OpenAI-compatible - Batch (file input)

OpenAI Python SDK

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

# Initialize the client
client = OpenAI(
    # If no environment variable is set, replace the line below with api_key="sk-xxx". But never hard-code in production to reduce leak risk.
    # API keys differ between Singapore and Beijing regions.
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # Beijing region's base_url. For Singapore, use: https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1
    # Note: Update the API key when switching regions.
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1"  # The base_url for the Model Studio service
)

def upload_file(file_path):
    print(f"Uploading the JSONL file that contains request information...")
    file_object = client.files.create(file=Path(file_path), purpose="batch")
    print(f"File uploaded successfully. File ID: {file_object.id}\n")
    return file_object.id

def create_batch_job(input_file_id):
    print(f"Creating a batch task based on the file ID...")
    # Note: The value of the endpoint parameter here must match the url field in the input file.
    # For the test model (batch-test-model), use /v1/chat/ds-test.
    # For text embedding models, use /v1/embeddings.
    # For other models, use /v1/chat/completions.
    batch = client.batches.create(input_file_id=input_file_id, endpoint="/v1/chat/ds-test", completion_window="24h")
    print(f"Batch task created. Batch task ID: {batch.id}\n")
    return batch.id

def check_job_status(batch_id):
    print(f"Checking the batch task status...")
    batch = client.batches.retrieve(batch_id=batch_id)
    print(f"Batch task status: {batch.status}\n")
    return batch.status

def get_output_id(batch_id):
    print(f"Getting the output file ID for successful requests in the batch task...")
    batch = client.batches.retrieve(batch_id=batch_id)
    print(f"Output file ID: {batch.output_file_id}\n")
    return batch.output_file_id

def get_error_id(batch_id):
    print(f"Getting the output file ID for failed requests in the batch task...")
    batch = client.batches.retrieve(batch_id=batch_id)
    print(f"Error file ID: {batch.error_file_id}\n")
    return batch.error_file_id

def download_results(output_file_id, output_file_path):
    print(f"Printing and downloading the results of successful requests from the batch task...")
    content = client.files.content(output_file_id)
    # Print some content for testing
    print(f"Printing the first 1,000 characters of the successful request results: {content.text[:1000]}...\n")
    # Save the result file locally
    content.write_to_file(output_file_path)
    print(f"The complete output results have been saved to the local output file result.jsonl\n")

def download_errors(error_file_id, error_file_path):
    print(f"Printing and downloading the failure information for requests from the batch task...")
    content = client.files.content(error_file_id)
    # Print some content for testing
    print(f"Printing the first 1,000 characters of the request failure information: {content.text[:1000]}...\n")
    # Save the error information file locally
    content.write_to_file(error_file_path)
    print(f"The complete request failure information has been saved to the local error file error.jsonl\n")

def main():
    # File paths
    input_file_path = "test_model.jsonl"  # You can replace this with your input file path
    output_file_path = "result.jsonl"  # You can replace this with your output file path
    error_file_path = "error.jsonl"  # You can replace this with your error file path
    try:
        # Step 1: Upload the JSONL file containing request information to get the input file ID. To use an OSS file, replace the next line with: input_file_id = "actual_OSS_file_URL_or_resource_identifier"
        input_file_id = upload_file(input_file_path)
        # Step 2: Create a batch task based on the input file ID
        batch_id = create_batch_job(input_file_id)
        # Step 3: Check the batch task status until it is finished
        status = ""
        while status not in ["completed", "failed", "expired", "cancelled"]:
            status = check_job_status(batch_id)
            print(f"Waiting for the task to complete...")
            time.sleep(10)  # Wait 10 seconds and then query the status again
        # If the task fails, print the error message and exit
        if status == "failed":
            batch = client.batches.retrieve(batch_id)
            print(f"Batch task failed. Error message: {batch.errors}\n")
            print(f"For more information, see Error codes: https://help.aliyun.com/en/model-studio/developer-reference/error-code
            return
        # Step 4: Download results: If the output file ID is not empty, print the first 1,000 characters of the successful request results and download the complete results to a local output file.
        # If the error file ID is not empty, print the first 1,000 characters of the request failure information and download the complete information to a local error file.
        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"For more information, see Error codes: https://help.aliyun.com/en/model-studio/developer-reference/error-code
    except Exception as e:
        print(f"An error occurred: {e}")
        print(f"For more information, see Error codes: https://help.aliyun.com/en/model-studio/developer-reference/error-code

if __name__ == "__main__":
    main()

OpenAI Node.js SDK

/**
 * Model Studio Batch API Test - Using OpenAI Node.js SDK
 *
 * Install dependencies: npm install openai
 * Run: node test-nodejs.js
 */

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

// Base URL for the Beijing region
const BASE_URL = 'https://dashscope.aliyuncs.com/compatible-mode/v1';
// For Singapore, use: const BASE_URL = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1';

const apiKey = process.env.DASHSCOPE_API_KEY;
if (!apiKey) {
    console.error('Error: Please set the environment variable DASHSCOPE_API_KEY');
    process.exit(1);
}

// Initialize the client
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('=== Start Batch API Test ===\n');

        // Step 1: Upload file
        console.log('Step 1: Uploading the JSONL file that contains request information...');
        const fileStream = fs.createReadStream('test_model.jsonl');
        const fileObject = await client.files.create({
            file: fileStream,
            purpose: 'batch'
        });
        const fileId = fileObject.id;
        console.log(`✓ File uploaded successfully, File ID: ${fileId}\n`);

        // Step 2: Create batch task
        console.log('Step 2: Creating batch task...');
        const batch = await client.batches.create({
            input_file_id: fileId,
            endpoint: '/v1/chat/ds-test',  // Use /v1/chat/ds-test for the test model
            completion_window: '24h'
        });
        const batchId = batch.id;
        console.log(`✓ Batch task created successfully, Task ID: ${batchId}\n`);

        // Step 3: Poll task status
        console.log('Step 3: Waiting for task to complete...');
        let status = batch.status;
        let pollCount = 0;
        let latestBatch = batch;

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

        console.log(`\n✓ Task completed, final status: ${status}\n`);

        // Step 4: Process results
        if (status === 'completed') {
            console.log('Step 4: Downloading result file...');

            // Download successful results
            const outputFileId = latestBatch.output_file_id;
            if (outputFileId) {
                console.log(`  Output file ID: ${outputFileId}`);
                const content = await client.files.content(outputFileId);
                const text = await content.text();
                console.log('\n--- Successful results (first 500 characters) ---');
                console.log(text.substring(0, Math.min(500, text.length)));
                console.log('...\n');
            }

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

            console.log('\n=== Test completed successfully ===');
        } else if (status === 'failed') {
            console.error('\n✗ Batch task failed');
            if (latestBatch.errors) {
                console.error('Error message:', latestBatch.errors);
            }
            console.error('\nSee error code documentation: https://help.aliyun.com/en/model-studio/developer-reference/error-code
        } else {
            console.log(`\nTask status: ${status}`);
        }

    } catch (error) {
        console.error('An error occurred:', 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;

/**
 * Model Studio Batch API Test - Using HTTP API
 *
 * Prerequisites:
 * 1. Ensure the environment variable DASHSCOPE_API_KEY is set
 * 2. Prepare the test file test_model.jsonl (in the project root directory)
 *
 * Region configuration:
 * - Beijing region: https://dashscope.aliyuncs.com/compatible-mode/v1
 * - Singapore region: https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1
 */
public class BatchAPITest {

    // Base URL for the Beijing region (default)
    private static final String BASE_URL = "https://dashscope.aliyuncs.com/compatible-mode/v1";
    // For Singapore, use: private static final String BASE_URL = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1";

    private static String API_KEY;

    public static void main(String[] args) throws Exception {
        // Get API Key from environment variable
        API_KEY = System.getenv("DASHSCOPE_API_KEY");
        if (API_KEY == null || API_KEY.isEmpty()) {
            System.err.println("Error: Please set the environment variable DASHSCOPE_API_KEY");
            System.exit(1);
        }

        System.out.println("=== Start Batch API Test ===\n");

        try {
            // Step 1: Upload file
            System.out.println("Step 1: Uploading the JSONL file that contains request information...");
            String fileId = uploadFile("test_model.jsonl");
            System.out.println("✓ File uploaded successfully, File ID: " + fileId + "\n");

            // Step 2: Create batch task
            System.out.println("Step 2: Creating batch task...");
            String batchId = createBatch(fileId);
            System.out.println("✓ Batch task created successfully, Task ID: " + batchId + "\n");

            // Step 3: Poll task status
            System.out.println("Step 3: Waiting for task to complete...");
            String status = "";
            int pollCount = 0;

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

                // Step 4: If completed, download results
                if ("completed".equals(status)) {
                    System.out.println("\n✓ Task completed!\n");
                    System.out.println("Step 4: Downloading result file...");

                    String outputFileId = parseOutputFileId(batchInfo);
                    if (outputFileId != null && !outputFileId.isEmpty()) {
                        System.out.println("  Output file ID: " + outputFileId);
                        String content = getFileContent(outputFileId);
                        System.out.println("\n--- Successful results (first 500 characters) ---");
                        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("  Error file ID: " + errorFileId);
                        String errorContent = getFileContent(errorFileId);
                        System.out.println("\n--- Error information ---");
                        System.out.println(errorContent);
                    }

                    System.out.println("\n=== Test completed successfully ===");
                    break;
                } else if ("failed".equals(status)) {
                    System.err.println("\n✗ Batch task failed");
                    System.err.println("Task info: " + batchInfo);
                    System.err.println("\nSee error code documentation: https://help.aliyun.com/en/model-studio/developer-reference/error-code
                    break;
                } else if ("expired".equals(status) || "cancelled".equals(status)) {
                    System.out.println("\nTask status: " + status);
                    break;
                }
            }

        } catch (Exception e) {
            System.err.println("An error occurred: " + e.getMessage());
            e.printStackTrace();
        }
    }

    /**
     * Upload 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())) {
            // Add purpose field
            out.writeBytes("--" + boundary + "\r\n");
            out.writeBytes("Content-Disposition: form-data; name=\"purpose\"\r\n\r\n");
            out.writeBytes("batch\r\n");

            // Add 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*\"([^\"]+)\"");
    }

    /**
     * Create batch task
     */
    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*\"([^\"]+)\"");
    }

    /**
     * Get batch task info
     */
    private static String getBatch(String batchId) throws Exception {
        return sendRequest("GET", "/batches/" + batchId, null);
    }

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

    /**
     * Send HTTP request
     */
    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);
    }

    /**
     * Read response
     */
    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() : "";
        }
    }

    /**
     * Parse JSON field (simple implementation)
     */
    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*\"([^\"]+)\"");
    }

    /**
     * Check if status is terminal
     */
    private static boolean isTerminalStatus(String status) {
        return "completed".equals(status)
            || "failed".equals(status)
            || "expired".equals(status)
            || "cancelled".equals(status);
    }
}

curl (HTTP)

#!/bin/bash
# Model Studio Batch API Test - Using curl
#
# Prerequisites:
# 1. Ensure the environment variable DASHSCOPE_API_KEY is set
# 2. Prepare the test file test_model.jsonl (in the current directory)
#
# Region configuration:
# - Beijing region: https://dashscope.aliyuncs.com/compatible-mode/v1
# - Singapore region: https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1

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

# For Singapore, use: BASE_URL="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"

# Check API Key
if [ -z "$API_KEY" ]; then
    echo "Error: Please set the environment variable DASHSCOPE_API_KEY"
    exit 1
fi

echo "=== Start Batch API Test ==="
echo ""

# Step 1: Upload file
echo "Step 1: Uploading the JSONL file that contains request information..."
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 uploaded successfully, File ID: ${FILE_ID}"
echo ""

# Step 2: Create batch task
echo "Step 2: Creating batch task..."
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 "✓ Batch task created successfully, Task ID: ${BATCH_ID}"
echo ""

# Step 3: Poll task status
echo "Step 3: Waiting for task to complete..."
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}] Task status: ${STATUS}"
done

echo ""
echo "✓ Task completed, final status: ${STATUS}"
echo ""

# Step 4: Download results
if [[ "$STATUS" == "completed" ]]; then
    echo "Step 4: Downloading result file..."

    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 "  Output file ID: ${OUTPUT_FILE_ID}"

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

        echo ""
        echo "--- Successful results (first 500 characters) ---"
        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 "  Error file ID: ${ERROR_FILE_ID}"

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

        echo ""
        echo "--- Error information ---"
        echo "${ERROR_CONTENT}"
    fi

    echo ""
    echo "=== Test completed successfully ==="
elif [[ "$STATUS" == "failed" ]]; then
    echo ""
    echo "✗ Batch task failed"
    echo "Task info: ${BATCH_INFO}"
    echo ""
    echo "See error code documentation: https://help.aliyun.com/en/model-studio/developer-reference/error-code
else
    echo ""
    echo "Task status: ${STATUS}"
fi

OpenAI Python SDK

import os
from openai import OpenAI

client = OpenAI(
    # If no environment variable is set, use api_key="sk-xxx" (not in production - risk of leaks).
    # API keys differ between regions.
    api_key=os.getenv("DASHSCOPE_API_KEY"), 
    # Beijing region's base_url. For Singapore, use: https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1 and update the API key.
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)

batch = client.batches.create(
    input_file_id="file-batch-xxx",  # The ID returned after uploading the file
    endpoint="/v1/chat/completions",  # For text embedding models, enter "/v1/embeddings". For the test model batch-test-model, enter /v1/chat/ds-test. For other models, enter /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"
          }
        }'