# Example: Dynamic billing based on actual usage
def calculate_user_charge(api_response):
    actual_cost = api_response['cost']['total_cost']
    markup_rate = 1.5  # 50% profit margin
    user_charge = actual_cost * markup_rate
    return user_charge

import requests
import json
from datetime import datetime

class OneRouterBilling:
    def __init__(self, api_key):
        self.api_key = api_key
        self.base_url = "https://llm.onerouter.pro"
  
    def make_request_with_billing(self, prompt, user_id):
        response = requests.post(
            f"{self.base_url}/chat/completions",
            headers={"Authorization": f"Bearer {self.api_key}"},
            json={"messages": [{"role": "user", "content": prompt}]}
        )
      
        result = response.json()
      
        # Record user usage
        self.record_usage(user_id, result['cost'])
      
        return result
  
    def record_usage(self, user_id, cost_data):
        # Record cost data to user billing system
        billing_record = {
            "user_id": user_id,
            "timestamp": datetime.now(),
            "cost": cost_data['total_cost'],
            "details": cost_data
        }
        # Store to database...
      
    def generate_user_invoice(self, user_id, period):
        # Generate detailed invoice with usage breakdown
        usage_records = self.get_usage_records(user_id, period)
        total_cost = sum([record['cost'] for record in usage_records])
      
        return {
            "user_id": user_id,
            "period": period,
            "total_requests": len(usage_records),
            "total_tokens": sum([record['details']['total_tokens'] for record in usage_records]),
            "total_cost": total_cost,
            "detailed_breakdown": usage_records
        }

class MultiTenantBilling:
    def __init__(self, onerouter_client):
        self.client = onerouter_client
      
    def process_tenant_request(self, tenant_id, user_id, request):
        # Make OneRouter request
        response = self.client.make_request_with_billing(request, user_id)
      
        # Apply tenant-specific markup
        tenant_config = self.get_tenant_config(tenant_id)
        markup_rate = tenant_config['markup_rate']
      
        final_cost = response['cost']['total_cost'] * markup_rate
      
        # Bill both tenant and end user
        self.bill_tenant(tenant_id, response['cost']['total_cost'])
        self.bill_end_user(user_id, final_cost)
      
        return response

import numpy as np
from sklearn.linear_model import LinearRegression

class CostPredictor:
    def __init__(self):
        self.model = LinearRegression()
      
    def train_on_usage_history(self, usage_history):
        # Extract features: time of day, request complexity, user type
        features = []
        costs = []
      
        for record in usage_history:
            feature_vector = [
                record['hour'],
                record['prompt_length'],
                record['user_tier'],
                record['complexity_score']
            ]
            features.append(feature_vector)
            costs.append(record['cost'])
          
        self.model.fit(features, costs)
  
    def predict_request_cost(self, request_features):
        predicted_cost = self.model.predict([request_features])[0]
        return {
            'predicted_cost': predicted_cost,
            'confidence': self.calculate_confidence(request_features)
        }