API: Golden answer comparison algo for ASR

$ npm install node-fetch
$ export GOOEY_API_KEY=sk-xxxx

import fetch from 'node-fetch';

const payload = {
  "input_prompt": "You job is to assess AI translations. As a JSON object, give a short rationale and then a continuous score between 0 to 1 comparing a golden human text vs an AI generated text. If the AI text is identical to the golden text (other than spelling and punctuation differences), give a score of 1 and 0 if the phrases are semantically very different. \n\nExamples: \nGolden: In our chili farm there are white flies. What should we do?\nAI_text: We have white spots in the Mirapakaya Pulam. What to do?\nJSON: {\n\"rationale\": \"The ai_answer is missing key elements such as chili farm and white flies.\" ,\n\"score\": \".2\"\n}\n\nGolden: {{ golden }}\nAI_text: {{ai_answer}}\nJSON: \n",
  "selected_models": [
    "gpt_3_5_turbo"
  ]
};

async function gooeyAPI() {
  const response = await fetch("https://api.gooey.ai/v2/CompareLLM?example_id=2cl6c8gn", {
    method: "POST",
    headers: {
      "Authorization": "bearer " + process.env["GOOEY_API_KEY"],
      "Content-Type": "application/json",
    },
    body: JSON.stringify(payload),
  });

  if (!response.ok) {
    throw new Error(response.status);
  }

  const result = await response.json();
  console.log(response.status, result);
}

gooeyAPI();

$ python3 -m pip install requests
$ export GOOEY_API_KEY=sk-xxxx

import os
import requests

payload = {
    "input_prompt": 'You job is to assess AI translations. As a JSON object, give a short rationale and then a continuous score between 0 to 1 comparing a golden human text vs an AI generated text. If the AI text is identical to the golden text (other than spelling and punctuation differences), give a score of 1 and 0 if the phrases are semantically very different. \n\nExamples: \nGolden: In our chili farm there are white flies. What should we do?\nAI_text: We have white spots in the Mirapakaya Pulam. What to do?\nJSON: {\n"rationale": "The ai_answer is missing key elements such as chili farm and white flies." ,\n"score": ".2"\n}\n\nGolden: {{ golden }}\nAI_text: {{ai_answer}}\nJSON: \n',
    "selected_models": ["gpt_3_5_turbo"],
}

response = requests.post(
    "https://api.gooey.ai/v2/CompareLLM?example_id=2cl6c8gn",
    headers={
        "Authorization": "bearer " + os.environ["GOOEY_API_KEY"],
    },
    json=payload,
)
assert response.ok, response.content

result = response.json()
print(response.status_code, result)

export GOOEY_API_KEY=sk-xxxx

curl 'https://api.gooey.ai/v2/CompareLLM?example_id=2cl6c8gn' \
  -H "Authorization: bearer $GOOEY_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "input_prompt": "You job is to assess AI translations. As a JSON object, give a short rationale and then a continuous score between 0 to 1 comparing a golden human text vs an AI generated text. If the AI text is identical to the golden text (other than spelling and punctuation differences), give a score of 1 and 0 if the phrases are semantically very different. \n\nExamples: \nGolden: In our chili farm there are white flies. What should we do?\nAI_text: We have white spots in the Mirapakaya Pulam. What to do?\nJSON: {\n\"rationale\": \"The ai_answer is missing key elements such as chili farm and white flies.\" ,\n\"score\": \".2\"\n}\n\nGolden: {{ golden }}\nAI_text: {{ai_answer}}\nJSON: \n",
  "selected_models": [
    "gpt_3_5_turbo"
  ]
}'