Automatic Tracking | Paygent Documentation

Automatic tracking simplifies your integration by intercepting calls to LLM providers. You don’t have to manually extract token counts or call sendUsage() for each API request.

Scenario: You’re building a chatbot and making dozens of OpenAI API calls. Manually extracting usage data and calling the Paygent tracking API for each one is tedious and error-prone. You just want the tracking to happen automatically.

Solution: Use Paygent’s automatic wrappers or interceptors.

Python

Node.js

Go

Automatic tracking uses monkeypatching to intercept calls to LLM providers. This means you don’t have to change how you call the LLM, other than adding three optional tracking parameters.

Call paygent_sdk.init() once. Then, simply pass tracking IDs directly into your standard model calls.

automatic_tracking.py

1 import paygent_sdk
2 from openai import OpenAI
3 
4 # Initialize once at application start
5 paygent_sdk.init(api_key="your-paygent-api-key")
6 
7 client = OpenAI()
8 
9 # Standard call - usage is tracked automatically!
10 response = client.chat.completions.create(
11     model="gpt-4o",
12     messages=[{"role": "user", "content": "Explain automatic tracking"}],
13     
14     # These parameters are intercepted by Paygent
15     paygent_agent_id="research-agent",
16     paygent_customer_id="user-789",
17     paygent_indicator="explanation-requested"
18 )

Manual vs Automatic

Feature	Manual Tracking	Automatic Tracking
Setup	Client instance setup per call	Initialize once / Wrap client
Token Extraction	Manual code needed	Fully automatic
Error Risk	Can forget to track	Impossible to miss
Maintenance	High	Low
Recommended	For custom use cases	✓ Best for most users