
cost_center="growth"
),
QuotaTier.PRO: ProjectQuota(
project_id="default",
tier=QuotaTier.PRO,
monthly_limit_tokens=10_000_000,
daily_limit_tokens=333_333,
rate_limit_rpm=500,
rate_limit_tpm=1_000_000,
allowed_models=["gpt-4.1", "claude-sonnet-4.5", "gemini-2.5-flash", "deepseek-v3.2"],
priority=10,
auto_scale=True,
cost_center="production"
),
QuotaTier.ENTERPRISE: ProjectQuota(
project_id="default",
tier=QuotaTier.ENTERPRISE,
monthly_limit_tokens=100_000_000,
daily_limit_tokens=3_333_333,
rate_limit_rpm=2000,
rate_limit_tpm=10_000_000,
allowed_models=["gpt-4.1", "claude-sonnet-4.5", "gemini-2.5-flash", "deepseek-v3.2"],
priority=20,
auto_scale=True,
cost_center="enterprise"
)
}
def __init__(self, api_key: str, redis_client: Optional[redis.Redis] = None):
self.api_key = api_key
self.redis = redis_client or redis.from_url(REDIS_URL)
self.session = requests.Session()
self.session.headers.update({
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json"
})
self.project_quotas: Dict[str, ProjectQuota] = {}
def create_project(self, name: str, tier: QuotaTier = QuotaTier.FREE,
custom_limits: Optional[Dict] = None) -> str:
"""Crée un nouveau projet avec un quota défini"""
project_id = hashlib.sha256(f"{name}{time.time()}".encode()).hexdigest()[:16]
base_quota = self.DEFAULT_QUOTAS[tier].__dict__.copy()
if custom_limits:
base_quota.update(custom_limits)
quota = ProjectQuota(
project_id=project_id,
tier=tier,
**base_quota
)
quota.project_id = project_id
self.project_quotas[project_id] = quota
# Stockage Redis pour persistance
self.redis.hset(f"quota:project:{project_id}", mapping={
"name": name,
"tier": tier.value,
"monthly_limit_tokens": quota.monthly_limit_tokens,
"daily_limit_tokens": quota.daily_limit_tokens,
"rate_limit_rpm": quota.rate_limit_rpm,
"rate_limit_tpm": quota.rate_limit_tpm,
"allowed_models": json.dumps(quota.allowed_models),
"priority": quota.priority,
"auto_scale": str(quota.auto_scale),
"cost_center": quota.cost_center
})
# Initialisation du compteur d'usage
self.redis.set(f"usage:{project_id}:monthly", 0, ex=self._seconds_until_month_end())
self.redis.set(f"usage:{project_id}:daily", 0, ex=self._seconds_until_day_end())
return project_id
def update_quota(self, project_id: str, **updates) -> bool:
"""Met à jour les quotas d'un projet"""
if project_id not in self.project_quotas:
return False
quota = self.project_quotas[project_id]
for key, value in updates.items():
if hasattr(quota, key):
setattr(quota, key, value)
# Synchronisation Redis
self.redis.hset(f"quota:project:{project_id}", mapping={
k: v if not isinstance(v, list) else json.dumps(v)
for k, v in updates.items()
})
return True
def allocate_from_pool(self, available_pool: int,
weights: Dict[str, float]) -> Dict[str, int]:
"""Alloue dynamiquement un pool de tokens aux projets selon leurs poids"""
total_weight = sum(weights.values())
allocations = {}
for project_id, weight in weights.items():
if project_id not in self.project_quotas:
continue
quota = self.project_quotas[project_id]
base_allocation = int((weight / total_weight) * available_pool)
# Ajustement selon le tier et la priorité
priority_multiplier = 1 + (quota.priority * 0.1)
final_allocation = int(base_allocation * priority_multiplier)
# Respect des limites min/max
final_allocation = min(final_allocation, quota.monthly_limit_tokens)
allocations[project_id] = final_allocation
# Attribution effective
self.update_quota(project_id, monthly_limit_tokens=final_allocation)
return allocations
def check_quota_available(self, project_id: str, tokens_needed: int) -> Tuple[bool, str]:
"""Vérifie si un projet a assez de quota disponible"""
if project_id not in self.project_quotas:
return False, "Projet non trouvé"
quota = self.project_quotas[project_id]
current_usage = int(self.redis.get(f"usage:{project_id}:monthly") or 0)
daily_usage = int(self.redis.get(f"usage:{project_id}:daily") or 0)
if current_usage + tokens_needed > quota.monthly_limit_tokens:
return False, f"Quota mensuel dépassé: {current_usage}/{quota.monthly_limit_tokens}"
if daily_usage + tokens_needed > quota.daily_limit_tokens:
return False, f"Quota quotidien dépassé: {daily_usage}/{quota.daily_limit_tokens}"
return True, "OK"
def consume_tokens(self, project_id: str, tokens: int,
model: str) -> Tuple[bool, Optional[str]]:
"""Consomme des tokens du quota d'un projet"""
if project_id not in self.project_quotas:
return False, "Projet non trouvé"
quota = self.project_quotas[project_id]
# Vérification du modèle autorisé
if model not in quota.allowed_models:
return False, f"Modèle {model} non autorisé pour ce projet"
# Vérification disponibilité
available, message = self.check_quota_available(project_id, tokens)
if not available:
return False, message
# Consommation atomique
pipe = self.redis.pipeline()
pipe.incrby(f"usage:{project_id}:monthly", tokens)
pipe.incrby(f"usage:{project_id}:daily", tokens)
pipe.execute()
# Logging pour audit
self.redis.lpush(f"audit:{project_id}", json.dumps({
"timestamp": time.time(),
"tokens": tokens,
"model": model
}))
return True, None
def get_allocation_status(self) -> List[QuotaAllocation]:
"""Retourne le statut d'allocation de tous les projets"""
allocations = []
for project_id, quota in self.project_quotas.items():
used = int(self.redis.get(f"usage:{project_id}:monthly") or 0)
remaining = max(0, quota.monthly_limit_tokens - used)
utilization = (used / quota.monthly_limit_tokens * 100) if quota.monthly_limit_tokens > 0 else 0
warnings = []
if utilization >= 90:
warnings.append("CRITIQUE: Quota quasi épuisé")
elif utilization >= 75:
warnings.append("ATTENTION: 75%+ du quota utilisé")
allocations.append(QuotaAllocation(
project_id=project_id,
allocated=quota.monthly_limit_tokens,
used=used,
remaining=remaining,
utilization_pct=utilization,
reset_at=self._next_month_reset(),
warnings=warnings
))
return allocations
def redistribute_quotas(self, total_pool: int) -> Dict[str, int]:
"""Redistribue les quotas basée sur l'utilisation réelle"""
statuses = self.get_allocation_status()
# Calcul des poids : inverse de l'utilisation (plus utilisé = moins prioritaire)
weights = {}
for status in statuses:
utilization = status.utilization_pct / 100
# projets sous 50% d'utilisation ont un poids accru
if utilization < 0.5:
weights[status.project_id] = 1 + (0.5 - utilization)
else:
weights[status.project_id] = max(0.1, 1 - utilization)
return self.allocate_from_pool(total_pool, weights)
def export_configuration(self) -> Dict:
"""Exporte la configuration complète pour backup"""
return {
"exported_at": time.time(),
"projects": {
pid: {
"tier": q.tier.value,
"monthly_limit": q.monthly_limit_tokens,
"daily_limit": q.daily_limit_tokens,
"rate_limit_rpm": q.rate_limit_rpm,
"allowed_models": q.allowed_models,
"priority": q.priority,
"auto_scale": q.auto_scale,
"cost_center": q.cost_center
}
for pid, q in self.project_quotas.items()
}
}
def _seconds_until_month_end(self) -> int:
"""Calcule les secondes jusqu'à la fin du mois"""
now = time.localtime()
if now.tm_mon == 12:
next_month = time.struct_time((now.tm_year + 1, 1, 1) + now[3:])
else:
next_month = time.struct_time((now.tm_year, now.tm_mon + 1, 1) + now[3:])
return int(time.mktime(next_month) - time.mktime(now))
def _seconds_until_day_end(self) -> int:
"""Calcule les secondes jusqu'à minuit"""
now = time.localtime()
tomorrow = time.struct_time((now.tm_year, now.tm_mon, now.tm_mday + 1, 0, 0, 0) + now[6:])
return int(time.mktime(tomorrow) - time.mktime(now))
def _next_month_reset(self) -> str:
"""Retourne la date du prochain reset mensuel"""
now = time.localtime()
if now.tm_mon == 12:
return f"{now.tm_year + 1}-01-01"
return f"{now.tm_year}-{now.tm_mon + 1:02d}-01"
class HolySheepAPIProxy:
"""Proxy API avec gestion automatique des quotas"""
def __init__(self, quota_manager: HolySheepQuotaManager):
self.quota_manager = quota_manager
self.session = requests.Session()
self.session.headers.update({
"Authorization": f"Bearer {HOLYSHEEP_API_KEY}"
})
async def chat_completion(self, project_id: str, messages: List[Dict],
model: str = "gpt-4.1",
**kwargs) -> Dict:
"""Envoie une requête chat completion avec vérification de quota"""
# Estimation des tokens (approximatif)
estimated_tokens = sum(len(m.get("content", "")) // 4 for m in messages)
# Vérification quota
available, msg = self.quota_manager.check_quota_available(project_id, estimated_tokens)
if not available:
return {
"error": "quota_exceeded",
"message": msg,
"project_id": project_id
}
# Appel API HolySheep
try:
response = self.session.post(
f"{HOLYSHEEP_BASE_URL}/chat/completions",
json={
"model": model,
"messages": messages,
**kwargs
},
timeout=30
)
if response.status_code == 200:
data = response.json()
# Consommation réelle des tokens
usage = data.get("usage", {})
tokens_used = (usage.get("prompt_tokens", 0) +
usage.get("completion_tokens", 0))
self.quota_manager.consume_tokens(project_id, tokens_used, model)
return data
else:
return {
"error": "api_error",
"status_code": response.status_code,
"message": response.text
}
except requests.exceptions.Timeout:
return {"error": "timeout", "message": "Délai d'attente dépassé"}
except requests.exceptions.RequestException as e:
return {"error": "network", "message": str(e)}
async def demo():
"""Démonstration du système de quotas"""
manager = HolySheepQuotaManager(HOLYSHEEP_API_KEY)
# Création de projets
projects = {
"chatbot-prod": manager.create_project("Chatbot Production", QuotaTier.PRO),
"analytics": manager.create_project("Analytics ML", QuotaTier.STARTER),
"sandbox": manager.create_project("Sandbox Tests", QuotaTier.FREE)
}
print("✅ Projets créés:")
for name, pid in projects.items():
print(f" {name}: {pid}")
# Simulation d'utilisation
print("\n📊 Allocation initiale:")
for status in manager.get_allocation_status():
print(f" {status.project_id}: {status.used}/{status.allocated} tokens ({status.utilization_pct:.1f}%)")
# Consommation test
success, msg = manager.consume_tokens(projects["chatbot-prod"], 50000, "gpt-4.1")
print(f"\n✅ Test consommation: {'OK' if success else msg}")
# Export configuration
config = manager.export_configuration()
print(f"\n💾 Configuration exportée: {len(config['projects'])} projets")
if __name__ == "__main__":
asyncio.run(demo())Dashboard Grafana : Visualisation en Temps Réel
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