Source-driven docs
Introduction
Trackly is a Python usage-tracking layer for LLM apps. It hooks into LangChain callbacks or native Ollama and Gemini SDK calls, then records provider, model, tokens, latency, and your own labels in the background.
INFO
This page is written from the actual repository code, not just the README. A few important details are easy to miss otherwise:
callback() takes no arguments, native Ollama uses theollama package, native Gemini uses google-genai, and the ingest route is /api/v1/events.What Trackly records
Provider + model
Trackly stores the provider name and exact model string so pricing and filtering stay accurate.
Token usage
Prompt, completion, and total tokens are captured when the provider exposes them.
Latency
Each event records the wall-clock duration in milliseconds when available.
Your metadata
Feature, environment, user, session, tags, and extra JSON help you slice usage later.
Provider constants
The SDK exports a tiny helper object if you prefer constants over raw strings.
python
from trackly import providers
print(providers.LANGCHAIN) # "langchain"
print(providers.OLLAMA) # "ollama"
print(providers.GEMINI) # "gemini"