Alibaba Cloud Model Studio:Data mining (Qwen-Doc-Turbo)

import os
import dashscope

response = dashscope.Generation.call(
    api_key=os.getenv('DASHSCOPE_API_KEY'), # If you have not configured the environment variable, replace this with your API key
    model='qwen-doc-turbo',
    messages=[
    {"role": "system","content": "You are a helpful assistant."},
    {
        "role": "user",
        "content": [
            {
                "type": "text",
                "text": "From this customer feedback report, extract all feedback information and organize it into a standard JSON array. Each object must include the following: feedback_id (string), product_name (string), user_name (string), rating_score (an integer from 1 to 5), feedback_type (string), and summary (a Chinese summary of no more than 30 characters)."
            },
            {
                "type": "doc_url",
                "doc_url": [
                    "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250910/gokhyx/%E5%AE%A2%E6%88%B7%E5%8F%8D%E9%A6%88%E6%8A%A5%E5%91%8A.txt"
                ],
                "file_parsing_strategy": "auto"
            }
        ]
    }]
)
try:
    if response.status_code == 200:
        print(response.output.choices[0].message.content)
    else:
        print(f"Request failed, status code: {response.status_code}")
        print(f"Error code: {response.code}")
        print(f"Error message: {response.message}")
        print("For more information, see https://www.alibabacloud.com/help/en/model-studio/developer-reference/error-codes")
except Exception as e:
    print(f"An error occurred: {e}")
    print("For more information, see https://www.alibabacloud.com/help/en/model-studio/developer-reference/error-codes")

curl --location 'https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer $DASHSCOPE_API_KEY' \
--header 'X-DashScope-SSE: enable' \
--data '{
    "model": "qwen-doc-turbo",
    "input": {
        "messages": [
                {
                    "role": "system",
                    "content": "you are a helpful assistant."
                },
                {
                    "role": "user",
                    "content": [
                        {
                            "type": "text",
                            "text": "From this customer feedback report, extract all feedback information and organize it into a standard JSON array. Each object must include the following: feedback_id (string), product_name (string), user_name (string), rating_score (an integer from 1 to 5), feedback_type (string), and summary (a Chinese summary of no more than 30 characters)."
                        },
                        {
                            "type": "doc_url",
                            "doc_url": [
                                "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250910/gokhyx/%E5%AE%A2%E6%88%B7%E5%8F%8D%E9%A6%88%E6%8A%A5%E5%91%8A.txt"
                            ],
                            "file_parsing_strategy": "auto"
                        }
                    ]
                }
            ]
    }
}'

import os
from openai import OpenAI, BadRequestError

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"), # If you have not configured the environment variable, replace this with your API key
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)

try:
    completion = client.chat.completions.create(
        model="qwen-doc-turbo",
        messages=[
            {'role': 'system', 'content': 'You are a helpful assistant.'},
            {'role': 'system', 'content': 'Feedback ID: 001 User: Zhang Wei (vip_zhang@example.com) Product: Model Studio AI-Writer Pro...'},
            {'role': 'user', 'content': 'From this customer feedback report, extract all feedback information and organize it into a standard JSON array. Each object must include the following: feedback_id (string), product_name (string), user_name (string), rating_score (an integer from 1 to 5), feedback_type (string), and summary (a Chinese summary of no more than 30 characters).'}
        ],
        # This code example uses streaming output to clearly and intuitively show the model's output process. For non-streaming output examples, see https://www.alibabacloud.com/help/en/model-studio/user-guide/text-generation
        stream=True,
        stream_options={"include_usage": True}
    )

    full_content = ""
    for chunk in completion:
        if chunk.choices and chunk.choices[0].delta.content:
            full_content += chunk.choices[0].delta.content
            print(chunk.model_dump())
    
    print(full_content)

except BadRequestError as e:
    print(f"Error message: {e}")
    print("For more information, see https://www.alibabacloud.com/help/en/model-studio/developer-reference/error-codes")

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.core.http.StreamResponse;
import com.openai.models.chat.completions.*;

public class Main {
    public static void main(String[] args) {
        // Create a client and use the API key from the environment variable
        OpenAIClient client = OpenAIOkHttpClient.builder()
                // If you have not configured the environment variable, replace the next line with your Alibaba Cloud Model Studio API key: .apiKey("sk-xxx");
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();

        ChatCompletionCreateParams chatParams = ChatCompletionCreateParams.builder()
                .addSystemMessage("You are a helpful assistant.")
                .addSystemMessage("Feedback ID: 001 User: Zhang Wei (vip_zhang@example.com) Product: Model Studio AI-Writer Pro...")
                .addUserMessage("From this customer feedback report, extract all feedback information and organize it into a standard JSON array. Each object must include the following: feedback_id (string), product_name (string), user_name (string), rating_score (an integer from 1 to 5), feedback_type (string), and summary (a Chinese summary of no more than 30 characters).")
                .model("qwen-doc-turbo")
                .build();

        try (StreamResponse<ChatCompletionChunk> streamResponse = client.chat().completions().createStreaming(chatParams)) {
            streamResponse.stream().forEach(chunk -> {
                String content = chunk.choices().get(0).delta().content().orElse("");
                if (!content.isEmpty()) {
                    System.out.print(content);
                }
            });
        } catch (Exception e) {
            System.err.println("Error message: " + e.getMessage());
        }
    }
}

curl --location 'https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header "Content-Type: application/json" \
--data '{
    "model": "qwen-doc-turbo",
    "messages": [
        {"role": "system","content": "You are a helpful assistant."},
        {"role": "system","content": "Feedback ID: 001 User: Zhang Wei (vip_zhang@example.com) Product: Model Studio AI-Writer Pro..."},
        {"role": "user","content": "From this customer feedback report, extract all feedback information and organize it into a standard JSON array. Each object must include the following: feedback_id (string), product_name (string), user_name (string), rating_score (an integer from 1 to 5), feedback_type (string), and summary (a Chinese summary of no more than 30 characters)."}
    ],
    "stream": true,
    "stream_options": {
        "include_usage": true
    }
}'