tapas_demo

/*
 * Converts table from [[Header0, Header1, Header2], [Column0Val0, Column1Val0, Column2Val0], ...]
 * to {Header0: [ColumnVal0, ...], Header1: [Column1Val0, ...], Header2: [Column2Val0, ...]}
 */
function convertTableToData(table) {
    transposed = table[0].map((_, colIndex) => table.map(row => row[colIndex]));
    result = {}
    for(var i = 0; i < transposed.length; i++) {
      header = transposed[i][0]
      result[header] = transposed[i].slice(1, 4).map(String);
    }
    return result;
}


function ANSWER_QUESTION(query, table, repo_id="google/tapas-base-finetuned-wtq") {
  const endpoint = "https://api-inference.huggingface.co/pipeline/";
  const pipeline = "table-question-answering/"
  const payload = JSON.stringify({
    "query": query,
    "table": convertTableToData(table),
  });

  // Add your token from https://huggingface.co/settings/token
  const options = {
      "headers" = {"Authorization": "Bearer YOUR_TOKEN"},
      "wait_for_model": true,
      "use_gpu": false,
      "method" : "POST",
      "contentType" : "application/json",
      "payload" : payload
    };

  path = endpoint + pipeline + repo_id
  const response = UrlFetchApp.fetch(path, options);
  const data = JSON.parse(response.getContentText());

  // There is a lot of other useful data here that is useful for
  // more complex questions.
  return data["cells"];
}

Hi @osanseviero,

Is there another pipeline besides "table-question-answering/" that can be used?

I was trying with "sentiment-analysis/", but it did not work :)

Yes, you should be able to adapt this example for the rest of the use cases, which are easier.

https://twitter.com/osanseviero/status/1410222232706727945
https://twitter.com/osanseviero/status/1410252607558492161
https://api-inference.huggingface.co/docs/python/html/detailed_parameters.html

Thanks 😃 👍