📖 To learn more, take a look at our complete API
📤 Example Request
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 [email protected] and make sure to include the full code snippet and the error message.
import fetch from 'node-fetch';
const payload = {
"input_prompt": "{{messages}}\n\n###\n\nYour job is to analyze the user's messages above and determine how to categorize them.\n\nCategory choices: [ \"\ud83d\ude0a Happy\", \"\ud83d\ude1f Worry\", \"\ud83c\udf1f Hopeful\", \"\ud83d\ude28 Fear\", \"\ud83e\udd2f Mind Blown\" ]\n\nReturn your analysis as the following json object: { \"How did this evening make you feel about AI and Robots?\": \"<category>\" }\n\nIf the messages doesn't fit into any of the categories, return an empty object (`{}`)",
"selected_models": [
"gpt_4_turbo"
]
};
async function gooeyAPI() {
const response = await fetch("https://api.gooey.ai/v2/CompareLLM?example_id=z9dhbssar6n6", {
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 [email protected] and make sure to include the full code snippet and the error message.
import os
import requests
payload = {
"input_prompt": '{{messages}}\n\n###\n\nYour job is to analyze the user\'s messages above and determine how to categorize them.\n\nCategory choices: [ "😊 Happy", "😟 Worry", "🌟 Hopeful", "😨 Fear", "🤯 Mind Blown" ]\n\nReturn your analysis as the following json object: { "How did this evening make you feel about AI and Robots?": "<category>" }\n\nIf the messages doesn\'t fit into any of the categories, return an empty object (`{}`)',
"selected_models": ["gpt_4_turbo"],
}
response = requests.post(
"https://api.gooey.ai/v2/CompareLLM?example_id=z9dhbssar6n6",
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 [email protected] and make sure to include the full curl command and the error message.
curl 'https://api.gooey.ai/v2/CompareLLM?example_id=z9dhbssar6n6' \
-H "Authorization: bearer $GOOEY_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"input_prompt": "{{messages}}\n\n###\n\nYour job is to analyze the user'"'"'s messages above and determine how to categorize them.\n\nCategory choices: [ \"\ud83d\ude0a Happy\", \"\ud83d\ude1f Worry\", \"\ud83c\udf1f Hopeful\", \"\ud83d\ude28 Fear\", \"\ud83e\udd2f Mind Blown\" ]\n\nReturn your analysis as the following json object: { \"How did this evening make you feel about AI and Robots?\": \"<category>\" }\n\nIf the messages doesn'"'"'t fit into any of the categories, return an empty object (`{}`)",
"selected_models": [
"gpt_4_turbo"
]
}'
🎁 Example Response
{4 Items"url":
string
"https://gooey.ai/compare-large-language-models/"
"created_at":
string
"2024-05-14T16:25:18.620249+00:00"
Please Login to generate the $GOOEY_API_KEY