from together import Together
import os

client = Together(
    api_key=os.environ.get("TOGETHER_API_KEY"),
)

response = client.evals.create(
    type="classify",
    parameters=ParametersEvaluationClassifyParameters(
        judge=ParametersEvaluationClassifyParametersJudge(
            model="openai/gpt-oss-120b",
            model_source="serverless",
            system_template="You are an expert evaluator...",
        ),
        input_data_file_path="file-abc123",
        labels=["good", "bad"],
        pass_labels=["good"],
        model_to_evaluate="Qwen/Qwen3.5-9B"
    )
)

print(response.workflow_id)

import Together from "together-ai";

const client = new Together({
  apiKey: process.env.TOGETHER_API_KEY,
});

const response = await client.evals.create({
  type: 'classify',
  parameters: {
    judge: {
      model: 'openai/gpt-oss-120b',
      model_source: 'serverless',
      system_template: 'You are an expert evaluator...',
    },
    input_data_file_path: 'file-abc123',
    labels: ['good', 'bad'],
    pass_labels: ['good'],
    model_to_evaluate: 'Qwen/Qwen3.5-9B',
  },
});

console.log(response.workflow_id);

import Together from "together-ai";

const client = new Together({
  apiKey: process.env.TOGETHER_API_KEY,
});

const response = await client.evals.create({
  type: 'classify',
  parameters: {
    judge: {
      model: 'openai/gpt-oss-120b',
      model_source: 'serverless',
      system_template: 'You are an expert evaluator...',
    },
    input_data_file_path: 'file-abc123',
    labels: ['good', 'bad'],
    pass_labels: ['good'],
    model_to_evaluate: 'Qwen/Qwen3.5-9B',
  },
});

console.log(response.workflow_id);

curl --request POST \
  --url https://api.together.ai/v1/evaluation \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "type": "classify",
  "parameters": {
    "judge": {
      "model": "Qwen/Qwen3.5-9B",
      "system_template": "Imagine you are a helpful assistant",
      "external_api_token": "<string>",
      "external_base_url": "<string>",
      "num_workers": 5,
      "max_tokens": 8192,
      "temperature": 0
    },
    "labels": [
      "yes",
      "no"
    ],
    "pass_labels": [
      "yes"
    ],
    "input_data_file_path": "file-1234-aefd",
    "model_to_evaluate": "<string>"
  }
}
'

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.together.ai/v1/evaluation",
  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([
    'type' => 'classify',
    'parameters' => [
        'judge' => [
                'model' => 'Qwen/Qwen3.5-9B',
                'system_template' => 'Imagine you are a helpful assistant',
                'external_api_token' => '<string>',
                'external_base_url' => '<string>',
                'num_workers' => 5,
                'max_tokens' => 8192,
                'temperature' => 0
        ],
        'labels' => [
                'yes',
                'no'
        ],
        'pass_labels' => [
                'yes'
        ],
        'input_data_file_path' => 'file-1234-aefd',
        'model_to_evaluate' => '<string>'
    ]
  ]),
  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;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.together.ai/v1/evaluation"

	payload := strings.NewReader("{\n  \"type\": \"classify\",\n  \"parameters\": {\n    \"judge\": {\n      \"model\": \"Qwen/Qwen3.5-9B\",\n      \"system_template\": \"Imagine you are a helpful assistant\",\n      \"external_api_token\": \"<string>\",\n      \"external_base_url\": \"<string>\",\n      \"num_workers\": 5,\n      \"max_tokens\": 8192,\n      \"temperature\": 0\n    },\n    \"labels\": [\n      \"yes\",\n      \"no\"\n    ],\n    \"pass_labels\": [\n      \"yes\"\n    ],\n    \"input_data_file_path\": \"file-1234-aefd\",\n    \"model_to_evaluate\": \"<string>\"\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.together.ai/v1/evaluation")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"type\": \"classify\",\n  \"parameters\": {\n    \"judge\": {\n      \"model\": \"Qwen/Qwen3.5-9B\",\n      \"system_template\": \"Imagine you are a helpful assistant\",\n      \"external_api_token\": \"<string>\",\n      \"external_base_url\": \"<string>\",\n      \"num_workers\": 5,\n      \"max_tokens\": 8192,\n      \"temperature\": 0\n    },\n    \"labels\": [\n      \"yes\",\n      \"no\"\n    ],\n    \"pass_labels\": [\n      \"yes\"\n    ],\n    \"input_data_file_path\": \"file-1234-aefd\",\n    \"model_to_evaluate\": \"<string>\"\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.together.ai/v1/evaluation")

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  \"type\": \"classify\",\n  \"parameters\": {\n    \"judge\": {\n      \"model\": \"Qwen/Qwen3.5-9B\",\n      \"system_template\": \"Imagine you are a helpful assistant\",\n      \"external_api_token\": \"<string>\",\n      \"external_base_url\": \"<string>\",\n      \"num_workers\": 5,\n      \"max_tokens\": 8192,\n      \"temperature\": 0\n    },\n    \"labels\": [\n      \"yes\",\n      \"no\"\n    ],\n    \"pass_labels\": [\n      \"yes\"\n    ],\n    \"input_data_file_path\": \"file-1234-aefd\",\n    \"model_to_evaluate\": \"<string>\"\n  }\n}"

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

{
  "workflow_id": "eval-1234-1244513",
  "status": "pending"
}

{
  "error": {
    "message": "<string>",
    "type": "<string>",
    "param": null,
    "code": null
  }
}

{
  "error": {
    "message": "<string>",
    "type": "<string>",
    "param": null,
    "code": null
  }
}