Alibaba Cloud Model Studio:Structured output

from openai import OpenAI
import os

client = OpenAI(
    # Kunci API berbeda berdasarkan wilayah. Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan: api_key="sk-xxx"
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # Jika Anda menggunakan model wilayah Beijing, ganti base_url dengan: https://dashscope.aliyuncs.com/compatible-mode/v1
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="qwen-flash",
    messages=[
        {
            "role": "system",
            "content": "Extract the user's name and age, and return them in JSON format"
        },
        {
            "role": "user",
            "content": "Hi everyone, my name is Alex Brown, I'm 34 years old, my email is alexbrown@example.com, and I enjoy playing basketball and traveling", 
        },
    ],
    response_format={"type": "json_object"}
)

json_string = completion.choices[0].message.content
print(json_string)

Respons

{
  "Name": "Alex Brown",
  "Age": 34
}

import OpenAI from "openai";

const openai = new OpenAI({
    // Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan: apiKey: "sk-xxx"
    apiKey: process.env.DASHSCOPE_API_KEY,
    // Untuk model wilayah Beijing, ganti baseURL dengan: https://dashscope.aliyuncs.com/compatible-mode/v1
    baseURL: "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
});

const completion = await openai.chat.completions.create({
    model: "qwen-flash",
    messages: [
        {
            role: "system",
            content: "Extract the user's name and age, and return them in JSON format"
        },
        {
            role: "user",
            content: "Hi everyone, my name is Alex Brown, I'm 34 years old, my email is alexbrown@example.com, and I enjoy playing basketball and traveling"
        }
    ],
    response_format: {
        type: "json_object"
    }
});

const jsonString = completion.choices[0].message.content;
console.log(jsonString);

Respons

{
  "name": "Alex Brown",
  "age": 34
}

# ======= Penting =======
# Kunci API berbeda berdasarkan wilayah. Untuk mendapatkan kunci API, kunjungi: https://www.alibabacloud.com/help/en/model-studio/get-api-key
# Jika Anda menggunakan model wilayah Beijing, ganti URL dengan: https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions
# === Hapus komentar ini sebelum eksekusi ===
curl -X POST https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
    "model": "qwen-plus",
    "messages": [
        {
            "role": "system",
            "content": "You need to extract the name (string), age (string), and email (string). Output the result as a JSON string. Do not include any other irrelevant content.\nExamples:\nQ: My name is Zhang San, I am 25 years old, and my email is zhangsan@example.com\nA: {\"name\":\"Zhang San\",\"age\":\"25 years old\",\"email\":\"zhangsan@example.com\"}\nQ: My name is Li Si, I am 30 years old, and my email is lisi@example.com\nA: {\"name\":\"Li Si\",\"age\":\"30 years old\",\"email\":\"lisi@example.com\"}\nQ: My name is Wang Wu, my email is wangwu@example.com, and I am 40 years old\nA: {\"name\":\"Wang Wu\",\"age\":\"40 years old\",\"email\":\"wangwu@example.com\"}"
        },
        {
            "role": "user", 
            "content": "Hello everyone, my name is Alex Brown, I am 34 years old, and my email is alexbrown@example.com"
        }
    ],
    "response_format": {
        "type": "json_object"
    }
}'

Respons

{
    "choices": [
        {
            "message": {
                "role": "assistant",
                "content": "{\"name\":\"Alex Brown\",\"age\":\"34 years old\"}"
            },
            "finish_reason": "stop",
            "index": 0,
            "logprobs": null
        }
    ],
    "object": "chat.completion",
    "usage": {
        "prompt_tokens": 207,
        "completion_tokens": 20,
        "total_tokens": 227,
        "prompt_tokens_details": {
            "cached_tokens": 0
        }
    },
    "created": 1756455080,
    "system_fingerprint": null,
    "model": "qwen-plus",
    "id": "chatcmpl-624b665b-fb93-99e7-9ebd-bb6d86d314d2"
}

import os
import dashscope
# Untuk model wilayah Beijing, ganti URL dengan: https://dashscope.aliyuncs.com/api/v1
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

messages=[
    {
        "role": "system",
        "content": "Extract the user's name and age, and return them in JSON format"
    },
    {
        "role": "user",
        "content": "Hi everyone, my name is Alex Brown, I'm 34 years old, my email is alexbrown@example.com, and I enjoy playing basketball and traveling", 
    },
]
response = dashscope.Generation.call(
    # Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan: api_key="sk-xxx" (Kunci API Alibaba Cloud Model Studio),
    api_key=os.getenv('DASHSCOPE_API_KEY'),
    model="qwen-flash", 
    messages=messages,
    result_format='message',
    response_format={'type': 'json_object'}
    )
json_string = response.output.choices[0].message.content
print(json_string)

Respons

{
  "name": "Alex Brown",
  "age": 34
}

Respons

{
  "name": "Alex Brown",
  "age": 34
}

# ======= Catatan penting =======
# Untuk model wilayah Beijing, ganti URL dengan: https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation
# Kunci API berbeda berdasarkan wilayah. Dapatkan kunci API: https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# === Hapus komentar ini sebelum menjalankan ===

curl -X POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
    "model": "qwen-flash",
    "input": {
        "messages": [
            {
                "role": "system",
                "content": "Extract the user's name and age, and return them in JSON format"
            },
            {
                "role": "user", 
                "content": "Hi everyone, my name is Alex Brown, I'm 34 years old, my email is alexbrown@example.com, and I enjoy playing basketball and traveling"
            }
        ]
    },
    "parameters": {
        "result_format": "message",
        "response_format": {
            "type": "json_object"
        }
    }
}'

Respons

{
  "name": "Alex Brown",
  "age": 34
}

import OpenAI from "openai";

const openai = new OpenAI({
  // Kunci API berbeda berdasarkan wilayah. Dapatkan kunci API: https://www.alibabacloud.com/help/zh/model-studio/get-api-key
  // Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan: apiKey: "sk-xxx" (Kunci API Model Studio)
  apiKey: process.env.DASHSCOPE_API_KEY,
  // Untuk model wilayah Beijing, ganti base_url dengan https://dashscope.aliyuncs.com/compatible-mode/v1
  baseURL: "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
});

async function main() {
  const response = await openai.chat.completions.create({
    model: "qwen3-vl-plus",
    messages: [{
        role: "system",
        content: [{
          type: "text",
          text: "You are a helpful assistant."
        }]
      },
      {
        role: "user",
        content: [{
            type: "image_url",
            image_url: {
              "url": "http://duguang-labelling.oss-cn-shanghai.aliyuncs.com/demo_ocr/receipt_zh_demo.jpg"
            }
          },
          {
            type: "text",
            text: "Extract ticket (array type, including travel_date, trains, seat_num, arrival_site, price) and invoice information (array type, including invoice_code and invoice_number) from the image. Output a JSON containing both ticket and invoice arrays"
          }
        ]
      }
    ],
    response_format: {type: "json_object"}
  });
  console.log(response.choices[0].message.content);
}

main()

Respons

{
  "ticket": [
    {
      "travel_date": "2013-06-29",
      "trains": "stream",
      "seat_num": "371",
      "arrival_site": "Development Zone",
      "price": "8.00"
    }
  ],
  "invoice": [
    {
      "invoice_code": "221021325353",
      "invoice_number": "10283819"
    }
  ]
}

from openai import OpenAI
import os
import json
import textwrap  # Menangani indentasi untuk string multi-baris guna meningkatkan keterbacaan kode

# Respons contoh yang telah didefinisikan sebelumnya untuk menunjukkan format output yang diharapkan kepada model
# Contoh 1: Respons lengkap dengan semua field
example1_response = json.dumps(
    {
        "info": {"name": "Zhang San", "age": "25 years old", "email": "zhangsan@example.com"},
        "hobby": ["singing"]
    },
    ensure_ascii=False
)
# Contoh 2: Respons dengan beberapa hobi
example2_response = json.dumps(
    {
        "info": {"name": "Li Si", "age": "30 years old", "email": "lisi@example.com"},
        "hobby": ["dancing", "swimming"]
    },
    ensure_ascii=False
)
# Contoh 3: Respons tanpa field hobby (hobby opsional)
example3_response = json.dumps(
    {
        "info": {"name": "Zhao Liu", "age": "28 years old", "email": "zhaoliu@example.com"}
    },
    ensure_ascii=False
)
# Contoh 4: Respons lain tanpa field hobby
example4_response = json.dumps(
    {
        "info": {"name": "Sun Qi", "age": "35 years old", "email": "sunqi@example.com"}
    },
    ensure_ascii=False
)

# Inisialisasi klien OpenAI
client = OpenAI(
    # Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan: api_key="sk-xxx"
    # Kunci API berbeda berdasarkan wilayah. Dapatkan kunci API: https://www.alibabacloud.com/help/en/model-studio/get-api-key
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # Ini adalah URL dasar wilayah Beijing. Jika Anda menggunakan model wilayah Singapura, ganti URL dasar dengan: https://dashscope-intl.aliyuncs.com/compatible-mode/v1
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)

# dedent menghapus spasi awal umum dari setiap baris, memungkinkan string di-indentasi dengan rapi dalam kode tanpa menyertakan spasi ekstra saat runtime
system_prompt = textwrap.dedent(f"""\
    Extract personal information from the user input and output it in the specified JSON Schema format:

    [Output format requirements]
    The output must strictly follow this JSON structure:
    {{
      "info": {{
        "name": "string type, required field, user's name",
        "age": "string type, required field, format 'number years old', e.g., '25 years old'",
        "email": "string type, required field, standard email format, e.g., 'user@example.com'"
      }},
      "hobby": ["string array type, optional field, contains all user hobbies; omit entirely if not mentioned"]
    }}

    [Field extraction rules]
    1. name: Identify the user's name from the text, must extract
    2. age: Identify age information, convert to 'number years old' format, must extract
    3. email: Identify email address, keep original format, must extract
    4. hobby: Identify user hobbies, output as string array; omit hobby field entirely if hobbies are not mentioned

    [Reference examples]
    Example 1 (with hobby):
    Q: My name is Zhang San, I'm 25 years old, my email is zhangsan@example.com, and my hobby is singing
    A: {example1_response}

    Example 2 (with multiple hobbies):
    Q: My name is Li Si, I'm 30 years old, my email is lisi@example.com, and I enjoy dancing and swimming
    A: {example2_response}

    Example 3 (without hobby):
    Q: My name is Zhao Liu, I'm 28 years old, and my email is zhaoliu@example.com
    A: {example3_response}

    Example 4 (without hobby):
    Q: I'm Sun Qi, 35 years old, and my email is sunqi@example.com
    A: {example4_response}

    Extract information and output JSON strictly according to the above format and rules. Do not include the hobby field if the user doesn't mention hobbies.\
""")

# Panggil API LLM untuk ekstraksi informasi
completion = client.chat.completions.create(
    model="qwen-plus",
    messages=[
        {
            "role": "system",
            "content": system_prompt
        },
        {
            "role": "user",
            "content": "Hi everyone, my name is Alex Brown, I'm 34 years old, my email is alexbrown@example.com, and I enjoy playing basketball and traveling", 
        },
    ],
    response_format={"type": "json_object"},  # Tentukan pengembalian format JSON
)

# Ekstrak dan cetak hasil JSON yang dihasilkan model
json_string = completion.choices[0].message.content
print(json_string)

Respons

{
  "info": {
    "name": "Alex Brown",
    "age": "34 years old",
    "email": "alexbrown@example.com"
  },
  "hobby": ["Basketball", "Traveling"]  
}

import OpenAI from "openai";

// Respons contoh yang telah didefinisikan sebelumnya (untuk menunjukkan format output yang diharapkan kepada model)
// Contoh 1: Respons lengkap dengan semua field
const example1Response = JSON.stringify({
    info: { name: "Zhang San", age: "25 years old", email: "zhangsan@example.com" },
    hobby: ["singing"]
}, null, 2);

// Contoh 2: Respons dengan beberapa hobi
const example2Response = JSON.stringify({
    info: { name: "Li Si", age: "30 years old", email: "lisi@example.com" },
    hobby: ["dancing", "swimming"]
}, null, 2);

// Contoh 3: Respons tanpa field hobby (hobby opsional)
const example3Response = JSON.stringify({
    info: { name: "Zhao Liu", age: "28 years old", email: "zhaoliu@example.com" }
}, null, 2);

// Contoh 4: Respons lain tanpa field hobby
const example4Response = JSON.stringify({
    info: { name: "Sun Qi", age: "35 years old", email: "sunqi@example.com" }
}, null, 2);

// Inisialisasi konfigurasi klien OpenAI
const openai = new OpenAI({
    // Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan: apiKey: "sk-xxx" (Kunci API Alibaba Cloud Model Studio),
    // Kunci API berbeda berdasarkan wilayah. Dapatkan kunci API: https://www.alibabacloud.com/help/en/model-studio/get-api-key
    apiKey: process.env.DASHSCOPE_API_KEY,
    // Ini adalah URL dasar wilayah Beijing. Jika Anda menggunakan model wilayah Singapura, ganti URL dasar dengan: https://dashscope-intl.aliyuncs.com/compatible-mode/v1
    baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
});

// Buat permintaan penyelesaian chat menggunakan prompt terstruktur untuk meningkatkan akurasi output
const completion = await openai.chat.completions.create({
    model: "qwen-plus",
    messages: [
        {
            role: "system",
            content: `Extract personal information from the user input and output it in the specified JSON Schema format:

[Output format requirements]
The output must strictly follow this JSON structure:
{
  "info": {
    "name": "string type, required field, user's name",
    "age": "string type, required field, format 'number years old', e.g., '25 years old'",
    "email": "string type, required field, standard email format, e.g., 'user@example.com'"
  },
  "hobby": ["string array type, optional field, contains all user hobbies; omit entirely if not mentioned"]
}

[Field extraction rules]
1. name: Identify the user's name from the text, must extract
2. age: Identify age information, convert to 'number years old' format, must extract
3. email: Identify email address, keep original format, must extract
4. hobby: Identify user hobbies, output as string array; omit hobby field entirely if hobbies are not mentioned

[Reference examples]
Example 1 (with hobby):
Q: My name is Zhang San, I'm 25 years old, my email is zhangsan@example.com, and my hobby is singing
A: ${example1Response}

Example 2 (with multiple hobbies):
Q: My name is Li Si, I'm 30 years old, my email is lisi@example.com, and I enjoy dancing and swimming
A: ${example2Response}

Example 3 (without hobby):
Q: My name is Zhao Liu, I'm 28 years old, and my email is zhaoliu@example.com
A: ${example3Response}

Example 4 (without hobby):
Q: I'm Sun Qi, 35 years old, and my email is sunqi@example.com
A: ${example4Response}

Extract information and output JSON strictly according to the above format and rules. Do not include the hobby field if the user doesn't mention hobbies.`
        },
        {
            role: "user",
            content: "Hi everyone, my name is Alex Brown, I'm 34 years old, my email is alexbrown@example.com, and I enjoy playing basketball and traveling"
        }
    ],
    response_format: {
        type: "json_object"
    }
});

// Ekstrak dan cetak hasil JSON yang dihasilkan model
const jsonString = completion.choices[0].message.content;
console.log(jsonString);

Respons

{
  "info": {
    "name": "Alex Brown",
    "age": "34 years old",
    "email": "alexbrown@example.com"
  },
  "hobby": [
    "playing basketball",
    "traveling"
  ]
}

import os
import json
import dashscope

# Jika Anda menggunakan model wilayah Singapura, hapus komentar pada baris berikut
# dashscope.base_http_api_url = "https://dashscope-intl.aliyuncs.com/api/v1"

# Respons contoh yang telah didefinisikan sebelumnya (untuk menunjukkan format output yang diharapkan kepada model)
example1_response = json.dumps(
    {
        "info": {"name": "Zhang San", "age": "25 years old", "email": "zhangsan@example.com"},
        "hobby": ["singing"]
    },
    ensure_ascii=False
)
example2_response = json.dumps(
    {
        "info": {"name": "Li Si", "age": "30 years old", "email": "lisi@example.com"},
        "hobby": ["dancing", "swimming"]
    },
    ensure_ascii=False
)
example3_response = json.dumps(
    {
        "info": {"name": "Wang Wu", "age": "40 years old", "email": "wangwu@example.com"},
        "hobby": ["Rap", "basketball"]
    },
    ensure_ascii=False
)

messages=[
        {
            "role": "system",
            "content": f"""Extract personal information from the user input and output it in the specified JSON Schema format:

[Output format requirements]
The output must strictly follow this JSON structure:
{{
  "info": {{
    "name": "string type, required field, user's name",
    "age": "string type, required field, format 'number years old', e.g., '25 years old'",
    "email": "string type, required field, standard email format, e.g., 'user@example.com'"
  }},
  "hobby": ["string array type, optional field, contains all user hobbies; omit entirely if not mentioned"]
}}

[Field extraction rules]
1. name: Identify the user's name from the text, must extract
2. age: Identify age information, convert to 'number years old' format, must extract
3. email: Identify email address, keep original format, must extract
4. hobby: Identify user hobbies, output as string array; omit hobby field entirely if hobbies are not mentioned

[Reference examples]
Example 1 (with hobby):
Q: My name is Zhang San, I'm 25 years old, my email is zhangsan@example.com, and my hobby is singing
A: {example1_response}

Example 2 (with multiple hobbies):
Q: My name is Li Si, I'm 30 years old, my email is lisi@example.com, and I enjoy dancing and swimming
A: {example2_response}

Example 3 (with multiple hobbies):
Q: My email is wangwu@example.com, I'm 40 years old, my name is Wang Wu, and I can Rap and play basketball
A: {example3_response}

Extract information and output JSON strictly according to the above format and rules. Do not include the hobby field if the user doesn't mention hobbies."""
        },
        {
            "role": "user",
            "content": "Hi everyone, my name is Alex Brown, I'm 34 years old, my email is alexbrown@example.com, and I enjoy playing basketball and traveling", 
        },
    ]
response = dashscope.Generation.call(
    # Jika Anda belum mengonfigurasi variabel lingkungan, ganti baris berikut dengan: api_key="sk-xxx" (Kunci API Alibaba Cloud Model Studio),
    api_key=os.getenv('DASHSCOPE_API_KEY'),
    model="qwen-plus", 
    messages=messages,
    result_format='message',
    response_format={'type': 'json_object'}
    )
json_string = response.output.choices[0].message.content
print(json_string)

Respons

{
  "info": {
    "name": "Alex Brown",
    "age": "34 years old",
    "email": "alexbrown@example.com"
  },
  "hobby": [
    "playing basketball",
    "traveling"
  ]
}

Respons

{
  "info": {
    "name": "Alex Brown",
    "age": "34 years old",
    "email": "alexbrown@example.com"
  },
  "hobby": [
    "Playing basketball",
    "Traveling"
  ]
}