Alibaba Cloud Model Studio：長上下文（Qwen-Long）

Python

import os
from pathlib import Path
from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"),  # 如果您沒有配置環境變數，請在此處替換您的API-KEY
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",  # 填寫DashScope服務base_url
)

file_object = client.files.create(file=Path("阿里雲百鍊系列手機產品介紹.docx"), purpose="file-extract")
print(file_object.id)

Java

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

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

public class Main {
    public static void main(String[] args) {
        // 建立用戶端，使用環境變數中的API密鑰
        OpenAIClient client = OpenAIOkHttpClient.builder()
                // 若沒有配置環境變數，請用百鍊API Key將下行替換為：.apiKey("sk-xxx")
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();
        // 設定檔案路徑,請根據實際需求修改路徑與檔案名稱
        Path filePath = Paths.get("src/main/java/org/example/阿里雲百鍊系列手機產品介紹.docx");
        // 建立檔案上傳參數
        FileCreateParams fileParams = FileCreateParams.builder()
                .file(filePath)
                .purpose(FilePurpose.of("file-extract"))
                .build();

        // 上傳檔案列印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=@"阿里雲百鍊系列手機產品介紹.docx"' \
  --form 'purpose="file-extract"'

Python

import os
from openai import OpenAI, BadRequestError

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"),  # 如果您沒有配置環境變數，請在此處替換您的API-KEY
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",  # 填寫DashScope服務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.'},
            # 請將 '{FILE_ID}'替換為您實際對話情境所使用的 fileid。
            {'role': 'system', 'content': f'fileid://{FILE_ID}'},
            {'role': 'user', 'content': '這篇文章講了什麼?'}
        ],
        # 所有程式碼範例均採用流式輸出，以清晰和直觀地展示模型輸出過程。如果您希望查看非流式輸出的案例，請參見https://www.alibabacloud.com/help/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:
            # 拼接輸出內容
            full_content += chunk.choices[0].delta.content
            print(chunk.model_dump())
        
        # 擷取 token 使用方式
        if chunk.usage:
            print(f"總計 tokens: {chunk.usage.total_tokens}")

    print(full_content)

except BadRequestError as e:
    print(f"錯誤資訊：{e}")
    print("請參考文檔：https://www.alibabacloud.com/help/zh/model-studio/error-code")

Java

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) {
        // 建立用戶端，使用環境變數中的API密鑰
        OpenAIClient client = OpenAIOkHttpClient.builder()
                // 若沒有配置環境變數，請用百鍊API Key將下行替換為：.apiKey("sk-xxx")
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();

        // 建立聊天請求
        ChatCompletionCreateParams chatParams = ChatCompletionCreateParams.builder()
                .addSystemMessage("You are a helpful assistant.")
                //請將 '{FILE_ID}'替換為您實際對話情境所使用的 fileid。
                .addSystemMessage("fileid://{FILE_ID}")
                .addUserMessage("這篇文章講了什嗎？")
                .model("qwen-long")
                .build();

        StringBuilder fullResponse = new StringBuilder();

        // 所有程式碼範例均採用流式輸出，以清晰和直觀地展示模型輸出過程。如果您希望查看非流式輸出的案例，請參見https://www.alibabacloud.com/help/zh/model-studio/text-generation
        try (StreamResponse<ChatCompletionChunk> streamResponse = client.chat().completions().createStreaming(chatParams)) {
            streamResponse.stream().forEach(chunk -> {
                // 列印每個 chunk 的內容並拼接
                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("錯誤資訊：" + e.getMessage());
            System.err.println("請參考文檔：https://www.alibabacloud.com/help/zh/model-studio/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": "這篇文章講了什嗎？"}
    ],
    "stream": true,
    "stream_options": {
        "include_usage": true
    }
}'

傳入多文檔

import os
from openai import OpenAI, BadRequestError

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"),  # 如果您沒有配置環境變數，請在此處替換您的API-KEY
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",  # 填寫DashScope服務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.'},
            # 請將 '{FILE_ID1}' 和 '{FILE_ID2}' 替換為您實際對話情境所使用的 fileid。
            {'role': 'system', 'content': f"fileid://{FILE_ID1},fileid://{FILE_ID2}"},
            {'role': 'user', 'content': '這幾篇文章講了什嗎？'}
        ],
        # 所有程式碼範例均採用流式輸出，以清晰和直觀地展示模型輸出過程。如果您希望查看非流式輸出的案例，請參見https://www.alibabacloud.com/help/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:
            # 拼接輸出內容
            full_content += chunk.choices[0].delta.content
            print(chunk.model_dump())
    
    print(full_content)

except BadRequestError as e:
    print(f"錯誤資訊：{e}")
    print("請參考文檔：https://www.alibabacloud.com/help/zh/model-studio/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) {
        // 建立用戶端，使用環境變數中的API密鑰
        OpenAIClient client = OpenAIOkHttpClient.builder()
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .baseUrl("https://dashscope.aliyuncs.com/compatible-mode/v1")
                .build();

        // 建立聊天請求
        ChatCompletionCreateParams chatParams = ChatCompletionCreateParams.builder()
                .addSystemMessage("You are a helpful assistant.")
                //請將 '{FILE_ID1}' 和 '{FILE_ID2}' 替換為您實際對話情境所使用的 fileid。
                .addSystemMessage("fileid://{FILE_ID1},fileid://{FILE_ID2}")
                .addUserMessage("這兩篇文章講了什嗎？")
                .model("qwen-long")
                .build();

        StringBuilder fullResponse = new StringBuilder();

        // 所有程式碼範例均採用流式輸出，以清晰和直觀地展示模型輸出過程。如果您希望查看非流式輸出的案例，請參見https://www.alibabacloud.com/help/zh/model-studio/text-generation
        try (StreamResponse<ChatCompletionChunk> streamResponse = client.chat().completions().createStreaming(chatParams)) {
            streamResponse.stream().forEach(chunk -> {
                // 每個 chunk 的內容
                System.out.println(chunk);
                String content = chunk.choices().get(0).delta().content().orElse("");
                if (!content.isEmpty()) {
                    fullResponse.append(content);
                }
            });
            System.out.println("\n完整回複內容：");
            System.out.println(fullResponse);
        } catch (Exception e) {
            System.err.println("錯誤資訊：" + e.getMessage());
            System.err.println("請參考文檔：https://www.alibabacloud.com/help/zh/model-studio/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": "這兩篇文章講了什嗎？"}
    ],
    "stream": true,
    "stream_options": {
        "include_usage": true
    }
}'

追加文檔

import os
from openai import OpenAI, BadRequestError

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"),  # 如果您沒有配置環境變數，請在此處替換您的API-KEY
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",  # 填寫DashScope服務base_url
)
# 初始化messages列表
messages = [
    {'role': 'system', 'content': 'You are a helpful assistant.'},
    # 請將 '{FILE_ID1}' 替換為您實際對話情境所使用的 fileid。
    {'role': 'system', 'content': f'fileid://{FILE_ID1}'},
    {'role': 'user', 'content': '這篇文章講了什嗎？'}
]

try:
    # 第一輪響應
    completion_1 = client.chat.completions.create(
        model="qwen-long",
        messages=messages,
        stream=False
    )
    # 列印出第一輪響應
    # 如果需要流式輸出第一輪的響應，需要將stream設定為True，並拼接每一段輸出內容，在構造assistant_message的content時傳入拼接後的字元
    print(f"第一輪響應：{completion_1.choices[0].message.model_dump()}")
except BadRequestError as e:
    print(f"錯誤資訊：{e}")
    print("請參考文檔：https://www.alibabacloud.com/help/zh/model-studio/error-code")

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

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

# 將追加文檔的fileid添加到messages中
# 請將 '{FILE_ID2}' 替換為您實際對話情境所使用的 fileid。
system_message = {'role': 'system', 'content': f'fileid://{FILE_ID2}'}
messages.append(system_message)

# 添加使用者問題
messages.append({'role': 'user', 'content': '這兩篇文章討論的方法有什麼異同點？'})

# 追加文檔後的響應
completion_2 = client.chat.completions.create(
    model="qwen-long",
    messages=messages,
    # 所有程式碼範例均採用流式輸出，以清晰和直觀地展示模型輸出過程。如果您希望查看非流式輸出的案例，請參見https://www.alibabacloud.com/help/zh/model-studio/text-generation
    stream=True,
    stream_options={
        "include_usage": True
    }
)

# 流式列印出追加文檔後的響應
print("追加文檔後的響應：")
for chunk in completion_2:
    print(chunk.model_dump())

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.chat.completions.*;
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<>();
        
        // 添加用於角色設定的資訊
        ChatCompletionSystemMessageParam roleSet = ChatCompletionSystemMessageParam.builder()
                .content("You are a helpful assistant.")
                .build();
        messages.add(ChatCompletionMessageParam.ofSystem(roleSet));
        
        // 請將 '{FILE_ID1}' 替換為您實際對話情境所使用的 fileid。
        ChatCompletionSystemMessageParam systemMsg1 = ChatCompletionSystemMessageParam.builder()
                .content("fileid://{FILE_ID1}")
                .build();
        messages.add(ChatCompletionMessageParam.ofSystem(systemMsg1));

        // 使用者提問訊息（USER角色）
        ChatCompletionUserMessageParam userMsg1 = ChatCompletionUserMessageParam.builder()
                .content("請總結文章內容")
                .build();
        messages.add(ChatCompletionMessageParam.ofUser(userMsg1));

        // 構造第一輪請求並處理異常
        ChatCompletion completion1;
        try {
            completion1 = client.chat().completions().create(
                    ChatCompletionCreateParams.builder()
                            .model("qwen-long")
                            .messages(messages)
                            .build()
            );
        } catch (Exception e) {
            System.err.println("請求出錯，請查看錯誤碼對照網頁：");
            System.err.println("https://www.alibabacloud.com/help/zh/model-studio/error-code");
            System.err.println("錯誤詳情：" + e.getMessage());
            e.printStackTrace(); 
            return; 
        }

        // 第一輪響應
        String firstResponse = completion1 != null ? completion1.choices().get(0).message().content().orElse("") : "";
        System.out.println("第一輪響應：" + firstResponse);

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

        // 請將 '{FILE_ID2}' 替換為您實際對話情境所使用的 fileid。
        ChatCompletionSystemMessageParam systemMsg2 = ChatCompletionSystemMessageParam.builder()
                .content("fileid://{FILE_ID2}")
                .build();
        messages.add(ChatCompletionMessageParam.ofSystem(systemMsg2));

        // 第二輪使用者提問（USER角色）
        ChatCompletionUserMessageParam userMsg2 = ChatCompletionUserMessageParam.builder()
                .content("請對比兩篇文章的結構差異")
                .build();
        messages.add(ChatCompletionMessageParam.ofUser(userMsg2));

        // 所有程式碼範例均採用流式輸出，以清晰和直觀地展示模型輸出過程。如果您希望查看非流式輸出的案例，請參見https://www.alibabacloud.com/help/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最終響應：");
            System.out.println(fullResponse.toString().trim());
        } catch (Exception e) {
            System.err.println("錯誤資訊：" + e.getMessage());
            System.err.println("請參考文檔：https://www.alibabacloud.com/help/zh/model-studio/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": "這篇文章講了什嗎？"},
        {"role": "system","content": "fileid://file-fe-xxx2"},
        {"role": "user","content": "這兩篇文章討論的方法有什麼異同點？"}
    ],
    "stream": true,
    "stream_options": {
        "include_usage": true
    }
}'