Bulk Runner & Evaluator
Which AI model actually works best for your needs? Upload your own data and evaluate any Gooey.AI workflow, LLM or AI model against any other. Great for large data sets, AI model evaluation, task automation, parallel processing and automated testing. To get started, paste in a Gooey.AI workflow, upload a CSV of your test data (with header names!), check the mapping of headers to workflow inputs and tap Submit. More tips in the Details below.
📖 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 = {
"documents": [
"https://storage.googleapis.com/dara-c1b52.appspot.com/daras_ai/media/ea4bdae4-678f-11ee-9748-02420a00014c/Gooey%20AI_testing%20feedback%20-%20Oct%202023.csv"
],
"run_urls": [
"https://gooey.ai/copilot/?example_id=nuwsqmzp"
],
"input_columns": {
"input_prompt": "Sample Question"
},
"output_columns": {
"run_url": "run url",
"output_text": "output text"
}
};
async function gooeyAPI() {
const response = await fetch("https://api.gooey.ai/v2/bulk-runner/", {
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 = {
"documents": [
"https://storage.googleapis.com/dara-c1b52.appspot.com/daras_ai/media/ea4bdae4-678f-11ee-9748-02420a00014c/Gooey%20AI_testing%20feedback%20-%20Oct%202023.csv"
],
"run_urls": ["https://gooey.ai/copilot/?example_id=nuwsqmzp"],
"input_columns": {"input_prompt": "Sample Question"},
"output_columns": {"run_url": "run url", "output_text": "output text"},
}
response = requests.post(
"https://api.gooey.ai/v2/bulk-runner/",
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/bulk-runner/ \
-H "Authorization: Bearer $GOOEY_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"documents": [
"https://storage.googleapis.com/dara-c1b52.appspot.com/daras_ai/media/ea4bdae4-678f-11ee-9748-02420a00014c/Gooey%20AI_testing%20feedback%20-%20Oct%202023.csv"
],
"run_urls": [
"https://gooey.ai/copilot/?example_id=nuwsqmzp"
],
"input_columns": {
"input_prompt": "Sample Question"
},
"output_columns": {
"run_url": "run url",
"output_text": "output text"
}
}'
🎁 Example Response
{4 Items"url":
string
"https://gooey.ai/bulk/"
"created_at":
string
"2023-10-03T07:04:27.317090+00:00"
"output":
{1 Items"output_documents":
[1 Items0:
string
"https://storage.googleapis.com/dara-c1b52.appspot.…"
Please Login to generate the $GOOEY_API_KEY