Quickstart: tracepilot-openai

TRACEPILOT_API_KEY=tp_live_xxxxxxxxxxxxxxxx
OPENAI_API_KEY=sk-...

import OpenAI from 'openai';
import { TracePilotOpenAI } from 'tracepilot-openai';

export const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
export const tp = new TracePilotOpenAI(process.env.TRACEPILOT_API_KEY!);

import { openai, tp } from './lib/clients';

async function runAgent(userMessage: string) {
  await tp.startTrace('my-agent');

  const messages = [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: userMessage },
  ];

  const { result, spanId } = await tp.wrapOpenAI(
    () => openai.chat.completions.create({
      model: 'gpt-4o',
      messages,
    }),
    messages,
    undefined, // root span — no parent
    1
  );

  console.log(result.choices[0].message.content);
  // → Open your dashboard. The trace is already there.
}

runAgent('Summarise the latest AI research.');

import { openai, tp } from './lib/clients';

async function runResearchAgent(query: string) {
  await tp.startTrace('research-agent');

  const messages = [{ role: 'user', content: query }];

  // Step 1 — planning
  const { result: plan, spanId: planSpanId } = await tp.wrapOpenAI(
    () => openai.chat.completions.create({ model: 'gpt-4o', messages }),
    messages,
    undefined,
    1
  );

  // Step 2 — web search tool call
  const { result: searchResult, spanId: searchSpanId } = await tp.wrapToolCall(
    'web-search',
    () => webSearch(plan.choices[0].message.content ?? ''),
    planSpanId, // child of the planning span
    2
  );

  // Step 3 — synthesis
  const followUp = [
    ...messages,
    plan.choices[0].message,
    { role: 'tool', content: searchResult.summary },
  ];

  const { result: answer } = await tp.wrapOpenAI(
    () => openai.chat.completions.create({ model: 'gpt-4o', messages: followUp }),
    followUp,
    searchSpanId, // child of the search span
    3
  );

  return answer.choices[0].message.content;
}

// TracePilot records this automatically for every wrapOpenAI call:
{
  spanId: 'span_abc123',
  model: 'gpt-4o',
  messages: [ /* exact input */ ],
  output: { /* full ChatCompletion */ },
  usage: {
    prompt_tokens: 48,
    completion_tokens: 120,
    estimated_cost_usd: 0.0018
  },
  latency_ms: 1240,
  error: null
}
// Fork & Rerun lets you edit `messages` and re-execute from this exact state.