How Can I Use Google Apps Script to Send Google Sheet Data to the OpenAI API for Analysis?

Below is a concise example that shows how to use Google Apps Script to send data from a Google Sheet to an OpenAI API endpoint for analysis. You can customize the script to read the desired range (like a thousand rows) and build a prompt containing the data along with your analysis questions.

Sample Google Apps Script

JAVASCRIPTCopied
function analyzeSheetData() {
  // Get the active spreadsheet and desired sheet
  var sheet = SpreadsheetApp.getActiveSpreadsheet().getSheetByName('Sheet1');
  // Adjust the range as needed; this example gets 1,000 rows from column A
  var data = sheet.getRange(1, 1, 1000, sheet.getLastColumn()).getValues();
  
  // Build a prompt that includes sheet data and your custom questions
  var prompt = "Analyze the following data and answer these questions: " +
               "\n\nData: " + JSON.stringify(data.slice(0, 10)) +  // sample data; for large sets, consider summarizing or sending chunks
               "\n\nQuestions: [insert your questions here]";
  
  // Create the JSON payload for the API request
  var payload = {
    "model": "gpt-4o-mini",  // change model if needed
    "messages": [{
      "role": "user",
      "content": prompt
    }],
    "temperature": 0.7
  };

  // Set the API endpoint and options for the POST request
  var url = "https://api.openai.com/v1/chat/completions";
  var options = {
    "method": "POST",
    "contentType": "application/json",
    "headers": {
      "Authorization": "Bearer YOUR_OPENAI_API_KEY"
    },
    "payload": JSON.stringify(payload)
  };

  // Make the request and parse the response
  var response = UrlFetchApp.fetch(url, options);
  var jsonResponse = JSON.parse(response.getContentText());
  
  // Log for debugging or write results back to the sheet
  Logger.log(jsonResponse);
  
  // Example: Write the response text to a cell
  sheet.getRange("B1").setValue(jsonResponse.choices[0].message.content);
}

Steps Outline

1. Retrieve Data:
   Use the SpreadsheetApp service to read data from your sheet. You can adjust the range as needed for your dataset.

2. Prepare the Prompt:
   Concatenate your data (or a summary of it) with the specific questions you want OpenAI to address.

3. Configure the API Request:
   Create a JSON payload with your chosen model (e.g., "gpt-4o-mini"), the prompt wrapped inside a message (note: you'll need to adjust this if using a different endpoint/model), and any other settings like temperature.

4. Send via UrlFetchApp:
   Send the prepared request using UrlFetchApp.fetch and include the authorization header with your OpenAI API key.

5. Handle the Response:
   Parse the JSON response and either log it or write it back into your Google Sheet for further analysis.

Considerations

• Data Size:
  If you're sending large quantities of data (e.g., 1,000 rows), you might want to process or summarize the information before sending it to avoid hitting payload size limits or incurring high latency.

• Rate Limits & Costs:
  Ensure you are aware of OpenAI's API rate limits and pricing when integrating with batch data.

This approach allows you to integrate OpenAI’s capabilities directly into your Google Sheets, letting you automate analysis and receive insights as part of your workflow.