Iniciar uma análise de erro de uma linha da classificação

using MeetKai.MKA1;
using MeetKai.MKA1.Types.Components;

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

var res = await sdk.Llm.Evals.CreateErrorAnalysisAsync(
    suiteId: "eval_suite_aa87e2b1112a455b8deabed784372198",
    body: new MeetKai.MKA1.Types.Components.CreateEvalErrorAnalysisRequest() {
        Model = "meetkai:functionary-urdu-mini-pak",
        MetricId = "score",
    }
);

// handle response

from meetkai_mka1 import SDK


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

    res = sdk.llm.evals.create_error_analysis(suite_id="eval_suite_aa87e2b1112a455b8deabed784372198", model="meetkai:functionary-urdu-mini-pak", metric_id="score")

    # 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.createErrorAnalysis({
    suiteId: "eval_suite_aa87e2b1112a455b8deabed784372198",
    createEvalErrorAnalysisRequest: {
      model: "meetkai:functionary-urdu-mini-pak",
      metricId: "score",
    },
  });

  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.CreateErrorAnalysis(ctx, "eval_suite_aa87e2b1112a455b8deabed784372198", components.CreateEvalErrorAnalysisRequest{
        Model: "meetkai:functionary-urdu-mini-pak",
        MetricID: mka1.Pointer("score"),
    }, nil)
    if err != nil {
        log.Fatal(err)
    }
    if res.EvalErrorAnalysisObject != nil {
        // handle response
    }
}

curl --request POST \
  --url https://apigw.mka1.com/api/v1/llm/evals/suites/{suite_id}/error-analyses \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "meetkai:functionary-urdu-mini-pak",
  "metric_id": "score"
}
'

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({model: 'meetkai:functionary-urdu-mini-pak', metric_id: 'score'})
};

fetch('https://apigw.mka1.com/api/v1/llm/evals/suites/{suite_id}/error-analyses', 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/suites/{suite_id}/error-analyses",
  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([
    'model' => 'meetkai:functionary-urdu-mini-pak',
    'metric_id' => 'score'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($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/suites/{suite_id}/error-analyses")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"meetkai:functionary-urdu-mini-pak\",\n  \"metric_id\": \"score\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://apigw.mka1.com/api/v1/llm/evals/suites/{suite_id}/error-analyses")

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

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"model\": \"meetkai:functionary-urdu-mini-pak\",\n  \"metric_id\": \"score\"\n}"

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

{
  "id": "eval_ea_aa87e2b1112a455b8deabed784372198",
  "object": "eval.error_analysis",
  "suite_id": "eval_suite_aa87e2b1112a455b8deabed784372198",
  "suite_version": 3,
  "model": "meetkai:functionary-urdu-mini-pak",
  "metric_id": "score",
  "kind": "text",
  "status": "queued",
  "analyzer_model": "gemini-4-argon",
  "prompt_version": "2026-11-04.1",
  "cache_key": "3b2c…",
  "selection": {
    "failures_total": 146,
    "selected": 100,
    "tiered": true
  },
  "samples_analysed": 100,
  "usage": null,
  "error": null,
  "created_by": "user_123",
  "created_at": 1762243200,
  "started_at": null,
  "finished_at": null,
  "sample_ids": [],
  "tags": [],
  "report": null,
  "report_markdown": null
}