Crear un alias de modelo

POST

api

llm

models

aliases

Go (SDK)

package main

import(
	"context"
	mka1 "github.com/MeetKai/mka1-sdks/go"
	"github.com/MeetKai/mka1-sdks/go/optionalnullable"
	"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.Models.CreateAlias(ctx, components.CreateModelAliasRequest{
        Name: "best-math-model",
        SuiteID: "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
        Metric: "accuracy",
        CandidateModelIds: []string{
            "meetkai:functionary-pt",
            "meetkai:functionary-es",
        },
        DefaultModelID: optionalnullable.From(mka1.Pointer("meetkai:functionary-pt")),
    })
    if err != nil {
        log.Fatal(err)
    }
    if res.ModelAlias != nil {
        // handle response
    }
}

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

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

CreateModelAliasRequest req = new CreateModelAliasRequest() {
    Name = "best-math-model",
    SuiteId = "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
    Metric = "accuracy",
    CandidateModelIds = new List<string>() {
        "meetkai:functionary-pt",
        "meetkai:functionary-es",
    },
    DefaultModelId = "meetkai:functionary-pt",
};

var res = await sdk.Llm.Models.CreateAliasAsync(req);

// handle response

from meetkai_mka1 import SDK


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

    res = sdk.llm.models.create_alias(name="best-math-model", suite_id="eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a", metric="accuracy", candidate_model_ids=[
        "meetkai:functionary-pt",
        "meetkai:functionary-es",
    ], default_model_id="meetkai:functionary-pt")

    # 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.models.createAlias({
    name: "best-math-model",
    suiteId: "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
    metric: "accuracy",
    candidateModelIds: [
      "meetkai:functionary-pt",
      "meetkai:functionary-es",
    ],
    defaultModelId: "meetkai:functionary-pt",
  });

  console.log(result);
}

run();

curl --request POST \
  --url https://apigw.mka1.com/api/v1/llm/models/aliases \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "best-math-model",
  "suite_id": "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
  "metric": "accuracy",
  "candidate_model_ids": [
    "meetkai:functionary-pt",
    "meetkai:functionary-es"
  ],
  "default_model_id": "meetkai:functionary-pt"
}
'

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: 'best-math-model',
    suite_id: 'eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a',
    metric: 'accuracy',
    candidate_model_ids: ['meetkai:functionary-pt', 'meetkai:functionary-es'],
    default_model_id: 'meetkai:functionary-pt'
  })
};

fetch('https://apigw.mka1.com/api/v1/llm/models/aliases', 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/models/aliases",
  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([
    'name' => 'best-math-model',
    'suite_id' => 'eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a',
    'metric' => 'accuracy',
    'candidate_model_ids' => [
        'meetkai:functionary-pt',
        'meetkai:functionary-es'
    ],
    'default_model_id' => 'meetkai:functionary-pt'
  ]),
  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/models/aliases")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"best-math-model\",\n  \"suite_id\": \"eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a\",\n  \"metric\": \"accuracy\",\n  \"candidate_model_ids\": [\n    \"meetkai:functionary-pt\",\n    \"meetkai:functionary-es\"\n  ],\n  \"default_model_id\": \"meetkai:functionary-pt\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://apigw.mka1.com/api/v1/llm/models/aliases")

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  \"name\": \"best-math-model\",\n  \"suite_id\": \"eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a\",\n  \"metric\": \"accuracy\",\n  \"candidate_model_ids\": [\n    \"meetkai:functionary-pt\",\n    \"meetkai:functionary-es\"\n  ],\n  \"default_model_id\": \"meetkai:functionary-pt\"\n}"

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

{
  "object": "model.alias",
  "name": "best-math-model",
  "suite_id": "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
  "suite_version": 3,
  "metric": "accuracy",
  "higher_is_better": true,
  "task_id": null,
  "candidate_model_ids": [
    "meetkai:functionary-pt",
    "meetkai:functionary-es"
  ],
  "api_format": "responses",
  "default_model_id": "meetkai:functionary-pt",
  "pinned_model_id": null,
  "current_model_id": "meetkai:functionary-es",
  "served_model_id": "meetkai:functionary-es",
  "served_because": "benchmark",
  "state": "ok",
  "resolvable": true,
  "standings": [
    {
      "model_id": "meetkai:functionary-pt",
      "score": 0.81,
      "run_id": "eval_run_5e1f7c3a-92b4-4d68-8f0a-b3c9d2e6a1f4",
      "completed_at": "2026-11-09T02:14:00.000Z",
      "sample_count": 500,
      "failed_count": 0,
      "eligible": true,
      "ineligible_reason": null
    },
    {
      "model_id": "meetkai:functionary-es",
      "score": 0.86,
      "run_id": "eval_run_5e1f7c3a-92b4-4d68-8f0a-b3c9d2e6a1f4",
      "completed_at": "2026-11-09T02:14:00.000Z",
      "sample_count": 500,
      "failed_count": 0,
      "eligible": true,
      "ineligible_reason": null
    }
  ],
  "evaluated_at": "2026-11-09T02:14:05.000Z",
  "created_by": "user-org-admin-1",
  "created_at": "2026-11-01T18:00:00.000Z",
  "updated_by": "user-org-admin-1",
  "updated_at": "2026-11-01T18:00:00.000Z"
}

Autorizaciones

Authorization

string

header

requerido

Send Authorization: Bearer , using an MKA1 API key for automation or an OAuth API access token for a signed-in application. Use a dynamic security callback to refresh OAuth access tokens. Browser session-only operations still require their declared cookie.

Cuerpo

application/json

name

string

requerido

El nombre del modelo que usan los llamantes. Está reclamado en el registro de la organización, por lo que no debe estar ya activo.

Required string length: 1 - 255

suite_id

string

requerido

Una suite de evaluación propiedad de esta organización.

Required string length: 1 - 255

metric

string

requerido

Un id de métrica que declara la versión activa de la suite. Su higher_is_better decide qué puntuación gana.

Required string length: 1 - 128

candidate_model_ids

string[]

requerido

Dos a 16 modelos activos de un formato de API. El alias solo sirve uno de estos. El orden rompe los empates: el modelo anterior gana en caso de puntuación igual.

Required array length: 2 - 16 elements

Required string length: 1 - 255

task_id

string | null

Una tarea del conjunto sobre la que clasificar. Null clasifica la métrica promediada sobre cada tarea, contando solo las ejecuciones que cubren cada tarea de la versión.

Required string length: 1 - 255

default_model_id

string | null

Un candidato para servir hasta que exista un primer ganador. Null deja el alias sin resolver hasta entonces.

Required string length: 1 - 255

Respuesta

200 - application/json

Está bien

object

any

requerido

name

string

requerido

suite_id

string

requerido

suite_version

integer | null

requerido

La versión de la suite se volvió a calcular por última vez clasificada. Nula antes de que se pudiera leer.

Rango requerido: -9007199254740991 <= x <= 9007199254740991

metric

string

requerido

higher_is_better

boolean | null

requerido

task_id

string | null

requerido

candidate_model_ids

string[]

requerido

api_format

enum<string>

requerido

Opciones disponibles:

responses,

completions,

embeddings,

images,

transcriptions,

tts,

rerank

default_model_id

string | null

requerido

pinned_model_id

string | null

requerido

current_model_id

string | null

requerido

El ganador del punto de referencia. Nulo hasta que exista uno.

served_model_id

string | null

requerido

Qué solicitud para el alias se atiende por: el pin, si no el ganador, si no el valor predeterminado.

served_because

enum<string> | null

requerido

Opciones disponibles:

pinned,

benchmark,

default

state

enum<string>

requerido

ok: sirviendo a un ganador clasificado. waiting_for_results: aún no hay un resultado completo para clasificar, por lo que se mantiene el último ganador o el predeterminado. metric_missing: la versión activa de la suite ya no declara la métrica o la tarea. suite_missing: la suite fue eliminada. Los dos últimos conservan al último ganador hasta que se edita el alias.

Opciones disponibles:

ok,

waiting_for_results,

metric_missing,

suite_missing

resolvable

boolean

requerido

Si una solicitud del alias se resuelve en este momento: sirve un modelo que todavía está activo en el registro.

standings

object[]

requerido

Show child attributes

evaluated_at

string<date-time> | null

requerido

created_by

string

requerido

created_at

string<date-time>

requerido

updated_by

string

requerido

updated_at

string<date-time>

requerido

⌘I

Go (SDK)

package main

import(
	"context"
	mka1 "github.com/MeetKai/mka1-sdks/go"
	"github.com/MeetKai/mka1-sdks/go/optionalnullable"
	"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.Models.CreateAlias(ctx, components.CreateModelAliasRequest{
        Name: "best-math-model",
        SuiteID: "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
        Metric: "accuracy",
        CandidateModelIds: []string{
            "meetkai:functionary-pt",
            "meetkai:functionary-es",
        },
        DefaultModelID: optionalnullable.From(mka1.Pointer("meetkai:functionary-pt")),
    })
    if err != nil {
        log.Fatal(err)
    }
    if res.ModelAlias != nil {
        // handle response
    }
}

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

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

CreateModelAliasRequest req = new CreateModelAliasRequest() {
    Name = "best-math-model",
    SuiteId = "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
    Metric = "accuracy",
    CandidateModelIds = new List<string>() {
        "meetkai:functionary-pt",
        "meetkai:functionary-es",
    },
    DefaultModelId = "meetkai:functionary-pt",
};

var res = await sdk.Llm.Models.CreateAliasAsync(req);

// handle response

from meetkai_mka1 import SDK


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

    res = sdk.llm.models.create_alias(name="best-math-model", suite_id="eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a", metric="accuracy", candidate_model_ids=[
        "meetkai:functionary-pt",
        "meetkai:functionary-es",
    ], default_model_id="meetkai:functionary-pt")

    # 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.models.createAlias({
    name: "best-math-model",
    suiteId: "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
    metric: "accuracy",
    candidateModelIds: [
      "meetkai:functionary-pt",
      "meetkai:functionary-es",
    ],
    defaultModelId: "meetkai:functionary-pt",
  });

  console.log(result);
}

run();

curl --request POST \
  --url https://apigw.mka1.com/api/v1/llm/models/aliases \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "best-math-model",
  "suite_id": "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
  "metric": "accuracy",
  "candidate_model_ids": [
    "meetkai:functionary-pt",
    "meetkai:functionary-es"
  ],
  "default_model_id": "meetkai:functionary-pt"
}
'

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: 'best-math-model',
    suite_id: 'eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a',
    metric: 'accuracy',
    candidate_model_ids: ['meetkai:functionary-pt', 'meetkai:functionary-es'],
    default_model_id: 'meetkai:functionary-pt'
  })
};

fetch('https://apigw.mka1.com/api/v1/llm/models/aliases', 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/models/aliases",
  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([
    'name' => 'best-math-model',
    'suite_id' => 'eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a',
    'metric' => 'accuracy',
    'candidate_model_ids' => [
        'meetkai:functionary-pt',
        'meetkai:functionary-es'
    ],
    'default_model_id' => 'meetkai:functionary-pt'
  ]),
  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/models/aliases")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"best-math-model\",\n  \"suite_id\": \"eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a\",\n  \"metric\": \"accuracy\",\n  \"candidate_model_ids\": [\n    \"meetkai:functionary-pt\",\n    \"meetkai:functionary-es\"\n  ],\n  \"default_model_id\": \"meetkai:functionary-pt\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://apigw.mka1.com/api/v1/llm/models/aliases")

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  \"name\": \"best-math-model\",\n  \"suite_id\": \"eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a\",\n  \"metric\": \"accuracy\",\n  \"candidate_model_ids\": [\n    \"meetkai:functionary-pt\",\n    \"meetkai:functionary-es\"\n  ],\n  \"default_model_id\": \"meetkai:functionary-pt\"\n}"

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

{
  "object": "model.alias",
  "name": "best-math-model",
  "suite_id": "eval_suite_0b9c2a1e-7d43-4f0e-9a51-2c6f8e1d4b7a",
  "suite_version": 3,
  "metric": "accuracy",
  "higher_is_better": true,
  "task_id": null,
  "candidate_model_ids": [
    "meetkai:functionary-pt",
    "meetkai:functionary-es"
  ],
  "api_format": "responses",
  "default_model_id": "meetkai:functionary-pt",
  "pinned_model_id": null,
  "current_model_id": "meetkai:functionary-es",
  "served_model_id": "meetkai:functionary-es",
  "served_because": "benchmark",
  "state": "ok",
  "resolvable": true,
  "standings": [
    {
      "model_id": "meetkai:functionary-pt",
      "score": 0.81,
      "run_id": "eval_run_5e1f7c3a-92b4-4d68-8f0a-b3c9d2e6a1f4",
      "completed_at": "2026-11-09T02:14:00.000Z",
      "sample_count": 500,
      "failed_count": 0,
      "eligible": true,
      "ineligible_reason": null
    },
    {
      "model_id": "meetkai:functionary-es",
      "score": 0.86,
      "run_id": "eval_run_5e1f7c3a-92b4-4d68-8f0a-b3c9d2e6a1f4",
      "completed_at": "2026-11-09T02:14:00.000Z",
      "sample_count": 500,
      "failed_count": 0,
      "eligible": true,
      "ineligible_reason": null
    }
  ],
  "evaluated_at": "2026-11-09T02:14:05.000Z",
  "created_by": "user-org-admin-1",
  "created_at": "2026-11-01T18:00:00.000Z",
  "updated_by": "user-org-admin-1",
  "updated_at": "2026-11-01T18:00:00.000Z"
}

Responses and conversations

Models and routing

Images and audio

Files and retrieval

Agents

Tools and sandbox

Evals and feedback

Compute

Repositories

Dataset generations

Organizations and access

Usage and budgets

Application utilities

Analytics

Legacy APIs

Additional APIs

Crear un alias de modelo

Autorizaciones

Cuerpo

Respuesta