Alibaba Cloud Model Studio:Kompatibel dengan OpenAI - Batch (input file)

SDK Python OpenAI

import os
from pathlib import Path
from openai import OpenAI
import time

# Inisialisasi klien.
client = OpenAI(
    # Jika variabel lingkungan belum diatur, ganti baris berikut dengan Kunci API Model Studio Anda: api_key="sk-xxx".
    # Untuk keamanan, jangan hard-code Kunci API Anda dalam kode produksi.
    # Kunci API untuk wilayah Singapura dan Beijing berbeda.
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # Berikut adalah URL dasar untuk wilayah Singapura. Jika Anda menggunakan model di wilayah Beijing, ganti base_url dengan: https://dashscope.aliyuncs.com/compatible-mode/v1
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1"  # base_url untuk layanan Alibaba Cloud Model Studio
)

def upload_file(file_path):
    print(f"Mengunggah file JSONL yang berisi informasi permintaan...")
    file_object = client.files.create(file=Path(file_path), purpose="batch")
    print(f"File diunggah. ID File: {file_object.id}\n")
    return file_object.id

def create_batch_job(input_file_id):
    print(f"Membuat tugas batch dari ID file...")
    # Catatan: Nilai parameter endpoint harus sama dengan nilai field url dalam file input. Untuk model uji (batch-test-model), atur endpoint ke /v1/chat/ds-test. Untuk model text embedding, atur ke /v1/embeddings. Untuk model lainnya, atur ke /v1/chat/completions.
    batch = client.batches.create(input_file_id=input_file_id, endpoint="/v1/chat/ds-test", completion_window="24h")
    print(f"Tugas batch dibuat. ID Tugas batch: {batch.id}\n")
    return batch.id

def check_job_status(batch_id):
    print(f"Memeriksa status tugas batch...")
    batch = client.batches.retrieve(batch_id=batch_id)
    print(f"Status tugas batch: {batch.status}\n")
    return batch.status

def get_output_id(batch_id):
    print(f"Mendapatkan ID file output untuk permintaan yang berhasil dalam tugas batch...")
    batch = client.batches.retrieve(batch_id=batch_id)
    print(f"ID file output: {batch.output_file_id}\n")
    return batch.output_file_id

def get_error_id(batch_id):
    print(f"Mendapatkan ID file output untuk permintaan yang gagal dalam tugas batch...")
    batch = client.batches.retrieve(batch_id=batch_id)
    print(f"ID file error: {batch.error_file_id}\n")
    return batch.error_file_id

def download_results(output_file_id, output_file_path):
    print(f"Mencetak dan mengunduh hasil yang berhasil dari tugas batch...")
    content = client.files.content(output_file_id)
    # Cetak sebagian konten untuk pengujian.
    print(f"Mencetak 1000 karakter pertama dari hasil yang berhasil: {content.text[:1000]}...\n")
    # Simpan file hasil secara lokal.
    content.write_to_file(output_file_path)
    print(f"Output lengkap telah disimpan ke file hasil lokal result.jsonl\n")

def download_errors(error_file_id, error_file_path):
    print(f"Mencetak dan mengunduh informasi kegagalan dari tugas batch...")
    content = client.files.content(error_file_id)
    # Cetak sebagian konten untuk pengujian.
    print(f"Mencetak 1000 karakter pertama dari informasi kegagalan: {content.text[:1000]}...\n")
    # Simpan file informasi error secara lokal.
    content.write_to_file(error_file_path)
    print(f"Informasi kegagalan lengkap telah disimpan ke file error lokal error.jsonl\n")

def main():
    # Path file
    input_file_path = "test_model.jsonl"  # Ganti dengan path file input Anda.
    output_file_path = "result.jsonl"  # Ganti dengan path file output Anda.
    error_file_path = "error.jsonl"  # Ganti dengan path file error Anda.
    try:
        # Langkah 1: Unggah file JSONL yang berisi informasi permintaan untuk mendapatkan ID file input.
        input_file_id = upload_file(input_file_path)
        # Langkah 2: Buat tugas batch berdasarkan ID file input.
        batch_id = create_batch_job(input_file_id)
        # Langkah 3: Periksa status tugas batch hingga selesai.
        status = ""
        while status not in ["completed", "failed", "expired", "cancelled"]:
            status = check_job_status(batch_id)
            print(f"Menunggu tugas selesai...")
            time.sleep(10)  # Tunggu 10 detik sebelum memeriksa status lagi.
        # Jika tugas gagal, cetak pesan error dan keluar.
        if status == "failed":
            batch = client.batches.retrieve(batch_id)
            print(f"Tugas batch gagal. Error: {batch.errors}\n")
            print(f"Untuk informasi lebih lanjut, lihat https://www.alibabacloud.com/help/en/model-studio/developer-reference/error-code")
            return
        # Langkah 4: Unduh hasilnya. Jika ID file output tidak kosong, cetak 1000 karakter pertama dari hasil yang berhasil dan unduh hasil lengkap ke file output lokal.
        # Jika ID file error tidak kosong, cetak 1000 karakter pertama dari informasi kegagalan dan unduh informasi lengkap ke file error lokal.
        output_file_id = get_output_id(batch_id)
        if output_file_id:
            download_results(output_file_id, output_file_path)
        error_file_id = get_error_id(batch_id)
        if error_file_id:
            download_errors(error_file_id, error_file_path)
            print(f"Untuk informasi lebih lanjut, lihat https://www.alibabacloud.com/help/en/model-studio/developer-reference/error-code")
    except Exception as e:
        print(f"Terjadi kesalahan: {e}")
        print(f"Untuk informasi lebih lanjut, lihat https://www.alibabacloud.com/help/en/model-studio/developer-reference/error-code")

if __name__ == "__main__":
    main()

SDK Node.js OpenAI

/**
 * Pengujian API Batch Alibaba Cloud Model Studio - Menggunakan SDK Node.js OpenAI
 *
 * Instal dependensi: npm install openai
 * Jalankan: node test-nodejs.js
 */

const OpenAI = require('openai');
const fs = require('fs');

// URL dasar untuk wilayah Singapura
const BASE_URL = 'https://dashscope-intl.aliyuncs.com/compatible-mode/v1';
// Jika Anda menggunakan wilayah Beijing, gunakan URL berikut:
// const BASE_URL = 'https://dashscope.aliyuncs.com/compatible-mode/v1';

const apiKey = process.env.DASHSCOPE_API_KEY;
if (!apiKey) {
    console.error('Error: Harap atur variabel lingkungan DASHSCOPE_API_KEY.');
    process.exit(1);
}

// Inisialisasi klien.
const client = new OpenAI({
    apiKey: apiKey,
    baseURL: BASE_URL
});

async function sleep(ms) {
    return new Promise(resolve => setTimeout(resolve, ms));
}

async function main() {
    try {
        console.log('=== Memulai pengujian API Batch ===\n');

        // Langkah 1: Unggah file
        console.log('Langkah 1: Mengunggah file JSONL dengan informasi permintaan...');
        const fileStream = fs.createReadStream('test_model.jsonl');
        const fileObject = await client.files.create({
            file: fileStream,
            purpose: 'batch'
        });
        const fileId = fileObject.id;
        console.log(`✓ File diunggah. ID File: ${fileId}\n`);

        // Langkah 2: Buat tugas batch
        console.log('Langkah 2: Membuat tugas batch...');
        const batch = await client.batches.create({
            input_file_id: fileId,
            endpoint: '/v1/chat/ds-test',  // Gunakan /v1/chat/ds-test untuk model uji
            completion_window: '24h'
        });
        const batchId = batch.id;
        console.log(`✓ Tugas batch dibuat. ID Tugas: ${batchId}\n`);

        // Langkah 3: Periksa status tugas secara berkala
        console.log('Langkah 3: Menunggu tugas selesai...');
        let status = batch.status;
        let pollCount = 0;
        let latestBatch = batch;

        while (!['completed', 'failed', 'expired', 'cancelled'].includes(status)) {
            await sleep(10000); // Tunggu 10 detik
            latestBatch = await client.batches.retrieve(batchId);
            status = latestBatch.status;
            pollCount++;
            console.log(`  [${pollCount}] Status tugas: ${status}`);
        }

        console.log(`\n✓ Tugas selesai. Status akhir: ${status}\n`);

        // Langkah 4: Proses hasilnya
        if (status === 'completed') {
            console.log('Langkah 4: Mengunduh file hasil...');

            // Unduh hasil yang berhasil
            const outputFileId = latestBatch.output_file_id;
            if (outputFileId) {
                console.log(`  ID file output: ${outputFileId}`);
                const content = await client.files.content(outputFileId);
                const text = await content.text();
                console.log('\n--- Hasil yang berhasil (500 karakter pertama) ---');
                console.log(text.substring(0, Math.min(500, text.length)));
                console.log('...\n');
            }

            // Unduh file error (jika ada)
            const errorFileId = latestBatch.error_file_id;
            if (errorFileId) {
                console.log(`  ID file error: ${errorFileId}`);
                const errorContent = await client.files.content(errorFileId);
                const errorText = await errorContent.text();
                console.log('\n--- Informasi error ---');
                console.log(errorText);
            }

            console.log('\n=== Pengujian selesai dengan sukses ===');
        } else if (status === 'failed') {
            console.error('\n✗ Tugas batch gagal');
            if (latestBatch.errors) {
                console.error('Informasi error:', latestBatch.errors);
            }
            console.error('\nUntuk informasi lebih lanjut, lihat https://www.alibabacloud.com/help/en/model-studio/developer-reference/error-code');
        } else {
            console.log(`\nStatus tugas: ${status}`);
        }

    } catch (error) {
        console.error('Terjadi kesalahan:', error.message);
        console.error(error);
    }
}

main();

Java (HTTP)

import java.io.*;
import java.net.HttpURLConnection;
import java.net.URL;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.Scanner;

/**
 * Pengujian API Batch Alibaba Cloud Model Studio - Menggunakan panggilan API HTTP
 *
 * Prasyarat:
 * 1. Pastikan variabel lingkungan DASHSCOPE_API_KEY telah diatur.
 * 2. Siapkan file uji test_model.jsonl di direktori root proyek.
 *
 * Catatan konfigurasi wilayah:
 * - Wilayah Beijing: https://dashscope.aliyuncs.com/compatible-mode/v1
 * - Wilayah Singapura: https://dashscope-intl.aliyuncs.com/compatible-mode/v1
 */
public class BatchAPITest {

    // URL dasar untuk wilayah Singapura
    private static final String BASE_URL = "https://dashscope-intl.aliyuncs.com/compatible-mode/v1";
    // Jika Anda menggunakan wilayah Beijing, ganti BASE_URL di atas dengan:
    // private static final String BASE_URL = "https://dashscope.aliyuncs.com/compatible-mode/v1";

    private static String API_KEY;

    public static void main(String[] args) throws Exception {
        // Dapatkan Kunci API dari variabel lingkungan.
        API_KEY = System.getenv("DASHSCOPE_API_KEY");
        if (API_KEY == null || API_KEY.isEmpty()) {
            System.err.println("Error: Harap atur variabel lingkungan DASHSCOPE_API_KEY.");
            System.exit(1);
        }

        System.out.println("=== Memulai pengujian API Batch ===\n");

        try {
            // Langkah 1: Unggah file
            System.out.println("Langkah 1: Mengunggah file JSONL dengan informasi permintaan...");
            String fileId = uploadFile("test_model.jsonl");
            System.out.println("✓ File diunggah. ID File: " + fileId + "\n");

            // Langkah 2: Buat tugas batch
            System.out.println("Langkah 2: Membuat tugas batch...");
            String batchId = createBatch(fileId);
            System.out.println("✓ Tugas batch dibuat. ID Tugas: " + batchId + "\n");

            // Langkah 3: Periksa status tugas secara berkala
            System.out.println("Langkah 3: Menunggu tugas selesai...");
            String status = "";
            int pollCount = 0;

            while (!isTerminalStatus(status)) {
                Thread.sleep(10000); // Tunggu 10 detik
                String batchInfo = getBatch(batchId);
                status = parseStatus(batchInfo);
                pollCount++;
                System.out.println("  [" + pollCount + "] Status tugas: " + status);

                // Langkah 4: Jika selesai, unduh hasilnya
                if ("completed".equals(status)) {
                    System.out.println("\n✓ Tugas selesai!\n");
                    System.out.println("Langkah 4: Mengunduh file hasil...");

                    String outputFileId = parseOutputFileId(batchInfo);
                    if (outputFileId != null && !outputFileId.isEmpty()) {
                        System.out.println("  ID file output: " + outputFileId);
                        String content = getFileContent(outputFileId);
                        System.out.println("\n--- Hasil yang berhasil (500 karakter pertama) ---");
                        System.out.println(content.substring(0, Math.min(500, content.length)));
                        System.out.println("...\n");
                    }

                    String errorFileId = parseErrorFileId(batchInfo);
                    if (errorFileId != null && !errorFileId.isEmpty() && !"null".equals(errorFileId)) {
                        System.out.println("  ID file error: " + errorFileId);
                        String errorContent = getFileContent(errorFileId);
                        System.out.println("\n--- Informasi error ---");
                        System.out.println(errorContent);
                    }

                    System.out.println("\n=== Pengujian selesai dengan sukses ===");
                    break;
                } else if ("failed".equals(status)) {
                    System.err.println("\n✗ Tugas batch gagal");
                    System.err.println("Informasi tugas: " + batchInfo);
                    System.err.println("\nUntuk informasi lebih lanjut, lihat https://www.alibabacloud.com/help/en/model-studio/developer-reference/error-code");
                    break;
                } else if ("expired".equals(status) || "cancelled".equals(status)) {
                    System.out.println("\nStatus tugas: " + status);
                    break;
                }
            }

        } catch (Exception e) {
            System.err.println("Terjadi kesalahan: " + e.getMessage());
            e.printStackTrace();
        }
    }

    /**
     * Unggah file
     */
    private static String uploadFile(String filePath) throws Exception {
        String boundary = "----WebKitFormBoundary" + System.currentTimeMillis();
        URL url = new URL(BASE_URL + "/files");
        HttpURLConnection conn = (HttpURLConnection) url.openConnection();
        conn.setDoOutput(true);
        conn.setRequestMethod("POST");
        conn.setRequestProperty("Authorization", "Bearer " + API_KEY);
        conn.setRequestProperty("Content-Type", "multipart/form-data; boundary=" + boundary);

        try (DataOutputStream out = new DataOutputStream(conn.getOutputStream())) {
            // Tambahkan field purpose
            out.writeBytes("--" + boundary + "\r\n");
            out.writeBytes("Content-Disposition: form-data; name=\"purpose\"\r\n\r\n");
            out.writeBytes("batch\r\n");

            // Tambahkan file
            out.writeBytes("--" + boundary + "\r\n");
            out.writeBytes("Content-Disposition: form-data; name=\"file\"; filename=\"" + filePath + "\"\r\n");
            out.writeBytes("Content-Type: application/octet-stream\r\n\r\n");

            byte[] fileBytes = Files.readAllBytes(Paths.get(filePath));
            out.write(fileBytes);
            out.writeBytes("\r\n");
            out.writeBytes("--" + boundary + "--\r\n");
        }

        String response = readResponse(conn);
        return parseField(response, "\"id\":\s*\"([^\"]+)\"");
    }

    /**
     * Buat tugas batch
     */
    private static String createBatch(String fileId) throws Exception {
        String jsonBody = String.format(
            "{\"input_file_id\":\"%s\",\"endpoint\":\"/v1/chat/ds-test\",\"completion_window\":\"24h\"}",
            fileId
        );

        String response = sendRequest("POST", "/batches", jsonBody);
        return parseField(response, "\"id\":\s*\"([^\"]+)\"");
    }

    /**
     * Dapatkan informasi tugas batch
     */
    private static String getBatch(String batchId) throws Exception {
        return sendRequest("GET", "/batches/" + batchId, null);
    }

    /**
     * Dapatkan konten file
     */
    private static String getFileContent(String fileId) throws Exception {
        return sendRequest("GET", "/files/" + fileId + "/content", null);
    }

    /**
     * Kirim permintaan HTTP
     */
    private static String sendRequest(String method, String path, String jsonBody) throws Exception {
        URL url = new URL(BASE_URL + path);
        HttpURLConnection conn = (HttpURLConnection) url.openConnection();
        conn.setRequestMethod(method);
        conn.setRequestProperty("Authorization", "Bearer " + API_KEY);

        if (jsonBody != null) {
            conn.setDoOutput(true);
            conn.setRequestProperty("Content-Type", "application/json");
            try (OutputStream os = conn.getOutputStream()) {
                os.write(jsonBody.getBytes("UTF-8"));
            }
        }

        return readResponse(conn);
    }

    /**
     * Baca respons
     */
    private static String readResponse(HttpURLConnection conn) throws Exception {
        int responseCode = conn.getResponseCode();
        InputStream is = (responseCode < 400) ? conn.getInputStream() : conn.getErrorStream();

        try (Scanner scanner = new Scanner(is, "UTF-8").useDelimiter("\\A")) {
            return scanner.hasNext() ? scanner.next() : "";
        }
    }

    /**
     * Parsing field JSON (implementasi sederhana)
     */
    private static String parseField(String json, String regex) {
        java.util.regex.Pattern pattern = java.util.regex.Pattern.compile(regex);
        java.util.regex.Matcher matcher = pattern.matcher(json);
        return matcher.find() ? matcher.group(1) : null;
    }

    private static String parseStatus(String json) {
        return parseField(json, "\"status\":\s*\"([^\"]+)\"");
    }

    private static String parseOutputFileId(String json) {
        return parseField(json, "\"output_file_id\":\s*\"([^\"]+)\"");
    }

    private static String parseErrorFileId(String json) {
        return parseField(json, "\"error_file_id\":\s*\"([^\"]+)\"");
    }

    /**
     * Periksa apakah statusnya terminal
     */
    private static boolean isTerminalStatus(String status) {
        return "completed".equals(status)
            || "failed".equals(status)
            || "expired".equals(status)
            || "cancelled".equals(status);
    }
}

curl (HTTP)

#!/bin/bash
# Pengujian API Batch Alibaba Cloud Model Studio - Menggunakan curl
#
# Prasyarat:
# 1. Pastikan variabel lingkungan DASHSCOPE_API_KEY telah diatur.
# 2. Siapkan file uji test_model.jsonl di direktori saat ini.
#
# Catatan konfigurasi wilayah:
# - Wilayah Beijing: https://dashscope.aliyuncs.com/compatible-mode/v1
# - Wilayah Singapura: https://dashscope-intl.aliyuncs.com/compatible-mode/v1

API_KEY="${DASHSCOPE_API_KEY}"
BASE_URL="https://dashscope-intl.aliyuncs.com/compatible-mode/v1"

# Jika Anda menggunakan wilayah Beijing, ganti BASE_URL dengan:
# BASE_URL="https://dashscope.aliyuncs.com/compatible-mode/v1"

# Periksa Kunci API
if [ -z "$API_KEY" ]; then
    echo "Error: Harap atur variabel lingkungan DASHSCOPE_API_KEY."
    exit 1
fi

echo "=== Memulai pengujian API Batch ==="
echo ""

# Langkah 1: Unggah file
echo "Langkah 1: Mengunggah file JSONL dengan informasi permintaan..."
UPLOAD_RESPONSE=$(curl -s -X POST "${BASE_URL}/files" \
  -H "Authorization: Bearer ${API_KEY}" \
  -F 'file=@test_model.jsonl' \
  -F 'purpose=batch')

FILE_ID=$(echo $UPLOAD_RESPONSE | grep -o '"id":"[^"]*"' | head -1 | cut -d'"' -f4)
echo "✓ File diunggah. ID File: ${FILE_ID}"
echo ""

# Langkah 2: Buat tugas batch
echo "Langkah 2: Membuat tugas batch..."
BATCH_RESPONSE=$(curl -s -X POST "${BASE_URL}/batches" \
  -H "Authorization: Bearer ${API_KEY}" \
  -H "Content-Type: application/json" \
  -d "{\"input_file_id\":\"${FILE_ID}\",\"endpoint\":\"/v1/chat/ds-test\",\"completion_window\":\"24h\"}")

BATCH_ID=$(echo $BATCH_RESPONSE | grep -o '"id":"[^"]*"' | head -1 | cut -d'"' -f4)
echo "✓ Tugas batch dibuat. ID Tugas: ${BATCH_ID}"
echo ""

# Langkah 3: Periksa status tugas secara berkala
echo "Langkah 3: Menunggu tugas selesai..."
STATUS=""
POLL_COUNT=0

while [[ "$STATUS" != "completed" && "$STATUS" != "failed" && "$STATUS" != "expired" && "$STATUS" != "cancelled" ]]; do
    sleep 10
    BATCH_INFO=$(curl -s -X GET "${BASE_URL}/batches/${BATCH_ID}" \
      -H "Authorization: Bearer ${API_KEY}")
    STATUS=$(echo $BATCH_INFO | grep -o '"status":"[^"]*"' | cut -d'"' -f4)
    POLL_COUNT=$((POLL_COUNT + 1))
    echo "  [${POLL_COUNT}] Status tugas: ${STATUS}"
done

echo ""
echo "✓ Tugas selesai. Status akhir: ${STATUS}"
echo ""

# Langkah 4: Unduh hasilnya
if [[ "$STATUS" == "completed" ]]; then
    echo "Langkah 4: Mengunduh file hasil..."

    OUTPUT_FILE_ID=$(echo $BATCH_INFO | grep -o '"output_file_id":"[^"]*"' | cut -d'"' -f4)
    if [[ -n "$OUTPUT_FILE_ID" && "$OUTPUT_FILE_ID" != "null" ]]; then
        echo "  ID file output: ${OUTPUT_FILE_ID}"

        RESULT_CONTENT=$(curl -s -X GET "${BASE_URL}/files/${OUTPUT_FILE_ID}/content" \
          -H "Authorization: Bearer ${API_KEY}")

        echo ""
        echo "--- Hasil yang berhasil (500 karakter pertama) ---"
        echo "${RESULT_CONTENT:0:500}"
        echo "..."
        echo ""
    fi

    ERROR_FILE_ID=$(echo $BATCH_INFO | grep -o '"error_file_id":"[^"]*"' | cut -d'"' -f4)
    if [[ -n "$ERROR_FILE_ID" && "$ERROR_FILE_ID" != "null" ]]; then
        echo "  ID file error: ${ERROR_FILE_ID}"

        ERROR_CONTENT=$(curl -s -X GET "${BASE_URL}/files/${ERROR_FILE_ID}/content" \
          -H "Authorization: Bearer ${API_KEY}")

        echo ""
        echo "--- Informasi error ---"
        echo "${ERROR_CONTENT}"
    fi

    echo ""
    echo "=== Pengujian selesai dengan sukses ==="
elif [[ "$STATUS" == "failed" ]]; then
    echo ""
    echo "✗ Tugas batch gagal"
    echo "Informasi tugas: ${BATCH_INFO}"
    echo ""
    echo "Untuk informasi lebih lanjut, lihat https://www.alibabacloud.com/help/en/model-studio/developer-reference/error-code"
else
    echo ""
    echo "Status tugas: ${STATUS}"
fi

SDK Python OpenAI

import os
from openai import OpenAI

client = OpenAI(
    # Jika Anda belum mengatur variabel lingkungan, ganti baris berikut dengan: api_key="sk-xxx". Namun jangan hard code Kunci API Anda dalam kode produksi. Hard coding meningkatkan risiko eksposur.
    # Kunci API berbeda antara wilayah Singapura dan Beijing.
    api_key=os.getenv("DASHSCOPE_API_KEY"), 
    # URL dasar untuk wilayah Beijing. Untuk model wilayah Singapura, gunakan: https://dashscope-intl.aliyuncs.com/compatible-mode/v1
    # Catatan: Ubah Kunci API Anda saat Anda mengganti wilayah.
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)

batch = client.batches.create(
    input_file_id="file-batch-xxx",  # ID yang dikembalikan setelah mengunggah file
    endpoint="/v1/chat/completions",  # Untuk model text embedding, gunakan "/v1/embeddings". Untuk model uji seperti batch-test-model, gunakan "/v1/chat/ds-test". Untuk model lainnya, gunakan "/v1/chat/completions".
    completion_window="24h", 
    metadata={
            "ds_batch_finish_callback": "https://xxx/xxx"
          }
)
print(batch)

curl (HTTP)

curl -X POST --location "https://dashscope.aliyuncs.com/compatible-mode/v1/batches" \
    -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
          "input_file_id": "file-batch-xxxxx",
          "endpoint": "/v1/chat/completions",
          "completion_window": "24h",
          "metadata": {
            "ds_batch_finish_callback": "https://xxx/xxx"
          }
        }'