API: Compare LLMs to create structured data from a transcript

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📤 Example Request

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Generate an api key below👇
Install node-fetch & add the GOOEY_API_KEY to your environment variables.
Never store the api key in your code and don't use direcly in the browser.

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

Use this sample code to call the API.
If you encounter any issues, write to us at support@gooey.ai and make sure to include the full code snippet and the error message.

import fetch from 'node-fetch';

const payload = {
  "input_prompt": "Given the transcript below of a medical conversation, tell me the following info about the patient:\nName\nDOB\nTopics discussed. \n\n{{transcript}}\npatient data (export as JSON with newlines)\n",
  "selected_models": [
    "gemini_2_5_flash",
    "llama4_scout_17b_16e"
  ]
};

async function gooeyAPI() {
  const response = await fetch("https://api.gooey.ai/v2/compare-large-language-models?example_id=m8cwhp1cdb81", {
    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();

Generate an api key below👇
Install requests & add the GOOEY_API_KEY to your environment variables.
Never store the api key in your code.

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

Use this sample code to call the API.
If you encounter any issues, write to us at support@gooey.ai and make sure to include the full code snippet and the error message.

import os
import requests

payload = {
    "input_prompt": "Given the transcript below of a medical conversation, tell me the following info about the patient:\nName\nDOB\nTopics discussed. \n\n{{transcript}}\npatient data (export as JSON with newlines)\n",
    "selected_models": ["gemini_2_5_flash", "llama4_scout_17b_16e"],
}

response = requests.post(
    "https://api.gooey.ai/v2/compare-large-language-models?example_id=m8cwhp1cdb81",
    headers={
        "Authorization": "bearer " + os.environ["GOOEY_API_KEY"],
    },
    json=payload,
)
assert response.ok, response.content

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

Generate an api key below👇
Install curl & add the GOOEY_API_KEY to your environment variables.
Never store the api key in your code.

export GOOEY_API_KEY=sk-xxxx

Run the following curl command in your terminal.
If you encounter any issues, write to us at support@gooey.ai and make sure to include the full curl command and the error message.

curl 'https://api.gooey.ai/v2/compare-large-language-models?example_id=m8cwhp1cdb81' \
  -H "Authorization: bearer $GOOEY_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "input_prompt": "Given the transcript below of a medical conversation, tell me the following info about the patient:\nName\nDOB\nTopics discussed. \n\n{{transcript}}\npatient data (export as JSON with newlines)\n",
  "selected_models": [
    "gemini_2_5_flash",
    "llama4_scout_17b_16e"
  ]
}'

🎁 Example Response

{4 Items"id":
string
"2lvsq6ftw5pr"
"url":
string
"https://gooey.ai/compare-large-language-models/"
"created_at":
string
"2025-08-06T19:47:24.027674+00:00"
"output":
{1 Items"output_text":
{2 Items"gemini_2_5_flash":
[…
]1 Items
"llama4_scout_17b_16e":
[…
]1 Items
}
}
}

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