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Overview

“How much does our summarization feature cost?” “Which users are the most expensive?” These questions are hard to answer when all your LLM calls look the same in billing. This cookbook shows how to tag requests with metadata so you can break down costs by feature, user, team, or any dimension you care about.

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Tag requests with metadata

Add metadata and customer_identifier to every LLM call: 
from openai import OpenAI

client = OpenAI(
    base_url="https://api.respan.ai/api/",
    api_key="YOUR_RESPAN_API_KEY",
)

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Summarize this document..."}],
    extra_body={
        "customer_identifier": "user_456",
        "metadata": {
            "feature": "summarization",
            "team": "content",
            "environment": "production",
        },
    },
)
Be consistent across your codebase. Here’s a practical schema:
KeyPurposeExamples
featureWhich product feature made the call"summarization", "chat", "search"
teamWhich team owns this feature"content", "support", "product"
environmentDeployment environment"production", "staging"
versionFeature or prompt version"v2", "2024-01"

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Create a helper function

Centralize your metadata tagging so it’s consistent: 
from openai import OpenAI

client = OpenAI(
    base_url="https://api.respan.ai/api/",
    api_key="YOUR_RESPAN_API_KEY",
)

def llm_call(messages, model="gpt-4o-mini", feature="unknown", customer_id=None, **kwargs):
    """Wrapper that ensures every call is tagged."""
    extra_body = {
        "metadata": {
            "feature": feature,
            "environment": "production",
        },
    }
    if customer_id:
        extra_body["customer_identifier"] = customer_id

    return client.chat.completions.create(
        model=model,
        messages=messages,
        extra_body=extra_body,
        **kwargs,
    )

# Usage
response = llm_call(
    messages=[{"role": "user", "content": "Summarize..."}],
    feature="summarization",
    customer_id="user_456",
)

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Analyze costs on the dashboard

Once your requests are tagged, go to the Dashboard:
  1. Cost by feature: Filter by metadata.feature to see cost per feature over time
  2. Cost by user: Go to Users to see total cost per customer
  3. Cost by model: Use model breakdown to see which models drive the most spend
  4. Custom views: Create saved views with preset filters for recurring cost analysis

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Set user budgets

For per-user cost control, set budgets on individual customers: 
import requests

requests.post(
    "https://api.respan.ai/api/users/create/",
    headers={"Authorization": "Bearer YOUR_RESPAN_API_KEY"},
    json={
        "customer_identifier": "user_456",
        "period_budget": 10.00,        # $10 per period
        "budget_duration": "monthly",   # Reset monthly
    },
)
When a user exceeds their budget, Respan blocks further requests and returns a 429 status. See User budgets for details.

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Next steps

Customer identifier

Track users, set budgets and rate limits

Dashboard

Monitor metrics and trends