Importar resultados históricos de avaliação do Hugging Face

using MeetKai.MKA1;
using MeetKai.MKA1.Types.Components;
using System.Collections.Generic;

var sdk = new SDK(bearerAuth: "<YOUR_BEARER_TOKEN_HERE>");

var res = await sdk.Llm.Evals.ImportHistoricalResultsAsync(
    xHuggingFaceToken: "hf_your_read_token",
    body: new MeetKai.MKA1.Types.Components.ImportHistoricalEvalResultsRequest() {
        Source = new ImportHistoricalEvalResultsRequestSource() {
            PathPrefix = "functionary/ur/",
        },
        SuiteName = "MKA1 historical eval results",
        Metadata = new Dictionary<string, string>() {
            { "owner", "eval-team" },
        },
    }
);

// handle response

from meetkai_mka1 import SDK


with SDK(
    bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as sdk:

    res = sdk.llm.evals.import_historical_results(x_hugging_face_token="hf_your_read_token", source={
        "path_prefix": "functionary/ur/",
    }, suite_name="MKA1 historical eval results", create_missing_tasks=True, dry_run=False, metadata={
        "owner": "eval-team",
    })

    # Handle response
    print(res)

import { SDK } from "@meetkai/mka1";

const sdk = new SDK({
  bearerAuth: "<YOUR_BEARER_TOKEN_HERE>",
});

async function run() {
  const result = await sdk.llm.evals.importHistoricalResults({
    xHuggingFaceToken: "hf_your_read_token",
    importHistoricalEvalResultsRequest: {
      source: {
        pathPrefix: "functionary/ur/",
      },
      suiteName: "MKA1 historical eval results",
      metadata: {
        "owner": "eval-team",
      },
    },
  });

  console.log(result);
}

run();

package main

import(
	"context"
	mka1 "github.com/MeetKai/mka1-sdks/go"
	"github.com/MeetKai/mka1-sdks/go/models/components"
	"log"
)

func main() {
    ctx := context.Background()

    s := mka1.New(
        mka1.WithSecurity("<YOUR_BEARER_TOKEN_HERE>"),
    )

    res, err := s.Llm.Evals.ImportHistoricalResults(ctx, "hf_your_read_token", components.ImportHistoricalEvalResultsRequest{
        Source: &components.ImportHistoricalEvalResultsRequestSource{
            PathPrefix: mka1.Pointer("functionary/ur/"),
        },
        SuiteName: mka1.Pointer("MKA1 historical eval results"),
        Metadata: map[string]string{
            "owner": "eval-team",
        },
    }, nil)
    if err != nil {
        log.Fatal(err)
    }
    if res.EvalHistoricalImportObject != nil {
        // handle response
    }
}

curl --request POST \
  --url https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --header 'X-HuggingFace-Token: <x-huggingface-token>' \
  --data '
{
  "source": {
    "type": "huggingface",
    "repo": "meetkai/lm-eval-harness-result",
    "revision": "main",
    "path_prefix": "functionary/ur/"
  },
  "suite_name": "MKA1 historical eval results",
  "create_missing_tasks": true,
  "metadata": {
    "owner": "eval-team"
  }
}
'

const options = {
  method: 'POST',
  headers: {
    'X-HuggingFace-Token': '<x-huggingface-token>',
    Authorization: 'Bearer <token>',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    source: {
      type: 'huggingface',
      repo: 'meetkai/lm-eval-harness-result',
      revision: 'main',
      path_prefix: 'functionary/ur/'
    },
    suite_name: 'MKA1 historical eval results',
    create_missing_tasks: true,
    metadata: {owner: 'eval-team'}
  })
};

fetch('https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'source' => [
        'type' => 'huggingface',
        'repo' => 'meetkai/lm-eval-harness-result',
        'revision' => 'main',
        'path_prefix' => 'functionary/ur/'
    ],
    'suite_name' => 'MKA1 historical eval results',
    'create_missing_tasks' => true,
    'metadata' => [
        'owner' => 'eval-team'
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json",
    "X-HuggingFace-Token: <x-huggingface-token>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

HttpResponse<String> response = Unirest.post("https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results")
  .header("X-HuggingFace-Token", "<x-huggingface-token>")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"source\": {\n    \"type\": \"huggingface\",\n    \"repo\": \"meetkai/lm-eval-harness-result\",\n    \"revision\": \"main\",\n    \"path_prefix\": \"functionary/ur/\"\n  },\n  \"suite_name\": \"MKA1 historical eval results\",\n  \"create_missing_tasks\": true,\n  \"metadata\": {\n    \"owner\": \"eval-team\"\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://apigw.mka1.com/api/v1/llm/evals/imports/huggingface-results")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["X-HuggingFace-Token"] = '<x-huggingface-token>'
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"source\": {\n    \"type\": \"huggingface\",\n    \"repo\": \"meetkai/lm-eval-harness-result\",\n    \"revision\": \"main\",\n    \"path_prefix\": \"functionary/ur/\"\n  },\n  \"suite_name\": \"MKA1 historical eval results\",\n  \"create_missing_tasks\": true,\n  \"metadata\": {\n    \"owner\": \"eval-team\"\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "object": "eval.import",
  "source": {
    "type": "huggingface",
    "repo": "meetkai/lm-eval-harness-result",
    "revision": "main"
  },
  "suite_id": "eval_suite_aa87e2b1112a455b8deabed784372198",
  "suite_version": 1,
  "created_suite": true,
  "created_suite_version": true,
  "dry_run": false,
  "discovered_files": 30,
  "imported_runs": 30,
  "skipped_runs": 0,
  "imported_samples": 8870
}