长上下文（Qwen-Long）

Python

import os
from pathlib import Path
from openai import OpenAI

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",  # 填写DashScope服务base_url
)

file_object = client.files.create(file=Path("阿里云百炼系列手机产品介绍.docx"), purpose="file-extract")
print(file_object.id)

Java

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.*;

import java.nio.file.Path;
import java.nio.file.Paths;

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()
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();
        // 设置文件路径,请根据实际需求修改路径与文件名
        Path filePath = Paths.get("src/main/java/org/example/阿里云百炼系列手机产品介绍.docx");
        // 创建文件上传参数
        FileCreateParams fileParams = FileCreateParams.builder()
                .file(filePath)
                .purpose(FilePurpose.of("file-extract"))
                .build();

        // 上传文件打印fileid
        FileObject fileObject = client.files().create(fileParams);
        System.out.println(fileObject.id());
    }
}

curl

curl --location --request POST 'https://dashscope.aliyuncs.com/compatible-mode/v1/files' \
  --header "Authorization: Bearer $DASHSCOPE_API_KEY" \
  --form 'file=@"阿里云百炼系列手机产品介绍.docx"' \
  --form 'purpose="file-extract"'

Python

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",  # 填写DashScope服务base_url
)
try:
    # 初始化messages列表
    completion = client.chat.completions.create(
        model="qwen-long",
        messages=[
            {'role': 'system', 'content': 'You are a helpful assistant.'},
            # 请将 '{FILE_ID}'替换为您实际对话场景所使用的 fileid。
            {'role': 'system', 'content': f'fileid://{FILE_ID}'},
            {'role': 'user', 'content': '这篇文章讲了什么?'}
        ],
        # 所有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:
            # 拼接输出内容
            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")

Java

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

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()
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();

        // 创建聊天请求
        ChatCompletionCreateParams chatParams = ChatCompletionCreateParams.builder()
                .addSystemMessage("You are a helpful assistant.")
                //请将 '{FILE_ID}'替换为您实际对话场景所使用的 fileid。
                .addSystemMessage("fileid://{FILE_ID}")
                .addUserMessage("这篇文章讲了什么？")
                .model("qwen-long")
                .build();

        StringBuilder fullResponse = new StringBuilder();

        // 所有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
        try (StreamResponse<ChatCompletionChunk> streamResponse = client.chat().completions().createStreaming(chatParams)) {
            streamResponse.stream().forEach(chunk -> {
                // 打印每个 chunk 的内容并拼接
                System.out.println(chunk);
                String content = chunk.choices().get(0).delta().content().orElse("");
                if (!content.isEmpty()) {
                    fullResponse.append(content);
                }
            });
            System.out.println(fullResponse);
        } catch (Exception e) {
            System.err.println("错误信息：" + e.getMessage());
            System.err.println("请参考文档：https://help.aliyun.com/zh/model-studio/developer-reference/error-code");
        }
    }
}

curl

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-long",
    "messages": [
        {"role": "system","content": "You are a helpful assistant."},
        {"role": "system","content": "fileid://file-fe-xxx"},
        {"role": "user","content": "这篇文章讲了什么？"}
    ],
    "stream": true,
    "stream_options": {
        "include_usage": true
    }
}'

传入多文档

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",  # 填写DashScope服务base_url
)
try:
    # 初始化messages列表
    completion = client.chat.completions.create(
        model="qwen-long",
        messages=[
            {'role': 'system', 'content': 'You are a helpful assistant.'},
            # 请将 '{FILE_ID1}' 和 '{FILE_ID2}' 替换为您实际对话场景所使用的 fileid。
            {'role': 'system', 'content': f"fileid://{FILE_ID1},fileid://{FILE_ID2}"},
            {'role': 'user', 'content': '这几篇文章讲了什么？'}
        ],
        # 所有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:
            # 拼接输出内容
            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.*;

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()
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();

        // 创建聊天请求
        ChatCompletionCreateParams chatParams = ChatCompletionCreateParams.builder()
                .addSystemMessage("You are a helpful assistant.")
                //请将 '{FILE_ID1}' 和 '{FILE_ID2}' 替换为您实际对话场景所使用的 fileid。
                .addSystemMessage("fileid://{FILE_ID1},fileid://{FILE_ID2}")
                .addUserMessage("这两篇文章讲了什么？")
                .model("qwen-long")
                .build();

        StringBuilder fullResponse = new StringBuilder();

        // 所有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
        try (StreamResponse<ChatCompletionChunk> streamResponse = client.chat().completions().createStreaming(chatParams)) {
            streamResponse.stream().forEach(chunk -> {
                // 每个 chunk 的内容
                System.out.println(chunk);
                String content = chunk.choices().get(0).delta().content().orElse("");
                if (!content.isEmpty()) {
                    fullResponse.append(content);
                }
            });
            System.out.println("\n完整回复内容：");
            System.out.println(fullResponse);
        } catch (Exception e) {
            System.err.println("错误信息：" + e.getMessage());
            System.err.println("请参考文档：https://help.aliyun.com/zh/model-studio/developer-reference/error-code");
        }
    }
}

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-long",
    "messages": [
        {"role": "system","content": "You are a helpful assistant."},
        {"role": "system","content": "fileid://file-fe-xxx1"},
        {"role": "system","content": "fileid://file-fe-xxx2"},
        {"role": "user","content": "这两篇文章讲了什么？"}
    ],
    "stream": true,
    "stream_options": {
        "include_usage": true
    }
}'

追加文档

import os
from openai import OpenAI

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",  # 填写DashScope服务base_url
)
# 初始化messages列表
messages = [
    {'role': 'system', 'content': 'You are a helpful assistant.'},
    # 请将 '{FILE_ID1}' 替换为您实际对话场景所使用的 fileid。
    {'role': 'system', 'content': f'fileid://{FILE_ID1}'},
    {'role': 'user', 'content': '这篇文章讲了什么？'}
]

try:
    # 第一轮响应
    completion_1 = client.chat.completions.create(
        model="qwen-long",
        messages=messages,
        stream=False
    )
    # 打印出第一轮响应
    # 如果需要流式输出第一轮的响应，需要将stream设置为True，并拼接每一段输出内容，在构造assistant_message的content时传入拼接后的字符
    print(f"第一轮响应：{completion_1.choices[0].message.model_dump()}")
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")

# 构造assistant_message
assistant_message = {
    "role": "assistant",
    "content": completion_1.choices[0].message.content}

# 将assistant_message添加到messages中
messages.append(assistant_message)

# 将追加文档的fileid添加到messages中
# 请将 '{FILE_ID2}' 替换为您实际对话场景所使用的 fileid。
system_message = {'role': 'system', 'content': f'fileid://{FILE_ID2}'}
messages.append(system_message)

# 添加用户问题
messages.append({'role': 'user', 'content': '这两篇文章讨论的方法有什么异同点？'})

# 追加文档后的响应
completion_2 = client.chat.completions.create(
    model="qwen-long",
    messages=messages,
    # 所有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
    }
)

# 流式打印出追加文档后的响应
print("追加文档后的响应：")
for chunk in completion_2:
    print(chunk.model_dump())

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

import java.util.ArrayList;
import java.util.List;

public class Main {
    public static void main(String[] args) {
        OpenAIClient client = OpenAIOkHttpClient.builder()
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();
        // 初始化messages列表
        List<ChatCompletionMessageParam> messages = new ArrayList<>();
        
        // 添加用于角色设定的信息
        ChatCompletionSystemMessageParam roleSet = ChatCompletionSystemMessageParam.builder()
                .content("You are a helpful assistant.")
                .build();
        messages.add(ChatCompletionMessageParam.ofSystem(roleSet));
        
        // 请将 '{FILE_ID1}' 替换为您实际对话场景所使用的 fileid。
        ChatCompletionSystemMessageParam systemMsg1 = ChatCompletionSystemMessageParam.builder()
                .content("fileid://{FILE_ID1}")
                .build();
        messages.add(ChatCompletionMessageParam.ofSystem(systemMsg1));

        // 用户提问消息（USER角色）
        ChatCompletionUserMessageParam userMsg1 = ChatCompletionUserMessageParam.builder()
                .content("请总结文章内容")
                .build();
        messages.add(ChatCompletionMessageParam.ofUser(userMsg1));

        // 构造第一轮请求并处理异常
        ChatCompletion completion1;
        try {
            completion1 = client.chat().completions().create(
                    ChatCompletionCreateParams.builder()
                            .model("qwen-long")
                            .messages(messages)
                            .build()
            );
        } catch (Exception e) {
            System.err.println("请求出错，请查看错误码对照网页：");
            System.err.println("https://help.aliyun.com/zh/model-studio/developer-reference/error-code");
            System.err.println("错误详情：" + e.getMessage());
            e.printStackTrace(); 
            return; 
        }

        // 第一轮响应
        String firstResponse = completion1 != null ? completion1.choices().get(0).message().content().orElse("") : "";
        System.out.println("第一轮响应：" + firstResponse);

        // 构造AssistantMessage
        ChatCompletionAssistantMessageParam assistantMsg = ChatCompletionAssistantMessageParam.builder()
                .content(firstResponse)
                .build();
        messages.add(ChatCompletionMessageParam.ofAssistant(assistantMsg));

        // 请将 '{FILE_ID2}' 替换为您实际对话场景所使用的 fileid。
        ChatCompletionSystemMessageParam systemMsg2 = ChatCompletionSystemMessageParam.builder()
                .content("fileid://{FILE_ID2}")
                .build();
        messages.add(ChatCompletionMessageParam.ofSystem(systemMsg2));

        // 第二轮用户提问（USER角色）
        ChatCompletionUserMessageParam userMsg2 = ChatCompletionUserMessageParam.builder()
                .content("请对比两篇文章的结构差异")
                .build();
        messages.add(ChatCompletionMessageParam.ofUser(userMsg2));

        // 所有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
        StringBuilder fullResponse = new StringBuilder();
        try (StreamResponse<ChatCompletionChunk> streamResponse = client.chat().completions().createStreaming(
                ChatCompletionCreateParams.builder()
                        .model("qwen-long")
                        .messages(messages)
                        .build())) {

            streamResponse.stream().forEach(chunk -> {
                String content = chunk.choices().get(0).delta().content().orElse("");
                if (!content.isEmpty()) {
                    fullResponse.append(content);
                }
            });
            System.out.println("\n最终响应：");
            System.out.println(fullResponse.toString().trim());
        } catch (Exception e) {
            System.err.println("错误信息：" + e.getMessage());
            System.err.println("请参考文档：https://help.aliyun.com/zh/model-studio/developer-reference/error-code");
        }
    }
}

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-long",
    "messages": [
        {"role": "system","content": "You are a helpful assistant."},
        {"role": "system","content": "fileid://file-fe-xxx1"},
        {"role": "user","content": "这篇文章讲了什么？"},
        {"role": "system","content": "fileid://file-fe-xxx2"},
        {"role": "user","content": "这两篇文章讨论的方法有什么异同点？"}
    ],
    "stream": true,
    "stream_options": {
        "include_usage": true
    }
}'