数据挖掘（Qwen-Doc-Turbo）

import os
import dashscope

response = dashscope.Generation.call(
    api_key=os.getenv('DASHSCOPE_API_KEY'), # 如果您没有配置环境变量，请在此处替换您的API-KEY
    model='qwen-doc-turbo',
    messages=[
    {"role": "system","content": "You are a helpful assistant."},
    {
        "role": "user",
        "content": [
            {
                "type": "text",
                "text": "从这份客户反馈报告中，提取所有反馈信息，并整理成一个标准的JSON数组。每个对象需要包含：feedback_id (字符串)、product_name (字符串)、user_name (字符串)、rating_score (1-5的整数)、feedback_type (字符串) 和 summary (不超过30字的中文摘要)。"
            },
            {
                "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"请求失败，状态码: {response.status_code}")
        print(f"错误代码: {response.code}")
        print(f"错误信息: {response.message}")
        print("请参考文档：https://help.aliyun.com/zh/model-studio/developer-reference/error-code")
except Exception as e:
    print(f"发生错误: {e}")
    print("请参考文档：https://help.aliyun.com/zh/model-studio/developer-reference/error-code")

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": "从这份客户反馈报告中，提取所有反馈信息，并整理成一个标准的JSON数组。每个对象需要包含：feedback_id (字符串)、product_name (字符串)、user_name (字符串)、rating_score (1-5的整数)、feedback_type (字符串) 和 summary (不超过30字的中文摘要)。"
                        },
                        {
                            "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"), # 如果您没有配置环境变量，请在此处替换您的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': '反馈ID: 001 用户: 张伟 (vip_zhang@example.com) 产品: 百炼 AI-Writer Pro...'},
            {'role': 'user', 'content': '从这份客户反馈报告中，提取所有反馈信息，并整理成一个标准的JSON数组。每个对象需要包含：feedback_id (字符串)、product_name (字符串)、user_name (字符串)、rating_score (1-5的整数)、feedback_type (字符串) 和 summary (不超过30字的中文摘要)。'}
        ],
        # 本代码示例均采用流式输出，以清晰和直观地展示模型输出过程。如果您希望查看非流式输出的案例，请参见https://help.aliyun.com/zh/model-studio/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"错误信息：{e}")
    print("请参考文档：https://help.aliyun.com/zh/model-studio/developer-reference/error-code")

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) {
        // 创建客户端，使用环境变量中的API密钥
        OpenAIClient client = OpenAIOkHttpClient.builder()
                // 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：.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("反馈ID: 001 用户: 张伟 (vip_zhang@example.com) 产品: 百炼 AI-Writer Pro......")
                .addUserMessage("从这份客户反馈报告中，提取所有反馈信息，并整理成一个标准的JSON数组。每个对象需要包含：feedback_id (字符串)、product_name (字符串)、user_name (字符串)、rating_score (1-5的整数)、feedback_type (字符串) 和 summary (不超过30字的中文摘要)。")
                .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("错误信息：" + 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": "反馈ID: 001 用户: 张伟 (vip_zhang@example.com) 产品: 百炼 AI-Writer Pro..."},
        {"role": "user","content": "从这份客户反馈报告中，提取所有反馈信息，并整理成一个标准的JSON数组。每个对象需要包含：feedback_id (字符串)、product_name (字符串)、user_name (字符串)、rating_score (1-5的整数)、feedback_type (字符串) 和 summary (不超过30字的中文摘要)。"}
    ],
    "stream": true,
    "stream_options": {
        "include_usage": true
    }
}'