API: Gooey Bot Chat Analysis Script


📖 To learn more, take a look at our complete API

📤 Example Request

  1. Generate an api key below👇

  2. 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
  1. 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, determine how to categorize them and determine if the bot answered their question with \"Found\" or \"Missing\". Your response should contain exactly one JSON object.\n\nCategory choices: [ \"API Usage\", \"General Support Query\", \"Pricing & Credits\", \"Sales\", \"Others\" ]\n\nReturn your analysis as the following json object: { \n\"What was the category of the user query?\": \"<category>: <which tool>\", \n\"assistant\": {\"answer\": \"Found || Missing\"}}}\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=27lrilywfzmv", {
    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();
  1. Generate an api key below👇

  2. 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
  1. 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, determine how to categorize them and determine if the bot answered their question with "Found" or "Missing". Your response should contain exactly one JSON object.\n\nCategory choices: [ "API Usage", "General Support Query", "Pricing & Credits", "Sales", "Others" ]\n\nReturn your analysis as the following json object: { \n"What was the category of the user query?": "<category>: <which tool>", \n"assistant": {"answer": "Found || Missing"}}}\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=27lrilywfzmv",
    headers={
        "Authorization": "bearer " + os.environ["GOOEY_API_KEY"],
    },
    json=payload,
)
assert response.ok, response.content

result = response.json()
print(response.status_code, result)
  1. Generate an api key below👇

  2. 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
  1. 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=27lrilywfzmv' \
  -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, determine how to categorize them and determine if the bot answered their question with \"Found\" or \"Missing\". Your response should contain exactly one JSON object.\n\nCategory choices: [ \"API Usage\", \"General Support Query\", \"Pricing & Credits\", \"Sales\", \"Others\" ]\n\nReturn your analysis as the following json object: { \n\"What was the category of the user query?\": \"<category>: <which tool>\", \n\"assistant\": {\"answer\": \"Found || Missing\"}}}\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
"id"
:
string
"m9gcknhpzft4"
"url"
:
string
"https://gooey.ai/compare-large-language-models/"
"created_at"
:
string
"2024-08-09T20:10:16.121681+00:00"
"output"
:
{2 Items
"output_text"
:
{1 Items
"gpt_4_turbo"
:
[
]1 Items
}
"called_functions"
:
[1 Items
0
:
{
}3 Items
]
}
}

Please Login to generate the $GOOEY_API_KEY