Scoring with SDK

import { LaminarClient, Laminar, observe } from "@lmnr-ai/lmnr";

const laminarClient = new LaminarClient({
  apiKey: "your-project-api-key"
});

// First, capture your LLM calls
await observe(
  {
    name: "chat_completion",
    input: { messages: [...] },
  },
  () => {
    // Your LLM call here
    return {
      output: { content: "AI response" }
    };
  }
);

// IMPORTANT: Flush data to ensure it reaches the backend
await Laminar.flush();

// Score by trace ID (attaches to root span)
const traceId = Laminar.getTraceId();
if (!traceId) {
  // To avoid this, we must be inside an observed function
  throw new Error("No active trace found");
}

await laminarClient.evaluators.score({
  name: "quality",
  traceId: traceId,
  score: 0.95,
  metadata: { model: "gpt-4" }
});

// Score by span ID 
// IMPORTANT: This code must be run after span is already recorded
// In production, ensure this runs later
await new Promise(resolve => setTimeout(resolve, 1000));

const spanContext = Laminar.getLaminarSpanContext();
if (!spanContext) {
  throw new Error("No active span found");
}

await laminarClient.evaluators.score({
  name: "relevance", 
  spanId: spanContext.spanId,
  score: 0.87
});