Overview - TraceRoot

Once you have initialized TraceRoot, LLM calls are traced automatically. To go further — tracing custom functions, identifying users, grouping sessions, or tracking cost — you can use observe and attach rich context to every trace.

Quickstart

Here’s everything you can attach in one place:

Python
TypeScript

import traceroot
from traceroot import Integration, observe, using_attributes
from openai import OpenAI

traceroot.initialize(integrations=[Integration.OPENAI])

client = OpenAI()

@observe(name="run_agent", type="agent", metadata={"version": "v2"})
def run_agent(query: str) -> str:
    response = client.chat.completions.create(...)  # tokens + cost tracked automatically
    return response.choices[0].message.content

with using_attributes(user_id="user-42", session_id="chat-abc", tags=["production"]):
    run_agent("What's the weather?")
    run_agent("What about tomorrow?")

import OpenAI from 'openai';
import { TraceRoot, observe, usingAttributes } from '@traceroot-ai/traceroot';

TraceRoot.initialize({ instrumentModules: { openAI: OpenAI } });

const client = new OpenAI();

async function runAgent(query: string): Promise<string> {
  return observe({ name: 'run_agent', type: 'agent', metadata: { version: 'v2' } }, async () => {
    const response = await client.chat.completions.create({ ... }); // tokens + cost tracked automatically
    return response.choices[0].message.content ?? '';
  });
}

await usingAttributes(
  { userId: 'user-42', sessionId: 'chat-abc', tags: ['production'] },
  async () => {
    await runAgent("What's the weather?");
    await runAgent('What about tomorrow?');
  },
);

Quick Reference

I want to…	Attribute	Guide
Identify which user triggered a trace	User ID	Users
Group traces from the same conversation	Session ID	Sessions
Label traces for filtering	Tags	Tags
Attach structured key-value context	Metadata	Metadata
Track token usage and LLM cost	auto via instrumentation	Cost Tracking
Link traces back to source code + commit	auto via `observe`	Git Context

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