Using Evaluators via the API

curl --request POST \
     --url https://api.orq.ai/v2/evaluators/tone_of_voice \
     --header 'accept: application/json' \
     --header 'authorization: Bearer ORQ_API_KEY' \
     --header 'content-type: application/json' \
     --data '
{
  "query": "Validate the tone of voice if it is professional.",
  "output": "Hello, how are you ??",
  "model": "openai/gpt-4o"
}
'

{
  "value": {
    "value": false,
    "explanation": "The output does not align with a professional tone. The use of 'Hello, how are you ??' is informal and lacks the formality expected in professional communication. The double question marks and casual greeting are more suited to a casual or friendly context rather than a professional one. A professional tone would require a more formal greeting and a clear purpose for the communication."
  }
}

import { evaluatorq, job } from "@orq-ai/evaluatorq";

const textAnalyzer = job("text-analyzer", async (data) => {
  const text = data.inputs.text;
  const analysis = {
    length: text.length,
    wordCount: text.split(" ").length,
    uppercase: text.toUpperCase(),
  };

  return analysis;
});

await evaluatorq("text-analysis", {
  data: [
    { inputs: { text: "Hello world" } },
    { inputs: { text: "Testing evaluation" } },
  ],
  jobs: [textAnalyzer],
  evaluators: [
    {
      name: "length-check",
      scorer: async ({ output }) => {
        const passesCheck = output.length > 10;
        return {
          value: passesCheck ? 1 : 0,
          explanation: passesCheck
            ? "Output length is sufficient"
            : `Output too short (${output.length} chars, need >10)`,
        };
      },
    },
  ],
});